The questions on the creation of mankind and the inner workings of the universe have been the primary issues that have had a profound impact on both modern, secular philosophy and traditional religion. Our collective experiences in natural sciences and educational disciplines have taught us that certain models can be developed to help us comprehend the functioning of the universe.

One of the fundamental questions in this respect relates to how a great deal of orderliness and discipline is possible in the universe despite its immense scale. Exploring the potential of this orderliness encourages our curiosity to examine life at the most minuscule level, and some scientists aim to explain this perceived system within the universe via an idea called “the Computational Universe.” In this article we will discuss how this idea can be considered to support the perceptions of monotheistic belief. In scientific literature, the term “computational” refers to anything that possesses any relationship to complex calculations, as various disciplines such as physics, chemistry; the term is used even by the discipline of psychology.

Thanks to relatively recent developments and discoveries in science, we are able to better understand the events in our world and universe. To put it into perspective, humanity was deprived of certainty on the shape of the world up until several centuries ago. However, scientific developments, especially during the 19th and 20th centuries, formed the basis of the stunning technological developments that we live with today. Comparatively, it could be argued that what we know, comprehend, and understand about the universe that we live in is only a small fraction of what the universe actually contains. Continuous developments in science and technology help us understand more and more about the way the universe works. “Our science and applications to space technology have evolved by improving our abilities to measure, test, and analyze physical events and by developing their mathematical models” (Fontana 2005).

As humanity began to uncover some of the codes by which our universe is made to function, we have been using these rules to make our lives easier. This is common human behavior: we learn new things and try to use them to improve our lives. In fact, human technology has advanced so much that we now have machines that can move and function like a nano-universe. Basically, we are giving them a code, a sheet of rules to function in the way we desire. As a result, we are much less dependent on physical labor; for instance, we now can farm with high-tech machines instead of our hands.

New ideas are born with these emerging technologies and with more ease than they were back in the old days; thus we have had a progress at an exponential rate. Looking at all these historical aspects and experience , some scientists conclude that the universe we take part in might be a “mother computation” and all of these things that keep the universe well-oiled and functioning might be parts of codes and commands coming from this mother computation.

The argument does not end at whether we live in a computation or not though. From that point, people who believe that we live in a mother computation split sides, with some providing the explanation that we are real, and this is reality, but controlled by a mother computation. This group argues that everything that happens around us is part of reality, just like we are, but that they function via a code that was inserted into their cores in order for them to work the way their coder wants them to.

The other school of thought challenges the vast majority of conventional theological thought and logic. This argument agrees that we do live in a computation, however that this life is not reality. Events in the universe, including our lives are just a simulation, and we are test subjects.

“Several physicists, cosmologists and technologists are now happy to entertain the idea that we are all living inside a gigantic computer simulation… Our instincts rebel, of course. It all feels too real to be a simulation. The weight of the cup in my hand, the rich aroma of the coffee it contains, the sounds all around me – how can such richness of experience be faked?” (Ball 2016).

Though this idea of a computational universe appears to be new because of the fact that computers and digital simulations appeared only a few decades ago, its origins go back to antiquity. Some of history’s greatest minds, such as Plato and Descartes, have actually provided their views on this concept even without these technologies being present at the time. They questioned reality and dug deep into life and how we perceive everything around us, however their arguments were not widespread among their contemporaries because they had no proofs to support their controversial ideas that challenged everything that people believed.

So, is the universe a mother computer or a giant computer simulation?

It is widely accepted by almost all people that there are principles and rules by which the universe is governed and which we can observe on both the macro and micro levels. Events are considered supernatural or miraculous if they take place outside of these principles. Therefore, scientific findings may allow us to develop a deeper appreciation for the “computational” orderliness that can be found in our universe among the orbits of the planets down to the multitude of complex ecosystems that exist across our world in a variety of different biomes.

Religious traditions

From the perspective of monotheistic religions, it is believed that the Creator creates and pursues everything with an order in the universe, which allows the universe to keep working in a perfect balance. The universe’s orderliness, especially that which occurred during its creation, is stressed profoundly in the holy books. For example, it is stated in Genesis 1-2 that the creation of the entire universe occurred in “six days,” and this process was described day by day in the relevant verses. This implies a certain order in the development of events during the creation of the universe.

A certain orderliness is also clearly declared in the Qur’an: “He to whom belongs the dominion of the heavens and the earth … has created each thing and determined it with [precise] determination” (2:25). Today, the scientific community explains this order and design in the universe with concepts such as the “Anthropic Principle.” According to this principle, the universe possesses such perfect features that it could not have arisen by chance without purpose. The situation can be understood more thoroughly if major examples of design existing in the universe are briefly examined. Doing so, we will find out several aspects of this principle that we encounter in our daily lives, which in turn will lead us to further understand God’s complex creation of the universe.

Based upon the evidence that some scientists have shown that a starter leads off, like a coder writes codes, in order for the universe to function correctly and in a perfect continuity, the faithful of religious traditions might reasonably suggest that this entire universe is just like a computer created by the Creator who continuously controls it by constantly creating new every moment for it to function as the codes are based on His commands. This rationale is the essence of and consistent with not only monotheistic religions but also in many ways with other belief systems.

Overall, the concept of a “mother computation” placed on duty in the functioning of our universe is not just a singular subject but instead a comprehensive set of ideas people have focused deeper. While, according to some, there is indication for the universe being a reality and being controlled by a “computer,” according to others, there might also be indication for how the universe could also just be a simulation. A team of physicists working at the University of Bonn claim that they have come up with a measurable way of showing that our universe is indeed “simulated” (Yirka 2012). The main focus of their paper is that in order to create a simulation of our universe, there has to be a three-dimensional framework to represent real world objects and processes. But the problem is, this paper is based on only what we know of reality today. This means that an exact copy of our universe would be impossible to create until the end of time, when we have all the knowledge that the universe presents us with – the entire idea splits right at this point.

Religion also becomes a separate argument along with these two different beliefs. Monotheistic religions believe in an Almighty God, who creates ex nihilo and put things in order in a perfectly “computed” order. God, in these traditions, are also believed to sustain all the existence by constant governance; as a matter of fact, everything is an outcome of the manifestation of God’s names and attributes – nothing comes out outside of His Divine realm and authority.

With there being many more religious traditions and philosophical approaches in this world, many different ideas can emerge as possible theories. In regard to the idea of the world being a computation, scientific theoreticians cannot definitively know for sure whether we live in a computational or fundamental reality, and do not speculate on who might be the one who programs this computer that way. Religious traditions, however, take one more step and claim if there is a computation, then there must be an agent who makes it possible and wills the world to be as it is rather than something else. Otherwise, claiming the universe to be a mother computer on its own would be no different than believing in nature to be the creator of everything, as opposed to nature itself being a created being.

While the computational model seems to support the arguments of believers in terms of explaining that there is an established order in the universe and that this order operates within certain laws and rules created and maintained by a creator in a perfect continuity, thinkers and philosophers may come up with different explanations in their own words and formulations to understand creation and life as we know it.

The mysteries of the universe offer us an expansive space to bring about the best of our rational and spiritual capacities, so our existence in this life becomes a meaningful one.

References

• Giorgio Fontana. “Why we live in the Computational Universe,” https://arxiv.org/ftp/physics/papers/0511/0511157.pdf.
• Philip Ball. 5 September “We might live in a computer program, but it may not matter” http://www.bbc.com/earth/story/20160901-we-might-live-in-a-computer-program-but-it-may-not-matter.
• Bob Yirka. 2012. “Is it real? Physicists propose method to determine if the universe is a simulation,” Phys.org.

Is it why we cannot attain maximum mental performance?

If you are one of those people who are unsatisfied with their foreign language competence after many years of hard work, practice, and exposure, then this article may be for you. Even though research in foreign language learning enumerates several factors for foreign language failure – social, psychological, cognitive and affective – whose roles cannot be overlooked, my own view is somewhat different: I firmly believe that one of the main reasons why so many people cannot attain maximum performance, not only in foreign languages but also in other subjects, is largely because of “mental pollution.” This is why, I think, children are superior to adults at learning foreign languages, for they are devoid of severe mental pollution.

Let me first clarify what I mean by “mental pollution.” Certain images of different sizes, qualities, and shapes displayed on billboards, shop windows, posters, brochures, magazines, ads, TV, movies, videos, websites – these are mental pollution. Depending on their form and characteristic, they may greatly abuse a person’s mental energy and lead to chaotic and disturbing emotions. The more irrelevant, enticing, or lustful images are, the more detrimental they are to our social and academic life. For example, a small logo of a computer game – perhaps the size of a 5 cent coin – such as the dragon from Mortal Kombat, contains at minimum three kilobytes (3072 characters), which is equal to about 400 English words. Despite the premise that we only use 8-10 percent of our mental capacity, the amount of visual data the human brain is permanently exposed to cannot be underestimated when so many people, especially children, watch TV, play computer games, and surf the internet. Obscene pictures, in particular, are a common form of mental pollution nowadays, and they are some of the most deleterious to the human mind; they drastically increase blood pressure and heart rate and thus weaken the memory. As an example, a study by Brad J. Bushman has apparently revealed that watching violent television programs has adverse effects on one’s ability to remember.

Fethullah Gülen, a renowned modern Islamic intellectual, reminds us of the seriousness of the topic, while more people than ever before complain about forgetfulness and memory weakness. According to Gülen, the process of learning now takes longer than in the past, and forgetfulness, like an infection, has become prevalent among all levels of society due to polluted minds teeming with irrelevant information. He also points out that long ago people complained when they were not able to memorize and recite by heart a page after only one reading. In this day and age, people complain about weak memory and confess that they have great difficulty memorizing a short text that they have read more than 20 times. For a keen memory, his message to the present generation is to stay away from useless routines, frivolous conversations, irrelevant knowledge, and sources of obscenity.

Similar to a computer, the untrained human mind whose protection filter is set to a low level is under constant visual attack. Given this, mental pollution acts like a computer virus, a code that replicates by copying itself to another program, document, or e-mail, thereby seriously slowing down memory operations. Also, it can erase data or damage the computer’s hard disk, which is analogous to long-term memory in the human brain. Interestingly enough, lab experiments on rats have revealed that these animals simply choose to starve to death when they are tempted by brain reward-stimulus circuits in quests for neuro-orgasms. These rats rarely attain balanced brain chemistry, while the orgasm they experience results in a hangover that lasts for weeks. The same condition is also true for the human mind: the unnecessary over-discharge of hormones triggered by electrifying visual stimuli can lead to long-lasting forgetfulness, fatigue, and serious concentration problems. In such a case, a person cannot make sense of whatever he is studying until the side effects of mental pollution are over.

Foreign language learning also substantially suffers from the harmful effects of copious amounts of mental pollution. The modern methodology and technology to facilitate foreign language learning can be hampered by overwhelming exposure to mental pollution. Although they did not have the contemporary language learning resources and facilities, many early scholars and polyglots managed to learn numerous foreign languages. For instance, Guiseppe Caspar Mezzofanti, an Italian cardinal and famed linguist, is believed to have spoken 38 languages and 50 dialects fluently. Similarly, Sir John Bowring (100), Emil Krebs (68), Ziad Youssef Fazah (56), Ali Ufki (16), Muhammad Hamidullah (22), Pamulaparthi Venkata Narasimha Rao (13), Jose Rizal (22), and Sir Richard Francis Burton (29) were able to speak and read in many languages and dialects, as shown in parentheses, and their success is considerably astonishing when we compare them to present academics who have problems at mastering only one foreign language despite the available modern resources. I believe that these past scholars and polyglots, besides their talent and enthusiasm, did not suffer from widespread mental pollution as we do today. For example, the polyglot Mezzofanti was a prodigy in languages mostly because he spent his life in a monastery and therefore was not subject to any form of mental pollution that could preoccupy his mind and weaken his memory.

I am greatly convinced that an oft-overlooked but very serious barrier – mental pollution – which is very common among people, is a crucial reason for many people’s failure to learn a foreign language, among other subjects. In any discipline (academic or non-academic) where memory involvement is important, it is necessary to be aware of mental pollution. As long as we are unable to control our contact with mental pollution, learning new material will be very difficult and time-consuming, no matter how hard we try, and forgetfulness will continue to be unavoidable.

History of discussion about singularity

Vernor Vinge, a science fiction writer, first wrote about the vision of technological singularity and coined the term in 1993. He wrote, "Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended."
Ray Kurzweil, inventor and futurist, is a fervid proponent of technological singularity. Kurzweil predicts the timeline of singularity as follows:

• By 2019, a $1000 PC will have the computing power of the human brain. It will be capable of performing 20 million billion calculations.
• By 2029, a $1K PC will be a thousand times more powerful than the human brain; the human brain itself will be successfully reverse engineered.
• 2045 is singularity: machines will have surpassed humans in intelligence and in fact will have created next-generation robots even smarter than themselves. We should either merge with our creations or step out of their way. Immortality!
• By 2055, $1K of computing power will equal the processing power of all the humans on the planet.

In 2011, Ray Kurzweil sponsored a movie/documentary about singularity, titled "Transcendent Man," which has been screened in five major cities in the U.S., as well as London. In December 2012, Kurzweil was hired by Google as a director of engineering to "work on new projects involving machine learning and language processing."
In 2000, Bill Joy, a well known computer scientist and the primary figure behind the BSD operating system (on which MacOS was built on) and the widely used Java programming language, joined this discussion. In a Wired magazine article, "Why the future doesn’t need us," Joy declared, in what some have described as a "neo-Luddite" position, that he was convinced that growing advances in genetic engineering and nanotechnology would pose severe risks to humanity.

Arguments and counterarguments about the feasibility of singularity

Proponents of singularity often cite Moore’s law to support their claim. Moore’s law states, crudely, that the capacity of computer chips doubles every two years. That is, the speed and capability of computers grows at an exponential speed. Such an exponential growth is a powerful enabler. Consider the series 1,2,4,8,16,32… The small increments in the beginning may be misleading about the overall speed of the series’ growth. The 20th element in this series would be 1 million. The 266th element in this series is 1080, which is more than the number of atoms in the universe.
Proponents of singularity argue that thanks to this exponential growth, the processing powers of computers will reach such high levels in the next few decades that it will be possible to simulate the human brain in high fidelity. The workings of each neuron in the brain will be simulated in real time, achieving a full simulation of the brain. At that point, the computer will essentially have the equivalent of human intelligence. In the succeeding years, with the increase in capacity, the computer intelligence will be several folds ahead of human intelligence.
Opponents of the feasibility of singularity cite that exponential growth is hard to sustain. Exponential growth is seen in the beginning of a series, but then due to limitations/adversities, most series will level off and stay constant. An example of this is the population of rabbits. Initially, the increase is exponential; however, due to scarcity of food sources and an abundance of predators, the population stabilizes around a constant. Therefore, opponents of singularity argue that the exponential progress of computer processing speeds will similarly hit a brick wall. At the chip level, physical issues such as heating will make exponential speedup unsustainable. At the cluster level, latency, consistency, and scalability issues will also prevent exponential growth.
Underlying all of Kurzweil’s ideas regarding the progress of technology and the singularity is the Law of Accelerating Returns. This Law states that technological progress occurs exponentially instead of linearly, meaning that each new advancement enables several higher advancements instead of just one higher advancement, and, concordantly, every year brings more useful inventions and discoveries than were made in the last. The first generation artificial intelligence (AI) approaches failed, but simulating a human brain may work if we know the workings of the brain in excruciating detail. As a promising development, recently, “deep learning” and “deep neural networks” technologies achieved great success in image and speech recognition tasks.
However, the opponents of singularity like to point out that the workings of the brain as a whole are still a big mystery. We have information about the rough mechanism of how a neuron works. An excited neuron can transmit a signal to a neighboring neuron through its synapses. But, there is no clear explanation about how thought occurs from this process. Brain-scanning techniques are improving, as they are based on computers, but the brain may throw us more complex surprises as we learn more about it.
In fact, much of the brain power comes about through organic materials, and the very low-level analog physical interactions between these materials. These physical phenomena could be close to impossible to model/simulate in a digital environment. Henry Markram, lead researcher of the "Blue Brain Project" for simulating mammal brains at the molecular level, has stated that "it is not [their] goal to build an intelligent neural network." He claimed, “[That would] be very difficult because, in the brain, every molecule is a powerful computer and we would need to simulate the structure and function of trillions upon trillions of molecules as well as all the rules that govern how they interact. You would literally need computers that are trillions of times bigger and faster than anything existing today."
Another relevant question is whether we can develop the parallel processing architectures needed to support the parallel processing that goes on in the brain. The brain uses far more parallel processing than exists in most classical computing designs.
Even if a computer successfully simulates the human brain, whether such a computer design will be “scalable” to two times, ten times, or even one hundred times the brain’s normal power is an unknown; for the human brain’s computation power may be inherently unscalable. Also, if a computer models the human brain, human emotions would also be modeled. Would the resulting computer be stable? As it scales up, would it become existential and suicidal, or perhaps become an arrogant killer?

The aftermath of singularity

Several questions are raised about the aftermath of singularity. Can a downloaded personality replace the spirit? How does this equate to living forever? Singularity promises are similar to claiming that you can live forever by cloning yourself. One copy dies, but another digital copy survives. But it is clear that the copies are different entities.
And it is also clear that this is not true immortality. If we stretch singularity’s approach to immortality a little further, we can argue that humans can achieve immortality through their work or art. And to this idea Woody Allen provided the best response: "I don’t want to achieve immortality through my work. I want to achieve it by not dying."

References

• Vernor Vinge, “The Coming Technological Singularity: How to Survive in the Post-Human Era”, 1993, available from https://www-rohan.sdsu.edu/faculty/vinge/misc/singularity.html
• Ray Kurzweil, ”The singularity is near: When humans transcend biology”, Penguin books, 2005.
• Bill Joy, “Why the future doesn’t need us”, Wired 8 (04), 2000.  
• Henry Markram, “The blue brain project”, Nature Reviews Neuroscience, 7 (2), 153–160, 2006.

The dispersal of scent takes place via the thermal and light-like behavior of the fragrant particles in the air. Thousands of points, letters, and words are positioned in each and every air particle. Each molecule is created in a form to carry sounds, sights, and odor. Millions of sound waves, scents and images are being transported and translocated into each of the trillions of air particles without deforming or mixing. As our knowledge pertaining to this transport grows, new technological products that will enable the transport of odors will be offered to the service of mankind.

Our sense of smell occurs in the brain. The chemical molecules exiting a lemon peel stimulate the odor receptors in the nose, which are then transmitted to brain to be interpreted as electric signals. Our olfactory system can easily distinguish more than ten thousand scents. This has inspired scientists to design similar devices. These models are called “electronic noses.”

A series of chemical receptors are utilized in the electronic nose instead of the receptor proteins of the human nose. Each of these is designed to sense various scents. These devices are difficult to produce, as the cost grows for a more sensitive device. The signals that sensors collect from the environment are converted into binary codes via electronic systems and then sent to a computer. The role of human nerve cells in charge of sensing odor is replaced by the electronic systems of a computer.

Mostly in their early phases, electronic noses are beginning to be used in various sectors, primarily those involving foods and perfumes, as well as the medical and chemical industries.

How does odor transportation take place?

As I already mentioned, the aromatic molecules transported via air particles in their gaseous state are detected by the smell sensor system and converted into electric signals. Quite a few different materials are used as conductors: conductive polymers, semi-conductive metal oxides, a quartz-crystal micro-balance (QMB), surface acoustic wave (SAW) sensors, pellistors, and infrared sensors.

Once the electric signals are converted into binary, the odor information is determined via a software program in which algorithms such as artificial nerve networks and support vector machines are employed. This information is then transmitted to a remote medium via lines of communication, such as a computer network, the internet, or another form of mobile communication. The odor type is received in the target computer. This detection stage can be completed in the target PC when necessary.

Today’s technology can only permit the transmission of odor data. In order to perceive the transmitted information at the target location as smell, the scents must be present as stored in containers and must be triggered via received odor data to be dispersed. The research in this field is limited, with ongoing pilot studies.

How can diseases be diagnosed with odors?

The natural functions of the human body, such as sweat, blood, urine, and feces, can be used to help diagnose diseases. The odor of the gases in human breath holds significant information regarding body health. There are between two hundred and four hundred different gases found in human breath. Furthermore, the number of gas types detected and described in the breath can exceed three thousand. While blood gets cleaned in the lungs, the gases of the used blood pass to the breath via the alveoli. Therefore, many critical pieces of bodily information are present in the breath.

The gases exhaled through our breath are composed of various alkaline and aromatic compounds. Each of these is a potential indicator that provides information about a disease. The gases and their ratio in the breath of a healthy person are well established. Since the ratio of the gases in the breath gets altered depending on the cause of an illness – such as diabetes (Type I and II), cancer of the ear-nose-throat, tuberculosis, and women’s reproductive diseases – can be diagnosed by utilizing the electronic nose.

There are other uses for the technology, too. NASA is developing a highly sensitive artificial nose for space research. This device will almost be able to distinguish every type of chemical compound, making more sensitive measurements than a human nose. With this device, the detection of harmful substances in the space station will be possible.

Google has announced that significant progress has been made regarding the “Google nose” which helped revolutionize searching for aromas. The Google Aroma database (http://www.google.com.tr/intl/tr/landing/nose/) stores more than 15 million kinds of scent. The days when we will be able to smell the scent of any product through our internet based devices do not seem to be too distant. To make this possible, sound waves would be converted into odor signals. There is a partially-imaginary video prepared to show how this can feel.

New technologies will change our relationship with smell, which has always been deeply important to humanity. Reference is made of this in the Qur’an, especially when the Prophet Jacob of Canaan sensed the fragrance of his son, Joseph, who was hundreds of miles away. The verse, from the chapter of Joseph, reads, “Surely, I sense the fragrance of Joseph, unless you would consider me a dotard. “It shows how valuable scent is to us, as anyone who has had a long lost memory triggered by an unexpected smell understands. As the verse suggests, losing our sense of smell is akin to losing our minds. Research has borne this out, as one of the first symptoms of Alzheimer’s disease is the loss of smell. In fact, monitoring loss of scent has helped with the early detection and prevention of Alzheimer’s. This is yet another way that our body has been perfectly calibrated to cue us in to its messages. In this regard, as with many, technology is still trying to catch up to nature.

The importance of character education programs

There are some programs that are called character education for detection of problematic behavior and school violence prevention or reduction. Was, Woltz, and Drew (2006) underscored the need for character education programs through utilizing statistics concerning school violence, absence, and dropout percentages. Bohlin, Farmer, and Ryan (2001) utter that in the US, there is a rising demand in schools to provide effective character education, whose purpose is to increase moral values, respect, citizenship, social skills, etc.

One of the most significant goals of character education programs is to decrease the bullying and peer-victimization that pervade many schools (Batsche – Knoff, 1994). Hence, character education programs should be taught effectively to prevent behavior problems and help students solve their own problems, since effective character education programs can alter the climate of a school by influencing the behaviors and attitudes of the students. That is, when appropriately implemented, character education programs encourage a positive school climate, thus improve academic performance and learning (Sherblom, Marshall – Sherblom, 2006). In addition, Leming (1993) expressed that “teachers in the program classrooms reported a statistically significant two-and-one-half times reduction in problem behavior in students” (p. 68).

The need for computer-based animated vignettes

In order to cope with the aforementioned problems such as bullying, victimization, unwanted behaviors within schools, etc., character education institutions can hire more teaching staff, or teachers can work more than they have done before. However, neither hiring more staff nor working harder is an appropriate solution to help students deal with the problems encountered in schools, because students should learn to cope with the problems by themselves. Thus, they need to have the self-confidence and self-esteem to overcome inappropriate behaviors. It means that the implementation of the character education programs is crucial in terms of their effectiveness.

In this respect, there could be some efforts to facilitate social competence within the classroom and to lead to positive behavioral outcomes (Kam, Greenberg, – Kusche, 2004). Therefore, as an alternative solution, computer-based animated vignettes utilized in character education programs such as Clover, which “is a multimedia tool that empowers students to construct their own animated vignettes that meaningfully express personal experiences” (Baily, Tettegah – Bradley, 2006, p. 802) can be part of these efforts to solve students’ problems in moral and social situations by stimulating them to engage in problem solving (Bailey et al., 2006).

It is important for these programs to be computer-based, since, as Bers (2001) underscored, computers are influential tools for self-exploration. Computers are also beneficial for children in terms of socialization. Heft and Swaminathan (2002) mentioned in their study that children could interact with one another because instructors want them to work in pairs. This provokes them to ask questions to each other to solve problems. Furthermore, in the study done by Nastasi and Clements (1992), it was revealed that a computer-based program, Logo, could foster cognitive development by stimulating cognitively-based resolution of cognitive struggles.

Definitions of animated vignettes

Tettegah and Anderson (2007) describe Animated Narrative Vignettes (ANV’s) as “concrete examples of people and their behaviors, and stories about individuals, situations, and structures that can make reference to important points in the study of perceptions, beliefs, and attitudes” (p. 51). Some researchers, Zhou et al. (2003) define vignettes as ”emotion-evoking stimuli presented via audiotapes, videotapes, or realistic enactments that aim to make participants believe that the events and people involved in the stimuli are real, not hypothetical.” As understood through the definitions, animated vignettes are related to either behaviors or real visual events. Therefore, animated vignettes may be utilized in character education classes to make them more effective to reduce behavioral distortions.

Animated vignettes in character education

Bailey et al., (2006, p. 796) pointed out that when technology education is integrated within learning activities that are meaningful to students, it could be more effective. Therefore, they aimed to seek to link the delivery of technology and character education through the utilization of animated vignettes. In this process, students can gain and exercise technological skills and learn how to figure out concepts within a learning activity that is important to them while also building the vignettes via computers (Bailey et al., 2006, p. 796). Vignettes have been utilized to instruct Mathematics and Science, management skills, problem solving, and character education (Bailey et al., 2006,p. 797). In the sense of character education, Vignettes are typically used to facilitate some techniques, such as reflection, role-playing, problem solving, and ethical thinking and positive social behavior among students (Bailey et al., 2006,p. 797).

So far, this paper has discussed the importance of character education programs, the need for animated vignettes, and their definitions. Next, this paper will present the effectiveness of animated vignettes and how they can facilitate learners to recognize and reduce problem behaviors.

The effectiveness of animated vignettes

Vignettes are beneficial and effective as a teaching instrument; this is because they can provide real representations of situations, helping students solve problems (Bailey et al., 2006). In the article of Bailey et al., (2006), it is sought to link technology and character education through constructing and utilizing animated vignettes. Researchers illustrate that animated vignettes could be more beneficial when they provide three important features: meaningfulness, personal experiences, and having a dialogue.

a) Meaningfulness

Thanks to these computer-based animated vignettes, students will be able to learn via some activities that are meaningful to them. To provide effective character education, vignettes can be used as a significant tool (Bailey et al., 2006, p. 796). For example, in the study implemented by Tettegah and Anderson (2007), animated vignettes were used for gathering data. Vignettes showed an interaction between two children – “Scott, a 9-year old Caucasian boy, and Jamilah, a 9-year old African American girl; or Jamal, a 9-year old African American boy, and Erin, a 9-year old Caucasian girl) – and one teacher (Ms. Litts), and one parent (Mr. Young)” (Tettegah – Anderson, 2007, p. 52).

The vignettes were counterbalanced to determine if responses given by pre-service teachers are different from one another about the race of the victim and perpetrator. A child told the animated vignette; thus, the characters in these vignettes symbolized real people in real life. Ms. Litts (the teacher) was working with the class on a supportive learning activity, such as making paper puppets or building bridges. However, there was no difference between activities in terms of vignettes. That is, the same performances were represented in each vignette. In these processes, making paper puppets or building bridges, the teacher wanted students to work each other, like “Scott with Jamilah in the puppet making activity or Jamal with Erin in the bridge making activity, depending on the vignette” (Tettegah – Anderson, 2007, p. 52). In each scenario, the boy (Scott or Jamal) told the girl (Jamilah or Erin) that they did not want to be in the same group with the girls because of their skin color. They added that their skin color might influence them. After that, the girl’s fathers reported the event to the teacher, Ms. Litts, and the teacher was surprised, since they had talked about Martin Luther King Jr., which she believed was relevant to the topic.

After watching the vignette, participants were asked how they would respond if they were in the teacher’s position, and they wrote down their responses. In this example, participants were asked to put themselves into another person’s position through animated vignettes. As a consequence of the study, participants could place themselves into another character, and could try to consider helping their children solve the prescribed problems.

b) Personal experiences

As a solution, computer-based character education programs could be effective if animated vignettes are “based on personal experiences rather than on artificially constructed circumstances” (Bailey et al., 2006, p. 794). Students can improve both self-awareness and interpersonal skills by practicing some skills shown in vignettes. That is, they can also incorporate theory and practice in a personally related way (Barter – Renold, 2000). Thanks to this process, students are able to engage in their own ethical and social thinking. This allows students to become more engaged in their own moral and social thinking (Tappan, 1991).

To illustrate, consider this example: in the study implemented by Tettegah (2005), there was a real experience of a father, daughter, classmate, and teacher developed in the animated narrative vignettes and told by a real person. After viewing the vignettes, the educators wrote some responses for problem solving to questions like, “Who does the participant express empathy with? In whose position does the respondent imagine himself?” (Tettegah, 2005, p.383). Thanks to these questions, teachers could better understand peer conflicts related to classroom education. Responses were to involve educators and students in sharing with others to help them to be aware of conflicts that are both peer and teacher-related (Tettegah, 2005, p.383).

c) Dialogue opportunities

Through using animated narrative vignettes, it is possible to have a dialogue that will allow educators to talk over and also foster a better understanding of bullying and victimization (Tettegah, 2005). Computer-based animated vignettes are beneficial tools for discovering relationships between people (Fong – Woodruff, 2003). For instance, well-known educators are brought together to discuss issues about oppression and discrimination in their classrooms through cultural portals. In these meetings, they try to figure out how to cope with the problems in the classroom and within the school’s social environment. Using computer-based tools to find the cause of complex behaviors in the class is very useful (Tettegah, 2005). Although this seems to affect students’ problem behaviors indirectly, it may be effective in comprehending the problems and discovering some solutions to reduce problem behaviors.

Conclusion

Implementing computer-based programs to help recognize and solve problematic behaviors could be very beneficial to many schools. As emphasized above, researchers have shown that there are problematic behaviors observed in schools. Therefore, character education programs could be effective to reduce and solve these problems. Making the programs more beneficial as a means of computer-based animated vignettes helps students notice and reduce problems. They can be more effective if they are meaningful to students and if students can put themselves into the real characters in the vignettes to recognize the problems. The personal experiences underscored in the vignettes trigger students’ awareness through practicing the skills showed in the vignettes. And the vignettes can assist in generating a dialogue between educators and students to understand the issues and help develop some solutions together.

Namik Top is a PhD candidate in the Department of Educational Psychology at Texas A-M University.

References

• Algozzine, K., Christian, C., Marr, M. B., McClanahan, T., – White, R. (2008). Demography of problem behavior in elementary schools. Exceptionality, 16, 93 – 104.
• Baily, B.P., Tettegah, S.Y., – Bradley, T.J. (2006). Clover: Connecting technology and character education using personally-constructed animated vignettes. Interacting with Computers, 18, 793-819
• Barter, C., – Renold, E. (2000). I wanna tell you a story: Exploring the application of vignettes in qualitative research with children and young people. International Journal of Social Research Methodology, 3(4), 307-323.
• Batsche, G.M., – Knoff, H.M., 1994. Bullies and their victims: understanding a pervasive problem in the schools. School Psychology Review 23 (2), 165-174.
• Bers, M. (2001). Identity construction environments: Developing personal and moral values through the design of a virtual city. Journal of the Learning Sciences, 10, 365-415.
• Bohlin, K.E., Farmer, D., – Ryan, K., 2001. Building Character in Schools. Jossey-Bass, San Francisco, CA.
• Bowen, J., Jenkins, W., – Clark, E. (2004). School-based intervention for students with behavior problems. New York: Kluewer Academic.
• Fong, C., – Woodruff, E. (2003). Web based video and frame theory in the professional development of teachers: Some implications for distance education. Distance Education, 24(2), 195-211.
• Freeman, R., Eber, L., Anderson, C., Irvin, L., Horner, R., – Bounds, M. (2006). Building an inclusive school culture using school-wide PBS: Designing effective individual support systems for students with disabilities. Research and Practice for Persons with Severe Disabilities, 31(1), 4-17.
• Heft, T.M., – Swaminathan, S. (2002). The effects of computers on the social behavior of preschoolers. Journal of Research in Childhood Education, 16(2) 162-174.
• Henricsson, L., – Rydell, A. M. (2004). Elementary school children with behavior problems: Teacher-child relations and self-perception. A prospective study. Merrill-Palmer Quarterly, 50, 111−138.
• Kam, C. M., Greenberg, M. T., – Kusche, C. A. (2004). Sustained effects of the PATHS curriculum on the social and psychological adjustment of children in special education. Journal of Emotional and Behavioral Disorders, 12, 66−78.
• (Heft, 2002) (Heft, 2002) (Heft, 2002)Nastasi, B.K. – Clements, D.H. (1992). Social-cognitive behaviors and higher-order thinking in educational computer environments. Learning and Instruction, 2, 215-238.
• Pace, T. M., Mullins, L. L., Beesley, D., Hill, J. S., – Carson, K. (1999). The relationship between children’s emotional and behavioral problems and the social responses of elementary school teachers. Contemporary Educational Psychology, 24, 140−155.
• Sherblom, S., Marshall, J., – Sherblom, J. (2006). The relationship between school climate and math and reading achievement. Journal of Research in Character Education, 1(1), 19-31.
• Tappan, M., 1991. Narrative, language, and moral experience. Journal of Moral Education 20, 243-256.
• Tettegah, S., 2005. Technology, narratives, vignettes, and the intercultural and cross-cultural teaching portal. Urban Education 40 (4), 368-393.
• Tettegah, S., – Anderson. C. J. (2007). Pre-service teachers’ empathy and cognitions: Statistical analysis of text data by graphical models. Contemporary Educational Psychology 32, 48-82.
• Was, C., Woltz, D., – Drew, C. (2006). Evaluating character education programs and missing the target: A critique of existing research. Educational Research Review, 1(2), 148-156.
• Zhou, Q., Valiente, C., – Eisenberg, N. (2003). Empathy and its measurement. In N. Lopez – C. R. Snyder (Eds.), Positive psychological assessment: A handbook of models and measures (pp. 269-281). American Psychological Association.

Despite advances in technology, computers still can’t come close to the power of the world’s most remarkable computer – the human brain.

Computing machines have seen three phases: the tabulating phase, the programmable phase, and now the new era of computing, the cognitive phase [1]. Tabulating machines performed a fixed task, whereas programmable machines could be reprogrammed to execute different tasks without any change in the hardware. Cognitive machines, however, promise learning and reasoning capabilities.

The possibility of such machines raises the question: is cognition the ultimate test for conscious existence? What do we know about cognition? How do we define intelligence? The questions go on and on. One thing, however, everyone seems to agree with is the fact that understanding the mechanism of human cognition is the key to developing advanced artificial intelligence, and cognitive machines.

Cognitive machines have the ability to learn, and they employ artificial intelligence to “reason.” Artificial intelligence is defined as, “The science of making machines do things that would require intelligence if done by men” [2]. The good news is that cognitive computing is no longer an esoteric pursuit of some futurists. It is, and has been, essential for the operation of many big-data driven processes. The 21st century has been flooded with data coming from almost every aspect of our lives. Technology has made it possible to generate data at an exponential rate. Temperature distribution throughout our buildings, the number of people diagnosed with cancer in the last six months, real-time changes in customer preferences, ethnic profiles of college applicants, and the top three words trending in online conversations at this very moment, are some examples of the kind of data available today.

As the amount of data generated increases, it also becomes harder and harder to process and make sense of the data collected. Our “greedy and ambitious” human nature does not want to waste, and it wants to use every bit of available data. This is where it becomes imperative to have a computing machine that goes beyond performing pre-programmed tasks and learns as it goes, without human interference. For this kind of computing, we need cognition.

The biggest challenge in imitating human cognition is to understand how cognition happens in the brain. It is obviously beyond our ability to monitor such activity that is constantly taking place in our brains, let alone recreating such marvels in the first place. Nevertheless, it will be a great achievement if we can manage to somewhat imitate human cognition, even partially. It would open a whole new era in terms of what can be achieved from a computing standpoint. For instance, the entire curriculum of a college degree can be processed by a cognitive machine in a fraction of a second; such machine can digest the whole of medical literature in a short period of time, provide human doctors with second opinions on their diagnoses [3].

Despite the fact that there have been substantial improvements in designing “intelligent” computing machines, mimicking the hardware of the human brain and simulating its decision-making processes, have posed three fundamental challenges: a hardware with comparable processing power and memory, a software algorithm to implement intelligent behavior, and the necessity of both being self-adapting and self-improving.

First of all, human intelligence has not been fully characterized – its capabilities and limitations are still unknown. This lack of knowledge makes it difficult, and perhaps even impossible, to reduce such intelligence to smaller, or simpler, modules. Therefore, we don’t have a good handle on how to mimic the human brain in a behavioral sense.

The second major problem is that we are still far away from having the hardware on which our “intelligence” software could run. Implementing intelligence in conventional computing machines, evidently, seems to be a futile undertaking. Programmable machines are no match for human brains; even the fastest supercomputers, taking advantage of thousands of processors, is able to mimic just one percent of one second worth of human brain activity-and even that takes 40 minutes [4]. Therefore, cognitive computing machines must incorporate different hardware architecture from conventional computers to achieve cognition comparable to humans. IBM’s SyNAPSE chip is one example of hardware inspired by the brain, and it has the potential to carry out the required, intense computations.

Lastly, the human brain and its cognitive power are constantly changing. Depending on various factors and experiences, our brains can improve or deteriorate; this is also true of our cognitive power. However, such improvement or deterioration could be in the form of a change in the physical structure or the amount of capacity utilized [5]. Such dynamic flexibility, also called Brain Plasticity [6], is essential to our intelligence. At this time, no self-evolving computing hardware has been worked out. However, promising developments have been reported with respect to cognitive computing machines that can learn – that is, they can make deductions and reach conclusions that are not preprogrammed.

Along the way, human supervision will be the ultimate guide in perfecting such imitation. Therefore, human cognition, taken for granted in our daily lives, remains to be the final frontier for our thousands-years long technological journey. Once again, the creation set the boundaries for human development.

Adem G. Aydin holds a Phd degree in Electrical and Computer Engineering. He works as an engineer scientist at IBM.

References

[1] Virginia Rometty, 2013, http://smarterplanet.tumblr.com/post/32816006311/i-b-m-chief-on-watson-cognitive-computing-and-her

[2] Marvin Minsky, 1968, http://www.akri.org/ai/defs.htm

[3] “WellPoint and IBM Announce Agreement to Put Watson to Work in Health Care”, http://www-03.ibm.com/press/us/en/pressrelease/35402.wss

[4] “Largest neuronal network simulation achieved using K computer” http://www.riken.jp/en/pr/press/2013/20130802_1/

[5] William James, The Principles of Psychology

[6] Bryan Kolb and Ian Q. Whishaw, Brain Plasticity and Behavior, Annual Review of Psychology, Vol. 49: 43-64

It was only a decade ago that a phenomenon called the “Internet” came along and changed the way we communicated, did business and conducted our lives. Now, computer technology has become an essential and significant part of our daily lives. But how did it all start and where is it heading?

I entered the world of computers at an early age. I had an Atari 800 XL, the third version of the Atari introduced in 1983, and I was doing some basic programming. The computer contained a full 64K of memory, 1.8 MHz processing power (CPU), and looked like a bulky keyboard. I enjoyed spending a lot of time with games and programming; however I felt very limited with its capabilities. After more than 20 years, from time to time I still feel the same about my 2.8 GHz eight-core desktop computer with 8 GB of memory. While the computers are getting faster and more powerful, our need for computing power is also increasing just to complete our daily tasks at home and work. I always wondered how it all started and where we are heading with computer technology.

Over forty years ago, Gordon Moore, Intel Co-founder, predicted the number of transistors incorporated in a chip to double every 24 months. This is popularly known as Moore’s law, and used countless times by futurists [1] and science fiction writers. For the last half century, computer’s functionality and performance increased in line with Moore’s law, while costs are decreasing. However, fundamental barriers in semiconductor technology are emerging including the power needs and limits of manufacturing in atomic dimensions. Computer industry is already working on technologies to keep Moore’s Law alive.

Intel is already experimenting with 3D transistors that are smaller, faster and more energy efficient using a 22nm (nanometer, 10-12 m) manufacturing process compared to today’s 32nm systems. This will be a significant step forward to build more transistors onto silicon chips. Another approach will be by replacing the silicone in transistors. In 2010, IBM showcased a graphene transistor running at 100 GHz, with a potential of up to 1000 GHz. A graphene layer is only one atom thick with a honeycomb-like structure of carbon atoms. The graphene has unique electrical, optical, mechanical and thermal properties with promising applications in many industries.

In 1971, a theoretical prediction was made for the missing link in electronics, memristor, a fourth element to supplement resistor, capacitor and inductor, which form the basis of today’s electronic devices. HP’s demonstration in 2010 shows a resistor with memory that remembers the electric voltage applied even when the power is turned off. Requiring very little energy to store information promises to run ten times more power efficient and ten times faster than current counterparts.

In 1994, Leonard Adelman [2] proposed DNA computing to solve the famous, “shortest path problem”. Since then, many approaches have been made to utilize the properties of DNA for computing. In 2010, researchers at California Institute of Technology demonstrated a DNA computer, most advanced to date, which can calculate square roots. This approach could be put in use inside living organisms, and perform vital tasks such as disease detection. The promise of DNA computers depends on the parallel processing capabilities of DNA molecules that can try many possibilities at once with low power requirements [3]. Further advancements in DNA based computers in the coming decades will bring faster and low-powered computers to our daily lives.

In 1981, the famous physicist Richard Feynman speculated the possibility of computers obeying quantum mechanical laws that might best simulate the real-world quantum systems. This is a big challenge even for today’s fastest supercomputers. Since then, researchers are pacing towards building quantum computers that rely on quantum mechanics to conduct operations. Quantum computers can use properties like entanglement [4] and qubits. In entanglement, particles behave identically independent of the distance between them, and qubits act as both memory and state of the entanglement. Shor’s Algorithm, formulated by Peter Shor in 1994 for prime factorization is a powerful example of quantum computing that allows breaking encryption algorithms like RSA encryption more effectively and quickly than today’s super computers. Quantum computers can perform at much higher speeds than traditional computers, and are able to solve more complex problems. Recent developments in quantum computing such as quantum photonic chips [5], and first commercial quantum computer by D-Wave shows that we might be closer than we think to have our very own quantum computer in the coming decades.

While greater shift in computing might stem from the change in underlying technology in processing the information, computer form factors (desktop, laptop, tablet, phone, etc.) have a more direct effect in our daily use of computers. Human computer interaction changed significantly with the introduction of smartphones (e.g. iPhone, Android phones), and tablets (e.g. iPad), moving from keyboards and mouse as the primary input methods towards touch screens.

Today’s touch screens, although providing infinite ways of input structures available on their screens, lack tactile feedback when compared to keyboards. New keyboard designs with small screens on each key opens infinite customization of the input, but are still limited to initial design of the key (e.g. usually cubic). Recent developments in touchscreen designs enable users to feel clicks, vibrations and other tactile input by using “haptic technology”. Haptic technology takes advantage of the user’s sense of touch and provides feedback by applying forces, vibrations, or motions to the user. As seen in early prototypes, flexible screens and electronics will provide a more realistic feel for human computer interaction by shifting their forms to a specific shape (e.g. game pad, key, and wheel) in the coming decades.

Another level in human computer interaction even eliminates user’s touch. Apple introduced Siri, a smart virtual assistant, in 2011 as a part of their iOS operating system for iPhones and iPads. Siri is capable of analyzing user’s complex audio inputs to carry out many tasks including scheduling a meeting, creating a reminder, typing and sending SMS messages, and many other functions available in smart phones. Microsoft introduced Kinect in 2010, a motion-sensing device that enables users to control and interact with the game console using gestures and spoken commands. The Kinect interprets specific gestures by using an infrared projector and camera to track the movement of objects and individuals in three dimensions.

Samsung introduced a 46’’ transparent display using LCD technology in 2010, and demonstrated flexible displays in CES 2011. Transparent and flexible displays will easily find use in wearable electronics such as contact lenses and glasses. An obvious application of transparent display is Augmented Reality (AR) where information is displayed on top of real world images. While today’s smartphones and tablets allows augmented reality by combining information with the real-time video feed from the camera of the device, transparent display eliminates the need of using camera. Current AR technology includes head-mounted displays and virtual retinal displays for visualizing the information. It is widely applied in various areas including entertainment, advertising, game industry, navigation, education, military applications, and information sharing.

While having larger, transparent, and flexible displays in different forms, one direction in display technologies is to reduce the size or even eliminate the display through projection and holograms. Current trends in projectors include 3D projection, synchronization of multiple projections, and pico projectors. The world’s smallest glass lens (1mm x 1mm) introduced in 2011 will help minimize some of the problems of projectors such as size, power and heat, and improve their integration in smartphones and tablets.

Recent prototypes of holographic displays progressed significantly demonstrating 3D and full color animated images, since its first introduction at the MIT Media Lab 1989 [6]. While developments in 3D displays are promising, holography provides the best 3-D experience since it is closest to how we see our environment. A hologram uses an optical effect called “diffraction” to produce the light that would have come from an object, and makes the image of the object appear in front of the viewer. It is possible to view objects from different angles in holographic display by walking around them. Unlike other 3D display systems, holographic displays do not require special glasses for viewing and allows multiple viewers to experience the view from different angles at the same time. Future applications of holography can be implemented in health, entertainment and communication sectors, from 3D movies to telepresence applications.

All of the above examples and trends in computers deal with the computing as a product. Cloud computing can be defined as the delivery of computing as a service where shared resources, software, and information are provided over a network. Cloud computing describes a new delivery and consumption model that allows dynamic scalability and virtualization of resources. Users can dynamically upgrade the storage and computing power from virtualized resources on demand without hardware changes on the base system. Organizations can save from investing on expensive hardware, and human capital.

Many technologies from coming centuries are featured in science fiction books and movies such as Minority Report, Star Trek, and Star Wars. While some of them are already available to consumers, others might require decades to come. Motivation for the advancement in computer technologies usually stems from our needs and desires. At the same time, new technologies significantly impact consumer behavior and increase our dependence on new technologies. Our economy is structured such that all citizens have to consume more and more, even if that means disposing of perfectly good technological devices. Do we really need a new computer or phone every year? Most of us don’t.

Computer technologies are a significant part of our daily lives, and the line between the products and services is becoming thinner with the dependency on computers increasing in every aspect of our life. While improving the quality of our lives by making our daily tasks easier, computers and Internet technologies can affect us in different ways. It has already started to change how we read, write and even communicate with others. Many concerns are raised about the negative effects of the use of technology including Internet addiction, privacy, attention span, concentration, time consumption, anxiety, isolation, depression, digital security, communication disorder and various health issues. The challenge for us is to understand the benefits of the technology, have a balance in dependence and its use, and protect ourselves from its adverse effects.

Acknowledgment: This article is produced at Mergeous [7], an online article and project development service for authors and publishers dedicated to the advancement of technologies in the merging realms of science and religion.

References

1. Kaku, Michio. 2011. Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives by the Year 2100, Knopf Doubleday Publishing Group.

2. Demir, Halil I. 2011. Super Computers in a Cell, The Fountain, Issue 80, March – April.

3. Adleman, Leonard M. 1994. “Molecular Computation of Solutions to Combinatorial Problems,” Science, 266 (11), 1021–1024.

4. Demir, Halil I. 2011. Quantum Worlds from Entanglement to Telepathy, The Fountain, Issue 84, November – December.

5. Shadbolt, P. J. et al., Generating, manipulating and measuring entanglement and mixture with a reconfigurable photonic circuit, arXiv:1108.3309v1 [quant-ph].

6. Hilaire, P. St., S. A. Benton, M. Lucente, M. L. Jepsen, J. Kollin, H. Yoshikawa and J. Underkoffler. 1990. “Electronic display system for computational holography.”In Practical Holography IV, Proceedings of the SPIE, volume 1212-20, pp. 174-182, Bellingham, WA. 7. Mergeous, Online article and project development platform, http://www.mergeous.com

In spite of the developments in science and technology, we are still so powerless at predicting phenomena; there is so little we can control and uncertainties are so many. We do not face the challenge of uncertainties at predicting happenings but also at decision-making. While we make decisions in daily life we try to minimize uncertainties. Any decision that holds uncertainties in its nature is risky. Therefore, decision-making processes are a kind of risk management at the same time. All the efforts are directed toward reducing the possible risks and mistakes. High-risk problems have a higher ratio of mistakes.

Studies of forecast need collecting numeric data and analyzing them along with obtaining relevant information based on observations. The data to be collected should be objective and the statistical methods appropriate. Otherwise, unsuccessful forecasts will lead to waste of time, money, and resources. Decision problems with uncertainties can be of different nature. For example, it is possible to reckon when an apple which broke off from its branch will reach the ground by knowing physical laws. As factors get more complicated, possibility of surprises is much higher. The discipline which systematizes these studies is econometrics. Statistics, mathematics, economics, optimization, decision-making, and computer science fall within the studies of econometrics. Forecast problems are mainly studied with numeric and extrapolative analyses.

In recent years, intuitive methods have been added to these two major approaches. Along with other issues, numeric analysis is frequently used in artificial neural networks, computer simulations, and computer-based learning methods. Artificial neural networks are formed by trying to model the millions of neurons in human brain work. The artificial cells whose number varies between five to ten are educated by using a certain mathematical transformation function, with recurring algorithmic processes. At the end of the process of education with past data, the performances of the calculations in new situations are evaluated. This method, which is used at various forecast problems, is really meaningful in terms of reflecting what can be done by merely copying a few of the millions of human nerves. However, the greatest obstacle before the studies of artificial neural networks are the computers with insufficient capacity. Even super computer systems have difficulty in an optimization problems with more than a hundred cells and the data obtained is far from useable. One cannot help but amaze at the perfect capacity of human brain and how it tackles hundreds of parallel processes incessantly. In some decision-making problems, due to insufficient numeric data, the parameters targeted to be forecast may not be reliable and present a peculiar nature. The studies about very rare diseases and forecasting technological developments are examples to that. In such cases, numeric analyses do not help because of not having any reliable numeric data. Therefore, extrapolative analysis methods are preferred at such forecast problems. At forecasts based on extrapolation, the expert’s level of knowledge, intuition, experience, capacity of processing information, and power of judgment are important but they remain limited. There are lots of forecast problems about socioeconomic life such as economic fluctuations, price moves, and commercial size. Healthy forecasts on how and when to make investments are very important in order for the investors’ determining how to utilize their resources. However, the investors’ decisions will inevitably have uncertainties to a great degree. Therefore, it can be said that studies of forecasting are still in the cradle.

No matter of what quality, forecasts are always needed, since expectations for the future need to be determined and met. One of the basic assumptions of the economic system that make its effect felt in the global scale is that, human beings are self-centered creatures who act on opportunist drives. Such philosophies have always impelled people to be egocentric. However, people can listen to their conscience instead. They can simply choose to be altruistic; they can choose to care about others and help them. It is possible to reverse such an understanding of selfishness by giving charity and fulfilling other responsibilities. Thus, the forecasts about the future depend on what is to be given priority. In other words, the science of forecast can serve a more humane philosophy.

Everything is finely balanced with appropriate measures in this universe. Everything is created with wisdom. From the perspective of forecasting studies, our efforts can in a way be seen as guesswork to learn about destiny. Although we can try to make predictions within certain limits, we can never ignore possible surprises which take place totally out of our control. Human beings are equipped with an ability to make decisions in the face of uncertainty. We are supposed to comprehend the philosophy of creation and try to discern the meaning of the pattern being woven by Providence.

Ertugrul Deniz is a freelance writer from Turkey with a PhD degree in mathematics.

References

• Makridakis, Spyros; Wheelwright, Steven; Hyndman, Rob J. (1998). Forecasting: methods and applications, New York: John Wiley & Sons.
• Fama, Eugene (1970). “Efficient Capital Markets: A Review of Theory and Empirical Work”. Journal of Finance 25 (2): 383–417.

ENIAC had cost around $500.000 and was capable of 5000 simple operations per second. Today, basic personal computers (PC) cost around $500 with enough processing power to perform millions of operations per second. An average PC is enough in terms of computing power for everyday use like word processing, checking emails, and computer games. However, some areas in scientific research require computers at the frontline of current processing capacity, called Super Computers. Twice a year, the TOP500 project, which started in 1993, ranks and publishes details of the 500 most powerful super computers in the world. The IBM Roadrunner, located at Los Alamos National Laboratory, was announced as the fastest supercomputer in the world as of May 2008.

In computing, “flop” (Floating Point Operations Per Second) is a measure of a computer’s performance which is similar to calculations per second. The IBM Roadrunner had cost $133 million and had a peak performance of 1.7 petaflops, which is around 1.7×1015 operations per second. The Roadrunner was delivered on 21 tractor-trailer trucks to its current location. Supercomputers are an essential component of research in areas like computational biology, fluid dynamics, structural mechanics and cancer research, which requires high computing power.

While computers get faster every year, their computing power is way behind when compared to a human brain. They consume hundreds of times more energy than a brain. It is estimated that a computer will be able to simulate a human brain in seven years, yet we are decades away from expecting a computer that can think like a human and make decisions. The brain is one of the most miraculous parts of the human body, full of mysteries. It works more efficiently than any machine developed in the last 50 years of the computer history.

However, the human brain is not the only body part which has an incredible computing power. In 1994, Leonard M. Adleman, a professor at the University of Southern California, introduced the idea of using DNA (Deoxyribonucleic Acid) to solve computational problems [3]. This idea then led to a new field of science, called DNA Computing, which combines two disciplines, biology and computer science, to build the fastest and smallest computers ever. DNA is known as the blueprint of life, with unique properties such as self-assembly, molecular recognition, minute size and high information density.

Computationally challenging problems have known solutions, but enormous amounts of resources (time and/or cost) are required to find the optimum solution. Some problems, such as optimization, can be solved by generating many possible solutions, and then selecting the optimum one. Standard computing methods can generate or test a possible solution one at a time. On the other hand, parallel computing methods can carry out this process simultaneously for thousands of possible solutions.

Similarly, enzymes can work in parallel for replicating and repairing DNA strands. They can even work on the next strand before the first one is replicated. An enzyme can replicate a DNA strand 500 times in a second, which is equal to 0.001 MIPS (million instructions per second). The computations in DNA can reach to 1014 MIPS, while a modern computer runs at an average of 1000 MIPS. DNA computing is not only faster in processing, but also much more efficient in energy consumption. The energy consumption of a DNA operation (on one strand) is about 1010 times less than the energy consumption of an operation on modern computers.

The Traveling Salesman Problem (TSP) is one of the most studied problems in computational mathematics. Here is an example of the problem: a traveling salesman needs to visit 20 cities once, with predefined starting and ending locations, and certain rules. The complexity of the TSP problems increases exponentially with the number of cities, so problems with only hundreds of cities will take thousands of years to solve by modern computers. If there are 18 factorial possible paths in this problem, it will take 2 whole years for a computer with 100 MIPS of processing power to generate the possible paths and find the correct answer. However, all possible paths can be generated in a very short time by using DNA computing. A simplified version of the Traveling Salesman problem presented by Adleman involves the following scenario:

A salesman wants to visit the cities (Figure 3) Monroe, Gainesville, and Conyers, starting from Athens, and arriving at Atlanta last. Each city should be visited only once. The cities are not fully connected. While some cities are connected to another in one direction, others are connected in both directions. Our objective is to find the shortest route to visit all cities once. The solution for this problem is a travel from Athens -> Gainesville -> Monroe -> Conyers -> Atlanta.

When we convert the problem to a molecular language, each city is coded as a single-stranded DNA molecule with 8 nucleotides. We can think of nucleotides as bytes in computer programming, which will take the value 0 or 1. Nucleotides exist as four bases: adenine (A), thymine (T), guanine (G) and cytosine (C). All cities are coded with eight nucleotides as follows:

City Code

Athens ATGC CATG

Gainesville TCAG GTCA

Monroe GACT TGAC

Conyers CGTA ACGT

Atlanta AGCT TAGC

Connections between two cities are coded with the last 4 nucleotides of the departure city and the first 4 nucleotides of the arrival city. For example, the connection between Athens (ATGCCATG) and Monroe (GACTTGAC) is coded as CATGGACT. The complementary codes for connections (the Watson-Crick complements), where every C is replaced by a G, every G by a C, every A by a T, and every T by an A, and connection codes are given below:

Connection Code Complementary Code

Athens – Gainesville CATG TCAG GTAC AGTC

Athens – Monroe CATG GACT GTAC CTGA

Gainesville – Atlanta GTCA AGCT CAGT TCGA

Gainesville – Monroe GTCA GACT CAGT CTGA

Monroe – Conyers TGAC CGTA ACTG GCAT

Conyers – Atlanta ACGT AGCT TGCA TCGA

Conyers – Monroe ACGT GACT TGCA CTGA

The mixture for performing reactions will include DNA strands and their complements for 5 cities and 7 connections between cities in our example. If an Athens molecule (ATGC CATG) encounters the complement strand of an Athens-Monroe (GTAC CTGA) connection in the mixture, a hydrogen bond will be formed between strands (Figure 4). Other strands will continue forming bonds for valid connections between cities, building a complete travel path with the help of DNA ligase. There needs to be enough copies of each DNA strand to generate all possible travel paths.

ATGC – CATG

| | | |

GTAC – CTGA

Polymerase Chain Reaction (PCR) will be used to make multiple duplicates of DNA strands containing Athens (start) and Atlanta (end) cities. The result of PCR will be the amplification of correct travel from Athens to Atlanta, which makes it easy to separate. PCR is a method by which a few strands of DNA can be copied into millions in a very short amount of time. This also makes PCR a very important method to increase small amounts of DNA found in blood or hair samples, which could be enough to carry out analysis and reveal a person’s identity in forensic science.

Electrophoresis follows the PCR process to sort the resulting paths according to their sizes. Since every city is coded with 8 nucleotides, the correct path should include exactly 40 nucleotides representing a full path for 5 cities. The gel electrophoresis process uses an electric field to separate DNA strands by size as they travel through a gel matrix. The speed of DNA molecules differs by their size, which results in the sorting of the molecules by size. After this step, DNA strands starting with the code of Athens, ending with the code of Atlanta and with a size of 40 nucleotides are separated from the mixture.

The last step will be reading the code and removing the DNA strands that didn’t contain all the cities. Adleman used a common method known as affinity purification for the separation process. Finally, the mixture has the DNA strands with the correct travel path, starting from Athens and arriving to Atlanta, and traveling through every city once. All the laboratory work looks complex for this simple problem, but as a new concept for computing, it is revolutionary. In its ability to perform parallel computations, DNA computing shows great promise over traditional computing approaches.

Data density is another unique advantage of DNA. Billions of DNA strands can be stored in a regular laboratory tube. A DNA strand is composed of bases A, T, C and G spaced evenly, 0.35 nanometers apart from each other. The data density of DNA is around 106 GB (gigabytes) per square inch, which is 100,000 times larger than the data density of today’s storage technologies (7 GB per square inches). Moreover, DNA is a durable and strong molecule; the information stored within it can be kept for thousands of years in the right conditions. In 2008, 80% of the woolly mammoth genome, several thousand years old, has been identified from tufts of frozen woolly mammoth hair [4].

DNA is also created with remarkable mechanisms such as built-in error correction. The double stranded nature of DNA provides a double check on pairing. Error repairing enzymes are always ready to search for anomalies during the DNA replication process. It results ina ratio of one error per billion replications. DNA is located and protected at the center of each cell with a perfect balance. The miraculous architecture of DNA has waited for thousands of years to be understood by humans and be used for the benefit of the world. Further studies on DNA might open new opportunities to help researchers in solving technologically challenging problems.

Acknowledgment: This article was produced at MERGEOUS [5], an online article and project development service for authors and publishers dedicated to the advancement of technologies in the merging realms of science and religion.

Halil I. Demir is a postdoctoral scholar in the area of Informatics, and lives in Iowa.

References

[1] ENIAC, Image Credit: Wikimedia, http://upload.wikimedia.org/wikipedia/commons/4/4e/Eniac.jpg

[2] IBM Roadrunner, Image Credit: Wikimedia,

http://upload.wikimedia.org/wikipedia/commons/c/c7/Roadrunner_supercomputer_HiRes.jpg

[3] Leonard M. Adleman (1994-11-11). “Molecular Computation of Solutions to Combinatorial Problems.” Science, 266 (11): 1021–1024.

[4] Miller, W (et al). 2008. “Sequencing the nuclear genome of the extinct woolly mammoth”, November, Nature.

[5] Mergeous, http://www.mergeous.com

How about quantum computers? Quantum computers make use of a quantum mechanical phenomenon, so-called quantum superposition (being in different states simultaneously). Classically, voltage across a circuit element can be either positive or negative when measured by a voltmeter, but not simultaneously negative and positive. Could it somehow be possible to be in both states simultaneously?

Quantum superposition

For electrical circuits, the answer is obviously no. In microscopic scales of single atoms, or photons (i.e., single quantized packets that constitutes the light beam), however, the answer is yes. Consider an optical component, for instance, that splits an incoming light beam into two beams of equal intensity. In optics, such a device is called a 50/50-beam splitter. You can ask what happens when a single photon is sent to such a beam splitter. Since a single photon cannot be split in this simple experiment, you might expect that it would either be transmitted or reflected with equal probability . Experiments, however, show that this is not actually true in the single photon level. The single photon is indeed simultaneously reflected and transmitted.

Once microscopic quantum superposition is brought into our macroscopic world, we can imagine many interesting phenomena. Simultaneously occupying many different places and being dead and alive at the same time are only two of them. Of course such technology, especially applied to humans is highly science fiction, given current experimental and theoretical challenges. Nevertheless, quantum superposition has a strikingly interesting similarity with the spiritual states already achievable by saints, such that they can be available in more than one place at a given time or become dead and alive, in the sense that they live both in the future and in the past.

It is not known exactly why quantum superposition exists, but what we know is that it is a necessary ingredient for our complex universe to perform its vital functions in a finite amount of time. Quantum superposition principle reflects the great wisdom and power of the Omnipotent. Similar to the single photon example above, with this principle, God gives the underlying particles of the universe an immense power to achieve many tasks simultaneously. Otherwise, regarding the finite age of the universe (about 15 billion years), our physical universe and the events taking place all around us would not come into existence. The Quantum superposition principle has also inspired researchers to build unprecedentedly fast computers to solve the problems that are intractable with any classical computing method. In this article, we introduce this new strategy to computing.

Quantum computing with superposition

Having provided some background about the quantum superposition, we ask the question “How could we exploit quantum superposition for fast computing?” Below we will give a glimpse of that power. Consider a three-bit register. It can only store one out of eight numbers in the set, {0, 1, 2, 3, 4, 5, 6, 7}, in a given moment of time. For example, number 5 is stored in a three-bit register as “101.” Now suppose that these three bits are replaced by their quantum cousins, so-called qubits (short for quantum bit). You can imagine, for example, a quantum register consisting of three rubidium (Rb) atoms. These individual atoms can be prepared in the 0 and 1 logical states simultaneously by shining a laser beam for a certain amount of time. Then it is possible for three atoms combined to be prepared in a superposition of eight numbers, which is impossible classically. In other words all those eight guys physically exist in the same room, although it doesn’t allow more than one guy to fit classically. If we want to make operations on all of these numbers, we don’t need to perform serially; instead, we can achieve that in only one computational step on a single hardware. Thus, quantum superposition leads to a massive parallelism, which renders the computational complexity (i.e., a measure of how efficiently a given problem could be solved) highly reduced for various difficult problems in computer science.

For example, let’s consider RSA, a well-known algorithm (i.e., a set of instructions to solve a problem on a computer) for secure communication that was invented by Rivest, Shamir, and Adelman, hence the name, in 1977 at MIT. It is widely used in electronic commerce protocols. The details of RSA are out of scope in this article (See the FAQ section of the RSA Laboratories’ web site in Ref. [1] for a brief introduction to RSA). Here, we only want to mention its vulnerability to quantum computers if they were to exist. The security of the RSA cryptosystem relies on the difficulty of factoring large numbers, which is intractable with classical computers. Factorization for small numbers, say 15, is quite simple. When the number of digits increase up to a few 100s, for example, enormous computational resource is required. RSA Laboratories publish the RSA challenge numbers (see Ref. [2] for the list of challenge numbers and the prize) on their web site to test the security of their algorithm at various key lengths. The largest integer, RSA-640, which has 193 decimal digits (640 bits), was factorized recently by F. Bahr, et al. The next challenge number in turn is RSA-704, and the prize is $30,000. Imagine factorizing a 1000-digit number. You would probably be a considerably rich person in just a few minutes, if you had a moderate quantum computer and the RSA Laboratories kept feeding you with new challenge numbers, because the factorization of such a large number with current computational resources takes forever, perhaps even more than the estimated age of the universe. Of course, the RSA Laboratories will not let you be very rich, by simply quitting posting new challenge numbers. They would be interested in your quantum computer, though.

How does the quantum computer crack the world’s most secure cryptosystems with little effort? One can construct new algorithms for quantum computers based on above described principle of superposition. These algorithms can take the outcome of previous calculations and input them as a superposition to the next stage of the instructions, which results in a highly efficient form of computing (please consult Ref [3] to have for a simple explanation of quantum superposition for fast computation). In 1994, Peter Shor from AT&T’s Bell Labs in New Jersey just did that. He developed the world’s first quantum algorithm, which efficiently performs factorization. In 1996, Lov Grover also at Bell Labs invented the unstructured database (i.e., a disordered list such as a list of city names not in alphabetical order) search algorithm for quantum computers, so-called Grover’s algorithm.

Suppose that there is a basket with ten balls in it. You are now asked to find a specific one with your eyes closed, say red. It is known, however, beforehand that there is only one red ball in the basket. All you, or your smart digital friend, can do is just pick one randomly and see if it is red. If you are lucky enough, the first ball you pick might be red. In the worst case, however, you will be successful at your last choice. So, classically you have to repeat the process on average at half times the number of balls. If you made a quantum friend rather than classical, however, your life would be smoother. You would be able to find and manage your stuff easily, no matter how messy you are. Quantum computers speed up such unsorted database searches quadratically. You can find, say your favorite socks, in a number of trials that is about the square root of the total number of your stuff. You may think that you don’t have that much stuff. But consider identifying a specific element in a considerably large pool of unsorted data. As the number of elements in the set increases, it quickly becomes intractable to find what exactly you are looking for. In that case the significance of quadratic boost cannot be denied.

Motivated by the above mentioned factorization and unsorted database search algorithms, the power of quantum computing has inspired great attention, since their invention, among many disciplines including physicists, computer scientists, mathematicians, engineers, and material scientists.

Quantum computer today

Despite promising developments in theory, progress in the physical realization of quantum circuits, algorithms, and communication systems have been extremely challenging to date. There are many approaches for quantum information processing. Major model physical systems include nuclear spins, ions, neutral atoms, solid state nanostructures, superconductors, and optical circuits. In optics, for example, the qubit can be represented by the polarization (i.e., direction of oscillation of electric field) state of a single photon. So that the instructions described by the algorithm could be implemented by manipulating the polarization states of single photons. Unfortunately, all the models for quantum computing have their own drawbacks besides their advantages.

Given the trends, nobody knows whether or not a sufficiently scalable (i.e., large enough to harvest its potential power) quantum computer would be available in the decades to come. Nonetheless, D-Wave Systems, Inc., The Quantum Computing Company, was eager enough to unveil the “world’s first commercially viable quantum computer” (see Figure 1, and Ref [4] for the story.). D-Waves’ 16-qubit quantum computer makes use of superconducting element niobium, which operates at an extremely low temperature. It can search for molecular structures that match a target molecule, create a complicated seating plan, and fill in Sudoku puzzles. Although the device is very slow compared to an inexpensive PC, D-Wave intends to develop a 1000-qubit quantum computer.* The goal is to scale the quantum computer to about 10 thousand qubits to solve the most challenging problems outright, which are simply intractable with classical computers. The researchers, however, are not very optimistic. Prof. Lloyd of Massachusetts of Institute of Technology, a pioneering scientist in superconducting approach for quantum computing that underlies the D-Wave’s quantum computer, says “It’s too good to be true.”

Once quantum computers of reasonable power are built, the world will be unimaginably exciting and perhaps scary too. When the first commercial computer, Universal Atomic Computer I (UNIVAC I) (see Figure 2), was shipped to the United States Air Force in 1952, nobody was indeed aware of what this fat guy would lead to in our social, economical, political, and psychological life. Its descendants, however, are now inevitable parts of our lives. They are helping us in many aspects of daily life. Controlling machines, sending electronic mail, scheduling our plane tickets, communicating with our best friends, playing games, making our payments are only some of them.

In this article we only sketched the quantum superposition principle as an important ingredient for quantum computation. This is certainly not the whole story. “Entanglement” [6], for example, is another complementary resource for quantum computing and communications, as well as quantum mechanics to test its foundations.

Contrary to its classical counterparts, the power of quantum computers indeed comes directly from our granted capability of tailoring and mimicking the amazing design hidden in the microscopic world of atoms, photons or other quantum particles. Quantum computers sooner or later will bring the most science-fiction into reality. They will play a significant role especially in the development of ultra-intelligent machines and robots superior to classical ones, and communication systems whose ultimate security is guarantied by the nature’s architecture which was lay down by God. Quantum computers will reveal to us the deepest secrets of our Creator embedded in our universe, which cannot be explored using conventional computers. That day, the future will only be lacked by our limited imagination.

Acknowledgment

This article was produced in MERGEOUS [7], an online article and project development service for authors and publishers dedicated to the advancement of technologies in the merging realm of science and religion.

Omer D. Ikramoglu is a freelance writer in optics and quantum physics.

References

1. RSA Laboratories, http://www.rsa.com/rsalabs/

2. RSA Challenge Numbers, http://www.rsa.com/rsalabs/node.asp?id=2093

3. A short introduction to quantum computation by A. Barenco, A.Ekert, A. Sanpera and C.Machiavello from La Recherche, November 1996. http://cam.qubit.org/articles/intros/comp.php

4. J. R. Minkel, “First “Commercial” Quantum Computer Solves Sudoku Puzzles”, Scientific American, Feb 13 (2007).

5. UNIVAC I, http://en.wikipedia.org/wiki/UNIVAC_I

6. S. Candaroglu, “Quantum Entanglement: Illusion or Reality?” Fountain, Issue 61 (January-February 2008).

7. http://www.mergeous.com/

* At the time of writing D-Wave Systems had only 16-qubit quantum chip and they were intending to develop a 1000-qubit quantum computer by the end of 2008. Although they couldn’t meet their goal, they now have a design of a 128-qubit most powerful ever quantum chip which awaits the tests (see http://www.dwavesys.com for up to date information).