What have the Electrical Engineers to face up to?

Md. Soriful Islam Shorif
Student ID :060105189
Department of Electrical and Electronic Engineering,
Ahsanullah University of Science and Technology.

In our Present world, a global positioning system can identify a car's location. Giant generators that can power entire cities. A new design for an airplane's electrical system. Electrical and electronics engineers work on high-tech projects like these.

Electrical engineers work with electricity in its many forms - from the electrons to the large scale magnetic fields. In addition to designing new products, they construct, operate, and maintain a wide variety of electrical systems and equipment. Some specialize in electronics, others in even more specific areas, like space communications or industrial robotics.

Examples of Such Contributions:

• Invent better MRI scanners, allowing doctors to see even more clearly inside a patient’s body
• Create special effects for the movies
• Design cell phones that work more reliably and have more features
• Develop artificial retinas for the blind
• Work on satellite communications systems that connect people around the world

Electrical engineers design new and better electronics. They also test equipment and solve problems. A project starts by deciding what the new electronics will do. Then, the engineer designs the circuits and other parts of the electronics. Engineers might draw their designs using computers. Afterward, the engineers test their designs and make them better. Many projects don't work at first. The engineers have to figure out why and then fix them.

Work environment:

Electrical engineers usually work 48-hour weeks, but can work longer hours on projects with pressing deadlines or in emergency situations. They often work on teams with other engineers and scientists and can find jobs in industry, government, universities, or in consulting.

**Electrical engineers have good job prospects. Jobs for electrical engineers are expected to grow about as fast as the average for all occupations through 2014. There will be a need for more electronic devices like giant electric power generators or wireless phone transmitters.

**The starting salary for an electrical engineers:

B.S. Degree: $51,888

M.S. Degree:$64,416

Ph.D. :$ 80,206

So,Now it’s the time to think about Electrical Engineering to meet the challenge of Avant-garde modern Technical Global world.

[** source:Internet]

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Great News!

AUST Wins 1st Prize in IEEE

Participants of Bangladesh section along with Mr. Jahangir Alam Majumder, Assistant Professor, AUST are in the IEEE Region 10 Students Congress-2008.

IEEE Region 10 Students Congress was held at SSN College of Engineering, Chennai, India from 28 January to 30 January 2008. Students from about fifteen countries of Region 10 attended the congress. Under the IEEE Bangladesh section, IEEE Students Branch of Ahsanullah University of Science and Technology (AUST) and Bangladesh University of Engineering and Technology (BUET) attended the congress. One of the events of the congress was students’ project presentation by different section of different countries. Bangladesh section stood first in the competition. Md. Rizwan Ahmed, student of 4th Year 2nd Semester, Department of Electrical and Electronic Engineering, AUST, Sajid Muhaimin Chowdhury and Anika Sharin, Students of BUET attended the congress under the guidance of Mr. Jahangir Alam Majumder, Assistant Professor, AUST.
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Keyboard versus Mouse: Which one is faster to use

Md. Adnan Quaium

Lecturer
Department of Electrical and Electronic Engineering
Ahsanullah University of Science and Technology
adnan.quaium@gmail.com
www.maq.spyw.com

Who doesn’t know what is a Keyboard and what is a mouse? I guess it is a silly question especially in today’s world where Personal Computers (PC) are like parts of the life. They are the two main input devices of a PC. But if I ask among them which one has a faster functionality? Well, I guess no answer! I doubt, how many people think in this way. Actually people don’t bother about the speed rather than comfort. If any one is comfort with mouse it is very difficult to sooth the use of keyboard. Actually both input devices need some training to get used to. I found such people who can’t even control the mouse pointer!

The rise of “Mouse”

Though Stanford Research Institute invented the mouse in 1963, with the release of the Apple Macintosh in 1984 mice became the part of all the Apple PCs. At that time Apple was using GUI (Graphical User Interface) Macintosh OS (Operating System). GUI was more users friendly than a CLI (Command Line Interface), which attracted more users. Even a non-technical person knowing no computer programming can easily handle the PC smoothly, just by clicking on the various icons. As a result mice got wide popularity at that time which made it another input device besides keyboard for a PC. Thus the story of the second input device was begun.

B: Introduction to CKIT- 06A

Which one is handy?

Experienced mouse users are effectively capable of moving the pointer from one side of the screen to the other side to click on a tiny button within a fraction of a second. Besides moving and aiming the pointer, they know how to use the two buttons and the scroll wheel at the right moment simultaneously. Advanced mouse users sometimes use mouse-gesture enabled applications to perform even more functions with the mouse. Experienced keyboard users are able to reach high key rates using all ten fingers. Besides high-speed data entry, they also use the CTRL and ALT keys to navigate through applications.

But persons who have reached the highest levels in using both devices are rare to find. Mouse-wizards usually type with two or three fingers, while keyboard enthusiast loose time navigating by his two hands. The problem is that we have only two hands, which seems not enough! Efficient and perfect use of both devices requires three hands: two for the keyboard and on for the mouse. Depending on the type of work done mostly frequently, people become either mouse-addicted or keyboard-bound. But not the wizard of both gadgets.

The Debate

Bruce Tognazzini (a.k.a.Tog) is a well-known user-interface expert with the Nielsen Norman Group, the "dream team" firm specializing in human-computer interaction and was Apple employee. Once he wrote in his website that while continuing a $50 million of Research on the Apple Human Interface, his team discovered two pertinent facts:

• Test subjects consistently report that keyboarding is faster than mousing.
• The stopwatch consistently proves mousing is faster than keyboarding.

According to Tognazzini, cursoring around required a higher level of mental planning to organize the interaction, which apparently obscures the perception of the passage of time-think of being deeply engaged in something and being surprised when user look at a clock whereas the use of the mouse was done at a lower mechanical level that left the mind free for higher things, such as complaining about the mouse. One common complaint is that moving hand from keyboard to mouse and back takes time and interrupts typing. This is true, but it doesn't take as much time as we think. Especially if user is using a keyboard without a numeric keypad, the mouse can be close by. With or without a keypad, eventually we get to the point where we don't need to look for the mouse. Our hand always leaves it in the same general place and automatically goes there, often in preparation for a mouse operation while the other hand is still typing.

But some opposes Tognazzini’s idea. To them typing and navigate with keyboard is much more faster even in a GUI PC. Because in this case user don’t wasting the time for switch his hand between mouse and keyboard. This facility adds keyboard shortcuts, which makes life easier for the geeks. According to those geeks any task we perform often enough to learn the keyboard shortcut by heart is a faster process for using the keyboard, otherwise using the mouse is faster. This means that when one begin using a new command frequently, one has to go through a period of slower performance in order to learn the keyboard shortcut, after which he/she should be faster.

Last Words

For a novice PC user mice are faster but for a hunt-and-peck typist keyboard is obviously the first choice. But what will happen if a user uses both devices? I know most of the people will not believe, but there are some persons who can type in one hand and use mouse in other hand. Despite of their one handed typing their speed is almost 60 word-per-minute to 70 word-per-minute! Are they achieving the highest performance from a PC? Don’t know the exact answer. But it is sure that they are above the ultimate battle between keyboard and mouse, which they left for the general PC users.

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89S51 Microcontroller Based System Design using CKIT-06A

Golam Mostafa
Associate Professor, AUST,
Tel: 7161846, Email: mostafagb@yahoo.com

A: Introduction to 89S51 Microcontroller

A single chip of 40-pin dip package (Fig-1) containing (i) Boolean Processor (ii) 4K Flash to store Program Codes, (iii) 128 Byte RAM, (iv) 2 Timers/Counters, (v) 2 Hardware Interrupts, (vi) Full-duplex Serial IO, (vii) 26 Individual Programmable IO Lines, (viii) Program Code Security Bit and (ix) In System Programming Interface (ISP). The 89S51 MCU provides a very cost effective single chip solution to many of the system designs like Digital Taximeter, Digital Weighing Machine and the similar. The readers are referred to ‘MicroTalk-8051/User Technical Reference Manual/By: Golam Mostafa’ for the detailed application notes of the 89S51 microcontroller. The ISP interface of the 89S51 allows a user to program it (reading, erasing, writing and security bit set) without removing it from the holding instrument and using a very simple PC-based driver and a communication link (Fig-2).

B: Introduction to CKIT- 06A

The CKIT (Fig-3a and 3b) is a very low cost MCU learning/development system and is particularly built for the students and the amateurs, who cannot easily afford to procure the costly development systems like MicroTalk-8051 (Fig-4) and a conventional ROM programmer.

Thanks to the Atmel Co. for the development and release of their ‘S-Series’ of CISC (89S51, 89S52, 89S8252) and RISC (S2313, S8515) microcontrollers, which inspired the author to develop the CKIT. These MCU have hardware ports called ‘In System Programming Port’ or simply ISP Port. The ISP port allows a user to write binary codes into the EEPROM of the MCU using only a 3-core cable and a programming driver.

Figure-2 refers to the hardware aspect of the ISP port of the MCU. The DOS-based Software Driver (P89S51.EXE), DOS-based 8051 Assembler (ASM51), InteHex-to-BINary Converter, Example Programs, Data Conversion Algorithms and Example System Designs (Digital Taximeter, Digital Weighing Machine and Remote Controlled Regulation System) could be found in the User Technical Reference Manual that accompanies the CKIT trainer. The source codes for the software driver could be obtained from the author under some moderate conditions.

The users are informed that there exits some instability within the functioning of the ‘Programming Driver’. It has been observed that the programmer does not always become successful in writing the codes/data into the EEPROM in one attempt. It requires erasing the chip for the second and third times and then writing the codes into the EEPROM. Some of us may be inspired to write a GUI-based driver for the CKIT, which would work in the WINDOWS platform.

C: Example System Design using CKIT06A and 89S51 MCU

Procedures:

1. Use telephone hook up wires and build the following circuit on the breadboard and connect them with the MCU as per diagram of Fig-5.

i. 20mS TT (Time Tick) acquisition circuit from the line frequency

ii. Time Display Unit using CC-type 7-Sement Display devices

2. Boot the PC in pure DOS mode and enter in the path: C:\CKITA

3. Connect the CKIT with the PC using the LPT port.

4. Store the program C:\CKITA\CK24HR.BIN in the code memory of the MCU.

5. Execute the program: CK24HR.

6. The 24-Hr Clock should run. If the clock does not work, adjust the time delay of the program.

Design Analysis of the 24-Hr Clock System:

1. See Figure-6 for the Data Structure of 24-Hr Clock

2. The Source Codes for the 24-Hr Clock:

$mod51

; program for 7segment test

$OBJECT(c:\ckita\CK24Hr.obj)

ORG 0000H

DB 02H

DB 00H

DB 10H

ORG 0010H

L1: MOV SP, #70H
MOV PSW, #00H

MOV 54H, #00H ; Hour
MOV 53H, #00H ; Minutes
MOV 52H, #00H ; Seconds

MOV 40H, #3FH ; 0
MOV 41H, #06H ; 1
MOV 42H, #5BH ; 2
MOV 43H, #4FH ; 3
MOV 44H, #66H ; 4
MOV 45H, #6DH ; 5
MOV 46H, #7DH ; 6
MOV 47H, #07H ; 7
MOV 48H, #7FH ; 8
MOV 49H, #6FH ; 9 CC-code table at upper RAM of MCU

MOV IE, #00H ; all interrupts are disabled
MOV TMOD, #06H; ; Time Integration Tick (for 1sec)
MOV TH0, #0CEH;
MOV TL0, #0CEH
CLR TF0
SETB TR0 ; Timer-0 is put into run mode

HERE:

JBC TF0, TIME_UPDATE
LJMP CCX7S ; 1-sec has not yet elapsed

TIME_UPDATE:

MOV A, 52H
ADD A, #01H
DA A
CJNE A, #60H, ADJ1
MOV 52H, #00H
MOV A, 53H
ADD A, #01H
DA A
CJNE A, #60H, ADJ2
MOV 53H, #00H
MOV A, 54H
ADD A, #01H
DA A
CJNE A, #24H, ADJ3
MOV 54H, #00H
LJMP BCD2CC

ADJ1:

MOV 52H, A
LJMP BCD2CC

ADJ2:

MOV 53H, A
LJMP BCD2CC

ADJ3:

MOV 54H, A

BCD2CC:

MOV R0, #54H ; R0 points at BCD Table
MOV R1, #3FH ; R1 points at CA Table
MOV R2, #03H ; Number of BCD bytes to convert

LSR1:

MOV A, @R0 ; A=00 ; getting 1st BCD
RR A
RR A
RR A
RR A
ANL A, #0FH ; A =00 ; to get cc code
ADD A, #40H ; A= 80
MOV 03H, R1 ; R1=R3=3F ; temporary saved
MOV R1, A ; R1 = 40
MOV A, @R1 ; A = C0
MOV R1, 03H ; R1 = R3 = 3F
MOV @R1, A ; (3F) = C0H
MOV A, @R0 ; A = 00
ANL A, #0FH
ADD A, #40H ; A = 40
MOV 03H, R1 ; R1=R3=3F
MOV R1, A ; R1 = 40
MOV A, @R1 ; A = C0
MOV R1, 03H ; R1=R3 = 3F
DEC R1 ; R1=3E
MOV @R1, A ; (3EH) = C0
DJNZ R2, LFW
LJMP FRWX

LFW:

DEC R0
DEC R1
LJMP LSR1

FRWX:

MOV A, 3EH ; placing points
ORL A, #80H
MOV 3EH, A
MOV A, 3CH
ORL A, #80H
MOV 3CH, A

CCX7S:

MOV P0, 3FH
MOV P2, #3EH ; DP0 0011 1110
LCALL TDELAY
MOV P0, 3EH
MOV P2, #3DH ; DP1 0011 1101
LCALL TDELAY
MOV P0, 3DH
MOV P2, #3BH ; DP2 0011 1011
LCALL TDELAY
MOV P0, 3CH
MOV P2, #37H ; DP3 0011 0111
LCALL TDELAY
MOV P0, 3BH
MOV P2, #2FH ; DP4 0010 1111
LCALL TDELAY
MOV P0, 3AH
MOV P2, #1FH ; DP5 0001 1111
LCALL TDELAY
LJMP HERE

TDELAY:

MOV R6, #20H

HERE2:

MOV R7, #20H

HERE1:

DJNZ R7, HERE1
DJNZ R6, HERE2
RET

END

Figure-1

Figure-2

Figure-3
Figure-4 and Figure-5

Figure-6

Figure-7

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Challenges in 3G Mobile Communication

Mohammad Mahfujur Rashid (Ferdous)
Assistant Professor
Department of Electrical and Electronic Engineering, AUST
[ A PowerPoint presentation ]
Click here to view the presentation in web browser.
Click here to view in PowerPoint.
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Nonlinear effect in Power Electronics

Md. Minhaz Akram
Lecturer, EEE, AUST
Email: eminhaz@gmail.com

In many applications of power electronics, an inductor may carry a high current at a high frequency. The capacitors are also stressed where they usually operate at high frequency with current surges passing through them periodically. These factors have made power electronics an exciting and challenging field in which the scope of the applications is growing at a fast pace. Unfortunately, the widespread use of power electronics is now one of the sources of the increasing electrical pollutions (a form of harmonics or electromagnetic noises) [1]. These devices draw distorted and often fluctuating current that can disturb not only other utilities indirectly connected to the polluting device, but also the device itself. They also generate high-frequency conducted and radiated noise due to the sharp edges of the waveform characteristics of the switching power processors employed in them. The miniaturization of power converters by higher switching frequencies and high density packaging increases the importance of noise problems.

Chaos in Power Electronics Circuits

CHAOS is largely unpredictable long-term evolution occurring in deterministic, nonlinear dynamical system because of sensitivity to initial conditions. Power electronics circuits are rich in nonlinear dynamics. Their operation is characterized by the cyclic switching of circuit topologies, which gives rise to a variety of chaotic behavior.

Sources of Unwanted Nonlinearity

There are several unavoidable sources of unwanted nonlinearity in practical power electronics circuits [3]:

1. The semiconductor switching devices have intrinsically nonlinear DC characteristics: BJTs, MSOFETs, IGBTs, thyristors, diodes.

2. They also have nonlinear capacitances, and most suffer from minority carrier charge storage.

3. Nonlinear inductances abound: transformers, chokes, ferroresonant controllers, magnetic amplifiers and transconductors, and saturable snubber inductors.

4. The control circuits usually involve nonlinear components: comparators, pulse-width modulators (PWMs), multipliers, phase-locked loops (PLLs), monostables (autonomous timers) and digital controllers.

Since power converters are suffered tremendous disturbance. To fully quantify the converter performance, effects of these disturbances must be reflected in the system dynamics.

To design a system we have to make mathematical modeling with adequate parameters. The following topic provides backgrounds on the deterministic power electronic converter models, random noise in power electronics, and the evolution of stochastic differential equations.

The basic operation of any power electronic circuit involves toggling among a set of piecewise linear or nonlinear circuits. Each circuit has its own mathematical model relating the system dynamics. The differential equations that describe the converter operation can be written as:

x^.(t)=fi(x,u) (Eq………..1)

where x denotes the system states which usually are inductor currents and capacitor voltages, u(t) denotes the input vector which consists of voltage or current sources and i represents the status of switching devices. Typically, there are two modes of operation in a switching power converter, continuous and discontinuous conduction modes, indicated by the inductor current. In continuous conduction mode where the inductor current is always greater than zero, there are two sets of differential equations: one set describes the circuit operation during the switch on interval (i =0 ) and the other set describes the switch off interval (i =1).

Recently, nonlinear phenomena in power electronic circuits such as sub-harmonics, bifurcations, and chaos, have received wide attention in power electronic communities.

The concept of chaos in deterministic power electronics were introduced by Deane and Hamill where a set of ordinary differential equations has an alarming property of introducing a noise-like behavior which is essentially unquantifiable and unpredictable.

The discrete modeling technique has been used in which a discrete-time formulation of the switched-mode operation does not involve discontinuities associated to control actions and results in smooth functions that describe the system. The work on chaos has been further extended. Tse et al. determined the condition of period doubling bifurcation, which is the route to chaos, by evaluating the Jacobian of the iterative map around the fixed point. Di Bernado and Vasca reported various sampling schemes of discrete maps to identify bifurcations and chaos.

Noises in Power Electronic Converters

As the demand for better functionality, reliability and performance of power converter increases, design engineers need to account for existing disturbances in power electronic circuitry such as parasitic effects, measurement and sensor inaccuracies, electromagnetic interference (EMI), harmonics, and ambient temperature effects. These disturbances have been considered causes of random noises in power converters.

Particularly hard-switching converters such as those of PWM types generate wide-band spectra that give rise to conducted EMI interference.

Since power electronic components are designed to operate in a certain range of temperature, ambient temperature change can influence operating characteristics of the devices. For example, leakage current in a BJT is doubled for every 12⁰ C which results in higher off-state loss. The threshold voltage of a MOSFET can vary over the range of –2 to –100mV / ^oC. In addition, electrolytic capacitors were reported with high possibility of failure under high ambient temperatures. Mazumder et al. pointed out the shortcoming of the averaged model in predicting fast-scale instabilities. They also demonstrated the impact of parasitic parameters as a cause of instability. Parasitic become very important and analysis based on a nominal model may not be accurate. The parasitic effects were included to the system dynamics as a stochastic recursion relation. The random nature of harmonics injected into the network by distorting loads was reported by Cavallini et al.. They proposed a procedure to evaluate the resultant probability density and cumulative functions of the sum of harmonic currents at buses of electrical networks.

Evolution of Stochastic Partial Differential Equations in Power Electronics:

Random effects of existing disturbances in power electronic converters may essentially affect dynamics of the converters. Even if the system is initially at a stable equilibrium point, random noise may force the system out of the domain of attraction of the corresponding equilibrium point. In such a case, the system will eventually leave the stability boundary with probability one [16]. Taking random noise into account, the deterministic concept of stability no longer applies. A concept of first passage time may be used to quantify the robustness of the dynamical systems under influence of random perturbations. Historically, the random effects are modeled as additive Gaussian distributed white noise. If the strength of the noise is small, the resulting diffusion process can be solved asymptotically. Cohen and Lewis first obtained such a solution by a ray method. Later Freidlin and Wentzell approximated the lowest eigenvalue of the system by means of an asymptotic solution of a diffusion process where the expected value of the first passage time was shown as exponential growth. Ludwig obtained more rigorous results of the expected passage time. They converted differential equations into an integral equation where the integral equation can be solved asymptotically by applying standard methods. Matkowsky and Schuss developed another method to solve the same problem. They used an asymptotic expansion of a small parameter of the probability distribution of points on the boundary of the domain, where 10 trajectories of the perturbed system first exit. From the derived probability distribution, the expected exit times can be found.

REFERENCES

[1] Paul S Addison. Fractals and Chaos. An illustrated course. IOP

Publishing Limited. 1997.

[2] Robert C. Hilborn. Chaos and Nonlinear Dynamics. An Introduction for

Scientists and Engineers. Oxford University Press. 1994.

[3] D. C. Hamill, S. Banerjee and G. C. Verghese, “Chapter 1:

Introduction,” in Nonlinear Phenomena in Power Electronics, edited by

S. Banerjee and G. C. Verghese, New York, IEEE Press, 2001.

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Artificial Intelligence: A.I.

Md. Adnan Quaium
Lecturer
Department of Electrical and electronic Engineering
adnan.quaium@gmail.com
www.maq.spyw.com

Have you seen the sci-fi movie A.I. Or I, Robot? Both movie's stories are based on Artificial Intelligence. First one is directed by famous Steven Spielberg where David, a highly-advanced artificial intelligent robotic boy, hopes to become a real boy so that he can win back the affection of his human mother who abandoned him. Like Pinocchio, he goes on a long journey hoping to find his Blue Fairy, who can make his dreams come true. The latter movie's (which was actually written by Isaac Asimov) plot is in the year 2035. When everybody in the world relies on a huge system of robots except Chicago homicide detective Del Spooner, who thinks Robots are not so much harmless. While investing the abnormal death of a renowned robot scientist, Spooner discovered Sonny, a unique artificial intelligent robot, who is just more than a robot! Both movies highlights the advanced intelligent machines which in some cases can react and feel like the humans. For a long time in the technical world, there are two questions; one is - Is it possible to implement AI? and another is - How far will the AI be advanced? For the rapid advancement of electronics technology, in the last several years the first question has undoubtedly become obsolete. Second question still remains and till now no one can exactly answer it. May be some day the above discussed movies are considered as drama or action rather than Science fiction!

The NOT-SO-DETAILS Definition:

So the basic question should be What is Artificial Intelligence? For this we have to know what is intelligence. In a word Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees of intelligence occur in people and many animals. There is no solid definition of intelligence that doesn't depend on relating to human intelligence. The problem is that we cannot yet characterize in general what kinds of computational procedures we want to call intelligent. We understand some of the mechanisms of intelligence and not others. And AI is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. Actually it is a combination of computer science, physiology and philosophy. AI is a broad topic, consisting of different fields, from machine vision to expert systems. The element that the fields of AI have in common is the creation of machines that can "think".

AI is somewhat different to IQ. IQ is based on the rates at which intelligence develops in children. It is the ratio of the age at which a child normally makes a certain score to the child's age. The scale is extended to adults in a suitable way. IQ correlates well with various measures of success or failure in life, but making computers that can score high on IQ tests would be weakly correlated with their usefulness.

The Short History:

The beginnings of AI reach back before electronics,to philosophers and mathematicians such as George Boole and others theorizing on principles that were used as the foundation of AI Logic. AI really began to intrigue researchers with the invention of the computer in 1943. The technology was finally available, or so it seemed, to simulate intelligent behavior.

In 1961, A.L. Samuel Developed a program which learned to play checkers at Masters level. J.A. Robinson introduced resolution as an inference method in logic in 1965. In the same year work on DENDRAL was begun at Stanford University. DENDRAL is an expert system which discovers molecule structure given only information of the constituents of the compound and mass spectra data. DENDRAL was the first knowledge-based expert system to be developed. After three years, in 1968 work on MACSYMA was initiated at MIT. MACSYMA is a large interactive program which solves numerous types of mathematical problems. Written in LISP, MACSYMA was a continuation of earlier work on SIN, an indefinite integration solving problem.

Over the next four decades, despite many stumbling blocks, AI has grown from a dozen researchers, to thousands of engineers and specialists; and from programs capable of playing checkers, to systems designed to diagnose disease.

The Turing Test:

Perhaps the best way to gauge the intelligence of a machine is British computer scientist Alan Turing's test. He stated that a computer would deserves to be called intelligent if it could deceive a human into believing that it was human. It was developed in 1950, allows subjects to interact with a person or a computer in another room by speaking into a microphone or typing questions on to a computer. When they receive an answer by voice synthesizer or by text on their computers screens, subjects must determine whether they have been communicating with a computer or a human. If they think that they have been interacting with a person or they are unable to decide, then the computer has passed the Turing Test, proving that the machine is actually capable of higher level thought processes similar to those of a human brain.

But is Turing Test flawless? A machined can be programmed to produce responses that appear to be intelligent without the awareness required for thought. According to the philosopher John Searle in his famous Chinese Room Argument, an English-speaking person is able to to respond to questions in Chinese by referring to source material that allows him to break the code without comprehending the underlying meaning of the symbols. The person can behave correctly without the higher level thought requires to process the meaning. Therefore, a computer could pass the Turing test if it were programmed to generate behavioral output but the Turing Test itself would be flawed. This test is not enough to prove that machine can think. Whatever the fact is, no superior test to Turing Test is invented yet.

Methods Used to Create Intelligence:

In the quest to create intelligent machines, the field of Artificial Intelligence has split into several different approaches. These rivaling theories have lead researchers in one of two basic approaches: bottom-up and top-down. Bottom-up theorists believe the best way to achieve artificial intelligence is to build electronic replicas of the human brain's complex network of neurons, while the top-down approach attempts to mimic the brain's behavior with computer programs.

(i) Neural Networks and Parallel Computation:

The human brain is made up of a web of billions of cells called neurons, and understanding its complexities is seen as one of the last frontiers in scientific research. It is the aim of AI researchers who prefer this bottom-up approach to construct electronic circuits that act as neurons do in the human brain. Although much of the working of the brain remains unknown, the complex network of neurons is what gives humans intelligent characteristics. By itself, a neuron is not intelligent, but when grouped together, neurons are able to pass electrical signals through networks.

A century earlier the true / false nature of binary numbers was theorized in 1854 by George Boole in his postulates concerning the Laws of Thought. Boole's principles make up what is known as Boolean algebra, the collection of logic concerning AND, OR, NOT operands. For example according to the Laws of thought the statement: (for this example consider all apples are red)

• Apples are red-- is True
• Apples are red AND oranges are purple-- is False
• Apples are red OR oranges are purple-- is True
• Apples are red AND oranges are NOT purple-- is also True

Boole also assumed that the human mind works according to these laws, it performs logical operations that could be reasoned. Ninety years later, Claude Shannon applied Boole's principles in circuits, the blueprint for electronic computers. Boole's contribution to the future of computing and Artificial Intelligence was immeasurable, and his logic is the basis of neural networks.

(ii) Top Down Approaches (Expert System):

Because of the large storage capacity of computers, expert systems had the potential to interpret statistics, in order to formulate rules. An expert system works much like a detective solves a mystery. Using the information, and logic or rules, an expert system can solve the problem. For example if the expert system was designed to distinguish birds it may have the logic trees like the figure. Charts like these represent the logic of expert systems. Using a similar set of rules, experts can have a variety of applications. With improved interfacing, computers may begin to find a larger place in society.

(iii) Chess:

AI-based game playing programs combine intelligence with entertainment. On game with strong AI ties is chess. World-champion chess playing programs can see ahead twenty plus moves in advance for each move they make. In addition, the programs have an ability to get progressively better over time because of the ability to learn. Chess programs do not play chess as humans do. In three minutes, Deep Thought (a master program) considers 126 million moves, while human chess-master on average considers less than 2 moves.

(iv) Frames:

On method that many programs use to represent knowledge are frames. Pioneered by Marvin Minsky, frame theory revolves around packets of information. For example, say the situation was a birthday party. A computer could call on its birthday frame, and use the information contained in the frame, to apply to the situation. The computer knows that there is usually cake and presents because of the information contained in the knowledge frame. Frames can also overlap, or contain sub-frames. The use of frames also allows the computer to add knowledge. Although not embraced by all AI developers, frames have been used in comprehension programs.

Specialized Languages for A.I.:

AI research has led to many advances in programming languages including the first list processing language by Allen Newell et al., Lisp dialects, Planner, Actors, the Scientific Community Metaphor, production systems, and rule-based languages.

GOFAI research is often done in programming languages such as Prolog or Lisp. Matlab and Lush include many specialist probabilistic libraries for Bayesian systems. AI research often emphasizes rapid development and prototyping, using such interpreted languages to empower rapid command-line testing and experimentation. Real-time systems are however likely to require dedicated optimized software.

Notable examples include the languages LISP and Prolog, which were invented for AI research but are now used for non-AI tasks. Hacker culture first sprang from AI laboratories, in particular the MIT AI Lab, home at various times to such luminaries as John McCarthy, Marvin Minsky, Seymour Papert (who developed Logo there) and Terry Winograd (who abandoned AI after developing SHRDLU).

A.I. in Myth and Fiction:

In science fiction AI is often portrayed as an upcoming power trying to overthrow human authority, usually in the form of futuristic humanoid robots. Best known examples include the films The Terminator and The Matrix, as well as TV shows such as the re-imagined Battlestar Galactica series. Another common theme is the suspicion and hatred by humanity for AIs and the AIs attempt to gain human acceptance. Films include Bicentennial Man, Artificial Intelligence: A.I. and The Iron Giant. This concept is also explored in the Uncanny Valley hypothesis.

Isaac Asimov wrote stories where engineers understood these potential problems and designed their robots accordingly. Positive examples of AIs include Robby from Forbidden Planet, R2D2, C3PO and Data (Star Trek). A negative example, I, Robot is based on Asimov's stories in which an AI positronic brain develops own radical understanding of the "three laws of robotics." The inevitability of the integration of AI into human society is also argued by some science/futurist writers such as Kevin Warwick and Hans Moravec and the Animation Ghost in the Shell.

ASIMO & AIBO:

Perhaps the most celebrated two non-biological intelligent machines in the today's world are ASIMO and AIBO. ASIMO is a humanoid robot created by Honda Motor Company. ASIMO is an acronym for Advanced Step in Innovative MObility. Honda's official statements indicate that the robot's name is not a reference to science fiction writer and inventor of the Three Laws of Robotics, Isaac Asimov. In Japanese, the name is pronounced ashimo and, not coincidentally, means legs also. With 2000's ASIMO model Honda added many features that enable ASIMO to interact better with humans. These features include- Recognition of moving objects, Recognition of postures and gestures, Environment recognition, Distinguishing sounds and Facial recognition. Utilizing networks such as the Internet, ASIMO can provide information and function better for various commercial applications, such as reception. It can integrate with user's network system and by accessing information via the Internet, ASIMO can, for example, become a provider of news and weather updates.

AIBO - Artificial Intelligence roBOt, is one of several types of robotic pets designed and manufactured by Sony. Able to walk, see its environment via camera and recognize spoken commands, they are considered to be autonomous robots, since they are able to learn and mature based on external stimuli from their owner or environment, or from other AIBOs. AIBOware, is the title given to the software the AIBO runs on its pink Memory Stick. The Life AIBOware allows the robot to be raised from pup to fully grown adult while going through various stages of development as its owner interacts with it. The Explorer AIBOware allows the owner to interact with a fully mature robot able to understand 100 voice commands. Without the AIBOware, the AIBO will run in what is called Clinic Mode and can only perform basic actions. The AIBO has seen use as an inexpensive platform for artificial intelligence research, because it integrates a computer, vision system, and articulators in a package vastly cheaper than conventional research robots. The autonomous soccer competition has a "RoboCup Four-Legged Robot Soccer League" in which numerous institutions from around the world participate. Competitors program a team of AIBO robots to play games of autonomous robot soccer against other competing teams.

Last Words:

Last words about AI is there is no last word. Some people considering it as a threatening to the human kind. The philosopher John Searle thinks that the idea of a non-biological machine being intelligent is incoherent. He proposes the Chinese room argument in this regard. The philosopher Hubert Dreyfus says that AI is impossible. The computer scientist Joseph Weizenbaum says the idea is obscene, anti-human and immoral. Various people have said that since artificial intelligence hasn't reached human level by now, it must be impossible. Just think what will happen if your PC or Laptop or other equipments become more intelligent than you. It raises the common but unsolved question- Then who'll dominate whom?

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