Speech Compression – a novel method

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This paper illustrates a novel method of speech compression and transmission. This method saves the transmission bandwidth required for the speech signal by a considerable amount. This scheme exploits the property of low pass nature of the speech signal. Also this method applies equally well for any signal, which is low pass in nature, speech being the more widely used in Real Time Communication, is highlighted here.

As per this method, the low pass signal (speech) at the transmitter is divided into set of packets, each containing, say N number of samples. Of the N samples per packet, only certain lesser number of samples, say aN alone are transmitted. Here a is less than unity, so compression is achieved. The N samples per packet are subjected to a N-Point DFT. Since low pass signals alone are considered here, the number of significant values in the set of DFT samples is very limited. Transmitting these significant samples alone would suffice for reliable transmission. The number of samples, which are transmitted, is determined by the parameter a.

The parameter a is almost independent of the source of the speech signal. In other methods of speech compression, the specific characteristics of the source such as pitch are important for the algorithm to work.

An exact reverse process at the receiver reconstructs the samples. At the receiver, the N-point IDFT of the received signal is performed after necessary zero padding. Zero padding is necessary because at the transmitter of the N samples only aN samples are transmitted, but at the receiver N samples are again needed to honestly reconstruct the signal.

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DATA SECURITY

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Steganography is the art and science of communicating in such a way that the presence of a message cannot be detected. It belongs to the field of information hiding, which has received considerable attention recently. One may distinguish two general directions in information hiding, determined by the power of an adversary: protection only against the detection of a message by a passive adversary and hiding a message such that not even an active adversary can remove it.

An information-theoretic model for steganography with a passive adversary is proposed. The adversary’s task of distinguishing between an innocent cover message C and a modified message S containing a hidden information is interpreted as a hypothesis testing problem.The security of a steganographic system is quantified in terms of the relative entropy (or discrimination) between PC and PS, which gives quantitative bounds on the detection capability of any adversary. It is shown that secure steganographic schemes exist in this model provided the covertext distribution satisfies certain conditions. A universal stegosystem is presented in this model that needs no knowledge of the covertext distribution.

Steganography’s goal is to conceal the presence of a secret message within an innocuous-looking communication.In other words, steganography consists of hiding a secret hiddentext message within a public covertext to obtain a stegotext in such a way that any observer (except, of cthese, the intended recipient) is unable to distinguish between a covertext with a hiddentext and one without. The model is perhaps best illustrated by Simmons”Prisoners’ Problem”. Alice and Bob are in jail,locked up in separate cells far apart from each other, and wish to devise an escape plan. Theyare allowed to communicate by means of sending authenticated messages via trusted ctheiers,provided they do not deal with escape plans. The ctheiers are agents of the warden Eve (the adversary) and will leak all communication to her. If Eve detects any sign of conspiracy, she will ution, except that it is generated from independently repeated experiments.

This paper views steganography as information hiding with a passive adversary thwart the escape plans by transferring both prisoners to high-security cells from which nobody has ever escaped. Alice and Bob are well aware of these facts, so that before getting locked up, they have shared a few secret codewords that they are now going to exploit for adding a hidden meaning to their seemingly innocent messages. Alice and Bob succeed if they can exchange information allowing them to coordinate their escape and Eve does not become suspicious.

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ARTIFICIAL NEURAL NETWORKS

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In the present paper the proposed system is self organizing map method used to recognize the Devanagiri characters. The som is trained for hundred handwritten devangri characters. The som is trained for hundred hand written devanagari numerals. The Network was tested for different parameters such as o/p nodes, neighborhood size, no of cycle. The process of training was repeated for number of times.

INTRODUCTION:

We begin by considering an Artificial neural n/w architecture in which every node is connected to every node and these connect as are either excitatory or inhibitory or irrelevant.

A single node is insufficient for many patricidal problems and large number of nodes is frequently used. The way nodes are connected determines how computations proceed and constitutes an important early design decision by a neural network developer. A brief discussion of biological neural networks is relevant, prior to examining artificial neural network architectures.

Different parts of the central nervous system are structured differently hence incorrect to claim that a single architecture models all neural processing. The cerebral cortex, where most processing is believed to occur, consists of five to seven layers of neurons with each layer supplying inputs to the next. However, layer boundaries are not strict and connections that cross layers are known to exit. Feedback pathways are also known to exists, e.g. between (to and fro) the visual context and the lateral genetical nucleus. Each neuron is connected with many, but not all, of the neighboring neurons within the some “veto” neurons that have overwhelming power of neutralizing the effects of a large number of excitatory inputs to a neuron. Some amount of indirect self-excitation also occurs – one node’s activation excites its neighbor, which excites the first again. In the following sub sections, we discuss artificial neural network architectures, some of which derive inspiration from biological neural networks.

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MOLETRONICS

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As a scientific pursuit, the search for a viable successor to silicon computer technology has garnered considerable curiosity in the last decade. The latest idea, and one of the most intriguing, is known as molecular computers, or moletronics, in which single molecules serve as switches, “quantum wires” a few atoms thick serve as wiring, and the hardware is synthesized chemically from the bottom up.

The central thesis of moletronics is that almost any chemically stable structure that is not specifically disallowed by the laws of physics can in fact be built. The possibility of building things atom by atom was first introduced by Richard Feynman in 1959.

An “assembler”, which is little more than a submicroscopic robotic arm can be built and be controlled. We can use it to secure and position compounds in order to direct the precise location at which chemical reactions occur. This general approach allows the construction of large, atomically precise objects by initiating a sequence of controlled chemical reactions. In order for this to function as we wish, each assembler requires a process for receiving and executing the instruction set that will dictate its actions. In time, molecular machines might even have onboard, high speed RAM and slower but more permanent storage. They would have communications capability and power supply. Moletronics is expected to touch almost every aspect of our lives, right down to the water we drink and the air we breathe. Experimental work has already resulted in the production of molecular tweezers, a carbon nanotube transistor, and logic gates. Theoretical work is progressing as well. James M. Tour of Rice University is working on the construction of a molecular computer. Researchers at Zyvex have proposed an Exponential Assembly Process that might improve the creation of assemblers and products, before they are even simulated in the lab. We have even seen researchers create an artificial muscle using nanotubes, which may have medical applications in the nearer term.

Teramac computer has the capacity to perform 1012 operations in one seconds but it has 220,000 hardware defects and still has performed some tasks 100 times faster than single-processor .The defect-tolerant computer architecture and its implications for moletronics is the latest in this technology. So the very fact that this machine worked suggested that we ought to take some time and learn about it.

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AI for speech Recognition

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When you dial the telephone number of a big company, you are likely to hear the sonorous voice of a cultured lady who responds to your call with great courtesy saying “welcome to company X. Please give me the extension number you want” .You pronounce the extension number, your name, and the name of the person you want to contact. If the called person accepts the call, the connection is given quickly. This is artificial intelligence where an automatic call-handling system is used without employing any telephone operator.

AI is the study of the abilities for computers to perform tasks, which currently are better done by humans. AI has an interdisciplinary field where computer science intersects with philosophy, psychology, engineering and other fields. Humans make decisions based upon experience and intention. The essence of AI in the integration of computer to mimic this learning process is known as Artificial Intelligence Integration

Artificial intelligence (AI) involves two basic ideas. First, it involves studying the thought processes of human beings. Second, it deals with representing those processes via machines (like computers, robots, etc).AI is behaviour of a machine, which, if performed by a human being, would be called intelligence. It makes machines smarter and more useful, and is less expensive than natural intelligence.

Natural language processing (NLP) refers to artificial intelligence methods of communicating with a computer in a natural language like English. The main objective of a NLP program is to understand input and initiate action.

The input words are scanned and matched against internally stored known words. Identification of a keyword causes some action to be taken. In this way, one can communicate with the computer in one’s language. No special commands or computer language are required. There is no need to enter programs in a special language for creating software.

VoiceXML takes speech recognition even further.Instead of talking to your computer, you’re essentially talking to a web site, and you’re doing this over the phone.OK, you say, well, what exactly is speech recognition? Simply put, it is the process of converting spoken input to text. Speech recognition is thus sometimes referred to as speech-to-text.

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ATM

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Nowadays, most us are surrounded by powerful computer systems with graphics oriented input and output.

These computers include the entire spectrum of PCs, through professional workstations upto super-computers. As the performance of computers has increased, so too has the demand for communication between all systems for exchanging data, or between central servers and the associated host computer system.

The replacement of copper with fiber and the advancement sin digital communication and encoding are at the heart of several developments that will change the communication infrastructure. The former development has provided us with huge amount of transmission bandwidth. While the latter has made the transmission of all information including voice and video through a packet switched network possible.

With continuously work sharing over large distances, including international communication, the systems must be interconnected via wide area networks with increasing demands for higher bit rates.

For the first time, a single communications technology meets LAN and WAN requirements and handles a wide variety of current and emerging applications. ATM is the first technology to provide a common format for bursts of high speed data and the ebb and flow of the typical voice phone call. Seamless ATM networks provide desktop-to-desktop multimedia networking over single technology, high bandwidth, low latency network, removing the boundary between LAN WAN.

ATM is simply a Data Link Layer protocol. It is asynchronous in the sense that the recurrence of the cells containing information from an individual user is not necessarily periodic. It is the technology of choice for evolving B-ISDN (Board Integrated Services Digital Network), for next generation LANs and WANs. ATM supports transmission speeds of 155Mbits / sec. In the future. Photonic approaches have made the advent of ATM switches feasible, and an evolution towards an all packetized, unified, broadband telecommunications and data communication world based on ATM is taking place.

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Blue Eyes

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Imagine yourself in a world where humans interact with computers. You are sitting in front of your personal computer that can listen, talk, or even scream aloud. It has the ability to gather information about you and interact with you through special techniques like facial recognition, speech recognition, etc. It can even understand your emotions at the touch of the mouse. It verifies your identity, feels your presents, and starts interacting with you .You ask the computer to dial to your friend at his office. It realizes the urgency of the situation through the mouse, dials your friend at his office, and establishes a connection.

Human cognition depends primarily on the ability to perceive, interpret, and integrate audio-visuals and sensoring information. Adding extraordinary perceptual abilities to computers would enable computers to work together with human beings as intimate partners. Researchers are attempting to add more capabilities to computers that will allow them to interact like humans, recognize human presents, talk, listen, or even guess their feelings.

The BLUE EYES technology aims at creating computational machines that have perceptual and sensory ability like those of human beings. It uses non-obtrusige sensing method, employing most modern video cameras and microphones to identifies the users actions through the use of imparted sensory abilities . The machine can understand what a user wants, where he is looking at, and even realize his physical or emotional states.

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Brain Computer Interface

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The proliferation of computer use in today’s networked society is creating some complex side effects in the application of the age-old greed, jealousy, and revenge. Criminals are becoming much more sophisticated in committing crimes. Computers are being encountered in almost every type of criminal activity. Gangs use computers to clone mobile telephones and to re-encode credit cards. Drug dealers use computers to store their transaction ledgers. Child pornography distributors use the Internet to peddle and trade their wares. Fraud schemes have been advertised on the Internet. Counterfeiters and forgers use computers to make passable copies of paper currency or counterfeit cashiers checks, and to create realistic looking false identification. In addition, information stored in computers has become the target of criminal activity. Information such as social security and credit card numbers, intellectual property, proprietary information, contract information, classified documents, etc., have been targeted. Further, the threat of malicious destruction of software, employee sabotage, identity theft, blackmail, sexual harassment, and commercial and government espionage is on the rise. Personnel problems are manifesting themselves in the automated environment with inappropriate or unauthorized use complaints resulting in lawsuits against employers as well as loss of proprietary information costing millions of dollars. All of this has led to an explosion in the number and complexity of computers and computer systems encountered in the course of criminal or internal investigations and the subsequent seizure of computer systems and stored electronic communications.

Computer evidence has become a ‘fact of life’ for essentially all law enforcement agencies and many are just beginning to explore their options in dealing with this new venue. Almost overnight, personal computers have changed the way the world does business. They have also changed the world’s view of evidence because computers are used more and more as tools in the commission of ‘traditional’ crimes. Evidence relative to embezzlement, theft, extortion and even murder has been discovered on personal computers. This new technology twist in crime patterns has brought computer evidence to the forefront in law enforcement circles.

WHAT IS COMPUTER FORENSICS?

Computer forensics is simply the application of disciplined investigative techniques in the automated environment and the search, discovery, and analysis of potential evidence. It is the method used to investigate and analyze data maintained on or retrieved from electronic data storage media for the purposes of presentation in a court of law, civil or administrative proceeding. Evidence may be sought in a wide range of computer crime or misuse cases.

Computer forensics is rapidly becoming a science recognized on a par with other forensic sciences by the legal and law enforcement communities. As this trend continues, it will become even more important to handle and examine computer evidence properly. Not every department or organization has the resources to have trained computer forensic specialists on staff.

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Computer memory based on the protein bacterio-rhodopsin

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Since the dawn of time, man has tried to record important events and techniques for everyday life. At first, it was sufficient to paint on the family cave wall how one hunted. Then came the people who invented spoken languages and the need arose to record what one was saying without hearing it firsthand. Therefore, years later, earlier scholars invented writing to convey what was being said. Pictures gave way to letters which represented spoken sounds. Eventually clay tablets gave way to parchment, which gave way to paper. Paper was, and still is, the main way people convey information. However, in the mid twentieth century computers began to come into general use . . .

Computers have gone through their own evolution in storage media. In the forties, fifties, and sixties, everyone who took a computer course used punched cards to give the computer information and store data. In 1956, researchers at IBM developed the first disk storage system. This was called RAMAC (Random Access Method of Accounting and Control)

Since the days of punch cards, computer manufacturers have strived to squeeze more data into smaller spaces. That mission has produced both competing and complementary data storage technology including electronic circuits, magnetic media like hard disks and tape, and optical media such as compact disks.

Today, companies constantly push the limits of these technologies to improve their speed, reliability, and throughput — all while reducing cost. The fastest and most expensive storage technology today is based on electronic storage in a circuit such as a solid state “disk drive” or flash RAM. This technology is getting faster and is able to store more information thanks to improved circuit manufacturing techniques that shrink the sizes of the chip features. Plans are underway for putting up to a gigabyte of data onto a single chip.

Magnetic storage technologies used for most computer hard disks are the most common and provide the best value for fast access to a large storage space. At the low end, disk drives cost as little as 25 cents per megabyte and provide access time to data in ten milliseconds. Drives can be ganged to improve reliability or throughput in a Redundant Array of Inexpensive Disks (RAID). Magnetic tape is somewhat slower than disk, but it is significantly cheaper per megabyte. At the high end, manufacturers are starting to ship tapes that hold 40 gigabytes of data. These can be arrayed together into a Redundant Array of Inexpensive Tapes (RAIT), if the throughput needs to be increased beyond the capability of one drive.

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DYNAMIC VIRTUAL PRIVATE NETWORK

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Based on internet technology, intranets are becoming an essential part of corporate information systems today. However, internets were not originally designed with businesses in mind. It lacks the technology required for secure business transactions and communications. A challenge therefore arises for businesses with intranet, i.e. how to establish and maintain trust in an environment which was originally designed for open access to information. More specifically, a way has to be found to secure an intranet without impinging on its inherent benefits of flexibility, interoperability and ease of use.

Unlike traditional VPNs that offer limited or inflexible security, a dynamic VPN provide both high levels of security and, equally important, the flexibility to accommodate dynamically changing groups of users and information needs. Our dynamic VPN can provide this flexibility based on a unique agent-based architecture as well as other features.

Because information can now be made available in such a flexible and fine-grained fashion, a company’s files, documents or data that had to locked in the past can now be accessed in either whole or in part to carefully selected groups of users in precisely determined ways. As a result, a dynamic VPN is an intranet enabler. It enables an intranet to offer more services and services than it could otherwise, thereby allowing the business to make more use of its information resources.

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