This paper proposes a new irrigation system using fuzzy logic technique by mapping the knowledge and experience of a traditional farmer. Fuzzy logic control, which is similar to the human way of thinking, has emerged as the most active tool in automatic control. The purpose of fuzzy logic controller is to automatically achieve and maintain some desired state of a system and process by monitoring system variables as well as taking appropriate control action.

The aim of this work is to develop an intelligent control using fuzzy logic approach for irrigation of agricultural field, which simulates or emulates the human being’s intelligence. The status of any agricultural field, in terms of evapotranspiration and error may be assumed as input parameters and the decision is made to determine the amount of water required for the area to be irrigated, well in advance. This leads to use effective utilization of various resources like water and electricity and hence becomes a cost effective system for the expected yield.

INTRODUCTION

In the past few years, there has been an increasing interest in the application of the fuzzy set theory to many control problems. For many complex control systems, the construction of an ordinary model is difficult due to nonlinear and time varying nature of the system. Fuzzy Control has been applied in traditional control systems, which yields promising results, It is applied for the processes, which yields promising results, it is applied for the processes, which are too complex to be analyzed by conventional techniques or where the available information is uncertain. In fact, fuzzy logic controller (FLC) is easier to prototype, simple to describe and verify, can be maintained and also extended with grater accuracy in less time. These advantages make fuzzy logic technology to be used for irrigation system also.

NEED FOR MODERN IRRIGATION SYSTEM

Water and electricity should be optimally utilized in an agricultural like India. The development in the filed of science and technology should be appropriately used in the field of agriculture for better yields. Irrigation has traditionally resulted in excessive labour and nonuniformity in water application across the filed. Hence, an automatic irrigation system is required to reduce the labour cost and to give uniformity in water application across the field.

PHYSIOLOGICAL PROCESSING

In the irrigation system, plant take-varying quantities of water at different stages of plant growth. Unless adequate and timely supply of water is assured, the physiological activities taking place within the plant are bound to be adversely affected, thereby resulting in reduced yield of crop. The amount of water to be irrigated in an irrigation schedule depends upon the evapotranspiration(ET) from adjacent soil and from plant leaves at that specified time. The rate of ET of a given crop is influenced by its growth stages, environmental conditions and crop management. The consumptive use or evapotranspiration for a given crop at a given place may vary through out the day, through out the month and through out the crop period. Values of daily consumptive use or monthly consumptive use are determined for a given crop and at a given place. It also varies from crop to crop. There are several elimatological factors, which will influence and decide the rate of evaporation. Some of the important factors of elimate influencing the evaporation are radiation, temperature, humidity and wind speed. In this work, the input variables chosen for the system are evapotranspiration and rate of change of evapotranspiration called as error

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We propose a new method for strengthening the security of information through a combination of signal processing, cryptography and steganography. Cryptography provides the security by concealing the contents and steganography provides security by concealing existence of information being communicated. Signal processing adds additional security by compressing and transforming the information. The proposed method, viz. Steganography Based Information Protection Method (SBIPM), consists of scanning, coding, encryption, reshaping, cover processing and embedding steps.

Scanning, coding, encryption steps make the information unintelligible sothat one cannot extract plain message. Embedding make the message invisible so that one cannot detect it. Reshaping spreads the message so that embedded message can be detected from distorted steganos by authorized receivers. Cover processing makes detection of embedded message more difficult since the distortion is either due to noise addition or due to message embedding. Simulation and steganlysis results show the method provides high security and the information is safe from various attacks.

INTRODUCTION

Now a days, various modes of communication like LAN, WAN and INTERNET are widely used for communicating information from one place to another around the globe. Such communication networks are open which any one can access easily. They are regularly monitored and an intercepted. In steganography, a message is embedded in a cover media in an invisible manner so that one could not suspect about its existence.

In this paper we present a substitution based information protection method where we combine cryptographic, steganographic and signal processing concepts together for achieving security. The method is known as Steganography Based Information Protection method. In this method we substitute the information bit in randomly selected pixels at random places within LSB region.

STEGANOGRAPHY TECHNIQUE

Steganography is the art and science of communicating in a way which hides the the existence of the secret message communication. It aims to hide information /covered writing. Information to be protected is hidden in another data known as cover or carrier. Data containing hidden message are called as Steganos or Stegos. Steganos look like cover data and it is difficult to differentiate between them. Steganography based communication over easily accessible platforms to prevent leakage of information.

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My voting goes mobile ….

Newton did see an apple falling down.. Of what?? For what?? Why??

It is falling…

We do visualize the drop of success in the Election System of India…

Of what?? For what?? Why?? It is so …

Yes it is the patriotistic, socialistic, humanistic, economistic, thinking of us that lead to visualize & analyze the election system (voting process) and project a viable solution of voting through (Mobile) CELLULAR PHONES guarded by Finger print sensors by the new mobile language of SMS. YAHOOO! Crazy … might be … but it isn’t.

Motion is the basic physical property of anything in this hi-tech info era. Time is a precious thing and correct information is the most precious thing. Merging all these together we look in for easier, cost effective, time managing way of casting my vote thro’ my Cell Phone with a finger print sensor.

Why looking in for a finger print sensor in a Mobile phone?? Of course it is the security that we add to all the confidential communications which goes natural and highly secured. A finger print guarded cell phone can afford a lot in the forthcoming technocrats like M-commerce, M-governance, M-voting, and M-security.

Thus, by our concept of Finger print guarded cell phones can serve better in all corners of communication especially for voting process.

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Fuzzy logic is an outcome of merging the techniques of traditional rule based expert system, set theory and control theory, which is essentially based on mathematical models of the controlled process.

The concept of this paper is to control the illumination of a light source by using the fuzzy logic.

Here the error and error rate are input parameters and the voltage is the output. Theses are all normalized in the form of intersecting triangular membership functions with seven linguals each. The rules are formed by the knowledge.

At a time four rules are fired, and the maximum of their output is taken. The value is defuzzified by the method named center of the area or center of gravity.

The defuzzified voltage is denormalised and made as a pulse to be given to a power control circuit using phase control method.

The pulse produced proportionally to give the power to the circuit, the illumination is again sensed and given to the controlling unit

1. INTRODUCTION

1.1. An Overview of the Paper : -

In some situations in industries and also for some research processes, constant illumination is to be maintained. For example , to study the photosynthetic process constant illumination is to be maintained throughout twenty four hours. But the sun, the natural source for photosynthetic process, does not give light for twenty four hours. so we have to use an artificial supplementary light source.

Depending upon the changes in the illumination intensity of the sun light, due to reasons beyond control, the artificial light source acts as an automatically adjusted supplementary light source acts with the natural sun light, the resultant light intensity is maintained constant.

While there are so many techniques available, to have an automatic controller, the system adopts the fuzzy logic technique, the emerging technique being adopted for industry appliances, to control the artificial light source.

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Fuzzy Logic has played a pivotal part in this age of rapid technological development .In this paper we have elaborated on the automation process used in a washing machine. This paper has focused on the two subsystems of the washing machine namely the sensor mechanism and the controller unit. It also discuss on the use of singletons for fuzzy sets. This paper also highlights the use of a fuzzy controller to give the correct wash time. The use of fuzzy controller has the advantage of managing time, increasing equipment effiency and diagnosing malfunctions.

1.INTRODUCTION:

Classical feedback control theory has been the basis for the development of simple automatic control systems .It is easily comprehensible principle and relatively simple implementation has been the main reason for its wide applications in industry. Such fixed-gain feedback controllers are insufficient, however to compensate for parameter variations in the plant as well as to adapt to changes in the environment. The need to overcome such problems and to have a controller well-tuned not just for one operating point for a whole range of operating points has motivated the idea of an adaptive controller.

HOW DOES FUZZY LOGIC WORK?

In order to illustrate some basic concepts in fuzzy logic consider a simplified example of a thermostat controlling a heater fan illustrated in fig.1.The room temperature detected through a sensor is input to a controller which outputs a control force to adjust the heater fan speed.

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Controlling a substation by a fuzzy controller speeds up response time diminishes up the possibility of risks normally related to human operations. The automation of electric substation is an area under constant development Our research has focused on, the Selection of the magnitude to be controlled, Definition and implementation of the soft techniques, Elaboration of a programming tool to execute the control operations. it is possible to control the desired status while supervising some important magnitudes as the voltage, power factor, and harmonic distortion, as well as the present status. The status of the circuit breakers can be control by using a knowledge base that relates some of the operation magnitudes, mixing status variables with time variables and fuzzy sets .The number of necessary magnitudes to a supervise and to control a substation can be very high in the present research work, many magnitudes were not included .To avoid the extensive number of required rules nevertheless , controlling a substation by a fuzzy controller has the advantage that it can speed up the response time and diminish the possibility of risks normally related to human operations.

AI AUTOMATES SUBSTATION CONTROL

Introduction

Electric substations are facilities in charge of the voltage transformation to provide safe and effective energy to the consumers. This energy supply has to be carried out with sufficient quality and should guarantee the equipment security. The associated cost to ensure quality and security during the supply in substations is high. Automatic mechanisms are generally used in greater or lesser scale, although they mostly operate according to an individual control and protection logic related with the equipment itself and not with the topology of the whole substation in a given moment.

The automation of electric substation is an area under constant development. Nevertheless, the control of a substation is a very complex task due to the great number of related problems and, therefore, the decision variables that can influence the substation performance. Under such circumstances, the use of learning control systems can be very useful.

Many papers on applications of artificial intelligence (AI) techniques to power system have been published in the last year. The difficulties associated with the application of this technique include:

1. Selection of the magnitude to be controlled

2. Definition and implementation of the soft techniques

3. Elaboration of a programming tool to execute the control operations

4. Selection, acquisition and installation of the measurement and control equipment

5. Interface with this equipment and

6. Applications of the controlling technique in existent substations.

Our research has focused on the first three points, and the interest of the present work is to expose the obtained result and to present them for discussion. The objective is to show that it is possible to control the status of circuit breakers (CB) in a substation making use of a knowledge, mixing status variables with time variables and fuzzy sets.

Even when all the magnitudes to be controlled cannot be included in the analysis (mostly due to the great number of measurements and status variables of the substation and, therefore, to the rules that would be required by the controller), it is possible to control the desired status while supervising some important magnitudes as the voltage, power factor, and harmonic distortion, as well as the present status.

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Download Full Article 96facility-layout-design-using-genitic-algorithm

Any major industry’s success depends invariably on the location of its bases, production centers and warehouses. Thus locating the sites before establishing these units is done by facility location and planning unit of the industry. For greater profits the facilities should be located at an optimum distance from the market , raw material procurement sites utilities like water , sand etc. For these problems involving layout a number of algorithms are in use like ALDEP,CORELAP, CRAFT etc. But since the location of facilities have become very complex due to greater constraints these days a determined search of a good algorithm begins. This can be achieved by using GENETIC ALGORITHMS. This type of evolutionary algorithms have made the computational effort fast and accurate.

1 Introduction

Material handling and layout related costs have been estimated to be about 20%-50% of the total operating expenses in manufacturing. To stay competitive in the market these high overhead costs have to be reduced considerably. One way of doing this is to develop an efficient facility layout. The secondary benefit of doing so is in reducing the large Work-In-Process inventory and justifying the costly long-term investment. Developing an efficient layout is primarily finding the most efficient arrangement of n facilities in m locations (m >= n).

Traditionally the layout problem has been presented as a Quadratic Assignment problem (QAP). The layout problem can also be termed as one-dimensional or two-dimensional problem corresponding to the single-row or multi-row patterns of layout. It is well known that QAP is NP-complete category due to the combinatorial function involved and cannot be solved for large layout problems. An alternative model for the QAP that consists of absolute values in the objective function and constraints that can be used for continuous formulations instead of discrete. The efficiency of these models however depends upon the efficient integer programming algorithms.

2 Problem Formulation

The facility layout problem has been termed as Quadratic Assignment Problem (QAP) because the objective function is a second-degree polynomial function of the variables, and the constraints are identical to the constraints of the assignment problem. The objective of the QAP is to find the optimal assignment of n facilities to n sites in order to minimize the material handling cost expressed as the product of workflow and the travel distance.

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WiFi …Think of it as an eighteen-wheeler screaming down the pike, carrying the future of computing with it. The driver is friendly. You can stick out your thumb and hitch a ride, or be left in the dust. WIFI, in the broadest sense is a term used for a specific protocol to network your computer to another computer or network.

It allows you to connect to the Internet from your couch at home, a bed in a hotel room or a conference room at work without wires with a speed several times faster than the fastest cable connection. We have attempted to review all the major aspects of wireless networking and the 802.11x protocol corresponding to Wi-Fi .The paper deals with the basic concepts of wireless networking and goes into the in-depth of 802.11x protocol which forms the backbone of the upcoming technology, Wi-Fi. Seamless networking is neither a compromise anymore nor a showpiece of high end business markets. The wave of the future is already sweeping through.

Over the past decade, two trends have been clearly identifiable in the area of personal computing; first, computers have gotten smaller and much more portable. Secondly, the internet has increasingly become a bigger part of the daily routines of many people, especially college students. The combination of these two trends have paved the way for the introduction of a fast and reliable wireless networking infrastructure so that people can use their portable computers without being restrained by cables.

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In many applications of speech processing the noise reveals some specific features. Although the noise could be quite broadband, there are a limited number of dominant frequencies, which carry the most of its energy. This fact implies the usage of narrow-band notch filters that must be adaptive in order to track the changes in noise characteristics. In present contribution, a method and a system for noise suppression are developed. The method uses adaptive notch filters based on second-order Gray-Markel lattice structure. The main advantages of the proposed system are that it has very low computational complexity, is stable in the process of adaptation, and has a short time of adaptation. Under comparable SNR improvement, the proposed method adjusts only 3 coefficients against 250-450 for the conventional adaptive noise cancellation systems. A framework for a speech recognition system that uses the proposed method is suggested.

The noise existence is inevitable in real applications of speech processing. It is well known that the additive noise affects negatively the performance of the speech codecs designed to work with noise-free speech especially codecs based on linear prediction coefficients (LPC). Another application strongly influenced by noise is related to the hands free phones where the background noise reduces the signal to noise ratio (S/N) and the speech intelligibility.

Last but not least, is the problem of speech recognition in a noisy environment. A system that works well in noise-free conditions, usually shows considerable degradation in performance when background noise is present It is clear that a strong demand for reliable noise cancellation methods exists that efficiently separate the noise from speech signal. The endeavors in designing of such systems can be followed some 20 years ago The core of the problem is that in most situations the characteristics of the noise are not known a priori and moreover they may change in time. This implies the use of adaptive systems capable of identifying and tracking the noise characteristics. This is why the application of adaptive filtering for noise cancellation is widely used.

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When reference signal for the FxLMS algorithm is taken from an acoustic sensor convergence can be very slow due to great eigen value spread. Using a non acoustic sensor, Such as a tachometer, cancellation of narrow band noise in the sensed fundamental frequency and harmonically related ones can be achieved very fast, although other periodic noises and underline broad band noise will remain.

Backward prediction errors resulting at the various stages of an adaptive lattice predictor(ALP) represent a a time-domain orthogonalization of the input signal.An ALP structure, with the acoustic reference has input signal, before a FxLMS makes up the FxGAL algorithm. Due to the orthogonalization, FxGAL can be significantly faster compared to FxLMS with reference from a microphone. When compared to FxLMS with tachometer signal, it is not faster but it can cancel every periodic noise, independently of the harmonical relation between them, as well as the underlined broad band noise. Comparative results between FxLMS (with acoustic and nonacoustic reference) and FxGAL are presented.

The Filtered-x Least Mean Square (FxLMS) algorithm(1) is the most widely used in the context of adaptive active control, due to its simplicity as well as robustness.However the main drawback of this algorithm is its relatively slow and signal dependent convergence, which is determined by the eigen value spread of the underlying corelation matrix of the input signal.When working in nonstationary environments such as automobiles, slow convergence is a critical problem, since we would desire to cancel transient noise, which occurs at the vehicle start-ups, stops or gear-Shifts, or with sudden changes of engine speeds or road noise from tyres.

A practical solution to this problem, very commonly used, is to use non acoustic sensors, such as tachometer instead of acoustic ones and artificially generate the signal to use as reference. This way, convergence can be achieved very fast, since it is possible to generate orthogonal references(in-face and quadrate components).On the other hand, it is only possible to cancel narrow band noises in the fundamental frequency sensed by the non acoustic sensor and other harmonically related frequencies, where as every other periodic or broad band noise will remain uncancelled.

In this paper, we introduce an algorithm the Filtered-x Gradient Adaptive Lattice(FxGAL), that aims to improve the convergence of the whole adaptive systems when using acoustic sensors to get the reference signal, at the expense of increased computational complexity.

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