Oriental Journal of Computer Science and Technology An International research journal of Computer Science and Technology

For enhancing the high color depth and to provide higher resolution for LCD signal driver. This paper proposes a complementary differential amplifier with offset voltage cancellation technique. In order to improve the offset cancellation ability the complementary differential pairs are separated into main and auxiliary trans conductance amplifiers. This achieves Rail-to-Rail output swing. In the proposed method offset cancellation is achieved by dividing offset cancellation and driving phases with the help of three switches. With this proposed architecture the offset voltage is reduced from 8.9 mV to 0.3 mV, which is a considerable amount of reduction. It is also observed that CMRR and Slew rate are not affected with the proposed technique.

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AIDE is an idea in advance that only ensures safe navigation, but also lets you link up to the universe. AIDE projects a transparent image into the driver’s field of view which appears to roam out of doors of the windscreen. The icon is centered in the space and then the track remains in focus while the driver looks at the information presented by AIDE. This, combined with touchless gesture control, means that the driver is able to use AIDE without ever holding their eyes off the road. When you synchronize the device with your  Android handset or iPhone and by  placing  the AIDE onto your car's dashboard. With this we can start communicating with the  vehicle and other people without ever removing your eyes off the road. It is designed to give  relevant information at a glance and the power to respond to that information with voice and theme song-less gesture controls i.e.  embedded with IR camera and internal microphone. It grows better  as it possess  an accelerometer, an e-compass and  an ambient brightness sensing element. The device, which is to be designed to run on Android 5.0   has transparent HUD display of 5.1-inch and has Wi-Fi and Bluetooth for connectivity. For the touch less controls, in terms of navigating it employs an IR camera , it also includes a GLOAN-ASS, digital compass, accelerometer and ambient brightness sensor. It can also warn us when  car needs to be served next and when  oil needs replacement. This paper present a novel and useful interface for the future automated vehicles and disabled people.

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Wireless Sensor Networks (WSNs) consists of low power, low-cost smart devices which have limited computing resources. A lot of real world applications have been already deployed and many of them will be based on wireless sensor networks. These applications include geographical monitoring, medical care, manufacturing, transportation, military operations, environmental monitoring, industrial machine monitoring, and surveillance systems. In this paper, we present a snapshot of the wireless sensor network architecture, security requirements and obstacles of sensor security.

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Various attributes within a dataset relate to each other and with the class attribute. The relationship between the different attributes with class attribute may improve the classification accuracy. The paper introduces CCSA algorithm that performs the clustering that is cascaded by classification based on association. The Clustering process generates a group of various instances within the dataset. These clustered instances are classified by using the association. This paper uses the Apriori association to generate the rules for classification. The technique is analyzed by using the soil data set and various other online available datasets using WEKA. The simulation result using the WEKA shows that reduced rules with the improved classification accuracy as compared to the existing association with classification algorithms. 

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Security is the important criteria relevant to information in transit as well as in storage. Steganography is the technique of hiding secret message in a cover medium in such a way that only the sender and the intended recipient knows the existence of communication. DNA due to its immense storage capacity and high randomness is used now in the field of steganography. Audio steganography is concerned with hiding information in a cover (host) audio signal in an imperceptible way. In this paper, various techniques using DNA sequences and audio files for data hiding is discussed for secure data transmission and reception. It also proposes highly secure method to hide the existence of secret message to prevent unauthorized access. The proposed method has three levels. Single level of encryption and two levels of steganography are used. The main objective of this method is that no one could be able to find the existence of secret message.  

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As the propagation of video and image data in digital form has increased, Content Based Image Retrieval (CBIR) has become a prominent research topic. Therefore an important problem that needs to be addressed is fast retrieval of images from large databases. To find images that are perceptually similar to a query image, image retrieval systems attempt to search through a database. CBIR can greatly enhance the accuracy of the information being returned and is an important alternative and complement to traditional text-based image searching. This paper presents an overview on content-based image retrieval.

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Query optimization in fuzzy relational databases aims to come out with a minimal execution cost for the available execution strategies.  Each type of cost is estimated by a cost function. All cost functions together with their parameters and assumptions forms a cost model for the fuzzy query optimizer. The cost function usually takes the size of tables as inputs.  It is possible that exact information is not available where by fuzzy data is assumed. Also estimating the nature of different cost models needs to be examined. A fuzzy cost function is used for this purpose which produces a fuzzy value that represents a soft estimate of the real cost while a traditional crisp cost function, produces a hard crisp estimate.

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Computer Application will optimize solution in dairy industry. Using solution, user has optimized their production in the reducing production cost and unit costs. Computer application/ automation will improve the physical working environment considering the number of monotonous, repetitive tasks to be eliminated or minimize, increasing efficiency in production.Computer application available in the agriculture today, makes it possible to manage a dairy industry on a more detailed level than before. The dairy manager can make more rational decision through acquiring amount of information, the dairy manager has to operate several computers each day and manually transfer data from one unit to another. The paper aims to analyze information feasibility and the application of computer in modern dairy industry, this system as dairy management tools to describe, document and control all processes on dairy production, especially the multi-purpose and multi-agent system application support management of the dairy and provide documentation for entire dairy supply chain members. Customization of IT platforms for use in dairy industry is emerging as a major opportunity for change.

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In a peer to peer system searching a file in each and every node it is very difficult. These days everybody using file sharing, and video streaming. So here while sharing or downloading a file there may be loss of data in the file. To avoid all these problems I proposed a concept providing file surveillance to actively search for files by using query performance in structured peer to peer overlay systems. using querying performance in structured overlay peer to peer systems if any node is leaving dynamically data should not loss.

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Classification is used to find out in which group each data instance is related within a given dataset. It is used for classifying data into different classes according to some constrains. Several major kinds of classification algorithms including C4.5, ID3, k-nearest neighbor classifier, Naive Bayes, SVM, and ANN are used for classification. Generally a classification technique follows three approaches Statistical, Machine Learning and Neural Network for classification. While considering these approaches this paper provides an inclusive survey of different classification algorithms and their features and limitations.

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Cloud computing is a type of parallel distributed computing system that has become a frequently used computer application. Increasingly larger scale applications are generating an unprecedented amount of data. However, the increasing gap between computation and I/O capacity on High End Computing machines makes a severe bottleneck for data analysis. Big data is an emerging paradigm applied to data sets whose size or complexity is beyond the ability of commonly used computer software and hardware tools. Such data sets are often from various sources (Variety) yet unstructured such as social media, sensors, scientific applications, surveillance, video and image archives, Internet texts and documents, Internet search indexing, medical records, business transactions and web logs; and are of large size (Volume) with fast data in/out (Velocity). More importantly, big data has to be of high value (Value) and establish trust in it for business decision making (Veracity). To handle the dynamic nature of big data successfully, architectures, networks, management, mining and analysis algorithms should be scalable and extendable to accommodate the varying needs of the applications. In this paper we propose a big data solution through cloud computing by using divide and conquer technique in parallel distribution system.

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Easy and safe people transportation is a big challenge facing the governments any time anywhere. So roads and Traffic control lie at the heart of the modern civilization. [1] (OTS)

The integration of Geographic Information System (GIS) and Global Positioning System (GPS) technologies together can be achieved by a variety of ways and their applications are numerous [1]. Determining the overall transport monitoring (OTM) is essential issue of integration GPS and GIS.

Transport Monitoring System (TMS), which can efficiently monitor and control the vehicles location, speed, traffic congestion and delay, is emerging in many Intelligent Transportation Management Systems (ITMS) [4]. GIS and GPS technology linked with means of wireless communication are essential to the system for determining the vehicle location and speed and from the data collected by GPS receiver and that stored in Databases we can derived a lot of useful helpful information in monitoring and managing transport. It is required to have a technique to handle the huge amount of spatial data entailed in a digital road map and data that received from the GPS belongs to the coordinates and speed, in order to trace the accurate position within a reasonable time. In this paper, we propose a client/server solution, two integrated databases the first for the spatial data processing and the second is textual as an alternative database to store text coordinates of the spatial data to eliminate the processing time, and a cache method to improve the system performance.

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Depression is one of the most common and debilitating diseases worldwide, especially in industrialized countries. Depression is traditionally managed with psychological, pharmacological, or physical interventions alone or in combination forms. However, all of the conventional methods have various limitations, such as medication side effects, frequent relapse, and high economics costs. In addition, a significant portion of the depressive disorders are treatment-refractory that do not respond to the usual medications. These different challenges emphasize the need for effective alternative treatment for depression.

Neurofeedback technique (NFT) is a noninvasive and non-drug treatment through which patients learn to modulate their brain activities using repeated practice to eliminate the disease-specific patterns in electroencephalogram (EEG) of the patient. NFT emphasizes on the correlation between EEG and cognitive and behavioral disorders. There are several clinical protocols for NFT in treatment of Depression. All of these protocols aim to shift the brain activities, EEG waves, from disorder into normal state. Therefore, in developing efficient NFT for depression or any other disorders, determining the EEG based indices which are specifically correlated with different cognitive states is necessary. Several protocols have been developed based on these indices for depressive disorders and some of them are clinically used. Left to the right hemisphere alpha predominance, decreasing Theta/Beta ratio in left prefrontal cortex, decreasing left- or increasing right- hemispheric alpha activity, shifting an asymmetry index toward the right to rebalance activation levels in favor of the left hemisphere are some of the main protocols.  This paper reviews the basic principles of NFT, its procedures and protocols for the treatment of depressive disorders and clinical outcomes.

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Brain computer interface (BCI) is relatively new technology aiming at assisting, augmenting, or repairing human cognitive or sensory-motor functions. Recent advances in bio-signal processing as well as advances in neuro-imaging techniques have boosted BCI development.  The most important barrier in developing BCI technology is currently the lack of a sensor modality that provides safe, accurate and robust access to brain signals. However, recent advances in biosensor technology, signal processing and new insights into association between EEG-based measures and mental states and advances in high resolution EEG measurements have dramatically revolutionized the BCI development.  The present study reviews the basic principles of BCI, recent advances and future directions of the technology.

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Support Vector Machine SVM is one of the most effective Machine Learning Algorithms for data classification, which has a significant area of research. Since the training process of large data sets is very computationally intensive, there is a need to improve its efficiency using high performance computing techniques. Initially, SVM was used for binary classification, but most applications have more than two categories, resulting in multiclass classification. Classifying different categories among large data sets has become one of the most important computing problems. Since the complexity of training of non-linear SVMs has been estimated to be quadratic in the number of training examples, which is unreasonable for data sets with tens of thousands of training examples. In this paper, we developed an efficient parallel algorithm which combines Parallel Binary Class with Parallel Multi Class Support Vector Machines for classification, PMC-PBC-SVM, which means two level parallel algorithm. The main idea of this algorithm is how to divide a set of processors into two subsets, one is responsible for the multi class case and the other is responsible for the binary class case. PMC-PBC-SVM algorithm was implemented using C++ programming language and Message passing Interface, MPI, communication routines. The parallel code was executed on an ALBACORE Linux cluster, and then tested with four data sets with difference sizes, Earthworm, Protein, Mnist, and Mnist8m. The results show that the PMC-PBC-SVM implementation can significantly improve the performance of data classification without loss of accuracy. The results also demonstrated a form of proportionality between the size of the data set and the PMC-PBC-SVM efficiency. The larger the data set is the higher efficiency the PMC-PBC-SVM achieves.

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Day-by-day smartphone network’s structures are improving in an efficient manner; they are becoming ideal users to accessing the any web resources or a service, specifically, Services which are access by Internet. Web services that are used to provide changed kind of services for an app running on smart mobile users suitable and widespread used; still there are some limitations of the current smart phone clients in common manner, like as low processing speed, limited storage capacity, less band-width, latency, and in-adequate memory. This paper gears a platform free architecture for connecting mobile users to the existing Internet based Services. In this architecture includes a cross-platform design of smart mobile users based on client services and a middle ware for acquisitive the communication between mobile users and Internet based Web Services. We have used the architecture for deployed services on cloud platforms, such as “Google App Engine” (GAE) and “Cloud Sim” to enhance the consistency and scalability and reached up to the end-users.

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Time Analytic Processing (RTAP) in this modern world is inducing huge data traffic by everyone knowingly or unknowingly compared to few years back data traffic where only few companies was source of data traffic. This is really a challenge to the technology and needs a solution which can be implemented at the earliest and with an ease. This paper tries to discuss about the solution for handling the Big-Data traffic without downgrading the processing time. However, the analysis of big data can be troublesome because of its heterogeneous nature i.e. Big-data often involves the collection and storage of mixed data based on different patterns or rules. This has made the heterogeneous mixture property of data a very important issue.This paper focuses on applying “Divide and Conquer Technique” to handle the Big-data traffic using parallel processing in Network”

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Directive Access control system provides protected information with storage facility. This information can be shared among other connected or connectionless system. It is designed for the automation of time and attendance of authenticated or unauthenticated employee/visitor using RFID technology. Each Employee has RFID tag which carries his/her personnel recognition information. When these tags pass through the reader mounted at the specific division’s magnetic door, it generates interrogation field, they transmit information back to the Reader, thereby identifying them, attendance is recorded and access gates are opened, so the system monitor the movement of employee and record their real time data in a Time-stamp, which provides real time employee’s record like attendance, authorized and unauthorized entry in division, and visitor’s database with their purpose. The proposed RFID system’s objectives are to make automatic effective and efficient system so the administration time can be effectively reduced.

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Active learning has received considerable attention over the past several years. Often presented or perceived as a radical change from traditional instruction, the topic frequently polarizes faculty. Active learning has attracted strong advocates among faculty looking for alternatives to traditional teaching methods, while skeptical faculty regard active learning as another in a long line of educational fads. This study examines the evidence for the effectiveness of active learning. It defines the common forms of active learning most relevant for engineering faculty and critically examines the core element of each method. It is found that there is broad but uneven support for the core elements of active, collaborative, cooperative and problem-based learning.

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Technical Analysis is widely used by traders for trading decisions in the stock market especially intraday trading. Various technical indicators like the moving averages or momentum indicators assist the traders in decision making. One such trend indicator is the Moving Average Convergence and Divergence (MACD) indicator. This paper analyses the profit or loss generated on application of this indicator on selected five stocks from the Bombay Stock Exchange (BSE). It has been observed after application on a daily basis for over a year that all the decisions based on MACD have generated a profit. Certain precautionary measures have also been suggested for successful implementation of the indicator.

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Always has the potential to improve the quality of agricultural products and production using information technology that requires efficiency and information in all sectors of agriculture. Emerging view of a non-regularity in agriculture, thanks to the World Trade Organization [WTO], to make a great need and urgency to bring in it’s an integral part of decision making by the Indian Farming Community. Information Technology (IT) has a major role to play in all facets of India Agriculture. In addition to facilitating and improving the efficiency of farmers productivity in agriculture and allied activities, bringing the potential of IT about qualitative improvement in the overall quality of life by providing timely and data inputs for decision making. Who work for the welfare of employees Indian farmers such as extension workers, do not have access to the latest hinders their ability to serve the farming community information effective. This manuscript focusses on the opportunity for people living in the e-powering in India, as well as those peoples who work for their welfare. Latest developments changing patterns of IT in rural India that facilitate effective IT penetration information requirements & IT role, the post-WTO necessarily systems environment, with possible bottlenecks in rural India, e-powering solutions are examined.

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A finite state automata is the most important type of graphs ,which is called conceptual graphs, while the expansion of using the graphs in the process of data mining, the use of FSM is still limited because of the difficulty in processing in databases, therefore in order to find methods that make it easier to deal with large groups of machines, as a database, is encourage to  use of this type of representation in this paper of graph mining .  This paper present a method  using vectors of features for find machines matching, which is one task of mining graph data , which are frequently found in a single environment or similar environments, thereby reducing the number of records and increase efficiency of mining tasks.

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Cyclomatic complexity is software metric used in structural testing. The purpose of the paper is to describe the analysis on Cyclomatic complexity with an example. The Cyclomatic complexity is computed using the flow graph of the program: the nodes of the graph correspond to one or more code statement and the edges connect two nodes. Based on the flow graph how to find Cyclomatic complexity is described here.

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Agriculture is different from industry and plays a significant role in the economic development of a nation. India’s prosperity depends upon the agricultural prosperity. There are many kinds of agricultural products produced in India and the marketing of all these farm products generally tends to be a complex process. Agricultural marketing involves many operations and processes through which the food and raw materials move from the cultivated farm to the final consumers. The conventional approach of extension services have not been able to resolve the challenges posed by various factors in Indian Agriculture marketing. The paper at length discusses about the challenges and the opportunities for ICT mediated services for agricultural marketing.

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This paper continues the earlier thought of evolutionary study of sorting problem and sorting algorithms (Root to Fruit (1): An Evolutionary Study of Sorting Problem) [1]and concluded with the chronological list of early pioneers of sorting problem or algorithms. Latter in the study graphical method has been used to present an evolution of sorting problem and sorting algorithm on the time line.

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In wireless sensor-actor networks, the sensors sense the surroundings and transmit the sensed data to the actors. The actor nodes respond collectively to achieve their purpose. Since the actors and sensors have to communicate at all times, a strong network topology has to be established. A failure of an actor may cause the network to be broken into two. The solution can be provided by moving actor node thus restoring connectivity. Current recovery schemes consider only single node failure. This paper overcomes this shortcoming by recovering from multiple node failures through Least-Disruptive topology Repair (LeDiR) algorithm. LeDiR algorithm depends on the local view of each node about its neighbor to find the recovery plan.

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Steganography is the science of hiding the fact in the information which we are sending. The goal of steganography is to embed a secret message inside a piece of unsusceptible information. The result of steganography depends on the secrecy of the cover carrier. After the steganographic carrier is disclosed, the security depends on the robustness of the algorithm and the cryptographic methods used. In order, to achieve secrecy, either the carrier must be made more robust against steganalysis or new and better carriers must be discovered. The main intention behind this paper is to discuss a new steganography technique for indexed images. 

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Camtasia Studio (CS) used to enhance, supplement, or replace a traditional educational curriculum. As computer technology has become more accessible, inexpensive, and powerful, the demand has increased, leading to more frequent use of resources within classroom. This application is a professional quality video production software package designed to capture, edit, interpret and organize moving action of computer screen into a computer video file. It is the ideal piece of software for creating, editing and distributing interactive multimedia video files for any other range of computer applications. The component of Camtasia is adding caption to recorded lectures &power point presentation, visual training materials. Thus by using Camtasiateacher will have an opportunity to create and edit short video snips. Camtasia helps in creating training material or demonstrating a software feature on-line and allows editing newly created video, also to save it in multiple formats. It is one of the desktop recording applications that adapt the work flow by keeping track of on-screen action. It makes the final editing process much easier and quicker. 

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Intrusion Detection System (IDS) serves as an important tool in preventing, detecting and defending against network attack. Due to increasing incidence of cyber-attacks, building an effective hybrid intrusion detection system is essential for prevention of any attack, protecting information system, monitoring networks against attacks or intrusion, and reporting these attacks to the appropriate centre for immediate action. In this paper, a hybrid intrusion detection system, integrating the strengths of the misuse detection system and the anomaly detection system were used to reduce the chances or occurrence of attacks on the network to a minimal level. This system works as an alert device in the event of attacks directed at an entire network and it also helps in reducing the number of false positive as well as false negative alarm.

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Understanding decision making activities in static and dynamic decision tasks are reserving a large area of the field of research. This research focuses on how to support dynamic decision making in real-time environments with interdependent decisions. Tracing decision making efforts in different fields are deployed to identify how models, information streams, values and assumptions constrain in decision making.  The study of DMM is experimented in the laboratories using computer to test the impact of computer support on overcoming cognitive limitations. As a result new rules, methodologies and tools are rising up and the technological base is expanded in complex decision making situation. This research investigates the effect of the change of the environment on dynamic decision making. An experiment is represented to study the effects of the change of the environment on decisions in respond to time and the surrounding environment.

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Creation of natural human sources to communicate with the computer is currently one of the greatest challenges of modern science. The speech input facility is the most user-friendly way, adopted by development of speech recognition based on sophisticated technologies. Scientists began the selection of informative signs, describing the voice signal, afterwards the task of classification of speech signals as a set of informative signs. The development of methods of signal processing in the absence of sufficient models lead to questions about the processes of generation signals using artificial neural networks, As a result; when building a signal processing system, the structure of the network should be selected; according to parameters of the signals and training network using an algorithm to maximize the use of the information contained in the data of the experiment.

This article proposes the Application of wavelet transform for reduction of the value of artificial neural networks for speech recognition tasks this method a present Study a new modification of neural networks a neural network with inverse Wavelet Decomposition of the signal. For example, the speech recognition task, the analysis of the proposed method. The effectiveness of the method is proved by the results of computer simulations.

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Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning.[1]Clustering is one of the most important data mining techniques that partitions data according to some similarity criterion. The problems of clustering categorical data have attracted much attention from the data mining research community recently [2].The original k-means algorithm [3] or known as Lloyd's algorithm, is designed to work primarily on numeric data sets. This prohibits the algorithm from being applied to definite  data clustering, which is an integral part of data mining and has attracted much attention recently In this paper delineates increase to the k-modes algorithm for clustering definite data. By modifying a simple corresponding Variation measure for definite entities, a heuristic approach was developed in [4, 12], which allows the use of the k-modes paradigm to obtain a cluster with strong intra-similarity, and to efficiently cluster large definite data sets. The main aim of this paper is to derive severely the updating formula of the k-modes clustering algorithm with the new Variation measure, and the convergence of the algorithm under the optimization framework.

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Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. A framework to guide a phone business is discussed using data mining tools (decision Tree) to predict future trends and behaviors of their customers, thus, allowing their businesses to make proactive, knowledge-driven decisions. The impact of integrating data mining with acquisition marketing campaign management is also explained.

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In Semantic web, domain model is an abstract image of a small part of the world. It serves to capture the common understanding of the domain to create a basis for clear communication. This paper performs a study clarifying the different domain modeling types to help the individual interested by this topic to gain new insights and gudlines.  In this paper, after a general introduction about the basis of ontologies and its components, a description of the most common domain modeling schema and a comparison between them has given.

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Intensive research has been carried out and is still taking place in the field of detection of counterfeit money. This area of research plays a vital role in the maintenance of consistency in economy and also crime -free society by detecting counterfeit money.

In this paper we have proposed a system for automatic detection of counterfeit notes.  This paper is based on the fact that all notes are printed with unique serial number. Every person who is currently using the note for transaction has to register the serial number of the note in his account along with his unique identity number. This serial number is used for validating the notes and data base transactions.

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Cloud computing is an up-and-coming architecture with strengths and room for improvement. Cloud computing is an extension of grid computing and distributed computing, which is a software concept indeed, it works through variety of technologies such as software technologies, integration, management, and the use of various hardware resources. The progress of cloud computing for information processing creates significant technological opportunities and economic benefits. Many organizations and individuals will use cloud platform as data storage and in the mean times as their publishing environment, i.e. public and private clouds can be combined into a hybrid cloud. Cloud storage is an important part of cloud computing, which is used to achieve the target of storing data in the cloud. In our this research work researcher tries to deal with problem of security of store data in a Cloud Computing provider which would be handle by ensemble cryptography methods.

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Graphene, a sheet of carbon atoms arrayed in a honeycomb pattern, could be a better semiconductor than silicon.Due to many such properties graphene has been under study as a alternative substance used, rather then graphite and silicon in transistors.But the main function of a transistor is to perform the operation of switching, i:e on and off.The problem that arises here is that graphene has no energy band gap and therefore in this paper i review the various possibilities with which a band gap can be induced in graphene and with all the possible alternatives of use of graphene in LSIs.

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There are many applications like military or public emergency have main concern with secure communication. All this applications use ad hoc environments, so secure key management and message distribution is necessary. The best solution to provide the reliable security to these services is the stipulation of a key management protocol. This paper shows the specific challenges towards key management protocols and different approaches for key management. It also shows the multicast communication with OMCT and its limitations. A new approach, called combination of OMCT with DSDV, can be good. It is not required geographical location information for true connection. It provide high packet ratio with less energy consumption and delay.

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Malaria remains one of the world’s most deadly infectious diseases and arguably, the greatest menace to modern society in terms of morbidity and mortality. To choose the right treatment and to ensure a quality of life suitable for a specific patient condition, early and accurate diagnosis of malaria is essential. It reduces disease and prevents deaths. It also contributes to reducing malaria transmission. In recent times, Information Technology (IT) has played a significant role in the task of medical diagnosis. This paper work focused on Fuzzy Expert System for malaria diagnosis. It is simple to use, portable, low cost and makes malaria diagnosis more rapid and accurate. It supports medical practitioners and assists malaria researchers to deal with the vagueness, imprecision and time-consuming found in traditional laboratory diagnosis of malaria, and provide accurate output based on the input data.

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A variety of researches Dealt with the iris identification in different ways and Showed different results. A new system for personal identification based on iris patterns is presented in this paper .We propose to use two activation function wavelet neural network for feature extraction and identification  process after segments the image into 32 blocks with (128*128) dimension. The proposed  method in this paper involves three steps. First reduced  image size using wavelet packet 1-level decomposition , second  feature extraction using two activation  function wavelet neural network and finally identification using trained data and correlation .

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Thehydro cyclone is an important and popular industrial apparatus to separate by centrifugal action disperse solid particles from a liquid suspension fed to it. It has been widely used in industry, particularly in the mineral and chemical processing industry because of its simplicity in design and operation, high capacity, low maintenance and operating cost as well as its small physical size. In general how a hydro cyclone works is included, providing a background to discuss a process and hydro cyclone geometry variables. The CFD technique popularly in process design and predicting equipment performance of hydro cyclone under a wide range of geometric and operating condition by using ANSYS.CFX; it also offers an effective way of design and modeling of hydro cyclone.

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Fingerprint recognition is one of the biometric techniques that are used for identification purpose. A number of recognition methods have been used to perform fingerprint matching. The Straightforward matching between the fingerprint pattern to be identified and many already known patterns would not serve well due to its high sensitivity to errors. This paper presents a combination of pattern based and minutiae based method. Here first core point, delta points and minutiae features are found and based on that matching is to be done. Here poor quality of fingerprint images are also enhanced using wiener low pass filter.

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Automatic real time video monitoring and object detection is indeed a challenge since there are many criteria that should be taken In mind in designing and implementing algorithms for this sake. The criteria that should be considered for example are processing speed, scene illumination variation and dynamic outdoor environment. In this study we propose a fast, flexible and immune against illumination variation approach for moving object detection based on the combination of edge segment based background modeling and background subtraction techniques. The first technique is used for building robust and flexible statistical background model, while the other technique is used for the prime detection of moving object to be compared later withthe flexible background. Thus this combination leads to computational reduction due to the second technique, and then flexible matching and precise detection due to the first technique.

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Computers are changing our language, our habits, our environment and generally our world. Solving mathematics is more interesting when it is carried out via a computer. So also is statistics which can be broadly classified into descriptive and inferential classes. Statistical inference varies when a sample data that is a subject of the population is well used to make statements about a population. This research is focused on the development of a software program to solve problems on hypothesis testing of population mean and population variance. It showed that solving statistical inference is easier, interactive and interesting when it’s carried out in a computerized system.

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Organization are increasingly tuning to data warehouses for decision making.why is it that certain projects fail, while others succed? The aim of this article is to identify the key success factors for data warehouse implimentation, few studies have assessed data warehousing practices in general and critical success factors for implimentation . some have proved guidelines for implimentation but no framework exists which are used to find the success factors. This article provide key success factors for data warehouse implimentation and how best to utilize their limited resource to choose critical succes factors.

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A "mobile ad hoc network" (MANET) is an autonomous system of mobile routers (and associated hosts) connected by wireless links, the union of which forms an arbitrary graph. The routers are free to move randomly and organize themselves arbitrarily; thus, the network's wireless topology may be changed change rapidly and unpredictably. The changing state of the topology makes MANET ideal for emergency and rescue situation.

 Wireless ad-hoc networks will enable emergency services to continuously overview and act upon the actual status of the situation by retrieving and exchanging up-to-date detailed information between the rescue parties. Deployment of high-bandwidth, robust, self-organizing ad-hoc networks will enable quicker response to typical what/where/when questions, than the more vulnerable low-bandwidth communication networks currently in use. This paper addresses two proposal studies for constructing a net emergency system using ad hoc, with perspective, these studies take in consider to minimize the control overhead for route/location discovery by doing selective forwarding where only a few selected nodes in the network do the broadcasting, it is assumed that the mobile nodes can discern their relative positions with respect to other nodes in the range of communication. Using a real urban area being set for the emergency state, NS2 simulator has been used. 

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This paper introduces a well known NP- Complete problem called the Knapsack Problem, presents several algorithms for solving it, and compares their performance. The reason is that it appears in many real domains with practical importance. Although it’s NP-Completeness, many algorithms have been proposed that exhibit impressive behaviour in the average case. This paper introduce A New approach to solve a Knapsack Problem. An overview of the previous research and the most known algorithms for solving it are presented. The paper concludes with a practical situation where the problem arises. 

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Background: The world is at a crucial point in its development of effective strategies on the prevention, care and control of HIV/AIDS at the national and provincial levels. Given the necessary resources and expertise, it may be possible to keep the epidemic at bay in most parts of the World, and to considerably reduce the negative impacts of the disease on individuals and society. Early detection of HIV has the potential to reduce mortality and morbidity. There are many diagnostic technologies and tests to diagnose HIV. However many of these tests are extremely complex and subjective and depend heavily on the experience of the clinician. Aims:This paper made significant contribution to the ongoing worldwide research on the lasting solution to this enemy of man-HIV. Methods: It uses a synergistic combination of neural network (NN) and fuzzy inference systems (Neuro-Fuzzy) to generate a model for the detection of the risk level of patients with HIV. Results: The user friendliness and accuracy rate of HIV diagnosis using neuro-fuzzy system makes its output an interesting one. Conclusion: using neuro-fuzzy system is one of the best ways to deal with the vagueness and imprecision of data in the health care sector, and no doubt will exploit tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness, low solution cost and better report with reality in medical diagnosis.

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The field of Graph Theory plays vital role in various fields. One of the important areas in graph theory is Graph Labeling used in many applications like coding theory, x-ray crystallography, radar, astronomy, circuit design, communication network addressing, data base management. This paper gives an overview of labeling of graphs in heterogeneous fields to some extent but mainly focuses on the communication networks. Communication network has two types ‘Wired communication’ and ‘wireless communication’. Day by day wireless networks have been developed to ease communication between any two systems, results more efficient communication. This paper also explored role of labeling in expanding the utility of this channel assignment process in communication networks. Various papers based on graph labeling have been observed, and identified its usage towards communication networks. This paper addresses how the concept of graph labeling can be applied to network security, network addressing, channel assignment process, social networks. An overview and new ideas has been proposed here.

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The Neural Network Trainer (NNT) was originally developed as a tool for training neural networks for use on a PC or comparable computing machine. NNT originally produced for the user an array of weights that corresponded to the weights in a neural network architecture designed by that user. From this point, it is was the user's responsibility to create a neural network that could utilize these weights. This paper transforms this original tool into a complete neural network implementation package for microcontrollers. This software package includes the trainer, an assembly language based generic neural network for the PIC 18 series microcontroller, 8-bit neural network simulator, a microcontroller communication interface for testing embedded neural networks, and a C implemented neural network for any microcontroller with a C compiler.

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