Volume 5, Issue 4, April 2014 Edition

Publication for Volume 5, Issue 4, April 2014 is in-process.

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An Artificial Neural Network Controlled SVC for Dynamic Stability Enhancement of Power Transmission System[ ]


This paper reviews new approach in modern research using Artificial Neural Network. Voltage level of the system changes at the time of fault and the drop in the load voltage leads to an increased demand for the reactive power that, if not met by the power system leads to a further decline in the bus voltage. This decline eventually leads to a progressive rapid decline of voltage at that location, which may have a cascading effect on neighboring regions that causes voltage collapse. In this paper, In order to maintain system stability after faults, the transmission line is shunt compensated at its center by a 200-Mvar Static Var Compensator (SVC) in MATLAB / SIMULINK. SVC was used to maintain the voltage within the limits. SVC will either supply the reactive power or extract the reactive power. An Artificial Neural Network (ANN) is also developed with a systematic step-by-step procedure which optimizes a criterion commonly known as the learning rule. The input/output training data is fundamental for these networks as it conveys the information which is necessary to discover the optimal operating point. It is shown that trained Neural Network developed has excellent capabilities of forecasting which can be very useful in research.

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Assessment of Soil Characteristics around Municipal Solidwaste Disposal site in sulur block- Coimbatore Town Panchayats-Tamilnadu,India[ ]


Solid waste is defined as those wastes from human & animal activities. In domestic environment the solid waste includes paper, food waste, plastics, ash etc. Soil is a dynamic system because of the presence of microorganisms and their biochemical activities liberating a lot of enzymes in soil, which become stabilized in soil by binding to soil components.[11] It is the environment for plant root system. It exhibits continuous interplay between the living and non-living components.Soil pollution and contamination is a serious problem especially in country as densely populated as India. Due to rapid industrialization, the soils in the industrial areas are polluted by various toxic substances such as heavy metals, pesticides, dioxins, polyvinyl compounds etc. from sourcesThe Present work was undertaken to analyse the physical chemical characteristics of the ground water in and around the municipal solidwaste 4 disposal sites town panchayats in Coimbatore .[12]The Chemical characteristics of Soil Samples like pH, EC, Mg, Na, K, Ca, Moisture content & Sodium Absorption Ratio were studied.

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Computational Identification of MicroRNAs for Targeting Long and Short Segments of Lassa Virus[ ]


MicroRNAs (miRNAs), are a class of approximately 22 nucleotide long non coding RNAs which play critical role in different biological processes. The mature microRNA is usually 19–27 nucleotides long and is derived from a bigger precursor that folds into an flawed stem-loop structure which are involve in many cellular process that encompass development, proliferation, stress response, apoptosis, fat metabolism by gene regulation. Resent finding reveal that certain viruses encode their own miRNA that processed by cellular RNAi machinery. In recent research indicates that cellular microRNA can target the genetic material of invading viruses were reported. Cellular miRNA can be used in virus life cycle; either to up regulate or down regulate viral gene expression. Computational tools utilize in miRNA target prediction has been changing drastically in recently. Where many of them are available on the web and can be used by researcher and scientist without of bioinformatics. The development genomes analysis technologies recorded during the previous decade has tremendously cleared the biology of miRNA. In this study nucleotide sequences of long (23343512) and short segments (23343509) sequences of Lassa viruses; L and S segment; composing the genome of Lassa virus which naturally affect human were analyzed using VMir analyzer program (computational approach) to predict the counter human cellular miRNAs candidates targeting viral genome. The 50 nt minimum hairpin size, 90 nt maximum hairpin size and 50 minimum hairpin score were used for the filter of sequence, as well as pairing energy less than 10 kcal/mol was utilize as cutoff score. The results of RNA hybrid were categories in terms of pairing energy (minimum free energy) and hybridization pattern. Four types of hybridization patterns were obtain from RNA hybrid analysis. According to L segment analysis, 34 potent miRNA divided into three groups, subsequently, hsa-miR-608, hsa-miR-3692-5p, hsa-miR-557, hsa-miR-1273d, hsa-miR-136-5p and hsa-miR-3164 are selected as potential human cellular miRNAs. From the miRBase database 16 potential miRNA were predicted as potential miRNA targeting S segment, therefore, hsa-miR-4691-5p, hsa-miR-581 and hsa-miR-622 were selected as potential human cellular miRNAs on the basis of pairing energy. The results suggested that microRNAs from MD30, MR19 and MR30 as well as MD15 and MR1 from L segment and S segment, respectively, might be best candidate to targeting human cellular miRNAs.

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Design Feed Forward Neural Networks To Solve Control Problem In Electric Power System[ ]


The main aim of this paper is to use artificial neural networks to solve control problem in electric power system, since the neural networks are universal and effective means for the different control problems. The use of such method of the artificial intelligence allows solving the reactive power and voltage control problem with higher level of its reliability and quality. The solving of the reactive power and voltage control problem is to increase the electric network effectiveness. It allows to reduce the electric power losses, substation loading and to improve the electric power quality. In this paper, the main principles of such control is considered on the basis of the neural networks.

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Compare Between Flat and Hierarchical Architecture In Learning Classifier System for Robotics Controller[ ]


A control system is an interconnection of components forming a system configuration that will provide a desired system response. A network of different Classifier Systems can implement the control system of an agent. The issue of architecture is therefore the problem of designing the network that best fits some various classes of robotics behaviors. The case study is system called (FTS),The system Seek For Food And Avoid Tree (FTS) built of three-classifier subsystem work together, each classifier system learns a simple behavior, the system as a whole has as its learning goal the control of robot activities. two levels hierarchical architecture was used. The hierarchical organization allows distinguish between two different learning activities: the learning of basic behavior and the learning of switch behavior. two classifier systems in hierarchical model, learn basic behavioral,(chase / avoid), they are used, to learn the simulated robot, single step movement in every direction in the environment, where the switch classifier systems learn to control the activities of basic classifier systems, they are used to learn, to choose between basic behavior using suppression as a composition mechanism to chose between two basic behaviors which represent complex behavior. The Seek for food and avoid Tree (FTS) system is repeated again using flat architecture by built of two learning classifier systems only (instead of three classifier systems) Organized in one level architecture( instead of two level architecture),In this work we compare between the flat architecture and the hierarchal architecture ,difference in performance between these two architectures is examined. Experimentally show that the use of hierarchal architecture can help to control the complexity of learning. our study shows that learning classifier system are a feasible tool to build control system .to achieve this goal we found very helpful to decompose the desired overall task into a set of simpler interacting classifiers organized in a hierarchy. these interacting behaviors were implemented as a set of classifier systems using a distributed architecture in which each classifier system runs on a different set of processors. this choice was sufficient to achieve adequate levels of performance for a variety of tasks. Results using hierarchal architecture show improvement over the flat architecture by reduce the learning complexity ,reduce time need to perform task, and signal accuracy.

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Study Of Stabilizing Agent For Different Soil Varieties[ ]


Soil species like loose sand, soft clays, black soil etc. lack adequate engineering properties to be appropriately as construction entities. Method of removing the soil and bringing in a new variety of soil is uneconomical. Thus stabilization offers economical and environment friendly remedy. The suitability and feasibility of soil for stabilization, the selection of most appropriate stabilizing agent and quantity of the agent are generally calculated by keeping in mind the chemical and mineralogical composition and texture of a soil along with physical properties and compositional indices of the soil. This research investigated some of the materials and their feasibility as stabilizers in different kind of soils. It reviewed the results of tests like CBR conducted by various researchers on soil engineering properties and strength test to determine the suitability of particular stabilizers in a specific soil condition. In the study it was also shown that although the soil engineering test and strength test like California Bearing Ratio and Atterberg limits do give a general idea about the kind of stabilizers to be used but grouping of soils according to area and field experience is also given importance.

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Development and Validation of High Performance Liquid Chromatographic Method for the Determination of Nateglinide in Human Plasma by HPLC-UV Detection[ ]


A rapid, specific and accurate high performance liquid chromatographic method for the determination of Nateglinide in human plasma using Repaglinide as internal standard was developed and validated by UV detection. The extraction process involved a liquid-liquid extraction using ethyl acetate. Both Nateglinide and the internal standard were eluted under isocratic mode using a 150 X 4.6 mm i.d, 5 µm Phenomenex ODS 2 C18 column. The mobile phase composed a mixture of 50:50 % v/v Methanol and 10 mM phosphate buffer at a flow rate of 1.0 mL/minute. The wavelength of detection is 225 nm. The injection volume is 10 µL. The runtime of the method is 5 minutes. The method showed good linearity in the range of 50.42 – 10079.52 ng/mL. The mean recovery of Nateglinide from all the quality control samples is 89.34 % with a % c6efficient of variation of of 2.2 % and recovery of internal standard was 93.3% at MQC level. Matrix effects were not observed. The method is validated as per ICH guidelines.

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Comprehensive Overview of Basic Photovoltaic (PV) Power System[ ]


This paper gives a comprehensive review of Basic Photovoltaic (PV) Power System which can be now considered as one of the most useable renewable electrical power generation technology. This paper is intended to present a broad overview of different possible classifications of PV Power System and their main components including PV Panels, DC-DC Converters, Control System, Maximum Power Point Tracking and enhancement of basic PV Power System.

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A NEW COLOUR IMAGE STEGANOGRAPHY USING LSB APPROACH WITH HALFTONING DETERMINATION EMBEDDING POSITION[ ]


Steganography is the art and science of encoding secret messages in such a way that no one, apart from the sender and intended recipient, suspects the existence of the hidden message. The Least Significant Bit (LSB) insertion is a well-established method for embedding the secret message that is known for its superiority in terms of imperceptibility; however, it suffers from robustness against Chi-square attack. In this study, a new colour image steganography technique is proposed using the LSB insertion coupled with a halftone image, which is used to determine embedding pixels. The technique involves four stages: secret message preparation, image halftoning, embedding and extraction. Firstly, the secret message is converted from character to a bit-stream. Secondly, a halftone image is created from the cover image in order to determine the embedding pixels. Thirdly, the secret message’s bit-steam is sequentially embedded onto the embedding pixels until all the bits are exhausted. Upon the embedding, final stage is to extract the embedded secret message; this is done in the same way as embedding process except it is performed in a reverse order. A series of experiments is conducted using a standard dataset to evaluate the performance of the proposed method in terms of both imperceptibility and robustness. The experimental results have revealed that the method yielded very high imperceptibilty with Peak Signal-to-Noise Ratio averaged at 67dB, and was able to withstand against the Chi-square attack.

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A Modified PSO Based Solution Approach for Economic Load Dispatch Problem in Power Systems[ ]


This paper presents a new algorithm that utilizes the PSO with double chaotic maps to solve the economic load dispatch problem with different cost functions. In proposed approach, we employ the PSO method that involves the alternating use of chaotic maps in estimating the velocity of the particle. Presently the PSO method has been widely used in complex designs problems with multiple variables where the optimization of a cost function is required. The use of the PSO method for the economic load dispatch problem is widely studies however the best solution may require higher number of iterations and at the worst it fails to achieve global best solution, hence to overcome the problem irregular velocity updates are performed by some kind of random function which force the particles to search greater space for best global solution. However the random function itself derived from a well-defined mathematical expression which limits its redundancy hence in the paper we are utilizing the two different chaotic maps which are used alternatively this mathematically increased the randomness of the function. The simulation of the algorithm verifies the effectiveness and superiority of the algorithm over standard PSO and single chaotic map based PSO.

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Secure Data Intrusion Resilience in Mobile Unattended WSNs[ ]


Wireless Sensor Networks (WSNs) are causes a wide range of attacks due to their distributed nature, limited sensor resources, and lack of tamper resistance. A sensor is corrupted, the adversary learns all secrets. Most security measures become ineffective. Recovering secrecy after compromise requires help from a trusted third party In Unattended Wireless Sensor Networks (UWSNs), where the sink visits the network periodically. Unattended Wireless Sensor Networks (UWSNs), where sensors move according to some mobility models. That such a mobility feature could be independent from security (e.g., sensors move to improve area coverage). Here define novel security metrics to evaluate intrusion resilience protocols for sensor networks. And also propose a cooperative protocol that by leveraging sensor mobility allows compromised sensors to recover secure state after compromise

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Novel Iris Recognition Technique using Fractional Energies of Transformed Iris Images using Haar and Kekre Transforms.[ ]


The theme of the work presented in the paper is novel Iris feature extraction technique using fractional energies of transformed iris image. To generate image transforms, Haar and Kekre transforms are used. The above transforms are applied on the iris images to obtain transformed iris images. From these transformed Iris images, feature vectors are generated by taking the advantage of energy compaction of transforms in higher coefficients. Due to this the size of feature vector reduces greatly. Feature vectors are extracted in 5 different ways from the transformed iris images. First way considers all the coefficients of the transformed iris image and the rest considers 99%, 98%, 97%, and 96% of the higher energy coefficients for generating the feature vector. Considering fractional energies lowers the computations and gives better performance. Also the size of feature vector is reduced greatly. Performance comparison among various proposed techniques of feature extraction is done using Genuine Acceptance Rate (GAR). Results have shown that by considering fractional energies gives better results as compared to considering 100% energies. Also, the retrieval speed and computations are reduced greatly. Finally, Haar transform gives better performance as compared to Kekre transform. The proposed technique is tested on Palacky University Dataset.

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Survey on Multipath Routing Protocols in Wireless Ad-Hoc Networks[ ]


A Wireless ad hoc network consists of wireless mobile nodes. Such a network does not have a fixed infrastructure but nodes perform the networking function by acting not only as a host but also as a router forwarding packets to other nodes that may not be within direct wireless transmission range of each other. Since the inception of wireless technologies, the concept of Mobile Ad-hoc Networks is becoming increasingly popular. The disaster relief management, battlefield communication, electronic classrooms, conferences are main applications of mobile ad-hoc networks. In MANET, all nodes move freely without enforcing any network topology. Moreover, a node is free to leave or join the MANET without any notification. This behavior causes the breakup and automation of topology. Ad Hoc routing has been widely researched over the past years but widely used implementations are yet to come. Several protocols have been developed under the authority of Mobile Ad hoc Networking (MANET) working group. MANET is charter of Internet Engineering Task Force (IETF). Lots of research has also been done about the performance of ad hoc networks under varying scenarios. Different kind of metrics or characteristics may be used to analyze the performance of an ad hoc network.

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Survey on Proactive and Reactive Protocols in MANETs[ ]


A Mobile Ad-hoc Network (MANET) is infrastructure less network formed by mobile nodes sharing wireless channel without any centralized administration. As nodes are mobile they can move arbitrarily, the network topology, which is typically multi-hop, can change frequently and unpredictably resulting in route changes, frequent links break and possibly packet losses. One of the main challenges of MANET is the design of robust routing algorithms that adopt to the frequent and randomly changing network topology. There are several routing protocols which have already been proposed for providing communication among all the nodes in the network and are classified into proactive and reactive protocols. In this paper , we compare and evaluate the performance of widely used both table-driven such as DSDV and on-demand unipath and multipath routing protocols such as AODV and AOMDV by passing various parameter metrics like Throughput, End-to-End delay, Packet delivery ratio, Packet drop and Average energy consumption by using simulation.

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Customer classification in retail marketing by data mining[ ]


Capital investment in retail sector and competition in the market has changed the style of marketing. At the same time the enhancements in the field of information technology provided an upper hand to the marketer to know the exact need, preference and perches trend of the customer. By knowing the actual need, preference and purchase trend of customers the marketer can make a future business plan to increase the sale and earn more profit. This paper provides a framework to the retail marketer to find the potential customer by analyzing the previous purchase history of the customer. This task can be accomplished by the use of data mining technique. In this paper we have used k-mean clustering algorithm and Navie Byes’ classifier for indentifying potential customer for a particular section of products of the retailer.

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Text & Non-Text Segmentation in Colored Images[ ]


The purpose of this paper color images with complex background for text and non-text segmentation is to propose a new system. The existing text extraction methods in the case of images with complex background do not work efficiently. Locating text in case of variation in style, color, as well as complex image background makes text reading from images challenging. Here the approach used is based on pre-processing steps, edge detection, CC-analysis, bounding rectangles, segmentation and finally extraction of only those blobs which consist of textual part. This approach is tested successfully across various images taken manually and from internet.

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Static Voltage Collapse Studies In Power Systems[ ]


This paper concentrates on the static voltage stability studies on power systems. The behavior of the system when subjected to gradual and steady increase in system loading is studied. The tool like continuation load flow using the modal analysis technique is used in a systematic way so as to predict the system behavior at different operating conditions. The method devised is a worthy tool to use in power system planning studies from the view point of voltage stability. The main objective is to device suitable computer programs so as to conduct planning studies on a power system from the view point of voltage stability. To do the load flow and identify the weak buses in the system using Eigen value analysis.

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Theosophy and the artistic scope of Mawlana Jalal al-Din Rumi[ ]


Undoubtedly, one of the most renowned personalities of the Islamic mysticism and philosophy is Mawlana Jalal al-Din Rumi. Various illustrations presented by him regarding knowledge, cognition, God and the universe introduce certain theosophy and a special theological and artistic-philosophical system whose roots are deeply rooted above any other in the Islamic holy scripture, and then in the abundant artistic-philosophical tradition of the East and antique, its branches stretch to a large number of mental and artistic systems of the Middle ages and the present times. His eternal style remains fresh and attainable for the spirit in every time and space. Hence, the figure of Mawlana continues to stand solid between East and West.

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Prodution of Ferrous Sulfate From Steelmeking Mill Scale[ ]


Spent pickle liquor from steel manufacturers is usually used to produce ferrous sulfate in the route of acid recovery. This work proposes a new process to be used industrially by which clean mill scale is used as raw material for the production of ferrous sulfate by acid leaching. Process simplicity and abundance of raw material may be invoked as factors that encourage its implementation. In this work, after characterization, a sample of mill scale from a semi-integrated steelmaking plant is leached with sulfuric acid (at concentrations of 5%, 10%, and 15%) inside percolation columns; by recirculation of the acid solution, a liquor rich in Fe2+ is produced. Next to the leaching step, the liquor is concentrated by evaporation at the temperature of 80 °C and, in the sequence, is left to cool naturally until room temperature. This procedure allows for the crystallization of ferrous sulfate. To finish, the crystals are collected, purified with ethanol, and characterized by X-ray diffraction. X-ray analysis indicate Melanterite (FeSO4?7H2O) as the main compound present in the solid fraction, followed by Szomolnokite (FeSO4?H2O) and Rozenite (Fe SO4?4H2O).

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