Showing papers by "Narula Institute of Technology published in 2014"

Employee Motivation from Performance Appraisal Implications: Test of a Theory in the Software Industry in West Bengal (India)

Abstract: The Software industry and its operation have attracted the concentration of a considerable number of researchers in the last decade, as the industry has proven its uniqueness in nature, operation, contribution to GDP and HR practice. The software industry is distinguished from other industries, by fast changing technology, quality conscious and multinational clients, stiff international competition and shortage as well as fast obsolesce of skill, although the success of IT companies depends on its’ talented and skilled workforce. As a result, measurement and management of performance of individual, team and the organization as a whole is a requisite. The paper tried to study the attitude of the employees’ of the software companies in West Bengal (India) towards performance appraisal. The paper has identified main consequences of appraisal from the previous literatures and tried to find out the effects of those end results on employee motivation towards performance appraisal. The exploratory paper, based on primary survey of 506 employee data collected from 19 software companies of Kolkata, the tier I region for the software industry in West Bengal. Data are analyzed using factor analysis, to find out the applications of appraisal, followed by a binary regression to understand their implications on the employee motivation. The study has found the importance of the line managers in the practice of the appraisal process also reviewed different dilemmas regarding appraisal practice and employee issues depending on company's size, business focus. The practice of appraising and its implications are also diverse in different companies throughout the industry.

What and When Can We Gain From the Kernel Versions of C-Means Algorithm?

Abstract: In the recent past, different kernelized versions of c-means (hard and fuzzy) clustering algorithms have been proposed. Here, we focus on kernel clustering of only object data, X = { x1, ...,xn } ⊂ Rp. We first raise a basic question: Should we really cluster any given object data in the kernel space? The answer is NO! Here are our line of arguments: 1) The objective of any clustering algorithm is to find natural subgroups in X, where the subgroups are defined by a measure of similarity between the vectors in X. 2) If we transform the data X into Y in another space by a nonlinear transformation and try to find clusters in Y, then such clusters can be useful if and only if Y helps us to find the same clusters that are present in X because that is our objective. 3) If Y maintains the same structure/topology as that of X, then the use of Y may not give any advantage. 4) On the other hand, if Y changes the structure (i.e., imposes a new structure) on the data and that change makes the extraction of the desired clusters present in X easier, then clustering of Y is useful. 5) But when Y imposes new (nonexistent) structures, the clustering algorithm may find very strange clusters with no relation to the actual clusters present in X. 6) Thus, when we try to cluster in a transformed space, the issue is to know if it could help us to find the clusters present in X. To get any benefit from kernel clustering (or clustering in any other transformed space), we need to answer this question first; otherwise, we may find completely irrelevant clusters without knowing it and thereby making kernel clustering useless. 7) This issue is a philosophical one and is neither dependent on the choice of clustering algorithm nor on the particular transformation (kernel function) used. 8) Except for 2-D/3-D data, we do not know of any way to answer the question in 6) and for 2-D/3-D data, since we can look at the data, we do not need kernel clustering. Therefore, there is no benefit from kernel clustering. We demonstrate and justify our claims using both synthetic and real datasets with visual assessment as well as with normalized mutual information, adjusted Rand index, and cluster instability. We propose to use Sammon's nonlinear projection method to get a crude visual representation of the data in the kernel space. We discuss the issue of how to choose appropriate parameters of the kernel function, but we could not provide a solution to this problem. Finally, we discuss how the kernel parameters and the algorithmic parameters interact.

An observer-based distributed scheme for selfish-node detection in a post-disaster communication environment using delay tolerant network

Abstract: Aftermath of disaster causes severe destruction/damage to physical infrastructures. As a result, communication infrastructure gets disrupted for weeks. In such situations, smart-phone based adhoc opportunistic networks may be set up with the smart-phones carried by the relief workers (also referred as nodes) to communicate the situational information from different affected corners to some remote monitoring station. In such scenario, some malicious nodes may try to intercept and manipulate the sensitive situational data with the intention of corruption and fraud. One way of preventing such corruption is to devise an automated mechanism to detect and avoid the malicious nodes during data communication process. Reputation of nodes may be used as a measure to detect malicious nodes where reputation is estimated based on their degree of cooperation with other nodes in the network during data communication. In this paper, we propose an observer based dynamic reputation estimation technique for detection of selfish nodes where a group of independent roving observer nodes were introduced in the network to monitor the behavior of volunteer nodes as forwarder and receiver and to identify whether a node has any group-bias. Observers estimate the reputation of nodes based on their interaction patterns and group-biasness and periodically publishes global node reputation matrix based on which volunteer nodes may select an unselfish forwarder node during their data communication. The performance of the proposed scheme was evaluated on ONE simulator [19].

Low-Energy Adaptive Unequal Clustering Protocol Using Fuzzy c-Means in Wireless Sensor Networks

Abstract: Clustering technique in wireless sensor networks incorporate proper utilization of the limited energy resources of the deployed sensor nodes with the highest residual energy that can be used to gather data and send the information. However, the problem of unbalanced energy consumption exists in a particular cluster node in the network. Some more powerful nodes act as cluster head to control sensor network operation when the network is organized into heterogeneous clusters. It is important to assume that energy consumption of these cluster head nodes is balanced. Often the network is organized into clusters of equal size where cluster head nodes bear unequal loads. Instead in this paper, we proposed a new protocol low-energy adaptive unequal clustering protocol using Fuzzy c-means in wireless sensor networks (LAUCF), an unequal clustering size model for the organization of network based on Fuzzy c-means (FCM) clustering algorithm, which can lead to more uniform energy dissipation among the cluster head nodes, thus increasing network lifetime. A heuristic comparison between our proposed protocol LAUCF and other different energy-aware protocol including low energy adaptive clustering hierarchy (LEACH) has been carried out. Simulation result shows that our proposed heterogeneous clustering approach using FCM protocol is more effective in prolonging the network lifetime compared with LEACH and other protocol for long run.

Optimization of Laplace of Gaussian (LoG) filter for enhanced edge detection: A new approach

Abstract: In this paper a very remarkable approach on edge detection has been explored. The most important aspect of image segmentation is edge detection. Edge detection is a meaningful interpretation of discontinuities of similar intensity values in image analysis [1]. Laplace of Gaussian (LoG) filter is a conventional edge detecting tool. Threshold neighboring pixel value (T) and standard deviation parameters are optimized with the help of Cuckoo Search optimization in order to augment the edge detection potential of LoG. PFOM (Pratt's Figure of Merit) is used as quality factor for edge detection analysis.

Exotic systems under screened Coulomb interactions: a study on Borromean windows

Abstract: An extensive calculation of Borromean windows (BWs) for 22 different configurations of three-body exotic systems have been done using an explicitly correlated Hylleraas type basis set. From the variation of BWs with mass relation parameter (q) as observed from our calculations, a physical argument is being placed to interpret the existence of a BW for only q < 1 configurations.

Haar Wavelet Transform image compression using Run Length Encoding

Abstract: In modern technology memory storing space is not a very big deal But when it comes to a portable system ie a digital camera with internet as well as communication facility, then the bandwidth for communication as well as storage are of serious concern Huge useful information has to be stored and retrieved efficiently for practical purposes The Haar wavelet, which is the simplest of all the 2D DWT, along with thresholding has been applied on a JPEG image After that Run Length Entropy Coding has been adopted This is the novel approach that authors have proposed for compression of image using parameter CR (Compression Ratio) without losing the parameter PSNR, the quality of image, using less bandwidth

Extreme wind climate modeling of some locations in India for the specification of the design wind speed of structures

Abstract: The wind load on a structure is proportional to the square of the wind speed. Extreme wind climate modeling should be required for specifying the design wind speed of structures. Extreme wind speeds for a storm type should be fitted in a suitable probability distribution, from which the design wind speed can be specified for a particular service life of a structure. The methodology, used in India for the specification of the design wind speed of existing structures, is fairly old and should be updated. Extreme wind climate in India is mainly influenced by thunderstorms and cyclones. Because thunderstorms and cyclones occur due to different geophysical reasons, it is necessary to fit extreme events of these two storm types in separate probability distributions, which can be subsequently combined to determine the overall non-exceedance probability. For a thunderstorm analysis, the wind speed data for three stations were considered, namely Kolkata, Lucknow and New Delhi. However, the statistical analysis greatly suffered due to the low ensemble size in Lucknow. Moreover, cyclones very rarely occur; as a result, cyclone modeling for the Bay of Bengal (total east coast) was initially considered to obtain a sufficient ensemble size. This paper provides a strategy to determine the specification of the design wind speed of structures at a particular location, which is affected by both thunderstorms and cyclones. The motivation of this work is to improve the current design methodology as well as the national code of standards to make engineering structures in India less vulnerable to damage due to strong winds.

Flow Features of a Conducting Fluid Near an Accelerated Vertical Plate in Porous Medium with Ramped Wall Temperature

Abstract: The unsteady MHD free convection and mass transfer boundary layer flow of an incompressible electrically conducting fluid past an accelerated infinite vertical flat plate embedded in porous medium with ramped wall temperature is considered here. It is assumed that the plate accelerates in its own plane in the presence of thermal radiation incorporating first order chemical reaction. The governing equations are solved analytically using the Laplace transformation technique. The flow phenomenon has been characterized with the help of flow parameters such as permeability parameter, Hartmann number, phenomenon has been characterized with the help of flow parameters such as permeability parameter, Hartmann number, thermal radiation parameter etc. The influences of these parameters on the velocity, temperature field and concentration distribution have been studied and the results are presented graphically and discussed quantitatively. Also, the effects of the various parameters on the skin friction coefficient, the rate of heat and mass transfer at the surface are discussed.

Energy efficient modified SPIN protocol with high security in Wireless Sensor Networks using TOSSIM

Abstract: Sensor nodes are very important attribute in Wireless Sensor Networks (WSNs), due to communication over wireless links but it has some constrains i.e. limited transmission range, processing, storage capacity and energy. To get secure communication under these circumstances SPIN protocol incorporated data security for transferring data safely to the destination. To overcome the problem of SPIN protocol such as blind forward and data inaccessible, in this paper, we propose and design modified SPIN routing protocol to save energy and give secure transmission to minimize overhead with data delivery guarantees. Our goal is to find an optimal path and efficient implementation of protocol for data negotiation, set up route and finally transfer data to specific nodes. Our novelty in this paper is more secure data transmission than SPIN. The simulations have been carried out by new operating system TOSSIM to compare data transfer rate with communication security and lifetime of networks.

Implementation of optimized high performance 4×4 multiplier using ancient Vedic sutra in 45 nm technology

Abstract: With the enrichment of new technology in the fields of VLSI design and communication there is also a demand of high speed and low area. The aim of this paper is to design a multiplier circuit based on Vedic sutras. The algorithms based on conventional mathematics can be optimized and simplified by using Vedic sutras. In this paper we have given the design up to Multipliers based on Vedic multiplication sutra “Urdhva-Tiryakbhyam” the design of 2×2, 4×4 has been designed in DSCH2 and all the outputs have been given. The layout of those circuits has been also generated by Microwind. The internal circuit diagram of all the blocks has been explained The noise, power have been calculated by T-Spice-13 in 45nm Technology. The hardware has also been implemented in XILINX and tested in Basys™2 Spartan-3E FPGA Board.

Development of Gis Tool for the Solution of Minimum Spanning Tree Problem using Prim's Algorithm

Abstract: . minimum spanning tree (MST) of a connected, undirected and weighted network is a tree of that network consisting of all its nodes and the sum of weights of all its edges is minimum among all such possible spanning trees of the same network. In this study, we have developed a new GIS tool using most commonly known rudimentary algorithm called Prim’s algorithm to construct the minimum spanning tree of a connected, undirected and weighted road network. This algorithm is based on the weight (adjacency) matrix of a weighted network and helps to solve complex network MST problem easily, efficiently and effectively. The selection of the appropriate algorithm is very essential otherwise it will be very hard to get an optimal result. In case of Road Transportation Network, it is very essential to find the optimal results by considering all the necessary points based on cost factor (time or distance). This paper is based on solving the Minimum Spanning Tree (MST) problem of a road network by finding it’s minimum span by considering all the important network junction point. GIS technology is usually used to solve the network related problems like the optimal path problem, travelling salesman problem, vehicle routing problems, location-allocation problems etc. Therefore, in this study we have developed a customized GIS tool using Python script in ArcGIS software for the solution of MST problem for a Road Transportation Network of Dehradun city by considering distance and time as the impedance (cost) factors. It has a number of advantages like the users do not need a greater knowledge of the subject as the tool is user-friendly and that allows to access information varied and adapted the needs of the users. This GIS tool for MST can be applied for a nationwide plan called Prime Minister Gram Sadak Yojana in India to provide optimal all weather road connectivity to unconnected villages (points). This tool is also useful for constructing highways or railways spanning several cities optimally or connecting all cities with minimum total road length.

QoS and Mobility Management Issues on Next Generation Mobile WiMAX Networks

Abstract: Selection of a MIMO (Multiple Input Multiple Output) antenna to achieve high throughput, minimize errors, and optimize data speed is an important design issue. Radio resource management to provide Quality of Service (QoS) in WiMAX involves dynamic scheduling of resources according to the user’s priority, based classes Platinum, Gold, Silver, and Bronze. Mobility and handoff management in WiMAX is another important issue involving location update, signaling traffic and service delay, and call blocking and dropping. This chapter focuses on some issues concerning MIMO configuration to improve transmit diversity, developing an appropriate scheduling algorithm to improve QoS, and presenting a novel mobility management protocol THMIP (Three Level Hierarchical Mobile IP) in IEEE 802.16e environment to reduce signaling cost with respect to QoS parameters like throughput, end-to-end delay, interference, path loss, bit error rate, and Signal-to-Noise Ratio (SNR). For the simulation, the authors use OPNET Modeler and MATLAB.

A complete virtual instrument for measuring and analyzing human stress in real time

Abstract: A virtual Instrument is designed, prototyped and developed for the real time measurement and recording of galvanic skin response (GSR), also known as electrodermal response to recognize human psycho physiological state under stressed condition. The virtual instrument also analyzes the galvanic skin response signals by statistical features. The Galvanic Skin Response (GSR) is a measure of skin conductivity which is extensively linked to human emotional condition during stress and activation. An emotional reaction under stressed condition often causes increased sweat gland activity in the palms of the hands and the soles of the feet, making the skin more conductive in these areas. The experiments are done under stress and no-stress conditions on 14 subjects of both the gender in the age group of 18 to 28 years old, mainly on university students. The experimental observations demonstrate a strong correlation between measured signals for galvanic skin response (GSR) and human physiological states. LabVIEW software is used for the front panel of the virtual instrument whereas MATLAB software is used for the calculation of features in the back end of the virtual instrument.

Study of parametric optimization of the Cuckoo Search algorithm

Abstract: Cuckoo search (CS) is one of the latest and most efficient optimization techniques developed so far. Several attempts have been made in past in order to improve the efficiency of CS algorithm. In this paper we have tried to exploit several parameters of the CS algorithm in order to increase its efficiency. Cuckoo search is a metaheuristic optimization technique. Its parameters involve the Levy distribution factor beta (β) and the probability factor (P) with which solutions are replaced with new solutions. Hence for optimum values of the aforesaid parameters, efficiency of CS algorithm can be improved and can be used to solve optimization problems.

Dynamical system analysis of modified chaplygin gas in Einstein-Aether gravity

Abstract: In this work we investigate the background dynamics when dark energy is coupled to dark matter with a suitable interaction in the universe described by the Einstein-Aether gravity. Dark energy in the form of modified Chaplygin gas is considered. A suitable interaction between dark energy and dark matter is considered in order to at least alleviate (if not solve) the cosmic coincidence problem. The dynamical system of equations is solved numerically and a stable scaling solution is obtained. A significant attempt towards the solution of the cosmic coincidence problem is taken. The statefinder parameters are also calculated to classify the dark energy models. Graphs and phase diagrams are drawn to study the variations of these parameters. It is also seen that the background dynamics of the modified Chaplygin gas in the Einstein-Aether gravity is completely consistent with the notion of an accelerated expansion in the late universe. Finally, it has been shown that the universe follows the power law form of expansion around the critical point.

Study the effect of music on HRV impulse using multifractal DFA analysis

Abstract: The 2D Poincare' plot of HRV signal reflects the effect of different external stimuli on ANS. The classification is generally done by fitting an `ellipse' on the dense region of the constructed Poincare' plot of HRV signal. However 2D Poincare' plot sometimes fails to describe the proper behavior of the system. One such example is 2D Poincare' plot of HRV signal in pre-music and on-music condition. In fact 2D Poincare' plots in pre and on-music condition look almost similar for few subjects. So a proper classification tool is sought for. In this article, multi-fractal DFA analysis has been applied to properly distinguish the pre-music and on-music state of some normal healthy subjects. The whole experiment is carried out at School of Bio-Science and Engineering, Jadavpur University, Kolkata, India.

Comparative analysis of binding sites of human meprins with hydroxamic acid derivative by molecular dynamics simulation study

Abstract: Meprins are complex and highly glycosylated multi-domain enzymes that require post-translational modifications to reach full activity. Meprins are metalloproteases of the astacin family characterized by a conserved zinc-binding motif (HExxHxxGFxHExxRxDR). Human meprin-α and -β protease subunits are 55% identical at the amino acid level, however the substrate and peptide bond specificities vary markedly. Current work focuses on the critical amino acid residues in the non-primed subsites of human meprins-α and -β involved in inhibitor/ligand binding. To compare the molecular events underlying ligand affinity, homology modeling of the protease domain of humep-α and -β based on the astacin crystal structure followed by energy minimization and molecular dynamics simulation of fully solvated proteases with inhibitor Pro-Leu-Gly-hydroxamate in S subsites were performed. The solvent accessible surface area curve shows a decrease in solvent accessibility values at specific residues upon inhibitor binding. The potential energy, total energy, H-bond interactions, root mean square deviation and root mean square fluctuation plot reflect the subtle differences in the S subsite of the enzymes which interact with different residues at P site of the inhibitor.

Spectrum hole detection in TV band using ANN model for opportunistic radio communication

Abstract: Here we propose an artificial neural network (ANN) model for spectrum sensing in TV band specifically for identifying presence of audio signals. The ANN model is trained with parameters which are a combination of cyclostationary and SNR based features like channel capacity, bandwidth efficiency, autocorrelation. The ANN model is trained based on a new decision making factor termed as utilization factor based on the above combination of attributes which lead to a method for detection of spectrum holes. This unique combination of hypotheses tries to remove the disadvantages of energy detection and cyclostationary feature detection technique, which is helpful for opportunistic cognitive radio applications.

Performance analysis of CSMA/CA protocol during white space identification in cognitive radio networks

Abstract: In this paper, we analyze the delay performance of distributed and centralized cooperative sensing approaches to find out which one is suitable for sensing inter packet white space. For simultaneous sharing of channels by primary users (PUs) and secondary users (SUs), the white space has duration of approximately 50 ms. In distributed cooperative sensing, the SUs perform carrier sense multiple access with collision avoidance (CSMA/CA) with distributed coordination function (DCF) for accessing common control channel to share sensing information among each other. In centralized cooperative sensing, SUs access common control channel to send sensing result to a fusion centre (FC) using CSMA/CA point coordination function (PCF) mechanism. Total delay of these two sensing approaches is given as the sum of total channel access delay and queuing delay. We find that for a particular number of SUs, the delay of sensing in centralized environment is within the permissible limit (i.e. within 50 ms). Although distributed cooperative sensing is much more reliable and scalable than centralized cooperative sensing, it has higher sensing delay than centralized sensing approach.

Solar resource assessment in India a case study

Abstract: This paper represent and assessment on solar power resource available in India Day by day electrical energy consumption is increasing which also increases the generation of greenhouse gases due to uses of fossil fuel The pollution level is crossing the danger limit, so world is moving towards practices of renewable energy sources Solar energy is one of the largest and easily available renewable energy sources Through this paper an attempt has been taken to discuss the solar resource available in India and the potentials related to solar energy has to be discovered One detail case study on solar power uses has been given, the problem related to solar power application has been highlighted and finally the future aspect in India on solar power has been mentioned India collects good annual solar emission although having several climatic zones With this background India began its study towards renewable energy over three decades ago

Studies and Implementation of Subband Coder and Decoder of Speech Signal Using Rayleigh Distribution

Abstract: In the last 40 years a number of coding techniques for analog sources (speech and images) has been employed. Subband coding, a kind of transform coding, splits analog speech signal into a number of different smaller frequency bands. By subbanding data rate has been reduced to 12.13804 Kbps [Sangita et al. Studies and implementation of subband coder and decoder of speech signal, Proceedings of national conference on electronics, communication and signal processing, 8–16, 1] on 64 Kbps telephone line. In this paper a method has been proposed by which data rate has been reduced to 9.4875 Kbps using Rayleigh distribution where data rate can be reduced to 9.6 Kbps [Crochiere et al. Digital coding of speech in subbands, The BELL System Technical Journal, 2]. Proposed method can save data rate which in turn saves bandwidth as well as spectrum. Moreover this proposed method provides acceptable probability of error and quantization noise i.e. SNR.

Identification of spectrum holes using ANN model in TV bands with AWGN

Abstract: Here we propose an artificial neural network (ANN) model for spectrum sensing in TV band specifically for detecting the presence of audio signals. The ANN model is trained with parameters which are a combination of cyclostationary and SNR based features like channel capacity, bandwidth efficiency, autocorrelation. The ANN model is trained with a new decision making factor termed as utilization factor (U) based on the above combination of attributes which lead to a method for detection of spectrum holes. The bandwidth efficiency (η) is also considered as a decision making factor to identify spectrum holes. This unique combination of hypotheses tries to remove the disadvantages of conventional energy detection and cyclostationary feature detection technique commonly used for CR applications.

Thermal comfort inside residential building with varying window locations and size

Abstract: In eastern India use of shading devices (with or without glazing) is desirable, as this zone predominantly suffers from hot and humid climate and high solar radiation. There are scanty literature on the subject of the effect of shading devices of variety of materials and design and orientations on the building internal spaces. Therefore, further research is required to investigate the effect of location of window or opening on the indoor thermal condition with respect to the orientation of the building or room irrespective of design criteria. This paper discusses about the window size and location to be used in residential buildings. The study presented in this paper evaluates the optimal internal sunlight penetration through windows for different locations and orientation of residential building during the overheating and high humid periods. The effect of various locations of windows to reduce the required cooling loads and thermal performance considering the use of best shading devices is presented through simulation. This study also compares its simulation data for the proposed building height to the height recommended by National Building Code of India. The main aim of this work is to assess different thermal condition created by different locations of windows and the reduction percentage of cooling loads through the selected optimum location of window. The outcomes of this research will reduce the efforts in planning and designing residential building by practicing architects and engineers in regions with hot and humid climatic characteristics.

Temperature Induced Mean Based Cloud Motion Prediction Model for Multiple Cloud Clusters in Satellite Infrared Images

Abstract: Thermal infrared images are quite useful in detection of convective clouds for meteorological purposes. Several techniques are available for the detection and tracking of clouds in satellite thermal infrared images. Temperature induced mean based cloud motion prediction model is one of them. But so far, it has been implemented for tracking single cloud cluster. In the present work this model is extended and applied for tracking of multiple cloud clusters so that it can be utilized for weather nowcasting.

Study of the effect of different music stimuli on autonomic nervous system of a single subject

Abstract: Study of the effect of music on autonomic nervous system of human being through the analysis of Heart rate variability (HRV) signals is a very recent area of research. The present paper considers the effect of seven different types of music stimuli on a single subject. The data of the HRV signals are subjected to a recently developed technique known as `frequency-delay plot'. The quantification is done by `ellipsoid fit' and allied five different types of quantification measures. Such results of quantification are then analyzed by the method of 'randomized block ANOVA. It is proved that all the different types of music stimuli have different effects on ANS of the subject, and that the effects are significantly different. Moreover the five different measures also do differ significantly on the music data. Finally to test which music signal affects ANS most, we consider, as population, the totality of all data corresponding to different types of songs and different types of measures taken. By considering the data of individual song under all measures as data of a sample, we calculate the interval of confidence of the population mean and the population variance with the help of each sample mean and sample variance at 0.95 level of confidence. It is proved that the length of confidence interval for population mean as well as for population variance is minimum only in the case of song1. In other words, it means that song1 is the most effective one on ANS of the subject.

Threshold voltage roll-off for triple gate FinFET analysis based on several semiconductors used as substrate

Abstract: The literature of power device must aware of the fact of proper tradeoff between the choice of semiconductor material and the proper oxide along with it. With the growing semiconductor technology, the traditional semiconductor now has the promising competitors like silicon carbide and gallium nitride.The simulation considers the calculation of minimum potential at the center plane of the FinFET channel through which roll-off of threshold voltage is measured. The analysis proves gallium nitride and silicon carbide as the most promising material for FinFET manufacturing industries. The drain to source voltage along with fin-height, fin thickness and channel length are varied keeping other parameters constant. The purpose of this work is to find out the “other than silicon” material in solid state device technology.

Modified Gossip Protocol in Wireless Sensor Networks Using Chebyshev Distance and Fuzzy Logic

Abstract: The Flooding is a traditional flat based routing protocol where unlimited broadcasting of the packets in the flooding scheme will cause the huge energy consumption to send the packets from source to sink due to implosion, overlap, resource blindness and consequently creates broadcast storm. However Gossiping routing protocol in WSNs is very much effective due to its simplicity, robustness, distributed and capability to work in noisy and uncertain environments. But due to recirculation of information and repeated data communication of randomized gossip protocol which can lead to a significant energy consumption of the network. This paper proposes an energy efficient routing protocol based on Fuzzy Logic and Chebyshev Distance, which is a modification of gossip protocol. The new protocol determines the optimal routing path from source to destination by selected the best node from candidate nodes in the forwarding paths by favoring highest remaining energy and the lowest distance to the sink. Simulation results shows that the proposed method is efficient to control messages forwarding and improves the performance which minimizes the overall energy consumption and maximize WSNs lifespan.

Mesoscale convective system tracking in satellite thermal infrared images

Abstract: In the field of meteorology, mesoscale convective systems are required to be distinguished, tracked, and their lifecycle to be observed, for precipitation forecasting. Mesoscale convective systems are easily identifiable from satellite infrared images. There are several existing techniques like temperature induced mean based cloud motion prediction model, for identification and tracking of cloud structures from a series of thermal infrared images. This technique has been previously implemented for tracking of single and then multiple cloud clusters. In this study, temperature induced mean based cloud motion prediction model has been deployed for tracking and predicting the motion of an entire convective system.