bluuebunny/crossref_metadata_2025 huggingface dataset:
An Approach of Semantic Similarity Measure between Documents Based on Big Data
Authors: Erritali Mohammed , Beni-Hssane Abderrahim , Birjali Marouane , Madani Youness
Published: March 2017

Semantic indexing and document similarity is an important information retrieval system problem in Big Data with broad applications. In this paper, we investigate MapReduce programming model as a specific framework for managing distributed processing in a large of amount documents. Then we study the state of the art of different approaches for computing the similarity of documents. Finally, we propose our approach of semantic similarity measures using WordNet as an external network semantic resource. For evaluation, we compare the proposed approach with other approaches previously presented by using our new MapReduce algorithm. Experimental results review that our proposed approach outperforms the state of the art ones on running time performance and increases the measurement of semantic similarity.
PAPR Reduction for Improved Efficiency of OFDM Modulation for Next Generation Communication Systems
Authors: Prasad Yadav Shatrughna , Bera Subhash Chandra
Published: March 2017

Highly linear power amplifiers are required for transferring   large amount of data for future communication. Orthogonal frequency division multiplexing (OFDM) provides high data rate transmission capability with robustness to radio channel impairments. It has been widely accepted for future communication for different services. But, it suffers from high value of peak-to-average power ratio (PAPR). High value of PAPR drives high power amplifier into its saturation region and causes it to operate in the nonlinear region.  In this paper, comparative study of four different PAPR reduction techniques: clipping and filtering (CF), selective mapping  method (SLM), partial transmit sequence (PTS) and DFT- spread technique  have been done. Mathematical modeling and Matlab simulations have been performed to arrive at the results with 4 QAM modulation format and 1024 number of sub carriers. At 0.01 % of complementary cumulative distribution function (CCDF) significant reduction of 11.3, 3.5, 3.4 and 1.0 dB have been obtained with DFT- spread, SLM, PTS and CF techniques respectively.
Improved Canny Edges Using Cellular Based Particle Swarm Optimization Technique for Tamil Sign Digital Images
Authors: Krishnaveni M , Subashini P , Dhivyaprabha TT
Published: March 2017

The development of computer based sign language recognition system, for enabling communication with hearing impaired people, is an important research area that faces different challenges in the pre-processing stage of image processing, particularly in boundary detection stage. In edge detection, the possibility of achieving high quality images significantly depends on the fitting threshold values, which are generally selected using canny method, and these threshold values may vary, based on the type of images and the applications chosen. This research work presents a novel idea of establishing a hybrid particle swarm optimization algorithm, which is a combination of PSO with the behavioural pattern of cellular organism in canny method, that defines an objective to find optimal threshold values for the implementation of double thresholding hysteresis method, which is viewed as a non-linear complex problem. The attempt to incorporate the model has minimized the problem of quick convergence of PSO algorithm which has improved the detection of broken edges. The efficiency of the proposed algorithm is proved through the experimental observation, done in Tamil sign images to indicate the better performance of canny operator by introducing new variant based PSO.
Rapid Prototyping Methodology of Lightweight Electronic Drivers for Smart Home Appliances
Authors: Adiono Trio , Putra Rachmad Vidya Wicaksana , Fathany Maulana Yusuf , Lawu Braham Lawas , Afifah Khilda , Santriaji Muhammad Husni , Fuada Syifaul
Published: March 2017

Many researches have been conducted in smart home topic. Mostly, they discussed on the specific aspect of application. On the other side, many applications still can be explored and attached into the system. Several main challenges in designing the application devices are system complexity, reliability, user friendliness, portability, and low power consumption. Thus, design of electronic driver is one of the key elements for overcoming these challenges. Moreover, the drivers have to comply the rules of smart home system, data protocol, and application purpose. Hence, we propose a rapid prototyping methodology on designing lightweight electronic drivers for smart home appliances. This methodology consists of three main aspects, namely smart home system understanding, circuitry concept, and programming concept. By using this method, functional and lightweight drivers can be achieved quickly without major changes and modifications in home electrical system. They can be remotely controlled and monitored anytime and from anywhere. For prototyping, we design several drivers to represent common electronic and mechanical based applications. Experimental results prove that the proposed design methodology can achieve the research target.
Improved Performance of DPFC Using Sliding Mode Controller Method
Authors: Rao D Narasimha , Surnedra T , Kalyani S Tara
Published: March 2017

Modern power systems demand the need of active power flow with the help of Power Electronics control devices is needed. In the family of Flexible AC Transmission devices (FACTS), Dynamic PFC (DPFC) offers the same controlling function as Unified PFC (UPFC), comprising the control of transmission angle, bus voltage and line impedance. A technical modification of UPFC is DPFC in which fluctuations of voltage at DC link is eliminated that enables the individual operation as series and parallel controllers. The concept of DFACTS is used in design of the series converter. The replacement of  the  high  rating  three  phase  series  converter with  the multiple low rating single phase converters results in cost reduction and increases reliability greatly. This DC Link is used to transfer the real power between two converters in UPFC such as in DPFC which eliminates the 3rd harmonic frequencies at transmission lines. D-FACTS converters are acting as insulation between high voltage phases acts as 1-ᴓ floating with respect to ground. These results in lower cost for the DPFC system compared to the UPFC. This paper describes the comparison of PI and Sliding Mode Controllers which conclude that SMC is a better control strategy compared to PI.
DPFC Performance with the Comparison of PI and ANN Controller
Authors: Rao D Narasimha , Surendra T , Kalyani S Tara
Published: March 2017

Modern power systems demand the active control of power flow and for this purpose Power flow controlling devices (PFCDs) are required. Distributed FACTS Controller (DPFC) is a part of FACTS family. DPFC offers equal control ability same as UPFC, comprising the adjustment of the internal angle of the machine and bus voltage includes line impedance. In addition to UPFC a new device evolved known as DPFC in which common DC link is eliminated that enables the exclusive working between the two converters which are shunt and the series. The Distributed-FACTS (D- FACTS) idea is adopt in the series converter scheme. The replacement of the high rating three phase series converter  with the multiple low rating single phase converters results in cost reduction and increases reliability greatly. The useful power transfer between the two converters which are shunt and series through common dc link in UPFC where as in DPFC in this the required power is transferred in the transmission line with three times of natural fundamental frequency. Where as in the new device no need of large voltage separation between the line and PFC Device is no requirement of high voltage isolation between because D-FACTS converters which are 1-ᴓ floating device with respect to the ground. Accordingly, In this paper we bring out the DPFC performance differences with different control techniques which are PI and Artificial Neural Network Controllers and bring with conclusion that ANN is a better control strategy compared to PI.
Review of IDS Develepment Methods in Machine Learning
Authors: Aburomman Abdulla , Ibne Reaz Mamun Bin
Published: March 2017

Due to the rapid advancement of knowledge and technologies, the problem of decision making is getting more sophisticated to address, therefore the inventing of new methods to solve it is very important. One of the promising directions in machine learning and data mining is classifier combination. The popularity of this approach is confirmed by the still growing number of publications. This review paper focuses mainly on classifier combination known also as combined classifier, multiple classifier systems, or classifier ensemble. Eventually, recommendations and suggestions have also included.
Node Cooperation to Avoid Early Congestion Detection Based on Cross-Layer for Wireless Ad Hoc Networks
Authors: Rahem Abdalrazak Tareq , Ismail Mahamod , Abdullah Nor Fadzilah , Balfaqih Mohammed
Published: March 2017

The resent application of wireless ad hoc networks (WANET) demands a high and reliable data load. The simultaneous transfer of large amounts of data different nearby sources to nearby destinations in a massive network under these circumstances results in the possibility of network congestion. Congestion is an extremely unwanted condition because it creates extra overhead to the already deeply loaded environment, which ultimately leads to resource exhaustion, and can lead to packet drops and retransmission at either the MAC or upper layers. We present a lightweight congestion control and early avoidance congestion control scheme, which can effective control congestion while keeping overhead to a minimum. This scheme is based on the Cross-layer between the MAC and network layers lead to early detection of congestion. With the help of node cooperation the sender node is triggered to find an alternative route based on TMT. This mechanism controls the network resources rather than the data traffic. Detailed performance results show enhancement in the throughput and packet delivery ratio, as well as a reduction in packet drop. Generally, network performance increases.
Design of Observer-Based Robust Power System Stabilizers
Authors: Soliman Hisham M. , Soliman Mahmoud
Published: March 2017

Power systems are subject to undesirable small oscillations that might grow to cause system shutdown and consequently great loss of national economy. The present manuscript  proposes two  designs for observer-based robust power system stabilizer (PSS) using Linear Matrix Inequality (LMI) approach to damp such oscillations. A model to describe power system dynamics for different loads is derived in the norm-bounded form. The first controller design is based on the derived model to achieve  robust stability against load variation. The design is based on a new Bilinear matrix inequality (BMI) condition. The BMI optimization  is solved interatively in terms of Linear Matrix Inequality (LMI) framework. The condition contains a symmetric positive definite full matrix to be obtained, rather than the commonly used block diagonal form. The difficulty in finding a feasible solution is thus alleviated. The resulting LMI is of small size, easy to solve. The second PSS design shifts the closed loop poles in a desired region so as to achieve a favorite  settling time and damping ratio via a non-iterative solution to a set of LMIs.  The approach provides a systematic way to design a robust output feedback PSS which  guarantees good dynamic performance for different loads. Simulation results based on single-machine and multi-machine power system models verify the ability of the proposed PSS to satisfy control objectives for a wide range of load conditions.
Statistical Based Audio Forensic on Identical Microphones
Authors: Kurniawan Fajri , Mohd. Rahim Mohd. Shafry , S. Khalil Mohammed , Khurram Khan Muhammad
Published: March 2017

Microphone forensics has become a challenging field due to the proliferation of recording devices and explosion in video/audio recording. Video or audio recording helps a criminal investigator to analyze the scene and to collect evidences. In this regards, a robust method is required to assure the originality of some recordings. In this paper, we focus on digital audio forensics and study how to identify the microphone model. Defining microphone model will allow the investigators to conclude integrity of some recordings. We perform statistical analysis on the recording that is collected from two microphones of the same model. Experimental results and analysis indicate that the signal of sound recording of identical microphone is not exactly same and the difference is up to 1% - 3%.
The Analysis of Student Colla borative Work Inside Social Learning Network Analysis Based on Degree and Eigenvector Centrality
Authors: Mansur Andi Besse Firdausiah , Yusof Norazah , Basori Ahmad Hoirul
Published: March 2017

Social learning network analysis is a potential approach to analyze the behaviour of students in collaborative work. However, most of the previous works focus on asynchronous discussion forum as the learning activity.  Very few of them are trying to analyze the students' collaborative work while using wiki e-learning. This paper proposes the degree centrality and eigenvector method for identifying the collaborative work of students while in wiki e-learning. The log data of the Moodle e-learning system is observed that records the students' activities and actions while using wiki.  The result shows that there is a close similarity between the degree centrality and the eigenvector. The result also reveals the students who obtain high outdegree values.  Furthermore, Agent_1 and Agent_12 represent the students who obtained high outdegree values, which mean these two nodes are acting as source providers that able to supply information and knowledge through the network. This result also strengthened by value of closeness and betweenness where Agent_1 and Agent_12 leading on this measurement. The high closeness value of Agent_1 and Agent_12 will lead into fast spreading information since they have fastest route and has the most direct route to the other node inside the network, thus collaborative work is easy to be initialized by these Agents. This work has successfully identified collaborative work of student. This finding is believed to bring enormous benefit on the e-learning system improvement in the future.
Hover Position of Quadrotor Based on PD-like Fuzzy Linear Programming
Authors: Iswanto Iswanto , Wahyunggoro Oyas , Imam Cahyadi Adha
Published: March 2017

The purpose of this paper is to present the altitude control algorithm for quadrotor to be able to fly at a particular altitude. Several previous researchers have conducted studies on quadrotor altitude by using PID control but there are problems in the overshoot and oscillation. To optimize the control, tunning on PID algorithm must be first conducted to determine proportional and derivative constants. Hence, the paper presents altitude control modification by using PID-like fuzzy without tuning. The PID algorithm is a control algorithm for linear systems. While, system to be controlled is a non-linear, so that linearization is needed by using equilibrium. The proposed algorithm is a modification of the PID algorithm used as an altitude control which enables quadrotor to be stable when hovering. The algorithm used is not PID algorithm with tuning using fuzzy, but this is a single input single output (SISO) control PID-like fuzzy linear programming. The result of the research shows that quadrotor can hover in a rapid raise time, steady state and settling time without performing overshoot and oscillation.
Development of a Measuring Sensory System Based on LabVIEW for Determining Elastic Proprieties of Solid Materials
Authors: Ezzouine Zakaryae , Nakheli Abdelrhani
Published: March 2017

This article develops also a measure and prototype to allow the acquisition of real time data for display, analysis, control and storage with a proposed test program for determining the model parameters. The aim is to be able to measure, and apply moment to a specimen, and collect data from the resulting deformation in the material. At the same time, the reliability of this test system has been proved by precision analysis and data processing for a simple test validation (metal wire). The force-deformation curves of solids materials in this tensile test are measured accurately in real time, to obtain the values of solid materials mechanical property parameters, The minimal change in length of the test Specimen that can be resolved by this system is 1µm, which yields the sensitivity comprised between 10-4µm and 10-5 µm. Based on the experience that compressive tensile test have the smallest statistical scatter and that they are simplest to carry out. The measuring device can improve the measuring efficiency and accuracy distinctly while has advantages of simple configuration, low cost and high stability.
Trust-Based Privacy for Internet of Things
Authors: Suryani Vera , Sulistyo Selo , Widyawan Widyawan
Published: March 2017

Internet of Things or widely known as IOT makes smart objects become active participants in the communication process between objects and their environment. IoT services that utilize Internet connection require solutions to a new problem: security and privacy. Smart objects and machine-to-machine communications in IOT now become interesting research, including that related to security. Privacy, which is a safe condition in which object is free from interference from other objects, is one of the important aspects in IOT. Privacy can be implemented using various ways for examples by applying encryption algorithms, restrictions on access to data or users, as well as implementing rules or specific policy. Trustable object selection is one technique to improve privacy. The process of selecting a trustable object can be done based on past activities or trust history of the object, also by applying a threshold value to determine whether an object is "trusted" or not. Some researchers have studied this approach. In this study, the selection processes of trustable objects are calculated using Modified Ant Colony algorithm. The simulation was performed and resulted in declining graphic trend but stabilized in certain trust value.
An IoT Framework for Addressing Parents Concerns about Safety of School Going Children
Authors: Gupta Poonam , Shah D D , Satyanarayana K V V
Published: March 2017

In this paper, we have proposed a novel application using Internet of things (IOT). This application is focused to address the concerns of the parents towards their school going kids. Mainly the concerns of the parents are to ensure the safety of their kids in school bus as well as at school premises. In this paper, we have tried to provide detailed technical implementation about how different sensing, communication technologies clubbing together provides a platform in terms of IoT, where proposed application can be implemented to ensure safety of school going children as it is the priority and concern for parents. In Proposed application, parents get notification when his child boards the bus for school and gets down the bus at home’s doorstep. Parents also get notification when child enters his Class Room first time in a day. Parents any time can access the location his child or school bus in which his child is travelling. In case of emergency, child can disseminate the signal to parents / Single point of contact (SPOC) at school to make them aware about emergency.
The Contour Extraction of Cup in Fundus Images for Glaucoma Detection
Authors: Septiarini Anindita , Hamdani Hamdani , Khairina Dyna Marisa
Published: March 2017

Glaucoma is the second leading cause of blindness in the world; therefore the detection of glaucoma is required. The detection of glaucoma is used to distinguish whether a patient's eye is normal or glaucoma. An expert observed the structure of the retina using fundus image to detect glaucoma. In this research, we propose feature extraction method based on cup area contour using fundus images to detect glaucoma. Our proposed method has been evaluated on 44 fundus images consisting of 23 normal and 21 glaucoma. The data is divided into two parts: firstly, used to the learning phase and secondly, used to the testing phase. In order to identify the fundus images including the class of normal or glaucoma, we applied Support Vector Machines (SVM) method. The performance of our method achieves the accuracy of 94.44%.
Study on Improving the Network Life Time Maximazation for Wireless Sensor Network using Cross Layer Approach
Authors: R Bhandari Rajiv , Rajasekhar K
Published: March 2017

In recent the espousal of Wireless Sensor Networks has been broadly augmented in numerous divisions. Battery operated Sensor nodes in the wireless network accomplish main task of capturing and responding to the surroundings. The lifetime of the network depends on the energy consumption of the sensor nodes. This paper contributes the survey on how the energy consumption should be managed for maximizing the life time of network and how to improve the efficiency of Network by using Cross layer architecture. The traditional MAC Layer, Network Layer & Transport for WLAN having their own downsides just by modifying those we can achieve the network life time maximization goal. This paper represents analytical study for Energy efficiency by modifying Scheduling algorithm, by modifying traditional AODV routing algorithm for efficient packet transmission and by effectively using TCP for End to End Delivery of Data.
Evaluation of the Forward-Backward Sweep Load Flow Method using the Contraction Mapping Principle
Authors: Issicaba Diego , Coelho Jorge
Published: March 2017

This paper presents an assessment of the forward-backward sweep load flow method to distribution system analysis. The method is formally assessed using fixed-point concepts and the contraction mapping theorem. The existence and uniqueness of the load flow feasible solution is supported by an alternative argument from those obtained in the literature. Also, the closed-form of the convergence rate of the method is deduced and the convergence dependence of loading is assessed. Finally, boundaries for error values per iteration between iterates and feasible solution are obtained. Theoretical results have been tested in several numerical simulations, some of them presented in this paper, thus fostering discussions about applications and future works.
The Study Methods of Increase Efficiency Algorithms Pulse width Modulation in AC Electric Drives
Authors: Y. Vasilev Bogdan
Published: March 2017

In the paper describes the AC electric drive, which consists of the induction motor and the semiconductor converter. Structure of the frequency converter, which includes a three-phase bridge inverter on based fully controlled transistors, is considered. The algorithm of pulse width modulation, which used in the majority of the electric drives, is discussed. The characteristics and shortcomings of the algorithm is shows. Algorithmically methods to improve the efficiency of the inverter – promodulation control signal. The efficiency of this method in different variations is given. The level electromagnetic compatibility inverter and efficiency various control algorithms are analyzed. The conclusions about feasibility of using the method promodulation.
Microruban Dipole Antenna for RFID Applications at 2.45 GHz
Authors: Berrich Loubna , Zenkouar Lahbib
Published: March 2017

Radio Frequency Identification (RFID) is a technology used mainly to identify tagged items or to track their locations. The most used antennas for RFID application are planar dipoles. For antenna design, it is necessary that the antenna has an impedance value equal to the conjugate of the impedance of the integrated circuit CI. To have a good adaptation allowing the maximum power transfer, there are several techniques. In this work we focus to the adaptation technical T-match which is based on the insertion of a second folded dipole in the center of the first dipole. This technique is modeled by an equivalent circuit to calculate the size of the folded dipole to have new input impedance of the antenna equal to the conjugate of the impedance of the IC. We also look to present a conceptual and technological approach of new topologies of linear dipoles. We proceeded to fold at right angles of the radiating strands in order to explore other topologiesof type  L and Z. The interest of this microstrip folded dipole is their effectiveness to achieve coverage of Blind directions. The results obtained by the platform Ansoft HFSS, allowed us to obtain a quasi-uniform radiation patterns and the reflection coefficients that exceed -37 dB.
Localization of Cooperative WSN using Distributed PSO with Optimum References
Authors: Janapati Ravichander , Balaswamy Ch. , Soundararajan K.
Published: March 2017

In indoor environment WSN nodes are deployed randomly and do not know the accurate position. Find the node position with the help of anchor nodes is known as localization. CRB algorithm selects the best anchor nodes which gives high accuracy. In this paper distributed PSO algorithm with optimum selection of reference nodes using CRB is proposed to find accurate node position. The proposed method performs better in comparison with other algorithms like PSO, RLS, LMS and GPS in terms of position accuracy, latency and complexity.
Design and Implementation of Wheelchair Controller Based Electroencephalogram Signal using Microcontroller
Authors: Arzak M. I. , Sunarya U. , Hadiyoso S.
Published: March 2017

Wheelchair is a medical device that can help patients, especially for persons with physical disabilities. In this research has designed a wheelchair that can be controlled using brain wave. Mind wave device is used as a sensor to capture brain waves. Fuzzy method is used to process data from mind wave. In the design was used a modified wheelchair (original wheelchair modified with addition dc motor that can be control using microcontroller ). After processing data from mindwave using fuzzy method, then microcontroller ordered dc motor to rotate.The dc motor connected to gear of wheelchair using chain. So when the dc motor rotated the wheelchair rotated as well.  Controlling of DC motor used PID control method. Input encoder was used as feedback for PID control at each wheel.From the experimental results concentration level data of the human brain waves can be used to adjust the rate of speed of the wheelchair. The level accuracy of respons Fuzzy method ton system obtained by devide total true respons data with total tested data and the result is 85.71 %.  Wheelchairs can run at a maximum speed of 31.5 cm/s when the battery voltage is more than 24.05V. Moreover, the maximum load of wheelchair is 110 kg.
Finding the Optimal Value for Threshold Cryptography on Cloud Computing
Authors: Janratchakool Weena , Boonkrong Sirapat , Smanchat Sucha
Published: March 2017

The objective of using threshold cryptography on cloud environment is to protect the keys, which are the most important elements in cryptographic systems. Threshold cryptography works by dividing the private key to a number of shares, according to the number of virtual machines, then distributing them each share to each virtual machine. In order to generate the key back, not all the shares are needed. Howerver, the problem is that there has been no research attemping to find a suitable threshold value for key reconstruction. Therefore, this paper presented a guildline designed and implemented that can assist to choose such value. The experiment was setup using CloudSim to simulate cloud environment and collecting time taken in key distribution and key reconstruction process to achieve the optimal threshold value.
Image Retrieval with Relevance Feedback using SVM Active Learning
Authors: Ngo Giang Truong , Ngo Tao Quoc , Nguyen Dung Duc
Published: March 2017

In content-based image retrieval, relevant feedback is studied extensively
to narrow the gap between low-level image feature and high-level semantic
concept. In general, relevance feedback aims to improve the retrieval
performance by learning with user's judgements on the retrieval results.
Despite widespread interest, but feedback related technologies are often
faced with a few limitations. One of the most obvious limitations is often
requiring the user to repeat a number of steps before obtaining the
improved search results. This makes the process inefficient and tedious
search for the online applications. In this paper, a effective feedback
related scheme for content-based image retrieval is proposed. First, a
decision boundary is learned via Support Vector Machine to filter the
images in the database. Then, a ranking function for selecting the most
informative samples will be calculated by defining a novel criterion that
considers both the scores of Support Vector Machine function and similarity
metric between the "ideal query" and the images in the database. The
experimental results on standard datasets have showed the effectiveness
of the proposed method.
Overvoltage Effects on Ground Grid Systems of Single and Two Neighboring High Voltage Substations
Authors: Luewattana Krung , Pruksanubal Aphibal
Published: March 2017

The power networks with reliable transmission and distribution systems require high voltage substations with effective ground grid systems. Therefore, this study aimed to analyze the effects of overvoltage on ground grid systems within high voltage substations in two cases, including a single substation and the two neighboring substations, by using ATP/EMTP and ANSYS softwares. The simulations were performed to show both graphs and 3D results when the fault current flowed into the ground grids of substations at various positions. In case of the single high voltage substation, the overvoltage was highest when the fault current was injected at the corner of ground grid. However, in case of two neighboring high voltage substations, the levels of overvoltage were similar between that caused by injecting the fault current at the center and at the corner of ground grid. The simulation showed that overvoltage which occurring at the ground grid of high voltage substation A could permeate to the ground grid of nearby high voltage substation B, which nevertheless depending on the how the fault current was injected at different spots. The data from these simulations and analysis can be useful for future designs of ground grid systems with high reliability.
Combination a Skeleton Filter and Reduction Dimension of Kernel PCA Based on Palmprint Recognition
Authors: Kusban Muhammad , Susanto Adhi , Wahyunggoro Oyas
Published: March 2017

Palmprint identification is part of biometric recognition, which attracted many researchers, especially when fusion with face identification that will be applied in the airport to hasten knowing individual identity. To accelerate the process of verification feature palms, dimension reduction method is the dominant technique to extract the feature information of palms.The mechanism will boost if the ROI images are processed prior to get normalize image enhancement.In this paper with three sample input database, a kernel PCA method used as a dimension reduction compared with three others and a skeleton filter used as a image enhancement method compared with six others. The final results show that the proposed method successfully achieve the target in terms of the processing time of $ 0.7415 $ second, the EER performance rate of 0.19 % and the success of verification process about 99,82 %.
Modelling and Predicting of the Characteristics of a Photovoltaic Generator on a Horizontal and Tilted Surface
Authors: Elyaqouti Mustapha , Bouhouch Lahoussine , Ihlal Ahmed
Published: March 2017

In the present paper, we will attempt to predict the Ipv-Vpv output characteristic of a photovoltaic generator (PVG) and consequently the generated electric power. This will be possible through modeling, extracting the electrical parameters of the PVG under study and also, by estimating the global incident solar radiation, on a surface, first horizontally, and then tilted to a given angle. Mathematical models developed in Matlab, to characterize the studied PVG are validated by experimental data of the PVG manufacture. While models associated with global radiation are validated by measurements taken by the meteorological station installed on the laboratory site ERTAIER (Team for Research in Technology and Advanced Engineering of Renewable Energies) of Higher School of Technology Agadir (ESTA).

 
Three Patterns Programmable Russian Form Functional Electrical Stimulator
Authors: Orand Abbas , Tanino Genichi , Miyasaka Hiroyuki , Takeda Kotaro , Sonoda Shigeru
Published: March 2017

In this paper, a programmable, multi-pattern, wide frequency and duty cycle range electrical stimulator is presented. Using a programmable micro-controller, two waves of carrier and modulating sources are produced. By modulating the two sources, 3 bi-phasic charge-balanced rectangular, triangular and sinusoidal stimulating patterns are produced. The frequency range of the carrier is fixed at 2.5 kHz and the carrier source frequency can be adjusted between 1 and 500 Hz. The duty cycle of both sources can be adjusted between 10% and 90%.
A Cloud Based Secure Voting System using Homomorphic Encryption for Android Platform
Authors: Ranjan Manish , Mondal Ayub Hussain , Saikia Monjul
Published: March 2017

Cloud based service provider are at its top of its services for various applications, as their services are very much reachable from anywhere anytime in current days. It is responsibility of the company that the Cloud storage is owned and maintained by themselves keeping the data available and accessible, and the physical environment protected and running. Could storage provider seem to be uncertain of confidentiality in many cases, as we need to limit ourselves on trust to a third party. Keeping our sensitive data ready to access any time anywhere with preventing any information leakage is a challenging task. Cryptography in this scenario plays an important role, providing security for information to protect valuable information resources on intranets, Internet and the cloud. In addition, Homomorphic cryptosystem is a form of Cryptography where some specific computation can be performed over the cipher text producing a resultant cipher text which, when decrypted, equals the result of operations carry out on the plaintext. With help of this unique property of homomorphism cryptography we proposed a system to keep sensitive information in encrypted form in the cloud storage/service provider and used those data as whenever we require. The scheme proposed here is designed for a secure online voting system on Android platform and voted information is encrypted and stored those in the cloud.
Face Recognition using Multi Region Prominent LBP Representation
Authors: Konda Srinivasa Reddy , Kumar V Vijaya , Krishna Venkata
Published: March 2017

Various face recognition methods are derived using local features among them the Local Binary Pattern (LBP) approach is very famous. The histogram techniques based on LBP is a complex task. Later Uniform Local Binary Pattern (ULBP) is derived on LBP, based on the bitwise transitions and ULBP’s are treated as the fundamental property of texture. The ULBP approach treated all Non-Uniform Local Binary Patterns’ (NULBP) into one miscellaneous label. Recently we have derived Prominent LBP (PLBP), Maximum PLBP (MPLBP) and Smallest PLBP (SPLBP). The PLBP consists of the majority of the ULBP’s and some of the NULBP’s. The basic disadvantage of these various variants of LBP’s  is they are basically local approaches and completely failed in representing features derived from large regions or macrostructures, which are very much essential for faces. This paper derives PLBP’s on the large region. The rectangular region of this paper is assumed with a size of multiples of three and PLBPs are evaluated on dividing each region into multiple regions. The proposed Multi Region-PLBP (MR-PLBP) approach is tested on three facial databases namely Yale, Indian and AT&T ORL. The experimental results show the proposed approach significantly outperforms the other LBP based face recognition methods.
Simulation and Performance Evaluation of Shunt Hybrid Power Filter for Power Quality Improvement Using PQ Theory
Authors: Balasubramanian R. , Palani S.
Published: March 2017

This work proposes the design of shunt hybrid filter using instantaneous power theory to improve the power quality and simulation has been carried out for 3 phase distribution system feeding different types of non linear loads. The proposed filter consists of parallel combination of 5th and 7th tuned selective harmonic elimination passive filters, which is connected in series with a small rating IGBTs based voltage source inverter. In this work, principle of compensation and filtering behavior of the system has been discussed in detail. Instantaneous real and reactive power theory based controller has been designed to estimate the reference current from the distorted current. In order to reduce the harmonics, generated reference currents are tracked by voltage source inverter using hysteresis band current controller. The performance of the hybrid scheme is evaluated for various nonlinear loads using Matlab/ Simulink tool. The detailed analysis has been carried out on harmonics reduction and DC bus voltage regulation and the simulation result ensures the feasibility of suggested control strategy. The proposed topology improves the filtering performance of the passive filter in hybrid scheme.
FPGA Hardware Realization: Addition of Two Digital Signals Based on Walsh Transforms
Authors: Zulfikar Zulfikar , Abbasi Shuja A , Alamoud Abdul Rahman M
Published: March 2017

This paper presents hardware realization of addition of two digital signals based on Walsh transforms and inverse Walsh transforms targeted to the Xilinx FPGA Spartan 3 board. The realization utilizes Walsh Transform to convert the input data to frequency domain and the inverse Walsh transform to reconvert the data from frequency domain. The designed system is capable of performing addition, subtraction, multiplication and Arbitrary Waveform Generation (AWG). However, in the present work, the hardware realization of addition only has been demonstrated. The Clock frequency for realization into the board is supplied by an external function generator. Output results are captured using a logic analyzer. Input data to the board (system) is passed manually through the available slide switches on-board.
Fault Diagnosis and Reconfiguration of Multilevel Inverter Switch Failure-A Performance Perspective
Authors: Manjunath T.G. , Kusagur Ashok
Published: March 2017

Multilevel Inverters (MLI) gains importance in Distribution systems, Electrical Drive systems, HVDC systems and many more applications. As Multilevel Inverters comprises of number of power switches the fault diagnosis of MLI becomes tedious. This paper is an attempt to develop and analyze the fault diagnosis method that utilizes Artificial Neural Network to get it trained with the fault situations. A performance analysis of Genetic Algorithm (GA) and the Modified Genetic Algorithm (MGA), which optimizes the Artificial Neural Network (ANN) that trains itself on the fault detection, and reconfiguration of the Cascaded Multilevel Inverters (CMLI) is attempted. The Total Harmonic Distortion (THD) occurring due to switch failures or driver failures occurring in the CMLI is considered for this comparative analysis. Elapsed time of recovery, Mean Square Error (MSE) and the computational budgets of ANN are the performance parameters considered in this comparative analysis. Optimization is involved in the process of updating the weight and the bias values in the ANN network.  Matlab based simulation is carried out and the results are obtained and tabulated for the performance evaluation. It was observed that Modified Genetic Algorithm performed better than the Genetic Algorithm while optimizing the ANN training.
Data transmission in Hybrid Distributed Environment
Authors: Teykhrib Anton Pavlovich
Published: March 2017

This article discusses a hybrid distributed environment including two levels of nodes: the first level which has high quality channels between the nodes, and the second one in which the nodes are directly involved in communication and the communication is performed through the first-level nodes. For the indicated distribution scheme, the questions of selection of the best path between the first-level nodes are solved based on such communication channel characteristics as delay in packet transmission, jitter in transmission, packet loss in transmission, and choosing a method for data transmission through the selected best path: protocols of transport and network layers have been compared, and the use of network layer has been preferred.
Minimizing Energy Consumption by Task Consolidation in Cloud Centers with Optimized Resource Utilization
Authors: Gourisaria Mahendra Kumar , Patra S. S. , Khilar P. M.
Published: March 2017

Cloud computing is an emerging field of computation. As the data centers consume large amount of power, it increases the system overheads as well as the carbon dioxide emission increases drastically. The main aim is to maximize the resource utilization by minimizing the power consumption. However, the greatest usages of resources does not mean that there has been a right use of energy.  Various resources which are idle, also consumes a significant amount of energy. So we have to keep minimum resources idle. Current studies have shown that the power consumption due to unused computing resources is nearly 1 to 20%. So, the unused resources have been assigned with some of the tasks to utilize the unused period. In the present paper, it has been suggested that the energy saving with task consolidation which has been saved the energy by minimizing the number of idle resources in a cloud computing environment. It has been achieved far-reaching experiments to quantify the performance of the proposed algorithm. The same has also been compared with the FCFSMaxUtil and Energy aware Task Consolidation (ETC) algorithm. The outcomes have shown that the suggested algorithm surpass the FCFSMaxUtil and ETC algorithm in terms of the CPU utilization and energy consumption.
WWLLN Data Cluster Analysis Methods for Lightning-Caused Forest Fires Monitoring
Authors: Nikolay Baranovskiy , Svetlana Krechetova , Marina Belikova , Anton Perelygin
Published: March 2017

Storm activity is the main reason for forest fires to occur in remote forested territories. The current article presents the results for cluster analysis of WWLLN data on lightning discharges. It provides the description for clusterization algorithms of lightning discharges over the controlled territory. Research area is Timiryazevskiy forestry of the Tomsk region (Siberia, Russia). We analyzed the applicability of cluster analysis results for monitoring of the forest fire danger caused by storm activity. As a result of the conducted research, we established that the following characteristics of storm activity can be included in deterministic-probabilistic criterion to assess the forest fire danger. The article gives the recommendations how to create new generation information-computer and geoinformation systems for monitoring of the forest fire danger caused by storm activity in the controlled forested territory.
EEG Based Eye State Classification using Deep Belief Network and Stacked AutoEncoder
Authors: Narejo Sanam , Pasero Eros , Kulsoom Farzana
Published: March 2017

A Brain-Computer Interface (BCI) provides an alternative communication interface between the human brain and a computer. The Electroencephalogram (EEG) signals are acquired, processed and machine learning algorithms are further applied to extract useful information.  During  EEG acquisition,   artifacts  are induced due to involuntary eye movements or eye blink, casting adverse effects  on system performance. The aim of this research is to predict eye states from EEG signals using Deep learning architectures and present improved classifier models. Recent studies reflect that Deep Neural Networks are trending state of the art Machine learning approaches. Therefore, the current work presents the implementation of  Deep Belief Network (DBN) and Stacked AutoEncoders (SAE) as Classifiers with encouraging performance accuracy.  One of the designed  SAE models outperforms the  performance of DBN and the models presented in existing research by an impressive error rate of 1.1% on the test set bearing accuracy of 98.9%. The findings in this study,  may provide a contribution towards the state of  the  art performance on the problem of  EEG based eye state classification.
The Impact of Tunneling on the Subthreshold Swing in Sub-20 nm Asymmetric Double Gate MOSFETs
Authors: Jung Hak Kee , Dimitrijev Sima
Published: March 2017

This paper analyzes the subthreshold swing in asymmetric double gate MOSFETs with sub-20 nm channel lengths. The analysis of the carrier transport in the subthreshold region of these nano scaled MOSFET includes tunneling as an important additional mechanism to the thermionic emission. It is found that the subthreshold swing is increasing due to tunneling current and that the performance of nano scaled MOSFETs is degraded. The degradation of the subthreshold swing due to tunneling is quantified using analytical potential distribution and Wentzel–Kramers–Brillouin (WKB) approximation in this paper. This analytical approach is verified by two dimensional simulation. It is shown that the degradation of subthreshold swing increases with both reduction of channel length and increase of channel thickness. We also show that the subthreshold swing is increasing in case of different top and bottom gate oxide thicknesses.
Effective Computer-Assisted Automatic Cervical Vertebrae Extraction with Rehabilitative Ultrasound Imaging by using K-means Clustering
Authors: Lee Hae-Jung , Song Doo Heon , Kim Kwang Baek
Published: March 2017

Neck pain is one of most common musculoskeletal condition resulting in significant clinical, social and economic costs. Muscles around cervical spine including deep neck flexors play a key role to support and control its stability, thus monitoring such muscles near cervical vertebrae is important. In this paper, we propose a fully automated computer assisted method to detect cervical vertebrae with K-means pixel clustering from ultrasonography. The method also applies a series of image processing algorithms to remove unnecessary organs and noises in the process. The experiment verifies that our approach is consistent with human medical experts’ decision to locate key measuring point for muscle analysis and successful in detecting cervical vertebrae accurately – successful in 48 out of 50 test cases (96%).