bluuebunny/crossref_metadata_2025 huggingface dataset:
Insight on Effectiveness of Frequently Exercised PQ Classification Techniques
Authors: Vighneshwari BDevi , Neela R.
Published: October 2019

The growing demands of global consumer market in green energy system have opened the doors for many technologies as well as various sophisticated electrical devices for both commercial and domestic usage. However, with the increasing demands of energy and better quality of services, there is a significant increase in non-linearity in load distribution causing potential effect on the Power Quality (PQ). The harmful effects on PQ are various events e.g. sag, swell, harmonics etc that causes significant amount of system degradation. Therefore, this paper discusses various significant research techniques pertaining to the PQ disturbance classification system introduced by the authors in the past and analyzes its effectiveness scale in terms of research gap. The paper discusses some of the frequently exercised PQ classification techniques from the most relevant literatures in order to have more insights of the techniques.
Adaptive Adjustment of PSO Coefficients Taking the Notion from the Bee Behavior in Collecting Nectar
Authors: Fadavi Abbas , Faez Karim , Famili Zeinab
Published: October 2019

In particle swarm optimization, a set of particles move towards the global optimum point according to their experience and experience of other particles. Parameters such as particle rate, particle best experience, the best experience of all the particles and particle current position are used to determine the next position of each particle. Certain relationships received the input parameters and determined the next position of each particle. In this article, the relationships are accurately assessed and the amount of the effect of input parameters is horizontally set. To set coefficients adaptively, the notion is taken from bee behavior in collecting nectar. This method was implemented on software and examined in the standard search environments. The obtained results indicate the efficiency of this method in increasing the rate of convergence of particles towards the global optimum.
Protection Coordination and Anti Islanding Protection Solution for Biomass Power Plant Connected on Distribution Network
Authors: Nikolovski Srete N , Vukobratović Marko , Majdandzic Ljubomir
Published: October 2019

Protection coordination as well as anti-island protection play significant role in the process of biomass power plant connection on the distribution network. Distribution generation island operation in Croatia is unacceptable according to the existing National grid code Paper presents a protection coordination of all passive protections used in the real biomass power plant and connected distriubution network feeder. Short-circuits three phase, two phase and single line to ground faults and generator islanding simulations have been performed and simulated in the time domain at the different network  locations using DIgSILENT Power Factory software. The time-current plots coordination of protective devices are made using Smart PDC module in Easy Power Protector software tool.
Optimum Permanent Magnets Configuration in Flat-Quasi Linear Permanent Magnet Generators
Authors: Wijaya Fransisco Danang , Azhari Budi , Stephanus Harnoko
Published: October 2019

Flat-quasi type of linear permanent magnet generators (LPMGs) have been considered to be applied for several applications, such for wave energy conversion and free piston combustion engine. One of the important issues concerning LPMG is the permanent magnets configuration, due to its effects to the generator’s excitation performance. In this paper, a 1 kW flat-quasi LPMG would be designed and built. During the process, optimum permanent magnets configuration was required and researched. The optimum configuration considered the output power and resulted cogging force. Invetigation was then conducted by modifying several variables, including poles’ arrangement, pole length, number of pole, and pole skewing angle. The modification constraints were total permanent magnets’ volume and generator dimension. The results showed that permanent magnet configuration with halbach arrangement, pole length equals 55% of the slot pitch length, and 61.19o skewing angle produced the optimum output values.
Fault Diagnosis and Reconfiguration of Multilevel Inverter Switch Failure-A Performance Perspective
Authors: Manjunath T.G. , Kusagur Ashok
Published: October 2019

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.
A Modified ABC Algorithm for Solving Non-Convex Dynamic Economic Dispatch Problems
Authors: Hardiansyah Hardiansyah
Published: October 2019

In this paper, a modified artificial bee colony (MABC) algorithm is presented to solve non-convex dynamic economic dispatch (DED) problems considering valve-point effects, the ramp rate limits and transmission losses. Artificial bee colony algorithm is a recent population-based optimization method which has been successfully used in many complex problems. A new mutation strategy inspired from the differential evolution (DE) is introduced in order to improve the exploitation process. The feasibility of the proposed method is validated on 5 and 10 units test system for a 24 h time interval. The results are compared with the results reported in the literature. It is shown that the optimum results can be obtained more economically and quickly using the proposed method in comparison with the earlier methods.
Power Quality Enhancement of Integration Photovoltaic Generator to Grid under Variable Solar Irradiance Level using MPPT-Fuzzy
Authors: Amirullah Amirullah , Kiswantono Agus
Published: October 2019

The paper presents power quality enhancement on low voltage of three phase grid caused by PV generator integration under variabel solar irradiance level on constant temperature and load. MPPT Fuzzy helps to generate duty cycle to control DC/DC boost converter of PV generators. This model was expected to improve power quality due to unbalance voltage and current, low voltage and current harmonics, and low input power factor. There were eigth scenarios PV generator connected to three phase grid using MPPT Fuzzy and compared with MPPT P and O. The research results that application of two methods on different irradiance and PV generator integration level produces unbalanced voltage value stable at 0%. At the same conditions, the use of MPPT Fuzzy results unbalanced current was greater than MPPT P and O. On solar irradiance level fixed, the greater number of PV generator connected to three-phase grid, then value of average voltage and current harmonics (THD) will increases. At the level of solar radiation increases, average grid voltage and current THD also have increased. The average grid voltage and current THD was reduced after using MPPT Fuzzy. The application of MPPT Fuzzy was able to enhance profile of grid voltage and current THD due to integration of a number of PV generator to three phase grid corresponding with IEEE Standard 519-1992. MPPT Fuzzy was capable to improve input power factor better than MPPT P and O.
Time Independent Signature Verification using Normalized Weighted Coefficients
Authors: Singhal Manas , Trikha Manish , Dutta Maitreyee
Published: October 2019

Signature verification is one of the most widely accepted verification methods in use. The application of handwritten signatures includes the banker’s checks, the credit and debit cards issued by banks and various legal documents. The time factor plays an important role in the framing of signature of an individual person. Signatures can be classified as: offline signature verification and online signature verification. In this paper a time independent signature verification using normalized weighted coefficients is presented. If the signature defining parameters are updated regularly according to the weighted coefficients, then the performance of the system can be increased to a significant level. Results show that by taking normalized weighted coefficients the performance parameters, FAR and FRR, can be improved significantly.
Improved Capacity Image Steganography Algorithm using 16-Pixel Differencing with n-bit LSB Substitution for RGB Images
Authors: Arya Meenakshi S , Rani Meenu , Singh Bedi Charndeep
Published: October 2019

With the intrusion of internet into the lives of every household and terabytes of data being transmitted over the internet on daily basis, the protection of content being transmitted over the internet has become an extremely serious concern. Various measures and methods are being researched and devised everyday to ensure content protection of digital media. To address this issue of content protection, this paper proposes an RGB image steganography based on sixteen-pixel differencing with n-bit Least Significant Bit (LSB) substitution. The proposed technique provides higher embedding capacity without sacrificing the imperceptibility of the host data. The image is divided into 4×4 non overlapping blocks and in each block the average difference value is calculated. Based on this value the block is classified to fall into one of four levels such as, lower, lower-middle, higher-middle and higher. If block belongs to lower level then 2-bit LSB substitution is used in it. Similarly, for lower-middle, higher-middle and higher level blocks 3, 4, and 5 bit LSB substitution is used. In our proposed method there is no need of pixel value readjustment for minimizing distortion. The experimental results show that stego-images are imperceptible and have huge hiding capacity.
On Usable Speech Detection by Linear Multi-Scale Decomposition for Speaker Identification
Authors: Ghezaiel Wajdi , Ben Slimane Amel , Ben Braiek Ezzedine
Published: October 2019

Usable speech is a novel concept of processing co-channel speech data. It is proposed to extract minimally corrupted speech that is considered useful for various speech processing systems. In this paper, we are interested for co-channel speaker identification (SID). We employ a new proposed usable speech extraction method based on the pitch information obtained from linear multi-scale decomposition by discrete wavelet transform. The idea is to retain the speech segments that have only one pitch detected and remove the others. Detected Usable speech was used as input for speaker identification system. The system is evaluated on co-channel speech and results show a significant improvement across various Target to Interferer Ratio (TIR) for speaker identification system.
The Study Methods of Increase Efficiency Algorithms Pulse width Modulation in AC Electric Drives
Authors: Y. Vasilev Bogdan
Published: October 2019

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.
Performance Enhancement of TCP Friendly Rate Control Protocol over Wired networks
Authors: Reddy N. Ramanjaneya , Pakanati Chenna Reddy , Padmavathamma M.
Published: October 2019

One of the main aims of transport layer protocol is achieving best throughput without any congestion or reduced congestion.  With rapid growing application needs and with increasing number of networks in Internet, there is a primary need to design new protocols to transport layer.  To transmit multimedia applications, one of the suitable congestion control mechanisms in transport layer is TCP Friendly Rate Control Protocol (TFRC).  It controls congestion based on its equation. However, every packet requires an acknowledgement in TFRC. It creates congestion in the network when the transmitted data is very large, which results in reduced throughput. This paper aims to increase the throughput when the transmitted data is large with minimal congestion by reducing the number of acknowledgements in the network.  We modified some fixed parameters in the TFRC equation. The results show the increased throughput with minimal congestion.
Data transmission in Hybrid Distributed Environment
Authors: Teykhrib Anton Pavlovich
Published: October 2019

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.
A Cloud Based Secure Voting System using Homomorphic Encryption for Android Platform
Authors: Ranjan Manish , Mondal Ayub Hussain , Saikia Monjul
Published: October 2019

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.
Structural Equation Modeling to Analyze Person-Organization Fit and Organizational Effectiveness
Authors: Teimouri Hadi , Jenab Kouroush , Rafei Somaye , Yonespoor Maryam
Published: October 2019

Efficient management and leadership can be achieved via precise planning for selection, recruitment, and optimization of the labor force. One of the major goals in labor force selection and recruitment is the fit between people and an organization. This phenomenon is known as person-individual fit. In this research, the authors collected data via a survey aimed at exploring the relationship between person-individual fit and organizational effectiveness at the University of Isfahan. The research hypotheses were tested through variables such as environmental congruence, KSA (knowledge/skills/abilities) congruence, goals congruence, values congruence, and personality congruence, as dimensions of person-individual fit. The aim of this study is developing and practical and from the procedure implemented is introducing-analyzing. The sample studied in this study is the mangers and employers of the university in Isfahan. A stratified random sampling method was used based the Morgan table and a sample size of 120 was chosen from among 150 persons. The results revealed that there is a significant relationship between dimensions of person-individual fit and organizational effectiveness.
ISAR Image Classification with Wavelet and Watershed Transforms
Authors: Mamatha B. , Valli Kumar V.
Published: October 2019

Inverse Synthetic Aperture Radar images are playing a significant role in classification of sea and air targets. First we acquire the ISAR images of targets using a sensor like radar and extract the characteristics of targets from the ISAR images in the form of feature vectors. The computed feature vectors are used for classification of targets. In this work, widely used and efficient segmentation tool Watershed transform and the multi resolution technique wavelet transform are explored to derive the target features. An artificial neural network based classifier is used for classification. The Wavelet analysis divides the information of an image into approximation and detail sub signals. The approximate and three detail sub signal values are taken as feature vectors and given as input to the classifier for ship ISAR image classification. The widely used segmentation technique, Watershed transform is applied to the ISAR images. The wavelet coefficients are computed for the segmented ISAR images and used as feature vectors for classification of the ISAR images. Also, the statistical moments mean and standard deviation are computed for the color ISAR images itself, taken in RGB format. These statistical color moments are used as feature vector.  The classification accuracy is compared for the feature vectors.
Model-based Automatic Segmentation of Ascending Aorta from Multimodality Medical Data
Authors: Seada Noha , Hamad Safwat , Mostafa Mostafa G. M.
Published: October 2019

Automatic Ascending Aorta Segmentation is one of the important steps towards automatic segmentation of the whole cardiac tree. This paper presents a novel approach for the automatic segmentation of the ascending aorta from two imaging modalities: CTA (Computed Tomography Angiography) and PC-MRI (Phase-Contrast Magnetic Resonance Images). The novel approach is an algorithm that works without the need for setting manual seed points or applying preprocessing steps or setting a region of interest. Instead, the proposed algorithm automatically detects and segments the ascending aorta using an ascending aorta model built from its anatomical features. The proposed segmentation algorithm begins with aorta detection through features model fitting augmented with Hough transform, where the ascending aorta is identified from the descending aorta and any other circular structures based on the proposed model. After detection, the whole ascending aorta is segmented up from the aortic arch down to the ostia points using a novel automatic seeded region growing algorithm. The proposed algorithm is fully automatic, works in real-time and robust as parameters used are the same for all the tested datasets. The detection and segmentation of the ascending aorta succeeded in all test cases acquired from the two imaging modalities; proving the robustness of the proposed ascending aorta model and algorithm for the automatic segmentation process even on data from different modalities and different scanner types. The accuracy of the segmentation has a mean Dice Similarity Coefficient (DSC) of 94.72% for CTA datasets and 97.13% for PC-MRI datasets.
Image Retrieval with Relevance Feedback using SVM Active Learning
Authors: Ngo Giang Truong , Ngo Tao Quoc , Nguyen Dung Duc
Published: October 2019

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.
Low Common-Mode Gain Instrumentation Amplifier Architecture Insensitive to Resistor Mismatches
Authors: Abidin Zainul , Tanno Koichi , Mago Shota , Tamura Hiroki
Published: October 2019

In this paper, an instrumentation amplifier architecture for biological
signal is proposed. First stage of conventional IA architecture was modified
by using fully balanced differential difference amplifier and evaluated by
using 1P 2M 0.6μm CMOS process. From HSPICE simulation result, lower
common-mode voltage can be achieved by proposed IA architecture.
Actual fabrication was done and six chips were evaluated. From the evaluation result, average common-mode gain of proposed IA architecture
is 10.84 dB lower than that of conventional one without requiring
well-matched resistors. Therefore, the proposed IA architecture
is suitable for biological signal processing.
Convergence Evaluation of a Load Flow Method based on Cespedes' Approach to Distribution System Analysis
Authors: Issicaba Diego , Coelho Jorge
Published: October 2019

This paper evaluates the convergence of a load flow method based on Cespedes' formulation to distribution system steady-state analysis. The method is described and the closed-form of its convergence rate is deduced. Furthermore, convergence dependence of loading and the consequences of choosing particular initial estimates are verified mathematically. All mathematical results have been tested in numerical simulations, some of them presented in the paper.
Minimizing Energy Consumption by Task Consolidation in Cloud Centers with Optimized Resource Utilization
Authors: Gourisaria Mahendra Kumar , Patra S. S. , Khilar P. M.
Published: October 2019

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.
Performance Analysis of Adaptive Filter Channel Estimated MIMO OFDM Communication System
Authors: Pyla Srinu , Padma Raju K , Subrahmanyam N Bala
Published: October 2019

Advanced Communication Systems are wideband systems to support multiple applications such as audio, video and data so and so forth. These systems require high spectral efficiency and data rates. In addition, they should provide multipath fading and inter-symbol interference (ISI) free transmission. Multiple input multiple output orthogonal frequency division multiplexing (MIMO OFDM) meets these requirements Hence, MIMO-OFDM is the most preferable technique for long term evaluation advanced (LTE-A). The primary objective of this paper is to control bit error rate (BER) by proper channel coding, pilot carriers, adaptive filter channel estimation schemes and space time coding (STC). A combination of any of these schemes results in better BER performance over individual schemes. System performance is analyzed for various digital modulation schemes. In this paper,adaptive filter channel estimated MIMO OFDM system is proposed by integrating channel coding, adaptivefilter channel estimation, digital modulation and space time coding. From the simulation results, channel estimated 2×2 MIMO OFDM system shows superior performance over individual schemes.
The Proposed Development of Prototype with Secret Messages Model in Whatsapp Chat
Authors: Hamdani Hamdani , Ismanto Heru , Munir Agus Qomaruddin , Rahmani Budi , Syafrianto Andri , Suprihanto Didit , Septiarini Anindita
Published: October 2019

Development of prototype at data security through secret messages is needed for disguising the messages sent in smartphone chatting application, WhatsApp (WA) Chat. We propose a model to disguise a plaintext message which is first encrypted by cryptosystem to change the plaintext message to ciphertext. Plaintext or plainimage entering the smartphone system is changed into encrypted text; receiver then can read the message by using similar key with the sender. The weakness of this proposal is the message random system is not planted directly in the chatting application; therefore message removing process from cryptosystem to WA application is still needed. The strength of using this model is the messages sent will not be easily re-encrypted by hacker and can be used at client computing section.
Daily Peak Load Forecast Using Artificial Neural Network
Authors: Kumar V Ramesh , Dixit Pradipkumar
Published: October 2019

The paper presents an Artificial Neural Network (ANN) model for short-term load forecasting of daily peak load. A multi-layered feed forward neural network with Levenberg-Marquardt learning algorithm is used because of its good generalizing property and robustness in prediction. The input to the network is in terms of historical daily peak load data and corresponding daily peak temperature data. The network is trained to predict the load requirement ahead. The effectiveness of the proposed ANN approach to the short-term load forecasting problems is demonstrated by practical data from the Bangalore Electricity Supply Company Limited (BESCOM). The comparison between the proposed and the conventional methods is made in terms of percentage error and it is found that the proposed ANN model gives more accurate predictions with optimal number of neurons in the hidden layer.
A transition from manual to Intelligent Automated power system operation -A Indicative Review
Authors: Doddamani Yamanappa N. , Kapale U. C.
Published: October 2019

This paper reviews the transition of the power system operation from the traditional manual mode of power system operations to the level where automation using Internet of Things (IOT) and intelligence using Artificial Intelligence (AI) is implemented. To make the review paper brief only indicative papers are chosen to cover multiple power system operation based implementation. Care is taken there is lesser repeatation of similar technology or application be reviewed. The indicative review is to take only a representative literature to bypass scrutinizing multiple literatures with similar objectives and methods. A brief review of the slow transition from the traditional to the intelligent automated way of carrying out power system operations like the energy audit, load forecasting, fault detection, power quality control, smart grid technology, islanding detection, energy management etc is discussed .The Mechanical Engineering Perspective on the basis of applications would be noticed in the paper although the energy management and power delivery concepts are electrical.
Evolution of Microcontroller-based Remote Monitoring System Applications
Authors: Salah Wael A. , Zneid Basem Abu
Published: October 2019

This study reviews the evolution of smart applications of microcontroller-based wireless/wired remote monitoring systems. Rapid developments in science and technology offer the advantages of using integrated embedded chips, microprocessors, and microcontrollers. The use of microcontrollers in industrial processes, such as automobiles, aeronautics, space, robotics, electronics, defense applications, mobile communications, rail transport, and medical applications, is rapidly increasing. This study aims to review the progress of microcomputers in smart remote monitoring and controlling applications for the control and management of different systems using wireless/wired techniques
An Efficient Design Approach of ROI Based DWT Using Vedic and Wallace Tree Multiplier on FPGA Platform
Authors: SM Vijaya , K Suresh
Published: October 2019

In digital image processing, the compression mechanism is utilized to enhance the visual perception and storage cost. By using hardware architectures, reconstruction of medical images especially Region of interest (ROI) part using Lossy image compression is a challenging task. In this paper, the ROI Based Discrete wavelet transformation (DWT) using separate Wallace- tree multiplier (WM) and modified Vedic Multiplier (VM) methods are designed. The Lifting based DWT method is used for the ROI compression and reconstruction. The 9/7 filter coefficients are multiplied in DWT using Wallace- tree multiplier (WM) and modified Vedic Multiplier (VM). The designed Wallace tree multiplier works with the parallel mechanism using pipeline architecture results with optimized hardware resources, and 8x8 Vedic multiplier designs improves the ROI reconstruction image quality and fast computation. To evaluate the performance metrics between ROI Based DWT-WM and DWT-VM on FPGA platform, The PSNR and MSE are calculated for different Brain MRI images, and also hardware constraints include Area, Delay, maximum operating frequency and power results are tabulated. The proposed model is designed using Xilinx platform using Verilog-HDL and simulated using ModelSim and Implemented on Artix-7 FPGA device.
Genetic Algorithm for Vertical Handover (GAfVH)in a Heterogeneous networks
Authors: Zubeiri Iman , Morabit Yasmina El , Mrabti Fatiha
Published: October 2019

The fifth generation (5G) wireless system will deal with the growing demand of new multimedia and broadband application. The 5G network architecture is based on heterogeneous Radio Access Technologies (RATs). In such implementation the Vertical handover is a key issue. Up till now, systems are using simple mechanisms to make handover decision, based on the evaluation of the Received Signal Strength (RSS). In some cases these mechanisms are not Efficient.This paper presents a new vertical handover algorithm based on Genetic Algorithm (GAfVH). It aims to reduce the number of unnecessary handovers, and optimizes the system performance. We compare our simulation results to the Received Signal Strength (RSS) based method. The results show that the number of handovers decreases. Moreover, we demonstrate that the network selection result can differ from an application to another.
Channel Capacity Maximization using NQHN Approach at Heterogeneous Network
Authors: Patil Savitha , Bhavikatti A.M.
Published: October 2019

In present scenario, the high speed data transmission services has pushed limits for wireless communication network capacity, at same time multimedia transmission in real-time needs provision of QoS, therefore the network capacity and small cell coverage has comes with lots of challenges. Improving the channel capacity and coverage area within the available bandwidth is necessary to provide better QoS to users, and improved channel capacity for the FCUs and MCUs in network. In this paper, we are proposing an NQHN approach that incorporate with efficient power allocation, improving the channel capacity by optimized traffic scheduling process in a small cell HetNets scenario. This work efficiently handle the interference with maintaining the user QoS and the implemented power controller uses HeNB power as per the real time based approach for macro-cell and femto-cell. Moreover, we consider the real traffic scenario to check the performance of our proposed approach with respect to existing algorithm
Online Data Preprocessing: A Case Study Approach
Authors: Al-Taie Mohammed Zuhair , Kadry Seifedine , Lucas Joel Pinho
Published: October 2019

Besides the Internet search facility and e-mails, social networking is now one of the three best uses of the Internet. A tremendous number of volunteers every day write articles, share photos, videos and links at a scope and scale never imagined before. However, because social network data are huge and come from heterogeneous sources, the data are highly susceptible to inconsistency, redundancy, noise, and loss. For data scientists, preparing the data and getting it into a standard format is critical because the quality of data is going to directly affect the performance of mining algorithms that are going to be applied next. Low-quality data will certainly limit the analysis and lower the quality of mining results. To this end, the goal of this study is to provide an overview of the different phases involved in data preprocessing, with a focus on social network data. As a case study, we will show how we applied preprocessing to the data that we collected for the Malaysian Flight MH370 that disappeared in 2014.
Predicting Heart Ailment in Patients with Varying number of Features using Data Mining Techniques
Authors: Mary T R Stella , Sebastian Shoney
Published: October 2019

Data mining can be defined as a process of extracting unknown, verifiable and possibly helpful data from information. Among the various ailments, heart ailment is one of the primary reason behind death of individuals around the globe, hence in order to curb this, a detailed analysis is done using Data Mining. Many a times we limit ourselves with minimal attributes that are required to predict a patient with heart disease. By doing so we are missing on a lot of important attributes that are main causes for heart diseases. Hence, this research aims at considering almost all the important features affecting heart disease and performs the analysis step by step with minimal to maximum set of attributes using Data Mining techniques to predict heart ailments. The various classification methods used are Naïve Bayes classifier, Random Forest and Random Tree which are applied on three datasets with different number of attributes but with a common class label. From the analysis performed, it shows that there is a gradual increase in prediction accuracies with the increase in the attributes irrespective of the classifiers used and Naïve Bayes and Random Forest algorithms comparatively outperforms with these sets of data.
Design of 2MHz OOK transmitter/receiver for inductive power and data transmission for biomedical implant
Authors: Boutahiri Abdelali El , Ouremchi Mounir , Rahali Ahmed , Alaoui Mustapha El , Farah Fouad , Khadiri Karim El , Tahiri Ahmed , Qjidaa Hassan
Published: October 2019

In this work a 2 MHz on-off keying (OOK) transmitter/receiver for inductive power and data transmission for biomedical implant system is presented. Inductive link, driven by a Class E power amplifier (PA) is the most PA used to transfer data and power to the internal part of biomedical implant system. Proposed transmitter consists of a digital control oscillator (DCO) and a class E PA which uses OOK modulation to transfer both data and power to a biomedical implant. In proposing OOK transmitter when the transmitter sends binary value “0” the DCO and PA are turned off. With this architecture and 2 MHz carrier wave we have implemented a wireless data and power transfer link which can transmit data with data rate 1Mbps and bit error rate (BER) of 10-5. The efficiency of power transfer is 42% with a 12.7 uH transmitter coil and a 2.4 uH receiver coil and the power delivered to the load is about 104.7 mW. Proposed transmitter is designed for output power 4.1V. OOK receiver consists of an OOK demodulator, powered by rectified and regulated 5V p-p RF signal across the receiver coil. The supply voltage of proposed voltage regulator is 5 V with 9mV/V line regulation of. All circuits proposed in this paper were designed and simulated using Cadence in 0.18 um CMOS process.
Feasibility study of achieving reliable electricity supply using hybrid power system for rural primary schools in Iraq: a case study with umm qasr primary school
Authors: Almukhtar Hussam M. , Al-Tameemi Zaid H. , Al-Anbary Karrar M. , Abbas Mohammed K. , Hsu Dr. Hung-Yao , Al-Mamoori Dalya H.
Published: October 2019

Electrical power is considered as a significant part of contemporary life, and an essential element for development. Fossil fuels have been utilized since the beginning of the twentieth century for electricity generation. However, fossil fuels depletion at the escalating pace as well as their formidable negative implications upon ecosystem contributed to increasing interest in harnessing renewable energy sources for producing electric power to meet the growing demand worldwide. In Iraq, the electrical supply is not sufficient to supply 12 hours a day of electricity. Many rural areas, particularly their schools are suffering from the electricity shortage such as Umm Qasr Primary School that located 20 km away from the city centre of Karbala city in the middle of Iraq. In order to overcome this issue, this paper proposes a hybrid system which relies on renewable resources and the local grid to electrify Umm Qasr Primary School. Various combinations of energy resources have been analysed by using HOMER software to estimate an optimum hybrid system. The analysis illustrates that the optimal configuration of the projected system is composed of 22.4 kW PV modules, 59 batteries, and 5738kWh purchased from the local grid which has reduced the net present cost(NPC)from US$ 163791 the current situation to US$60,420 for the proposed system. The simulation findings also demonstrate that detrimental emissions have been reduced significantly.
Fractal representation of the power demand based on topological properties of julia sets
Authors: Tabares-Ospina Hector A. , Candelo-Becerra John E. , Velasco Fredy E. Hoyos
Published: October 2019

In a power system, the load demand considers two components such as the real power (P) because of resistive elements, and the reactive power (Q) because inductive or capacitive elements. This paper presents a graphical representation of the electric power demand based on the topological properties of the Julia Sets, with the purpose of observing the different graphic patterns and relationship with the hourly load consumptions. An algorithm that iterates complex numbers related to power is used to represent each fractal diagram of the load demand. The results show some representative patterns related to each value of the power consumption and similar behaviour in the fractal diagrams, which allows to understand consumption behaviours from the different hours of the day. This study allows to make a relation among the different consumptions of the day to create relationships that lead to the prediction of different behaviour patterns of the curves.
Solving output control problems using Lyapunov gradient-velocity vector function
Authors: Beisenbi М. А. , Basheyeva Zh. O
Published: October 2019

This paper describes a controller and observer parameter definition approach in one input-one output (closed-loop) control systems using Lyapunov gradient-velocity vector function. Construction of the vector function is based on the gradient nature of the control systems and the parity of the vector functions with the potential function from the theory of catastrophe. Investigation of the closed-loop control system’s stability and solution of the problem of controller (determining the coefficient of magnitude matrix) and observer (calculation of the matrix elements of the observing equipment) synthesis is based on the direct methods of Lyapunov. The approach allows to select parameters based on the requested characteristics of the system.
Wavelet based multicarrier CDMA system
Authors: Hamad Nasser , Takruri Maen , Barhoush Mahdi
Published: October 2019

Emerging demands for high data rate services, high user capacity and low power consumption systems are the key driving forces behind the continued technology evolution in wireless communications. Multicarrier Modulation techniques support variety of services requiring different data rates and different QoS (quality of service) levels. Multicarrier CDMA is a wireless communication system that can be seen as a combination of direct sequence CDMA and Orthogonal Frequency Division Multiplexing techniques. The main benefits of this system are its robustness to inter symbol interference and multipath propagation in fading channels. This paper studies and simulates the Discrete Wavelet Transform based Multicarrier CDMA and compares it with the  Discrete Fourier Transform based one using different number of sub carriers, and different modulation techniques. The results shows that the Wavelet based system outperforms the Fourier based one since it has lower bit error rate BER performance, lower peak to verage power ratio PAPR and higher user capacity.
An effective approach to develop location-based augmented reality information support
Authors: Brata Komang Candra , Liang Deron
Published: October 2019

Using location-based augmented reality (AR) for pedestrian navigation can greatly improve user action to reduce the travel time. Pedestrian navigation differs in many ways from the conventional navigation system used in a car or other vehicles. A major issue with using location-based AR for navigation to a specific landmark is their quality of usability, especially if the active screen is overcrowded with the augmented POI markers which were overlap each other at the same time. This paper describes the user journey map approach that led to new insights about how users were using location-based AR for navigation. These insights led to a deep understanding of challenges that user must face when using location-based AR application for pedestrian navigation purpose, and more generally, they helped the development team to appreciate the variety of user experience in software requirement specification phase. To prove our concept, a prototype of intuitive location-based AR was built to be compared with existing standard-location based AR. The user evaluation results reveal that the overall functional requirements which are gathered from user journey have same level of success rate criteria when compared with standard location-based AR. Nevertheless, the field study participants highlighted the extended features in our prototype could significantly enhance the user action on locating the right object in particular place when compared with standard location-based AR application (proved with the required time).
Novel fractal antenna for UWB applications using the coplanar waveguide feed line
Authors: Hamdouni Akram El , Tajmouati Abdelali , Zbito Jamal , Tribak Abdelwahed , Latrach Mohamed
Published: October 2019

In this study an original Coplanar Waveguide (CPW) antenna has been achieved into simulation and manufacturing in order to be an important candidate for the Ultra-wideband applications. The area of the proposed structure is 34mm x 43mm operating in the frequency range 3.1 GHz – 10.6 GHz released as UWB by the Federal Communications Commission (FCC). To perform the design of the proposed CPW antenna two electromagnetic solvers has been adopted which are CST of Microwave Studio and ADS of Agilent. The radiating patch has been chosen circular with fractal geometry based on circular slots with different sizes. The dielectric substrate is an Epoxy FR4 with a Relative permittivity 4.4, a thickness 1.6 and a loss tangent 0.025. To valid the functionality of the antenna two parameters has been computed which are the coefficient of reflection and the radiation pattern and confirmed into measurement by using the Network Analyser and the anechoic chamber.
Adaptive power link adaptation on DVB-T system based on picture quality feedback
Authors: Kusuma Tubagus Maulana , Rahmanto Randy , Haryatmi Emy
Published: October 2019

In digital television systems such as DVB-T, service provider has difficulties to observe the quality of picture reception in the viewers’ television. This is due to the unavailability of quality feedback sent from viewers’ devices to the service provider. Therefore, this research proposes link adaptation method in DVB-T system based on image quality measurement at recipient side, so that service provider may adjust the transmission power in real-time to improve the image quality. Quality metric used in this research is human perception- based no-reference image quality metric, which does not need the presence of the reference frame. The quality assessment is focused on the severeness of blocking artifact, which is the dominant artifacts in MPEG video. The numerical results have shown that power adaptation could maintain good picture quality as well as transmission power efficiency at the same time on the digital television transmission system. The proposed scheme is also suitable for other DVB system as well as various digital television system standards.
MG-leach: an enhanced leach protocol for wireless sensor network
Authors: Ouldzira Hicham , Lagraini Hajar , Mouhsen Ahmed , Chhiba Mostafa , Tabyaoui Abdelmoumen
Published: October 2019

A wireless sensor network is made up of a large number of small sensor nodes with limited energy resources, which is a real problem for this network. In this article, we will study the ingestion of node energy in these networks at the routing level. In addition, we are modifying one of the most popular routing algorithms for data communication in the WSN: LEACH (Adaptive Hierarchy with Low Power Consumption). The modified version of the LEACH base version "MG_LEACH" uses an intermediate cluster header to transmit data, extend the network lifetime and send more data than the original protocol. Our proposed algorithm is simulated using MATLAB to verify the effectiveness of improving the lifetime of this network. The results of the simulation confirmed that the system was working better than the LEACH basic system and that the network life had been improved. 
 