bluuebunny/crossref_metadata_2025 huggingface dataset:
Critical Analysis of Data Forwarding Routing Protocols Based on Single path for UWSN
Authors: Ahmed Mukhtiar , Salleh Mazleena , Channa Mohammad Ibrahim
Published: October 2019

In Underwater Wireless Sensor Network (UWSN); the sensor node is responsible to extract the valuable application based information from underwater environment. The application based information covers the applications like: tactical surveillance, assisted navigation, disaster prevention, offshore exploration, pollution monitoring and oceanographic data collection. The design of routing protocol in underwater environment is one of the challenging issues for researchers. This research article focuses the designing issues of the data forwarding routing protocols based on single path. In this article the designing of 2D and 3D architecture of routing protocols are discussed with their different issues. This article also focuses the analytical approach of proposed routing protocols with different parameters, the simulation scenarios of the single path routing protocols with critical analysis; and the open research issues; will help the researchers to further research in the field of routing protocols for UWSN.
Coplanar Wave Guide Fed Dual Band Notched MIMO Antenna
Authors: Ramkiran D S , Madhav B T P , Reddy Kankara Narasimha , Shabbeer Shaik , Jain Priyanshi , Sowmya Saggurthi
Published: October 2019

A coplanar wave guide fed of semicircle monopole antenna is designed in this work to overcome polarization diversity mimo technique is implemented in this paper. The proposed antenna is designed to notch a particular band of frequencies in UWB range. The designed model is notching the first band from 2 to 5 GHz & the second band from 7 to 11 GHz. The proposed antenna has been fabricated on FR4 substrate with di electric constant 4.4 & tested for its reliability on ZNB20 vector network analyzer. The operating bands will come under WLAN, KU band, satellite communication applications. A peak realized gain of 4.3 dB with radiation efficiency 90% is attained at the operating bands of the designed antenna. At notch band significant gain reduction is observed from the current design. The antenna is showing omnidirectional radiation pattern in the pass band & disturbed radiation pattern in the notch band. Antenna is fabricated with dimensions of 40x68x1.6 mm & simulation works are carried with finite element method based HFSS tool.
Improved Model of the Selection with Soft- and Hard-Combining Decoding Strategies for Multi-User Multi-Relay Cooperative Networks
Authors: Nasaruddin Nasaruddin , Yunida Yunida , Munadi Khairul
Published: October 2019

In a wireless cooperative network, system reliability can be improved by introducing network coding (NC) for transmitting data packets from user to destination through relay nodes. At the destination, a decoding strategy is required to recover the original data packets. The use of NC in cooperative networks has been intensively studied in previous works in terms of the conventional model for two users and a single relay in a network. However, the network model cannot act as a virtual multiple-input multiple-output system, and a multi-user multi-relay network model could be used in a real system. Therefore, this paper proposes an improved model of two network decoding strategies, selection with soft combining (SSC) and selection with hard combining (SHC), for multi-user multi-relay cooperative networks. Users are classified based on their channel conditions, with better signal-to-noise (SNR) ratio sources being viewed as strong users, and others as weak or moderate users in the decoding strategies. To evaluate the performance of the proposed model, we first derive the bit error probability expressions for each strategy as a function of SNR and then evaluate the performance using numerical simulation for a Rayleigh fading channel. Simulation results show that SSC outperforms SHC. Furthermore, the improvement in network performance is achieved either by having a higher modulation level or using incremental relaying as the signal reception method at the destination.
Hybrid Approach for Prediction of Cardiovascular Disease Using Class Association Rules and MLP
Authors: Konda Srinivas , Balmuri Kavitha Rani , Basireddy Ramasubba Reddy , Mogili Ravindar
Published: October 2019

:  In data mining classification techniques are used to predict group membership for data instances. These techniques are capable of processing a wider variety of data and the output can be easily interpreted. The aim of any classification algorithm is the design and conception of a standard model with reference to the given input. The model thus generated may be deployed to classify new examples or enable a better comprehension of available data.  Medical data classification is the process of transforming descriptions of medical diagnoses and procedures used to find hidden information. Two experiments are performed to identify the prediction accuracy of Cardiovascular Disease (CVD).A hybrid approach for classification is proposed in this paper by combining the results of the associate classifier and artificial neural networks (MLP).  The first experiment is performed using associative classifier to identify the key attributes which contribute more towards the decision by taking the 13 independent attributes as input. Subsequently classification using Multi Layer Perceptrons (MLP) also performed to generate the accuracy of prediction using all attributes. In the second experiment, identified key attributes using associative classifier are used as inputs for the feed forward neural networks for predicting the presence or absence of CVD.
Segmentation of Retail Mobile Market Using HMS Algorithm
Authors: Anusha Koyi , C Yashaswini , S Manishankar
Published: October 2019

In the modern world of marketing, analyzing the trends in market is a key point towards to scope of improvement of any company. Considering the analysis of a retail market where market trends change very frequently based on customer needs and interest is highly challenging. Market segmentation is one of the approaches included in analysis of market trends which gives a diverse view of the market.  The research here concentrates, especially on a case study based on fast moving consumable goods market and identifying market change patterns by applying a novel data mining approach. Data mining includes a wide variety of techniques and algorithm which can be effectively used in the process of market analysis. The research work carried out coins a new algorithm which combines various association rules and techniques, the HMS (Hybrid market segmentation) algorithm with some specialized criteria is used to support the market segmentation. The primary data needed for the analysis and operation are collected through a questionnaire based survey conducted on people from various demographic regions as well as various age groups. Used a quota based sampling approach for the research, The data mining approach here helps to study the large dataset collected and also to extract the useful information required to model the system. The system here is a learning system which improves the market segmentation functionality as data set improves, The paper implements a hybrid data mining approach which effectively segments the retail mobile market in to various customer and product groups and also provides a prediction and suggestion system for company as well as customer. 
Disaster Recovery Services in Intercloud using Genetic Algorithm Load Balancer
Authors: Jena Tamanna , Mohanty J.R.
Published: October 2019

Paradigm need to shifts from cloud computing to intercloud for disaster recoveries, which can outbreak anytime and anywhere. Natural disaster treatment includes radically high voluminous impatient job request demanding immediate attention. Under the disequilibrium circumstance, intercloud is more practical and functional option. There are need of protocols like quality of services, service level agreement and disaster recovery pacts to be discussed and clarified during the initial setup to fast track the distress scenario. Orchestration of resources in large scale distributed system having muli-objective optimization of resources, minimum energy consumption, maximum throughput, load balancing, minimum carbon footprint altogether is quite challenging. Intercloud where resources of different clouds are in align, plays crucial role in resource mapping. The objective of this paper is to improvise and fast track the mapping procedures in cloud platform and addressing impatient job requests in balanced and efficient manner. Genetic algorithm based resource allocation is proposed using pareto optimal mapping of resources to keep high utilization rate of processors, high througput and low carbon footprint.  Decision variables include utilization of processors, throughput, locality cost and real time deadline. Simulation results of load balancer using first in first out and genetic algorithm are compared under similar circumstances.
Neural Networks for Flow Bottom Hole Pressure Prediction
Authors: Awadalla Medhat , Yousef Hassan
Published: October 2019

Installation of down-hole gauges in oil wells to determine Flowing Bottom-Hole Pressure (FBHP) is a dominant process especially in wells lifted with electrical submersible pumps.  However, intervening a well occasionally is an exhaustive task, associated with production risk, and interruption. The previous empirical correlations and mechanistic models failed to provide a satisfactory and reliable tool for estimating pressure drop in multiphase flowing wells. This paper aims to find the optimum parameters of Feed-Forward Neural Network (FFNN) with back-propagation algorithm to predict the flowing bottom-hole pressure in vertical oil wells.  The developed neural network models rely on a large amount of available historical data measured from actual different oil fields. The unsurpassed number of neural network layers, the number of neurons per layer, and the number of trained samples required to get an outstanding performance have been obtained. Intensive experiments have been conducted and for the sake of qualitative comparison, Radial Basis neural and network and the empirical modes have been developed. The paper showed that the accuracy of FBHP estimation using FFNN with two hidden layer model is better than FFNN with single hidden layer model, Radial Basis neural network, and the empirical model in terms of data set used, mean square error, and the correlation coefficient error. With best results of 1.4 root mean square error (RMSE), 1.4 standard deviation of relative error (STD), correlation coefficient (R) 1.0 and 99.4% of the test data sets achieved less than 5% error. The minimum sufficient number of data sets used in training ANN model can be low as 12.5% of the total data sets to give 3.4 RMSE and 97% of the test data achieved 90% accuracy.
Power-Flow Development Based on the Modified Backward-Forward for Voltage Profile Improvement of Distribution System
Authors: Suyanto Suyanto , Rahmadhani Citra , Penangsang Ontoseno , Soeprijanto Adi
Published: October 2019

Unbalanced three-phase radial distribution system has a complex problem in power system. It has many branches and it is sometimes voltage profile’s not stable at every end branches. For improvement of voltage profile, it can be performed by penetrating of a distributed generation models. Information of voltage profile can be gained by study of power flow.  The Modified Backward-Forward is one of the most widely used methods of development of power flow and has been extensively used for voltage profile analysis. In this paper, a study of power flow based on the Modified Backward-Forward method was used to capture the complexities of unbalanced three phase radial distribution system in the 20 kV distribution network in North Surabaya city, East Java, Indonesia within considering distributed generation models. In summary, for the informants in this study, the Modified Backward-Forward method has had quickly convergence and it’s just needed 3 to 5 iteration of power flow simulation which’s compared to other power flow development methods. Distributed Generation models in the modified the modified 34 BUS IEEE system and 20 kV distribution network has gained voltage profile value on limited range. One of the more significant findings to emerge from this development is that the Modified Backward-Forward method has average of error voltage about 0.0017 % to 0.1749%.
PV-Transformer-Less Inverter Topology for Battery-Equivalent DC Supply from Leakage Current
Authors: N. H. Khan Md. , Anowar Md. T. , Hossen Md. D. , M. Alam Md. , Ahmad K. J.
Published: October 2019

Solar panels used for electricity generation have got inverters as their core components. Such inverters are made from switching devices coupled with additional circuit component configured in a transformer-less topology in recent reported works. A transformer-less topology suffers from the drawbacks of lack of isolation leading to leakage current flow from various points of it down to ground. The leakage in inverters might be troublesome as it may lead to loss in power, and may cause malfunctioning of analog devices normally used in power inverters. In this work, we identify possible leakage currents in a given transformer-less topology using the circuit analysis principles. The conversion of so obtained leakage currents into a useful DC voltage is carried out in this work. This work focuses on converting leakage current into small DC voltage in the range of ~1.1004V using recently reported rectifier circuits, supplying a load of 200Ω in the mW range. Although small in magnitude, such voltage sources could be used for battery charging purposes or driving small loads.
Robustness Study of Fractional Order PID Controller Optimized by Particle Swarm Optimization in AVR System
Authors: Raju N. Ramesh , Reddy P. Linga
Published: October 2019

In this paper a novel design method for determining fractional order PID (PIλDµ) controller parameters of an AVR system using particle swarm optimization algorithm is presented. This paper presents how to employ the particle swarm optimization to seek efficiently the optimal parameters of PIλDµ controller. The robustness study is made for this controller against parameter variation of AVR system. This work has been simulated in MATLAB environment with FOMCON (Fractional Order Modeling and Control) tool box.The proposed PSOPIλDµ controller has superior performance and robust compared to GA tuned PIλDµ controller. The results are also compared with PSO tuned PID controller.
Optimal Placement of TCSC Based on Sensitivity Analysis for Congestion Management
Authors: Kumari.CH Naga Raja , Sekhar K. Chendra
Published: October 2019

In a deregulated electricity market whenever congestion management problem occurs, the network collapse because of voltage instability. In this paper total real and reactive power loss deviation based sensitivity indexes (PLDS and QLDS) with rank co-relation concept, has been proposed for the optimal location and operating range of TCSC device. With this placement  the power flow in over loaded overhead lines has been reduced and that results in an increased loadability of the power system and also improves the voltage stability and security and also solves the congestion management problem. So ultimately, a more energy efficient transmission system is possible. The case studies were conducted on IEEE 14 bus test system. The ensue corroborate the intended approach for social welfare maximization inreal time.
Decomposition-Coordinating Method for Parallel Solution of a Multi-area Combined Economic Emission Dispatch Problem
Authors: Krishnamurthy Senthil , Tzoneva Raynitchka
Published: October 2019

Multi-area Combined Economic Emission Dispatch (MACEED) problem is an optimization task in power system operation for allocating the amount of generation to the committed units within the system areas. Its objective is to minimize the fuel cost and the quantity of emissions subject to the power balance, generator limits, transmission line and tie-line constraints. The solutions of the MACEED problem in the conditions of deregulation are difficult, due to the model size, nonlinearities, and the big number of interconnections, and require intensive computations in real-time. High-Performance Computing (HPC) gives possibilities for the reduction of the problem complexity and the time for calculation by the use of parallel processing techniques for running advanced application programs efficiently, reliably and quickly. These applications are considered as very new in the power system control centers because there are not available optimization methods and software based on them that can solve the MACEED problem in parallel, paying attention to the existence of the power system areas and the tie-lines between them. A decomposition-coordinating method based on Lagrange’s function is developed in this paper. Investigations of the performance of the method are done using IEEE benchmark power system models.
Experimental and Simulation Studies of Thermal Distribution on Modified Connector of Li-Ion Battery for Electric Vehicles Application
Authors: Risdiyanto Agus , Khayam Umar , A. Rachman Noviadi , Arifin Maulana
Published: October 2019

One of the several failure cases in electric vehicle could be occured at the Lithium-ion (Li-ion) battery connectors when loaded by high current. This failure caused by bad contact of connectors so that the contact resistance increase and lead to high power losses, overheating, and it can even cause a fire hazard. This paper presents a thermal distributions of  Li-ion battery connectors on different coating material in relation to the value of contact resistance. There were two test samples of modeled: copper connection without coating and copper connection with silver coating. Each sample was loaded by the DC current of 350A, and temperature at the connection was measured until steady state condition reached and simulated by Solidwork software. The results show that the temperature at the inside contact area was higher than the outside contact area of connection that appears caused by higher of the contact resistance. Both measurement and simulation results have same tendency that copper connection with silver coating having lower contact resistance, lower maximum temperature, and lower losses about 32 % than copper connection without  coating. Silver coating can be considered as other alternative to prevent overheating, high losses, and failure in Li-ion battery connector.
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: October 2019

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.
Performance Analysis of Cooperative Hybrid Cognitive Radio Network with Various Diversity Techniques
Authors: Preetham C.S. , Prasad M.S.G. , Saranya D.S.S.L. , Somepalli Charan Teja , Sai Krishna D. Bhargava Satya , Rohit V.
Published: October 2019

The extensive growth in wireless communications leads to spectrum scarcity. Since the spectrum is limited spectrum usage is clogged. The best possible solution is usage of cognitive radio. A cognitive radio network with sender, receiver and intermediate devices as relays is analyzed. The channel is modelled with noise considerations, path loss and variance. The system is defined with one primary sender and one primary receiver, in between them five secondary users and two active users. The signals from all these paths are estimated and analyzed to draw the best signal with good signal to noise ratio (SNR). To improve the channel efficiency and quality, we have considered various diversity techniques for which the fading problem of channel can be eliminated. In view of this, we concentrated on improving the system performance with various diversity techniques and optimum weight adaptation concept.
Bangladesh Perspective: Vehicle Speed Proposition System using Localized Wireless Identification
Authors: Islam Md. Mamunoor , Chowdhury Mehdi Hasan
Published: October 2019

Even in the era of advanced engineering, road accident has been a regular phenomenon causing death of many people in Bangladesh due to over speeding action of reckless drivers. There are several key places (such as schools, colleges, hospitals, highways and constructional areas etc.) where the speed of the vehicle should be lessened to avoid accidents. The roads and highways authority may place the speed limiter signboards in these areas to avoid these accidents, but these are frequently overlooked by the drivers. So this paper demonstrates a wireless forewarning system which will aid to control the speed of the vehicles at speed restricted areas. The whole system is established on the basis of radio frequency (RF) communication. There are two parts of this system named as transmitting unit and receiving unit. Each RF transmitter positioned on the roadside will be transmitting the code signal continuously. Whenever the vehicle enters the range of transmission, the RF receiver which is attached in the vehicle, will receive the signal and will display the information in a LCD monitor by notifying the driver to reduce the speed while going through that area.
Improved Canny Edges Using Cellular Based Particle Swarm Optimization Technique for Tamil Sign Digital Images
Authors: Krishnaveni M , Subashini P , Dhivyaprabha TT
Published: October 2019

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.
Image Segmentation Based on Doubly Truncated Generalized Laplace Mixture Model and K Means Clustering
Authors: Jyothirmayi T , Srinivasa Rao K , Srinivasa Rao P , Satyanarayana Ch
Published: October 2019

The present paper aims at performance evaluation of Doubly Truncated Generalized Laplace Mixture Model and K-Means clustering (DTGLMM-K) for image analysis concerned to various practical applications like security, surveillance, medical diagnostics and other areas. Among the many algorithms designed and developed for image segmentation the dominance of Gaussian Mixture Model (GMM) has been predominant which has the major drawback of suiting to a particular kind of data. Therefore the present work aims at development of DTGLMM-K algorithm which can be suitable for wide variety of applications and data. Performance evaluation of the developed algorithm has been donethrough various measures like Probabilistic Rand index (PRI), Global Consistency Error (GCE) and Variation of Information (VOI). During the current work case studies forvarious different images having pixel intensities has been carried out and the obtained results indicate the superiority of the developed algorithm for improved image segmentation.
Speech Recognition Using Combined Fuzzy and Ant Colony algorithm
Authors: Jalili Fooad , Jafari Barani Milad
Published: October 2019

In recent years various methods has been proposed for speech recognition and removing noise from the speech signal became an important issue. In this paper a fuzzy system has been proposed for speech recognition that can obtain accurate results using classification of speech signals with “Ant Colony” algorithm.  First, speech samples are given to the fuzzy system to obtain a pattern for every set of signals that can be helpful for dimensionality reduction, easier checking of outcome and better recognition of signals.  Then, the “ACO” algorithm is used to cluster these signals and determine a cluster for each input signal. Also, with this method we will be able to recognize noise and consider it in a separate cluster and remove it from the input signal. Results show that the accuracy for speech detection and noise removal is desirable.
Synthesis of an Optimal Dynamic Regulator Based on Linear Quadratic Gaussian (LQG) for the Control of the Relative Humidity under Experimental Greenhouse
Authors: Outanoute M. , Lachhab A. , Ed-dahhak A. , Guerbaoui M. , Selmani A. , Bouchikhi B.
Published: October 2019

This paper describes one practical approach that suggests a model based technique to control in real time the relative humidity under greenhouse. The humidity level is one of the most difficult environmental factors to be regulated in greenhouse. Moreover, maintaining and correcting for more or less humidity can be a challenge for even the most sophisticated monitoring and control equipment. For these raisons, a Linear Quadratic Gaussian (LQG) controller for relative humidity regulation under greenhouse turns out to be useful. Indeed a LQG controller is proposed for a relative humidity under a greenhouse control task. So, the state space model, which is best fitting the acquired data, was identified using the Numerical Subspace State Space System IDentification (N4SID) algorithm. The mathematical model that is obtained will be used for evaluating the parameters of LQG strategy. The proposed controller is implemented in two steps, in one hand, Kalman filter (KF) is used to develop an observer that estimates the state of relative humidity under greenhouse. In the other hand, the state feedback controller gain is estimated using a linear quadratic criterion function. The suggested optimal implemented controller using Matlab/Simulink environment is applied to an experimental greenhouse. We found, according to the results, that the controller is able to lead the inside relative humidity to the desired value with high accuracy, regardless of the external disturbances.
Design of a Front-End for Satellite Receiver
Authors: Hoi Tran Van , Lanh Ngo Thi , Truong Nguyen Xuan , Duc Nguyen Huu , Duong Bach Gia
Published: October 2019

This paper focuses on the design and implementation of a front-end for a Vinasat satellite receiver with auto-searching mechanism and auto-tracking satellite. The front-end consists of a C-band low-noise block down-converter and a L-band receiver. The receiver is designed to meet the requirements about wide-band, high sensitivity, large dynamic range, low noise figure. To reduce noise figure and increase bandwidth, the C-band low-noise amplifier is designed using T-type of matching network with negative feedback and the L-band LNA is designed using cascoded techniques. The local oscillator uses a voltage controlled oscillator combine phase locked loop to reduce the phase noise and select channels. The front-end has successfully been designed and fabricated with parameters: Input frequency is C-band; sensitivity is greater than -130 dBm for C-band receiver and is greater than -110dBm for L-band receiver; output signals are AM/FM demodulation, I/Q demodulation, baseband signals.
Single Perceptron Model for Smart Beam forming in Array Antennas
Authors: Senthilkumar K.S. , Pirapaharan K. , Hoole P.R.P , Hoole R.R.H
Published: October 2019

In this paper, a single neuron neural network beamformer is proposed. A perceptron model is designed to optimize the complex weights of a dipole array antenna to steer the beam to desired directions. The objective is to reduce the complexity by using a single neuron neural network and utilize it for adaptive beamforming in array antennas. The selection of nonlinear activation function plays the pivotal role in optimization depends on whether the weights are real or complex. We have appropriately proposed two types of activation functions for respective real and complex weight values.   The optimized radiation patterns obtained from the single neuron neural network are compared with the respective optimized radiation patterns from the traditional Least Mean Square (LMS) method. Matlab is used to optimize the weights in neural network and LMS method as well as display the radiation patterns.
A Secured Cloud Data Storage with Access Privileges
Authors: Vurukonda Naresh , Rao B. Thirumala , Reddy B. Tirapathi
Published: October 2019

In proposed framework client source information reinforcements off-site to outsider distributed storage benefits to decrease information administration costs. In any case, client must get protection ensure for the outsourced information, which is currently safeguarded by outsiders. To accomplish such security objectives, FADE is based upon an arrangement of cryptographic key operations that are self-kept up by a majority of key supervisors that are free of outsider mists. In unmistakable, FADE goes about as an overlay framework that works flawlessly on today's distributed storage administrations. Actualize a proof-of-idea model of FADE on Amazon S3, one of today's distributed storage administrations. My work oversee, esteem included security highlights acclimatize were today's distributed storage administration. our research work proceeds in ensuring the file access control and assured deletion in multi cloud environment and reducing the meta data management, there by the cloud storage become more attractive and many users will adopt the cloud space in order to diminish the data storage cost.
EETA: An Energy Efficient Transmission Alignment for Wireless Sensor Network Applications
Authors: Lim Sangsoon , Oh Hayoung
Published: October 2019

Energy conserving MAC protocols performing adaptive duty-cycling mechanism have been widely studied to improve the energy efficiency in Wireless Sensor Networks (WSNs). In particular, several asynchronous Low Power Listening (LPL) MAC protocols such as B-MAC, X-MAC and ContikiMAC transmit a long preamble or consecutive data packets for an efficient rendezvous between senders and receivers. However, the rendezvous results in the challenging problem of unnecessary channel utilization since the senders occupy a large portion of the medium. Furthermore, when a traffic generation time overlaps with other neighbouring nodes, they frequently encounter spatially-correlated contention incurring excessive channel contention. In this paper, we propose a novel traffic distribution scheme called an Energy Efficient Transmission Alignment (EETA), that shifts a traffic generation time of the application layer. By using a MAC layer feedback including contention information, the cross-layer framework determines whether the node delays its transmission or not. EETA is robust from the heavy contending environment due to its traffic distribution feature. We evaluate the performance of EETA through diverse experiments on the TelosB platform. The results show that EETA improves the overall energy efficiency by up to 35%, and reduces the latency by up to 48% compared to the existing scheme.
Light-weight Routing Protocol in IoT-based Inter-Device Telecommunication Wireless Environment
Authors: Oh Hayoung , Lim Sangsoon
Published: October 2019

The primary task for IoT-based hyper-connectivity communications lies in the development of direct communications technique among IoT devices in RPL (Routing Protocol for Low-Power and Lossy Networks) environment without the aid from infras such as access points, base stations etc. In a low-power and lossy wireless network, IoT devices and routers cannot keep the original path toward the destination since they have the limited memory, except for a limited number of the default router information.. Different from the previous light-weight routing protocols focusing on the reduction of the control messages, the proposed scheme provides the light-weight IPv6 address auto-configuration, IPv6 neighbor discovery and routing protocol in a IoT capable infra-less wireless networks with the bloom filer and enhanced rank concepts. And for the first time we evaluate our proposed scheme based on the modeling of various probability distributions in the IoT environments with the lossy wireless link. Specifically, the proposed enhanced RPL based light-weight routing protocol improves the robustness with the multi-paths locally established based on the enhanced rank concepts even though lossy wireless links are existed. We showed the improvements of the proposed scheme up to 40% than the RPL based protocol.
Feasibility and Efficacy of BLE Beacon IoT Devices in Inventory Management at the Shop Floor
Authors: Ramakrishnan Ravi , Gaur Loveleen , Singh Gurinder
Published: October 2019

Inventory Management is a key area for customer service and cost optimization in any manufacturing setup. As companies turn global and have thousands of components and hundreds of warehouses the inventory becomes a nightmare and a lot of time is spend in tracking inventory and ensuring right shipments. Traditional systems of robotic arms for inventory pick and drop have been based on premises of marking areas of the warehouse and tracking it. However with the advent of IoT all this is set to change as inventory objects become more self-aware and self-broadcasting. This paper technically suggests an approach of managing inventory using low energy blue tooth beacons and also does a statistical case research on two groups of the same organization one before the pilot run where traditional barcode scanners are used to track inventory and other one where the pilot trial BLE beacon technology was used. Statistically the IoT-beacon users are much more efficient and accurate and save lot of time and costs in the short run itself.
Investigation on the Services of Private Cloud Computing by Using ADAM Method
Authors: Widiyasono Nur , Riadi Imam , Luthfie Ahmad
Published: October 2019

Cloud services are offered by many cloud service providers, but in for large companies generally are build  by a private cloud computing. In cloud systems of abuse it can be done by internal users or due to misconfiguration or may also refer to weaknesses in the system. This study evaluated the ADAM method (Advanced Data Acquisition Model) and tested the case schemes which are being carried out in the laboratory simulation of the process in order to obtain forensic evidence of digital data on private cloud computing services. Referring to the results of the investigation process by using ADAM Method, it can be verified that there are several parameters of the success investigation including the structure of files, files, time stamp, mac-address, IP address, username password, and the data from a server both from the desktop PC or smartphone, therefore the investigation by using ADAM can be succesed properly and correctly. Another contribution of this study was to identify the weaknesses of the service system that used owncloud in users list of the the same group can change another’s user’s passwod.
A Normative Process Model for ICT Business Continuity Plan for Disaster Event in Small, Medium and Large Enterprises
Authors: Sambo Fadeel , Bankole Felix Olu
Published: October 2019

Small, Medium and Large Enterprises (SMLs) are exposed to the risks of business interruption as they expand and become more dependent on Information Communication Technology (ICT) infrastructure. The current study seeks to determine why organization that have Business Continuity Plan (BCP) in place and implement regular testing of their plan still experience prolong downtime during a disaster event resulting in Service Level Agreement (SLA) not being met or major financial loss. By employing a descriptive analytics approach through a qualitative case study, the research propose a normative process model for comprehensive procedures of BCP for business leaders, ICT service managers, IS executives, data science researchers, risk managers, entrepreneur and policy makers on how to adopt strategies on effective disaster risk reduction and management in organizations. The current study offer both theoretical and practical implications for BCP in small, medium and large enterprises.
Multicriteria Group Decision Making Using Fuzzy Approach for Evaluating Criteria of Electrician
Authors: Hadikurniawati Wiwien , Mustofa Khabib
Published: October 2019

This paper presents an approach of fuzzy multicriteria group decision making in determining alternatives to solve the selection problem of the electrician  through  a competency test.   Fuzzy approach is used to determine the highest priority of alternative electrician who has knowledge and ability that best fits the given parameters. Linguistic variables are presented by triangular fuzzy numbers. They are used to represent a subjective assessment of the decision-makers so that uncertainty and imprecision in the selection process can be minimized. Fuzzy approach require transforming crisp data to fuzzy numbers. Output of the best alternatives is generated by ranking method. Ranking has been made base on eight criteria which make the evaluation basis of each alternative. Ranking of the results is determined using different value of optimism index (). The fuzzy multi criteria decision making (FMCDM) calculation is using the best alternative using three value of optimism index. The result of calculation shows that the same alternative reached from different index of optimism. This alternative is the highest priority of decision making process.
Analytical Estimation of the Electrostatic Field in Cylinder-Plane and Cylinder-Cylinder Electrode Configurations
Authors: Fylladitakis Emmanouil D. , Moronis Antonios X. , Theodoridis Michael
Published: October 2019

This work presents analytical formulas for the estimation of the electrostatic field in cylinder-plane and cylinder-cylinder electrode configurations. Assuming a predefined potential difference between the electrodes and given their geometrical characteristics, these could be useful for the solution of numerous problems involving such electrode sets. Moreover, the voltage distribution around the electrodes is defined by providing equations either for the equipotentials at a given voltage ratio, or the exact estimation of the potential at any point in the surrounding space. Simplified expressions for critical engineering parameters such as the peak electric field and the field enhancement factor are also given.
Environment Friendly Voltage Up-gradation Model for Distribution Power Systems
Authors: Nithiyananthan K. , Umasankar Umasankar
Published: October 2019

The main aim of this research work is to analyze and develop voltage up gradation procedure model for effective & economic power distribution in urban and suburban area. Voltage up gradation from 6.6KV to 11KV of the distribution power system network has been considered for the proposed research work. Electric power consumption has been increasing uninterruptedly, being this increase specially accelerated in the last few years. Nowadays electric lines are saturated; they are reaching critical values of ampere capacity and sag. Therefore, building new lines has been necessary to provide the ever increasing consumption.  The difficulty to find new corridors to construct new distribution lines, underground cables is increasing in cities, industrial areas and in many cases it is simply impossible. The construction of new electric lines is increasing difficulty, thus there is a need to look at alternatives that increases the power transfer capacity. Voltage up gradation of the existing electric cables/lines of the distribution system is the most viable solution and it stresses on the savings of power due to a reduction in system losses when the voltage is high. The proposed research work is to develop and analyze voltage up gradation procedures and protocols for converting 6.6KV network into 11KV network in a distributed system. It also takes into account the expenses incurred in the process and the various other important constraints.
Simulation and Performance Evaluation of Shunt Hybrid Power Filter for Power Quality Improvement Using PQ Theory
Authors: Balasubramanian R. , Palani S.
Published: October 2019

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.
Signature Verification using Normalized Static Features and Neural Network Classification
Authors: Trikha Manish , Singhal Manas , Dutta Maitreyee
Published: October 2019

Signature verification is very widely used in verification of the identity of any person. Now a days other biometric verification system has been evolved very widely like figure print, iris etc., but signature verification through computer system is still in development phase. The verification system is either through offline mode or online mode in online systems the dynamic information of a signature captured at the time the signature is made while in offline systems based on the scanned image of a signature. In this paper, a method is presented for Offline signatures Verification, for this verification system signature image is first pre-processed and converted into binary image of same size with 200x200 Pixels and then different features are extracted from the image like Eccentricity, Kurtosis, Skewness etc. and that features are used to train the neural network using back-propagation technique. For this verification system 6 different user signatures are taken to make database of the feature and results are analysed. The result demonstrate the efficiency of the proposed methodology when compared with other existing studies. The proposed algorithm gives False Acceptance Rate (FAR) as 5.05% and False Rejection rate (FRR) as 4.25%.
Optical Interconnect Waveguide in Electronic Circuit
Authors: Binti Md Sallah Siti Sarah , Md Ali Sawal Hamid , Binti Juhari Nurjuliana , Menon P. Sushitha , Islam Md Shabiul
Published: October 2019

The increasing demand in silicon nano-photonics has encouraged many researchers to put more efforts to explore the feasibility of using optics in the communication medium in order to replace the conventional electrical interconnects (EIs). In this paper, we proposed a SOI- based waveguide in the optical interconnect (OI) link at an operating frequency of 1550nm to work as an interconnection path in a circuit. The performance capability of the OI link was tested using a two-stage CE amplifier to work as the interconnection path from the 1st stage to the 2nd stage amplifier. In term of optical performances, the optical waveguide interconnect managed to achieve a single mode condition for a TE mode and fulfill the receiver sensitivity of a photodiode. While, in term of electrical performance, a two-stage CE amplifier is able to produce a high gain, a wide bandwidth and high slew rate. The proposed implementation of the OIs waveguide is succesfully enhance the performance of the two-stage CE amplifier as well as the analog electronic circuit applications.
Improvement of Tuning Fork Gyroscope Drive-mode Oscillation Matched using a Differential Driving Suspension Frame
Authors: Nguyen Van Thang , Tan Tran-Duc , Vu Ngoc Hung , Chu Duc Trinh
Published: October 2019

This paper presents a novel design of a vibration tuning fork gyroscope (TFG) based on a differential driving suspension coupling spring between two gyroscopes. The proposed TFG is equivalent to a transistor differential amplifier circuit. The mechanical vibrations of driving frames are, therefore, well matched. The matching level depends on stiffness of spring. When three various TFG structures respond to differential stiffness of spring, their the driving frame mechanical vibration is well matched in case the input excitation driving differential phase is less than 3.5°, 2.5°, and 4°, respectively. The fabricated tuning fork gyroscope linearly operates in the range from -200 to +200 degree/s with the resolution of about 0.45 mV/degree/s.
Real Time Weed Detection using a Boosted Cascade of Simple Features
Authors: Tannouche Adil , Sbai Khalid , Rahmoune Miloud , Agounoun Rachid , Rahmani Abdelhai , Rahmani Abdelali
Published: October 2019

Weed detection is a crucial issue in precision agriculture. In computer vision, variety of techniques are developed to detect, identify and locate weeds in different cultures. In this article, we present a real-time new weed detection method, through an embedded monocular vision. Our approach is based on the use of a cascade of discriminative classifiers formed by the Haar-like features. The quality of the results determines the validity of our approach, and opens the way to new horizons in weed detection.