bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of dualband antenna for RFID applications
Authors: Sahar N. M. , Islam M.T. , Misran N.
Published: October 2019

This paper focuses on the design and fabrication of dual band antenna for UHF RFID and ISM RFID applications. The U-shaped patch loaded with dipole is introduced and investigated. The antenna can be performed dual-band frequencies at 0.915 GHz and 2.4 GHz required in RFID applications with reflection coefficient is less than -10 dB. The lower band can be varied by adjusting both dipole arms length and upper band is tuned by U-shaped patches. The gains of the design with a size 130   45  1.6 mm3  are performed 1.89 dB and 3.65 dB for single and dual band respectively. This compact and low cost dual band antenna also performed total efficiency greater than 80%. The design methodology and antenna measurement results are both presented and discussed in this letter.
A systematic optimization procedure of antenna miniaturization for efficient wireless energy transfer
Authors: Misran Mohamad Harris , Abdul Rahim Sharul Kamal , Meor Said Maizatul Alice , Othman Mohd Azlishah
Published: October 2019

This paper presents a systematic optimization procedure to determine the reduced antenna size aimed at obtaining the best efficiency or at least equal performance with the initial large antenna design in a wireless energy transfer (WET) system. A low-cost, square-shaped planar loop antenna designed on each side of FR4 substrate is used as both the miniature transmitter and receiver antennas operating at 13.56 MHz for the near-field communication (NFC) band. The effect of distance and antenna size on the link parameters such as inductance, resistance and mutual coupling is studied, prior to the study of their effects on WTE. The accuracy of the procedure is cross-validated using two methods; analytically and using full wave simulations. The simulation then is verified using lab measurement setup at real scene environment. Trends of the resulting curves using both methods indicated good agreements, and optimal miniature antenna for the best wireless transfer efficiency (WTE) is able to be quickly determined. A miniature antenna is able to achieve 4% wireless transfer efficiency improvement with 47% antenna size reduction. Such method can be applied to efficiently estimate a low-cost WTE system setup, besides enabling the integration of self-tuning or reconfigurability features in such systems for a known initial antenna size to mitigate changes to its operating distance.
Onto2DB: towards an eclipse plugin for automated database design from an ontology
Authors: Hajji Morad , Qbadou Mohammed , Mansouri Khalifa
Published: October 2019

Ontologies are spreading more and more in the field of information technologies as a privileged solution allowing the formalization of knowledge. The theoretical model of ontologies is most promising. They are increasingly ubiquitous given the benefits they present. Despite the proliferation of research proposing approaches dedicated to the design of a database from an ontology, the tools to design a database from an ontology are rare or inaccessible. Thus, in this contribution, we present our approach for the development of an Eclipse Plug-in, in order to automatically generate a conceptual model of a relational database from an ontology. To evaluate the usefulness of our approach, we used our resulting Eclipse Plug-in to automatically generate a conceptual model of a relational database from an ontology, customize it, and automatically generate the corresponding SQL script for Data Definition. The results of this experiment showed that our Plug-in constitutes a concretization of our approach and a means of automatic translation from the ontological model to the relational model.
Opinion mining using combinational approach for different domains
Authors: Deshmukh Jyoti Sandesh , Tripathy Amiya Kumar , Hiran Dilendra
Published: October 2019

An increase in use of web produces large content of information about products. Online reviews are used to make decision by peoples. Opinion mining is vast research area in which different types of reviews are analyzed. Several issues are existing in this area. Domain adaptation is emerging issue in opinion mining. Labling of data for every domain is time consuming and costly task. Hence the need arises for model that train one domain and applied it on other domain reducing cost aswell as time. This is called domain adaptation which is addressed in this paper. Using maximum entropy and clustering technique source domains data is trained. Trained data from source domain is applied on target data to labeling purpose A result shows moderate accuracy for 5 fold cross validation and combination of source domains for Blitzer et al (2007) multi domain product dataset.
Developing a grid-connected DFIG strategy for the integration of wind power with harmonic current mitigation
Authors: Mahieddine Hacil , Zarour Laid , Lamri Louze , Lokmane Nemmour Ahmed
Published: October 2019

The aim of this paper is to present a study of the efficiency of the electrical part of a wind generation system. Two back-to-back PWM voltage-fed inverters connected between the stator and the rotor are used to allow bidirectional power flow. The second inverter grid side, has a role of a power active filter, to eliminate the harmonic generated by the non linear load, in the same time gives an active and reactive power needed by the rotor of DFIG. The harmonics of switching frequency in the current stator, pose a major problem in the moment where commutations in the diode bridge, to solve this problem, we introduce a small-sized passive LC filter for the purpose of eliminating high-frequency shaft voltage and grid current from a DFIG driven by a voltage-source pulse width-modulation rotor inverter controlled with SVM. The control theory is discussed, and the controller implementation is described. Design criteria are also given. The results of simulation tests show excellent static and dynamic performances.
Modified phase locked loop for grid connected single phase inverter
Authors: Radwan Eyad , Salih Khalil , Awada Emad , Nour Mutasim
Published: October 2019

Connecting a single-phase or three-phase inverter to the grid in distributed generation applications requires synchronization with the grid. Synchronization of an inverter-connected distributed generation units in its basic form necessitates accurate information about the frequency and phase angle of the utility grid. Phase Locked Loop (PLL) circuit is usually used for the purpose of synchronization. However, deviation in the grid frequency from nominal value will cause errors in the PLL estimated outputs, and that’s a major drawback. Moreover, if the grid is heavily distorted with low order harmonics the estimation of the grid phase angle deteriorates resulting in higher oscillations (errors) appearing in the synchronization voltage signals. This paper proposes a modified time delay PLL (MTDPLL) technique that continuously updates a variable time delay unit to keep track of the variation in the grid frequency. The MTDPLL is implemented along a Multi-Harmonic Decoupling Cell (MHDC) to overcome the effects of distortion caused by gird lower order harmonics. The performance of the proposed MTDPLL is verified by simulation and compared in terms of performance and accuracy with recent PLL techniques.
Prediction the data consumption for power demands by elman neural network
Authors: Ismael Lafta , Ismael Ammar Issa
Published: October 2019

The load forecasting consider as part important in power system operation.  The exact prediction for power demand is important for planning how much need extra power generation to cover extra load to keep without happen shutdown. Neural networks stay frequently designed for modeling dynamic processes. The Multi-Layer Perceptron (MLP) with Radial Basis Functions (RBF) network is static approximations used fewer frequently in the discrete-time domain. In this paper proposed predict method for daily peak load by Elman Neural Network (ENN) with using data power demand for 2 years collected from National Control Center (NCC) and comparing the result. The result show the proposal is evaluated and followed the power demand.
Biological landmark Vs quasi-landmarks for 3D face recognition and gender classification
Authors: Abbas Hawraa H. , Altameemi Ammar A. , Farhan Hameed R.
Published: October 2019

Face recognition and gender classification are vital topics in the field of computer graphic and pattern recognition. We utilized ideas from two growing ideas in computer vision, which are biological landmarks and quasi-landmarks (dense mesh) to propose a novel approach to compare their performance in face recognition and gender classification. The experimental work is conducted on FRRGv2 dataset and acquired 98% and 94% face recognition accuracies using the quasi and biological landmarks respectively. The gender classification accuracies are 92% for quasi-landmarks and 90% for biological landmarks.
Dynamic analysis and qft-based robust control design of a coaxial micro-helicopter
Authors: Aissa Meksi , Boudinar Ahmed Hamida , Kouadri Benatman
Published: October 2019

This paper presents the dynamic behavior of a coaxial micro-helicopter, under Quantitative Feedback Theory (QFT) control. The flight dynamics of autonomous air vehicles (AAVs) with rotating rings is non-linear and complex. Then, it becomes necessary to characterize these non-linearities for each flight configuration, in order to provide these autonomous air vehicles (AAVs) with autonomous flight and navigation capabilities. Then, the nonlinear model is linearized around the operating point using some assumptions. Finally, a robust QFT control law over the coaxial micro-helicopter is applied to meet some specifications. QFT (quantitative feedback theory) is a control law design method that uses frequency domain concepts to meet performance specifications while managing uncertainty. This method is based on the feedback control when the plant is uncertain or when uncertain disturbances are affecting the plant. The QFT design approach involves conventional frequency response loop shaping by manipulating the gain variable with the poles and zeros of the nominal transfer function. The design process is accomplished by using MATLAB environment software.
Design and performance comparison of different adaptive control schemes for pitch angle control in a twin – rotor – MIMO – system
Authors: Netto Winston , Lakhani Rohan , Sundaram S. Meenatchi
Published: October 2019

The Twin Rotor MIMO System is a higher order non-linear plant and is inherently unstable due to cross coupling between tail and main rotor. In this paper only the control of main rotor is considered which is non-linear and stable by using adaptive schemes. The control problem is to achieve perfect tracking for input reference signals while maintaining robustness and stability. Four adaptive schemes were implemented, two using Model Reference Adaptive Control under which MIT rule and Modified MIT rule are used. The other two using Adaptive Interaction, namely, Adaptive PID and Approximate Adaptive PID. It is observed that adaptive schemes fulfill all the three system performance requirements at the same time. Modified MIT rule was found to give superior performance in comparison to other controllers. Also Approximate Adaptive PID was able to stabilize the main rotor and cancel the effect of cross coupling between tail rotor and main rotor when operating simultaneously without the need for designing decouplers for the system. Thus the main rotor can be made independent from the state of the tail rotor by using Approximate Adaptive PID.
The saturation of population fitness as a stopping criterion in genetic algorithm
Authors: Yeng Foo Fong , Yoke Soo Kum , Suhaimi Azrina
Published: October 2019

Genetic Algorithm is an algorithm imitating the natural evolution process in solving optimization problems. All feasible (candidate) solutions would be encoded into chromosomes and undergo the execution of genetic operators in evolution. The evolution itself is a process searching for optimum solution. The searching would stop when a stopping criterion is met. Then, the fittest chromosome of last generation is declared as the optimum solution. However, this optimum solution might be a local optimum or a global optimum solution. Hence, an appropriate stopping criterion is important such that the search is not ended before a global optimum solution is found. In this paper, saturation of population fitness is proposed as a stopping criterion for ending the search. The proposed stopping criteria was compared with conventional stopping criterion, fittest chromosomes repetition, under various parameters setting. The results show that the performance of proposed stopping criterion is superior as compared to the conventional stopping criterion.
Smart prepaid energy metering system to detect energy theft with facility for real time monitoring
Authors: T. E Somefun , C.O.A Awosope , A. Chiagoro
Published: October 2019

Electricity theft remains a huge loss incurred by electricity distribution companies. This theft arises majorly because of activities carried out by consumers such as energy-meter by-passing, energy-meter tampering etc. This research study offers an approach for handling energy meter by-passing and tampering. The system design is based on the monitoring of the readings of two current sensors by a programmed microcontroller. While one of the current sensors monitors the current drawn by the user’s load, the latter installed before the meter monitors current drawn by all loads. Any discrepancy between the values read, indicates theft. A momentary switch is also installed in the meter to trigger the meter once it is tampered with. Furthermore, the user is provided with a remote access to the energy meter for recharging energy units and for monitoring energy consumption. It was observed that the system accurately measured load consumption and detect any attempt to by-pass or tamper with the energy meter. Lastly, all unscrupulous attempts were reported using GSM technology.
Design and implementation of the subsystem subject to emission of multicomponent high-frequency signals to ensure its reliability
Authors: Daneshvar Milad , Parhizgar Naser , Oraizi Homayoon
Published: October 2019

Telecommunication systems, especially digital ones, are mostly known to be immune to noise given their extensive range of applications. This study aimed to investigate the methods and tools used for the analysis of multicomponent signals input to high-frequency digital subsystems, including the analysis of changes in its electrical behavior. This research mainly focuses on analyzing a high-frequency telecommunication subsystem, recording the results, investigating the system behavior against signals with different amplitudes and phases, detecting the received signals, and measuring the phase differences. The study extended the mono-component signals to multi-component signals and accurately extracted the statistical signal specifications using analytic signals in the time-frequency domain. To this end, a method was proposed based on the switch matrix to relate the different components and parameters, and also a mathematical model based on the state-space equations was employed to evaluate the nonlinear system modes. Given that the decoupling of measurement parameters is a problem to be tackled from multiple aspects, the costs and test durations were also taken into calculations in addition to considering all the detection methods for interference signals, reliability and time under test.
Implementation of FOAF, AIISO and DOAP ontologies for creating an academic community network using semantic frameworks
Authors: Ahuja Himanshu , R Sivakumar
Published: October 2019

Web 2.0 delivers the information which is then displayed in human readable content, omitting the crucial information which can be drawn from the data by the applications. Web 3.0 or semantic web is an extension to the current web, with an ambition to determine the drawbacks of the current web. The semantic web has already proven its influence in several communities around the globe, such as social media, music industry, healthcare domain, online blogs or articles, etc.; Among the several tools and technologies, ontologies or vocabularies are the foundation pillar for the semantic web. In this paper, the developed system aims at improving the collaboration and academic relations among staff which is directly related to our education community by providing a better networking platform which lets the agents discuss their achievements, titles, domain interests, and various other activities. Results have been analyzed to show how new facts, information can be implied from the presented knowledge of several agents and help generate a relationship graph by utilizing various semantic tools. The system discussed in this paper processes all the information in a format which can be understood by both humans and the machines, to interpret the underlying meaning about it and provide effective results.
The impact of IT investment on firm performance based on MCDM techniques
Authors: Daghouri Ansar , Mansouri Khalifa , Qbadou Mohammed
Published: October 2019

In the recent past years, researchers have presented conflicting results regarding the impact of information technology investment on firm performance. Almost all studies on information technology productivity and it role for companies performance are based on data collected and meta-analysis and do not offer a methodology or prototype of analysis in any field This study presents an attempt to adopt a multi-criteria decision making approach to evaluate the non-financial performance of companies using two famous methods. Furthermore, our results try to investigate the effects of information technology investments on firms’ non-financial performance. Finding show that investment in information systems is not necessarily related to achieving a good non-financial performance at the firm level.
An overview of virtual machine live migration techniques
Authors: Mazrekaj Artan , Nuza Shkelzen , Zatriqi Mimoza , Alimehaj Vlera
Published: October 2019

In a cloud computing the live migration of virtual machines shows a process of moving a running virtual machine from source physical machine to the destination, considering the CPU, memory, network, and storage states. Various performance metrics are tackled such as, downtime, total migration time, performance degradation, and amount of migrated data, which are affected when a virtual machine is migrated. This paper presents an overview and understanding of virtual machine live migration techniques, of the different works in literature that consider this issue, which might impact the work of professionals and researchers to further explore the challenges and provide optimal solutions.
Variable structure control for an isolated boost converter used in fuel cell applications
Authors: Madhavi S. Vijaya , Tulasi Ram Das G.
Published: October 2019

In recent years fuel cells have become prominent as an alternative source of energy to meet the society’s energy requirements. A control strategy derived from variable structure theory known as Sliding Mode Control (SMC) was proposed for an Isolated Boost topology which was mostly used in fuel cell systems. Converter operation and its detailed mathematical modelling are also presented. Then the converter with the control strategy suggested is simulated in MATLAB/SIMULINK and compared with other controllers. The results show that transient response of the converter is very fast and steady state error is reduced throughout the load change period with proposed control topology.
Internet of things based industrial environment monitoring and control: A design approach
Authors: Jaber Alaa Adulhady , Al-Mousawi Firas Khalil Ibrahim , Jasem Hayder Sabeeh
Published: October 2019

In this research an internet of things (IoT) system is designed for the purpose of industrial environment monitoring and control. The system is mainly composed of control and sensor units. Control unit has the responsibility of managing the received data form the sensor unit and then executing the developed control algorithm based on the measured parameters.  NodeMCU development kit is used as the core of the control unit. The senor unit contains gas and temperature sensors utilized for measuring the temperature and concentration of toxic gases in the monitored space. A buzzer has also been embedded in the sensor unit for alerting the occupants acoustically in the danger situations. If the monitored temperature gets higher or lower than the set levels, the air conditioning system will be automatically operated. Similarly, the fan (ventilation) system will be operated if the level of toxic gases becomes high. A mobile application, based on Blynk platform, is then developed to enable the wireless monitoring and control of the environment by the in charge people. In addition to the automatic and wireless control the manual control capability is considered in the developed IoT system.
Effect of errors on miss distance of missile trackers in active decoy environment
Authors: Lakshmi Edury Vijaya , Sastry N. N. , Rao B. Prabhakar
Published: October 2019

Lock on missiles are a major threat to vital installations. Soft kill solutions against lock on incoming missiles such as deployment of active decoys can be very effective to war of threat. The weaknesses in onboard missile tracking radars can be gainfully used to increase the miss distance between target and the missile. The effect of geometrical positioning errors of two horn monopulse missile mounted radars has been analyzed in this paper. As so gain differences between the two horns can cause variations in the miss distance. This aspect has also been studied. The variation of miss distance with jammer power to signal ratio (J/S) is also presented. It can be seen that the miss distance is always midway between the target and the decoy. Random angular positioning errors of the missile radar have been analyzed and it is found that the miss distance increases with increase of angular errors.
Dual iris authentication system using dezert smarandache theory
Authors: Ghalem Kamel Ghanem , Hendel Fatiha
Published: October 2019

In this paper, a dual iris authentication using Dezert Smarandache theory is presented. The proposed method consists of three main steps: In the first one, the iris images are segmented in order to extract only half iris disc that contains relevant information and is less affected by noise. For that, a Hough transform is used. The segmented images are normalized by Daugman rubber sheet model. In the second step, the normalized images are analyzed by a bench of two 1D Log-Gabor filters to extract the texture characteristics. The encoding is realized with a phase of quantization developed by J. Daugman to generate the binary iris template. For the authentication and the similarity measurement between both binary irises templates, the hamming distances are used with a previously calculated threshold. The score fusion is applied using DSmC combination rule. The proposed method has been tested on a subset of iris database CASIA-IrisV3-Interval. The obtained results give a satisfactory performance with accuracy of 99.96%, FAR of 0%, FRR of 3.89%, EER of 2% and processing time for one iris image of 12.36 s. 
An implementation of optimal control methods (LQI, LQG, LTR) for geostationary satellite attitude control
Authors: Djaballah Farid , Si Mohammed M. A. , Boughanmi Nabil
Published: October 2019

This paper investigates a new strategy for geostationary satellite attitude control using Linear Quadratic Gaussian (LQG), Loop Transfer Recovery (LTR), and Linear Quadratic Integral (LQI) control techniques. The sub-system satellite attitude determination and control of a geostationary satellite in the presence of external disturbances, the dynamic model of sub-satellite motion is firstly established by Euler equations. During the flight mission at 35000 Km attitude, the stability characteristics of attitude motion are analyzed with a large margin error of pointing, then a height performance-order LQI, LQG and LTR attitude controller are proposed to achieve stable control of the sub-satellite attitude, which dynamic model is linearized by using feedback linearization method. Finally, validity of the LTR order controller and the advantages over an integer order controller are examined by numerical simulation. Comparing with the corresponding integer order controller (LQI, LQG), numerical simulation results indicate that the proposed sub-satellite attitude controller based on LTR order can not only stabilize the sub-satellite attitude, but also respond faster with smaller overshoot.

 
Ensuring telecommunication network security through cryptology: a case of 4G and 5G LTE cellular network providers
Authors: Manasreh Adnan , Sharadqh Ahmed A. M. , Alkasassbeh Jawdat S. , Al-Qaisi Aws
Published: October 2019

This paper aims to present the details regarding telecommunication network security through cryptology protocols. The data was based on scientific data collection and the quantitative method was adopted. The questionnaire was developed and the primary respondents were approached who were working in 4 telecommunication networking companies namely Huawei, Ericsson, SK Telecom and Telefonica. The sample size of the research was 60 participants and the statistical analysis was used to analyze research. The finding shows that cryptology protocol such as SSH, SSL, Kerberos PGP and SET are implemented within the companies in order to secure network.
Secure data aggregation in IoT using Efficient-CSDA
Authors: S Swathi , H K Yogish
Published: October 2019

In recent days, IoT has been widely accepted and WSN (Wireless Sensor network) is being used for variety of the applications such as transportation, medical, environmental, military, it moreover the main aim to deploy the WSN is to collect the data about the given set of phenomena. The common task of WSN is to sense the data and send over the network. Moreover, due to the various purpose such as statistical analysis, the data aggregation is required.  However, the when the dynamic network topology is considered, it is considered to be the very difficult task to provide the secure and efficient data aggregation. The main issue here is to ensure the security and accuracy of the data aggregation. Hence, in this research we have proposed an algorithm named as E-SDA (Efficient Secure Data Aggregation) in order to provide the secure data. In this, the algorithm provides the flexibility to detect the dishonest honest through neighbor monitoring. Later, extensive simulation has been done in order to prove the convergence of our algorithm.
Hybrid swarm and GA based approach for software test case selection
Authors: Palak Palak , Gulia Preeti
Published: October 2019

Being a crucial step and deciding factor for software reliability, software testing has evolved a long way and always attracted researchers due to various inherent challenges. The quality of a software application depends on the effectiveness of the testing carried out during development and maintenance phase. Testing is a crucial but time consuming activity that influences the overall cost of software development. Thus a minimal but efficient test suite selection is the need of the hour. This paper presents a hybrid technique based on swarm based search technique and GA (Genetic Algorithm) for selection of promising test cases to reduce the overall development cost and time of the application. We took component based software into consideration as they offer some inherent advantages over traditional software development paradigms.
Design and implementation of a Context-Aware Health Service Platform (CAHS)
Authors: Belhadi Siham , Merzougui Rachid
Published: October 2019

Computers are no match to humans in deducing situational information from their environment and in using it in their interactions. The advent of the context-aware applications seems to offer a way out to the computer that is not context-sensitive. The context aware applications can adapt their behaviors according to the perceived context or situation, without explicit user intervention, thereby providing human-centric services. To simplify the complexity of developing applications, context aware framework, which introduces context awareness into the environment where the applications are executed, is highlighted to provide a homogeneous interface involving generic context management and adaptation solutions. This papier has focused on the design of Context-Aware Health Services (CAHS) platform, which provide a health applications framework embedded on mobile devices. Our proposed platform is capabilities for context manager and adaptations according to context changes. It is designed to base on the SOA principles for achieving a flexible and dynamic architecture.
Power system voltage collapse prediction using a new line stability index (NLSI-1): A case study of the 330-kV nigerian national grid
Authors: Samuel I. A. , Katende J. , Awosope C. O. A. , Awelewa A. A. , Adekitan A. I. , Agbetuyi F. A.
Published: October 2019

The cumulative number of historical and recent power system outages substantiates the fact that further studies are necessary for an improved solution to the issue of voltage instability on the grid and the subsequent system collapse. Voltage collapse is a serious reliability issue which inhibits the objective of running a reliable and secure power system network. In this study, a new line stability index (NLSI_1) for predicting voltage collapse is presented.  The new index considers a switching logic which is derived from the difference of voltage angle between the two load buses. The index is deployed for performance analysis using the 28-bus, 330-kV Nigeria National Grid (NNG).  The simulation implemented in MATLAB shows that the index gives the same results as Line stability index (Lmn) and Fast Voltage Stability Index (FVSI) indices. The base case and the contingency scenarios were considered during the simulation. The base case analysis using the NNG values of all the three indices FVSI, Lmn, and NLSI_1 for simulation generates a value less than one for the entire lines which implies that the NNG is stable in this mode. The values of the three indices are almost the same, which confirms the accuracy of the novel index developed. The analysis for the contingency case reveals that the load bus 16 (Gombe) which has the lowest, maximum permissible reactive load of 139.5MVAR is the weakest; also power line 16-19 is identified as the critical line. The result of the simulation confirms that the accuracy was improved by using NLSI_1.
Automatic segmentation of wrist bone fracture area by K-means pixel clustering from X-ray image
Authors: Kim Kwang Baek , Song Doo Heon , Yun Sang-Seok
Published: October 2019

Early detection of subtle fracture is important particularly for the senior citizens’ quality of life. Naked eye examination from X-ray image may cause false negatives due to operator subjectivity thus computer vision based automatic detection software is much needed in practice.  In this paper, we propose an automatic extraction method for suspisious wrist fracture regions. We apply K-means in pixel clustering to form the candidate part of possible fracture from wrist X-ray image automatically. This method can recover previously detected patterned false cases with edge detection method after fuzzy stretching. The proposed method is successful in 16 out of 20 tested cases in experiment.
Modified JSEG algorithm for reducing over-segmentation problems in underwater coral reef images
Authors: Aloun Mohammad Sameer , Hitam Muhammad Suzuri , Yussof Wan NuralJawahir Hj Wan , Hamid Abdul Aziz K Abdul , Bachok Zainuddin
Published: October 2019

The original JSEG algorithm has proved to be very useful and robust in variety of image segmentation case studies.However, when it is applied into the underwater coral reef images, the original JSEG algorithm produces over-segementation problem, thus making this algorithm futile in such a situation. In this paper, an approach to reduce the over-segmentation problem occurred in the underwater coral reef image segmentation is presented. The approach works by replacing the color histogram computation in region merge stage of the original JSEG algorithm with the new computation of color and texture features in the similarity measurement. Based on the perceptual observation results of the test images, the proposed modified JSEG algorithm could automatically segment the regions better than the original JSEG algorithm.
Human activity recognition by using convolutional neural network
Authors: Kim Hankil , Lee Sungock , Jung Hoekyung
Published: October 2019

In recent years, many researchers have studied the HAR (Human Activity Recognition) system. HAR using smart home sensor is based on computing in smart environment, and intelligent surveillance system conducts intensive research on peripheral support life. The previous system studied in some of the activities is a fixed motion and the methodology is less accurate. In this paper, vision-based studies using thermal imaging cameras improve the accuracy of motion recognition in intelligent surveillance systems. We use one of the deep learning architectures widely used in image recognition systems called Convolutional Neural Networks (CNN). Therefore, we use CNN and thermal cameras to provide accuracy and many features through the proposed method.
Sensor data identification based reagent cabinet management system
Authors: Kim Changsu , Kim Hongyoul , Jung Hoekyung
Published: October 2019

Recently, a reagent cabinet is used in a laboratory or a laboratory is required to have a system capable of identifying a dangerous situation through sensor data as various sensors are utilized. The existing system identifies the dangerous situation through various sensor data, but there is a problem that the server performs all the operations and the operation of the device is performed manually. In order to solve this problem, this paper proposes a system that can identify the dangerous situation and automatically operate the equipment through the internal environment data of the reagent cabinet. Identification of the hazardous situation is done through the master node used in the reagent cabinet, not the server. The server can continuously update the sensor data through the master node and monitor the real-time status of the reagent cabinet through the application. In this way, it is expected that the risk situation will be promptly addressed by identifying the dangerous situation in the reagent cabinet and operating the device.
An intelligent spectrum handoff scheme based on multiple attribute decision making for LTE-A network
Authors: Alhammadi Abdulraqeb , Roslee Mardeni , Alias Mohamad Yusoff , Sheikhidris Khalid , Jack Yong Jun , Bin Abas Anas , Randhava Kesh. S.
Published: October 2019

Cognitive radio networks (CRNs) play an important role in wireless communications which have the ability to significantly utilize the spectrum that not in used and reduce the current spectrum scarcity. CR allows unlicensed users (secondary users) to occupy the licensed spectrums without causing interference with licensed users (primary users). This can be achieved smoothly through four main CR procedures: spectrum sensing, spectrum decision, spectrum sharing, and spectrum  mobility. In this paper, we propose an intelligent spectrum handoff (SH) scheme based on multiple attributes decision making. The handoff decision depends on three considered parameters: received power, traffic load and arrival rate of the primary users. The simulation results show the proposed scheme outperformed the conventional scheme by reducing the probability of SH which leads to improve system performance.
Study of two-layered circular patch using moment method and genetic algorithms
Authors: Mahamdi Ahmed , Benkouda Siham , Amir Mounir , Bedra Sami
Published: October 2019

In this paper, new expressions for the effective radius and fringing capacitance have been derived to predict accurately the resonant frequency of the two-layered circular microstrip patch antenna. These expressions are obtained based on genetic algorithm and the data base is generated using moment method (MOM). The proposed model is very simple, fast, and valid for an entire range of permittivities and thicknesses of two-layered substrate. The present model has been validated by comparing our numerical results obtained for the resonant frequencies with measurements. Finaly, the effect of the two-layered substrate on the resonant charateristics of the circular microstrip patch antenna has been presented.
Modifying playfair cipher algorithm using KAJ spiral method to fit any language regardless of the number of characters
Authors: Sholi Ibrahim A. , Mohamed Mohamad A.
Published: October 2019

In this paper we proposed KAJ Spiral method for supporting PlayFair cipher algorithm to use languages other than English and utilize block with more than two characters at once. Original method does not support block of characters and other languages. The method uses a spiral shape with two axes (X, Y) and the letters are spread on the axis within circles depending on the language. We use Friedman method analysis (index of coincidence) as a tool to test and prove the efficiency of KAJ Spiral method, and we found that it is at least equally secure to the original PlayFair cipher. The aims of this is making cryptography just like mathematics a universal language such that people with different languages can use this algorithm for secure communication, and at the same time make the algorithm stronger and easy to use, with the ability to fit any language.
Product recommendation system based user purchase criteria and product reviews
Authors: Kim Jinyoung , Hwang Doyeun , Jung Hoekyung
Published: October 2019

In this paper, we propose a system that provides customized product recommendation information after crawling product review data of internet shopping mall with unstructured data, morphological analysis using Python. User searches for a proudct to be purchased and select the most important purchase criteria when purchasing the product. User searches for a proudct to be purchased and select the most important purchase criteria when purchasing the product. And extracts and analyzes only the review including the purchase criterion selected by the user among the product reviews left by other users. The positive and negative evaluations contained in the extracted product review data are quantified and using the average value, we extract the top 10 products with good product evaluation, sort and recommend to users. And provides user-customized information that reflects the user's preference by arranging and providing a center around the criteria that the user occupies the largest portion of the product purchase. This allows users to reduce the time it takes to purchase a product and make more efficient purchasing decisions.
A data modeling conceptual framework for ubiquitous computing based on context awareness
Authors: Pungus Stenly Richard , Yahaya Jamaiah Haji , Deraman Aziz , Bakar Noor Hasrina Binti
Published: October 2019

This paper introduces a framework for data modeling to support ubiquitous computing based on context-awareness.  Data always grow in term of volume, variety, velocity, and value. The problem arises when it grows exponentially. Consequently, data is anywhere and requirements change in early data definitions then data design become not as the plan.  Therefore, suitable approach with new paradigm and methods of data modeling needs to be enhanced to solve the problems in the real world. Data model must consider the active object that related to each other. Any objects may interact with each other in a ubiquitous way and recorded in digital technology. Sensors, actuator devices, and radio frequency identification technology may support communication between objects through ubiquitous computing. The data model in Ubiquitous Computing needs to restructure to become active and dynamic.  Ubiquitous computing is a model that enable all objects around the people to communicate and invisible. In order to support this paradigm, a new perspective of how data are designed and stored on each object is needed. Furthermore, using ubiquitous computing, the pervasive network can request and response information, which means the devices may communicate and has the initiative to solve a problem without human intervention.  Human wants more intelligence objects. Therefore, more sensors and memory are required. Data structures need to enhance or embedded into any devices that interact with the human.
A review of cloud oriented mobile learning platform and frameworks
Authors: Moh Noor Ahmad Shukri Bin , Atoom Marwan Nasser Yousef , Mamat Rabiei
Published: October 2019

With the continued growth of mobile devices usage, wireless communications improvement, and cloud computing evolution, many educational institutions around the world, especially universities and colleges, began to provide their students with mobile learning systems based on cloud computing. The widespread, ubiquitous, and flexible natures of mobile devices make mobile learning an attractive alternative in education, particularly when integrating it with cloud computing which is the up-to-date technology that delivers computing hardware and software as services. However, the participatory between mobile learning and cloud computing as a cloud based mobile learning (CBML) becomes one of the important methods in the learning process. Many researches have attempted to combine the unique features of CBML in a form of frameworks. These frameworks have been designed to identify, categorize, or evaluate the major components of the CBML system. This paper is an attempt to identify the important role of cloud computing technology in mobile learning, investigate the main advantages and limitations of CBML systems, and explore the previously designed CBML frameworks.
Proposal for an approach to evaluate continuity in service supply chains: Case of the Moroccan electricity supply chain
Authors: Mezouar Houda , El Afia Abdellatif
Published: October 2019

The purpose of this paper is to develop an approach to analyse and evaluate continuity in Service Supply Chain (SSC), through a case study. This approach is based on the data-driven quality strategy "Define, Measure, Analyze, Improve, Control" (DMAIC) which is used to drive Six Sigma projects, and on the characteristics of Smart Supply Chain. It combines Business process management (BPM), Supply Chain Operations Reference (SCOR), and the Root cause analysis tree diagram. The chosen case study is the electricity SCC, especially the business process 'management of electricity for residential buildings' of the Moroccan electricity SSC. The paper shows that the suggested approach identifies the discontinuity causes for the studied SSC, improves the business process behavior and manages its control by providing a dashboard that encompasses KPIs for periodically controlling of the SSC "to-be" state.
Improve of contrast-distorted image quality assessment based on convolutional neural networks
Authors: Ahmed Ismail Taha , Der Chen Soong , Jamil Norziana , Mohamed Mohamad Afendee
Published: October 2019

Many image quality assessment algorithms (IQAs) have been developed during the past decade. However, most of them are designed for images distorted by compression, noise and blurring. There are very few IQAs designed specifically for Contrast Distorted Images (CDI), e.g. Reduced-reference Image Quality Metric for Contrast-changed images (RIQMC) and NR-IQA for Contrast-Distorted Images (NR-IQA-CDI). The existing NR-IQA-CDI relies on features designed by human or handcrafted features because considerable level of skill, domain expertise and efforts are required to design good handcrafted features. Recently, there is great advancement in machine learning with the introduction of deep learning through Convolutional Neural Networks (CNN) which enable machine to learn good features from raw image automatically without any human intervention. Therefore, it is tempting to explore the ways to transform the existing NR-IQA-CDI from using handcrafted features to machine-crafted features using deep learning, specifically Convolutional Neural Networks (CNN).The results show that NR-IQA-CDI based on non-pre-trained CNN (NR-IQA-CDI-NonPreCNN) significantly outperforms those which are based on handcrafted features. In addition to showing best performance, NR-IQA-CDI-NonPreCNN also enjoys the advantage of zero human intervention in designing feature, making it the most attractive solution for NR-IQA-CDI.
Cryptographic adaptation of the middle square generator
Authors: Ali-Pacha Hana , Hadj-Said Naima , Ali-Pacha Adda , Mohamed Mohamad Afendee , Mamat Mustafa
Published: October 2019

Currently, cryptography plays a major role in various computer and technological applications. With the high number of internet users, the use of cryptography to provide information security has become a priority. Several applications such as e-mails, electronic banking, medical databases and e-commerce require the exchange of private information. While, if the connection is not secure, this sensitive information can be attacked. The best-known cryptographic systems rely on the generation of random numbers, which are fundamental in various cryptographic applications such as key generation and data encryption. In what follows, we want to use pseudo-random sequences generated by the middle square generator. In this work, it must be possible to estimate that the data produced has random characteristics, knowing that the algorithm used is deterministic. Overall, this paper focuses on the testing of pseudo-random sequences generated by the middle square generator and its use in data encryption.
Experiment study of using parallel plate sensor for the detection of conductive material
Authors: Lokmanulhakim N. , Rashid W .N. Abd , Hussin N. H. , Mukhtar M. F.
Published: October 2019

Gold is the yellow precious metal that has been used in many applications likes medicine, electronics, jewelry, investment and others. Thus, gold is one of the commodities which has high demand in the global market. In other to secure the purity of gold and to protect the retailer and consumer from fraud, the detection of gold is very important in the industry. There are many techniques have been used to detect the purity of gold material and those techniques must consider a several factors such as non-destructive, inexpensive, precise, simple and widely accepted by the jewelry industries. Electrical capacitance tomography (ECT) is the most mature non-destructive technique among various tomography. The advantages of ECT are non-radioactive, non-intrusive, high imaging speed and low cost. This paper introduces the ECT using the square sensor. The aim of his paper this to present a new method of verifying the conductive materials using a parallel plate sensor which adopted from the ECT system.
Development of crack on composite detection sensor using magnetic induction concept
Authors: Ismail N. I. , Rashid W. N. A. , Lokmanulhakim N.
Published: October 2019

A crack detection is very important to control the quality of the composite itself that been widely used in industries. There are quite a numbers of techniques which are used to detect the crack such as visual inspection, radiography, ultrasonic, eddy current magnetic particle, and penetrant testing. In this paper, it focuses on designing and implementing the system to detect a crack on the composite material using magnetic induction concept. At the early stage, the miniature of composite detection sensor using magnetic induction concept is designed using Comsol Multiphysics software to see the current induced from the system. The current value from the sensor is measured based on magnetic induction concept. A complete design of a system then is designed which include the sensor design, the main controller unit design and Bluetooth electronic application. The experiment results show that the magnetic induction concept can be used to detect crack by changing the value of current. When crack occurs the value of current will decrease due to the changes of magnetic induction.