bluuebunny/crossref_metadata_2025 huggingface dataset:
Crowd Anomaly Detection Using Motion Based Spatio-Temporal Feature Analysis
Authors: G M Basavaraj , Kusagur Ashok
Published: January 2019

Recently, the demand for surveillance system is increasing in real time application to enhance the security system. These surveillance systems are mainly used in crowded places such as shopping malls, sports stadium etc. In order to support enhance the security system, crowd behavior analysis has been proven a significant technique which is used for crowd monitoring, visual surveillance etc. For crowd behavior analysis, motion analysis is a crucial task which can be achieved with the help of trajectories and tracking of objects. Various approaches have been proposed for crowd behavior analysis which has limitation for densely crowded scenarios, a new object entering the scene etc. In this work, we propose a new approach for abnormal crowd behavior detection. Proposed approach is a motion based spatio-temporal feature analysis technique which is capable of obtaining trajectories of each detected object.  We also present a technique to carry out the evaluation of individual object and group of objects by considering relational descriptors based on their environmental context. Finally, a classification is carried out for detection of abnormal or normal crowd behavior by following patch based process. In the results, we have reported that proposed model is able to achieve better performance when compared to existing techniques in terms of classification accuracy, true positive rate, and false positive rate.
Adaptive Angular-sector Segmentation Radar Target Recognition based on Grey System
Authors: Yongsheng Xiao , Lizhen Huang , Jianjiang Zhou
Published: January 2019

The aspect sensitivity of high-resolution range profile (HRRP) leads to the anomalous change of the HRRP statistical characteristic, which is one of inextricable problems on the target recognition based on HRRP. Aiming at the HRRP statistical characteristic, an adaptive angular-sector segmentation method is proposed through based on the grey relational mode. Comparing to the equal interval angular-sector segmentation method, the new method improves the recognition performance. And these simulation results of five kinds of aircraft targets HRRPs prove the feasibility and validity.
High Quality Video Assessment Using Salient Features
Authors: Rekha Bhanu , Kumar AV Ravi
Published: January 2019

An efficient modified video compression HEVC technique based on high quality assessment saliency features presented for the assessment of high quality videos. To create an efficient saliency map we extract global temporal alignment component and robust spatial components. To obtain high quality saliency here, we combine spatial saliency features and temporal saliency features together for different macroblocks in association with transformed residuals. In this way, our saliency model outperforms all the existing techniques. In this paper, we have generated high reconstruction quality video after compression considering SFU dataset. Our experimental results outperforms all the existing techniques in terms of saliency map detection, PSNR and high-resolution quality.
Developing a Modified HMAX Model Based on Combined with the Visual Featured Model
Authors: Pourasad Yaghoub
Published: January 2019

Identify objects based on modeling the human visual system, as an effective method in intelligent identification, has attracted the attention of many researchers. Although the machines have high computational speed but are very weak as compared to humans in terms of diagnosis. Experience has shown that in many areas of image processing, algorithms that have biological backing had more simplicity and better performance. The human visual system, first select the main parts of the image which is provided by the visual featured model, then pays to object recognition which is a hierarchical operations according to this, HMAX model is also provided. HMAX object recognition model from the group of hierarchical models without feedback that its structure and parameters selected based on biological characteristics of the visual cortex. This model is a hierarchical model neural network with four layers, is composed of alternating layers that are simple and complex. Due to the high complexity of the human visual system is virtually impossible to replicate it. For each of the above, separate models have been proposed but in the human visual system, this operation is performed seamlessly, thus, by combining the principles of these models is expected to be closer to the human visual system and obtain a higher recognition rate. In this paper, we introduce an architecture to classify images based on a combination of previous work is based on the basic operation of the visual cortex. According to the results presented, the proposed model compared with the main HMAX model has a much higher recognition rate. Simulations was performed on the database of Caltech101.
Routing Protocols for Mobile Ad Hoc Network - A Survey and Analysis
Authors: Desai Rahul M , Patil B P , Sharma Davinder Pal
Published: January 2019

Ad hoc networks are mobile wireless networks where each node is acting as a router. The existing routing protocols such as Destination sequences distance vector, Optimized list state routing protocols, Ad hoc on demand routing protocol, Ad hoc on demand multipath routing protocol, Dynamic source routing are optimized versions of distance vector or link state routing protocols.  In this paper, existing protocols such as DSDV, AODV, AOMDV, OLSR and DSR are analyzed on 50 nodes Mobile Ad Hoc network with random mobility. Packet delivery ratio, delay, control overhead and throughput parameters are used for performance analysis.
A Meaningful Compact Key Frames Extraction in Complex Video Shots
Authors: Mizher Manar Abduljabbar , Ang Mei Choo , Mazhar Ahmad Abdel Jabbar
Published: January 2019

Key frame extraction is an essential technique in the computer vision field. The extracted key frames should brief the salient events with an excellent feasibility, great efficiency, and with a high-level of robustness. Thus, it is not an easy problem to solve because it is attributed to many visual features. This paper intends to solve this problem by investigating the relationship between these features detection and the accuracy of key frames extraction techniques using TRIZ. An improved algorithm for key frame extraction was then proposed based on an accumulative optical flow with a self-adaptive threshold (AOF_ST) as recommended in TRIZ inventive principles. Several video shots including original and forgery videos with complex conditions are used to verify the experimental results. The comparison of our results with the-state-of-the-art algorithms results showed that the proposed extraction algorithm can accurately brief the videos and generated a meaningful compact count number of key frames. On top of that, our proposed algorithm achieves 124.4 and 31.4 for best and worst case in KTH dataset extracted key frames in terms of compression rate, while the the-state-of-the-art algorithms achieved 8.90 in the best case.
Software Aging Forecasting Using Time Series Model
Authors: Umesh I M , Srinivasan G N , Torquato Matheus
Published: January 2019

With the emergence of virtualization and cloud computing technologies, several services are housed on virtualization platform. Virtualization is the technology that many cloud service providers rely on for efficient management and coordination of the resource pool. As essential services are also housed on cloud platform, it is necessary to ensure continuous availability by implementing all necessary measures.  Windows Active Directory is one such service that Microsoft developed for Windows domain networks. It is included in Windows Server  operating systems as a set of processes and services for authentication and authorization of users and computers in a Windows domain type network. The service is required to run continuously without downtime. As a result, there are chances of accumulation of errors or garbage leading to software aging which in turn may lead to system failure and associated consequences. This results in software aging. In this work, software aging patterns of Windows active directory service is studied. Software aging of active directory needs to be predicted properly so that rejuvenation can be triggered to ensure continuous service delivery. In order to predict the accurate time, a model that uses time series forecasting technique is built.
On-line Assessment of Voltage Stability using Synchrophasor Technology
Authors: Singh Satyendra Pratap , Singh S.P.
Published: January 2019

Series of blackouts encountered in recent years in power system have been occurred because either of voltage or angle instability or both together was not detected within time and progressive voltage or angle instability further degraded the system condition, because of increase in loading. This paper presents the real-time assessment methodology of voltage stability using Phasor Measurement Unit (PMU) with observability of load buses only in power network. PMUs are placed at strategically obtained location such that minimum number of PMU’s can make all load buses observable. Data obtained by PMU’s are used for voltage stability assessment with the help of successive change in the angle of bus voltage with respect to incremental load, which is used as on-line voltage stability predictor (VSP). The real-time voltage phasors obtained by PMU’s are used as real time voltage stability indicator. The case study has been carried out on IEEE-14 bus system and IEEE-30 bus systems to demonstrate the results.
Enhanced BFGS Quasi-Newton Backpropagation Models on MCCI Data
Authors: Azura Md. Ghani Nor , Ahmad Kamaruddin Saadi , Mohammed Ramli Norazan , Musirin Ismail , Hashim Hishamuddin
Published: January 2019

Neurocomputing is widely implemented in time series area, however the nearness of exceptions that for the most part happen in information time arrangement might be hurtful to the information organize preparing. This is on the grounds that the capacity to consequently discover any examples without earlier suppositions and loss of all-inclusive statement. In principle, the most well-known preparing calculation for Backpropagation calculations inclines toward lessening ordinary least squares estimator (OLS) or all the more particularly, the mean squared error (MSE). In any case, this calculation is not completely hearty when exceptions exist in preparing information, and it will prompt false estimate future esteem. Along these lines, in this paper, we show another calculation that control calculations firefly on slightest middle squares estimator (FFA-LMedS) for BFGS quasi-newton backpropagation neural network nonlinear autoregressive moving (BPNN-NARMA) model to lessen the effect of exceptions in time arrangement information. In the in the mean time, the monthly data of Malaysian Roof Materials cost index from January 1980 to December 2012 (base year 1980=100) with various level of exceptions issue is adjusted in this examination. Toward the finish of this paper, it was found that the upgraded BPNN-NARMA models utilizing FFA-LMedS performed extremely well with RMSE values just about zero errors. It is expected that the finding would help the specialists in Malaysian development activities to handle cost indices data accordingly.
Power System State Estimation Bad Data Detection and Identification: A Review on Issues and Alternative Formulations
Authors: Fauzana Imran Gulcharan Nurul , Mohd Nor Nursyarizal , Ibrahim Taib , Daud Hanita
Published: January 2019

State Estimation (SE) is the main function of power system where Energy Management System (EMS) is obliged to estimate the available states. Power system is a quasi-static system and hence changes slowly with time. Dynamic State Estimation (DSE) technique represents the time deviation nature of the system, which allows the forecasting of state vector in advance. Various techniques for DSE are available in the literature. This paper presents a review on different methodologies and developments in DSE, based on comprehensive survey of the available literature. From the survey it can be concluded that there are still areas in the developing DSE that can still be improved in terms of system computational time, redundancy and robustness of the system.
Chaos Embedded Symbiotic Organisms Search Technique for Optimal FACTS Device Allocation for Voltage Profile and Security Improvement
Authors: Khairuzzaman Mohamad Zamani Mohamad , Musirin Ismail , Izwan Suliman Saiful , Bouktir Tarek
Published: January 2019

Due to the ever-increasing energy demand, power system operators have attempted to cope with these demands while keeping the power system remain operable. Economic constraints have forced the power system operator to abandon their effort in expanding the power system. The increased load demand can cause the power system to suffer from voltage instability and voltage collapse, especially during contingency condition. Hence, a strategy is required to maintain the steady state operation of a power system. Various research has been conducted to tackle this problem. Therefore, this paper presents the implementation of Chaos Embedded Symbiotic Organisms Search technique to solve optimal FACTS device allocation problem in power transmission system. Various practical constraints are also considered in the optimisation process to emulate the real-life constraints in power system. The optimisation process is conducted on a 26-bus IEEE RTS has validated that the results obtained has not violated the power system stability. The results provided by the proposed optimisation technique has successfully improved the voltage profile and voltage security in the system. Comparative studies are also conducted involving Particle Swarm Optimization and Evolutionary Programming technique resulting good results agreement and superiority of the proposed technique. Results obtained from this study would be beneficial to the power system operators regarding optimisation in power system operation for the implementation in real power transmission network.
Sizing Optimization of Large-Scale Grid-Connected Photovoltaic System Using Cuckoo Search
Authors: Zakyizzuddin Bin Rosselan Muhammad , Irwan Sulaiman Shahril , Musirin Ismail
Published: January 2019

This study presents the development of Cuckoo Search (CS)-based sizing algorithm for sizing optimization of 5MW large-scale Grid-Connected Photovoltaic (GCPV) systems. CS was used to select the optimal combination of the system components which are PV module and inverter such that the Performance Ratio (PR) is correspondingly optimized. The oversized and undersized of this large-scale GCPV system can give huge impact towards the performanceof this system. Before incorporating the optimization methods, a sizing algorithm for large-scale GCPV systems was developed. Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods.The results showed that the CS-based sizing algorithm was unable to found the optimal PR for the system if compared with ISA. However, CS was outperformed ISA in producing the lowest computation time in finding the optimal sizing solution.
Behavioral Tracking in E-Learning by Using Learning Styles Approach
Authors: Baharudin Amira Fatiha , Sahabudin Noor Azida , Kamaludin Adzhar
Published: January 2019

Currently, e-learning is becoming an option as it can save the cost of education, time, and more flexible in its implementation. The main problem that arises is how to create e-learning content that is interesting and really fit the needs of the users. One way that can be done to optimize the content of e-learning is to analyze the user behavior. This study aims to analyze user (student) behavior in KALAM UMP, based on logs report (activity history), which is often called as behavioral tracking. First, the learning style of the students is determined based on Honey and Mumford Learning Styles Model by using Learning Styles Questionnaire. The analysis is done using SPSS 16.0 for Windows. The results shows that student with Reflector and Theorist learning styles access e-learning materials the most. From Spearman Correlation analysis, the relationship between learning styles and students’ behavior in e-learning is found to be very weak (rs=.276, p=.000), but statistically significant (p<0.05). In other words, students’ learning styles and behavior in e-learning have significant impacts on the improvement or degradation of students’ performance. Therefore, from the results of this study, an adaptive KALAM e-learning system which can suits the learning styles of UMP students is proposed. In adaptive e-learning system, students can access learning materials that match the students' learning needs and preferences.
Energy Power Plant in Electric Power Distribution Systems Equipping With Distance Protection
Authors: Goh Hui Hwang , Sim Sy yi , Diblawe Dahir Khere , Ali Mortar Mohamed , Ling Chin Wan , Chua Qing Shi , Goh Kai Chen
Published: January 2019

This paper suggests the theory of distance protection criteria in power distribution systems for power plant generation. Multi-developed countries have energy power plants that placed in remote areas which are far from the grid line. Hence, they should be coupled to the low power transportation systems necessarily. While higher-rating relays are adopted to preserve feeders at power substations, fuses are merely obtainable outside on feeder channel. The safe system process, space protection is dispatched to save feeders. In this review, feeders with distance relays are equipped, together with over-current protection relays and fuses. Energy power plant having distance protection system is designed the implemented system was a 6-MW unit of compressed power energy reproduction. The sample feeder was shortened to be equal four-bus experiment feeder for transmitting resolution. The fault currents have chances adopted to form protecting regions of distance relays. Protection of the power line through the designed power plants for distance relaying can decrease problem in relay location because of the impedance-based location of the distance relay. 
Types of Circuit Breaker and its Application in Substation Protection
Authors: Goh Hui Hwang , Sim Sy yi , Bin Hamzah Nur Iskandar , Mazlan Sulaiman bin , Ling Chin Wan , Chua Qing Shi , Goh Kai Chen
Published: January 2019

Power system consists of the generation, transmission, distribution, and substation. All the power system component requires suitable protection devices as the protection system to protect the system during fault occur. In this paper, the circuit breaker has been selected as one of the protection devices in several applications. The types of circuit breaker that has been reviewed in this paper are oil circuit breaker (OCB), air circuit breaker (ACB), sulphur hexafluoride (SF6) circuit breaker, vacuum circuit breaker, and DC breaker which are hybrid DC breaker and solid-state DC breaker. Normally, the systems or the circuits disrupted or damaged by the fault. To implement the protection system in the system or circuit, the type of faults and cause of faults should be known to overcome the fault. To provide the suitable voltage for the consumer, the substation is needed to control the voltage transmitted at high voltage from the generating station. Protection system is also required in a substation.
A Review of Lightning Protection System - Risk Assessment and Application
Authors: Goh Hui Hwang , Sim Sy yi , Shaari Jamil , Azali Noor Atiqah , Ling Chin Wan , Chua Qing Shi , Goh Kai Chen
Published: January 2019

 A lightning strike could bring thousands mega-ampere of current in a blink of eyes. As a result, a failure of grounding the strike may cause serious damage to the home and industrial appliances and gadgets. Hence, a lightning protection system is essential to the current transmission system. Lighting is a natural phenomenon that is unavoidable. Hence, the study of the properties and characteristics of lightning is a must in designing lighting protection system. Every application has different criteria to be fulfilled. The type of lighting protection system is categorized based on the location and user. The different of location is a public area, transportation system, power system transmission and generation system which include renewable energy source. Each area can conclude different level of protection. This paper is assessing the possibility and probability of transient impact on all applications including, public area, power system line, and generating system. The review includes countermeasure which addressed few steps to determine the effect of lightning and countermeasure of protection.
Loss Of Excitation (LOE) Protection of Synchronous Generator
Authors: Goh Hui Hwang , Sim Sy yi , Abd Samat Mohd. Nasri , Mohamed Ahmad Mahmoud , Ling Chin Wan , Chua Qing Shi , Goh Kai Chen
Published: January 2019

Synchronous generators require certain protection against loss of excitation because it can lead to harmful effect to a generator and main grid. Systems of powers are evolving with applications of new techniques to increase reliability and security, at the meantime techniques upgradation is being existed to save financial cost of a different component of power system, which affect protection ways this report discuss the way of loss of excitation protection scheme for an increase in a synchronous generator. It is obvious that when direct axis synchronous reactance has a high value, the coordination among loss of excitation protection and excitation control is not effective. This lead to restricting absorption capability of the reactive power generator. This report also reviews the suitable philosophy for setting the limiters of excitation and discusses its effect on loss of excitation protection and system performance. A protection scheme is developed to allow for utilization of machine capability and power swing blocking is developed to increase the reliability when power swing is stable.

 
Evaluation of Standard Reference Environment for Photovoltaic Nominal Operating Cell Temperature Testing in Malaysia
Authors: Hanifah M. M. M. , Zainuddin H. , Hussin M. Z.
Published: January 2019

This paper presents six months evaluation in determining Standard Reference Environment (SRE) for Photovoltaic (PV) Nominal Operating Cell Temperature (NOCT) testing of IEC61215 and IEC61646 that suits Malaysian climate. The SRE is established based on the median environmental conditions in Malaysia when solar PV is producing power. The site of the study is located at the Energy and Environment Field Lab, Universiti Teknologi MARA (UiTM) Shah Alam(3.066239ºN, 101.491685ºE). Three types of PV module technologies involved are monocrystalline, polycrystalline and copper indium diselenide (CIS) thin film. The experimental setup is a test bed that meets the IEC61215, IEC61646 and IEC61724 requirements. The measurements of        module temperature (MT) and open circuit voltage (VOC) are taken simultaneously for the three PV module technologies together with other ambient parameters of solar irradiance(SI), ambient temperature(AT), relative humidity(RH), wind speed (Ws) and wind direction(Wd). The data set is taken for a six months period from February 2017 to July 2017. Based on the results obtained, a new proposed SRE of NOCT testing for IEC61215 and IEC61646 has been established to suit Malaysian climate. The SI and AT values for the SRE are 300W/m2 and 31°C respectively.
Development of Acoustical Feature Based Classifier Using Decision Fusion Technique for Malay Language Disfluencies Classification
Authors: Hamzah Raseeda , Jamil Nursuriati , Roslan Rosniza
Published: January 2019

Speech disfluency such as filled pause (FP) is a hindrance in Automated Speech Recognition as it degrades the accuracy performance. Previous work of FP detection and classification have fused a number of acoustical features as fusion classification is known to improve classification results. This paper presents new decision fusion of two well-established acoustical features that are zero crossing rates (ZCR) and speech envelope (ENV) with eight popular acoustical features for classification of Malay language filled pause (FP) and elongation (ELO). Five hundred ELO and 500 FP are selected from a spontaneous speeches of a parliamentary session and Naïve Bayes classifier is used for the decision fusion classification. The proposed feature fusion produced better classification performance compared to single feature classification with the highest F-measure of 82% for both classes.
Multiset Controlled Grammars: A Simple Method in Regulated Rewriting Theory
Authors: Ashaari Salbiah , Turaev Sherzod , M. Tamrin M. Izzuddin , Okhunov Abdurahim , Zhukabayeva Tamara
Published: January 2019

This study focus on defining a new variant of regulated grammars called multiset controlled grammars as well as investigating their computational power. We apply a constructive theoretical approach; the intent of which is to provide new theories based on computational methods where the results are appeared in the form of examples, lemmas and theorems. In the study, we have found that multiset is powerful and yet a simple method in regulated rewriting theory. We have proved that multiset controlled grammars are at least as powerful as additive valence grammars, and they are at most powerful as matrix grammars.
An Adaptive Scheme to Achieve Fine Grained Video Scaling
Authors: Safinaz S , V. Ravi Kumar A.
Published: January 2019

A robust Adaptive Reconstruction Error Minimization Convolution Neural Network ( ARemCNN) architecture introduced to provide high reconstruction quality from low resolution using parallel configuration. Our proposed model can easily train the bulky datasets such as YUV21 and Videoset4.Our experimental results shows that our model outperforms many existing techniques in terms of PSNR, SSIM and reconstruction quality. The experimental results shows that our average PSNR result is 39.81 considering upscale-2, 35.56 for upscale-3 and 33.77 for upscale-4 for Videoset4 dataset which is very high in contrast to other existing techniques. Similarly, the experimental results shows that our average PSNR result is 38.71 considering upscale-2, 34.58 for upscale-3 and 33.047 for upscale-4 for YUV21 dataset.
An Edge Exposure using Caliber Fuzzy C-means With Canny Algorithm
Authors: Jeyaraman Gowri , Subbiah Janakiraman
Published: January 2019

Edge exposure or edge detection is an important and classical study of the medical field and computer vision.  Caliber Fuzzy C-means (CFCM) clustering Algorithm for edge detection depends on the selection of initial cluster center value. This endeavor to put in order a collection of pixels into a cluster, such that a pixel within the cluster must be more comparable to every other pixel. Using CFCM techniques first cluster the BSDS image, next the clustered image is given as an input to the basic canny edge detection algorithm. The application of new parameters with fewer operations for CFCM is fruitful. According to the calculation, a result acquired by using CFCM clustering function divides the image into four clusters in common. The proposed method is evidently robust into the modification of fuzzy c-means and canny algorithm. The convergence of this algorithm is very speedy compare to the entire edge detection algorithms. The consequences of this proposed algorithm make enhanced edge detection and better result than any other traditional image edge detection techniques.
Pulse Density Modulation Flyback Converter for LED Automotive Lighting
Authors: Rohit Shinde , Gunabalan Ramachandiran , Pavan Kumar Mehtra
Published: January 2019

 Switched mode power supply (SMPS) converter is a dc-dc power electronic converter which is used to step up or step down the dc output voltage. A dimmable driver circuit for Light Emitting Diode (LED) lamp for automotive lighting with dimming feature is used in this paper. A flyback converter is used as a driver circuit operated in discontinuous conduction mode to perform dimming control of LEDs. High overall circuit efficiency is achieved by regulating the current through the LED lamps using pulse density modulation scheme. The LED driver circuit design and operating principle is discussed in detail. A gentle current control feature is achieved by pulse density modulation technique. The high performance driver circuit is designed for 25 W LED lamps.
Neoteric Hybrid Multilevel Cascade Inverter Based on Low Switch Numbers Along with Low Voltage Stress: Design, Analysis, Verification
Authors: Esmailzadeh Rasool , Ajami A. , Banaei M.R.
Published: January 2019

Abstract: With the purpose of rein in the high voltage of flexible power systems, renovation and amendment of multi-level structures aimed at acquisition of high quality voltage is certainly required. In this regard, robust topology must be occupied that encompass the maximum output voltage levels along with minimum of switch number, of course, with taking into account of Peak Inverse Voltage (PIV). In this paper, a neoteric high-performance multilevel cascaded inverter is suggested up to the problem of repetitive output levels to be unraveled and also number of output voltage levels to be maximized. It has been constructed by series-connected multilevel inverters blocks and three-level inverter. The simulation results along with experimental results extracted by manufactured prototype have transparently approved high efficiency of proposed inverter as well as its feasibility. Apart from above, new mathematical approach has been presented to calculate and define the DC voltage sources magnitudes in asymmetric converter.
The Non-Destructive Test Method as A Simple Way to Evaluate the Quality Of Metal Core Pcbs for High Power Micro-Assemblies
Authors: Sukhanov A.V. , Artemova A.I , Litvinenko R.S
Published: January 2019

The article describes the necessity of an incoming quality control of the delivered power electronics elements especially at the stage of choosing a reliable supplier. In particular, in the field of the metal core PCBs production, there is a need to control not only its heat sink parameters, but also to control the quality of the joint interface of the metal core PCBs. Since the use of poor-quality materials or the violation of the technological process by the manufacturer can lead to the defects in the PCBs structure. Thus it can affect the heat sink efficiency and the reliability of the entire assembly. The article proposes and describes the method of nondestructive incoming quality control of metal core PCBs. This method is based on the use of ultrasonic layer-by-layer scanning for obtaining the internal structure of PCBs. The article presents the results of applying this method for the PCBs of various manufacturers. The data of the structure visualization and the influence of environment temperatures changes were also obtained. The result pictures of the tested samples before and after the thermal circling were obtained to study the possible degradation of the PCBs structure and its parameters.
Energy Efficiency of a Building Using Capacitors Optimization
Authors: Asyraf Mohd Kamaruzaman Amirul , Murtadha Othman Muhammad , Mohd Arriffin Aainaa , Musirin Ismail , Azri Abdul Razak Muhd , Zakaria Zilaila
Published: January 2019

This paper presents the optimal location and sizing of capacitors to reduce the total power losses as well as its investment cost for a distribution system in a building. The capacitors location and sizing will be randomly chosen repetitively, via Stochasitic optimization method using MATLAB® and SIMULINK® software. The optimal capacitors location and sizing will be picked via analysis and comparisons between the results. The result shows improvement in power losses with minimal investment cost whilst providing optimal sizing and location of capacitors to be installed in a building.
Online Performance Monitoring of Grid-Connected Photovoltaic System using Hybrid Improved Fast Evolutionary Programming and Artificial Neural Network
Authors: Nor Ashikin Megat Yunus Puteri , Irwan Sulaiman Shahril , Maliki Omar Ahmad
Published: January 2019

This paper presents the development of online performance monitoring methods for grid-connected photovoltaic (GCPV) system based on hybrid Improved Fast Evolutionary Programming and Artificial Neural Network (IFEP-ANN). The approach has been developed and validated using previous predicted data measurement. Solar radiation (SR), module temperature (MT) and ambient temperature (AT) has been employed as the inputs, and AC output power (PAC) as the sole output to the neural network model. The actual data from the server has been called and uploaded every five minute interval into Matlab by using FTP (File Transfer Protocol) and the predicted AC output power has been produced based on the prediction developed in the training stages. It is then compared with the actual AC output power by using Average Test Ratio, AR. Any predicted AC output power less than the threshold set up, indicates an error has been occurred in the system. The obtained results show that the hybrid IFEP-ANN gives good performance by producing a sufficiently high correlation coefficient, R value of 0.9885. Besides, the proposed technique can analyse and monitor the system in online mode. 
Performance Study of Load Flow Algorithms in Well and Ill-Conditioned Systems
Authors: Tien Tay Lea , Seng Chieng Kai
Published: January 2019

Existing transmission systems are classified as either ill systems or healthy systems. Most of the load flow algorithms works proficiently under well-conditioned systems. However, some of those algorithms fail to produce the accurate results for ill-conditioned systems. This paper investigates the performance of eight load flow algorithms based on the conventional Newton-Raphson, Fast-decoupled and Second-order Load Flow methods for a wide range of electrical bus system sizes. Tests are carried out for each load flow algorithm on six different standard bus systems, each with five different ill-conditioning levels. The results show that improved load flow model with constant Jacobian has advantages over the conventional load flow approach in both well and ill-conditioned system, especially for large-scale system.
Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle
Authors: Ramli Muhammad Faiz Bin , Shamsudin Syariful Syafiq , Legowo Ari
Published: January 2019

Achieving a robust obstacle detection system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors have their own advantages and disadvantages in detecting the appearance of the obstacles. In this paper, combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector and queue for image capturing by the camera. Next, SURF algorithm is applied to find the obstacle sizes estimation by searching the connecting feature points in the image frame. Finally, safe avoidance path for UAV is determined through the exterior feature points from the estimated width of the obstacle. The proposed method was evaluated by conducting experiments in real time with indoor environment. In the experiment conducted, we successfully detect and determine a safe avoidance path for the UAV on 6 different sizes and textures of the obstacles including textureless obstacles.
Development of Efficient Iris Identification Algorithm using Wavelet Packets for Smartphone Application
Authors: Gunawan Teddy Surya , Solihin Nurul Shaieda , Morshidi Malik Arman , Kartiwi Mira
Published: January 2019

Nowadays, iris recognition is widely used for personal identification and verification based on biometrical technology, especially in the smartphone arena. By having this iris recognition for identification and verification, the smartphone will be secured since every person have their own iris type. In this paper, we proposed an efficient iris recognition using Wavelet Packets and Hamming distance which has lightweight computational requirements while maintaining the accuracy. There are several steps needed in order to recognize the iris which are pre-processing the iris image consists of segmentation and normalization, extract the feature that available in the iris image and identify this image to see whether it match with the person or not. For comparison purposes, different types of wavelet bases will be compared, including symlets, discrete meyer, biorthogonals, daubechies, and coiflets. Performance of the proposed algorithm was tested on Chinese Academy of Sciences Institute of Automation (CASIA) iris image database. The optimum wavelet basis function obtained is symlet. Results showed that the accuracy of the proposed algorithm is 100% identification rate.
Electrical Characterization of Commercial Power MOSFET Under Electron Radiation
Authors: Ayub Wan Nurhasana binti Wan , Hasbullah Nurul Fadzlin , Rashid Abdul Wafi
Published: January 2019

This paper presents the threshold voltage shifts for both p-channel and n-channel commercial power MOSFET before and after electron irradiation. The experiment was done under the 3MeV energy of electron with dose level varies from 50KGy until 250KGy. The results were plotted and analyzed in terms of the shifted voltage characteristics. It is observed that after irradiation, both p-channel and n-channel MOSFET experiences negative threshold voltage shifts. For n-channel devices, this is due to the radiation-induced positive charges dominated in the oxide traps while for p-channel devices it is believed due to radiation-induced ionization damage.
Development of an Autonomous Remote Access Water Quality Monitoring System
Authors: Ranjbar MD. Reza , Abdalla Aisha H.
Published: January 2019

Due to the vast increase in global industrial output, rural to urban drift and the over-utilization of land and sea resources, the quality of water available to people has deteriorated greatly. Before the sensor based approach to water quality monitoring, water quality was tested by collecting the samples of water and experimentally analyzing it in the laboratories. However, in today, with time being a scarce resource, the traditional method of water quality testing is not efficient anymore. To tackle this issue, several electronic (microcontroller and sensor based) water quality monitoring systems were developed in the past decade. However, an in depth study of this current water quality testing technology shows that there are some limitations that should be taken into consideration. Therefore, an automatic, remote, and low cost water quality monitoring system has been developed. This system consists of a core microcontroller, multiple sensors, GSM module, LCD display screen, and an alarm subsystem. The quality of water is read from the physical world through the water quality testing sensors and sent to the microcontroller. The data is then analyzed by the microcontroller and the result is displayed on the LCD screen on the device. At the same time, another copy of the sensor readings is sent remotely to the user’s mobile phone in the form of SMS. If an abnormal water quality parameter is detected by any sensor, the alarm system will turn on the respective red LED for that parameter and the buzzer will give warning sound. At the same time, the abnormality of the water parameter is reported to the user through SMS. The system is aimed to be used for wide applications and by all categories of users. It can facilitate the process of water quality monitoring autonomously and with low cost; to help people improve their quality of drinking water, household water supplies and aquaculture farms, especially in rural areas where residents do not have access to standardized water supply and suffer from different diseases caused by contaminated water.
Towards Scalable Algorithm for Closed Itemset Mining in High-Dimensional Data
Authors: Zaki Fatimah Audah Md. , Zulkurnain Nurul Fariza
Published: January 2019

Mining frequent itemsets from large dataset has a major drawback in which the explosive number of itemsets requires additional mining process which might filter the interesting ones. Therefore, as the solution, the concept of closed frequent itemset was introduced that is lossless and condensed representation of all the frequent itemsets and their corresponding supports.  Unfortunately, many algorithms are not memory-efficient since it requires the storage of closed itemsets in main memory for duplication checks. This paper presents BFF, a scalable algorithm for discovering closed frequent itemsets from high-dimensional data. Unlike many well-known algorithms, BFF traverses the search tree in breadth-first manner resulted to a minimum use of memory and less running time. The tests conducted on a number of microarray datasets show that the performance of this algorithm improved significantly as the support threshold decreases which is crucial in generating more interesting rules.
Simulation of Packet Scheduling in Cognitive Long Term Evolution-Advanced
Authors: Mansor Mohamad ‘Ismat Hafizi , Ramli Huda Adibah Mohd , Asnawi Ani Liza , Isa Farah Nadia Mohd
Published: January 2019

Real Time (RT) and Non-Real Time (NRT) multimedia content demand on mobile devices are increasing at a high pace. Long Term Evolution-Advanced (LTE-A) is expected to cater these demands. However, LTE-A operates at fixed spectrum which leads to spectrum scarcity. Cognitive Radio (CR) is one the promising technologies that is used to overcome spectrum scarcity and implementation of CR into LTE-A will improve spectrum availability and efficiency of the network. Furthermore, with addition of Packet Scheduling (PS) in the cognitive LTE-A, QoS requirement of the mobile users can be guaranteed. However, the study on the stated is very limited. Thus, this paper models, simulates and evaluates performance of five well-known PS algorithms for supporting the RT and NRT multimedia contents. The simulation results show that Maximum- Largest Weighted Delay First (M-LWDF) is the best candidate for implementation in the cognitive LTE-A.
Integrated Engineering Project Management Approach for Typical Small to Medium Manufacturing Companies
Authors: Adesta Erry Yulian Triblas , Abdullah K B Mohammed , Alazemi Yahya A
Published: January 2019

The aim of this paper is to identify the problem extents and successfully applying project management in SMEs with a focus on manufacturing industries. The organization of the study was mainly divided into the activity of literature study and the investigation through a survey conduct aimed to measure the awareness and implementation of project management at the selected SMEs in Malaysia. The questionnaire was designed with a section (Section A) involving project management in general and another section (Section B) involving the implementation of it. It was found that the level of awareness and implementation of project management especially in the selected small and medium manufacturing companies in Malaysia was quite satisfying. Most of the manufacturing companies were implementing project management, but the level was depending on the organization in the company itself.

 
Analysis and Measurement of Wave Guides Using Poisson Method
Authors: Sudha M. , Kumaravel A.
Published: January 2019

The Poisson equation is used to analyze and measure the waveguide in quick and exact calculation of Green's capacity. For this reason, Green's capacity is composed as far as Jacobian elliptic capacities including complex contentions. Another calculation for the quick and precise assessment of such Green's capacity is definite. The principle advantage of this calculation is effectively appeared inside the casing of the Limit Integral Resonant Mode Expansion technique, where a generous decrease of the computational exertion identified with the assessment of the referred to Green's capacity is gotten.
Analysis of Regulated Kinase Signal Network through Feedback Loops in Extra-Cellular Signal
Authors: Periyasamy C. Periyasamy
Published: January 2019

Signal network assumes a vital part in directing the principal cell capacities, for example, cell expansion, survival, separation and motility. Improvement and investigation of scientific model can help us gain a profound comprehension of the unpredictable conduct of ERK flag transduction organizes. This paper exhibits a computational model that offers an incorporated quantitative and dynamic reproduction of ERK flag transduction arranges, actuated by epidermal development figure. The mathematic demonstrate contains the enactment energy of the pathway, a huge number of input circles and association of platform proteins. The model gives knowledge into flag reaction connections between the authoritative of EGF to its receptor at the phone surface and actuation of downstream proteins in the flagging course. The diverse impact of positive and negative input circles of the ERK flag transduction pathway were for the most part examined, showing that criticism circles were the primary affecting variable to the swaying of ERK flag transduction pathway. The forecasts of this wavering of ERK enactment concur well with the writing. It can prompt flag floods of the downstream substrates and instigate relating natural practices.
Availability of Network Improvement for Ship’s Optical Communication Range
Authors: Kumar Ganesh , Arivazhagan A. Arivazhagan
Published: January 2019

Optical correspondence networks connecting ship’s system introduces the heuristic way to deal with accessibility investigation interfacing boat's frameworks. The availabilities of individual parts have been figured, as the reason for the whole framework accessibility assessment. A few system accessibility structures and assurance situations are exhibited and the accessibility assessed. In view of the examination, the likelihood for enhancing ship's correspondence framework accessibility has been proposed, adding to the general accessibility change of ship's frameworks.
Convolutional Neural Network Based Target Recognition for Marine Search
Authors: S. Ashwin J. , Manoharan N.
Published: January 2019

The key point of marine search and rescue is to find out and recognize the distress objects. At present, the visual search method is usually adopted to detect the ships in distress, and this method can only be used at good sea condition and visibility. In this paper, a new target detection and recognition system is proposed. The parameters of radar transmitter and echo graphics and the invariant moments of radar images are extracted as the system’s recognition features, and the system’s target classifier is based on Convolutional Neural Networks (CNN). The developed recognition classifier has been tested using three kinds of target Images, the target’s features are used as the inputs of trained CNN and the outputs of networks are target classification. Sea experimental results show that the proposed method is well-clustering and with high classified accuracy.
Real Time Application of Fourier Transforms
Authors: S.Shenbaga Ezhil S.
Published: January 2019

In recent days increasing the use of Fourier transform in various applications. The Fourier transform is the simplest among the other transformation method. It is less time consuming, used in power distribution system, mechanical system, industry and wireless network. Mainly in power distribution system the mitigation of power quality disturbance require fast, accuracy and high noise immune method. In the Fourier Transform (FT) area, the advancements of oversampling, computerized sifting and clamor molding are generally received for smothering the quantization commotion. The powerful quantize bits of an ADC are enhanced in view of these techniques. In any case, when preparing the wideband signs for example, linear frequency modulation flag, these strategies can't get viable results, and need high testing rate.