bluuebunny/crossref_metadata_2025 huggingface dataset:
Fuzzy expert systems (FES) for halal food additive
Authors: Zakaria M. Zaki , Nordin Norhana , Ab Malik Ariff Md , Elias Shamsul J , Shahuddin Ahmad Zambri
Published: April 2019

Halalan Toyyiban issues acknowledged the need of additional protection for good quality assurance food and should be applied in the food industries. All the food ingredients must be safe, hygiene and nutritious to be used by the consumers. Many chemical ingredients have been added in the food production process in enhancing the food characteristics and act as stabilizer, artificial colour, preservatives, artificial sweetener. This paper presents Halal Food Additive Using Fuzzy Expert Systems (FES) to determine the Halalan Toyyiban safety rating for food additives based on consumers’ past experienced record in allergy complication. The significant of this project is to provide the consumers with health awareness to prevent the health risk that caused by these food additives. This research focuses on 42 types of Halal food additives and 12 type symptoms of allergies that are commonly faced by the consumers.
Impact of annealing temperature to the performance of hematite based humidity sensor
Authors: Ahmad W.R.W. , Mamat M.H. , Khusaimi Z. , Ismail A.S. , Rusop M.
Published: April 2019

In the present study, hematite (α-Fe2O3) nanorod structure were grown on fluorine doped tin oxide coated glass substrate via sonicated immersion approach with variation of annealing temperature (350˚C – 600˚C) in one-hour treatment. The impact of varying the temperature of annealing treatment on crystalline phase, structure morphology, optical properties and humidity sensing performance of hematite were examined. X-ray diffraction pattern disclosed a rhombohedral structure with α-phase diffraction peaks. The surface morphology images taken from field emission scanning electron microscopy revealed that the hematite nanorod arrays were grown uniformly in all samples and the average diameters of nanorods were measured in the ranges between 55 and 80 nm. Ultraviolet–visible spectroscopy measurement spectra show that all samples exhibited good optical properties. The hematite humidity sensor sample annealed at 400°C has demonstrated the highest sensitivity response (S=177.78) to humidity range between 40%RH to 90%RH.
Modelling volatility of Kuala Lumpur composite index (KLCI) using SV and garch models
Authors: Abdullah Ezatul Akma , Zahari Siti Meriam , Shariff S.Sarifah Radiah , Abdul Rahim Muhammad Asmu’i
Published: April 2019

It is well-known that financial time series exhibits changing variance and this can have important consequences in formulating economic or financial decisions. In much recent evidence shows that volatility of financial assets is not constant, but rather that relatively volatile periods alternate with more tranquil ones. Thus, there are many opportunities to obtain forecasts of this time-varying risk. The paper presents the modelling volatility of the Kuala Lumpur Composite Index (KLCI) using SV and GARCH models.  Thus, the aim of this study is to model the KLCI stock market using two models; Stochastic Volatility (SV) and Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH). This study employs an SV model with Bayesian approach and Markov Chain Monte Carlo (MCMC) sampler; and GARCH model with MLE estimator. The best model will be used to forecast the future volatility of stock returns. The study involves 971 daily observations of KLCI Closing price index, from 2 January 2008 to 10 November 2016, excluding public holidays. SV model is found to be the best based on the lowest RMSE and MAE values.
Solving RFID mobile reader path problem with optimization algorithms
Authors: Zakaria M. Zaki , Mutalib Sofianita , Rahman Shuzlina Abdul , Elias Shamsul J , Shahuddin A Zambri
Published: April 2019

Radio Frequency Identification (RFID) is a one of the fastest growing and most beneficial technologies being adopted by businesses today. One of the important issues is localization of items in a warehouse or business premise and to keep track of the said items, it requires devices which are costly to deploy. This is because many readers need to be placed in a search space. In detecting an object, a reader will only report the signal strength of the tag detected. Once the signal strength report is obtained, the system will compute the coordinates of the RFID tags based on each data grouping. In this paper, algorithms using genetic algorithm, particle swarm, ant colony optimization are proposed to achieve the shortest path for an RFID mobile reader, while covering full search area. In comparison, for path optimization, the mobile reader traverses from one node to the next, moving around encountered obstacles in its path.  The tag reading process is iterative, in which the reader arrives at its start point at the end of each round. Based on the shortest path, an algorithm that computes the location of items in the search area is used. The simulation results show that the ACO method works more effectively and efficiently compare to others when solving shortest path problems.
Jobseeker-industry matching system using automated keyword selection and visualization approach
Authors: Kamaruddin Norhaslinda , Rahman Abdul Wahab Abdul , Mohd Lawi Ramizah Amirah
Published: April 2019

Learning opportunities are available with the accessibility of new learning technologies, discovery of untraditional learning pathways and awareness of the importance of connecting current knowledge with new learning. Such situation allows the expansion in the number of courses, programs and professional certifications offered to the students resulting to the increment of the number of graduates annually. The graduates then employed by the industry for executing the job. However, there is a growing concern about the increment of unemployed graduates in the job market. One of the reasons of the mismatch between graduates’ skills and employers’ needs is that the jobseekers tend to choose wrong job because they are overwhelmed by the choices and typically they just randomly send the application because it is time consuming to filter relevant advert. Such action may have repercussion to the industry because the employers need to select relevant candidates to fill up the post from the unfiltered pile of applications making the selection process lengthy and time consuming. In this paper we proposed an automated approach to match the graduates’ and employers’ needs using a hybrid of text mining and visualization approach to facilitate jobseekers’ task of relevant job application. The important keywords are automatically extracted based on the frequency of the word used in the adverts. Then, the graduates’ skills are matched from their personalized profile. Relevant visualization approaches are incorporated to facilitate the selection. It is practical and feasible for the proposed approach to be incorporated in job searching websites that can optimize jobseekers and employers time and effort for a suitable match.
Interlaboratory data fusion repository system (InDFuRS) for tocotrienols-based treatment
Authors: Kamaruddin Norhaslinda , Wahab Abdul
Published: April 2019

Tocotrienols and tocopherols are part of the vitamin E family and have shown to produce lots of benefits especially in health supplement product. Both tocotrienols and tocopherols exist in an edible oil but varies in their ratio. It is also observed that percentage of tocopherols is higher than tocotrienols in most of our diet. Recent researches have found that tocotrienols seems to have more benefit to health especially for delaying neuro-degeneration and this has led researchers to investigate tocotrienols rich fraction (TRF) from palm kernel oil. To date, the tocotrienols extraction process is still work in progress. Hence, it is imperative that all information and results from the various laboratories experiments to be made available thus data analysis can be optimized for optimal tocotrinols production. Data acquisition from inter-laboratory experiments are valuable for collaborative researches. Efforts from multiple sources need to be combined to make it accessible for data integration. The sources of fused data can be employed as secondary back up once the data is migrated to a central repository. Traditionally data has been residing in silos across organization. Such scenario posed as a major problem especially when there are insufficient human and computational resources to manage such data. In addition, longitudinal data collections always suffer from mismanagement of the data where the data are not labeled properly using mismatched data formatting resulting to poor data readability. Therefore, a repository to facilitate data fusion using a systematic cloud-based system is proposed to ensure the data are accessible with maintained data uniformity and format and yet the security of the data is ensured as well as cost effective and fault tolerant. It is envisaged a better solution can be identified to minimize repetition of experiments and looking towards at advancement of extraction processes.
Evaluating windowing-based continuous S-transform with neural network classifier for detecting and classifying power quality disturbances
Authors: Daud K. , Abidin A. Farid , Ismail A. Paud , Hasan M. Daud A. , Shafie M. Affandi , Ismail A.
Published: April 2019

The aim of this paper is to evaluate the implementation of windowing-based Continuous S-Transform (CST) techniques, namely, one-cycle and half-cycle windowing with Multi-layer Perception (MLP) Neural Network classifier. Both, the techniques and classifier are used to detect and classify the Power Quality Disturbances (PQDs) into one of possible classes, voltage sag, swell and interrupt disturbance signal. For realizing evaluation, we proposed the methodology that include the PQD generation, the signal detection using windowing-based CST, the features extraction from S-contour matrices, PQD classification using MLP classifier. Then, we perform two type of assessments. Firstly, the accuracy assessment of chosen classifier in relation to three different training algorithms. Secondly, the execution time comparison of the training algorithms. Based on assessment results, we outline several recommendations for future work.
Conceptual mobility model of vertical handover decision in heterogeneous networks
Authors: Arbain Norakmar , Kasiran Zolidah
Published: April 2019

In heterogeneous network, maintaining seamless connectivity needs excessive efforts from various aspects such as network availability and mobile node reliability. Presently, a vertical handover management is a practical approach in facilitating the service continuity for mobile users. Many researches have been conducted in this area by considering performance improvement in delay, latency, and overhead. Preserving the Quality of Services (QoS) based on user mobility and pattern movement during handover decision has become an important aspect in vertical handover management. This paper presents the conceptual mobility model of vertical handover decision in heterogeneous network. Hence, several researches in vertical handover decision management has been reviewed regarding the issues on the vertical handover decision algorithms such as RSS Based Algorithm, MADM Based Algorithm and Intelligence Based Algorithm.  This paper highlights the current decision algorithms that integrate the traditional methods with intelligence algorithm for better optimization. In decision parameters, the user mobility pattern can be importance in terms of direction randomness and mobility speed.  Hence, a conceptual mobility-awareness model for vertical handover are been proposed in targeting some improvement of handover performance.
Performance analysis of malaysian low voltage distribution network under different solar variability days
Authors: Zolkifr Nur Izzati , Kim Gan Chin , Shamsiri Meysam
Published: April 2019

The widespread of Photovoltaic (PV) systems as one of the distributed generation technologies could have profound impact on the distribution networks operation, particularly on network losses and network voltages fluctuations. This is mainly caused by the high PV penetrations coupled with high solar variability in the countries with large cloud cover. Therefore, this paper presents an investigation on the impact of residential grid-connected PV system by utilizing a typical low voltage (LV) network in Malaysia under various solar variability days. In this study, there are three scenarios; where, each scenario were performed with different levels of PV penetration and five different solar variability days. The impacts of PV system allocation in different scenarios and various solar variability days are assessed in term of voltage unbalance and network losses. The results propose that Scenario 1: randomly allocation of PV systems across the LV network has the lowest voltage unbalance and network losses especially during overcast day
Comparison between PI, PR+HC, and modified PR+HC current controller in inverter system
Authors: Salimin S. , Armstrong M. , Jumaat S.A. , Hamdan R.
Published: April 2019

This paper presents the comparison between proportional integral (PI) current controller, proportional resonance and harmonic compensator (PR+HC) current controller and modified PR+HC current controller in the inverter system. Power electronic components like inverter and current controller uses in the system produce unwanted harmonics that affect the quality of distribution power network. In this study, development and simulation of current controller using conventional proportional integral (PI), the selective harmonic compensation scheme (PR+HC), and modified version of the latter are considered so to overcome these harmonics injection. Modification is by adding control parameter randomisation technique to the PR+HC scheme. Results compare the three controllers and proved that with modification to the selective harmonic compensation scheme, the overall current THD can be reduced
Detection of keratoconus in anterior segment photographed images using corneal curvature features
Authors: Mat Daud Marizuana , Wan Zaki Wan Mimi Diyana , Hussain Aini , Mutalib Haliza Abdul
Published: April 2019

Keratoconus is a corneal ectatic disorder with complex aetiology and may induce mild to severe visual impairment and consequently decrease the quality of life. This paper presents a new keratoconus detection method using corneal curvature features to differentiate normal and keratoconus cases. In this study, the eye images known as anterior segmented photographed images (ASPIs) are captured from side view using a smartphone’s camera. For the side-view images, the corneal curvature is segmented using spline function to measure the corneal curvature. A template disc method is implemented to quantitatively measure the steepening of the corneal curvature of the captured ASPIs. Parameters obtained from three different template disc methods, namely, nonlinear, , crossover point, , and trigonometric, , are investigated to represent the most suitable curvature feature. SVM is then employed to classify normal and keratoconus eyes. Results reveal that a standalone nonlinear method gives a reliable parameter with 90% accuracy in classifying the data. However, the classification performance has increased to 99.5% accuracy with the use of all combined features known as a feature vector, . Additionally, classification with the proposed  has successfully distinguished normal and keratoconus cases with sensitivity and specificity rates of 99% and 100%, respectively. The results portray the bright potential of this method in assisting experts during ocular screening specifically to detect keratoconus disease.
Retinal blood vessel segmentation from retinal image using B-COSFIRE and adaptive thresholding
Authors: Ali Aziah , Wan Zaki Wan Mimi Diyana , Hussain Aini
Published: April 2019

Segmentation of blood vessels (BVs) from retinal image is one of the important steps in developing a computer-assisted retinal diagnosis system and has been widely researched especially for implementing automatic BV segmentation methods. This paper proposes an improvement to an existing retinal BV (RBV) segmentation method by combining the trainable B-COSFIRE filter with adaptive thresholding methods. The proposed method can automatically configure its selectivity given a prototype pattern to be detected. Its segmentation performance is comparable to many published methods with the advantage of robustness against noise on retinal background. Instead of using grid search to find the optimal threshold value for a whole dataset, adaptive thresholding (AT) is used to determine the threshold for each retinal image. Two AT methods investigated in this study were ISODATA and Otsu’s method. The proposed method was validated using 40 images from two benchmark datasets for retinal BV segmentation validation, namely DRIVE and STARE. The validation results indicated that the segmentation performance of the proposed unsupervised method is comparable to the original B-COSFIRE method and other published methods, without requiring the availability of ground truth data for new dataset. The Sensitivity and Specificity values achieved for DRIVE and STARE are 0.7818, 0.9688, 0.7957 and 0.9648, respectively.
Multiple error correction towards optimisation of energy in sensor network
Authors: Razali Samirah , Mamat Kamaruddin , Kamal Bashah Nor Shahniza
Published: April 2019

Hybrid ARQ (HARQ) is among the optimum error controls implemented in Wireless Sensor Network as it reduces the overhead from retransmission and error correcting codes. The advancement in WSN includes the usage of high number of nodes and the increase in traffic with large data transmitted among the nodes had concerned the need for a new approach in error control algorithm. This paper proposed the multiple error correction based on HARQ process to aid the changes in channel with proper error correction assignment towards optimising the performances of WSN in terms of bit error rates, remaining energy, and latency for different types of congestion and channel conditions. In this study, we have developed the channel adaptation algorithm that can adapt to sudden changes and demonstrated the optimal error correcting codes as well as adjustment on the transmit power for the given channel condition and congestion presented. From the result analysed, the optimisation between the remaining energy and Bit Error rates happened on the basis of adapting to these different channel condition and congestion to minimize redundancies appended. From the result obtained, we concluded that by using multiple error correction algorithm with the aid of adjustment on the transmit power, the remaining energy can be optimised together with Bit Error rates and the excessive redundancies can be reduced
Design and simulation of a combined serpentine t-shape magnetorheological brake
Authors: Hidayatullah Faishal Harish , Ubaidillah Ubaidillah , Purnomo Endra Dwi , Tjahjana Dominicus Danardono Dwi Prija , Wiranto Ilham Bagus
Published: April 2019

A magnetorheological brake (MRB) is a device to dissipate rotational energy using magnetorheological fluids (MRF). MRB can change its braking torque quickly in response to external magnetic field strength. The brake is rotational, utilizing the MRF in shear mode. In this study, the geometrical design of the MRB, magnetic circuit and MRF flow path is addressed. Mathematical models are presented that describe the braking torque of the MRB. A novel prototype is introduced combining T-shape rotor model with serpentine flux magnetic circuit configuration. The rotor member is selected to direct the flux concentration at that location. Serpentine flux configuration is selected to achieve higher torque without increasing the size of MRB by activated more surface area of MRF with the magnetic flux. The finite element method is used to evaluate the magnetic flux density in MRB using FEMM 4.2. FEMM results showed that this novel design could provide sufficient magnetic flux along MRF flow path. Finally, the influence of input current to the MRB on braking torque is investigated. It is found that the braking torque in MRB increases with the increase of the input current. The prototype is formulated as foot-drop prevention orthotic. The MRB would be further integrated into ankle-foot orthoses for post-stroke patients. The design is formulated as a preliminary geometrical design, aiming to obtain the minimum required braking torque.
Intrinsic motivations for productive ageing
Authors: Karim Norisan Abd , Haron Haryani , Abdullah Natrah , Wan Adnan Wan Adilah , Mustafa Sharifah Muzlia Syed
Published: April 2019

The involvement of the elderly in the activities is low compare to younger adult due to their frailty. This paper presents intrinsic motivations for productive ageing where it highlights the factors that motivate the elderly to participate in the activities. There are thirteen elderly respondents came from the people in the urban Klang Valley. The qualitative data analysis approach is used in this study. There are five intrinsic factors, which, consist of Autonomy, Competence, Relatedness, Curiosity and Altruism that motivate the participation of the elderly in volunteering, caregiving and self-development activities in this study. This research focuses on activities that resulted intrinsic values and not on monetary value like most of past researchers. Intrinsic motivation features are significant features in ICT as the identification of the ICT features is based on motivation to use the ICT.
Augmented reality application for location finder guidance
Authors: Rosman Anatun Nadrah , Samsudin Noor Azah , Ismail Azizan , Aripin Muhammad Syariff , Khalid Shamsul Kamal Ahmad
Published: April 2019

Finding directions to a specific location can be troublesome especially when we are not familiar with a new area. Conventionally, we may want to ask people around or possibly we use Global Positioning System (GPS) navigator. However, using GPS navigator may not be the best solution if the address is not entered accurately.  Therefore, this paper presents an augmented reality (AR) application for location finder guidance. Instead, a user is only required to scan the address indicated on a surface such as card or flyer using smart phone camera.The proposed application has utilized various components of AR technology including multiple image target, virtual button and markerless features. The development of the AR application follows phases of activities in Multimedia Mobile Content Development (MMCD) model. The proposed application is found to be very interactive and convenient in finding directions to specific location.
Development of software for Ku-Band signal availability due to rain attenuation
Authors: Ya’acob Norsuzila , Tajudin Noraisyah , Alui Muhammad Rezza , Naim Nani Fadzlina , Kassim Murizah , Muhamad Wan Norsyafizan Wan
Published: April 2019

Ku-Band signal is often used for satellite communication mainly for direct to home (DTH) broadcasting. One of the major issues using this band is that the signal will be affected by raindrops. Raindrops absorb and scatter signal that operates at a frequency of more than 10 GHz. However, studies have been done to predict and measure the rainfall rate and rain attenuation. The rain attenuation in Ku-Band range and the rain rate were measured at satellite receiving dish, pointed towards the orbital slot 91.5 E over a one-year period in 2013. The cumulative distribution of rain rate obtained as well as a cumulative distribution of rain attenuation obtained are presented and compared with the rain prediction models. The aim is to get the best model to be used for the purpose of software development. It was found out that the DAH prediction model is fairly equitable when compared to direct satellite dish receiving measurements in Malaysia. The model provided a suitable baseline in developing a user interface software for weather prediction.
Rainfall–landslide early warning system (RLEWS) using TRMM precipitation estimates
Authors: Ya’acob Norsuzila , Tajudin Noraisyah , Azize Aziean Mohd
Published: April 2019

This paper presents Rainfall–Landslide Early Warning System (RLEWS) using Tropical Rainfall Measuring Mission (TRMM) precipitation estimates to notify the warning level for the possibility of landslide occurrences in Ulu Kelang, Selangor. In this study, RLEWS is developed to monitor the possibility of rainfall-induced landslide occurrences by comparing real time TRMM rainfall data with a landslide rainfall threshold. The landslide rainfall threshold is constructed by using the accumulated rainfall-accumulated rainfall (E-E) diagram method. The warning levels of rainfall threshold are classified into three levels; high, moderate and low. The analysis and notification are updating every 24 hours to provide the initial potential landslide information signal. The rainfall threshold analysis was able to detect the early signal of initial potential landslide occurrences. The aims of this study are to develop a low-cost, sustainable early warning system and web base application to send notification and awareness for residential areas in Ulu Kelang, Selangor.
Voltage instability analysis based on modal analysis technique and artificial neural network
Authors: Mohamad Nor Ahmad Fateh , Sulaiman Marizan
Published: April 2019

One of the paramount importance in the operation of electrical power system operation order to sustain the equilibrium of the system is the stability of the load buses’ voltages. If the load buses voltages are not stable, this can cause serious problem especially power system blackout. This paper presents the analysis of voltage instability in electric power system by using modal analysis technique. However, one of the challenges of modal analysis is the intencive and complex calculation procedures. In order to overcome that, this paper implements Artificial Neural Network (ANN) to improve the implementation of modal analysis technique. ANN is used to determine the participation factors obtained from the modal analysis technique. The results show that modal analysis technique is able to show which bus is close towards experiencing voltage instability. In addition, the results also show that ANN is able to predict the values of participation factors. A load bus is considered a weak bus if the bus has high tendency towards experiencing voltage instability. IEEE-14 bus test power system has been chosen as the test power system.
Congestion control in vehicular adhoc network: a survey
Authors: Elias Shamsul Jamel , Hatim Shahirah Mohamed , Darus Mohamad Yusof , Abdullah Shapina , Jasmis Jamaluddin , Ahmad R. Badlishah , Yoon Khang Adam Wong
Published: April 2019

Vehicular adhoc network (VANET) has a significant potential in reducing traffic congestion to provide a stress-free and safer platform for road drivers to travel on the road. However, the current VANET is vulnerable to several challenges which need to be overcome. Congestion control is considered as one of the main challenges in VANET due to the high dynamic topology characteristic. Reliable congestion control (CC) are necessary to provide effectient dissemination of time-critical safety messages in VANET applications; safety and non-safety applications. In this paper, we present the overview on VANET, its application and challenges. We also discuss on the congestion control and provide a brief survey on the congestion control algorithms such as vehicular cloud computing, multiplicative rate decreasing algorithm, multi-objective Tabu search, D-FPAV algorithm and beaconing strategies which have been proposed in order to provide better solutions towards achieving a successful Smart Tranporation System.
M7 subtype leukemic cell edge detection techniques with threshold value comparison and noise filters
Authors: Salam A.S.A. , Isa M.N.M. , Ahmad M.I.
Published: April 2019

The aim of this paper is to study and identify various threshold values for two prevalently used edge detection techniques, which are Sobel and Canny. The purpose is to determine which value gives an accurate result for identifying a leukemic cell. Moreover, evaluating suitability of edge detectors is also essential as feature extraction of cell depends greatly on image segmentation (edge detection). Firstly, an image of M7 subtype of Acute Myelocytic Leukemia (AML) is selected due to its diagnosing which were found lacking. Next, apply noise filters for the best of image quality. Thus by comparing image with no filter, median and average filters, useful information can be acquired. Each edge detectors is fixed with threshold value of 0-0.5 but for Cann edge detection the value can increase until 0.9. From the research, it is found that Canny edge with no filter and a threshold value of 0.7 gives a clearer image with less noise reduction.
Autonomous coop cooling system using renewable energy and water recycling
Authors: Khalid Shamsul Kamal Ahmad , Che Dan Nurul Shafiqah , Samsudin Noor Azah , Aripin Muhammad Syariff , Nordin Nor Amirul Amri
Published: April 2019

Extreme temperature in a chicken coop can significantly affect the growth and productivity of poultry. Therefore, the temperature inside the chicken coop need to be controlled to protect it from extreme temperatures. Most of the technology use electrical energy supplied to an evaporative cooling system to control the temperature of a coop. This paper presents an autonomous chicken coop cooling system using renewable energy and water recycling (REMACT). In this study, a monitoring system with necessary hardware, control application, powered with solar power source and water recycling, has been developed. The proposed cooling system consists of hardware part such as an Internet of Things (IOT) controller platform, temperature sensor, solar panel, water pump, water storage, water drain and pipe. When the temperature sensor detects extreme temperature more than 28℃ in a chicken coop, the water in storage tank will flow throughout the pipe and pass into water pump before it irrigates the chicken coop roof. When the temperature is below 22℃, the bulb will light up to transfer heat to the chicken coop and cause the temperature drop back to a healthy range. The water drain that is attached to the roof will collect the water and return the water back to the water storage again. The software components required by the project are Arduino IDE, Thinger.io, and Android Studio Framework. Several experiments have been conducted with hot and cold scenarios. The system was able to stabilise the temperature back to a healthy range. A usability testing result demonstrates 80% satisfactory rate. The findings from the experiments show that IoT, renewable energy and water recycling have the potential for temperature control of a chicken coop.
Active and reactive power management of grid connected photovoltaic system
Authors: Jeman Ameerul A. J. , Hannoon Naeem M. S. , Hidayat Nabil , Adam Mohamed.M.H. , Musirin Ismail , V Vijayakumar.
Published: April 2019

Voltage-source converter (VSC) topology is widely used for grid interfacing of distributed generation (DG) systems such as the photovoltaic system (PV). Since the operation of the VSC is essential to ensure quality of active and reactive power injected to the grid, a control approach is needed to deal with the uncertainties in the grid such as faults. This paper presents a non-linear controller design for a three-phase voltage source converter (VSC). The dynamic variables adopted for the VSC are the instantaneous real and reactive power components. The control approach that interface the VSC between the PV system and the grid are subjected to the current-voltage based. PV system injects active power to the grid and local load while utility grid monitors the power compensation of load reactive power. The proposed non-linear control strategy is implemented for the VSC to ensure fast error tracking and finite convergence time. The adaptive nature of the proposed non-linear control provides more robustness, less sluggish fault recovery compared to conventional PI control. The comprehensive numerical model is demonstrated in MATLAB script environment with power system disturbances such as faults in the grid. The simulation of proposed system is being carried out in MATLAB/SIMULINK environment to validate the control scheme. The proposed control system regulates the VSC ac side real and reactive power component and the dc side voltage.
Simulation on microgrid connected PV system under balance and unbalance fault
Authors: Jeman Ameerul A. J. , Hannoon Naeem M. S. , Hidayat Nabil , Adam Mohamed M. H. , Musirin Ismail , V Vijayakumar
Published: April 2019

This paper presents an analysis in Matlab/Simulink of a three-phase photovoltaic system under balance and unbalance faults in Matlab/Simulink. The aim of this paper is to investigate the performance of the system under various types of fault. The simulation involved various types of faults occurring at different distances from the point of common coupling of the PV system. This paper also aimed to identify what type of fault that may severely damage the system. The simulation results presented in this paper show that the three-phase fault in the microgrid was severely affecting the system since it involved all the three phases of the system while the distance of the fault occurrence is less influenced in the system. The purpose of this research is to observe the effect on the system based on the types of faults occur and the distance faults occur.
Small signal fault analysis for renewable energy (Wind) power system distributed generation by using MATLAB software (Simulink)
Authors: Jeman Ameerul A. J. , Hannoon Naeem M. S. , Hidayat Nabil , Adam Mohamed.M.H. , Musirin Ismail , V Vijayakumar.
Published: April 2019

In distribution system, wind power plants are becoming popular renewable energy sources. It employs Doubly Fed Induction Generator (DFIG) to generate power based on wind conversion. Short and long transmission lines, presence of faults and presence of Static Synchronous Compensator (STATCOM) are highlighted issues in this paper. Basically, this research develops investigations on some electrical variables such as voltage and current to control them. Distribution Static Synchronous Compensator (DSTATCOM) is proposed in this paper. Wind farm acts as a source while DSTATCOM is connected to the distribution system with a DFIG based wind farm. The controller proposed is DSTATCOM is modeled and simulated in MATLAB/SIMULINK and the results are given. A microgrid based small signal analysis is performed in the laboratory using MATLAB and different comparisons are made and simulation case studies are presented and validated.
Optimisation of zinc oxide surge arrester design using gravitational search algorithm and imperialist competitive algorithm
Authors: Abd Halim Syahirah , Mohamed Azah , Mohamed Kamari Nor Azwan , Ayob Afida , Abu Bakar Ab Halim , Illias Hazlee Azil
Published: April 2019

Reducing electric field stress near the energised end of surge arresters is very important because it may increase the lifetime of the highly stressed ZnO column in vicinity of the high voltage electrode. Most of previous works were based on manufacturers’ procedures and trial and error method to improve the surge arrester designs. In this work, optimisation of ZnO surge arrester design models using Gravitational Search Algorithm (GSA) and Imperialist Competitive Algorithm (ICA) is proposed. The surge arrester models were developed using finite element analysis (FEA) and used to determine the electric field distribution. The optimisation methods were used to determine the arrester design parameters which yield the minimum electric field stress surrounding the energized end of the surge arresters. GSA is less complex since it requires only two parameters to be adjusted i.e. mass and velocity while ICA demonstrates faster convergence and better achievement of global optimum. The performance of the proposed methods was then compared with the manufacturer’s test data and previously developed methods.
Hunger and stress monitoring system using galvanic skin response
Authors: Gogate Uttara Dhananjay , Bakal Dr. Jagdish Wasudeorao
Published: April 2019

In the world, roughly more than 3 million people are affected by muscle power loss diseases which cause lack of communication. Further, this lack of communication is a severe problem with hunger and stress, which sometimes proves to be fatal. It is essential to monitor physical parameters such as hunger and mental stress of the patient. To observe hunger and stress, galvanic skin response (GSR) sensor is a most preferred method because it measures the conductance of skin due to sweating. We have designed new hunger and stress monitoring system (HS-MS) that helps patients and their caretakers to monitor stress and hunger level. HS-MS is two electrodes system that attaches to two fingers (index and middle) of the patient and monitors starvation and tension. According to the response of the sensor, caretakers can identify hunger and even the mental stress conditions of the patient. In all, 35 patients were examined using HS-MS system and 20 of them were used as a control. Overall system accuracy was found out to be 86.6% and response time of HS-MS 5 seconds. Sensitivity with respect to hunger and stress was about 99.9% and 73.3% respectively. Thus HS-MS can be identified as a helpful tool to provide comfort to the patient easily and can be used in hospitals or homes with lonely elderly people.
Speech intelligibility enhancement for Thai-speaking cochlear implant listeners
Authors: Dachasilaruk Siriporn , Jantharamin Niphat , Rungruang Apichai
Published: April 2019

Cochlear implant (CI) listeners encounter difficulties in communicating with other persons in noisy listening environments. However, most CI research has been carried out using the English language. In this study, single-channel speech enhancement (SE) strategies as a pre-processing approach for the CI system were investigated in terms of Thai speech intelligibility improvement. Two SE algorithms, namely multi-band spectral subtraction (MBSS) and Weiner filter (WF) algorithms, were evaluated. Speech signals consisting of monosyllabic and bisyllabic Thai words were degraded by speech-shaped noise and babble noise at SNR levels of 0, 5, and 10 dB. Then the noisy words were enhanced using SE algorithms. The enhanced words were fed into the CI system to synthesize vocoded speech. The vocoded speech was presented to twenty normal-hearing listeners. The results indicated that speech intelligibility was marginally improved by the MBSS algorithm and significantly improved by the WF algorithm in some conditions. The enhanced bisyllabic words showed a noticeably higher intelligibility improvement than the enhanced monosyllabic words in all conditions, particularly in speech-shaped noise. Such outcomes may be beneficial to Thai-speaking CI listeners.
Design and implementation of embedded auto car parking system using FPGA for emergency conditions
Authors: Yong Khor Jing , Salih Muataz H.
Published: April 2019

An automatic car parking system using FPGA based on emergency conditions was proposed to detect the driver’s condition and perform specific tasks such as warn the drivers and automatic parking depends on the behavior of the driver. Long journey driving on highway will lead loss of concentration of driver quickly and also cause the driver doze off. Based on statistics, driver tends to fall asleep more on high-speed, long, boring highway. Most crashes occur between 4.00a.m-6.00a.m and midnight 12.00a.m till 2.00a.m. Besides, heart attack during driving will also harm to other road users. The risk of accident will increase due to these conditions.
 In this paper, automatic car parking system using FPGA based on emergency conditions was proposed to detect the driver’s condition and perform specific tasks such as warn the drivers and automatic parking depends on the behavior of the driver. At the same times, this system can avoid all the obstacles and cars on the road from time to time. Input data management unit was designed as control unit for input data sensors of input and output control. Main processing was designed as speed controller and also the steering controller. Speed controller used to control the speed of vehicle while driving on the road by detecting the obstacles. Steering controller was designed to control automatic car parking and also assisted with sensors around the vehicles. Sensors were tested with many materials so that the system can flexible with any conditions. The total of 1083 logic elements and 676 registers being used in this project and up to 1.6GHz as operating frequency. The complete design is able to avoid obstacles surrounding of host vehicles and parked at a safe area automatically after heart attack of driver detected. Then, GSM send GPS coordination to hospital.
Traffic congestion detection in a city using clustering techniques in VANETs
Authors: Mohanty Anita , Mahapatra Sudipta , Bhanja Urmila
Published: April 2019

Road traffic congestion, a serious illness in developing regions, is one of the biggest problems in our day-to-day life, resulting in delays, wastage of fuel and money. In this paper, a new model is developed using Simulation of Urban Mobility (SUMO) simulator for simulating a realistic traffic scenario for a large city like Bhubaneswar where, traffic congestion is a critical issue. In a city, traffic congestion is characterised by many parameters such as rapid growth of population, number of four wheelers, inadequate and poor road infrastructures and shortage of physical plan to govern the developments, which are focused on enhancing the volume of the roads by raising the number of lanes, over-passes, underpasses and over-bridges at many junctions. However, for the success of these master plans to fully overcome the congestion issues, it is necessary to transmit the congestion information to vehicles coming towards a congestion area by using a Vehicular Ad-hoc Network. This paper analyzes clustering techniques in Vehicular Ad-hoc Networks to detect congestion in roads with the minimal infrastructural support. The raw data from vehicles are classified using cluster analysis. Out of a number of algorithms that are used to solve the congestion detection problem, three important algorithms such as Centroid based -means, object based FCM and FKM algorithms are compared in this work on the basis of data points and number of clusters. The results of the algorithms are close to each other, but fuzzy techniques are preferable as the traffic situations are dynamic in nature.
Ring oscillator physically unclonable function using sequential ring oscillator pairs for more challenge-response-pairs
Authors: Loong Teo Julius Han , Nor Hashim Noor Alia , Ghazali Azrul , Azlee Hamid Fazrena
Published: April 2019

The ring oscillator physically unclonable function (ROPUF) is one of the several types of PUF that has great potential to be used for security purposes. An alternative ROPUF design is proposed with two major differences. Firstly, the memristor is included in the ring oscillators as it is claimed to produce a more random oscillation frequency. Other reasons are its memory-like properties and variable memristance, relative compatibility with CMOS, and small size. Secondly, a different method of generating the response is implemented whereby a sequence of selection of ring oscillator pairs are used to generate a multiple bit response, rather than using only one ring oscillator pair to generate a single bit response. This method significantly expands the set of challenge-response pairs. The proposed memristor-based ROPUF shows 48.57%, 51.43%, and 51.43% for uniqueness, uniformity, and bit-aliasing, respectively. Also, modelling by support vector machine (SVM) on the proposed memristor-based ROPUF only shows 61.95% accuracy, thereby indicating strong resistance against SVM.
A comparative study of sentiment analysis using SVM and SentiWordNet
Authors: Fikri Mohammad , Sarno Riyanarto
Published: April 2019

Sentiment analysis has grown rapidly which impact on the number of services using the internet popping up in Indonesia. In this research, the sentiment analysis uses the rule-based method with the help of SentiWordNet and Support Vector Machine (SVM) algorithm with Term Frequency–Inverse Document Frequency (TF-IDF) as feature extraction method. Since the number of sentences in positive, negative and neutral classes is imbalanced, the oversampling method is implemented. For imbalanced dataset, the rule-based SentiWordNet and SVM algorithm achieve accuracies of 56% and 76%, respectively. However, for the balanced dataset, the rule-based SentiWordNet and SVM algorithm achieve accuracies of 52% and 89%, respectively.
A comparison between the secp256r1 and the koblitz secp256k1 bitcoin curves
Authors: Houria Azine , Mohamed Abdelkader Bencherif , Abderezzak Guessoum
Published: April 2019

Bitcoin uses elliptic curve cryptography for its keys and signatures, but the specific secp256k1 curve used is rather unusual. The ECDSA keys used to generate Bitcoin addresses and sign transactions are derived from some specific parameters. Due to this characteristic, several questions come up concerning Satoshi’s choice of this curve rather than that of the NIST standard secp256r1 curve. Former President Dan Brown’s address to Bitcoin users on the Bitcoin talk.org online forum concerning the use of secp256k1 in Bitcoin of SECG showed his surprise to see someone uses SECG secp256k1 instead of secp256r1 of NIST.In this article, we will analyze the random secp256r1 curve and the Koblitz Secp256k1 curve (parameters, equation, automorphism…), by giving the strengths and weaknesses of each one of them, in order to justify the choice of Bitcoin’s creator, and then we will tackle the mining using the new graphic cards.
Anomaly-based intrusion detector system using restricted growing self organizing map
Authors: Christyawan Tomi Yahya , Supianto Ahmad Afif , Mahmudy Wayan Firdaus
Published: April 2019

The rapid development of internet and network technology followed by malicious threats and attacks on networks and computers. Intrusion detection system (IDS) was developed to solve that problems. The development of IDS using machine learning is needed for classifying the attacks. One method of the classification is Self-Organizing Map (SOM). SOM able to perform classification and visualization in learning process to gain new knowledge. However, the SOM has less efficient in learning process when applied in Big Data. This study proposes Restricted Growing SOM method with clustering reference vector (RGSOM-CRV) and Parallel RGSOM-CRV to improve SOM efficiency in classification with accuracy consideration to solve Big Data problem. Growing process in RGSOM is restricted by maximum nodes and growing threshold, the reupdate weight process will update unused reference vector when map size already maximum, these two processes solve the consuming time of regular GSOM. From the results of this research against KDD Cup 1999 dataset, proposed method Parallel RGSOM-CRV able to give 91.86% accuracy, 20.58% false alarm rate, 95.32% recall or detection rate, and precision is 94.35% and time consuming is outperform than regular Growing SOM. This proposed method is very promising to handle big data problems compared with other methods.
An english-language teaching plan for children in the internet of things environment
Authors: Moradi Mohammad , Rahsepar Fard Kheirollah
Published: April 2019

An important topic that need to investigate is teaching of English language. In most educational methods, a series of pre-defined and fixed subjects are used for all individuals. There is also less attention paid to modern methods in education of English language. In this paper we present an application as a modern method in education of English language. In the proposed algorithm that is in the internet of things environment, has paid attention to teaching of English language, includes the use of objects, images, pronunciation, the use of vocabulary in sentences and texts, the relevance of content with the age and culture of the child, and the relevance of the content of the courses and exercises with the amount of learning each child.