bluuebunny/crossref_metadata_2025 huggingface dataset:
What affects digitalization process in developing economies? An evidence from SMEs sector in Oman
Authors: Alraja Mansour Naser , Hussein Muawya Ahmed , Ahmed Hanaa Mahmoud Sid
Published: October 2020

The main objective of this paper is to investigate the SMEs’ leader perspective about the basic factors influencing the transformation into digitalization by SMEs they lead, using technological, organizational, and environmental (TOE) Model. The data were collected from 61 SMEs leaders in Oman, to achieve the study objective TOE model has been adopted. Internal consistency and data normality, and factor analysis were implemented. Structural equation modeling (SEM) used to test the proposed hypotheses. The outcomes of SEM indicate that TOE factors are significantly affects the ability of SMEs to digitalize their business process. The study findings come in the context of Omani definition of SMEs. More, no control was made for industry type to which SMEs participants are belong. Leaders of SMEs should frame strategies to simplify the digital transformation of their enterprises and attempt to provide organizational and technological facilities that will smooth their digitalization which will improve SMEs capabilities, as well as, increasing the international competitiveness of the SMEs. To the best of the authors' knowledge, this study is one of the first that investigated the digital transformation among SMEs from the leaders’ perspective in Oman.
An efficient apriori algorithm for frequent pattern mining using mapreduce in healthcare data
Authors: Sornalakshmi M. , Balamurali S. , Venkatesulu M. , Krishnan M. Navaneetha , Ramasamy Lakshmana Kumar , Kadry Seifedine , Lim Sangsoon
Published: October 2020

The development for data mining technology in healthcare is growing today as knowledge and data mining are a must for the medical sector. Healthcare organizations generate and gather large quantities of daily information. Use of IT allows for the automation of data mining and information that help to provide some interesting patterns which remove manual tasks and simple data extraction from electronic records, a process of electronic data transfer which secures medical records, saves lives and cuts the cost of medical care and enables early detection of infectious diseases. In this research paper an improved Apriori algorithm names Enhanced Parallel and Distributed Apriori (EPDA) is presented for the health care industry, based on the scalable environment known as Hadoop MapReduce. The main aim of the work proposed is to reduce the huge demands for resources and to reduce overhead communication when frequent data are extracted, through split-frequent data generated locally and the early removal of unusual data. The paper shows test results, whereby the EPDA performs in terms of the time and number of rules generated with a database of healthcare and different minimum support values.
Employing non-orthogonal multiple access scheme in UAV-based wireless networks
Authors: Le Chi- Bao , Do Dinh- Thuan
Published: October 2020

This paper studies the two-hop transmission relying unmanned aerial vehicle (UAV) relays which is suitable to implement in the internet of things (IoT) systems. To enhance system performance in order to overcome the large scale fading between the base station (BS) and destination as well as achieve the higher spectrum efficiency, where non-orthogonal multiple access (NOMA) strategies were typically applied for UAV relays to implement massive connections transmission. In particular, outage probability is evaluated via signal to noise ratio (SNR) criterion so that the terminal node can obtain reasonable performance. The derivations and analysis results showed that the considered fixed power allocation scheme provides performance gap among two signals at destination.The numerical simulation confirmed the exactness of derived expressions in the UAV assisted system.
Enhancing reliability of electricity supply of city electric networks cities of Dushanbe
Authors: Sidorov Alexander Ivanovich , Tavarov Saidjon
Published: October 2020

The article is devoted to the actual problem of how to improve the reliability of the urban electric network. Based on the statistical analysis of the breakdown of electrical equipment in urban distribution networks in Dushanbe for the periods of 2017-2018 and for the reasons of damage leading to these emergency outages, the factors that affect the distribution of damage leading to emergency outages are identified. Taking into account the identified factors, a power consumption forecasting system is proposed that takes into account the local conditions of the city of Dushanbe. it allows us to suggest a way to control the operating parameters of the electric network, thereby increasing the reliability of the city's electric network in Dushanbe based on the recommendation of power consumption standards. Implementation of the control of the proposed method for improving the reliability of power supply to the urban electric network is proposed on the basis of the functionality of modern smart electricity metering using the control algorithm. To implement the control algorithm, schematic design for receiving and transmitting information from smart power metering to the data collection centre is proposed.
Hardware-software partitioning using three-level hybrid algorithm for system-on-chip platform
Authors: Xian Tiong Reng , Halim Zaini Abdul , Leong Ching Chia , Gim Tan Jiunn
Published: October 2020

This study discusses hardware-software partitioning, which is useful for system-on-chip (SoC) applications. Hardware-software partitioning attempts to obtain the lowest execution time by combining a hardware processor system and a field programmable gate array on the SoC platform in embedded system applications. A three-level hybrid algorithm called GAGAPSO is proposed in this study. The algorithm consists of two successive genetic algorithms (GAs) and one particle swarm optimization (PSO). The drawbacks of these two algorithms are GA has low convergence speed and PSO has premature convergence because of low diversity. These algorithms are combined in this study to achieve high-capacity global convergence and enhanced search efficiency. In this study, three algorithms are developed, namely, GA, GAPSO and GAGAPSO using MATLAB. These algorithms are evaluated on the basis of the number of nodes and the minimum cost that can be achieved. The number of nodes varies from 10 to 1000 nodes. The minimum cost and the number of iterations to achieve the minimum cost are recorded. Results show that GAGAPSO can converge faster than GA and GAPSO. Furthermore, GAGAPSO can achieve the lowest cost for all nodes.
Drunken drive detection with smart ignition lock
Authors: Muthukarpan S. L. A. , Osman M. N. , Jusoh M. , Sabapathy T. , Rahim M. K. A. , Elshaikh M. , Khalib Z. I. A.
Published: October 2020

Drink and drive issue have become solemnly that needs immediate attention. This is due to drivers’ ignorance towards road rules and regulations and their selfish attitude that caused loss of innocent lives. Although previously there is a drunk detecting mechanism using breathalyzer but it isn’t suitable for current fast-paced lifestyle. Therefore, to overcome these issues, this system is proposed. This system is fixed on vehicle’s steering to measure alcohol concentration reading using MQ-3 sensor from the driver’s exhaled breath. If the driver found to be drunk beyond the threshold level of 400 ppm, then ignition lock is activated and the car engine does not start till alcohol concentration falls to a safe level. Or, if the driver consumes an alcoholic drink while driving, upon exceeding permissible limit, the car slows down till it stops. Then, the location of the vehicle is tracked and sent as Google Map integrated link via text message to authorized unit. Simultaneously, the car buzzer goes off while the car slows down so that surrounding road users are aware of the driver’s condition and drives at a distance. The proposed detection system is highly potential to be implemented for reducing the drunk and drive accidents.
A fuzzy multi-criteria decision-making method for purchasing life insurance in India
Authors: Pattnaik Chinmaya Ranjan , Mohanty Sachi Nandan , Mohanty Sarita , Chatterjee Jyotir Moy , Jana Biswajit , Diaz Vicente Garcia
Published: October 2020

Life insurance is an agreement between an insured and an insurer, where the insurer pays out a sum of money either on a specific period or the death of the insured. Now a day, People can buy a policy through an online platform. There are a lot of insurance companies available in the market, and each company has various policies. Selecting the best insurance company for purchasing an online term plan is a very complex problem. People may confuse to choose the best insurance company for buying an online term. It is a multi-criteria decision making (MCDM) problem, and the problem consists of different criteria and various alternatives. Here in this paper, a model has been proposed to solve this decision-making problem. In this model, a fuzzy multi-criteria decision-making approach combined with technique for order preference by similarity to ideal solution (TOPSIS) and it has been applied to rank the different insurance companies based on online term plans. The experimental results show that the life insurance corporation of India (LIC) gets the top rank out of 12 companies for purchasing an online term plan. A sensitivity analysis has been performed to validate the proposed model.
Enhancement of digital signature algorithm in bitcoin wallet
Authors: Jasem Farah Maath , Sagheer Ali Makki , Awad Abdullah M.
Published: October 2020

Bitcoin is a peer-to-peer electronic cash system largely used for online financial transactions. It gained popularity due to its anonymity, privacy, and comparatively low transaction cost. Its wallet heavily relies on Elliptic Curve Digital Signature Algorithm (ECDSA). Weaknesses in such algorithms can significantly affect the safety and the security of bitcoin wallets. In this paper, a secure key management wallet was designed based on several changes in the wallet parts. In the cold wallet, we employed an image-based passphrase to achieve a strong entropy source of master seed. The hot wallet, the proposed key_ Gen algorithm is modifying to the key generation step of the ECDSA that it is to generate a fresh key pair at each transaction. The final part ensures recovering all keys on both hot and cold wallets without daily backups in case of losing the wallet. The findings prove that the proposed cold wallet is resisting against a dictionary attack and overcoming the memorizing problem. The proposed hot wallet model acquires good anonymity and privacy for bitcoin users by eliminating transaction likability without additional cost. The execution time for signing a transaction of the proposed model is~70 millisecond, which is then important in the bitcoin domain.
An improved age invariant face recognition using data augmentation
Authors: Okokpujie Kennedy , John Samuel , Ndujiuba Charles , Badejo Joke A. , Osaghae Etinosa Noma-
Published: October 2020

In spite of the significant advancement in face recognition expertise, accurately recognizing the face of the same individual across different ages still remains an open research question. Face aging causes intra-subject variations (such as geometric changes during childhood adolescence, wrinkles and saggy skin in old age) which negatively affects the accuracy of face recognition systems. Over the years, researchers have devised different techniques to improve the accuracy of age invariant face recognition (AIFR) systems. In this paper, the face and gesture recognition network (FG-NET) aging dataset was adopted to enable the benchmarking of experimental results. The FG-Net dataset was augmented by adding four different types of noises at the preprocessing phase in order to improve the trait aging face features extraction and the training model used at the classification stages, thus addressing the problem of few available training aging for face recognition dataset. The developed model was an adaptation of a pre-trained convolution neural network architecture (Inception-ResNet-v2) which is a very robust noise. The proposed model on testing achieved a 99.94% recognition accuracy, a mean square error of 0.0158 and a mean absolute error of 0.0637. The results obtained are significant improvements in comparison with related works.
Generation of high dynamic range for enhancing the panorama environment
Authors: Al_airaji Roa'a M. , Aljazaery Ibtisam A. , Al_Dulaimi Suha Kamal , Alrikabi Haider TH.Salim
Published: October 2020

This paper presents a methodology for enhancement of panorama images environment by calculating high dynamic range. Panorama is constructing by merge of several photographs that are capturing by traditional cameras at different exposure times. Traditional cameras usually have much lower dynamic range compared to the high dynamic range in the real panorama environment, where the images are captured with traditional cameras will have regions that are too bright or too dark. A more details will be visible in bright regions with a lower exposure time and more details will be visible in dark regions with a higher exposure time. Since the details in both bright and dark regions cannot preserve in the images that are creating using traditional cameras, the proposed system have to calculate one using the images that traditional camera can actually produce. The proposed systems start by get LDR panorama image from multiple LDR images using SIFT features technology and then convert this LDR panorama image to the HDR panorama image using inverted local patterns. The results in this paper explained that the HDR panorama images that resulting from the proposed method is more realistic image and appears as it is a real panorama environment.
Multischeme feedforward artificial neural network architecture for DDoS attack detection
Authors: Muhammad Arif Wirawan , Foozy Cik Feresa Mohd , Mohammed Kamaruddin Malik bin
Published: October 2020

Distributed denial of service attack classified as a structured attack to deplete server, sourced from various bot computers to form a massive data flow. Distributed denial of service (DDoS) data flows behave as regular data packet flows, so it is challenging to distinguish between the two. Data packet classification to detect DDoS attacks is one solution to prevent DDoS attacks and to maintain server resources maintained. The machine learning method especially artificial neural network (ANN), is one of the effective ways to detect the flow of data packets in a computer network. Based on the research that has carried out, it concluded that ANN with hidden layer architecture that contains neuron twice as neuron on the input layer (2n) produces a stable detection accuracy value on Quasi-Newton, Scaled-Conjugate and Resilient-Propagation training functions. Based on the studies conducted, it concluded that ANN Architecture sufficiently affected the Scaled-Conjugate and Resilient-Propagation training functions, otherwise the Quasi-Newton training function. The best detection accuracy achieved from the experiment is 99.60%, 1.000 recall, 0.988 precision, and 0.993 f-measure using the Quasi-Newton training function with 6-(12)-2 neural network architecture.
A novel technique for speech encryption based on k-means clustering and quantum chaotic map
Authors: Khaleel Amal Hameed , Abduljaleel Iman Qays
Published: October 2020

In information transmission such as speech information, higher security and confidentiality are specially required. Therefore, data encryption is a pre-requisite for a secure communication system to protect such information from unauthorized access. A new algorithm for speech encryption is introduced in this paper. It depends on the quantum chaotic map and k-means clustering, which are employed in keys generation. Also, two stages of scrambling were used: the first relied on bits using the proposed algorithm (binary representation scrambling BiRS) and the second relied on k-means using the proposed algorithm (block representation scrambling BlRS). The objective test used statistical analysis measures (signal-to-noise-ratio, segmental signal-to-noise-ratio, frequency-weighted signal-to-noise ratio, correlation coefficient, log-likelihood ratio) applied to evaluate the proposed system. Via MATLAB simulations, it is shown that the proposed technique is secure, reliable and efficient to be implemented in secure speech communication, as well as also being characterized by high clarity of the recovered speech signal.
Correlation of learning disabilities to porn addiction based on EEG
Authors: Kamaruddin Norhaslinda , Razi Nurul Izzati Mat , Wahab Abdul
Published: October 2020

Researchers were able to correlate porn addiction based on electroencephalogram (EEG) signal analysis to the psychological instruments’ findings. In this paper we attempt to correlate the porn addiction to various cases of learning disorders through analyzing EEG signals. Since porn addiction involved the brainwave power at the frontal of the brain, which reflects the executive functions, this may have correlation to learning disorder. Only three types of learning disorder will be of interest in our study involving dyslexic, attention deficit and hyperactivity disorder (ADHD) and autistic children because they involved reduced intellectual ability observed from the lack of listening, speaking, reading, writing, reasoning, or mathematical proficiencies. Children with such disorder when expose to the internet unfiltered porn contents may have minimal understanding of the negative effects of the contents. Such unmonitored exposure to pornographic contents may result to porn addiction because it may trigger excitement and induced pleasure. Experimental results show strong correlation of learning disorders to porn addiction, which can be worthwhile for further analysis. In addition, this paper also indicates that analyzing brainwave patterns could provide a better insight into predicting and detecting children with learning disorders and addiction with direct analysis of the brain wave patterns.
Deblurring of noisy iris images in iris recognition
Authors: Jamaludin Shahrizan , Zainal Nasharuddin , W Zaki W Mimi Diyana
Published: October 2020

Iris recognition used the iris features to verify and identify the identity of human. The iris has many advantages such as stability over time, easy to use and high recognition accuracy. However, the poor quality of iris images can degrade the recognition accuracy of iris recognition system. The recognition accuracy of this system is depended on the iris pattern quality captured during the iris acquisition. The iris pattern quality can degrade due to the blurry image. Blurry image happened due to the movement during image acquisition and poor camera resolution. Due to that, a deblurring method based on the Wiener filter was proposed to improve the quality of iris pattern. This work is significant since the proposed method can enhance the quality of iris pattern in the blurry image. Based to the results, the proposed method improved the quality of iris pattern in the blurry image. Moreover, it recorded the fastest execution time to improve the quality of iris pattern compared to the other methods.
Analyzing sentiment system to specify polarity by lexicon-based
Authors: Abd Dhafar Hamed , Abbas Ayad R. , Sadiq Ahmed T.
Published: October 2020

Currently, sentiment analysis into positive or negative getting more attention from the researchers. With the rapid development of the internet and social media have made people express their views and opinion publicly. Analyzing the sentiment in people views and opinion impact many fields such as services and productions that companies offer. Movie reviewer needs many processing to be prepared to detect emotion, classify them and achieve high accuracy. The difficulties arise due of the structure and grammar of the language and manage the dictionary. We present a system that assigns scores indicating positive or negative opinion to each distinct entity in the text corpus. Propose an innovative formula to compute the polarity score for each word occurring in the text and find it in positive dictionary or negative dictionary we have to remove it from text. After classification, the words are stored in a list that will be used to calculate the accuracy. The results reveal that the system achieved the best results in accuracy of 76.585%.
Data-based PID control of flexible joint robot using adaptive safe experimentation dynamics algorithm
Authors: Ahmad Mohd Ashraf , Ishak Haszuraidah , Nasir Ahmad Nor Kasruddin , Ghani Normaniha Abd
Published: October 2020

This paper proposes the data-based PID controller of flexible joint robot based on adaptive safe experimentation dynamics (ASED) algorithm. The ASED algorithm is an enhanced version of SED algorithm where the updated tuning variable is modified to adapt to the change of the objective function. By adopting the adaptive term to the updated equation of SED, it is expected that the convergence accuracy can be further improved. The effectiveness of the ASED algorithm is verified to tune the PID controller of flexible joint robot. In this flexible joint control problem, two PID controllers are utilized to control both rotary angle tracking and vibration of flexible joint robot. The performance of the proposed data-based PID controller is assessed in terms of trajectory tracking of angular motion, vibration reduction and statistical analysis of the pre-defined control objective function. The simulation results showed that the data-based PID controller based on ASED is able to produce better control accuracy than the conventional SED based method.
Physical activity prediction using fitness data: Challenges and issues
Authors: Zakariya Nur Zarna Elya , Rosli Marshima Mohd
Published: October 2020

In the new healthcare transformations, individuals are encourage to maintain healthy life based on their food diet and physical activity routine to avoid risk of serious disease. One of the recent healthcare technologies to support self health monitoring is wearable device that allow individual play active role on their own healthcare. However, there is still questions in terms of the accuracy of wearable data for recommending physical activity due to enormous fitness data generated by wearable devices. In this study, we conducted a literature review on machine learning techniques to predict suitable physical activities based on personal context and fitness data. We categorize and structure the research evidence that has been publish in the area of machine learning techniques for predicting physical activities using fitness data. We found 10 different models in Behavior Change Technique (BCT) and we selected two suitable models which are Fogg Behavior Model (FBM) and Trans-theoretical Behavior Model (TTM) for predicting physical activity using fitness data. We proposed a conceptual framework which consists of personal fitness data, combination of TTM and FBM to predict the suitable physical activity based on personal context. This study will provide new insights in software development of healthcare technologies to support personalization of individuals in managing their own health.
Classification of texture using random box counting and binarization methods
Authors: AL-kubaisy Wijdan Jaber , Mahmood Maha
Published: October 2020

The heterogeneous texture classifications with the complexity of structures provide variety of possibilities in image processing, as an example of the multifractal analysis features. The task of texture analysis is a highly significant field of study in the field of machine vision. Most of the real-life surfaces exhibit textures and an efficiently modelled vision system must have the ability to deal with this variety of surfaces. A considerable number of surfaces maintain a self-similarity quality as well as statistical roughness at different scales. Fractals could provide a great deal of advantages; also, they are popular in the process of modelling these properties in the tasks related to the field of image processing. With two distinct methods, this paper presents classification of texture using random box counting and binarization methods calculate the estimation measures of the fractal dimension BCM. There methods are the banalization and random selecting boxes. The classification of the white blood cells is presented in this paper based on the texture if it is normal or abnormal with the use of a number of various methods.
Robot control and kinematic analysis with 6DoF manipulator using direct kinematic method
Authors: Gaeid Khalaf S , Nashee Asaad F , Ahmed Ibrahim A. , Dekheel Mohammed H.
Published: October 2020

The robots pay important role in all parts of our life. Hence, the modeling of the robot is essential to develop the performance specification. Robot model of six degree of freedom (6DoF) manipulator implemented numerically using model-based technique. The kinematic analysis and simulation were studied with Inverse kinematics of the robot manipulator through Denevit and Hartenberg method. Matrix transformation method is used in this work in order to separate joint variables from kinematic equations. The finding of the desired configuration is obtained precisely in all motion trajectory along the end-effector path. MATLAB/SIMULINK with R2018b is used for the implementation of the model-based robot system. Simulation results showed that the robot rinks follow their references smoothly and precisely and ensure the effectiveness of direct kinematic algorithm in the analysis and control of the robotic field.
Statistical survey and comprehensive review on human skin detection
Authors: Al Naffakh Hussein Ali Hussein , Ghazali Rozaida , El Abbadi Nidhal Khdhair
Published: October 2020

With the advancement of data society today, pictures have turned out to be increasingly imperative. Automatic detection of human skin has been an area of active research for the past few years. Human skin detection assumes a vital job in a wide scope of picture preparing applications going from face detection, steganography, face tracking, age detection, discover pornographic images, the discovery of skin diseases gesture analysis and substance based picture recovery frameworks and to different human PC association spaces. Detecting human skin in complex pictures have ended up being a difficult issue since skin shading can fluctuate drastically in its appearance because of numerous variables, for example, illumination, race, maturing, imaging conditions, and complex foundation. In this study, we will study and analyze skin researches, where we will treat the weakness of previous research of survey on human skin detection methods. The reason for this investigation is to give a state-of-the-art study on human skin molding and detection methods in 1998-2019 periods. Furthermore, this research presented the statistical study for each issue stated before. We finish up with a few ramifications for a future course. Study results will benefit all researchers who are interested in human skin detection topic.
“Scrumbear” framework for solving traditional scrum model problems
Authors: Alsaber Leanah , Elsheikh Ebtesam Al , Aljumah Sarah , Jamail Nor Shahida Mohd
Published: October 2020

Software engineering is a discipline that is little understood by people. It defines how software is developed and maintained to meet the clients’ requirements. Software engineers follow certain systems and standards in their work to meet the clients’ desires. It is on this background that engineers follow specific models in coming up with the final product. One of the models highly used is scrum, which is one of the agile methodologies. However, despite being highly used, it has inherent flaws that need to be corrected. Those flaws are product owner continues changing; do not accept changes in working scrum, sprint’s release time limitation, finally wasting team time within each sprint. This paper presents a new framework, which is an updated version of the current Scrum, to overcome the scum models mentioned issues. In this study, a new framework is presented in a way that is understandable and needed by software developer’s team upon the collected qualitative and quantitative data. The implementation was by making some changes to the current scrum model leading to the “Scrumbear”, certain flaws can be corrected. One of the presented changes involve adding the control master rule to ensure controlling the requirements changing.
Analyzing bit error rate of relay sensors selection in wireless cooperative communication systems
Authors: Alawady Ahmed Allawy , Alkhayyat Ahmed , Jubair Mohammed Ahmed , Hassan Mustafa Hamid , Mostafa Salama A.
Published: October 2020

Cooperative communication systems, which make use of the intermediate relays between the transmitter and the receiver, have been employed as an effective technique to combat the channel fading and to enhance system performance. Cooperative systems have some drawbacks such as high latency and may diversity order not guaranteed. To alleviate the negative effects of these factors, the relay selection protocol is employed in cooperative communication systems to increase overall cooperative system performance. Relay selection in the cooperative systems enables the source to cooperate with the single relay node rather than multiple relay nodes which guaranteed the diversity order.
Research trends review on RSA scheme of asymmetric cryptography techniques
Authors: Mohamad Mohd Saiful Adli , Din Roshidi , Ahmad Jasmin Ilyani
Published: October 2020

One of the cryptography classifications is asymmetric cryptography, which uses two different keys to encrypt and decrypt the message. This paper discusses a review of RSA scheme of asymmetric cryptography techniques. It is trying to present the domains of RSA scheme used including in public network, wireless sensor network, image encryption, cloud computing, proxy signature, Internet of Things and embedded device, based on the perspective of researchers’ effort in the last decade. Other than that, this paper reviewed the trends and the performance metrics of RSA scheme such as security, speed, efficiency, computational complexity and space based on the number of researches done. Finally, the technique and strengths of the proposed scheme are also stated in this paper.
An optimal placement of phasor measurement unit using new sensitivity indices
Authors: Khalid K. , Ibrahim A. A. , Kamari N. A. M. , Zaman M. H. M.
Published: October 2020

This paper presents an alternative approach to solve an optimal phasor measurement unit (PMU) placement by introducing two new sensitivity indices. The indices are constructed from the information measured from PMUs such as voltage magnitude and angle. These two parameters are essential for power system stability assessment and control. Therefore, fault analysis is carried out to obtain the voltage magnitude and angle deviations at all buses in order to construct the indices. An exhaustive search method is used to solve the linear integer programming problem where all possible combinations of PMU placement are evaluated to obtain the optimal solution. Unfortunately, the traditional objective function to minimize the total number of PMU placement leads to multiple solutions. The indices can be used to assess multiple solutions of PMU placement from the exhaustive method. In this work, an optimal solution is selected based on the performance of PMU placement in according to the indices. The proposed method is tested on the IEEE 14 bus test system. Only four PMUs are required to monitor the whole test system. However, the number of PMUs can be reduced to three PMUs after applying zero injection bus elimination.
Visualizing stemming techniques on online news articles text analytics
Authors: Razmi Nurul Atiqah , Zamri Muhammad Zharif , Ghazalli Sharifah Syafiera Syed , Seman Noraini
Published: October 2020

Stemming is the process to convert words into their root words by the stemming algorithm. It is one of the main processes in text analytics where the text data needs to go through stemming process before proceeding to further analysis. Text analytics is a very common practice nowadays that is practiced toanalyze contents of text data from various sources such as the mass media and media social. In this study, two different stemming techniques; Porter and Lancaster are evaluated. The differences in the outputs that are resulted from the different stemming techniques are discussed based on the stemming error and the resulted visualization. The finding from this study shows that Porter stemming performs better than Lancaster stemming, by 43%, based on the stemming error produced. Visualization can still be accommodated by the stemmed text data but some understanding of the background on the text data is needed by the tool users to ensure that correct interpretation can be made on the visualization outputs.
Mobile ad-hoc network routing protocols of time-critical events for search and rescue missions
Authors: Hassan Marwan Hamid , Mostafa Salama A. , Mahdin Hairulnizam , Mustapha Aida , Ramli Azizul Azhar , Hassan Mustafa Hamid , Jubair Mohammed Ahmed
Published: October 2020

The most important experiences we discovered from several disasters are that cellular networks were vulnerable, and the loss of the communication system may have a catastrophic consequence. Mobile ad-hoc networks (MANETs) play a significant role in the construction of campus, resident, battlefield and search/rescue region. MANET is an appropriate network for supporting a communication where is no permanent infrastructure. MANET is an effective network that uses to establishing urgent communication between rescue members in critical situations like, disaster or natural calamities. The sending and receiving data in MANET is depending on the routing protocols to adapt the dynamic topology and maintain the routing information. Consequently, This paper evaluates the performance of three routing protocols in MANET: ad-hoc on-demand distance vector (AODV), destination sequenced distance vector (DSDV), and ad-hoc on-demand multipath distance vector (AOMDV). These protocols are inherent from different types of routing protocols: single-path, multi-path, reactive and proactive mechanisms. The NS2 simulator is utilized to evaluate the quality of these protocols. Several metrics are used to assess the performance of these protocols such: packet delivery ratio (PDR), packet loss ratios (PLR), throughput (TP), and end-to-end delay (E2E delay). The outcomes reveal the AOMDV is the most suitable protocol for time-critical events of search and rescue missions.
Cyclic voltammetry readout circuitry for DNA biosensor application
Authors: Hamzah I. H. , Malik A. A. , Rahim A. F. A. , Soh Z. H. C.
Published: October 2020

Cyclic voltammetry electrochemical biosensors reported a wide usage and applications for its fast response, able to be miniaturized and its sensitivity. However, the bulky, expensive and laboratory-based readout circuitry made it impossible to be used in the field-based environment. A miniaturized and portable readout circuitry for the DNA detection using hybridization technique had been design and developed in this work. It embedded with fabricated FR4 based sensor and produced respective current when the applied voltage was within the range of 0 to 0.5 V. The readout circuitry had been verified with five analysis environments. Bare Au with distilled water (dH2O), bare Au with ferricyanide reagent solution, DNA immobilization, DNA non-hybridization and DNA hybridization. All the results performed produced peak cathodic current when the applied input voltage is within 0.5 V to 3 V and hence proved that the miniaturized and portable readout circuitry is suitable to be implemented for cyclic voltammetry electrochemical biosensor.
Review on feature-based method performance in text steganography
Authors: Muhammad Mohd Hilal , Hussain Hanizan Shaker , Din Roshidi , Samad Hafiza , Utama Sunariya
Published: October 2020

The implementation of steganography in text domain is one the crutial issue that can hide an essential message to avoid the intruder. It is caused every personal information mostly in medium of text, and the steganography itself is expectedly as the solution to protect the information that is able to hide the hidden message that is unrecognized by human or machine vision. This paper concerns about one of the categories in steganography on medium of text called text steganography that specifically focus on feature-based method. This paper reviews some of previous research effort in last decade to discover the performance of technique in the development the feature-based on text steganography method. Then, ths paper also concern to discover some related performance that influences the technique and several issues in the development the feature-based on text steganography method.
Wireless sensor network calibration technique for low-altitude unmanned aerial vehicle localization in paddy field
Authors: Jaafar Azhar , Thamrin Norashikin M. , Zan Noorolpadzilah Mohamed
Published: October 2020

This paper presents the use of the received signal strength indicator (RSSI) from the RF signal to estimate the distance from a point where the signal is transmitted to the point where the signal is received. This can be a challenge as in the paddy field, the watery and dry conditions, as well as the height of the paddy plant can affect signal transmission during this estimation process. Two low-cost ground beacons, Beacon1 and Beacon2 (The coordinator), are used and placed in a known location with a fixed distance across the paddy field, which becomes the reference point during the distance estimation for the unmanned aerial vehicle (UAV). These signals are analyzed by using the non-right-angle trigonometry computation, to estimate the distance between the transmitter and the receiver. The estimated distance is compared with the measured value to determine the efficiency of this approach. The calibration trendlines of these beacons in the open, watery and dry paddy fields are discussed and presented. It is found that the dry paddy field gives less RSSI mean error and proved that humidity can contribute to the distance estimation error.
Integration of LED-based lighting in academic buildings for energy efficiency considerations
Authors: Hussin Mohamad Zhafran , Shukor Saiful Firdaus Abdul , Sin Nor Diyana Md , Yusof Yusrina , Nor Muhammad Zairil Muhammad , Rahman Noor Hasliza Abdul
Published: October 2020

This paper presents an assessment by integration of LED T8 tube lamps in academic buildings for energy efficiency considerations. The proposed project was implemented in conjunction with a national mission, national energy efficiency action plan (NEEAP) for 10-year implementation period of 2016-2025 in reducing allocation on subsidies for efficient expenditure towards energy-saving measures. A case of study in a real environment at one of the UiTM’s buildings as a target task area has been tested by replacing a LED lighting technology in consideration of current operating costs and power factor performances. From the results, LED T8 tubes have shown a better power factor of 0.89 compared to fluorescent lamps with about 0.61 and primarily driven by economic benefits in terms of cost savings of up to 50% with return-on-investment (ROI) 6 months after installation. By integrating this technology, nearly 50% of the total energy consumption in indoor lighting system could be significantly saved, thus reducing the total cost of electricity bills in the future within the target area.
Analyzing the impact of the number of nodes on the performance of the routing protocols in manet environment
Authors: Haglan Hussein M. , Mostafa Salama A. , Safar Noor Zuraidin Mohd , Mustapha Aida , Saringatb Mohd. Zainuri , Alhakami Hosam , Alhakami Wajdi
Published: October 2020

Mobile Ad-hoc Networks (MANETs) are independent systems that can work without the requirement for unified controls, pre-setup to the paths/routes or advance communication structures. The nodes/hubs of a MANET are independently controlled, which permit them to behave unreservedly in a randomized way inside the MANET. The hubs can leave their MANET and join different MANETs whenever the need arises. These attributes, in any case, may contrarily influence the performance of the routing conventions (or protocols) and the general topology of the systems. Along these lines, MANETs include uniquely planned routing conventions that responsively as well as proactively carry out the routing. This paper assesses and looks at the effectiveness (or performance) of five directing conventions which are AOMDV, DSDV, AODV, DSR and OLSR in a MANET domain. The research incorporates executing a simulating environment to look at the operation of the routing conventions dependent on the variable number of hubs. Three evaluation indices are utilized: Throughput (TH), Packet Delivery Ratio (PDR), and End-to-End delay (E2E). The assessment outcomes indicate that the AODV beats other conventions in the majority of the simulated scenarios.
An enhanced fireworks algorithm to generate prime key for multiple users in fingerprinting domain
Authors: Ismael Hussein Ali , Abbas Jamal Mustafa , Mostafa Salama A. , Fadel Ali Hussein
Published: October 2020

This work presents a new method to enhance the performance of fireworks algorithm to generate a prime key for multiple users. A threshold technique in image segmentation is used as one of the major steps. It is used processing the digital image. Some useful algorithms and methods for dividing and sharing an image, including measuring, recognizing, and recognizing, are common. In this research, we proposed a hybrid technique of fireworks and camel herd algorithms (HFCA), where Fireworks are based on 3-dimension (3D) logistic chaotic maps. Both, the Otsu method and the convolution technique are used in the pre-processing image for further analysis. The Otsu is employed to segment the image and find the threshold for each image, and convolution is used to extract the features of the used images. The sample of the images consists of two images of fingerprints taken from the Biometric System Lab (University of Bologna). The performance of the anticipated method is evaluated by using FVC2004 dataset. The results of the work enhanced algorithm, so quick response code (QRcode) is used to generate a stream key by using random text or number, which is a class of symmetric-key algorithm that operates on individual bits or bytes.
Effect of the defected microstrip structure shapes on the performance of dual-band bandpass filter for wireless communications
Authors: Mabrok Mussa , Zakaria Zahriladha , Masrukin Yully Erwanti , Sutikno Tole , Alsariera Hussein
Published: October 2020

Due to the progression growth of multiservice wireless communication systems in a single device, multiband bandpass filter has attract a great attention to the end user. Therefore, multiband bandpass filter is a crucial component in the multiband transceivers systems which can support multiple services in one device. This paper presents a design of dual-band bandpass filter at 2.4 GHz and 3.5 GHz for WLAN and WiMAX applications. Firstly, the wideband bandpass filter is designed at a center frequency of 3 GHz based on quarter-wavelength short circuited stub. Three types of defected microstrip structure (DMS) are implemented to produce a wide notch band, which are T-inversed shape, C-shape, and U- Shape. Based on the performance comparisons, U-shaped DMS is selected to be integrated with the bandpass filter. The designed filter achieved two passbands centered at 2.51 GHz and 3.59 GHz with 3 dB bandwidth of 15.94 % and 15.86 %. The proposed design is very useful for wireless communication systems and its applications such as WLAN and WiMAX
Behavioral studies of surge protection components
Authors: Kuan Teik Hua , Chew Kuew Wai , Chua Kein Huat
Published: October 2020

In our daily life, almost all the items we used, being a computer, television, lift or vehicle we drive consist of some kind of electrical or electronics component inside. The operation of these devices could be severely affected by lightning activity or electrical switching events, as there are more than 2000 thunderstorms in progress at any time resulting in 100 lightning flashes to ground per second. In practice, any device using electricity will subject to surge damages induced from the lightning or switching of heavy load. Surge protection device (SPD) is added at the power distribution panel and critical process loop to prevent damage subsequently cause plant shutdown. There are many questions raised on the SPD. How can this small device protect the equipment from large energy release by the lightning? What is inside the device? How does it work? This paper provides comprehensive detail in revealing the science and engineering behind the SPD, its individual component characteristic and how does it work. The technical information presented is limited to surge protection on equipment; surge protection for building structure will not be discussed here.
Signature PSO: A novel inertia weight adjustment using fuzzy signature for LQR tuning
Authors: Komarudin Achmad , Setyawan Novendra , Kamajaya Leonardo , Achmadiah Mas Nurul , Zulfatman Zulfatman
Published: October 2020

Particle swarm optimization (PSO) is an optimization algorithm that is simple and reliable to complete optimization. The balance between exploration and exploitation of PSO searching characteristics is maintained by inertia weight. Since this parameter has been introduced, there have been several different strategies to determine the inertia weight during a train of the run. This paper describes the method of adjusting the inertia weights using fuzzy signatures called signature PSO. Some parameters were used as a fuzzy signature variable to represent the particle situation in a run. The implementation to solve the tuning problem of linear quadratic regulator (LQR) control parameters is also presented in this paper. Another weight adjustment strategy is also used as a comparison in performance evaluation using an integral time absolute error (ITAE). Experimental results show that signature PSO was able to give a good approximation to the optimum control parameters of LQR in this case.
Implementation of vehicle ventilation system using NodeMCU ESP8266 for remote monitoring
Authors: Jalil Amirun Murtaza Abd , Mohamad Roslina , Anas Nuzli Mohamad , Kassim Murizah , Suliman Saiful Izwan
Published: October 2020

In this paper, an implementation of vehicle ventilation system using microcontroller NodeMCU is described, as an internet of things (IoT) platform. A low-cost wireless fidelity (Wi-Fi) microchip ESP8266 integrated with NodeMCU provides full-stack transmission control protocol/internet protocol (TCP/IP) to communicate between mobile applications. This chip is capable to monitor and control sensor devices connected to the IoT platform. In this reserach, data was collected from a temperature sensor integrated to the platform, which then monitored using Blynk application. The vehicle ventilation system was activated/deactivated through mobile application and controlled using ON/OFF commands sent to the connected devices. From the results, the vehicle ventilation system built using NodeMCU microcontroller is capable to provide near real-time data monitoring for temperature in the car before and after the ventilation system was applied.