bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of mobile robot for measuring distance using optical quadrature encoder
Authors: Zahari Madiha , Mutalib NurliyanaAbd , Natasya Affendi Nurnadia , Hashim N. , Hadi D. A. , Halma Johari Siti , Ab Wahab N. , Ahmad Suziana
Published: February 2020

This paper describes the design and development of a measuring tool using a mobile robot. At present, contractors are measuring distances using measuring tape which has few limitations. This includes using of another manpower or a marking flag. The Robot Measuring System is designed to measure distances at multiple conditions such as smooth and rough surface. An optical quadrature encoder is used as a sensor to measure the distances while a program is installed in Arduino Uno for reading and data collection. Graphical User Interface (GUI) was created using Android software so that the movement of the robot can be controlled using a smartphone within a Bluetooth range. An experiment was conducted to test the reliability in terms of accuracy and precision. The best accuracy and precision were obtained when the robot speed is at 90 cm/s on the plain tiles, 80 cm/s on the tar road and 90 cm/s on the grass surface. The robot speed needs to be adjusted accordingly based on the surfaces in order to get an accurate result.
 This paper proved that the robot measuring system was successfully designed, implemented and analyzed.
Eulerian video magnification: a review
Authors: Shahadi Haider Ismael , Albattat Hayder J. , Al-allaq Zaid Jabbar , Thahab Ahmed Toman
Published: February 2020

Many important subtle changes in the environment are invisible to the naked human eyes. These subtle changes occur because of colour variations, such as blood flow in a human face that leads to face colour change, or motion variations, such as vena movement under human skin and vibration of buildings. The human eye requires optical microscopes to detect these variations. Alternatively, new technologies, such as high-speed imagery and computer processing, can be used to detect these variations. These computerised microscopes depend on computation rather than optical amplification to amplify subtle colour and motion changes in videos. The most popular technique to achieve computation-based microscope is the Eulerian video magnification (EVM). However, several challenges in EVM still need to be solved to meet the requirements of real time and video quality. This paper presents a comprehensive study of EVM methods and reviews the related literature. The strengths and drawbacks of existing works are discussed, and the important research fields and challenges in the area of EVM are concluded.
The investigation on defect recognition system using gaussian smoothing and template matching approach
Authors: H. Harun M. , F. Yaakub M. , Z. Abidin A. F. , H. Azahar A. , M. Aras M. S. , N. Shah M. B. , M. Basar M. F.
Published: February 2020

This paper investigates various approaches for automated inspection of gluing process using shape-based matching application. A new supervised defect detection approach to detect a class of defects in gluing application is proposed. Creating of region of interest in important region of object is discussed. Gaussian smoothing features is proposed in determining better image processing. Template matching in differentiates between reference and tested image are proposed. This scheme provides high computational savings and results in high defect detection recognition rate. The defects are broadly classified into three classes: 1) gap defect; 2) bumper defect; 3) bubble defect. This system does lessen execution time, yet additionally produce high precision in deformity location rate. It is discovered that the proposed framework can give precision at 95.77% recognition rate in recognizing imperfection for gluing application.
An ensemble technique for speech recognition in noisy environments
Authors: Habeeb Imad Qasim , Fadhil Tamara Z. , Jurn Yaseen Naser , Habeeb Zeyad Qasim , Abdulkhudhur Hanan Najm
Published: February 2020

Automatic speech recognition (ASR) is a technology that allows a computer and mobile device to recognize and translate spoken language into text. ASR systems often produce poor accuracy for the noisy speech signal. Therefore, this research proposed an ensemble technique that does not rely on a single filter for perfect noise reduction but incorporates information from multiple noise reduction filters to improve the final ASR accuracy. The main factor of this technique is the generation of K-copies of the speech signal using three noise reduction filters. The speech features of these copies differ slightly in order to extract different texts from them when processed by the ASR system. Thus, the best among these texts can be elected as final ASR output. The ensemble technique was compared with three related current noise reduction techniques in terms of CER and WER. The test results were encouraging and showed a relatively decreased by 16.61% and 11.54% on CER and WER compared with the best current technique. ASR field will benefit from the contribution of this research to increase the recognition accuracy of a human speech in the presence of background noise.
Influence of device to device interconnection elements on the system behavior and stability
Authors: Sadegh Amiri Iraj , Zaki Rashed Ahmed Nabih , Yupapin Preecha
Published: February 2020

This work has presented the interaction between tangential/sagittal cylindrical thin lens in the titled plane parallel crystal. Stability criterion parameters are measured under the control of curvature radius of a spherical mirror, the thickness of the tilted plane crystal, the refractive index of tilted plane crystal, the thickness for a plate of matter and phase angle of the sagittal cylindrical thin lens. Beam radius waist is plotted against the focal length of the tangential cylindrical thin lens. Focal length for both thin lens in resonator crystal is optimized to upgrade the resonator system operation efficiency.
A new patch antenna for ultra wide band communication applications
Authors: Sabah Anwar , Frhan Malik Jasim
Published: February 2020

A printed monopole patch Ultra Wide Band (UWB) antenna for use in UWB application is proposed in this paper. The proposed antenna consists of a patch with appropriate dimensions on one side of a dielectric substrate, and a partial ground plane on the other side of the substrate. The techniques that used to enhance the bandwidth are the partial ground plane, feed point position and adjusted feed gap. The substrate that is used in the proposed antenna is Fr4 epoxy, the optimum dimensions of the antenna are 40mm×28mm×1.5mm this antenna designed by HFSS program. The band achieved by the proposed antenna is from 3.6GHz to 15GHz. This antenna is fabricated in the ministry of science and technology Baghdad-Iraq and a good agreement between simulation and measured S11 is achieved. 
Resource allocation algorithm for symmetrical services in OFDMA systems
Authors: P S Swapna , S Pillai Sakuntala , K. G Sreeni
Published: February 2020

The widespread acceptance of symmetrical services has urged for performance betterment techniques in wireless communication systems. In this paper, we propose an algorithm for resource allocation in MIMO-OFDMA system for applications that demand similar quality in uplink and downlink direction. The problem is formulated as multiobjective optimization problem with objectives to maximize the bidirectional data rates for individual users and to minimize the difference between the uplink and downlink data rate for each user. Fairness has been considered as a constraint in the optimization problem. The power allocation for each subcarrier in the OFDMA system is carried out using Linear Programming (LP) techniques, while the subcarrier allocation problem has been undertaken using an innovative multiobjective optimization technique that employs the concept of non-dominance in evolutionary algorithms. The results are extremely encouraging as they outperform the algorithms reported in literature using linear programming techniques or evolutionary algorithms solely. 
Analysis of substrateintegrated frequency selective surface antenna for IoT applications
Authors: Immadi Govardhani , Narayana M. Venkata , Navya A. , Varma C. Anudeep , Reddy A. Abhishek , Deepika A. Manisai , Kavya K.
Published: February 2020

Antennas are long used for communication of data since a century and their usage has been diversified over the past two decades and the antennas also entered the domain of medical fields. A rectangular microstrip patch antenna has been designed on a substrate integrated waveguide with frequency selective surface which is in the shape of a square. The design of this antenna with SIW are done by using CST on a low cost FR4 substrate where єr =4.4, h=1.58 mm and tan δ=0.0035. The SIW structure merit is utilized on the traditional FSS is simulated and verified by using CST.
Analysis of 4G mobile network coverage in UTeM technology campus
Authors: Manap Zahariah , Mohd Zain Anis Suhaila , Mohd Said Rahaini , Shivaneson Balakirisnan Shawn
Published: February 2020

This paper proposes an analysis of the coverage performance of 4G cellular services in UTeM Technology Campus. The performance of the cellular services is presented as the network’s coverage profile which is based on the received signal strength indicator (RSSI). The area under study is virtually divided into 64 grid points where the average RSSI measurements are captured by using an open source software namely G-Mon. The measured values are mapped into the network coverage profile which represents the signal reception quality at each of the grid points. A statistical analysis called Two-Way ANOVA is performed to investigate the correlation of the performance of 4G cellular services in UTeM Technology Campus with the mobile phone brands and service operators. Based on the analysis, it is found that the signal reception in outdoor areas are better than that of indoor areas. In addition, the analysis shows that the propagation loss and signal degradation are two factors that contribute to the 4G services’ performance in UTeM Technology Campus. 
Dental lasers applications in visible wavelength operational band
Authors: M. A. Eid Mahmoud , Sadegh Amiri Iraj , Zaki Rashed Ahmed Nabih , Yupapin Preecha
Published: February 2020

There is no doubt that radiation has many side effects in our lives, so our goal in this study is to reduce our use of radiation in the diagnosis of tooth caries, and in order to achieve this goal we used the field of optical fiber in the detection of some diseases associated with oral and dental medicine. This diagnosis was accomplished by shedding light on the teeth, to be diagnosed and creating an image that allows the doctor to examine them and determine whether there are caries or any root problems. The principle is also used to detect oral cancer, fractures, and cracks in bones. This study also allows us to detect early caries, and this method saves time because it gives the diagnosis at the same time while the patient is in the treatment unit of the dental clinic. Thus the main advantages of this method are, enable the dentist to view images on the display unit attached to the clinic in real-time, compare current photos with old photos of the same patient. Also, the dentist can create a photo archive of each tooth individually and can retrieve and compare them whenever he wants.    
Solving multi-objective master production schedule problem using memetic algorithm
Authors: Sadiq Shireen S. , Abdulazeez Adnan Mohsin , Haron Habibollah
Published: February 2020

A master production schedule (MPS) need find a good, perhaps optimal, plan for maximize service levels while minimizing inventory and resource usage. However, these are conflicting objectives and a tradeoff to reach acceptable values must be made. Therefore, several techniques have been proposed to perform optimization on production planning problems based on, for instance, linear and non-linear programming, dynamic-lot sizing and meta-heuristics. In particular, several meta- heuristics have been successfully used to solve MPS problems such as genetic algorithms (GA) and simulated annealing (SA). This paper proposes a memetic algorithm to solve multi-objective master production schedule (MOMPS). The proposed memetic algorithm combines the evolutionary operations of MA (such as mutation and Crossover) with local search operators (swap operator and inverse movement operator) to improve the solutions of MA and increase the diversity of the population). This algorithm has proved its efficiency in solving MOMPS problems compared with the genetic algorithm and simulated annealing. The results clearly showed the ability of the algorithm to evaluate properly how much, when and where extra capacities (overtime) are permitted so that the inventory can be lowered without influencing the level of service. 
A framework for named entity recognition of clinical data
Authors: J Ravikumar , Kumar P Ramakanth
Published: February 2020

With emergence of technologies like big data, the healthcare services are also being explored to apply this technology and reap benefits. Big Data analytics can be implemented as a part of e-health which involves the extrapolation of actionable insights from sources like health knowledge base and health information systems. Present day medical data creates a lot of information consistently. At present, Hospital Information System is a quickly developing innovation. This data is a major asset for getting data from gathering of gigantic measures of surgical information by forcing a few questions and watchwords. Be that as it may, there is issue of getting data precisely what the client need, because Hospital Information System contains more than one archive identified with a specific thing, individual or episode and so on. Information extraction is one of information mining systems used to concentrate models portraying essential information classes. The proposed work will work for the most part concentrating on accomplishing great execution in Medical Domain. Fundamentally this had two primary purposes one was separating significant information from patient content record and second one labelling name substance, for example, individual, association, area, malady name and symptoms. Improve survival rates and tweak care conventions and review inquiries to better deal with any interminable consideration populace. Lower costs by decreasing pointless hospitalizations. Abbreviate length of stay when confirmation is fundamental.
An Algorithm to construct nondominated k-coteries
Authors: Ginanjar Rikip , Hadisukmana Nur
Published: February 2020

One of the solution in solving k mutual exclusion problem is the concept of k-coterie. A k-coterie under a set S is a set of subsets of S or quorums such that any k + 1 quorums, there are at least two quorums intersect each other. The k mutual exclusion problern is the problem of managing processes in such a way that at most k processes can enter their critical sections simultaneously. Nondominated k-coteries are more resilient to network and site failures than doninated k-coteries; that is the availability and reliability of a distributed system is better if nondominated k-coteries are used. Algorithms to construct k-coteries have been proposed, unfortunately they have some restrictions, especially in constructing nondominated k-coteries. The restrictions are due to the combination of N, the number of nodes in a distributed system, and k, the number of processes allowed to enter their critical sections simultaneously. To solve this problem, this paper proposes an algorithm to construct nondominated k-coteries for all combination of N and k.
Statistical accuracy analysis of different detecting algorithms for surveillance system in smart city
Authors: Al-Yassin Hassan , Mousa Jaafar I. , Fadhel Mohammed A. , Al-Shamma Omran , Alzubaidi Laith
Published: February 2020

Several detecting algorithms are developed for real-time surveillance systems in the smart cities. The most popular algorithms due to its accuracy are: Temporal Differencing, Background Subtraction, and Gaussian Mixture Models. Selecting of which algorithm is the best to be used, based on accuracy, is a good choise, but is not the best. Statistical accuracy anlysis tests are required for achieving a confident decision. This paper presents further analysis of the accuracy by employing four parameters: false recognition, unrecognized, true recognition, and total fragmentation ratios. The results proof that no algorithm is selected as the perfect or suitable for all applications based on the total fragmentation ratio, whereas both false recognition ratio and unrecognized ratio parameters have a significant impact. The mlti-way Analysis of Variate (so-called K-way ANONVA) is used for proofing the results based on SPSS statistics.
Diagnosing of some hepatic lesions from light microscope images based on morphological and texture features
Authors: Jabr Zamen Fadhel , Alabbas Hasan Mohammed abd
Published: February 2020

One of the common problems observed in medicines is hepatotoxicity as liver play mainly role in metabolizes the herbal medicines. Although, the acceptance of herbal medicines is growing nowadays still there is an absence of knowledge about their toxicological properties and the right use being a hepatotoxic.This paper presents method to detect and diagnoses liver lesions in four types: necrotic cells, fatty degenerative cells, hepatocellular hypertrophic cells and congested cells using image processing techniques. The method is proposed to perform two tasks the first is conclude whether the liver image is normal or abnormal the second if abnormal state is detected then diagnosis lesions type must performs. The method progresses in many steps are preprocessing, features extraction, classification and lesion diagnosing. Grey level co-occurrence Matrix (GLCM) technique is utilize to concentrate features to distinguish between normal and abnormal case using neural network classifier if abnormal state is detected the method feedback with colour image to analyse cells shape and image intensity colour to determine which type of diseases founded in image based on statistical and morphological features of cells. The method tested on 107 images it is got on the accuracy 100% in classification and 95% in diagnosing.
A modified grey wolf optimizer for improving wind plant energy production
Authors: Tumari Mohd Zaidi Mohd , Suid Mohd Helmi , Ahmad Mohd Ashraf
Published: February 2020

The main problem of existing wind plant nowadays is that the optimum controller of single turbine degrades the total energy production of wind farm when it is located in a large wind plant. This is owing to its greedy control policy that can not cope with turbulence effect between turbines. This paper proposes a Modified Grey Wolf Optimizer (M-GWO) to improvise the controller parameter of an array of turbines such that the total energy production of wind plant is increased. The modification employed to the original GWO is in terms of the updated mechanism. This modification is expected to improve the variation of exploration and exploitation rates while avoiding the premature convergence condition. The effectiveness of the M-GWO is applied to maximize energy production of a row of ten turbines. The model of the wind plant is derived based on the real Horns Rev wind plant in Denmark. The statistical performance analysis shows that the M-GWO provides the highest total energy production as compared to the standard GWO, Particle Swarm Optimization (PSO) and Safe Experimentation Dynamics (SED) methods.
Fault classification in smart distribution network using support vector machine
Authors: Chuan Ong Wei , Ab Aziz Nur Fadilah , Yasin Zuhaila Mat , Salim Nur Ashida , Wahab Norfishah A.
Published: February 2020

Machine learning application have been widely used in various sector as part of reducing work load and creating an automated decision making tool. This has gain the interest of power industries and utilities to apply machine learning as part of the operation. Fault identification and classification based machine learning application in power industries have gain significant accreditation due to its great capability and performance. In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. Eleven different types of faults are generated with respect to actual network. A wide range of simulation condition in terms of different fault impedance value as well as fault types are considered in training and testing data. Right setting parameters are important to learning results and generalization ability of SVM. Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. Initial finding from simulation result indicates that the proposed method is quick in learning and shows good accuracy values on faults type classification in distribution system. The developed algorithm is tested on IEEE 34 bus and IEEE 123 bus test distribution system. 
Solar-powered flood early warning system with short message service (SMS) notifications
Authors: Athirah Nur Anis , Radzi N. H. , Abdullah M. N. , Jumaat S. A. , Mohamad N. Z.
Published: February 2020

Flood is one of the most common hazards in Malaysia. Flood effects can be local, or very large, affecting the neighborhood or community and entire river basins. This flood develops slowly; sometimes over a period of days while sometimes develop quickly in just few minutes. With the real time flood information, it will allow public safety organizations and other emergency managers to effectively plan their resource deployment within the limited time of alert. Hence, this project aims to design the solar powered flood alert warning system by using solar energy as the power supply. This system will send message using GSM to the residents to notify them about the flood occurred. In this project, three LEDs were used to indicate the height of the water levels which are safe, alert and danger conditions. Each of the height have different water level that indicates the level of safety for each condition. 
Electrical energy production from plant biomass: an analysis model development for Pandanus Amaryllifolius plant microbial fuel cell
Authors: Howe Cheng Teng , Boon Ching Kok , Uttraphan Chessda , Mei Heong Yee
Published: February 2020

Plant microbial fuel cell (P-MFC) is an electrochemical reactor that converts organic compounds to electrical energy through the catalytic reaction from electrochemically active bacteria (EAB). However, there is no sign of an attempt in developing the functional model in predicting the energy conversion and utilization of P-MFC. In this study, an analytic model is proposed to show the whole production process of the organic compound to electrical energy generation. Pandanus Amaryllifolius plant was used as sources of photosynthate, where biomass product from rhizodeposition, acetate was produced, and soil bacteria as the microbial culture, and air as the input to the cathode chamber. The proposed analytical model is able to predict the output of the P-MFC using the parameters from the experiment. The generated data from the model was then compared with the monitored data from the Pandanus Amaryllifolius P-MFC. The results show the electrical power output has a high similarity pattern with the bacterial growth curve model and able to achieve the coulombic efficiency of 95.32%.
Simulation and modeling of two-level DC/DC boost converter using ARX, ARMAX, and OE model structures
Authors: Amran M.A.N. , Bakar, A.A. , Jalil M.H.A. , Wahyu M.U. , Gani A.F.H.A.
Published: February 2020

This paper presents simulation and modeling of two-level DC/DC boost converter using system identification technique. The main objective is to identify the unknown mathematical model from designated converter that has 2 modes of operation. Signals from the converter were processed based on the impulse response from input and output voltages, which were in time domain data. Auto Regressive with eXogenous (ARX), Auto Regressive Moving Average with eXogenous (ARMAX), and Output-Error (OE) model structure techniques had been employed to generate a model from the converter, whose validation was based on coefficient of determination (R2) or best fits criterion. The result shows that the ARX model structure produced the best model with 94.03%, compared to ARMAX and OE with 93.70% and 92.25% respectively. In terms of stability for open-loop analysis, the ARX model structure gave the most stable system.
Development of a 3D bio-printer using CoreXY mechanism and syringe-based extrusion
Authors: Soon Chin Fhong , Ramilan Mohammad Faez , Hanafi Dirman , Wan Zakaria Wan Nurshazwani , Mohd Khialdin Safinaz , Isa Hazlita , Tee Kian Sek
Published: February 2020

3D Bio-printer is said to have potential in the applications of medical studies and tissue engineering. A 3D Bio-printer could be used to print the artificial organs for organs transplant and cell tissue culture for generating new cell tissue. It could help in future medical and biological research. This paper presents the development process, i.e. working principle of Fused Deposition Modelling (FDM), mechanical, electrical and related applied software, of a 3D Bio-printer using syringe-based extruder and Core XY mechanism. Up to date, FDM is a popular technique because it is easily implemented, precise and accurate. The printed product revealed high repeativity, where (sample mean, sample standard deviation) is (  mm. The procedure could help future customized 3D Bio-printer. 
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Cyclic voltammetry characterization analysis on the cu/flame retardant 4 fabricated biosensor
Authors: Hamzah Irni Hamiza , Malik Azman Ab , Zulhanip Aida Zulia , Soh Zainal Hisham Che , Rahim Alhan Farhanah Abd
Published: February 2020

Silicon, glass and ceramic are commonly base substrate used in DNA biosensor fabrication due to its biocompatible, expensive, hard and brittle. However due to the difficulty for drilling and dicing, these materials required expensive equipments and complex methodology of fabrication. Large gap of thermal expansion coefficient (TEC) between silicon/glass and film caused microcracks. Hence, the aim of this work is to investigate the suitability and the application of a non-biocompatible material, flame retardant 4 (FR4) as a base substrate for a label free DNA biosensor. Cyclic voltammetry (CV) reversible method has been implemented to test the fabricated Cu/Au on the FR4. It is found that the fabrication of Au has been made possible by the used of oxide-free Cu as an adhesion layer on the FR4 substrate. The area size of counter electrode (CE), working electrode (WE) and reference electrode (RE) are found to be 6.25 mm2, 0.581 mm2 and 1.04 mm2, respectively, in order to achieve the unity reversible redox relationship and to ensure the sensor’s reliability for 10 mM K3Fe(CN)6 solution in 0.1 M KCl. Thus it can be concluded that the proposed FR4-based substrate fulfilled the CV reversible process characterization.
Optimization of 16 nm DG-FinFET using L25 orthogonal array of taguchi statistical method
Authors: Roslan Ameer F. , Salehuddin F. , Zain A.S.M. , Kaharudin K.E. , Ahmad I.
Published: February 2020

The impact of the optimization using Taguchi statistical method towards the electrical properties of a 16 nm double-gate FinFET (DG-FinFET) is investigated and analyzed. The inclusion of drive current (ION), leakage current (IOFF), and threshold voltage (VTH) as part of electrical properties presented in this paper will be determined by the amendment of six process parameters that comprises the polysilicon doping dose, polysilicon doping tilt, Source/Drain doping dose, Source/Drain doping tilt, VTH doping dose, VTH doping tilt, alongside the consideration of noise factor in gate oxidation temperature and polysilicon oxidation temperature. Silvaco TCAD software is utilized in this experiment with the employment of both ATHENA and ATLAS module to perform the respective device simulation and the electrical characterization of the device. The output responses obtained from the design is then succeeded by the implementation of Taguchi statistical method to facilitate the process parameter optimization as well as its design. The effectiveness of the process parameter is opted through the factor effect percentage on Signal-to-noise ratio with considerations towards ION and IOFF. The most dominant factor procured is the polysilicon doping tilt. The ION and IOFF obtained after the optimization are 1726.88 μA/μm and 503.41 pA/μm for which has met the predictions of International Technology Roadmap for Semiconductors (ITRS) 2013. 
Fire alert system through text messages, with arduino mega technology and GSM SIM 900 module
Authors: Chamorro Atalaya Omar , Arce Santillan Dora
Published: February 2020

The purpose of this article is to develop a fire alert system, to implement under the use of Arduino Mega technology and GSM module SIM 900 (GSM: Global System for mobile communications, SIM: Minimum System), with which through The programming and interconnection between these components can be obtained by capturing data through MQ2 sensors installed in the Industrial Automation Laboratory of the National Technological University of South Lima, and then send a fire alert signal through text messages to a mobile equipment located outside the laboratory; at a distance of 1000 meters; The relevance of this research is that its optimal response, detects the application of this system to the industrial park of Villa El Salvador, which has multiple warehouses, which a newspaper is affected by fire hazards, by the amount of flammable material They owned. Developing the investigation will determine the existence of a correlation factor of 0.973, between the reception time of the alert signal, with respect to the distance in the MQ2 sensor to detect the smoke; This factor tells us to state that the correlation is significant between both variables; with a ratio percentage equal to 98.90%, which was selected by the determination factor R2. 
Prototype development of smart parking system powered by solar photovoltaic
Authors: Nasir M.Z.M. , Salimin S. , Chan B. , Jumaat S.A.
Published: February 2020

This paper proposed the prototype of smart car parking powered by photovoltaic. There is probability that cars will hit the wall or car out from the parking lot. The main objectives of this research are to determine the power rating and sizing of PV panel suitable for smart car parking system and design an ultrasonic parking sensor circuit to alert any obstacle while parking and development the prototype of smart car parking using PV. Smart car parking consists of distance sensors, LED, Arduino UNO potentiometer, resistors, and Node MCU. Where, Arduino UNO as a microcontroller was coding to receive the signal from the sensor and transmit signal to LED to display the car distance condition. To measure the distance between sensor positions to a car, HC-SR04 ultrasonic distance sensor is used. Whenever a car come near to the sensor within range specified, the red, yellow or green LED will light up and send the condition happening to the smartphone application. The application build-up can display the real situation and the PV system can supply enough electricity to the smart car parking. 
Automated monitoring and controlling pH levels for hydroponics cultivation technique
Authors: Saaid Mohammad Farid , Mohd Yassin Ahmad Ihsan , Md Tahir Nooritawati
Published: February 2020

A hydroponics plant can grow healthily with sufficient nutrient, temperature, light, humidity as well as pH level that is indeed vital in ensuring the plants will absorb maximum nutrient elements required. This paper presents automated monitoring and controlling pH levels for the hydroponic cultivation technique. In this study, automated monitoring and controlling of pH levels are developed specifically for the hydroponic cultivation technique. There are three main methods that involved in the development of the system namely hardware, programming and functionality test. Firstly, users need to set the maximum and minimum pH levels as required by the plant. Then, the pH sensor will monitor the real-time pH level of the water. A syringe pump that contains a pH up solution (alkaline) and a pH down solution (acid) will drip the solutions to neutralize the water content if the water pH level is not within the stated ranges as set by the user. Results showed that the automated monitoring and controlling pH levels were successfully developed and functionality was tested and confirmed as desired. The syringe pumps responded perfectly upon changes of the water pH value based on the validation done that showed 100% accuracy of the syringe pump responds. 
A posture monitoring system with IMU for ophthalmologist while operating the slit lamp
Authors: Sek Tee Kian , Low Eugene , Tony Wellesly , Khialdin Safinaz Binti Mohd , Pusppanathan Jaysuman Bin , Soon Chin Fhong , Sam Toong Hai
Published: February 2020

The posture monitoring system monitors the posture changes of the upper body and the spinal cord applying to ophthalmologists while operating the slit lamp. The motivation to the pursuit of this system is to relate posture changes while in a static sitting posture to the spinal deviation from the g-line. Often times, the spinal deviation from the g-line is classified as bad posture because of the shift in weight distribution on the spine causing pain and discomfort in certain areas of the spine. This paper presents the design concept, the development process and the working principle of the posture monitoring system using Inertial Measurement Unit (IMU) sensor. The raw measurement data obtained from human trials is tabulated and converted into a graphical representation in which all postures can be identified and distinguished by referring the relative wave pattern. The procedure is important in the improvement on the posture monitoring system for the human trials on the ophthalmologist in future.
Design and development of three stages maximum power tracking solar charge controller
Authors: Rahman N.H. Abdul , M. Omar A. , Mat Saat E. H. , I. Ilham N. , Z. Hussin M. , Y Yusrina
Published: February 2020

This paper presents the design of a Three Stages Maximum Power Point Tracking (MPPT) charge controller for improving the charging/discharging control of the battery. In this research, Buck Converter is used to regulate the voltage from the Photovoltaic (PV) module to the required voltage. This research is limited to Valve Regulated Lead Acid (VRLA) battery for 12V system voltage. The charge control algorithm envisages controlling the charging and discharging action in all the three stages of battery charging, bulk, absorption, and float. The idea is to control the battery charging and discharging status until meeting the battery set-point. The set-point is limited to High Voltage Disconnect (HVD), Low Voltage Disconnect (LVD) and Load Voltage Reconnect (LVR) to protect the battery from over-charging and deep-discharging. The results obtained demonstrate the good performance of the charge controller. With the application of the MPPT algorithm in the bulk stage, the time taken to get the battery to fully charged state becomes faster The regulation power from the converter to the inverter has performed well and the switching relay is managed to be controlled.
A business model canvas for crowdfunding platform: case study of crowdfunding platforms in Malaysia
Authors: Bin Nadir Muhammad Hakim , Syed Aris Syaripah Ruzaini , Janom Norjansalika , Ahmad Fauziah , Habibah Arshad Noor , Kamal Bashah Nor Shahniza
Published: February 2020

Crowdfunding allows entrepreneurs raise fund to help subsidizing their project. In other country, crowdfunding platform has become famous. In the contrary, it is yet to be trend in Malaysia. Financing using internet still irrelevant among Malaysian citizen. Without a proper guideline and strong crowdfunding platform based in Malaysia as a benchmark, it is hard to convince entrepreneurs and funders to consider crowdfunding as an option to fund a project. This research thus proposed business model canvas which can be applied by the crowdfunding platform organizations to manage their business and operation more efficiently. Case study method has been employed with two techniques of data collection: interview and document review. Two crowdfunding platforms based in Malaysia participated in the case study. The findings show that both crowdfunding platforms have fundamental business model elements that made of a solid foundation as a crowdfunding platform. These results offer insight into crowdfunding environment and how it links to another necessary part of business for it to function as a successful business. Nine building blocks fits well in the crowdfunding platform business model elements namely partner network, core competency, key resources, value proposition, customer relationship, distribution channel, customer segments, cost structure and revenue stream. Interestingly, the findings revealed another imperative element that should be part of the canvas: risk management.
Text analysis on health product reviews using r approach
Authors: Mohd Kadir Nasibah Husna , Aliman Sharifah
Published: February 2020

In the social media, product reviews contain of text, emoticon, numbers and symbols that hard to identify the text summarization. Text analytics is one of the key techniques in exploring the unstructured data. The purpose of this study is solving the unstructured data by sort and summarizes the review data through a Web-Based Text Analytics using R approach. According to the comparative table between studies in Natural Language Processing (NLP) features, it was observed that Web-Based Text Analytics using R approach can analyze the unstructured data by using the data processing package in R. It combines all the NLP features in the menu part of the text analytics process in steps and it is labeled to make it easier for users to view all the text summarization. This study uses health product review from Shaklee as the data set. The proposed approach shows the acceptable performance in terms of system features execution compared with the baseline model system.
The development of simulation logic model that dealing with uncertainty for piping construction industry
Authors: Baharum Zirawani , Mahdin HairulNizam , Rahman Fauziah Abdul
Published: February 2020

Basically, multi processes and activities involve in the piping construction (PC) projects needs to be followed before the project is handed over to the customer or client, called multi-project construction environment (MPCE). In PC, the MPCEs exist where more than one project is managed simultaneously within an organization become as a common phenomenon faced by managers that highly possible to face with uncertainty issues, lead to project completion late delivery (PCLD). Dealing with uncertainty in MPCE is a common, though managing uncertainty in PC become more complicated rather that others industry. Therefore, the objective of this paper is to develop the simulation logic model to deal with the uncertainty for PC projects that focused on environmental issues (EI). This result will be proceed for uncertainty model development in the next phase of this research. The simulation logic model development began with qualitative data collection towards the case study, to get all the activities throughout the water supply company. Then, the business model is developed with 14 activities before integrated with the uncertainty factors in EI. The integration of business model and uncertainty factors generated the simulation logic model as main contribution. Once the uncertainty model completely developed, it will provide a medium for PC that confront with MPCE to monitor the uncertainties and prepared to encounter any matters in future. Therefore, it is important to pursue in providing the PC company to all inclusive-model, and helping them in managing and tackling the uncertainty, especially for EI.
Welding station monitoring system using internet of thing (IOT)
Authors: Yusof Ernie Mazuin Mohd , Yusof Mohd Ismail , Ali Rafidah , Harjimi Izzat Hilmi , Bahrin Qasidah Kamarul
Published: February 2020

In oil and gas industry, productivity is very important as the industry involves high cost and can be considered as a large-scale industry. Therefore, time and budget should be kept minimal to avoid loss to the oil and gas company. An example of lack of productivity in the industry is there are many complaints in the oil and gas industry that welders do not perform their job on time. Therefore, this project discussed about a system that can be used to monitor these welding stations. This system is important because it can help supervisors track the welding works from afar or anywhere using internet of things (IoT). To achieve that, a system must consist of hardware and software that are capable of connecting to the internet and monitor the welding works. In this project, the hardware chosen were Arduino Uno for data processing, ESP8266 to connect the microcontroller to the internet, voltage sensor to detect the voltage of the welding machine and a website to show the data taken. Other than that, this system was able to warn the welder of overvoltage of the welding machine. Thus, the system solved the problem of welders not performing their job on time. Supervisors were also able to monitor the job of welders to ensure maximum productivity. Based on the testing done on the system, the prototype was able to work as intended. The welding station monitoring system was able to detect welding usage, measure voltage values of welding and send the data to IoT for monitoring.
Parkinson disease classification: a comparative analysis on classification techniques
Authors: Nawi Nazri Mohd , Makhtar Mokhairi , Afip Zehan Afizah , Salikon Mohd Zaki
Published: February 2020

Parkinson’s disease (PD) among Alzheimer’s and epilepsy are one of the most common neurological disorders which appreciably affect not only live of patients but also their households. According to the current trend of aging social behaviour, it is expected to see a rise of Parkinson’s disease. Even though there is no cure for PD, a proper medication at the early stage can help significantly in alleviating the symptoms. Since, the traditional method for identifying PD is rather invasive, expansive and complicated for self-use, there is a high demand for using classification method on PD detection. This paper compares the performance of Neural Network and decision tree for classifying and discriminating healthy people for people with Parkinson’s disease (PD) by distinguishing dysphonia. The simulation results demonstrate that Neural Network outperformed decision tree by giving accurate results with 87% accuracy as compared to decision tree with only 84% accuracy in determining the classification of healthy and people with Parkinson’s.
Fitting statistical distribution of extreme rainfall data for the purpose of simulation
Authors: Shaharudin S.M. , Ahmad N , Mohamed N.S. , Mahdin Hairulnizam
Published: February 2020

In this study, several types of probability distributions were used to fit the daily torrential rainfall data from 15 monitoring stations of Peninsular Malaysia from the period of 1975 to 2007. The study of fitting statistical distribution is important to find the most suitable model that could anticipate extreme events of certain natural phenomena such as flood and tsunamis. The aim of the study is to determine which distribution fits well with the daily torrential Malaysian rainfall data. Generalized Pareto, Lognormal and Gamma distributions were the distributions that had been tested to fit the daily torrential rainfall amount in Peninsular Malaysia. First, the appropriate distribution of the daily torrential rainfall was identified within the selected distributions for rainfall stations. Then, data sets were generated based on probability distributions that mimic a daily torrential rainfall data. Graphical representation and goodness of fit tests were used in finding the best fit model. The Generalized Pareto was found to be the most appropriate distribution in describing the daily torrential rainfall amounts of Peninsular Malaysia. The outputs can be beneficial for the purpose of generating several sets of simulated data matrices that mimic the same characteristics of rainfall data in order to assess the performance of the modification method compared to classical method. 
Design of dual-mode SIR bandpass filter based on shorting pin for wireless communication applications
Authors: Namiq Jenan Ayad , Jalil Mustafa A.
Published: February 2020

A new design of microstrip dual mode band-pass-filter (BPF) by using stepped impedance resonator (SIR) based on shorting pin is proposed. The designed structure use two U-shaped tri-sections SIR resonators coupled to each other and a two coupled line feeding ports each of 50 ohm impedance. Shorting pins are used to excite the upper frequency passband in the re   sponse of the filter due to current distribution perturbation at the locations of the shorting pins.  For demonstration, WLAN (5.2-5.7 GHz) and GSM (1.85-1.99 GHz) and Advanced Wireless Services (AWS) (1.71-1.755 GHz). The return losses are -32.469 dB and -26.18 dB respectively at the operating frequencies of the filter.  The results of  insertion losses of the filter is 0.37 and 0.24 dB during the operating bands and more than 25 dB which consider a good out-of- band rejection. 
Faulty sensor detection using multi-variate sensors in internet of things (IoTs)
Authors: Omar Khaldoon Ammar , Malik Ahmed Dhahir , Jamil Ansar , Gheni Hasan Muwafeq
Published: February 2020

IoT devices are lightweight and have limited computational capabilities often exposed to harsh environments, which can cause failure on the IoT devices [1, 2].  The failure on the IoT devices is also caused due to limited battery life, hardware failure or human mistakes. Sensor faults can be categorized under one type of hardware failure, such as sensor burn, reduced sensor sensitivity and malfunctioned sensors.  Any faulty on the IoT devices can cause a problem on the overall operation of the IoT system. Traditional ways in the management of IoT devices is a maintenance officer require to check each device every day  [1, 3]. Any faulty devices found needs to be fixed or replaced. This traditional method is not practical and very challenging especially in the management of a large scale deployment of IoT consist of hundreds or thousands devices. Because of this, we proposed a faulty sensor detection and identification mechanism using multivariate sensors. Two methods of decision making are introduced in detecting faulty sensors, which are logical and correlation method that implemented in smart parking system and smart agriculture system accordingly. The logical method compares state of all sensors (ultrasound, IR and hall-effect) in the smart parking system either a parking lot is occupied or available, and then determine the condition of the sensors. The drawback of this method is not able to detect faulty sensor properly for a constant fault, which the sensor reading remains the same value. The correlation method calculates the correlation between all sensors (soil moisture, soil temperature and soil water) in the smart agriculture system. This method uses a moving window technique to calculate the correlation for all sensor over time. Any incomparable and uncorrelated sensor readings means a presence of faulty sensors. Based on the experiment results, the findings shows that the proposed faulty sensor detection mechanism is working properly in detecting faulty sensor in a timely manner.