bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of mobile microwave radiation severity at al-door residential complex in Iraq
Authors: Alwan Younes S. , Zidan Mohammad Sami , Taha Mohammed Qasim
Published: April 2019

In this paper, the electromagnetic radiation of the mobile microwave signals, propagated by the mobile towers in Al-Door Residential Complex west of Iraq, is measured and evaluated. This complex contains main nodes and hub repeaters and feeders to transmit the service to the whole Salahuddin and the northern provinces. Therefore, this paper focused on this area to assess the radiation and to assess the radiation whether it is safe for humans or exceeded the dangerous level. The area has been divided on to 19 locations where there are mobile towers and the radiation is measured in these locations. The electric field intensity is unsafe and should be improved since it exceeds the level of 1.7 V/m. However, the magnetic field intensity is acceptable according to the measurements. In general, the electromagnetic radiation density is unsafe since many readings override the level of 1.3 μW/〖cm〗^2. The standards of the radiation severity are based on the recommendations of LATNEX Corp.
Data cryptography based on musical notes on a fingerboard along with a dice
Authors: Tripathy Asis Kumar , Das Tapan Kumar , C Navaneethan
Published: April 2019

The security of an online system is the foremost necessity nowadays. With huge growth of the IT power and with the invention of new technologies, the number of threats a user faces is growing exponentially. Cryptography is a combination of security engineering and mathematics. It is the best technology for securing distributed systems. Cryptography consists in processing plain information by applying a cipher and producing encoded output, unknown to a third-party who does has no idea about the key. In cryptography both encryption and decryption phase are processed by one or more keys. Encryption is extremely important for a safe and secure environment for the computers and the Internet.
Featureless EMG pattern recognition based on convolutional neural network
Authors: Jing Wei Too , Abdullah Abdul Rahim Bin , Mohd Saad Norhashimah Binti , Mohd Ali Nursabillilah Binti , Tengku Zawawi Tengku Nor Shuhada Binti
Published: April 2019

In this paper, the performance of featureless EMG pattern recognition in classifying hand and wrist movements are presented. The time-frequency distribution (TFD), spectrogram is employed to transform the raw EMG signals into time-frequency representation (TFR). The TFRs or spectrogram images are then directly fed into convolutional neural network (CNN) for classification. Two CNN models are proposed to learn the features automatically from the images without the need of manual feature extraction. The performance of CNN with different number of convolutional layers is examined. The proposed CNN models are evaluated using the EMG data from 10 intact and 11 amputee subjects through the publicly access NinaPro database. Our results show that CNN classifier offered the best mean classification accuracy of 88.04% in recognizing hand and wrist movements.
Building student’s performance decision tree classifier using boosting algorithm
Authors: Jauhari Farid , Supianto Ahmad Afif
Published: April 2019

Student’s performance is the most important value of the educational institutes for their competitiveness. In order to improve the value, they need to predict student’s performance, so they can give special treatment to the student that predicted as low performer. In this paper, we propose 3 boosting algorithms (C5.0, adaBoost.M1, and adaBoost.SAMME) to build the classifier for predicting student’s performance. This research used 1UCI student performance datasets. There are 3 scenarios of evaluation, the first scenario was employ 10-fold cross-validation to compare performance of boosting algorithms. The result of first scenario showed that adaBoost.SAMME and adaBoost.M1 outperform baseline method in binary classification. The second scenario was used to evaluate boosting algorithms under different number of training data. On the second scenario, adaBoost.M1 was outperformed another boosting algorithms and baseline method on the binary classification. As third scenario, we build models from one subject dataset and test using onother subject dataset. The third scenario results indicate that it can build prediction model using one subject to predict another subject.
Optimum partition in flight route anomaly detection
Authors: Pusadan Mohammad Yazdi , Buliali Joko Lianto , Hari Ginardi Raden Venantius
Published: April 2019

Anomaly detection of flight route can be analyzed with the availability of flight data set. Automatic Dependent Surveillance (ADS-B) is the data set used. The parameters used are timestamp, latitude, longitude, and speed. The purpose of the research is to determine the optimum area for anomaly detection through real time approach. The methods used are: a) clustering and cluster validity analysis; and b) False Identification Rate (FIR). The results archieved are four steps, i.e: a) Build segments based on waypoints; b) Partition area based on 3-Dimension features P1 and P2; c) grouping; and d) Measurement of cluster validity. The optimum partition is generated by calculating the minimum percentage of FIR. The results achieved are: i) there are five partitions, i.e: (n/2, n/3, n/4, n/5) and ii) optimal partition of each 3D, that is: for P1 was five partitions and the P2 feature was four partitions
Badminton player detection using faster region convolutional neural network
Authors: Rahmad Nur Azmina , Sufri Nur Anis Jasmin , Muzamil Nurul Hamizah , As'ari Muhammad Amir
Published: April 2019

Nowadays, coaches and sport analyst are concerning about sport performance analysis through sport video match. However, they still used conventional method which is through manual observation of the full video that is very troublesome because they might miss some meaningful information presence in the video. Several previous studies have discussed about tracking ball movements, identification of player based on jersey color and number as well as player movement detection in various type of sport such as soccer and volleyball but not in badminton. Therefore, this study focused on developing an automated system using Faster Region Convolutional Neural Network (Faster R-CNN) to track the position of the badminton player from the sport broadcast video. In preparing the dataset for training and testing, several broadcast videos were converted into image frames before labelling the region which indicate the players. After that, several different trained Faster R-CNN detectors were produced from the dataset before tested with different set of videos to evaluate the detector performance. In evaluating the performance of each detector model, the average precision was obtained from precision recall graph. As a result, this study revealed that the detector successfully detects the player when the detector is being fed with more generalized dataset.
Adaptive uplink scheduling model for WiMAX network using evolutionary computing model
Authors: S Mahesh D , H Chandramouli , Chitnis Sanjay R
Published: April 2019

the increased usage of smart phones has led to increase usage an internet based application services. These application requires different quality of service (QoS) and bandwidth requirement. WiMAX is an efficient network to provision high bandwidth connectivity and coverage to end user. To meet QoS requirement the exiting model used adaptive model selection scheme. However, these model induce bandwidth wastage as it does not considers any feedback information for scheduling. This work present an Adaptive Uplink Scheduling (AUS) by optimizing MAC layer using Multi-Objective Genetic Algorithm (MOGA). The MAC scheduler use feedback information from both physical layer and application layer. Further, to meet QoS requirement of application and utilize bandwidth efficiently this paper presented an adaptive modulation selection scheme based on user application requirement using MOGA. Our model provides application level based QoS provisioning for WiMAX network. Experiment are conducted to evaluate performance of AUS over exiting model. The overall result attained shows AUS model attain good performance in term of throughput, successful packet transmission and packet collision.
Toward semantic similarity measure between concepts in an ontology
Authors: Tongphu Suwan
Published: April 2019

A similarity measure is one classical problem in Description Logic which aims at identifying the similarity between concepts in an ontology. Finding a hierarchy distance among concepts in an ontology is one popular technique. However, one major drawback of such a technique is that it usually ignores a concept definition analysis. This work introduces a new method for similarity measure. The proposed system semantically analyzes structures of two concept descriptions and then computes the similarity score based on the number of shared features. The efficiency of the proposed algorithm is measured by means of the satisfaction of desirable properties and intensive experiments on the Snomed ct ontology.
Test-framework: performance profiling and testing web search engine on non factoid queries
Authors: A Althaf Ali , R Mahammad Shafi
Published: April 2019

Performance profiling and testing is one of the interesting topics in the big data management and Cloud Computing. In testing, we use test cases composed to different type of queries to evaluate the performance aspects of the information retrieval system for large scale information collection. This test scenarioperforms the evaluation ofretrieval accuracy for all kind of ambiguity and non factoid queries with result set as Training data. This stands difficult to evaluate the retrieval method in order to schedule or optimize the Recommendation and prediction technique of the IR method to the Real time queries. The Queries is considered as requirement specification which has to supply to search engine or web information provider applications for information or web page retrieval. In this paper, we propose a novel technique named as “Test Retrieval Framework“a performance profiling and testing of the web search engines on the information retrieved towards non factoid queries. In this technique, we apply expectation maximization algorithm as an iterative method to find maximum likelihood estimate.We discuss on the important aspects in this work based on Recommendation models integrating domain and web usage, Query optimization for navigational and Transactional queries, Query Result records.The Experimental results demonstrates the proposed technique outperforms of state of arts approaches in terms of set based measures like Precision, Recall and F measure and rank based measures like Mean Average Precision and Cumulative Gain.
AHP and TOPSIS applied in the field of scientific research
Authors: El Mohadab Mohamed , Bouikhalene Belaid , Ouatik Fahd , Safi Said
Published: April 2019

Scientific research is a major issue for universities because it ensures its innovation and productivity, but to ensure the proper functioning of universities, the decisions-makers need powerful tools to assist them in this process. Multi criteria decision making (MCDM) may present an appropriate asset for this area especially with the analytical hierarchy process (AHP) which presents a theory of measurement through pairwise comparisons and relies on the judgments of experts to derive priority scales.
Estimate model of system management for database security
Authors: Alisawi W. Ch , Abdul AlMuhsen Hussain Alaa , A. Alawsi Wasan
Published: April 2019

A generalized model of information protection of a database management system is proposed, which can be used to implement database protection under any database management system. This model development methodology consists of four stages: requirements gathering, database analysis, “multi-level relational logical construction and a specific logical construction. The first three steps define actions for analyzing and developing a secure database, thus creating a generalized and secure database model”.
Systematic literature review on designing trust-based security for WSNs
Authors: Anwar Raja waseem , Zainal Anazida , Iqbal Saleem
Published: April 2019

The study assessed the design and development of trust-based security for wireless sensor networks. A qualitative approach was opted by employing systematic review analysis, which was assessed using secondary data collection. The design and development of trust-based security were mainly targeted, and 140 publications were randomly reviewed, from which 24 studies were finalized after excluding irrelevant data and studies that only contained abstracts. The results were analyzed focusing on the designs, applications and protocols and trust factors. Different studies have been evaluated, which have suggested that proper design and development of trust-based security should be the foremost aim to be applied in user environments. The study suggested that designing the trust management models based on the taxonomy of routing applications and relevant algorithms could be a part of future investigations.
Data visualisation of vehicle crash using interactive map and data dashboard
Authors: Abd Razak Muhammad Zaki , Mohd Fauzi Shukor Sanim , JM Gining Ray Adderley , Jamaluddin Muhammad Nabil Fikri
Published: April 2019

Vehicle crash contributes to a significant number of deaths and injuries in human races around the world. The government and the transportation expert work together around the clock to lessen the number of injuries and fatalities cause from vehicle crash issues. To come out with an effective solution whether from improving the trafficking system including road conditions or increasing awareness among drivers, the experts must analyse the data of vehicle crash from the past decades to find the major causes and come out with a decision. The lack of suitable techniques and tools to analyse a large amount of data is a deterrent in analysing vehicle crash datasets, and the process costs a lot of time. Data visualisation is a technique that allows people to display data in a more infographic form via data visualisation models. Therefore, this study aims to promote and elaborate more on data visualisation techniques using the interactive map and data dashboard to display vehicle crash data. Interactive map and data dashboard can help the government and transportation experts to describe vehicle crash data for them to make right decision to lessen car accident issues. The interactive map focuses on displaying vehicle crash data in map presentation while the data dashboard shows some charts and graph that describe the vehicle crash data in the statistical form. This study can be a reference model of creating interactive map and data dashboard or enhancing the capabilities in managing vehicle crash.
Cluster mechanism for hot data storage in HBase system
Authors: Al-Momani Mohammad Musa
Published: April 2019

The evolution in different areas like e-business contributed to increase the number of data. So, a scalable database is required to accommodate a large number of data. Moreover, this data could be important and the number of accessing for reading or writing operations can make a pressure in some servers more than others, this pressure called unbalanced accessing. This will be achieved if a system that guarantees the distribution of this important data in useful form is used, because the pressure can causes a delay. Accordingly, when we design a multi storage node to keep this data, the pressure will transfer from a server to another. So, the proposed system searched for a satisfied solution to distribute all the users on the servers in a useful way to detect any mistake or repeating updating operation data by using identification feature. This method is applied on Hbase and called Clusterization.
A chaotic based integrity verification and encryption model for real-time VANET
Authors: Shaik Kareemulla , Ali Hussain Dr. Md.
Published: April 2019

Integrity and data privacy are the main security parameters between the vehicle and roadside unit (RSU) over large VANETs.  The integrity of the vehicle is used to check its identity against the neighboring nodes, whereas data privacy ensures that the data of a vehicle has not been altered during the communication process. VANETs provide vehicles to give information about the security parameters and identity to vehicle to infrastructure communication and vehicle to vehicle communication. Most of the traditional VANETs are vulnerable to data security, integrity and authentication due to change in dynamic topology. Also, Traditional security models require limited data size for data security between the V2V or V2I. In this paper, an integrity verification model and non-linear double encryption model were proposed and implemented on large geographical VANET map. The main objective of the proposed model is to improve the security of the V2V communication in large VANETs. Experimental results proved that the proposed security model has less computation cost for encryption model and higher bit change during integrity verification compared to the existing approaches.
Performance evaluation of proposed load balancing algorithm with unstable concurrent programs
Authors: Jittawiriyanukoon Chanintorn
Published: April 2019

IoT is the succeeding cohort of the digital computing environment. A swift progression in the IoT deployment and its applications are on the rise. Improving load balancing mechanisms induces healthier performance of the internet based computing as higher number of users can be comfortable. Implementing full services for tasks with unstable concurrency is an uphill process. One of the encounters allied with this administration is the task partition among the applications, regularly referred as concurrent programs. Through load balancing not only resources are equally utilized but also concurrent job’s response time can be promoted. Therefore, in this paper the widely used load balancing algorithms are investigated and yet the proposed algorithm is introduced. Simulation is employed in order to compare the performance metrics such as mean queue length, utilization and throughput between the recommended and existing algorithms. The proposed algorithm confirms the load balancing and outperforms when processing unstable concurrent programs.
QoS hybrid uplink scheduler based on service type for M2M communications in LTE networks
Authors: Ouaissa Mariyam , Rhattoy Abdallah
Published: April 2019

The introduction of Machine-to-Machine (M2M) communications in cellular networks creates a new set of challenges because of the unique service requirements and features of M2M devices. One of these challenges is the management of radio resources, especially on the uplink because of the unfairness and poor performance that occurs when allocating resources to users. Long Term Evolution (LTE) and LTE-Advanced (LTE-A) are excellent candidates for supporting M2M communications because of their native IP connectivity and scalability for a variety of devices. Therefore, LTE schedulers should be able to meet the needs of M2M devices such as time constraints and specific Quality of Service (QoS) requirements. In this paper, these constraints are studied and analyzed, focusing on three schedulers; they are Round Robin (RR), First Maximum Expansion (FME) and Maximum Throughput (MT). These methods do not provide QoS to users who use different types of traffic flows. The solution proposed in this work is a hybrid model between two schedulers each of them is the best scheduling solution for the real-time service and the other for the non-real-time service, in order to meet QoS criteria maximizing throughput and minimizing packet loss. Video and voip were selected as real-time traffic and best effort for non-real time. The simulations results show that the proposed scheduler reaches the lowest Packet Loss Rate (PLR), delivering highest throughput and goodput among the other strategies.
OCA: overlapping clustering application unsupervised approach for data analysis
Authors: Danganan Alvincent Egonia , Sison Ariel M. , Medina Ruji P.
Published: April 2019

In this paper, a new data analysis tool called Overlapping Clustering Application (OCA) was presented. It was developed to identify overlapping clusters and outliers in an unsupervised manner. The main function of OCA is composed of three phases. The first phase is the detection of the abnormal values(outliers) in the datasets using median absolute deviation. The second phase is to segment data objects into cluster using k-means algorithm. Finally, the last phase is the identification of overlapping clusters, it uses maxdist (maximum distance of data objects allowed in a cluster) as a predictor of data objects that can belong to multiple clusters.  Experimental results revealed that the developed OCA proved its capability in detecting overlapping clusters and outliers accordingly.
Study of multiple-source data collection in wireless sensor networks
Authors: Issa Radhi Sehen
Published: April 2019

A detailed survey on the process of data collection from multiple sources in Wireless Sensor Networks (WSNs) is introduced. The topologies that determine the location of the network components with respect to each other are presented. These topologies are often referred to as Mobility topologies. The performance of the overall WSN architecture significantly depends on these topologies. As a consequence, these topologies are elaborately compared and discussed. The most common network components that efficiently collaborate in data collection process are explained. To highlight the data collection process as a subject of our concern, the phases that describe the stages of the data collection are illustrated. These phases consist of three successive stages: discovery, data transfer, and routing. To sum up, the most recent approaches for developing the process of data collection in multiple-source WSNs are also presented.
Prediction of entering processes into the deadlock state
Authors: Nicheporuk Andrii , Klots Yuriy , Yashyna Oksana , Mostovyi Sergiy , Nicheporuk Yuriy
Published: April 2019

The work is devoted to the problem of processes’ deadlock in the multi-tasking system. On the basis of the study of the life cycle of the process, the boundary state of the process was distinguished, which will precede the deadlock state. Proposed the method for prediction of entering processes into the deadlock state, which consists of two algorithms: algorithm of detection of potential processes that may fall into the deadlock and algorithm of processes detection that falling into the state of deadlock. An evaluation of time complexity of proposed method is conducted. Unlike the known methods and algorithms, proposed method use fuzzy logic components to detect two or more processes that fall into the state of deadlock, and thus do not make the algorithm cumbersome, which allows it to be used in modern operating systems.
Recognize printed Arabic letter using new geometrical features
Authors: Mohamad Haidar , Hashim Seham , Al-Saleh Anwar
Published: April 2019

The task of recognizing the shape of Arabic letters using modified algorithms discussed in this paper. The difficulty of recognizing these letters is summarized in the shape of the Arabic letter within a word from a large set of letters has a similar shape. Moreover, the shape of the letter is different depending on its position begin, middle, end within a word. Therefore, it is necessary to introduce new geometric features to categorize each letter. The suggested algorithm with 19 features is used in this paper. These features, like define points for each letter, divide a letter to blocks, edge detection and other features are shown in the suggested algorithm. The introduced geometric features give a high accuracy to recognize printed Arabic letter within a word or text. Minimum distance criteria used to estimate the error of the recognition process between the database and the tested Arabic letter. This method is good to explain the behaviour of the designed algorithm code to distinguish the geometric properties and the accuracy reaches 99.8% for the proposed method. The letter size changes geometry details when the font size is changed. The studied font is Times New Roman with size 30, 36, and 39. 
Forecasting ASEAN countries exchange rates using auto regression model based on triangular fuzzy number
Authors: Rahman Hamijah Mohd , Arbaiy Nureize , Efendi Riswan , Chai Wen Chuah
Published: April 2019

Exchange rate forecasting is important to represent the expectation of exchange rates future values. The forecasting task is due to the economic factor and the historical data used to forecast are exposed to uncertainty and observational error during data collection. The existing auto regression model only deals with uncertainty exist in the model, not in the data preparation. Uncertainties may contained in the data input and should be treated during data preparation which is an early stage of forecasting process. To date, only few researches discuss intensely on a fuzzy data preparation. However, data treatment during data preparation is important to reduce model’s error due to uncertainty problem. Hence, this paper presents an approach to construct Triangular Fuzzy Number to handle uncertainty in data during data preparation. As the Triangular Fuzzy Number is often used to represent uncertain information in a form of interval, this study proposed a procedure to construct Triangular Fuzzy Number from single point data. In this study, the Triangular Fuzzy Number is built in a form of symmetric triangular with 1%, 3% and 5% spread value. Autoregressive model is then used to forecast the exchange rate of Association of South East Asian Nation (ASEAN) countries. The result in this study shows that the forecasting exchange rate is significantly important to trace the movement of ASEAN countries exchange rates and beneficial in forecasting planning.
Objective assessment of surgeon’s psychomotor skill using virtual reality module
Authors: Zawani Ahmmad Siti Nor , Lee Ming Eileen Su , Che Fai Yeong , Sood Suneet , Gandhi Anil , Mohamed Nur Syarafina , Rahman Hisyam Abdul , Burdet Etienne
Published: April 2019

This study aims to identify measurable parameters that could be used as objective assessment parameters to evaluate surgical dexterity using computer-based assessment module. A virtual reality module was developed to measure dynamic and static hand movements in a bimanual experimental setting. The experiment was conducted with sixteen subjects divided into two groups: surgeons (N = 5) and non-surgeons (N = 11). Results showed that surgeons outperformed the non-surgeons in motion path accuracy, motion path precision, economy of movement, motion smoothness, end-point accuracy and end-point precision. The six objective parameters can complement existing assessment methods to better quantify a trainee’s performance. These parameters also could provide information of hand movements that cannot be measured with the human eye. An assessment strategy using appropriate parameters could help trainees learn on computer-based systems, identify their mistakes and improve their skill towards the competency, without relying too much on bench models and cadavers.
A model of acceptance factors for business intelligence in manufacturing using theoretical models
Authors: Mohd Yusof Ernie Mazuin , Othman Mohd Shahizan , Mi Yusuf Lizawati , Raja Kumaran Shamini , Mohd Yusof Ahmad Rizal
Published: April 2019

Manufacturing organizations implemented Business Intelligence (BI) due to many advantages offered by it. The lack of research on the acceptance of BI in manufacturing motivates the initiative in this study to have an understanding of the factors that influence the acceptance of BI in manufacturing sector. Therefore, the research proposes a model which indicates the acceptance factors of BI in manufacturing. An integrated model consisting of underlying models of Technology Acceptance Model (TAM), Expectation Confirmation Theory (ECT) and Task-Technology Fit (TTF) will be developed. The new model will formulate 19 hypotheses and 11 factors contributing to the continuance and acceptance of BI. The model will be tested using quantitative and qualitative survey conducted to Malaysian manufacturing companies and validated using Structural Equation Modelling (SEM) to investigate the causal and mediating relationships between the factors. The expected result is hoping to suggest that selected factors in the model are positively related towards the acceptance of BI in manufacturing. The results are also hoping to guide future initiatives by industrial practitioners to develop and distribute BI to the manufacturing market.
Imbalance class problems in data mining: a review
Authors: Ali Haseeb , Mohd Salleh Mohd Najib , Saedudin Rohmat , Hussain Kashif , Mushtaq Muhammad Faheem
Published: April 2019

The imbalanced data problems in data mining are common nowadays, which occur due to skewed nature of data. These problems impact the classification process negatively in machine learning process. In such problems, classes have different ratios of specimens in which a large number of specimens belong to one class and the other class has fewer specimens that is usually an essential class, but unfortunately misclassified by many classifiers. So far, significant research is performed to address the imbalanced data problems by implementing different techniques and approaches. In this research, a comprehensive survey is performed to identify the challenges of handling imbalanced class problems during classification process using machine learning algorithms. We discuss the issues of classifiers which endorse bias for majority class and ignore the minority class. Furthermore, the viable solutions and potential future directions are provided to handle the problems.
Rain prediction using fuzzy rule based system in North-West malaysia
Authors: Mohd Safar Noor Zuraidin , Ramli Azizul Azhar , Mahdin Hirulnizam , Ndzi David , Naim Ku Khalif Ku Muhammad
Published: April 2019

The warm and humid condition is the characteristic of Malaysia tropical climate. Prediction of rain occurrences is important for the daily operations and decisions for the country that rely on agriculture needs. However predicting rainfall is a complex problem because it is effected by the dynamic nature of the tropical weather parameters of atmospheric pressure, temperature, humidity, dew point and wind speed. Those parameters have been used in this study. The rainfall prediction are compared and analyzed.   Fuzzy Logic and Fuzzy Inference System can deal with ambiguity that often occurred in meteorological prediction; it can easily incorporate with expert knowledge and empirical study into standard mathematical. This paper will determine the dependability of Fuzzy Logic approach in rainfall prediction within the given approximation of rainfall rate, exploring the use of Fuzzy Logic and to develop the fuzzified model for rainfall prediction. The accuracy of the proposed Fuzzy Inference System model yields 72%
Tunable function of feeding network and SPDT switch for WIMAX application
Authors: Edward N. , Shairi N. A. , Zakaria Z. , Sutikno Tole , Bahri I. D. Saiful
Published: April 2019

A tunable circuit that functions as a power divider and a single pole double throw (SPDT) switch is proposed in this paper. The power divider design was based on the conventional Wilkinson power divider (WPD). Since WPD design has wideband properties, a modification was made in the design to make it narrowband so that it will only work for WiMAX applications. Two shorted stubs were introduced in the transmission line of the output ports to encounter the mismatch when the function was switched to an SPDT switch. Rogers RO4350 (er = 3.48, h = 0.508mm) was used as a substrate material and copper (thickness = 0.035 mm) related to patch of this proposed design. When the circuit functioned as a power divider, the simulated result showed S11 < -16 dB, S12 > 3.97 dB, and S23 < -14 dB for both operating frequencies of 2.5 GHz and 3.5 GHz. On the other hand, when the circuit functioned as an SPDT switch and port 2 was in the ON state, the simulated result showed S11 < -35 dB, S12 > -1.1, S13 < -16 dB, and S23 < 18 dB for both operating frequencies of 2.5 and 3.5 GHz. The proposed design showed a good performance as a power divider and an SPDT switch, thus, it can be used for multifunctional microwave circuits.
Develop and implementation of PC based controller for humanoid robot using digital potentiometer
Authors: Mohd Shah Hairol Nizam , Abdollah Mohd Fairus , Kamis Zalina , Mohd Aras Mohd Shahrieel , Mohd Aras Mohd Shahrieel , Baharon Mohd Rizuan , Baharon Mohd Rizuan , Sallehoddin Muhammad Zakwan Akmal , Sallehoddin Muhammad Zakwan Akmal
Published: April 2019

This paper introduced to develop and implementation of PC based controller for humanoid robot using digital potentiometer. The main objective in this paper is to develop and implement the joystick controller by using a digital potentiometer circuit board that be able to control the humanoid robot movement. The Arduino board and digital potentiometer will be integrated by connecting both pins in between wiper, W pin and ground, GND to the DB9 pins of remote control platform, which is TX and RX pins respectively. Humanoid robot as known as TOMY i-SOBOT is used as a preferred model due to wide usage in many applications. A digital potentiometer will be transmitted the voltage and current value depend on the digital level through serial communication to give the instruction for humanoid robot movement. The humanoid movement based on Guided User Interface (GUI) where the user give a commands by pressing the button on the GUI such as turn left, right, forward, and reverse. The results show that the humanoid movement able to control based on the voltage and current in a digital potentiometers value.
Optimization of KOH etching process for MEMS square diaphragm using response surface method
Authors: Yusof Norliana , Bais Badariah , Yeop Majlis Burhanuddin , Soin Norhayati , Yunas Jumril
Published: April 2019

KOH wet etching is widely used in realizing MEMS diaphragm due to its low cost, safe and easy handling. However, wet etching process parameters need to be studied thoroughly in order to realize the desired shape and size of MEMS devices. This paper presents the numerical study and optimization of KOH etching process parameters using the response surface method (RSM). Face central composite design (FCC) of RSM was employed as the experimental design to analyze the result and generate a mathematical prediction model. From the analysis, the temperature was identified as the most significant process parameter that affects the etching rate, thus affecting the thickness and size of the diaphragm. The results of RSM prediction for optimization were applied in this study. Particularly, 45% of KOH concentration, temperature of 80°C, 1735 µm2 of mask size, and 7.2 hours of etching time were implemented to obtain a square MEMS diaphragm with thickness of 120 µm and size of 1200 µm2. The results of RSM based optimization method for KOH wet etching offers a quick and effective method for realizing a desired MEMS device.
Portable heart valve disease screening device using electronic stethoscope
Authors: Zubir Suboh Mohd , Yaakop Muhyi , Azlan Abu Mohd , Md Yid Mohd Syazwan , Faiz Ramli Aizat , Yusoff Mashor Mohd , Mohd Saad Abdul Rahman , Aziz Rashid Ali Mohd Shaiful
Published: April 2019

Heart sound analysis has been a popular topic of studies since a few decades ago. Most of the studies are done in PC platform since embedding the complex algorithm into a simple small device such as microcontroller board seems to be very difficult due to limited processing speed and memory. This study classifies normal and abnormal heart sound signal from four categories of Heart Valve Disease. An automated system that consists of segmentation, feature extraction and classification of the heart sound signal is developed in PC and hardware platforms. A multimedia board completed with a single board computer, audio codec and graphic LCD is used to make a portable heart valve disease screening device with electronic stethoscope as the input for the system. Both system recorded 96.3% specificity. However, the portable device has only 77.78% sensitivity and 87.04% accuracy compared to PC platform that have sensitivity and accuracy of more than 90%.
Determination of favorable blood glucose target range for stochastic TARgeted (STAR) glycemic control in Malaysia
Authors: Abu-Samah A. , A. Razak N. N. , A. Razak A. , K. Jamaludin U. , M. Suhaimi F. , M. Ralib A.
Published: April 2019

Stress-induced hyperglycemia is common in critically ill patients, but there is uncertainty about what constitutes an optimal blood glucose target range for glycemic control. Furthermore, to reduce the rate of hyperglycemic and hypoglycemic events, model-based glycemic control protocols have been introduced, such as the stochastic targeted (STAR) glycemic control protocol. This protocol has been used in the intensive care units of Christchurch and Gyulà Hospital since 2010, and in Malaysia since 2017. In this study, we analyzed the adaptability of the protocol and identified the blood glucose target range most favorable for use in the Malaysian population. Virtual simulation results are presented for two clinical cohorts: one receiving treatment by the STAR protocol itself and the other receiving intensive insulin therapy by the sliding scale method. Performance and safety were analyzed using five clinical target ranges, and best control was simulated at a target range of 6.0–10.0 mmol/L. This target range had the best balance of performance, with the lowest risk of hypoglycemia and the lowest requirement for nursing interventions. The result is encouraging as the STAR protocol is suitable to provide better and safer glycemic control while using a target range that is already widely used in Malaysian intensive care units
An adaptive intelligent alarm system for wireless sensor network
Authors: Salman Ayman Dawood , Khalaf Osamah Ibrahim , Abdulsaheb Ghaida Muttasher
Published: April 2019

Security is one of the imperative issues in an advanced local condition. The current center around formative and research issues of Wireless Sensor Network(WSN) based Smart Home.  WSN based shrewd home detection system gives a safe and safe living condition. A Wireless Sensor System (WSN) is a system which is building by utilizing little independent hubs (sensors). Its motivation is to screen certain ecological parameters, for example, temperature, dampness, brilliance, weight, sound, movement, and so forth. This paper depicts the improvement of a smart home condition dependent on exact Wireless Sensor Network and furthermore depicts private vitality observing and controlling procedures for keen home systems administration framework. This paper proposes a basic and adaptable remote arrange for domestics computerization of temperature, moistness, gas, movement and light by executing dependable sensor hubs which can be controlled too observed. This innovation offers energizing and new chance to build the availability of devices inside the home for the home computing.
Using infrared radiation in preparation of feed for farm livestock
Authors: Senthilkumar T , Reshetnik Ekaterina I. , Evdokimov Vyacheslav G. , Perepelkina Lyubov I. , Krivuca Zoya F. , Samarina Yulia R. , Kuznetsov Evgeniy E. , Kuznetsov Natalia A.
Published: April 2019

The article in hand describes a processing line for preparation of feed for farm livestock and the design of an infrared drying unit integrated into this line. The main objective of this study is to find ways to provide a full-value feeding of farm animals throughout the calendar year.  At present, there are various methods for preserving feed proposed with the aim of providing a full-fledged diet.  However, following the recommendations for feed storage according to the recommended conditions, as a rule, results in high losses of its total weight and nutritional properties due to a long winter period with low-temperature regimes, typical of the Amur Region of Russia. This article presents the results of the study of a prospective processing line for the preparation of feed for long-term storage, which ensures the preservation of their basic nutritional properties, with an integrated infrared drying unit.
A sub-1V high PSRR OpAmp based β-multiplier CMOS bandgap voltage reference with resistive division
Authors: SLAMTI Anass , MEHDAOUI Youness , CHENOUNI Driss , LAKHLIAI Zakia
Published: April 2019

A sub-1V opamp based β-multiplier CMOS bandgap voltage reference (BGVR) with high power supply rejection ratio (PSRR) and low temperature coefficient (TC) is proposed in this paper. A current mode regulator scheme is inserted to isolate the supply voltage of the operational amplifier (opamp) and the supply voltage of the BGVR core from the supply voltage source in order to reduce ripple sensitivity and to achieve a high PSRR. The proposed circuit is designed and simulated in 0.18-μm standard CMOS technology. The proposed voltage reference delivers an output voltage of 634.6mV at 27°C. Tthe measurement temperature coefficient is 22,3ppm/°C over temperature range -40°C to 140°C, power supply rejection ratio is -93dB at 10kHz and -71dB at 1MHz and a line regulation of 104μV/V is achieved over supply voltage range 1.2V to 1.8V. The layout area of the proposed circuit is 0.0337mm2. The proposed sub-1V bandgap voltage reference can be used as an internal voltage reference in low power LDO regulators and switching regulators.
Positioning of light shelves to enhance daylight illuminance in office rooms
Authors: Mohapatra Badri Narayan , Kumar M. Ravi , Mandal Sushanta Kumar
Published: April 2019

This paper aims to improve daylighting by using light shelves. Horizontal light shelf is found to increase the illuminance in the interior of office rooms. By tilting external light shelf more illuminance can be achieved. For uniformity of illuminance tiltable light shelf is the best choice instead of horizontal light shelf. The performance of light shelves was examined through simulations on DIALux and compared with experimental values obtained from a prototype. Substantial improvement in illuminance is obtained in the experimental studies with tilted light shelves on the prototype.
Real-time water quality monitoring system: an IoT application
Authors: Mohd Yusof Zulkhairi , Billah Md Masum , Kadir Kushsairy
Published: April 2019

There is huge number of disease which is caused through water drinking that being polluted was supplied to the consumer. This is something that cannot be underestimate because it can cause high cost of treatment or death. Its not only cause troubles to the consumer which is human, it is also included all aquatic life and surrounding ecosystem. There is way to overcome this problem that created before which is take the sample of water to the lab. The result of water being polluted or not will be released by the lab. But this system going to take lot of times because there are few process that should be followed. This system is not suitable anymore because it is not portable, easy and fastest. It should be upgraded to the IoT system because it can cut times, internet base and people will be more alert to the quality of water. Therefore, a real-time water quality monitoring system is proposed in this research to reduce number of fatality happened from water.
Design of remotely operated vehicle as installer tools of tidal turbine and seismograph under water
Authors: Mazaya Muhammad Sulthan
Published: April 2019

Tidal turbines and seismographs constitute instruments that can be used as an earthquake detector that lead to tsunamis. As an early detection instrument for tsunami disaster, tidal turbine and seismograph are generally placed under the surface of the water. The design objective in this study is designing a Remotely Operated Vehicle (ROV) which can be used as a tool for tidal turbine and seismograph installation. The design method applied in this study is designing a prototype by following the product research and development procedures. Making control systems has three stages, namely: software design, hardware manufacture, and software and hardware integration. The made software includes the ROV motion control program through the control of Arduino Nano R2 ATMega microcontroller with programming that uses C-Basic language. The design findings show that the designed ROV can be used effectively to simulate the installation of tidal turbine and seismograph under the surface of the water in 2 meters at depth with 15 minutes of installation time in undulating water.
Improving bearings-only target state estimation tracking problem by using adaptive and nonlinear kalman algorithms
Authors: Khadour Tammam , Saba Michel Al , Saleh Louay
Published: April 2019

Finding the best estimate of the process state from noisy data is the main problem in tracking systems, many efforts and researches have been done to remove this noise. More useful information about the target’s state can be extracted from observations by using a more appropriate model for the target’s motion or using additional sensors. In this paper, we will introduce two methods to improve the estimation of bearing-only target tracking problem in two dimensions (2D). The first method is by adding a third sensor and making a good alignment of those sensors, and at the same time an extended Kalman filter (EKF), unscented Kalman filter (UKF) and cubature Kalman filter (CKF) are implemented. The second method is by applying an adaptive nonlinear Kalman filter (ANKF) for two sensors to solve the problem of measurement variance uncertainty.
Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender
Authors: Nor Shahrudin N. S. , A. Sidek K. , Z. Jusoh A.
Published: April 2019

Good mental health is important in our daily life. A person commonly finds stress as a barrier to enhance an individual’s performance. Be reminded that not all people have the same level of stress because different people have dissimilar problems in their life. In addition, different level of age and gender will affect unequal amount of stress. Electrocardiogram (ECG) signal is an electrical indicator of the heart that can detect changes of human response which relates to our emotions and reactions. Thus, this research proposed a non-intrusive detector to identify stress level for both gender and different classification of age using the ECG. A total of 30 healthy subjects were involved during the data acquisition stage. Data acquisition which initialize ECG data were divided into two conditions; which are normal and stress states. ECG data for normal state only need the participant to breath in and out normally. In other hand, the participants also need to undergo Stroop Colour word test as a stress inducer to represent ECG in stress state. Then, Sgolay filter was selected in the pre-processing stage to remove artifacts in the signal. The process was followed by feature extraction of the ECG signal and finally classified using RR Interval (RRI), different amplitudes of R peaks and Cardioid graph were used to evaluate the performance of the proposed technique. As a result, Class 5 (age range between 50-59 years old) marks the highest changes of stress level rather than other classes, while women are more affected by stress rather than men by showing tremendous percentage changes between normal and stress level over the proposed classifiers. The result proves that ECG signals can be used as an alternative mechanism to recognize stress more efficiently with the integration of gender and age variabilities.