bluuebunny/crossref_metadata_2025 huggingface dataset:
On the latency and jitter evaluation of software defined networks
Authors: Numan Paulson Eberechukwu , Mohamad Yusof Kamaludin , Bin Marsono Muhammad Nadzir , Syed Yusof Sharifah Kamilah , Bin Mohd Fauzi Mohd Husaini , Nathaniel Salawu , Onwuka Elizabeth N. , Bin Baharudin Muhammad Ariff
Published: March 2020

Conventional networking devices require that each is programmed with different rules to perform specific collective tasks. Next generation networks are required to be elastic, scalable and secured to connect millions of heterogeneous devices. Software defined networking (SDN) is an emerging network architecture that separates control from forwarding devices. This decoupling allows centralized network control to be done network-wide. This paper analyzes the latency and jitter of SDN against a conventional network. Through simulation, it is shown that SDN has an average three times lower jitter and latency per packet that translate to improved throughput under varying traffic conditions.
The generation revenue and demand payment assessment for pool based market model in Malaysia electricity supply industry
Authors: Ngadiron Zuraidah , Radzi N. H. , Hassan M. Y.
Published: March 2020

The objective of this paper is to address the economic benefits in term of generation revenue and demand payment for the pool based market model in Malaysia electricity supply industry (MESI). In pool market model, there are issues on the benefit of the generators such as too high system marginal price (SMP) during peak demand and no revenue during low demand. Therefore, conceptual study for two bus test system in MESI involving four generators around Peninsular Malaysia is conducted to perform the economic analysis in term of generation revenue and demand assessment considering existing single buyer model and pool based market model, i.e., pool model, spot market model and the proposed model, in order to identify which market model is superior. As a result, the proposed model managed to decrease the demand payment as it is proportional to generation revenue, even though the generation revenue is at intermediate value and succeed to increase the low and medium generator’s revenue.
A simulation study of excitation coil design in single-sided mpi scanner for human body application
Authors: Othman Nurmiza , Shahkhirin Birahim Muhamad Fikri , Wan Zakaria Wan Nurshazwani , Md Tomari Mohd Razali , Ramdon Baharom Md Nor , Hakim Luqman
Published: March 2020

Magnetic particle imaging (MPI), a tomographic imaging method has been introduced for 3D imaging of human body with some potential applications such as magnetic hyperthermia and cancer imaging. It involves three important elements: tracer development using magnetic nanoparticles (MNPs), hardware realization (scanner using excitation and pickup coils), and image reconstruction optimization. Their combination will produce a high quality of image taken from any biological tissue in the human body based on the secondary magnetic field signal from the magnetized MNPs that are injected into human body. A homogeneous and adequate magnetic field strength from an excitation coil is needed to enhance the quality of the secondary signal. However, the complex surface topography of human body and physical properties of an excitation coil influence the strength and the homogeneity of the magnetic field generation at the MNPs. Therefore, this work focused on finding alternative design of excitation coil used in single sided MPI to produce up to 2 mT with high homogeneity of field distribution in the MNPs at the varied depth of 10 to 30 mm under the excitation coil. We proposed several designs with variation in physical properties and coil arrangement based on simulation study carried out by using Ansys Maxwell.
Performance comparison of SVM and ANN for aerobic granular sludge
Authors: Ahmad Yasmin Nur Sakinah , Wahab Norhaliza Abdul , Anuar Aznah Nor , Bob Mustafa
Published: March 2020

To comply with growing demand for high effluent quality of Domestic Wastewater Treatment Plant (WWTP), a simple and reliable prediction model is thus needed. The wastewater treatment technology considered in this paper is an Aerobic Granular Sludge (AGS). The AGS systems are fundamentally complex due to uncertainty and non-linearity of the system makes it hard to predict. This paper presents model predictions and optimization as a tool in predicting the performance of the AGS. The input-output data used in model prediction are (COD, TN, TP, AN, and MLSS). After feature analysis, the prediction of the models using Support Vector Machine (SVM) and Feed-Forward Neural Network (FFNN) are developed and compared. The simulation of the model uses the experimental data obtained from Sequencing Batch Reactor under hot temperature of 50˚C. The simulation results indicated that the SVM is preferable to FFNN and it can provide a useful tool in predicting the effluent quality of WWTP.
Graphene slurry based passive Q-switcher in erbium doped fiber laser
Authors: Fatin Zuikafly Siti Nur , Razak Nor Farhah , Rosnan Rizuan Mohd , Harun Sulaiman Wadi , Ahmad Fauzan
Published: March 2020

In this work, a Graphene slurry based passive Q-switcher fabricated from Graphene-Polylactic acid (PLA) filament which is used for 3D printing. To produce the Graphene slurry, the diameter of the filament was reduced and Tetrahydrofuran (THF) was used to dissolve the PLA. The Graphene-THF suspension was drop cast to the end of a fiber ferrule and the THF then evaporated to develop Graphene slurry based SA which is integrated in fiber laser cavity. At threshold input pump power of 30.45 mW, a Q-switched Erbium-doped fiber laser (EDFL) can be observed with the wavelength centered at 1531.01 nm and this remained stable up to a pump power of 179.5 mW. As the pump power was increased gradually, an increase in the repetition rates was recorded from 42 kHz to 125 kHz, while the pulse width was reduced to 2.58 μs from 6.74 μs. The Q-switched laser yielded a maximum pulse energy and peak power of 11.68 nJ and 4.16 mW, respectively. The proposed Graphene slurry based saturable absorber also produced a signal-to-noise ratio of 44 dB indicating a stable Q-switched pulsed laser.
Observation of dark and bright pulses in q-switched erbium doped fiber laser using graphene nano-platelets as saturable absorber
Authors: Muhamad Apandi Nur Hidayah , Fatin Zuikafly Siti Nur , Kasim Nabilah , Mohamed Mohd Ambri , Harun Sulaiman Wadi , Ahmad Fauzan
Published: March 2020

In this paper, a passively Q-switched Erbium doped fiber laser (EDFL) by residing Graphene nanoplatelets (GnPs) embedded in polyvinyl alcohol (PVA) based saturable absorber (SA) is demonstrated. To aid the dispersion of GNPs, a surfactant is used and then it is mixed with polyvinyl alcohol (PVA) as host polymer to develop GnPs-PVA film based passive SA. The GnPs-PVA based film then integrated in laser cavity in ring cavity configuration for pulse laser generation. The experimental works show that the proposed passive SA operates at input pump power range from 77 mW to 128 mW with a tunable repetition rate from 78.4 kHz to 114.8 kHz and a shortest pulse width of 3.69 µs. The laser produces maximum instantaneous output peak power and pulse energy of 7.3 mW and 30.46 nJ, respectively and accompanied by signal to noise ratio (SNR) of 64 dB.
Simulation study of single event effects sensitivity on commercial power MOSFET with single heavy ion radiation
Authors: Yahya Erman Azwan , Kannan Ramani , Lee Lini
Published: March 2020

High-frequency semiconductor devices are key components for advanced power electronic system that require fast switching speed. Power Metal Oxide Semiconductor Field Effect Transistor (MOSFET) is the most famous electronic device that are used in much power electronic system. However, the application such as space borne, military and communication system needs Power MOSFET to withstand in radiation environments. This is very challenging for the engineer to develop a device that continuously operated without changing its electrical behavior due to radiation. Therefore, the main objective of this study is to investigate the Single Event Effect (SEE) sensitivity by using Heavy Ion Radiation on the commercial Power MOSFET. A simulation study using Sentaurus Synopsys TCAD software for process simulation and device simulation was done. The simulation results reveal that single heavy ion radiation has affected the device structure and fluctuate the I-V characteristic of commercial Power MOSFET.
A hybrid predictive technique for lossless image compression
Authors: Azman N. A. N. , Ali Samura , A. Rashid Rozeha , Asraf Saparudin Faiz , Adib Sarijari Mohd
Published: March 2020

Compression of images is of great interest in applications where efficiency with respect to data storage or transmission bandwidth is sought.The rapid growth of social media and digital networks have given rise to huge amount of image data being accessed and exchanged daily. However, the larger the image size, the longer it takes to transmit and archive. In other words, high quality images require huge amount of transmission bandwidth and storage space. Suitable image compression can help in reducing the image size and improving transmission speed. Lossless image compression is especially crucial in fields such as remote sensing healthcare network, security and military applications as the quality of images needs to be maintained to avoid any errors during analysis or diagnosis. In this paper, a hybrid prediction lossless image compression algorithm is proposed to address these issues. The algorithm is achieved by combining predictive Differential Pulse Code Modulation (DPCM) and Integer Wavelet Transform (IWT). Entropy and compression ratio calculation are used to analyze the performance of the designed coding. The analysis shows that the best hybrid predictive algorithm is the sequence of DPCM-IWT-Huffman which has bits sizes reduced by 36%, 48%, 34% and 13% for tested images of Lena, Cameraman, Pepper and Baboon, respectively.
Performance analysis of ultrathin junctionless double gate vertical MOSFETs
Authors: E. Kaharudin K. , A. F. M. Napiah Z. , Salehuddin F. , S. M. Zain A. , F. Roslan Ameer
Published: March 2020

The main challenge in MOSFET minituarization is to form an ultra-shallow source/drain (S/D) junction with high doping concentration gradient, which requires an intricate S/D and channel engineering. Junctionless MOSFET configuration is an alternative solution for this issue as the junction and doping gradients is totally eliminated. A process simulation has been developed to investigate the impact of junctionless configuration on the double-gate vertical MOSFET. The result proves that the performance of junctionless double-gate vertical MOSFETs (JLDGVM) are superior to the conventional junctioned double-gate vertical MOSFETs (JDGVM). The results reveal that the drain current (ID) of the n-JLVDGM and p-JLVDGM could be tremendously enhanced by 57% and 60% respectively as the junctionless configuration was applied to the double-gate vertical MOSFET. In addition, junctionless devices also exhibit larger ION/IOFF ratio and smaller subthreshold slope compared to the junction devices, implying that the junctionless devices have better power consumption and faster switching capability.
Comparative analysis of classification algorithms for chronic kidney disease diagnosis
Authors: Saringat Zainuri , Mustapha Aida , Saedudin R. D. Rohmat , Samsudin Noor Azah
Published: March 2020

Chronic Kidney Disease (CKD) is one of the leading cause of death contributed by other illnesses such as diabetes, hypertension, lupus, anemia or weak bones that lead to bone fractures. Early prediction of CKD is important in order to contain the disesase. However, instead of predicting the severity of CKD, the objective of this paper is to predict the diagnosis of CKD based on the symptoms or attributes observed in a particular case, whether the stage is acute or chronic. To achieve this, a classification model is proposed to label stage of severity for kidney diseases patients. The experiments then investigated the performance of the proposed classification model based on eight supervised classification algorithms, which are ZeroR, Rule Induction, Support Vector Machine, Naïve Bayes, Decision Tree, Decision Stump, k-Nearest Neighbour, and Classification via Regression. The performance of the all classifiers is evaluated based on accuracy, precision, and recall. The results showed that the regression classifier perform best in the kidney diagnostic procedure.
A mapping study on blood glucose recommender system for patients with gestational diabetes mellitus
Authors: Rosli Shuhada Mohd , Rosli Marshima Mohd , Nordin Rosmawati
Published: March 2020

Blood glucose (BG) prediction system can help gestational diabetes mellitus (GDM) patient to improve the BG control with managing their dietary intake based on healthy food. Many techniques have been developed to deal with blood glucose prediction, especially those for recommender system. In this study, we conduct a systematic mapping study to investigate recent research about BG prediction in recommender systems. This study describes an overview of research (2014-2018) about BG prediction techniques that has been used for BG recommender system. As results, 25 studies concerning BG prediction in recommender system were selected. We observed that although there is numerous studies published, only a few studies took serious discussion about techniques used to incorporate the BG algorithms. Our result highlighted that only one study discusses hybrid filtering technique in BG recommender system for GDM even though it has an ability to learn from experience and to improve prediction performance. We hope that this study will encourage researchers to consider not only machine learning and artificial intelligent techniques but also hybrid filtering technique for BG recommender system in the future research.
Collaborative filtering content for parental control in mobile application chatting
Authors: Bin Mohamad Razali Muhamad Ridhwan , Ahmad Suzana , Diah Norizan Mat
Published: March 2020

Mobile phone is an important medium of communication for most people regardless their age. One of the most used mobile phone application is chat application. Since mobile users are across different age groups, from youngsters to senior citizen, each age level has their own ways or styles of communication when using mobile application chatting. Adult mostly used proper syntax with complete sentences while youngsters normally use short forms with incomplete sentences. In addition, improper communication styles, usage of bad and inappropriate words has become a trend among youngsters. This matter gives negative impact on the education system in a short-term and national language preservation in a long term. Hence, in this paper, researchers present a tool that provides word recommendations for mobile application chatting. This tool would be is an education material to younger generation users with subtle approach. Implementation of the tool is by adapting Collaborative Filtering approach with User-Based model which focusing on recommendation on similar interest between users. Collaborative filtering content tool is functioning well during the functionality testing and it is thriving as a mobile application chatting guidance.
Development of augmented reality to learn history
Authors: Hazirah Mohd Azhar Nur , Diah Norizan Mat , Ahmad Suzana , Ismail Marina
Published: March 2020

Augmented Reality (AR) is a technology that enables a new information delivery environment. AR promotes both engagement and motivation for people to obtain and acquire certain knowledge or information including those concerning history. People, especially the young generation, often view history as an uninteresting and boring subject matter. This may be due to the lack of interactivity and visual images that accompanying the information on history. This could affect our level of understanding about the history of our country such as the fall of Melaka Empire and weaken our spirit of patriotism. Thus, this research aims to study the effect of combining the AR technology together with the traditional information to create excitement in learning history. The development of the AR application in this project is to enhance the traditional book by allowing users to see the digital visual of historical events. The development of the application involves five phases that are analysis, design, develop, implement, and evaluate. The mobile application of AR book on the fall of Melaka Empire history has been developed successfully and the findings show that most users agree that the application contributes to higher users’ satisfaction.
On the use of voice activity detection in speech emotion recognition
Authors: Fahreza Alghifari Muhammad , Surya Gunawan Teddy , Aminah binti Wan Nordin Mimi , Asif Ahmad Qadri Syed , Kartiwi Mira , Janin Zuriati
Published: March 2020

Emotion recognition through speech has many potential applications, however the challenge comes from achieving a high emotion recognition while using limited resources or interference such as noise. In this paper we have explored the possibility of improving speech emotion recognition by utilizing the voice activity detection (VAD) concept. The emotional voice data from the Berlin Emotion Database (EMO-DB) and a custom-made database LQ Audio Dataset are firstly preprocessed by VAD before feature extraction. The features are then passed to the deep neural network for classification. In this paper, we have chosen MFCC to be the sole determinant feature. From the results obtained using VAD and without, we have found that the VAD improved the recognition rate of 5 emotions (happy, angry, sad, fear, and neutral) by 3.7% when recognizing clean signals, while the effect of using VAD when training a network with both clean and noisy signals improved our previous results by 50%.
PHP modernization approach generating KDM models from PHP legacy code
Authors: Moutaouakkil Amine , Mbarki Samir
Published: March 2020

With the rise of new web technologies such as web 2.0, Jquery, Bootstrap. Modernizing legacy  web systems to  benefit from the advantages of the new technologies is more and more relevant. The migration of a system from an environment to another is a time and effort consuming process, it involves a complete rewrite of the application adapted to the target platform. To realize this migration in an automated and standardized way, many approaches have tried to define standardized engineering processes. Architecture Driven Modernization (ADM) defines an approach to standardize and automate the reengineering process.  We defined an ADM approach to represent PHP web applications in the highest level of abstraction models. To do this, we have used software artifacts as a entry point . This paper describes the extraction process, which permits discovering and understanding of the legacy system. And generate models to represent the system in an abstract way.
A novel miniature coplanar band-pass filter for ISM applications
Authors: Nasiri Badr , Ennajih Abdelhadi , Errkik Ahmed , Zbitou Jamal , Derri Mounir
Published: March 2020

This paper presents a novel approach to design a compact miniature coplanar band-pass filter by using rectangular split ring resonator. This proposed circuit is designed for the Industrial, Scientific and, Medical (ISM) frequency band applications at 2.4 GHz. At the first stage, a metamaterial resonator is designed and simulated in a TEM waveguide to verifiy its electromagnetic proprieties around the desired frequency bands. At the second stage, a band pass filter is designed using the proposed metamaterial resonator. Many parametric studies are realized to investigate the effect and influence of some resonator parameters on the proposed BPF performances. ADS Agilent and CST-MWS solvers are used in order to verify the simulated results. The circuit frequency responses show an excellent insertion loss and good return loss in the passband.
Optimization of distance formula in K-Nearest Neighbor method
Authors: Lubis Arif Ridho , Lubis Muharman , Khowarizmi Al-
Published: March 2020

K-Nearest Neighbor (KNN) is a method applied in classifying objects based on learning data that is closest to the object based on comparison between previous and current data. In the learning process, KNN calculates the distance of the nearest neighbor by applying the euclidean distance formula, while in other methods, optimization has been done on the distance formula by comparing it with the other similar in order to get optimal results. This study will discuss the calculation of the euclidean distance formula in KNN compared with the normalized euclidean distance, manhattan and normalized manhattan to achieve optimization results or optimal value in finding the distance of the nearest neighbor.
Design of a low-power compact CMOS variable gain amplifier for modern RF receivers
Authors: Alam M. J. , Bhuiyan Mohammad Arif Sobhan , Badal Md Torikul Islam , Reaz Mamun Bin Ibne , Kamal Noorfazila
Published: March 2020

The demand for portability has speeded up the design of low-power electronic communication devices. Variable gain amplifier (VGA) is one of the most vulnerable elements of every modern receiver for the proper baseband processing of the signal. CMOS VGAs are generally suffered from low bandwidth and small gain range. In this research, a two-stage class AB VGA, each stage comprising of a direct transconductance amplifier and a linear transimpedance amplifier, is designed in Silterra 0.13-μm CMOS utilizing Mentor Graphics environment. The post-layout simulation results reveal that the VGA design achieves the widest bandwidth of 200 MHz and high gain range from -33 to 32 dB. The VGA dissipates only 2mW from a single 1.2 V DC supply. The core chip area of the VGA is also only 0.026 mm2 which is also the lowest compared to recent researches. Such a VGA will be a very useful module for all modern communication devices.
Bacterial quorum sensing applied to the coordination of autonomous robot swarms
Authors: Martinez S. Fredy H. , Martinez S. Fernando , Montiel A. Holman
Published: March 2020

This paper proposes a strategy for the coordination of a swarm of robots in an unknown environment. The basic idea is to achieve the autonomous movement of the group from an initial region to a target region avoiding obstacles. We use a behavior model similar to bacterial Quorum Sensing (QS) as a technique for the coordination of robots. This behavior has been described as a key element in the interaction between bacteria, and we use it as a basic tool for local interaction, both between the robot and between the robot and the environment. The movement of the swarm of robots, or multi-agent robotic system, is shown as an emerging behavior resulting from the interaction of agents (in the context of artificial intelligence) from basic rules of behavior. The proposed strategy was successfully evaluated by simulation on a set of robots.
Novel design of a fractional wavelet and its application to image denoising
Authors: Abderrahim Lanani , Salama Meghriche , Abdelbaki Djouambi
Published: March 2020

This paper proposes a new wavelet family based on fractional calculus. The Haar wavelet is extended to fractional order by a generalization of the associated conventional low-pass filter using the fractional delay operator Z-D. The high-pass fractional filter is then designed by a simple modulation of the low-pass filter. In contrast, the scaling and wavelet functions are constructed using the cascade Daubechies algorithm. The regularity and orthogonality of the obtained wavelet basis are ensured by a good choice of the fractional filter coefficients. An application example is presented to illustrate the effectiveness of the proposed method. Thanks to the flexibility of the fractional filters, the proposed approach provides better performance in term of image denoising.
System architecture to select the charging station by optimizing the travel time considering the destination of electric vehicle drivers in smart cities
Authors: El-fedany Ibrahim , Kiouach Driss , Alaoui Rachid
Published: March 2020

The main limitations of electric vehicles are the limited scope of the battery and their relatively long charging times. This may cause discomfort to drivers of electric vehicles due to a long waiting period at the service of the charging station, during their trips. In this paper, we suggest a model system based on argorithms, allowing the management of charging plans of electric vehicles to travel on the road to their destination in order to minimize the duration of the drivers' journey. The proposed system decision to select the charging station, during advance reservation of electric vehicles, take into account the time of arrival of electric vehicles at charging stations, the expected charging time at charging stations, the local status of the charging stations in real time, and the amount of energy sufficient for the electric vehicle to arrive at the selected charging station. Furthermore, the system periodically updates the electric vehicule reservations to adjust their recharge plans, when they reach their selected earlier station compared to other vehicules requesting new reservations, or they may not arrive as they were forecast, due to traffic jams on the road or certain reluctance on the part of the driver.
Development of vocabulary learning application by using machine learning technique
Authors: Mohd Ariff Brahin Noor , Mohd Nasir Haslinah , Zakwan Jidin Aiman , Faizal Zulkifli Mohd , Sutikno Tole
Published: March 2020

Nowadays an educational mobile application has been widely accepted and opened new windows of opportunity to explore. With its flexibility and practicality, the mobile application can promote learning through playing with an interactive environment especially to the children. This paper describes the development of mobile learning to help children above 4 years old in learning English and Arabic language in a playful and fun way. The application is developed with a combination of Android Studio and the machine learning technique, TensorFlow object detection API in order to predict the output result. Developed application namely “LearnWithIman” has successfully been implemented and the results show the prediction of application is accurate based on the captured image with the list item. The inclusion of the user database for lesson tracking and new lesson will be added for improvement in the future.
Performance evaluation for outdoor wireless scenarios based on IEEE 802.11b/g in the presence of co-channel interference
Authors: Lara-Cueva Roman Alcides , Simba-Herrera Michael Santiago
Published: March 2020

Voice over Internet Protocol (VoIP) has evolved over the years, being a real-time service. VoIP has been coupled to different technologies, one of them is WiFi, which is one of the most used for wireless local area networks in domestic and commercial environments. In this paper, we evaluate the performance of wireless scenarios by considering VoIP traffic, based on WiFi technology in conformance with IEEE 802.11b/g in interfered outdoor scenarios, by considering an intrusive injection traffic technique, for codecs G711 (1 sample), G711 (2 samples), G723, G729 (2 samples), and G729 (3 samples), related to the main metrics associated to Quality of Service (QoS) parameters. Our results show the best performance was obtained with the codecs G723 and G729 (3 samples), obtaining up to 30 simultaneous voice connections with optimal values of delay, jitter and packet loss according to the recommendations given for VoIP by ITU-T, while the worst performance was obtained with the codec G711 (2 samples), obtaining only 5 simultaneous voice connections, reaching an efficiency loss of around 18% in a co-channel interference scenario.
Low power wake-up receiver based on ultrasound communication for wireless sensor network
Authors: Wong Yan Chiew , Tan Szi Hui , Sarban Singh Ranjit Singh , Zhang Haoyu , Syafeeza A. R. , Hamid N. A.
Published: March 2020

Wireless sensor network (WSN) consists of base stations and sensors nodes to monitor physical and environmental conditions. Power consumption is a challenge in WSN due to activities of nodes. High power consumption is required for the main transceiver in WSN to receive communication requests all the time. Hence, a low power wake-up receiver is needed to minimize the power consumption of WSN. In this work, a low power wake-up receiver using ultrasound data communication is designed. Wake-up receiver is used to detect wake-up signal to activate a device in WSN. Functional block modelling of the wake-up receiver is developed in Silterra CMOS 130nm process technology. The performance of the wake-up receiver has been analyzed and achieving low power consumption which is 22.45μW. A prototype to demonstrate a wireless sensor node with wake-up receiver has been developed incorporating both ultrasonic and RF for internal and external communication respectively. We achieve 99.97% of power saving for 10s operation in the experimental setup for the WSN with and without wake-up receiver. Wake-up receiver used in WSN save power and prolong the lifetime of batteries and thus extending the operational lifetime of WSN.
Hybrid medical image compression method using quincunx wavelet and geometric actif contour
Authors: Imane Haouam , Mohammed Beladgham , Ahmed Bouida
Published: March 2020

The purpose of this article is to find an efficient and optimal method of compression by reducing the file size while retaining the information for a good quality processing and to produce credible pathological reports, based on the extraction of the information characteristics contained in medical images. In this article, we proposed a novel medical image compression that combines geometric active contour model and quincunx wavelet transform. In this method it is necessary to localize the region of interest, where we tried to localize all the part that contain the pathological, using the level set for an optimal reduction, then we use the quincunx wavelet coupled with the set partitioning in hierarchical trees (SPIHT) algorithm. After testing several algorithms we noticed that the proposed method gives satisfactory results. The comparison of the experimental results is based on parameters of evaluation.
Camera-projector calibration for near infrared imaging system
Authors: Yakno Marlina , Mohamad-Saleh Junita , Ibrahim Mohd Zamri , Samsudin W. N. A. W.
Published: March 2020

Advanced biomedical engineering technologies are continuously changing the medical practices to improve medical care for patients. Needle insertion navigation during intravenous catheterization process via Near infrared (NIR) and camera-projector is one solution. However, the central point of the problem is the image captured by camera misaligns with the image projected back on the object of interest. This causes the projected image not to be overlaid perfectly in the real-world. In this paper, a camera-projector calibration method is presented. Polynomial algorithm was used to remove the barrel distortion in captured images. Scaling and translation transformations are used to correct the geometric distortions introduced in the image acquisition process. Discrepancies in the captured and projected images are assessed. The accuracy of the image and the projected image is 90.643%. This indicates the feasibility of the captured approach to eliminate discrepancies in the projection and navigation images.
Development of fast and accurate algorithm to extract the five parameters of photovoltaic modules
Authors: Haider Hisham , Masri Syafrudin , H. Y. Saad Abdul-Malik , Bani Ahmad Ashraf , Sutikno Tole
Published: March 2020

The mathematical model of a photovoltaic (PV) cell can help in analyzing the PV system performance easily. In this paper, a new algorithm is developed to determine the values of five parameters model of photovoltaic module. The proposed method which is called Extract the Five Parameters of Photovoltaic Modules (EFPPM) is used to find the optimum values of the I-V equation’s parameters that fit with I-V curve. This method could reduce the computation time of finding the values of PV model parameters. The proposed algorithm does not only reduce the computation time but it provides accurate values of PV model’s parameters, too. A comparison with conventional algorithm shows superiority of the proposed EFPPM in term of computation speed. The results show that the reduction of the computation time can reach nearly twenty one times faster. The results also clarify that the I-V and P-V curves of EFPPM are exactly the same as provided by data sheets.
Compact tri-band T-shaped frequency reconfigurable antenna for cognitive radio applications
Authors: Jabber Abdullah Ali , Thaher Raad H.
Published: March 2020

This paper presents, new compact tri-band and broadband frequency reconfigurable antenna for cognitive radio applications. The proposed antenna consists of an Ultrawideband sensing antenna and reconfigurable communicating antenna at the same substrate. The sensing antenna is a UWB printed elliptical monopole antenna operates at frequency band from 2.72 to 23.8 GHz which can cover the entire UWB frequency band from 3.1 to 10.6 GHz and cover the broadband up to 20 GHz. The communicating antenna is a T-shaped frequency reconfigurable antenna operates on three bands of 7.925 GHz, 13.16 GHz, and 14.48 GHz under (S11≤-10 dB) with a fractional bandwidth of 14.55%, 6.2%, and 3.3% respectively. The proposed antenna used to operate in two modes one for cognitive radio applications to cover WiMAX, land, Fixed and Mobile satellite, Radar, and broadband applications. The frequency reconfigurability is obtained by using only one RF switch (PIN diode) for changing the operating frequency. The antenna overall dimensions are 42x30x1.6 mm3 printed on an FR-4 epoxy substrate with relative dielectric constant εr=4.3, loss tangent tan (δ)=0.002 and 50Ω microstrip line feed. The maximum obtained simulated gain is 8.5 dB at 13.16 GHz. The S11 is under -20 dB and coupling between the two antennas is less than -15 dB at the resonant frequencies.
Cloud-based people counter
Authors: Mahamad Abd Kadir , Saon Sharifah , Hashim Hamimi , Anuaruddin Ahmadon Mohd , Yamaguchi Shingo
Published: March 2020

Emergence of Industry 4.0 in current economic trend promotes the usage of Internet of Things (IoT) in product development. Counting people on streets or at entrances of places is indeed beneficial for security, tracking and marketing purposes. The usage of cameras or closed-circuit television (CCTV) for surveillance purposes has emerged the need of tools for the digital imagery content analysis to improve the system. The purpose of this project is to design a cloud-based people counter using Raspberry Pi embedded system and send the received data to ThingSpeak, IoT platform. The initial stage of the project is simulation and coding development using OpenCV and Python. For the hardware development, a Pi camera is used to capture the video footage and monitor the people movement. Raspberry Pi acts as the microcontroller for the system and process the video to perform people counting. Experiment have been conducted to measure the performance of the system in the actual environment, people counting on saved video footage and visualized the data on ThingSpeak platform.
Design and analysis of current mirror OTA in 45 nm and 90 nm CMOS technology for bio-medical application
Authors: Mohammad Ehsan Aiman Wan Jusoh Wan , Ruslan Siti Hawa
Published: March 2020

This paper proposed a design and performance analysis of current mirror operational transconductance amplifier (OTA) in 45 nm and 90 nm complementary metal oxide semiconductor (CMOS) technology for bio-medical application. Both OTAs were designed and simulated using Synopsys tools and the simulation results were analysed thoroughly. The OTAs were designed to be implemented in bio-potential signals detection system where the input signals were amplified and filtered according to the specifications. From the comparative analysis of both OTAs, the 45 nm OTA managed to produce open loop gain of 45 dB, with common mode rejection ratio (CMRR) of 93.2 dB. The 45 nm OTA produced only 1.113 μV√Hz of input referred noise at 1 Hz. The 45 nm OTA also consumed only 28.21 nW of power from ± 0.5 V supply. The low-power consumption aspect displayed by 45 nm OTA made it suitable to be implemented in bio-medical application such as bio-potential signals detection system where it can be used to amplify and filter the electrocardiogram (ECG) signals.
Malaysian car plate localization using region-based convolutional neural network
Authors: Liang Tay Eng , Sheikh Usman Ullah , Norzali Haji Mohd Mohd
Published: March 2020

Automatic car plate localization and recognition system is a system that identifies the car plate location and recognizes the characters on the car plate input images. Within the automated system, the car plate localization stage is the first stage and is the most crucial stage as the success rate of the whole system depends heavily on it. In this paper, a Malaysian car plate localization system using Region-based Convolutional Neural Network (R-CNN) is proposed. Using transfer learning on the AlexNet CNN, the localization was greatly improved achieving best precision and recall rate of 95.19% and 97.84% respectively. Besides, the proposed R-CNN was able to localize car plates in complex scenarios such as under occlusion.
Spiking neural network classification for spike train analysis of physiotherapy movements
Authors: ‘Atyka Nor Rashid Fadilla , Suriani Nor Surayahani
Published: March 2020

Classifying gesture or movements nowadays become a demanding business as the technologies of sensor rose. This has enchanted many researchers to actively investigated widely within the area of computer vision. Rehabilitation exercises is one of the most popular gestures or movements that being worked by the researchers nowadays. Rehab session usually involves experts that monitored the patients but lacking the experts itself made the session become longer and unproductive. This works adopted a dataset from UI-PRMD that assembled from 10 rehabilitation movements. The data has been encoded into spike trains for spike patterns analysis. Next, we tend to train the spike trains into Spiking Neural Networks and resulting into a promising result. However, in future, this method will be tested with other data to validate the performance, also to enhance the success rate of the accuracy.
A wearable UHF RFID tag antenna-based metamaterial for biomedical applications
Authors: Ennajih Abdelhadi , Nasiri Badr , Zbitou Jamal , Errkik Ahmed , Latrach Mohamed
Published: March 2020

The development of miniature antennas for bio-medical applications has attracted the attention of many researchers in the last years. In this letter, we provide a miniature antenna for the RFID tag for identifying patients in African and European hospitals. The proposed antenna is designed on a flexible silicon substrate with a relative dielectric constant of 11.9 and a thickness of 1.6mm. An in-depth study of the proposed wearable antenna was made in free space and on human tissue. The achieved results showed good performance in terms of miniaturization, bandwidth, impedance matching and, reading distance. The presented tag antenna is designed and simulated by using CST-MWS solver and the results were validated by HFSS and both results are in good agreement.
Design and analysis microstrip antenna with reflector to enhancement gain for wireless communication
Authors: Jassim ِAli Khalid , Thaher Raad H.
Published: March 2020

In this paper is presented the good solution to enhancement gain by using physical plane plate reflector with optimum distance by a reflector was used with the antenna and using a sweep parameter for the distance at which the reflector was placed at (, we found the best distance is when selected the bandwidth is 28GHz where . The gain at the bandwidth in 28GHz was improved from (5.48, 6.78, and 7.83) dB to 11.53 dB, while the gain without a reflector is 7.1 dB. The simulation results were obtained using CST which was more consistent with the practical results.
Implementation of face and eye detection on DM6437 board using simulink model
Authors: Vijayalaxmi B. , Sekaran Kaushik , Neelima N. , Chandana P. , Meqdad Maytham N. , Kadry Seifedine
Published: March 2020

Driver Assistance system is significant in drriver drowsiness to avoid on road accidents.  The aim of this research work is to detect the position of driver’s eye for fatigue estimation. It is not unusual to see vehicles moving around even during the nights. In such circumstances there will be very high probability that a driver gets drowsy which may lead to fatal accidents. Providing a solution to this problem has become a motivating factor for this research, which aims at detecting driver fatigue. This research concentrates on locating the eye region failing which a warning signal is generated so as to alert the driver. In this paper, an efficient algorithm is proposed for detecting the location of an eye, which forms an invaluable insight for driver fatigue detection after the face detection stage. After detecting the eyes, eye tracking for input videos has to be achieved so that the blink rate of eyes can be determined.
Increasing the required slip range of wound induction generator in wind power systems
Authors: Dalabeeh Ali , Anwar Al-Mofleh , Younes Tariq M. , Al-Rawashdeh Ayman , Hindi Ayman
Published: March 2020

Eddy currents losses in the rotor in high power generators do not allow operators, under high values of slip, to regulate voltage and control of reactive power flow. The paper presents a method that can accurately estimate the eddy current losses in electric machines with a less complicated procedure. The suggested method allows researchers to analyze and reduce the losses, and consequently, to improve the wind turbine induction generators efficiencies. The given approach, based on the conventional electric machine theory and the parameters supplied by the manufacturers, predicts the eddy current losses theoretically without the need of the measured material loss data or BH curve. Increasing the range of slip variation of induction motor can be achieved by using a rotor of two layers in the radial direction with different parameters. The first layer is a laminated layer of height (h), and the second is a solid (the rotor yoke). The computation of eddy current losses is useful to change the design of the machine to minimize the losses. This paper presents a detailed modeling of the effect parameters on the eddy current losses in wind turbine induction generator.
A new approach for impedance matching rotman lens using defected ground structure
Authors: Al-Obaidi Mohammed K. , Mohd Ezri , Abdullah Noorsaliza , Dahlan Samsul Haimi
Published: March 2020

Many recent radar applications and smart antenna are based on the electronically steerable beam in order to increase the performance of targeting the desired scan angle with the high performance of gain and directivity. Scanning angle with ±26o based on Microstrip Rotman lens and design frequency 2.45 GHz is presented in this study. Five beam ports provide five output beams directed the beams in five different scanning angles in the azimuth plane is provided. The traditional matching method by tapering the transmission line in order to guarantee a smooth energy transition from the 50 Ω input ports is replaced by Defected Ground Structure to achieve an acceptable return loss with a linear progressive phase for each beam port. The new approach is providing increasing in the scan angle. Besides, the size miniaturization is achieved by removing the tapering length and reduces the total size of the lens length by 23.67 mm. The proposed model is implemented using Computer Simulation Technology (CST) using the FR-4 substrate and the measurements lead to a good validation.
Recognition of brain cancer and cerebrospinal fluid due to the usage of different MRI image by utilizing support vector machine
Authors: Saeed Soobia , Abdullah Afnizanfaizal
Published: March 2020

Medicinal images assume an important part in the diagnosis of tumors as well as Cerebrospinal fluid (CSF) leak. Similarly, MRI could be the cutting-edge regenerative imaging technology that allows for a sectional angle perspective of the body that gives specialists convenience and will inspect the person-concerned. In this paper, the author has attempted the strategy to classify MRI images at the beginning of production to have a tumor or recognition. The study aims to address the aforementioned problems associated with brain cancer with a CSF leak. This research, the author focuses on brain tumor and applies the statistical model for the testing and also discusses the images of a brain tumor. They can judge the tumor region by conducting a comparative image analysis and applying Histogram function afterwards to construct a classifier that could be prepared to predict tumor and non-tumor MRI examinees based on the support vector machine. Our system is capable of detecting the right region that a pathologist also highlights. In the future, this should be more driven with the objective that tumors can be arranged and describe the solution in the medical terms implementation with gives some predictions about the future generated by modified technology.
Effect of DC voltage source on the voltage and current of transmitter and receiver coil of 2.5 kHz wireless power transfer
Authors: H. Butar-Butar A. , Leong J. H. , Irwanto M.
Published: March 2020

A solenoid supplied by alternating current (AC) voltage generates electromagnetic which has a field area depends on the level of supplied voltage and current flows through the solenoid. The electromagnetic filed can be captured by the other solenoid in the field area. This concept can be applied in a wireless power transfer (WPT) as presented in this paper. The WPT has transmitter coil and receiver coil which each has form of solenoid. The transmitter coil is connected a half bridge circuit to generate AC voltage on the transmitter coil which transferred to the receiver coil. In the experimental set up, the receiver coil is supplied by DC voltage source and it is changed to observe its effect on the voltage and current on the transmitter and receiver coil of the WPT system.
Cheap vs healthy: Analyzing McDonald’s menu using linear programming
Authors: Ibrahim Nur Fadhilah , Arunasalan Thurga Dewi , Mohamed Nurul Akmal
Published: March 2020

The factors that influence food choices nowadays are time, cost and deliciousness. An obvious example is fast food. Although consumers are aware that fast food is not a healthy choice, many still chooses fast food because it is convenient. Therefore in this paper, by using linear programming, we analyzed McDonald’s Malaysia menu in order to find the cheapest menu and the ‘healthiest’ menu. We developed a linear programming model for McDonald’s Malaysia menu which adheres to Malaysia Recommended Nutrient Intake 2017 (RNI 2017). Then we solved the model and proposed the cheapest menu and also the ‘healthiest’ menu that meets the nutrient requirement based on RNI 2017. The result showed that price for the cheapest palatable menu is RM21.69 a day. For set menu, we found that no menu meets this requirement, suggesting that McDonald’s set menu should not be taken three times a day. The price for the ‘healthiest’ McDonald’s menu with the least total of fat, sugar and salt that meets the nutrient requirement is RM42.99 a day.