bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling and Simulation for Integrating Four Reactors in the Continuous Catalytic Regeneration Reforming Process Using MATLAB
Authors: Babaqi Badiea S. , Takriff Mohd S. , Othman Nur Tantiyani A. , Abu Hasan Hassimi , Mahmoudi Ebrahim
Published: July 2021

Modeling and simulation were developed of the continuous catalytic regeneration reforming process for integrating four reactors and studying the effecting operating parameters to improve the process performance. The process model included four reactors as stack and used to investigate the profiles of reformate composition products and research octane number. The main reactions that occur in reforming reactors included five reactions namely; dehydrogenation, dehydrocyclization, isomerization, hydrocracking and hydrodealkylation. The kinetic and thermodynamic parameters were estimated by the particle swarm optimization approach to monitor the process behavior. The expected results have been validated of the model simulation with comparison to data of actual plant, and average absolute deviation (AAD%) of two parameters; reformate composition and octane number reached 0.04% and 1.3%, respectively. This evaluation was a fair agreement and within the acceptable limit.
Planning, Design and Simulation of a Network Access Based on FTTH-EPON for Hadhramout University
Authors: Bakarman H A , Alsaqaf A , Ba’afiah M , Baqhoom F , Baraja M
Published: July 2021

In our country copper infrastructure from Central Office (CO) to the end user is responsible for delivering poor Broadband services with loss reach 86% of the overall capacity speed. Not to mention the high prices and the impact of this inferior service to the education and economy of the country. Therefore, This paper presents a procedural proposal solution for planning, design and simulation of Ethernet Passive Optical Network (EPON) performance through Fiber-to-the-Home (FTTH) technology applied on College Of Engineering and Petroleum campus at Hadhramout University as it the best way to overcome all the problems related with copper. Since the fiber terminates at the campus, we termed the network, Fiber To The Campus (FTTCampus). FTTCampus planning the location network was developed through Google Earth and AUTOCAD software which was implemented to map out the college location areas. The proposed optical network system design has been simulated based on EPON IEEE 802.3ah standards through Optisystem software program. Simulation network components such as optical transmitters, Optical network terminals (ONTs), and optical splitters among others were allocated at different coverage areas and various network links were connected among these coverage areas. A downstream network of EPON has been simulated using Continuous Wave Laser (CW Laser) and Directed-modulated Laser (DM Laser) as different optical. Validation was performed with consistent output performance indicators like quality factor, optical source power (dBm) and bit error rate (BER). This paper has a main objective in designing an affordable and feasible network and it is accomplished by utilizing EPON that merges the low-cost Ethernet technology and low-cost PON structure with the DM Laser as an optical source. This unique work revealed that, FTTCampus could be a reliable technology in an educational academic institution, if implemented.
Hand Gesture to Control a Low Cost 3-D Printed Arm using Android Application
Authors: Mohd Noor Nurul Muthmainnah binti , Musrijan Mohd Muzammel bin
Published: July 2021

In this era, the technology on computer usage is highly increasing and demanding especially in engineering, business and communication sector. Many applications are built based on a smartphone technology. The idea of this paper is to develop a hand gesture system based on Android application in order to control the 3-D printed arm. A MIT application invertor was used in developing an algorithm of the hand gesture controller. The app inventor can be used and accessed with accelerometer sensor that already built-in the smartphone via a Bluetooth connection. The Android applications was used as a communication tool between the Arduino Uno and the 3-D printed arm. The accelerometer sensor was acted as an input signal to control the hand gesture of the 3-D printed arm by the change or tilt of smartphones position. The output of this system is a servo motor that was mounted on the arm and used to drive the fingers. In this project, there system was classified by two; hardware part that consists of 3D-printed arm, Arduino, electrical component, and smartphone, meanwhile, the software part consists of MIT application inverter. The result shows the 3-D printed arm was able to be implemented with the wireless and Android application.
A New Filtering Algorithm for Generating Path Loss Model to Improve Accuracy of Trilateration-Based Indoor Positioning System
Authors: Susanto L , Wibisono W , Ahmad T
Published: July 2021

Global Positioning System (GPS) is used to determine someone’s or something’s position. It is very accurate. But, GPS cannot be used in an indoor environment as its signal is blocked by an object (i.e. roof). To overcome this problem, Indoor Positioning System (IPS) is used in the indoor environment. There are two methods that IPS can use to determine the position. The first method is pattern matching. This method is highly accurate. But, the computation cost is expensive. The second method is the path loss model. Its computation cost is cheap. However, it is fairly accurate. In this paper, a new filter algorithm is proposed to improve path loss model accuracy. The algorithm works by filtering the received signal strength index (RSSI) in the training phase. The algorithm works by replacing the RSSI value at a certain distance by considering the current and the previous RSSI value. The experiment result shows that the proposed method has 3% better accuracy than the existing method.
Malware Detection Using Machine Learning Algorithms Based on Hardware Performance Counters: Analysis and Simulation
Authors: Bawazeer Omar , Helmy Tarek , Al-hadhrami Suheer
Published: July 2021

In the last decade, Hardware Performance Counters (HPCs) events are increasingly used by Machine Learning (ML) algorithms for malware detection. Modern processors provide a variety of HPCs to measure and monitor processes’ events such as memory accesses, instructions, etc. during their execution. In this paper, an analysis study to categorize the machine learning algorithms based on HPCs that have been used for malware detection is introduced. Besides, the most efficient and effective features of HPCs that have been exploited to recognize the abnormal activities on various systems are identified. Furthermore, the Neural Network (NN) algorithms including Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), and Full Order Radial Basis Function (RBF) algorithms are used to simulate several experiments from the literature. The simulation results show that the accuracy of MLP, CNN, and Full Order RBF are 96.95%, 98.22%, and 98.68%, respectively.
Design of Reconfigurable Antenna for RFID System
Authors: Sivakumar Renukka , Sabapathy Thennarasan , Jusoh Muzammil , Soh Ping Jack , Osman Mohamed Nasrun , Salem Al-Bawri Samir , Jayaprakasam Suhanya , Mohd Yasin Mohd Najib , Saluja Nitin
Published: July 2021

This paper proposes a reconfigurable antenna for RFID system which can operate between 860MHz to 960MHz frequency that belongs to ultra-high frequency (UHF) band used in Malaysia with the center frequency of 910MHz. One rectangular slot and two triangle-shaped slots are used in designing this antenna. A good circular polarization obtained from the slotted structure along the diagonal axis in the design. RF pin diodes are used as the switching mechanism of the antenna. However, in this work to proof the concept of switching mechanism, copper pins are used as artificial switches. Parasitic elements are deployed on the right and left side of the driven element to assist the radiation pattern reconfiguration. Overall, the proposed antenna able to steer the beam at approximately at -30°, -16°, and 10° with peak gain of 3.2dB and average gain of 2.5dB. With this result, overall coverage of UHF RFID reader antenna could be improved.
Effect of Sodium Hydroxide on Mechanical Characteristics of Kenaf Fibers Reinforced Concrete
Authors: Baarimah A O , Syed Mohsin S M , Alaloul W S , Ba-naimoon M S
Published: July 2021

This article shows the experimental analysis of sodium hydroxide (NaOH) effects on the mechanical properties upon the addition of kenaf fibres to the concrete mixture. The compression and flexural tests were carried out on seven different concrete mixtures for 28 days to evaluate the mechanical characteristics. Hence, the experimental trials comprise of seven different mixtures of concrete; the control (without the addition of kenaf fibre) was represented as the first mixture. The following six concrete mixtures contain different kenaf fibre volume fractions (1% and 2%); they were treated with 1%, 3% and 6% of sodium hydroxide concentrations in order to investigate their performances. The experimental results show that the compressive and flexural strengths of kenaf fibres reinforced concrete increase as sodium hydroxide concentration increases. Besides, it is worth noting that the addition of kenaf fibres has an insignificant effect on the compressive strength of the concrete owing to the reduction in concrete density. Therefore, the results of this study demonstrated that the concrete flexural strength increased to up to 12%) upon the addition of 1% kenaf fibre associated with 6% NaOH. Moreover, the failure state increasingly changed to ductile from brittle.
Threat Assessment Model in Electrical Power Grid Environment
Authors: Qassim Qais Saif , Jamil Norziana , Mahdi Mohammed Najah , Rahim Fiza Abd , Cob Zaihisma Che , Sidek Lariyah Mohd
Published: July 2021

At the heart of every critical national infrastructure, there is a SCADA system. The wide range of supported applications has made this life-saving management system the key element of every industrial control infrastructure in various sectors. The complexity and sophistication of SCADA systems have been increased dramatically over the last few years. Various cyberattacks have targeted these systems by exploiting zero-day vulnerabilities or targeting a nearby Internet-enabled appliance or computer system. To this end, many efforts have been proposed previously to model the threats on SCADA systems to eliminate potential danger and diminish the catastrophic consequences in the physical domain. The main contribution of this work is to present a multi-facets threat assessment model to aid security teams to systematically perform various cybersecurity analysis practices such as penetration testing, vulnerability assessment and risk analysis.
Selective Harmonic Elimination of Five Level Cascaded H-Bridge Inverter Using the Newton-Raphson Technique
Authors: Saifizi M. , Kasdi N. S. , Rahim H. A. , Mashagba H. A. , Mustafa Wan Azani , Aihsan M. Z. , Sulong Syahmi M. M.
Published: July 2021

Multilevel inverter becomes an alternative for high power and medium voltage applications recently and is more popular in renewable energy. The cascaded H-bridge multilevel inverter is more suitable for the Photovoltaic application because it acts as a separate DC source for each bridge. This paper presents a selective harmonic elimination (SHE) modulation for single-phase cascaded H-bridge (CHB) five level inverter. The optimum angle of the transcendental equations is solved the fundamental and harmonic elements using the Newton-Raphson (NR) process. The proposed selective harmonic elimination (SHE) scheme is tested using MATLAB/Simulink simulation. These simulation results are then verified through experiment using microcontroller. The proposed SHE is efficient in eliminating the 5th order harmonics and producing a higher quality output waveform with a better harmonic profile.
Plant Diseases Classification using Machine Learning
Authors: Xian Tan Soo , Ngadiran Ruzelita
Published: July 2021

Plant diseases are one of source of obstruction in the quality and productivity of plants which can lead to the shortage of food supply. Therefore, plant disease classification is essential to the agriculture industry. The objective of this research is to classify the plant diseases by assessing the images of the leaves with the application of Extreme Learning Machine (ELM), a Machine Learning classification algorithm with a single layer feed-forward neural network. This work proposed image features as input where the image is pre-processed via HSV colour space and features extraction via Haralick textures. The features are then fitted in the ELM classifier to perform the model training and testing. The accuracy of ELM is then calculated after the testing has been done. The dataset used comprises of tomato plant leaves which is a subset of the Plant-Village dataset. The results produced from the ELM shows a better accuracy that is 84.94% when compared to other models such as the Support Vector Machine and Decision Tree.
Water Pipeline Leakage Monitoring System based on Internet of Things
Authors: Che N N , Omar K N F , Azir Ku , Kamarudzaman M F
Published: July 2021

Water leakage detection of pipeline in the resident household is important to ensure that water supply networks can operate effectively. This paper presents an experimental investigation and prototype of a water pipeline leakage monitoring system based on a low-cost microcontroller, Arduino, with three types of sensors. The system will monitor the turbidity of the water before pump the water into water tank of household. Then, later if there any leakages, a notification will be given to the user either through SMS or Telegram notification. These leakages are being detected using water flow and water sensors. A simple mobile application has been designed to monitor the condition of water pipeline remotely and allowed user to remotely call the repairing services if the leakage happened when there are no one at home. Simulation analysis and experimental results indicate that the proposed leakage identification method can effectively identify water pipeline leakage and has lower consumption than other methods.
An Artificial Intelligent Approach for Black Oil PVT Properties
Authors: Abedelrigeeb Al-Gathe , El-Banbi Ahmed , Abdel Fattah Kh. A. , El-Metwally K. A.
Published: July 2021

In absence of experimental oil fluid samples, it is usually difficult to select the suitable correlation to estimate oil properties. However, the accuracy of these empirical correlations has become insufficient for the best calculation. The main objective of this work is to test the capability of Particle Swarm Optimization with Neural Network (PSONN) and Neuro-Fuzzy (NFuzzy) approaches to predict oil properties with simply and accurately. The proposed approaches are developed based on clustering the oil data into the three groups (light, medium and heavy light oil). Over five hundred of black oil samples were collected from Middle East Field to train the hybrid models whereas additional oil data samples were selected to validate. The developed models used to estimate bubble points pressure (Pb), solution gas oil ratio at and below Pb, undersaturated oil compressibility, saturated formation volume factor, saturated and undersaturated density. The recommended guidelines and optimal configuration of the PSONN and NFuzzy models are developed to estimate any oil property in future. Statistical error analyses show that the proposed models exhibit a robust predictive capability for estimating oil properties. The validation results show the PSONN model achieve the lowest average absolute percent relative error (0.04, 2.89 and 1.0) for estimating formation volume factor, gas oil ratio and oil compressibility respectively whereas the NFuzzy model obtains the best approximation in oil density and bubble point pressure with average absolute percent relative error (0.18 and 0.97) respectively.
Development of E-Healthcare Management System using PHP, Javascript and Cascading Style Sheets
Authors: Vijayasarveswari V. , Chyin Lim Jia , Wafi N. M. , Iszaidy I.
Published: July 2021

It is a responsibility for higher authorities in a government/private institute to provide an essential health care service to all their own community. The current health management is quite tedious and unpractical by using manual methods in order to get an appointment from doctor. Furthermore, the current situation, Covid-19 is spreading throughout Malaysia and it is very risky for direct doctor visit. This paper is mainly focused on developing an E-healthcare management system for government/private institute to make doctor appointment online. The used programming developing tools are CSS, PHP, Javascript and Cascading Style Sheets (CSS). Patients may log in to make appointment with the doctor with its specialized. All the appointment details is processed and directly sent to the centralized database system. Then doctors confirm the appointment through their web page. Finally, patients receive an alert from doctor after the confirmation. E-Healthcare Management system is successfully developed to cater all the needs in appointments and organizing the records. In addition, current patients’ data and appointment can be retrieved just in a click of second.
MOVE Mobility Model in GreedLea Routing Protocol for Internet of Vehicle (IoV) Network
Authors: Omar Normaliza , Yaakob Naimah , Elshaikh Mohamed , Husin Zulkifli
Published: July 2021

Internet of Vehicles (IoV) is a broad variety of mobile transmission purposes for file sharing [l]-[5]. There are still debates on the viability of purposes using end to end multi-hop communication, since the significant number of high mobility nodes involved in the networks. The main issue is the efficiency of IoV routing protocols in cities and highways can meet the ideal delay and throughput for such purposes. In particular, it is not usually a challenge to locate a node to hold a message in urban daytime situations, where vehicles are tightly packed. Since fewer number of vehicles are running in highway scenarios and cities at night, and it might not be possible to set up end-to-end roads. In general, each protocol offered a performance evaluation in contradiction of some other protocols, giving considerable importance to a detailed performance evaluation of each protocol type. After such an assessment, it was found that geocast routing would perform best in urban areas. GreedLea routing protocol is develop to overcome the current routing protocol drawback. The development of GreedLea routing protocol involved Greedy Perimeter Stateless Routing (GPSR) and reinforcement learning method in order to deliver better performance compared to current existing routing protocol. Urban environments without obstacles has been simulated using actual maps for example intersection density. In order to measure efficiency, the metrics are: average delivery rate, average delay, average length of path and overhead. From the analysis, it shows that GreedLea offers better performance compared to GPSR for both city and highway scenario. The first section in your paper
A Literature Survey on Cloud-RAN Architecture toward 5G Green Wireless Communication Systems
Authors: Saad N S , Ariffin W N S F W , Nordin J , Zain A S M , Asri L I M
Published: July 2021

Cell network architectures confront enormous challenges due to the unusual rise in mobile data traffic usage, thus reducing spectrum accessibility and heavy power consumption. Research communities are looking for breakthroughs in the development of advanced infrastructure networks to meet increased consumer demand and, at the same time, to reduce network operators’ capital and operational costs. Cloud Radio Access Network (Cloud-RAN) architecture is a recently proposed solution for wireless networks and is considered a strong candidate for potential 5G cellular coverage worldwide. This paper presents a literature survey on Cloud-RAN architectures toward Green 5G wireless communication systems and highlights Cloud-RAN benefits and limitations. Furthermore, this paper discusses Cloud-RAN’s potential enhancement techniques, including robust beamforming, multiple-input-multiple-output (MIMO) with non-orthogonal multiple access (NOMA) cooperative scheme, massive MIMO, mmWave communication, clustering techniques, coalition formation, energy harvesting and reinforcement learning output.
Broadband Sub-6GHz Slot-based MIMO Antenna for 5G NR Bands Mobile Applications
Authors: Al-Bawri Samir Salem , Islam Mohammad Tariqul , Singh Mandeep Jit , Alyan Emad , Jusoh Muzammil , Sabapathy Thennarasan , Padmanathan Surentiran , Hossain Kabir
Published: July 2021

A slot-based broadband single and MIMO antennas for 5G New Radio (5G NR) mobile applications are presented in this paper. The proposed MIMO antenna is investigated by loading two antennas into a low-cost material with the partial ground for sub-6GHz. Each antenna element is consisted of a hexagonal-shaped slot and is composed of a 50Ω microstrip feed line. The WLAN 5-GHz band and 5G NR Bands n77/n78/n79 are covered with good impedance matching. Besides, the mutual coupling between the adjacent elements is less than 15-dB whereas the desired antenna elements gains are 3.19 dBi and 3.09 dBi at 3.5 GHz 4.2 GHz respectively.
Emotion Recognition Using Convolutional Neural Network (CNN)
Authors: Badrulhisham Nur Alia Syahirah , Mangshor Nur Nabilah Abu
Published: July 2021

Emotion is an expression that human use in expressing their feelings. It can be express through facial expression, body language and voice tone. Humans’ facial expression is a major way in conveying emotion since it is the most powerful, natural and universal signal to express humans’ emotion condition. However, humans’ facial expression has similar patterns, and it is very confusing in recognizing the expression using naked eye. For instance, afraid and surprised is very similar to one another. Thus, this will lead to confusion in determining the facial expression. Hence, this study aims to develop a mobile based application for emotion recognition that can recognize emotion based on facial expression in real-time. The Deep Learning based technique, Convolutional Neural Network (CNN) is implemented in this study. The MobileNet algorithm is deployed to train the model for recognition. There are four types of facial expressions to be recognized which are happy, sad, surprise, and disgusting. As the result, this study obtained 85% recognition accuracy. In the future, the developed application could be improved by adding more face expression categories.
Acne Type Recognition for Mobile-Based Application Using YOLO
Authors: Isa Nur Ashiqin Mat , Mangshor Nur Nabilah Abu
Published: July 2021

Acne is a chronic skin condition that happens to most teenagers at the age of 12 and 25. Several types of acne are found as non-inflammatory and inflammatory skin disease. As the number of people facing acne problems increasing and there is the need to have an automated application for recognizing acne, this study proposed a mobile-based application that able to recognizes acne types. This study used the Deep Learning technology method, YOLOv4 in detecting and recognizing acne. There are four types of acne covered in this study which are cyst, papule, pustule, and whitehead. The dataset used for the purpose of training and testing the model is from the DermNet NZ dataset. Based on the testing conducted, the application achieved 91.25% average of accuracy. It is believe, the integration of YOLO with any existing Deep Learning approach could improve the recognition rate in future.
Dual Monopole Frequency Reconfigurable Antenna for MIMO 5G sub-6 GHz Mobile Terminal
Authors: Padmanathan Surentiran , Al-Hadi Azremi Abdullah , Soh Ping Jack , Al-Bawri Samir Salem
Published: July 2021

In this paper, a Dual Monopole Frequency Reconfigurable Antenna (DMFRA) for two port Multiple Input Multiple Output (MIMO) Fifth Generation (5G) sub-6 GHz mobile terminal is presented. A combination of dual monopole strips is implemented at a port, respectively to achieve tunable and fixed resonant frequencies. Varactor diode is utilized in this design to perform the frequency reconfiguration. Dual tunable resonant frequencies at the lower band (1690 MHz to 2200 MHz) and higher band (4400 MHz to 5400 MHz) are created by the monopole branch which accommodates the varactor diode. On the other hand, a fixed frequency band at 2400 MHz with -10 dB bandwidth of 450 MHz is achieved by another monopole branch without variable diode. Maximum realized gain achieved at both lower and higher reconfigurable frequency bands and fixed frequency band are 2.73 dB, 3.8 dB and 2.57 dB, respectively. Besides that, high isolation between 2 DMFRAs decreases the mutual coupling to result in less than 0.1 of the Envelope Correlation Coefficient (ECC). In addition to its frequency reconfiguration capability and low ECC, the proposed MIMO antenna is considered suitable for potential 5G mobile terminal applications.
Adopting Ant Colony Optimization Algorithm for Pairwise T-Way Test Suite Generation Strategy
Authors: Ramli Nuraminah , Othman Rozmie Razif , Hendradi Rimuljo , Fauzi Shukor Sanim Mohd , Ismail Iszaidy , Ahmad Mohd Zamri Zahir , Nasrudin Mohd Wafi
Published: July 2021

Combinatorial testing or t-way testing (t represents strength) is useful to detect faults due to interactions. Pairwise testing is one type of t-way testing. The technique is effective in reducing the number of test cases without decreasing the level of coverage. Besides, its purpose is to overcome the problem of exhaustive testing that produces a great number of test cases and is impossible to be implemented due to time and cost constraints. Pairwise T-way Test Suite Generation Strategy based on Ant Colony Optimization (pTTSGA) is introduced to generate a near-optimum test suite size. Experiments have been conducted to evaluate the ability of this strategy for pairwise testing. The results are compared to benchmark results. Overall, pTTSGA produces a comparable test suite size.
Zigzag low-complexity approximate DCT using frequency upscaling technique
Authors: Huang Junqi , Kumar T Nandha , Abbas Haider
Published: July 2021

Approximate computing is widely used in image processing field for reducing the energy dissipation, increasing the throughput, and decreasing the amount of computation by sacrificing some accuracy in the output results. Thus, this paper presents a runtime-based approximate computing approach by using frequency upscaling (FUS) technique into zigzag low-complexity approximate DCT (ZLCADCT). The presented technique allows to change the degree of approximation without changing the circuit of ZLCADCT while providing increased throughput by applying the input vectors of circuits at a rate beyond the maximum operating frequency. The results show that when FUS are implemented into ZLCADCT, approximate full adder can sustain significant higher input frequency (around 19.2GHZ using 32nm adders) when compared with an exact full adder (at around 15.4GHZ) without having significant decreases in PSNR value. The number of completed DCT operations for ZLCADCT (2.95 to 3.53 for approximate full adder at 16.6GHZ) is higher than 2.3 to 2.77 for ADCT by using FUS technique.
IoT-Based Automated and Contactless Shopping Cart During Pandemic Diseases Outbreak
Authors: Faang Ho Yun , Yaakob Naimah , Elshaikh Mohamed Elobaid , Sidek Azami Khairul , Lynn Ong Bi , Almashor Mahathir
Published: July 2021

Coronavirus (COVID-19) is an alarming disease outbreak that has affected more than 180 countries worldwide. It has caused close to 2.5 million deaths and has infected 114 million of the global population as of February 2021. This unprecedented pandemic, has caused severe socio-economic problems globally, catching many sectors off-guard and in a state of suspended uncertainty. While vaccines are just starting to circulate, there is still a need to practice new social norms, including social distancing during daily activities such as supermarket shopping. As such, contactless technology is critically needed and preferable to minimize physical contact and mitigate virus spread. In this paper, an automated shopping cart is proposed as a potential solution to avoid item scanning at cashiers and long queues at payment counters. This innovation leads to reduced risk of exposure to COVID-19. This is done by integrating a typical shopping trolley with Internet of Things (IoT) technology. A radio frequency identification (RFID) tag is attached to every product and automatically read whenever they are placed in a shopping cart. Payment and weighing processes can be conducted at the trolley itself which reduces direct and prolonged contact with both cashiers and other patrons, and at both checkout queues and weighing counters. This proves to be a critical way to break transmission chains.
Class Attendance System Using Viola-Jones Algorithm and Principal Component Analysis
Authors: Yaakub Nur Dini Ayuni , Nasrudin Mohd Wafi , Veeraperumal Vijayasarveswari , Ismail Iszaidy , Yob Rashidah Che , Zhe Leow Wai , Mustafa Wan Azani
Published: July 2021

Face recognition is one of the numerous biometrics approaches that can be implemented by smart and automated attendance management systems. The individual identity can be determined by the unique representation of the face structure of each individual face and it cannot be lost, stolen, or reproduced in the same way as other types of identification. Thus, this work is motivated to propose a class attendance system based on face recognition. With current approaches such as passwords, access cards, and identification numbers, face recognition can be used to prevent theft and fraud which can significantly reduce the chances of system hacking. In this proposed work, initially, video framing has been implemented by activating the Universal Serial Bus (USB) camera through a user-friendly interface which was created with Graphical user interfaces (GUI) in the MATLAB software. The image of each student’s face that was snapped by using the USB camera will be stored in a dataset. The dataset then will be divided into the training set and testing set. In the detection process, the Viola-Jones algorithm is utilized to detect and segment the image of student’s face from the video frame. Next, the scaling of the size of the images is carried out to prevent the loss of information in the pre-processing phase. Then, the Principal Component Analysis (PCA) is utilized in the face recognition process in order to extract the features from facial images.
A Comparative Study of Ring Oscillator PUFs Implementation on Different FPGA Families
Authors: Mustapa Muslim , Niamat Mohammed
Published: July 2021

Physical Unclonable Function (PUF) is an irreversible function that utilizes the process variation which occurs during silicon chip fabrication. The process variation is uncontrollable; thus, it cannot be modeled and is unique for each chip. Ring Oscillator PUF (ROPUF) has been used in the past to enhance the physical security of FPGAs by generating unique IDs which exploit the process variation introduced during the manufacturing process of the FPGA. In this paper, we describe the implementation and analysis of ROPUF on two different Xilinx FPGA families using 28 nm (Artix-7) and 90 nm (Spartan 3E) technologies. In each case, the ROPUF design is evaluated in terms of five parameters, namely, uniqueness, reliability, uniformity, bit aliasing, and diverseness. The reliability is measured based on responses generated from ROPUF at various temperature and voltage settings. The accelerated aging experiment results are also presented in the reliability evaluation. Our results show that the Artix-7 family yields the best results for uniqueness (45.15%) and diverseness (3.88). Based on the experimental results obtained, we suggest the scheme to increase the ROPUF’s reliability on both Spartan 3E and Artix-7 FPGAs by selecting ROs comparison pairs that have high frequency difference. We showed that the ROPUFs security is not been compromised by applying the scheme.
Mobile Green E-Waste Management Systems using IoT for Smart Campus
Authors: Rani K. N. A. , Rahim H.A. , Ong B. T. , Jusoh M. , Yasin M. N. M. , Sabapathy T. , Mustafa W. A. , Jamlos M.A. , Ahmad R. B. , Hammood D. A.
Published: July 2021

This paper presents the design and development of mobile “green” electronic waste (e-waste) management systems using Internet of Things (IoT) for smart campus. The system uses Raspberry Pi 3 Model B v1.2 microcontroller for monitoring e-waste object detection, e-waste count, and bin percentage level, respectively. TensorFlow Lite application programming interface (API) is used to run Single Shot Multibox Detector (SSD)Lite-MobileNet-v2 model trained on Microsoft Common Objects in Context (MSCOCO) dataset for e-waste object detection in image. All the monitoring data are stored and retrieved in ThingSpeak cloud platform using Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT) protocol over the Internet and displayed via interactive Android-based mobile user interface (UI). Furthermore, automatic e-mail notification will be sent to waste collector for bin collection whenever e-waste bin percentage level is greater than predetermined threshold value of 80% full.
Using Unmanned Aerial Vehicle in 3D Modelling of UniCITI Campus to Estimate Building Size
Authors: Saifizi M. , Syahirah N. , Mustafa Wan Azani , Rahim Hasliza A , Nasrudin Mohd Wafi
Published: July 2021

The drone mapping has a huge potential for numerous sectors including construction, agriculture, mining, infrastructure inspection and real estate. Drones are used as assisting tools in civil applications for large-scale aerial mapping of buildings, which is a difficult task for surveyors to do because of the unreachable access area, time consuming, and expensive due to limited resources and equipment. To address this issue, this paper introduces UAV-based mapping. Furthermore, when flying from a different flight plan, the UAV will capture and collect visual images. Then, the image from drone was process in Agisoft Metashape software to generate a 3D model of building. This process will go through several steps to analyze which method for capturing images can produce high-quality 3D mapping. The research results of this project are to determine which photogrammetry technique can generate a high quality of 3D mapping with accurate and fast.
RGB Image Encryption using Hill Algorithm and Chaos System
Authors: Ibada Ali Jawad , Ehkan Phaklen , Ngadiran Ruzelita , Hammood Dalal Abdulmohsin , Alkhayyat Ahmed
Published: July 2021

The development of modern technology in recent years, makes the data security very big issue. To secure our data from unauthorized person, encryption is used before transmission. Various sensitive information is using encryption such as: e-mail messages, banking transactions, credit information and military operations. The encrypted data can be in form of text, image, voice, and video. In this paper, a proposed Hill algorithm with chaos system is used to encrypt colour RGB (Red, Green and Blue) image. The key of Hill algorithm is a square matrix. The selection of matrix key numbers is very important. Therefore, chaos system is used to generate sequences of numbers for Hill key matrix. These sequences have a property of randomness that make it very difficult for guessing. Finally, the proposed system is simulated using MATLAB, and a test image is encrypted and decrypted using proposed system successfully.
Design of Internet of Things Based Air Pollution Monitoring System Using ThingSpeak and Blynk Application
Authors: Murad S. A. Z. , Bakar F.A. , Azizan A. , Shukri M.A.M
Published: July 2021

This paper presents the design of an IoT based air pollution monitoring system to measure carbon dioxide gas, butane gas, humidity and temperature. The hardware consists of MQ-2 gas sensor, ESP8266 Wi-Fi module, DHT22 temperature and humidity sensors. Meanwhile, the software used in this prototype is the Arduino Integrated Development Environment (IDE) written in function C and C++. The monitoring system indicate air quality is below than 100 AQI for safety air quality and more than 200 AQI for hazardous air quality. The green LED illuminated indicates there is no hazardous gas detected. Meantime, when the butane gas or carbon dioxide gas is identified, the red LED is illuminated. All the data are sent through ThingSpeak and Blynk applications. In ThingSpeak and Blynk applications, the data are displayed and updated after detected by the sensors in every 15 seconds and 1 second. In the Blynk application, when the hazardous gas is detected, the Blynk application sends a notification to alert the users immediately.
Implementation of the Friis Free Space Propagation Model in the Dynamic Source Routing (DSR) Routing Protocol in the Vehicular Ad-hoc Network (VANET) with Variations of Road Models
Authors: Nurwarsito H , Aziz A R
Published: July 2021

The use of VANET technology is to create better traffic management. Different road conditions and high mobility of vehicles cause problems in VANET such as efficient search processes, network routes that need to be maintained, and data transmission problems. DSR (Dynamic Source Routing) predefines and generates routes on demand and is designed to work on multihop ad-hoc networks without centralized control. The Friis Free Space propagation model is used to model the Line of Sight (LOS) that occurs in a free space environment. The variation of road models in Indonesia is grouped into four groups, namely express roads, intercity roads, urban roads, and residential roads. In each of these road models, simulation testing is carried out based on different vehicle number scenarios. Network Simulator v3.27 (NS-3.27) and SUMO as a mobility generator were used for the simulation. The parameters of average throughput, packet delivery ratio and MAC/PHY overhead sequentially measure the DSR performance. The results on the express roads with Friis Free Space propagation produce values of 6.52 KBps, 7.71%, 39.59 KBytes. Test results on intercity roads 5.72 KBps, 11.17%, 5.48 KBytes. Test results on urban roads 16.50 KBps, 32.22%, 0.0016 KBytes. While the test results on residential roads were 12.66 KBps, 24.72%, 0.779 KBytes. The test results show that the road model in Indonesia with the performance of the DSR routing protocol with Friis Free Space propagation on the VANET network from the best to the worst, respectively, is the urban road model, residential road model, intercity road model, and express road model.
AR Heart: A Development of Healthcare Informative Application using Augmented Reality
Authors: Romli Rusnida , Wazir Fatin Nur Hazwani Binti Mohd , Singh Amar Raaj Singh A/L Gurdial
Published: July 2021

The utilization of Augmented Reality (AR) in industrial transformation is very well aligned with the fourth industrial revolution’s values. AR innovation can improve the perceptual knowledge of humans and enable us to communicate with a large amount of data. Therefore, this project takes the opportunity to create an AR healthcare app related to the human heart. The scopes are focusing on the human heart and provide information about the heart to the public besides improving their knowledge. Society nowadays is less concerned about heart health. There is a lot of information about the heart in newspapers, televisions and social media but most of the public still ignore it. Therefore, the information needs to deliver attractively. AR technology will be one of the interesting ways to spread information. The main goal is to provide information about the human heart in an AR environment. The other goals are to provide exposure for the users on how the insides of the human heart work and to make the users familiarize themselves with AR technologies. By using Unity and Vuforia Software Development Kit (SDK), this application lets users easily scan the provided marker anywhere and anytime using their smartphone to see the virtual heart.
Metal-Ferroelectric-Metal Characterization for Optical Modulator
Authors: Razilam N. A. , Juhari Nurjuliana , Poopalan P.
Published: July 2021

Thermal annealing was performed on fused silica substrate for metal-ferroelectric-metal (MFM) at 900°C for 2 hours by sol-gel coated of BaTiO3as ferroelectric material and e-beam evaporation of ITO as electrode. Standard optical and physical characterization were performed such as XRD, UV-VIS Spectrophotometer, AFM and Hall measurement for electrical properties. XRD patterns of thin films shows that the samples is crystalline in a cubic structure. Optical analysis showed high transparency at 400-800nm which is >80% transmission while the low resistivity for ITO ∼ 10-3.
Characterization of Fuzzy Soft Tri-α-open set In Fuzzy Soft Tri-topological Spaces
Authors: Hassan Asmhan F. , Farhan Azhaar A.
Published: July 2021

In this paper, we investigate the properties of Fuzzy Soft Tri-α-open set (or Fuzzy Soft τ1τ2τ3-α-open set) in a Fuzzy Soft Tri-topological spaces, A detailed study is carried out on properties of Fuzzy Soft Tri-α-interior, Fuzzy Soft Tri-α-closure of Fuzzy Soft sets and Fuzzy Soft Tri-α-neighborhood of a Fuzzy Soft point which are fundamental for further research on the theory of Fuzzy Soft Tri-topological spaces (w.r.t. Fuzzy Soft Tri-α-open set).

General Terms

2010 AMS Classification: 54A05, 54A10, 54E55, 54E99.
Enhanced Optical Characteristics and Low Energy Gap of SrTiO3 Doped Polymeric Blend for Optoelectronics Devices
Authors: Hadi Abeer Ghalib , Al-Ramadhan Zainab , Hashim Ahmed
Published: July 2021

Films of PVA/PAA/SrTiO3 nanostructures were prepared for flexible optoelectronic devices. Studying the optical characteristics of PVA/PAA/SrTiO3 films were tested. The results showed the improving of the optical characteristics of (PVA/PAA) mixtures by the increase in SrTiO3 NPs content. Also, results showed the energy gap of PVA/PAA mixtures decreased from to with adding of SrTiO3 NPs. Finally, the results indicated to the PVA/PAA/SrTiO3 nanostructures may be used in various optoelectronic devices.
Improving the Optical Properties of PVA/PEG Blend Doped with BaTiO3 NPs
Authors: Mohammed Batool , Ahmed Hind , Hashim Ahmed
Published: July 2021

In this paper, synthesis in PVA/PEG/BaTiO3 new nanocomposites was investigated to use in various optoelectronics fields. The PVA/PEG/BaTiO3 nanostructures prepared from PVA/PEG blend with various ratios of BaTiO3 NPs. The optical characteristics of synthesized PVA/PEG/BaTiO3 nanostructures have studied. Results indicated that the optical characteristics of PVA/PEG improved as BaTiO3 NPs ratio increase, this behavior makes it may be used in different electronics and photonics fields.
Synthesis of ZnO: Sb thin films Dropped on glass and Porous Silicon for CO Gas Sensing
Authors: Jabbar Rashid Hashim , Jabbar Shurooq Jasim , Shakir Warqa Adnan , Abdulsattar Mudar Ahmed , Hilal Israa Hadi
Published: July 2021

Membranes Structural properties have been studied using XRD and compare the different values of the average crystallite size by using correction equations. undoped ZnO and ZnO: Sb for (0.5- 2) % membranes has been dropped on glass and p-type porous silicon (PS) substrate at 400 °C to use it as a sensor for CO gas. The crystal growth of the films that were deposited on the PS was not uniform due to the nature of the PS surface and due to the breakage of the crystal structure of the membrane material. the sensitivity of membranes dropped on (PS) for CO gas was higher than on glass substrate.
Controllable synthesization of Au nanoparticles by laser enhanced wet KOH etching process
Authors: Alwan Alwan M , Youssef Ali A. , Chasb Aseel A.
Published: July 2021

In Si substrate, anisotropic KOH etchants are mainly utilized to form pyramids like on the Si surface . However, this process is not well controlled way owing to the different and random etching pathway. In this work, we applied laser radiation during the anisotropic KOH wet etching process to modifies the topographical properties of Si substrate, as an efficient,simple and low cost texturing process for Si substrate. This approach employs different laser wavelength to modify the topographical features from a crater like structures to Si nanocrystallites in the form of pillars like structures on the Si surface. In order to investigate the formation of plasmonics species, gold nanoparticles was incorporated into Si surfaces by simple ion reduction process. The Si topographical features was studied with atomic scanning microscopy (AFM) images of Si before and after laser irradiation process. The irradiation with 405 laser wavelength, show the formation of thin and high density of Si nano pillars-like structures compared with more thick depther Si nano pillars like structures layer.
DFT/TD-DFT Study of Donorπ-Acceptor Organic Dye models contained Triarylamine for an Efficient Dye-Sensitized Solar Cell
Authors: Kzar Al-Masoodi Khulood Obaid , Rafiq I. , Assyry A. El , Derouiche A.
Published: July 2021

A systematic theoretical study was performed for dipolar triarylamine-based Dπ-A dyes. These dyes are composed of good required features to be active for enhancing the efficiency of solar cell such as arylamine donor moieties, and an acceptor part with cyanoacetic acid, while the conjugation process is adopted by the fluorene or biphenyl linkers. The required properties both electronic and opticals were computed with DFT/TDDFT levels and 6-31G (d, p) basis set, then show the response of the efficiency. The obtained results have predicted the excitation energies, HOMO-LUMO energy levels which indicate an improvement in the two principle processes; electron injection and the regeneration of dyes. Also, the important factors in close connection with the short-circuit current density (Jsc), such as light-harvesting efficiency (LHE), the open-circuit photovoltage (Voc), total reorganization energy (λtotal) and injection driving force (ΔGinject) have been explained. As a result, the calculated data verify that the D dye can represent a potential sensitizer for solar cells, this can be rationalized by its reasonable photovoltaic parameters with other electronic and optical properties.
Study for Food Recognition System Using Deep Learning
Authors: Salim Nareen O. M. , Zeebaree Subhi R.M. , Sadeeq Mohammed A. M. , Radie A. H. , Shukur Hanan M. , Rashid Zryan Najat
Published: July 2021

Accurate dietary appraisal has been found by literature to be very significant in the evaluation of weight loss treatments. Most current methods of dietary evaluation, however, depend on recollection. The development of a modern computer-based food recognition system for reliable food evaluation is now possible across comprehensive mobile devices as well as rich Cloud services. Fixing the problem of food detection and identification in photos of different kinds of foods. Given the variety of food products with low inter-and high intra-class variations and the limited information in a single picture, the problem is complicated. By propose the overall application of multiple fusion-trained classifiers to achieve increased identification and recognition capabilities on characteristics obtained from various deep models. This paper studied various techniques of food recognition using different approaches and based on several variables, compared their effectiveness. Our study results demonstrate that deep learning overcomes other strategies like manual feature extractors, standard ML algorithms, as well as DL as a practical tool for food hygiene and safety inspections.
A new method using the Forward Backward technique with Contra Harmonic mean formula
Authors: Jasim Mahmood D.
Published: July 2021

We introduce a new method for solving Initial Value Problems (IVPs) in Ordinary Differential Equations (ODEs), by making a mixing between the Forward (Predictor) – Backward (Corrector) technique and used it in the Contra Harmonic mean formula, this new method give us a parallelism in numerical calculations and it is more accurate than the old classical Runge – Kutta formula of the same order.