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IEEE International Conference on Semiconductor electronics (ICSE)

作者： Ahmad Muhajer Abdul Aziz Muhammad Idzdihar Idris Zul Atfyi Fauzan Mohammed Napiah Radi Husin Ramlee Muhammad Noorazlan Shah Zainudin Mohd Marzaini Mohd Rashid Mohd Iskandar Dzulkarnain M Rummaja Faculty of Electronic and Computer Technology and Engineering Universiti Teknikal Malaysia Melaka (UTeM) Malaysia Micro and Nano Electronic Research Group (MiNE) Faculty of Electronic and Computer Technology and Engineering Universiti Teknikal Malaysia Melaka (UTeM) Malaysia School of Physics Universiti Sains Malaysia (USM) Malaysia

ISBN: (数字)9798350378313

ISBN: (纸本)9798350378320

The study explores the characterization of electrodeposited Molybdenum Disulfide (MoS2) as a hole transport layer (HTL) in Methylammonium Perovskite Solar Cells. MoS2, a two-dimensional material, is meticulously deposited to ensure uniformity and then optimized to enhance its hole transport capabilities for efficient charge extraction. Comprehensive characterization techniques, including photovoltaic measurements, impedance spectroscopy, and morphology studies, evaluate the impact of MoS2 on the performance of Methylammonium Perovskite Solar Cells. The findings suggest that electrodeposited MoS2 exhibits promising potential as a high-performance HTL, offering insights into improving the efficiency and stability of Methylammonium Perovskite Solar Cells. This study contributes to advancing the understanding and development of efficient and stable solar cell technologies through the integration of MoS2 as a hole transport layer in Methylammonium Perovskite Solar Cells.

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Survey of Micro Fluidic Phased Array Antenna for Beam Steering Techniques

Survey of Micro Fluidic Phased Array Antenna for Beam Steeri...

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2022 International Conference on Intelligent technology, System and Service for Internet of Everything, ITSS-IoE 2022

作者： Osman, Shakib Abdulahi Abdullah, Qazwan Shah, Nor Shahida Mohd Koylu, Fehim Ali, Ahmed O. Hassan, Mohamud M. Hamzah, Shipun Hassan, Abdikarim Abi Osman, Abdirisak Ali Universiti Tun Hussein Onn Malaysia Faculty of Electrical and Electronic Engineering Johor Malaysia Community College of Yareem Ibb Yemen Universiti Tun Hussein Malaysia Faculty of Engineering Technology Johor Pagoh Muar Malaysia Erciyes University Faculty of Computer Engineering Kayseri Turkey Zamzam University Faculty of Computer Information and Engineering Technology Mogadishu Somalia Simad University Faculty of Engineering Mogadishu Somalia

ISBN: (数字)9781665459983

ISBN: (纸本)9781665459983

A spatially adaptable radio wire cluster (SAA) is an exhibit that can vary the actual field's actual area. Ability to expand connect limit without employing an expanded boundary or many receive antenna components. This study presents a thorough examination of current microfluidic over 5G technologies and strategies. In this composition, a new RF feed arrangement is shown, along with the first SAA trial check that makes use of microfluidic-based reconfiguration. This study presents a thorough examination of current microfluidic over 5G technologies and strategies. The investigation's goal was to create a component fix reception antenna using water-based fluidic stage shifters, where the pillar directing could be controlled by filling a few water channels for each antenna, and other approaches were put out by various researchers. These techniques have been broken down into categories that are easy to understand, such as the use of creating a stage Shifter and combining an array with a phase shifter. In each meeting, a limited number of excellent articles were examined and evaluated for idea confirmation. Finally, a comparison of various approaches was made. © 2022 IEEE.

关键词： Microfluidics

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Ontology-Based Crime News Semantic Retrieval System

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computers, Materials & Continua 2023年第10期77卷 601-614页

作者： Fiaz Majeed Afzaal Ahmad Muhammad Awais Hassan Muhammad Shafiq Jin-Ghoo Choi Habib Hamam Department of Information Technology University of GujratGujrat50700Pakistan Department of Computer Science University of Engineering&TechnologyLahore54890Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea Faculty of Engineering Uni de MonctonMonctonNB E1A3E9Canada International Institute of Technology and Management Commune d’AkandaBPLibreville1989Gabon School of Electrical Engineering Department of Electrical and Electronic Engineering ScienceUniversity of JohannesburgJohannesburg2006South Africa Spectrum of Knowledge Production&Skills Development Sfax3027Tunisia

Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular *** news exists on the Internet in unstructured formats such as books,websites,documents,and *** such homogeneous data,it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement ***-based Information Retrieval(IR)systems rely on statistics to retrieve results,making it difficult to obtain relevant *** are unable to understandthe user’s query and thus facewordmismatchesdue to context changes andthe inevitable semanticsof a given ***,such datasets need to be organized in a structured configuration,with the goal of efficiently manipulating the data while respecting the semantics of the *** ontological semantic IR systemis needed that can find the right investigative information and find important clues to solve criminal *** semantic system retrieves information in view of the similarity of the semantics among indexed data and user *** this paper,we develop anontology-based semantic IRsystemthat leverages the latest semantic technologies including resource description framework(RDF),semantic protocol and RDF query language(SPARQL),semantic web rule language(SWRL),and web ontology language(OWL).We have conducted two *** the first experiment,we implemented a keyword-based textual IR systemusing Apache *** the second experiment,we implemented a semantic systemthat uses ontology to store the data and retrieve precise results with high accuracy using SPARQL *** keyword-based system has filtered results with 51%accuracy,while the semantic system has filtered results with 95%accuracy,leading to significant improvements in the field and opening up new horizons for researchers.

关键词： Web 3.0 crime ontology semantic web knowledge representation

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Smart Happy Device with IoT : For those who suffer anxiety, stress, and depression 12

Smart Happy Device with IoT : For those who suffer anxiety, ...

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12th IEEE Region 10 Humanitarian technology Conference, R10-HTC 2024

作者： Yakub, Fitri Azizan, Azizul Dhamanti, Inge Khudzari, Ahmad Zahran Md. Govindan, Niranjana Muljono, Muljono UTM Malaysia-Japan International Institute of Technology Electronic System Engineering Department Kuala Lumpur Malaysia Universiti Teknologi Malaysia Cyberphysical Research Group Embedded AI & ML Science Lab Faculty of Artificial Intelligence Kuala Lumpur Malaysia Universitas Airlangga Faculty of Public Health Department of Health Policy and Administration Surabaya Indonesia UTM Faculty of Engineering Department of Biosciences & Medical Engineering Johor Bahru Malaysia SRMIST Faculty of Engineering & Technology Department of Computing Technologies Chennai India Universitas Dian Nuswantoro Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9798350340204

Due to the rising cases of Covid-19 in the world especially in Malaysia, the impact had been hit hard for many people. Due to this all people must be isolated in their home. It has affected the well-being and working life of millions of people across the world. Due to this disease, the mental health among people has increased significantly for the past 2 years. According to MoH, out of 983 Malaysian students, about 20.4%, 6.6%, and 2.8% are experienced minimal to moderate, marked to severe, and most extreme levels of anxiety, respectively. The main stressors are the remote online teaching, and uncertainty about the future regarding study and career which can affect mental health. Thus, the main objective of this project is to develop a product that may provide different medication methods to its users by helping people who suffer anxiety, stress, and depression. We used aromatherapy, positive quotes, and music therapy in order to release stress. The user can also check his or her pulse rate by only touching the fingerprint through the sensor. The microcontrollers used in this project are Arduino Uno and Arduino Mega to build the project circuit. The experimental results can improve body health, mind and spirit which enhances both physical and emotional health. © 2024 IEEE.

关键词： COVID-19

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A Novel Attention-based Explainable Deep Learning Framework Towards Medical Image Classification 7

A Novel Attention-based Explainable Deep Learning Framework ...

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7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023

作者： Muoka, Gladys W. Yi, Ding Ukwuoma, Chiagoziem Chima Martin, Moindi Duke Aydin, Ahmet Arif Al-Antari, Mugahed A. University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China Chengdu University of Technology Sichuan College of Nuclear Technology and Automation Engineering Chengdu China Unicaf University Lilongwe Department of Computer Science Lilongwe Malawi Inönü University Faculty of Engineering Department of Computer Engineering Turkey Sejong University College of Software & Convergence Technology Daeyang AI Center Department of Artificial Intelligence Seoul Korea Republic of

ISBN: (纸本)9798350383065

Deep learning applications for medical image classification have shown remarkable promise, particularly incorporating attention-based neural networks. This is particularly relevant in medical imaging, where the integration of Artificial Intelligence assists with various imaging tasks, including classification, segmentation, and detection. Deep learning is revolutionizing medical research and playing a significant role in advancing personalized clinical treatment. However, the lack of interpretability in these models presents a significant obstacle to their adoption in clinical practice. Therefore, there is a growing need for a comprehensive understanding of artificial intelligence systems and their internal mechanisms, capabilities, and limitations, which is the focus of the field of explainable AI. This study proposes a novel attention-based explainable deep learning framework for medical image classification tasks, including Covid-19, breast cancer (BreakHis), lung cancer (LC2500), and Retinal optical coherence tomography (OCT). The proposed framework recorded overall accuracies of 98% (Covid-19 Radiography), 95% (BreakHis), 99.8% (LC2500), and 95%(OCT). For visual analysis of the outcomes, we employ and use the LIME, SHAP, and ELI-5 to analyze the achieved results. The study's primary goal is to bridge the gap between the high performance achieved by attention-based models and the necessity for transparency and interpretability in medical image diagnostics. © 2023 IEEE.

关键词： Optical tomography

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Deep automatic segmentation of brain tumours in interventional ultrasound data

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Current Directions in Biomedical engineering 2022年第1期8卷 133-137页

作者： Zeineldin, Ramy A. Pollok, Alex Mangliers, Tim Karar, Mohamed E. Mathis-Ullrich, Franziska Burgert, Oliver Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany Research Group Computer Assisted Medicine Reutlingen University Reutlingen Germany Faculty of Electronic Engineering (FEE) Menoufia University Menouf Egypt

Intraoperative imaging can assist neurosurgeons to define brain tumours and other surrounding brain structures. Interventional ultrasound (iUS) is a convenient modality with fast scan times. However, iUS data may suffer from noise and artefacts which limit their interpretation during brain surgery. In this work, we use two deep learning networks, namely UNet and TransUNet, to make automatic and accurate segmentation of the brain tumour in iUS data. Experiments were conducted on a dataset of 27 iUS volumes. The outcomes show that using a transformer with UNet is advantageous providing an efficient segmentation modelling long-range dependencies between each iUS image. In particular, the enhanced TransUNet was able to predict cavity segmentation in iUS data with an inference rate of more than 125 FPS. These promising results suggest that deep learning networks can be successfully deployed to assist neurosurgeons in the operating room. © 2022 by Walter de Gruyter Berlin/Boston.

关键词： Ultrasonics

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Online Learning Behavior Analysis and Prediction Based on Spiking Neural Networks

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Journal of Social Computing 2024年第2期5卷 180-193页

作者： Yanjing Li Xiaowei Wang Fukun Chen Bingxu Zhao Qiang Fu the Institute of Education Science Research Heilongjiang UniversityHarbin 150080China the School of Cyberspace Security Shandong University of Political Science and LawJinan 250014China the School of Computer Science and Technology Harbin Engineering UniversityHarbin 150001China the Faculty of Electrical and Computer Engineering University of VictoriaVictoriaV8P 5C2Canada. the Guangxi Key Lab of Brain-Inspired Computing and Intelligent Chips School of Electronic and Information EngineeringGuangxi Normal UniversityGuilin 541004China

The vast amount of data generated by large-scale open online course platforms provide a solid foundation for the analysis of learning behavior in the field of *** study utilizes the historical and final learning behavior data of over 300000 learners from 17 courses offered on the edX platform by Harvard University and the Massachusetts Institute of technology during the 2012-2013 academic *** have developed a spike neural network to predict learning outcomes,and analyzed the correlation between learning behavior and outcomes,aiming to identify key learning behaviors that significantly impact these *** goal is to monitor learning progress,provide targeted references for evaluating and improving learning effectiveness,and implement intervention measures *** results demonstrate that the prediction model based on online learning behavior using spiking neural network achieves an impressive accuracy of 99.80%.The learning behaviors that predominantly affect learning effectiveness are found to be students’academic performance and level of participation.

关键词： online learning learning outcomes prediction learning behavior analysis spiking neural network

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Development of an Open-Source and Low-Cost Robotic Arm based on STM32 Microcontroller for Promoting STEM Education

Development of an Open-Source and Low-Cost Robotic Arm based...

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2023 IEEE Symposium on computers and Informatics, ISCI 2023

作者： Asri, Fatin Atirah Mohd Ayob, Mohammad Afif Rohaziat, Nurasyeera Rahman, Hisyam Abdul Rahman, Khairul Azlan A. Ayob, Mohd Erdi Universiti Tun Hussein Onn Malaysia Faculty of Electrical and Electronic Engineering Batu Pahat Parit Raja86400 Malaysia Uow Malaysia Kdu University College School of Engineering Selangor Shah Alam40150 Malaysia Faculty of Electronics and Computer Technology and Engineering Melaka Durian Tunggal76100 Malaysia

ISBN: (纸本)9798350302363

As a key component of Industry 4.0, robotics is acquiring traction in classrooms around the world. Robotics initiatives may stimulate students' interest in STEM (Science, technology, engineering, and Mathematics) subjects. Therefore, it is essential to translate theoretical information into tangible prototypes and study robotics using physical models. Most schools cannot afford to provide students with sufficient opportunities to work with robots due to the expense of robotics. This study aims to promote STEM education by describing the development of a free, open-source robot joint with three degrees of freedom (DOF). The control algorithm for a 3D-printed MK2 robot arm was programmed with an STM32 microcontroller. The robot has a servo-powered arm that has a gripper on the end-effector. A joystick can be used to control the movement of any mechanical joint. The forward kinematic has also been constructed and validated in a simulation-based environment in MATLAB and SolidWorks. The developed kinematics algorithm showed precise Denavit-Hartenberg (DH) characteristics with high accuracy with the worst-case scenario for the kinematic computation error contributes to only 0.26% or 0.0702mm of the end-effector position. © 2023 IEEE.

关键词： Kinematics

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A new dataset and systematic evaluation of deep learning models for student activity recognition from classroom videos

A new dataset and systematic evaluation of deep learning mod...

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2022 International Conference on Multimedia Analysis and Pattern Recognition, MAPR 2022

作者： Nguyen, Phuong-Dung Nguyen, Hong-Quan Nguyen, Thuy-Binh Le, Thi-Lan Tran, Thanh-Hai Vu, Hai Huu, Quynh Nguyen Hanoi University of Science and Technology School of Electrical and Electronic Engineering Hanoi Viet Nam Viet-Hung Industrial University Faculty of Information Technology Hanoi Viet Nam University of Transport and Communications Faculty of Electrical-Electronic Engineering Hanoi Viet Nam Thuyloi University Faculty of Computer Science and Engineering Hanoi Viet Nam

ISBN: (数字)9781665474108

ISBN: (纸本)9781665474108

Student activity, a non-verbal modality, is an important cue to imply the students' learning state and engagement level during class. Quantitative observation of the student activities will contribute to innovating teaching methods. However, traditional methods that rely on manual observation are time-consuming. Nowadays, surveillance cameras have been widely deployed in the classroom. This results in a massive amount of classroom videos. However, the exploitation of these videos is limited due to the lack of annotated information. This paper has two main contributions. First, a fully annotated dataset dedicated to student activity analysis has been proposed. To this end, five activities in the classroom context including sitting, standing, sleeping, raising-hand and using-phone have been defined and collected in different class sessions. Second, three deep learning models have been fully assessed for the activities recognition. © 2022 IEEE.

关键词： Object detection

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A New Perspective on Time and Gravity

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Journal of High Energy Physics, Gravitation and Cosmology 2024年第1期10卷 346-362页

作者： Ittipat Roopkom Wirote Jongchanachavawat Chermdhong Prattanaruk Kwanchai Nanan Pichet Wisartpong Thawatchai Mayteevarunyoo Paramote Wardkein Faculty of Engineering and Industrial Technology Phetchaburi Rajabhat University Phetchaburi Thailand School of Electrical and Electronic Engineering Mahanakorn University of Technology Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering Naresuan University Phitsanulok Thailand Department of Telecommunications Engineering School of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

This paper presents a hypothesis regarding the existence of time fused in spacetime, assuming that time possesses the properties of both a particle and a field. This duality is referred to as the field-particle of time (FPT). The analysis shows that when the FPT moves through matter, it causes time dilation. The FPT is also a significant element that appears in relativistic kinetic energy (KE = (γ - 1) · mc²). Accelerating matter to near the speed of light requires relativistic energy approaching infinity, which corresponds to the relativistic kinetic energy. Meanwhile, the potential energy (PE = mc²) from the rest mass remains constant. Then, the mass-energy equation can be rearranged in terms of PE and KE, as shown in E = (1 + (γ - 1)) · mc². The relativistic energy of the FPT also directly affects the gravitational attraction of matter. It transfers energy to each other through spacetime. The analysis demonstrates that the gravitational force is inversely proportional to the distance squared, following Newton’s law of gravity, and it varies with the relative velocity of matter. The relationship equation between relative time and the gravitational constant indicates that a higher intensity of the gravitational field leads to a slower reference time for matter, in accordance with the general theory of relativity. A thought experiment presents a comparison of two atomic clocks placed in different locations. The first one is placed in a room temperature, around 25°C, on the surface of the Earth, and the second one is placed in high-density areas. The analysis, considering the presence of the FPT, shows that the reference time slows down in high-density areas. Therefore, the second clock must be noticeably slower than the first one, indicating the existence of the FPT passing through both atomic clocks at different speeds.

关键词： Field-Particle of Time (FPT) Reference Time Relativistic Mass and Energy of FPT Gravity

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