Rateb Katmah, Fares Al-Shargie, U. Tariq, F. Babiloni, Fadwa Al-Mughairbi, H. Al-Nashash
{"title":"Mental Stress Analysis using the Power Spectrum of fNIRS Signals","authors":"Rateb Katmah, Fares Al-Shargie, U. Tariq, F. Babiloni, Fadwa Al-Mughairbi, H. Al-Nashash","doi":"10.1109/ICECTA57148.2022.9990237","DOIUrl":"https://doi.org/10.1109/ICECTA57148.2022.9990237","url":null,"abstract":"Mental stress is one of the major health problems in modern societies. Detecting mental stress at its early stage and developing a method of stress mitigation is very important for safety, health and quality of life. In this study, we employed a modified Stroop Color Word Task (SCWT) with time constrains and negative feedback about the performance, together with Binaural Beats Stimulation (BBs), to induce three varied levels of mental stress. Level one was based on SCWT alone and level two was based on SCWT+time-pressure and level three was by utilizing SCWT+time-pressure+BBs. We then quantified the level of stress using a NASA TLX questionnaire and functional near-infrared spectroscopy (fNIRS). The fNIRS signals were then analyzed using the Welch power spectrum density (PSD) to investigate the discrepancy in brain activity across the three levels of mental stress. We found that the mean PSD value in the frequency range of 0.2 to 0.5 Hz has significantly changed between the three stress levels. These findings indicate that the fNIRS power spectrum analysis method could be used as a robust marker for mental stress.","PeriodicalId":337798,"journal":{"name":"2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114282466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Basem Yousef, Ibrahim Chekfeh, Mohammed Hallalo, Mohammed Al Darmaki, Mohamad Kharseh, K. Al-Aribe
{"title":"Portable Coordinate Measuring Machine","authors":"Basem Yousef, Ibrahim Chekfeh, Mohammed Hallalo, Mohammed Al Darmaki, Mohamad Kharseh, K. Al-Aribe","doi":"10.1109/ICECTA57148.2022.9990333","DOIUrl":"https://doi.org/10.1109/ICECTA57148.2022.9990333","url":null,"abstract":"Many industrial and medical applications necessitate knowing or tracking, instantaneously, the position and orientation of objects relative to a known reference with high accuracy. Also quick setup time and calibration is always desired if the information is needed for real-time on-site application. Available coordinate measuring machines and surface profilers lack for orientation tracking, and available orientation trackers adopt techniques that lose accuracy or may need time consuming and difficult calibration procedures. In this project, a portable pre-calibrated mechanical device for position and orientation tracking in 3D space is designed and constructed. The device provided easy-to-use portable tool for on-site usage. Accuracy test showed that it can operate within ± 0.35 mm and ± 3° linear and angular accuracies respectively, and can be used for acquiring geometrical information such as length, surface orientation and distance between planes.","PeriodicalId":337798,"journal":{"name":"2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115156096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improved Boost Converter by Utilizing Sliding Mode Control; Comparative Study","authors":"H. Attia","doi":"10.1109/ICECTA57148.2022.9990353","DOIUrl":"https://doi.org/10.1109/ICECTA57148.2022.9990353","url":null,"abstract":"This study presents detailed designs for components of a boost converter, and parameters of a flexible sliding mode controller suitable for the boost converter applications. The converter performance is evaluated in a comparative way in terms of removing the overshoot and the oscillations in the load voltage during a sequence of reference voltages at fixed resistive load. The converter response is observed, firstly, using the equivalent duty cycles to produce the same sequence of reference voltages. Then, the converter response is observed after inserting the designed SM controller. The output voltage of the converter is monitored during tracking the desired reference voltage before and after inserting the controller. This study demonstrates a high priority of the boost converter effectiveness after involving the SM controller to the system. MATLAB/Simulink software is adopted to simulate the presented design and to observe the system performance to confirm the improving converter performance in terms of removing the overshoot and oscillation from load voltage during tracking the reference voltages.","PeriodicalId":337798,"journal":{"name":"2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130299393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maitha Alhammadi, Bara'Ah Othman, Sara Rashid Bani Rasheed, T. Bonny, Wafaa Al Nassan, K. Obaideen
{"title":"Cursor Control Using electroencephalogram (EEG) Technology","authors":"Maitha Alhammadi, Bara'Ah Othman, Sara Rashid Bani Rasheed, T. Bonny, Wafaa Al Nassan, K. Obaideen","doi":"10.1109/ICECTA57148.2022.9990531","DOIUrl":"https://doi.org/10.1109/ICECTA57148.2022.9990531","url":null,"abstract":"This paper aims to design an electroencephalogram (EEG)-based cursor control system that can control the computer cursor using non-invasive measurements of brain activity. The developed system is a user-friendly system that can be used by the general public, and it will mostly be convenient for people with disabilities. Moreover, the people living with upper limb paralysis will be able to control the cursor using their brain signals only. In order to develop the system, an enhancement of hardware and software was applied. The sensors were used to acquire the brain signals in real-time. These acquired signals were utilized to permit the user to move the cursor using their thoughts. Additionally, the system was able to translate the collected signals and program them into commands to control the cursor. Furthermore, the software is implemented using open-source tools to preprocess raw EEG signals, apply feature extraction, and classification.","PeriodicalId":337798,"journal":{"name":"2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125580071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anas AlMajali, Ahmad Qaffaf, Natali Alkayid, Y. Wadhawan
{"title":"Crypto-Ransomware Detection Using Selective Hashing","authors":"Anas AlMajali, Ahmad Qaffaf, Natali Alkayid, Y. Wadhawan","doi":"10.1109/ICECTA57148.2022.9990424","DOIUrl":"https://doi.org/10.1109/ICECTA57148.2022.9990424","url":null,"abstract":"Ransomware is a malicious software that attempts to encrypt the user’s files and demand a ransom in exchange for decrypting the files. This malware may have catastrophic impacts on the availability of data and consequently on the services provided by the infected organizations and institutes. Ransomware detection has been a challenge for researchers in the past few years. In this paper, we propose a behavioral ransomware detection method that utilizes fast selective hashing techniques. By selective we mean that only few selected blocks from a file are used for similarity comparison. Our experimental results demonstrate the efficacy of the proposed method in ransonware detection in terms of detection time. For 1000 files of a total size of 20GB and a detection threshold set to five files, our proposed system is able to detect a ransomware on average within 2.76 seconds saving 99.5% of the total files without taking much of the system resources and affecting user experience.","PeriodicalId":337798,"journal":{"name":"2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131586442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. F. Abdul Hadi, H. Hussin, M. Muhamad, Y. A. Wahab
{"title":"Study and Analysis on CNTFET Design and Process Parameters for Performance Optimization","authors":"M. F. Abdul Hadi, H. Hussin, M. Muhamad, Y. A. Wahab","doi":"10.1109/ICECTA57148.2022.9990357","DOIUrl":"https://doi.org/10.1109/ICECTA57148.2022.9990357","url":null,"abstract":"Carbon Nanotube Field Effect Transistor (CNTFET) technology is one of the favorable devices to replace MOSFET technology. A lot of research has been done to further enhance the CNTFET performance. This paper studies the implementation of Taguchi method to further optimize CNTFET design parameters. In this research, the HSPICE simulator is used to simulate the Stanford University CNFET model. The factors involved in the design of experiment include the diameter of CNT, oxide thickness and the dielectric constant. By using Taguchi method, the optimum combination of the three-design parameter is 1.0nm of CNT, 1.0 nm of oxide layer and Zirconium Dioxide (25) as the dielectric material. The optimum CNTFET design manages to produce the highest current ratio (Ion/Ioff. The ANOVA analysis is used to evaluate the percentage of each design parameter that affects the current ratio of the CNTFET. The result shows that the diameter of CNT had a significant effect towards the current ratio of 87.24%. The optimized CNTFET is applied to an inverter circuit to study the circuit performance in terms of propagation delay, power consumption and Power-Delay Product (PDP). From the study, the optimized CNTFET inverter had a better performance in term of PDP with $4.1984 text{x}10^{-18}text{J}$ compared to unoptimized CNTFET inverter design.","PeriodicalId":337798,"journal":{"name":"2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131367480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Feedback Linearizing Speed Control Strategy for Electric Vehicle Traction Motor drives","authors":"A. Prasanthi, H. Shareef, R. Errouissi, M. Asna","doi":"10.1109/ICECTA57148.2022.9990368","DOIUrl":"https://doi.org/10.1109/ICECTA57148.2022.9990368","url":null,"abstract":"Electric vehicles (EV) are the solution that can provide a sustainable transportation alternative to reduce carbon footprints. The design of a battery-powered DC traction motor system for an electric vehicle is presented in this study. The proposed EV system consists of a battery energy source, bidirectional DC-DC converter, and traction motor. The accurate mathematical modelling of the PI-controlled bi-directional DC-DC converter is incorporated in this work to provide the desired voltage at the motor side and to maintain the power flow under steady-state and dynamic conditions. In view of the demand of explicit speed control attribute of the EV and non-linear characteristics of traction motor with overall system unpredictable disturbances, this paper also illustrates the design and modelling of feedback linearizing control with disturbance observer for the speed control of traction motor. The MATLAB/Simulink simulation model of the proposed system is developed to examine the performance of the proposed system under various operating conditions. The simulation is performed with calculated load torque with the exact velocity and acceleration rate at the traction motor which represents the exact EV dynamics. The simulation results indicate that the designed battery-powered EV with the proposed non-linear controller can follow the speed and load torque thoroughly.","PeriodicalId":337798,"journal":{"name":"2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","volume":"402 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132033603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rayan Ajeeb, M. Madi, Olav Aaker, Efstratios Ntantis, Mahmood Sawadi Rahi
{"title":"Analytical Study of the Application of the Amorphous Core Material 2605HB1M to Reduce Core Loss in Electromagnetic Induction Motors","authors":"Rayan Ajeeb, M. Madi, Olav Aaker, Efstratios Ntantis, Mahmood Sawadi Rahi","doi":"10.1109/ICECTA57148.2022.9990362","DOIUrl":"https://doi.org/10.1109/ICECTA57148.2022.9990362","url":null,"abstract":"Due to their durable and simple manufacturing, three-phase electromagnetic induction motors presently provide even more than 90% of the mechanical power for use in industry. Many researchers have used artificial intelligence (AI) approaches to optimize electromagnetic induction motor design (TDO) and analyze performance. There are numerous methods for increasing efficiency and decreasing losses in these devices. Electromagnetic iron losses, that originate mostly within stator teeth and yoke along with the rotor yoke, are a critical element. For the convenience of modeling, electromagnetic iron losses are investigated on a 3-phase transformer rather than an electromagnetic induction motor since they both operate on electromagnetic induction and their core losses follow the same fundamental principles. This evaluation was carried out utilizing finite element methodologies with Ansys electronics desktop. A developed computational transformer model that delivers reliable data with high accuracy was proposed. The performance of the computational model was determined to match well with experimental data for a transformer with the same specifications and dimensions found in the labs of Østfold University-Collage Norway. Using the achieved computational model configuration on the Ansys electronics desktop, the core loss and efficiency of an electromagnetic induction transformer for Metglas-2605HBIM amorphous core transformer and M19 silicon steel core transformer at high and low frequencies were then examined and compared. According to the results, when used in electromagnetic induction transformers, amorphous core transformers have lower core losses, higher efficiency, and superior performance than traditional M19 silicon steel core transformers.","PeriodicalId":337798,"journal":{"name":"2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","volume":"337 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132572564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the Design of Broadband Doherty Power Amplifier for 5G Applications","authors":"A. Jarndal, K. Husna Hamza","doi":"10.1109/ICECTA57148.2022.9990305","DOIUrl":"https://doi.org/10.1109/ICECTA57148.2022.9990305","url":null,"abstract":"The design and analysis of GaN HEMT Doherty power amplifier (DPA) is done for 5G application. Different methods are investigated for overcoming the bandwidth limiting property of the DPA. The first technique used is the addition of low pass filter at the output terminal of both the carrier and peaking amplifier. The second technique is the addition of shunt short circuit stub each at the output terminal of carrier and peaking amplifier. And the third technique is to add two sections of transmission lines at the output terminal of peaking amplifier. These three circuit configurations were simulated in Keysight Advanced Design System software using the GaN HEMT Cree model CGH40006P as the carrier and peaking amplifiers. The performances were compared with the conventional DPA at 6 GHz frequency. The DPA with the two sections of transmission line at the output of the peaking amplifier exhibited the 3 dB bandwidth of 2 GHz. Besides the results were evaluated considering the state of the art of GaN DPAs for 5G applications.","PeriodicalId":337798,"journal":{"name":"2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122370403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Machine Learning Algorithms for Early Prediction of Diabetes: A Mini-Review","authors":"Rouaa Alzoubi, S. Harous","doi":"10.1109/ICECTA57148.2022.9990240","DOIUrl":"https://doi.org/10.1109/ICECTA57148.2022.9990240","url":null,"abstract":"Diabetes is a chronic disease caused by increased blood glucose levels. Several physical and chemical tests can be used to diagnose this disease. Untreated and undiagnosed diabetes, on the other hand, can harm human organs such as the eye, heart, kidneys, and nerves and may even lead to death. As a result, early detection and analysis of diabetes can help reduce the death rate. Machine learning and deep learning models have been used recently in many medical fields, and their efficiency for the early diagnosis of different diseases has been noticed. This study aims to discuss the different state-of-the-art algorithms that researchers have implemented for the early prediction of diabetes. The work focuses on highlighting different techniques used in the literature and the effectiveness of those techniques, which can help in knowing the current limitations of the work and making more improvements to it. As a result, our research showed that the random forest and KNN algorithms outperformed other algorithms in the literature with an accuracy of 98% in the early prediction of diabetes.","PeriodicalId":337798,"journal":{"name":"2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126167788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}