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Impact on mental health due to COVID-19 pandemic: A cross-sectional study in Bangladesh

Clinical eHealth 2023年第1期6卷 42-52页

作者： Pathan, Refat Khan Biswas, Munmun Yasmin, Suraiya Uddin, Mohammad Amaz Das, Anindya Khandaker, Mayeen Uddin Faruque, M.R.I. Sarker, Moniruzzaman Dept. of Computing and Information Systems School of Engineering and Technology Sunway University Selangor Bandar Sunway 47500 Malaysia Dept. of Computer Science and Engineering BGC Trust University Bangladesh Chittagong 4381 Bangladesh Department of Computer and Information Science Tokyo University of Agriculture and Technology Koganei - 184-0012 Tokyo Japan Dept. of Computer Science and Engineering Chittagong University of Engineering and Technology Chittagong 4349 Bangladesh Dept. of Electrical and Electronic Engineering Chittagong University of Engineering and Technology Chittagong 4349 Bangladesh Center for Applied Physics and Radiation Technologies School of Engineering and Technology Sunway University Selangor Bandar Sunway 47500 Malaysia Space Science Centre Universiti Kebangsaan Malaysia 43600 UKM Selangor Bangi Malaysia Department of Marketing Sunway University Business School Sunway University Selangor Bandar Sunway 47500 Malaysia Faculty of Graduate Studies Daffodil International University Daffodil Smart City Birulia Savar Dhaka – 1216 Bangladesh

The government of Bangladesh has implemented the “Stay Home” policy following the WHO recommendation to resist the community transmission of Covid-19. As a result, the routine activities of all government, semi-government establishments, including educational institutions, are severely affected, and the country's economic growth becomes slowed down. To overcome such a situation, the relevant authorities have introduced the “Work from Home” policy for the employees and “Remote Education” for students. However, due to the persistence of multi-dimensional socio-economic problems, many employees and students face big challenges in performing their regular jobs while adopting such a policy. Consequently, enormous psychological anxiety has been developed for all people, including students, parents, employees, etc., and concurrently created severe changes in their behavior. This study aims to analyze the reasons for the behavioral changes of the employees, students, academic staff, and family members of different ages due to psychological anxiety, stress, or physical issues. A comprehensive online-based survey has been carried out on people working in various sectors in Bangladesh. A modified Apriori Algorithm has been used to sort out the associations between the causes and types of behavioral changes. Analyzed data revealed a massive human behavioral change in most participants. This finding indicates that the negligence of those significant human behavioral changes may cause a higher risk of creating psychological imbalance. Therefore, there is a need to have a solid understanding of the reasons for the behavioral changes and set up standard guidelines to maintain “Work from Home” in this Covid-19 situation to avoid psychological imbalance. Based on this study, some suggestions have been given for implementation by the government on an urgent basis. © 2023

关键词： Apriori algorithm Behavioral changes Covid-19 outbreak Family crisis Work from home

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On the Feasibility of a 3D-Printable Conductive Filament-Based Antenna Array for Conformal Applications

On the Feasibility of a 3D-Printable Conductive Filament-Bas...

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Antennas and Propagation & USNC/URSI National Radio Science Meeting

作者： Hemachandra Konduru Benjamin Callies Dipankar Mitra Sayan Roy Shuvashis Dey Rahul Gomes Dept. of Computer Science and Computer Engineering University of Wisconsin La Crosse WI USA Dept. of Physics and Astronomy University of Wisconsin La Crosse WI USA Electrical and Computer Engineering Division of Energy Matter and Systems University of Missouri Kansas City MO USA Dept. of Electrical and Computer Engineering North Dakota State University Fargo ND USA Dept. of Computer Science University of Wisconsin Eau Claire WI USA

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

NASA is actively addressing communication challenges, particularly in developing phased array antenna systems (PAAS) within the 2-2.5 GHz frequency band. The initial stages involve designing individual flexible antenna elements and non-phased antenna arrays. To address the issues of conformal phased array antennas, this work presents design enhancements for a 3D-printable microstrip patch antenna using a conductive Electrifi filament. The modifications, informed by recent research, are evaluated for the antenna's return loss and surface current distributions. The adopted modifications demonstrated superior performances in terms of gain and input reflection (S 11 ). The investigation extends to a 1x4 antenna array based on the modified patch antenna element. Notably, the conformal antennas and the antenna array exhibit low return loss alongside high gain and directivity, suggesting substantial potential for efficient performance in conformal surface applications.

关键词： Phased arrays Microstrip antenna arrays Electric potential Patch antennas NASA Resonant frequency Microstrip antennas

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Securing Digital Media in the Age of AI and Deepfakes: A Hardware-Based Solution

Securing Digital Media in the Age of AI and Deepfakes: A Har...

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IEEE Southeastcon

作者： Eric Scott Sisson Steven C. Puckett Dept. of Electrical and Computer Engineering Mississippi State University Starkville AL USA Computer Science and Information Systems University of North Alabama Florence AL USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

The current capabilities of deepfake and Artificial Intelligence (AI) technologies make it difficult to distinguish what is original from what is fabricated. Electronic documents can be digitally signed to verify and authenticate their information, making them admissible as evidence in court. In contrast, images and videos from Internet of Things (IoT) devices-such as police body cameras, security cameras, and smartphones are susceptible to deepfake manipulation, which can undermine their authenticity in legal proceedings. This research hypothesizes that digitally signing image and video data utilizing hardware cryptographic coprocessors could render them admissible in court. Utilizing our processes will also identify if any manipulation of the image data has occurred. Our approach addresses a critical need in the justice system to combat the challenges deepfakes pose and could pave the way for enhanced trust in digital evidence, bolstering the integrity of the judicial process.

关键词： Deepfakes Law enforcement Media Cameras Hardware Cryptography Internet of Things Artificial intelligence Digital signatures Coprocessors

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Exploring the Efficacy of Spatial Subsampling Methods for 3D Image Projection for 2D Classification

Exploring the Efficacy of Spatial Subsampling Methods for 3D...

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IEEE International Workshop on Imaging systems and Techniques (IST)

作者： Alif Aditya Wicaksono I Ketut Eddy Purnama Reza Fuad Rachmadi Feby Artwodini Muqtadiroh Ardyono Priyadi Mauridhi Hery Purnomo Dept. of Electrical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Computer Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350378214

ISBN: (纸本)9798350378221

In this paper we purpose several methods for creating 2D projection image from a 3D scan such as from CT or MR scans, and then look at different types of 2.5D projections with a growing window sizes and see its effects on the efficacy of the machine learning model when combined with the selection algorithms. As such we are using Shi-Tomasi Detectors, Sobel Edge Detectors, Sum of Pixel Intensity, Center Select, and Random Selection as selection algorithms from which we select the most interesting index for a given scan, from which depending on the window size, we stack the neighboring slices in the axial plane to the channel dimension creating a 2.5D image from which we could pass into our ResNet-9 model configured for classification and train the model for a given number of epochs, under the same conditions for all of our tests, this ensures that for all of our experiments the main effector is window size and the selection algorithm. From our tests we found that the Center Select on average outperforming the other selection algorithm, this result indicate that medical information is mostly centered around the scan, and when combined with the saving of 60% less parameters, the purposed method shows a new way of processing 3D Scans for processing with a 2D CNN model.

关键词： Solid modeling Three-dimensional displays Machine learning algorithms Image edge detection Computed tomography Neural networks Detectors Machine learning Classification algorithms Indexes

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An Ising Machine-Based Hybrid Optimization Method Using Constraint Conversion and Correction

An Ising Machine-Based Hybrid Optimization Method Using Cons...

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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Iwata, Kinya Tawada, Masashi Togawa, Nozomu Dept. of Computer Science and Communications Engineering Waseda University Japan Green Computing Systems Research Organization Waseda University Japan

ISBN: (纸本)9798331521165

This paper proposes an Ising machine-based hybrid optimization method to solve combinatorial optimization problems, which consists of an approximate formulation process, an annealing process with an Ising machine, and a correction process. The approximate formulation and correction aim to improve the performance of the Ising machine. Computational experiments were conducted on the multi-dimensional knapsack problem (MKP) using an Ising machine. We compare the results with those of the proposed method and the conventional method and demonstrate the effectiveness of the proposed approach. © 2025 IEEE.

关键词： Combinatorial optimization

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Stock Price Prediction Using LSTMSeq2Seq: A Deep Learning Approach with Advanced Feature engineering

Stock Price Prediction Using LSTMSeq2Seq: A Deep Learning Ap...

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International Conference on computer and Information Technology (ICCIT)

作者： Md. Kalim Amzad Chy Abdul Kadar Muhammad Masum Mohammed Shamsul Alam Md. Abul Kalam Azad Md Zia Uddin Dept. of AI Innovation Liberate Labs Texas USA Dept. of Software Engineering Daffodil International University Dhaka Bangladesh Dept. of Computer Science and Engineering International Islamic University Chittagong Chittagong Bangladesh Dept. of Business and Technology Management Islamic University of Technology Gazipur Bangladesh Software and Service Innovation Department SINTEF Digital Oslo Norway

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

This paper explores stock price prediction in the context of the Bangladesh stock market using advanced deep learning methodologies, specifically the LSTMSeq2Seq model. Traditional analytical techniques often fail to capture the complex, non-linear patterns inherent in financial data. To address this limitation, our research leverages the strengths of the LSTM-Seq2Seq architecture, which is tailored to the unique dynamics of the Bangladesh market. A robust feature engineering process is employed, utilizing 67 diverse features, including market trends, stock-specific indicators, fundamental and technical variables, and key macroeconomic factors such as gold prices and foreign exchange reserves. The dataset encompasses historical stock market data from 2012 to 2022, and extensive data preprocessing is performed to handle inconsistencies. Hyperparameter optimization is conducted using grid search to ensure model performance. The LSTMSeq2Seq model is evaluated based on key metrics such as MAE, MAPE, MSE, and the R 2 score, demonstrating superior predictive capabilities compared to traditional methods. This research not only advances the application of deep learning in financial forecasting but also provides valuable insights into stock price prediction in emerging markets, addressing ethical concerns to mitigate risks like market manipulation.

关键词： Deep learning Measurement Sentiment analysis Computational modeling Time series analysis Predictive models Macroeconomics Stock markets Forecasting Long short term memory

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Analysis of Perturb and Observe MPPT Under Varying PV Operating Climatic Conditions

Analysis of Perturb and Observe MPPT Under Varying PV Operat...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Abdirahim Addawe Musaria K. Mahmood Sulaiman M. Karim Ahmad M. Nezam dept. of Energy Systems Engineering Ankara Yildirim Beyazit University Ankara Turkiye dept. of Medical Instr. Tech. Eng. Jannat Iraq College Ramadi Iraq dept. of Computer Technology Engineering Al-Hadba'a University College Mosul Iraq dept. of Computer Engineering Karabuk Üniversitesi Karabuk Turkey

ISBN: (数字)9798350374131

ISBN: (纸本)9798350374148

Improving the efficiency of photovoltaic (PV) sys-tems has emerged as a critical priority. Achieving optimal power production from solar modules requires operating at maximum power point (MPP) under various climatic conditions. This paper describes the operation of the Perturb and Observe (P&O) as an efficient Maximum Power-Point Tracking (MPPT) algorithm. Simulations of various operating scenarios are performed using MATLAB to assess the algorithm efficiency under both Standard Test Conditions (STC) and Partial Shading Conditions (PSC). This study considers factors such as output power efficiency, time response, and steady-state power oscillation. The simulation results show a fast-tracking, lower oscillation in the case of STC but fail to track the MPP in the case of multi-panel under PSC.

关键词： Photovoltaic systems Solar irradiance Simulation Production software Steady-state Time factors

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MTDC Fault Detection and Localization Using High-Pass Filter

MTDC Fault Detection and Localization Using High-Pass Filter

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Annual Conference of Industrial Electronics Society

作者： Saad Ahmed Khan Abhisek Ukil Nirmal-Kumar C. Nair Dongyu Li Dept. of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand School of Electrical and Automation Engineering East China Jiaotong University Nanchang China

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

The DC link capacitor discharge in the event of a DC fault is rapid and contains high frequencies. This rapid discharge of high current and frequency interface with DC bus, Voltage Source Converter (VSC), and AC source. This interface damages the equipment and possibly living beings in proximity. Therefore, it is necessary to develop a topology to detect and identify fault types promptly, along with the isolation and restoration of the system. This study introduces an improved novel fault detection technique using the Highpass Chebyshev type 2 filter due to its flatter pass-band response. Further, the polarities of peaks obtained from the fault detection calculation are used again for another proposed novel fault location method. It identifies fault types to locate and isolate the faulty system using only polarities of amplitude response peaks. In the simulation, both methods were fast and accurate in detecting, locating, and identifying appropriate fault types only by High Pass Filter (HPF) amplitude response peaks and their polarities.

关键词： Accuracy Fault detection Voltage Fault location Chebyshev approximation Discharges (electric) Topology Power systems Passband Voltage-source converters

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Web Application-Based Enhanced Esophageal Disease Diagnosis in Low-Resource Settings

Web Application-Based Enhanced Esophageal Disease Diagnosis ...

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IEEE International Conference on Biomedical engineering, computer and Information Technology for Health

作者： Abdullah Al Masum Zishad Hossain Limon Md Ariful Islam Md Shahidur Rahman Mahbub Khan Sheikh Shemanto Afridi Md. Redwan Ahmed Shafiur Rahman Dept. of Information Technology Westcliff University CA USA Dept. of Computer Science Westcliff University CA USA Dept. of Business Administration International American University CA USA Dept. of Engineering management Westcliff University CA USA Dept. of Management Information System Pacific State University CA USA Dept. of Computer Science and Engineering East West University Dhaka Bangladesh Dept. of Software Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798331534356

ISBN: (纸本)9798331534363

An essential part of the digestive system, the esophagus permits food and liquids to move easily from the throat to the stomach. Traditional diagnostic techniques, such as endoscopy and biopsy, are invasive and resource-intensive, making them less practical in resource-constrained environments. To address these challenges, we proposed utilizing a hybrid Deep Learning (DL) model called GAN-EfficientNet, which combines the power of Generative Adversarial Networks (GAN) and EfficientNet to effectively classify esophageal diseases. Our approach employs advanced image preprocessing techniques and data augmentation methods to enhance the diversity and balance of the dataset. Feature extraction using the Spatial Gray Level Dependence Method (SGLDM) and Principal Component Analysis (PCA) significantly reduces computational complexity without compromising accuracy. We explored both binary and multiclass classification methods, recognizing their crucial roles in various diagnostic scenarios. Binary classification distinguishes between normal and diseased states, essential for initial screening, while multiclass classification identifies specific esophageal diseases, aiding in personalized treatment plans. The GAN-EfficientNet model demonstrated exceptional performance, achieving an impressive F1 score of 99.44% for binary classification and 99.64% for multiclass classification. Additionally, we developed a web application that facilitates quick and precise disease diagnosis, particularly advantageous in areas with limited resources. This tool significantly improves patient outcomes through early detection, leading to reduced healthcare costs and less burden from advanced esophageal diseases.

关键词： Deep learning Accuracy Computational modeling Generative adversarial networks Feature extraction Data augmentation Data models Medical diagnosis Diseases Principal component analysis

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A Comparative Study of the Performance of Real time databases and Big data Analytics Frameworks

A Comparative Study of the Performance of Real time database...

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International Multi-Topic ICT Conference (IMTIC)

作者： Syed Muhammd Nabeel Mustafa Muhammad Umer Farooq Syeda Sundus Zehra Jospeh Peter Terenece Noronha Dept. of Computer Science & I.T NED University of Engineering and Technology Karachi Pakistan Dept. of Software Engineering Sir Syed University of Engineering and Technology Karachi Pakistan

The amelioration of information technology and the infiltration of it almost all the sectors of world have resulted in massive efflux of data. The rampant increase in the generation of data has introduced to a new term called, Big data. Big data is letting industry set the pace of future research and development. The need rose to further refine the data and get most out of it. Scientists and researchers performed analytic on the Big data to analyze it for patterns and behaviors hidden inside the data. Big data analytics aid in understanding the data through various tools, algorithms and frameworks. It allows stakeholders to make business plans and strategies according to the revelations from data. There are various tools and technologies available to perform analytics on the data. The most popular among scientists and researchers are real-time database and Big data analytics frameworks. In the paper, we evaluate the performance of the tools and technologies of Big data analytics. Mongodb and Firebase are real-time databases implemented in this study and Impala and Hive are the BDA frameworks. The parameter to perform the comparison is the query execution time. It is found out that Impala and Hive gave lesser execution time than Mongodb and Firebase. The query execution time of Impala on 50 mb dataset and 100 mb dataset was recorded to be 4 ms and 14 ms respectively. Hence, Big data Analytics Frameworks are better performing analytics tools for Big data Analytics.

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