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IEEE International WIE Conference on Electrical and computer engineering (WIECON-ECE)

作者： Md. Abul Basar Md. Faruk Hosen Md. Al Amin Nasima Islam Bithi Bikash Kumar Paul Department of Information and Communication Technology Mawlana Bhashani Science and Technology University Tangail Bangladesh Department of Software Engineering Daffodil International University (DIU) Dhaka Bangladesh Department of Computer Science and Engineering Daffodil International University (DIU) Dhaka Bangladesh

Stress means a lot of mental or physical strain. It can result from anything that provokes negative emotions, such as an idea or an experience. The World Health Organization cites depression as the leading nonfatal cause of disability worldwide. Major depressive disorder is one of the most common mental health illnesses that results in long-term damage (MDD). A major obstacle to the correct identification of stress and depression is the lack of good diagnostic biomarkers. By analyzing gene networks, we hoped to identify potential biomarkers of this disease. Samples of stress and depression were used to create the microarray and RNA-seq datasets GSE183648 and GSE101521. Through the use of R, it is possible to search for frequently occurring DEGs and filter preprocessed datasets. A Venn diagram illustrating the overlap between different sets of DEGs rules. When a group of DEGs is established, the PPIs network is built from them, with hub nodes selected according to topological features. In the PPI network, we found that ITGB3, ANGPTL4, ITGB1, PPARA, and RXRA serve as important hub genes. This research includes KEGG pathways as well. The development of the Gene Ontology, studies of gene-miRNA interactions, TF-gene interactions, and module analysis networks are all seen as important next steps in this field of study. Last but not least, various therapeutic possibilities have been found with identical DEGs as their primary base.

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UAV Virtual Antenna Array Deployment for Uplink Interference Mitigation in Data Collection Networks

arXiv

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arXiv 2024年

作者： Li, Hongjuan Kang, Hui Sun, Geng Li, Jiahui Wang, Jiacheng Wang, Xue Niyato, Dusit Leung, Victor C.M. College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore College of Computing and Data Science Nanyang Technological University Singapore Department of Communication Engineering Jilin University Changchun130012 China Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518115 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering The University of British Columbia VancouverV6T 1Z4 Canada

Unmanned aerial vehicles (UAVs) have gained considerable attention as a platform for establishing aerial wireless networks and communications. However, the line-of-sight dominance in air-to-ground communications often leads to significant interference with terrestrial networks, reducing communication efficiency among terrestrial terminals. This paper explores a novel uplink interference mitigation approach based on the collaborative beamforming (CB) method in multi-UAV network systems. Specifically, the UAV swarm forms a UAV-enabled virtual antenna array (VAA) to achieve the transmissions of gathered data to multiple base stations (BSs) for data backup and distributed processing. However, there is a trade-off between the effectiveness of CB-based interference mitigation and the energy conservation of UAVs. Thus, by jointly optimizing the excitation current weights and hover position of UAVs as well as the sequence of data transmission to various BSs, we formulate an uplink interference mitigation multi-objective optimization problem (MOOP) to decrease interference affection, enhance transmission efficiency, and improve energy efficiency, simultaneously. In response to the computational demands of the formulated problem, we introduce an evolutionary computation method, namely chaotic non-dominated sorting genetic algorithm II (CNSGA-II) with multiple improved operators. The proposed CNSGA-II efficiently addresses the formulated MOOP, outperforming several other comparative algorithms, as evidenced by the outcomes of the simulations. Moreover, the proposed CB-based uplink interference mitigation approach can significantly reduce the interference caused by UAVs to non-receiving BSs. Copyright © 2024, The Authors. All rights reserved.

关键词： Multiobjective optimization

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The Role of Machine Learning in Digital Forensics 8

The Role of Machine Learning in Digital Forensics

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8th International Symposium on Digital Forensics and Security, ISDFS 2020

作者： Qadir, Abdalbasit Mohammed Varol, Asaf University of Sulaimani Department of Computer Science Sulaimani Iraq Firat University Department of Software Engineering Elazig Turkey

ISBN: (数字)9781728169392

ISBN: (纸本)9781728169392

Digital forensics, as a branch of the forensic sciences, is facing new challenges from the aspect that potential digital evidence is growing and expanding. Rapid development in the fields of computer science and information technology provides innovative techniques for digital investigations. In this paper, the important role of machine learning is explained as an application of artificial intelligence, and how it can be used to analyse large amounts of diverse datasets in order to reveal any criminal behaviour and intent through learning from previous and historical activities to predict criminal behaviours in the future. © 2020 IEEE.

关键词： Digital forensics

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Integrating User Experience into Agile: An Experience Report on Lean UX and Scrum

arXiv

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arXiv 2022年

作者： Alhammad, Manal M. Moreno, Ana M. Department of Software Engineering King Saud University Riyadh Saudi Arabia School of Computer Science Universidad Politécnica de Madrid Madrid Spain

The integration of Agile development and user experience (UX) has received significant attention over the past decade. The literature contains several process models and wide-ranging discussion about the benefits and challenges of this integration. However, academia has given this integration short shrift. In fact, there are very few publications covering educational courses dealing with Agile development and UX. In this paper, we report on our experience of designing and running a graduate software engineering course that covers the integration of Lean UX into Scrum and employs gamification to improve student engagement. We identified six lessons learned that new point to important aspects to be considered when integrating Agile development and UX in academia. For example, we discuss the complexity of managing Lean UX activities in short sprints or how the design of a testable and tactical hypothesis can be one of the most challenging aspects of the Lean UX process. © 2022, CC BY.

关键词： Curricula

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Real-Time Resume Classification System Using LinkedIn Profile Descriptions 1

Real-Time Resume Classification System Using LinkedIn Profil...

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1st IEEE International Conference on Computational Intelligence for Smart Power System and Sustainable Energy, CISPSSE 2020

作者： Ramraj, S Sivakumar, V. Ramnath G, Kaushik Srm Institute of Science and Technology Department of Software Engineering Chennai India Srm Institute of Science and Technology Department of Computer Science Chennai India

ISBN: (纸本)9781728172743

In the domain of online job recruitment, accurate job and resume classification is vital for both the seeker and the recruiter. We have built an automatic text classification system that utilizes various techniques like Term frequency-inverse document frequency with Machine Learning and Convolution Neural network for training the model with texts and classifying them into labels and finally to compare their results. Using resume data of applicants, we have categorized them into different categories. Due to the sensitive nature of resume data, we have used domain adaptation. A classifier is trained on a large dataset of job description snippet, which is then used to classify resume data. Despite having a small dataset, consistent classification performance is seen. The primary filter for this type of work is the efficiency the system can provide. We aim to compare the results obtained by various algorithms that are generated using the same data so that the efficiency of each algorithm can be evaluated. From the result, it is evident that character-level CNN gives a better F1 score compared to other models. © 2020 IEEE.

关键词： Efficiency

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Canadarm, Canadarm2, and Canadarm3: The evolution of Canada's iconic robotic system and its impacts from space down to Earth 58

Canadarm, Canadarm2, and Canadarm3: The evolution of Canada'...

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58th IAA History of Astronautics Symposium at the 75th International Astronautical Congress, IAC 2024

作者： Hudon-Castillo, Yianni Lamanque, Jean-Christophe Thénault, Marion Zamudio-Turcotte, Katherine Musunuri, Sri Venkata Vathsala Thilloy, Auriane Leclair, Olivier Roberge, Julien Lavergne Elforaici, Mohamed El Amine Daigneault, Rafael Chazbek, Rachad Beltrame, Giovanni Department of Electrical Engineering Polytechnique Montréal 2500 Chemin de Polytechnique MontréalQCH3T 1J4 Canada Department of Electrical and Computer Engineering McGill University McConnell Engineering Building MontréalQCH3A 0E9 Canada Department of Aerospace Engineering Gina Cody School of Engineering and Computer Science Concordia University 1455 De Maisonneuve Blvd. W. MontréalQCH3G 1M8 Canada Department of Aerospace Engineering Polytechnique Montréal 2500 Chemin de Polytechnique MontréalQCH3T 1J4 Canada Department of Physics Université de Montréal 1375 Ave Thérèse-Lavoie-Roux MontréalQCH2V 0B3 Canada Department of Mechanical Engineering Université Laval QuébecQCG1V 0A6 Canada Department of Biomedical Engineering Polytechnique Montréal 2500 Chemin de Polytechnique MontréalQCH3T 1J4 Canada Department of Engineering Physics Polytechnique Montréal 2500 Chemin de Polytechnique MontréalQCH3T 1J4 Canada Department of Computer and Software Engineering Polytechnique Montréal 2500 Chemin de Polytechnique MontréalQCH3T 1J4 Canada

ISBN: (纸本)9798331312329

Considered to be Canada's groundbreaking technological achievement in the field of robotics and its greatest contribution to space, Canadarm and Canadarm2 have made their mark on both the Canadian and international scene. As the upcoming Canadarm3 reaches the culmination of its design phase for the Lunar Gateway, an opportunity to review the evolution of this robotic technology over its combined 53 years of service arises. Furthermore, the practical impacts of each Canadarm generation will be explored, regarding the safe and sustainable use of space, the commercialization of the space industry, and technological progress in the medical field, in nuclear power plant robotics and in remote explosives disarming robots. This paper will embark on a comprehensive literature review, complemented by interviews conducted with key contributors to the Canadarms' missions as well as Canadian astronauts. This methodological approach aims to provide an accurate outline of the technical, operational, and collaborative complexities that have underpinned the development and deployment of this technology. By comparing the technical specifications of each Canadarm generation in the context of their respective space program, namely Space Shuttle, ISS and Gateway, technological advancements will be highlighted from an engineering and operations standpoint. The conducted interviews with the Canadian Space Agency (CSA) and MacDonald Dettwiler And Associates (MDA) will also help illustrate the obstacles faced throughout the implementation of these programs. Foreseeing the next step in Canada's role in space exploration, this study will also examine Canadarm3's upcoming crucial contribution in missions to the Moon, Mars, and beyond. This outlook includes a mission concept study of the next generation Canadarm : Canadarm4, which will emphasize the ongoing significance of innovation and international collaboration, affirming Canada's leadership in space robotics technology. © 2024 Internation

关键词： Nuclear power plants

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Vertical-horizontal model of states of software with injected defects

Vertical-horizontal model of states of software with injecte...

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IEEE International Conference on Dependable Systems, Services and Technologies (DESSERT)

作者： Oleksandr Gordieiev Daria Gordieieva Department of Software engineering Lutsk National Technical University Lutsk Ukraine School of Electronics Electrical Engineering and Computer Science Queen's University Belfast Belfast United Kingdom

ISBN: (纸本)9798350333053

The article discusses an approach to software quality assessment based on injecting software defects. The concept of a profile of software defects is introduced and various types of profiles of software defects and their misalignments are considered. The main attention is paid to modelling software states with injected defects and transitions between them. The article proposes a horizontal model of software states with injected defects using Markov chains and a vertical-horizontal model as its evolution. A feature of the vertical-horizontal model is the description of software states before and after the injection of software defects for each horizontal level. In this case, the active states before the injection of the defects become passive after the injection of the defects in the software, and vice versa, the passive states before the injection of the defects pass into the active states after the injection. The results obtained made it possible to determine the probability distribution of transitions between states.

关键词： software quality Markov processes software Probability distribution

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Spatial release from masking in varying spatial acoustic under higher order Ambisonic-based sound reproduction system 50

Spatial release from masking in varying spatial acoustic und...

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50th International Congress and Exposition of Noise Control engineering, INTER-NOISE 2021

作者： Hui, C.T. Justine Hioka, Yusuke Watson, Catherine I. Masuda, Hinako Acoustics Research Centre Department of Mechanical Engineering University of Auckland Auckland1010 New Zealand Department of Electrical Computer and Software Engineering University of Auckland Auckland1010 New Zealand Faculty of Science and Technology Seikei University Tokyo180-8633 Japan

ISBN: (纸本)9781732598652

A previous study found that spatial release from masking (SRM) could be observed under virtual reverberant environments using a first order Ambisonic-based sound reproduction system, however, poor localisation accuracy made it difficult to examine effect of varying reverberation time on SRM. The present study follows on using higher order Ambisonics (HOA) to examine how benefits from SRM vary in different spatial acoustics. Subjective speech intelligibility was measured where four room acoustics:reverberation time (RT)= 0.7 s (clarity (C50)= 15.9 dB, 6.8 dB);RT= 1.7 s (C50= 10.3 dB, 3.3 dB) were simulated via a third order Ambisonics system with a 16 channel spherical loudspeaker array. The masker was played from 8 azimuthal angles (0, ±45, ±90, ±135, 180 degrees) while the target speech was played from 0 degree. The listeners are deemed to benefit from SRM if their intelligibility scores were higher when the masker was projected from a different angle than that of the target. We found while listeners could benefit from SRM at C50 = 15.9 dB and 10.3 dB, the benefit starts to diminish at C50 = 6.8 dB, and listeners could no longer benefit from SRM at C50 = 3.3 dB. © INTER-NOISE 2021 .All right reserved.

关键词： Reverberation

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An Exploratory Study of Students' Learning Performance in Flipped Classroom Using Decision Tree and Regression 3

An Exploratory Study of Students' Learning Performance in Fl...

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3rd International Conference on Computing, Mathematics and engineering Technologies, iCoMET 2020

作者： Bashir, Fatima Ahmed, Dr. Sohaib Marouf, Muhammad Bahria University Department of Computer Science Karachi Pakistan Bahria University Department of Software Engineering Karachi Pakistan

ISBN: (纸本)9781728149707

Flipped Classroom model is one of the most effective and influential approaches that follow a student-centered approach. It may enhance students' learning skills and creates a motivational level by conducting learning activities in pre-class and post-class sessions. The main purpose of this research is to demonstrate how a combined, teaching and machine learning approach can be useful in evaluating student learning outcomes by analyzing their learning performance. Furthermore, this can help the instructor to counsel students whose performance is lagging during the semester. To perform predictive analysis and classification, we have implemented linear regression and decision tree classifier that helps the instructor to predict and classify students learning outcomes based on their overall performance before final exams. © 2020 IEEE.

关键词： Decision trees

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Method for Quantum Denoisers Using Convolutional Neural Network

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Computational Intelligence and Neuroscience 2022年第0期2022卷 4885897页

作者： Kim, Bong-Hyun Madhavi, S. School of Software Computer Engineering Major Seowon University 377-3 Musimseo-ro Seowon-gu Cheongju-si Chungcheongbuk-do28674 Korea Republic of Computer Science and Engineering Department PVP Siddhartha Institute of Technology Andhra Pradesh Kanuru India

In many applications of quantum information science, high-dimensional entanglement is needed. Quantum teleportation is used for transferring information from one place to another using Einstein-Podolsk-Rosen pairs (EPR) and two classical bits of communication in a channel. Since we cannot produce multiple copies of an unknown state for amplification, we will generate multiple EPR pairs. However, after the distribution of the EPR pairs, they will have decreased fidelity with the ideal EPR state. So, to maintain the quantum states and maximize the quantification of the entanglement without losing the strength of the states, we propose to denoise the channel for a few types of noise. We created a random noise source and filtered out the irrelevant information without affecting the relevant information encoded in the quantum states. The proposed model is used for successful denoising of GHZ states from spin flips and bit flip errors. Much of the research work is not carried out by using machine-language-based neural networks for noise-reduction in quantum channels. In this paper, we propose a denoiser called quantum denoiser CNQD, which uses a feedforward convolution neural network model. We tuned our model with highly entangled GHZ states with zero phases and phase between [0, ∏] mixed with different kinds of noise. Finally, the proposed model can be used for optimal quantum communication via noisy quantum channels using GHZ states. © 2022 Bong-Hyun Kim and S. Madhavi.

关键词： Quantum entanglement

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