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Exploring the Past, Present, and Future of In-Band Full-Duplex Wireless Systems [Book/Software Reviews]

IEEE Microwave Magazine 2022年第12期23卷 16-19页

作者： James Chus Southern Polytechnic College of Engineering Kennesaw State University Marietta GA USA

Kenneth Kolodziej is a technical staff member in the RF technology Group at the Massachusetts Institute of technology (MIT) Lincoln Laboratory, where he is a principal investigator on wideband electronics and in-band full-duplex (IBFD), commonly known as simultaneous transmit and receive ( STAR) systems. He has conducted research on RF, microwave, and photonic circuits, including antenna, radar, and communications systems. He received his B.E. and M.E. degrees in electrical engineering from the Stevens Institute of technology in Hoboken, NJ. He has published numerous journal articles and conference papers and holds several patents in the field of antennas and RF systems. He is also an IEEE Member and is very actively serving the IEEE Society.

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Exploring the Vulnerabilities of Machine Learning and Quantum Machine Learning to Adversarial Attacks using a Malware Dataset: A Comparative Analysis

arXiv

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arXiv 2023年

作者： Akter, Shapna Shahriar, Hossain Iqbal, Iysa Hossain, M.D. Karim, M.A. Clincy, Victor Voicu, Razvan Department of Computer Science Kennesaw State University United States Department Information Technology Kennesaw State University United States Nicolet High School United States Southern Polytechnic College of Engineering and Engineering Technology United States Department of Engineering Kennesaw State University United States

The burgeoning fields of machine learning (ML) and quantum machine learning (QML) have shown remarkable potential in tackling complex problems across various domains. However, their susceptibility to adversarial attacks raises concerns when deploying these systems in security-sensitive applications. In this study, we present a comparative analysis of the vulnerability of ML and QML models, specifically conventional neural networks (NN) and quantum neural networks (QNN), to adversarial attacks using a malware dataset. We utilize a software supply chain attack dataset known as ClaMP and develop two distinct models for QNN and NN, employing Pennylane for quantum implementations and TensorFlow and Keras for traditional implementations. Our methodology involves crafting adversarial samples by introducing random noise to a small portion of the dataset and evaluating the impact on the models’ performance using accuracy, precision, recall, and F1 score metrics. Based on our observations, both ML and QML models exhibit vulnerability to adversarial attacks. While the QNN’s accuracy decreases more significantly compared to the NN after the attack, it demonstrates better performance in terms of precision and recall, indicating higher resilience in detecting true positives under adversarial conditions. We also find that adversarial samples crafted for one model type can impair the performance of the other, highlighting the need for robust defense mechanisms. Our study serves as a foundation for future research focused on enhancing the security and resilience of ML and QML models, particularly QNN, given its recent advancements. A more extensive range of experiments will be conducted to better understand the performance and robustness of both models in the face of adversarial attacks. © 2023, CC BY.

关键词： Machine learning

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AI-Powered IT Project Management: Analyzing the Effectiveness of Advanced Project Management Tools to Ensure Project Efficiency

AI-Powered IT Project Management: Analyzing the Effectivenes...

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IEEE Southeastcon

作者： Jiban Krisna Das Ifeoluwa Elegbe Lord Coffie Rojeena Khadka Lei Chen Yiming Ji Dept. of Information Technology Georgia Southern University Statesboro GA USA College of Computing and Software Engineering Kennesaw State University

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

The integration of Artificial Intelligence (AI) into project management has significantly transformed traditional methodologies, particularly within the Information technology (IT) sector. This study investigates the effectiveness of AI-powered tools, specifically Asana, Jira, and *** to improve project management efficiency through automation, resource optimization, and decision-making processes. Using a systematic literature review and quantitative analysis, the research highlights the capabilities and limitations of these tools in the management of complex IT projects. The study findings reveal that AI-powered platforms facilitate real-time tracking, predictive analytics and dynamic resource allocation, which collectively contribute to reduced project timelines and improved outcomes. However, challenges such as data quality, integration complexities, and the need for skilled personnel remain prevalent. The study was summarized with strategic recommendations for organizations to incorporate automation, leverage predictive analytics, and improve data integrity, thus maximizing the benefits of AI in project management. This research underscores the critical role of AI in modernizing project management practices, which ultimately leads to increased productivity and project success rates in the IT domain.

关键词： Automation Navigation Project management Organizations Predictive models Real-time systems Complexity theory Resource management Predictive analytics Optimization

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Banana MabHLH28 positively regulates the expression of softening-related genes to mediate fruit ripening independently or via cooperating with MaWRKY49/111

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园艺研究（英文） 2024年第4期11卷 233-245页

作者： Chaojie Wu Danling Cai Jun Li Zengxiang Lin Wei Wei Wei Shan Jianye Chen Wangjin Lu Xinguo Su Jianfei Kuang State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources/Guangdong Provincial Key Laboratory of Postharvest Science of Fruits and Vegetables/Engineering Research Center of Southern Horticultural Products Preservation Ministry of EducationCollege of HorticultureSouth China Agricultural UniversityGuangzhou 510642China Agronomy Dean Guangdong AIB Polytechnic CollegeGuangzhou 510507China

Texture softening is a physiological indicator of fruit ripening,which eventually contributes to fruit quality and the consumer's *** great progress having been made in identification of the genes related to fruit softening,the upstream transcriptional regulatory pathways of these softening-related genes are not fully ***,a novel bHLH gene,designated as MabHLH28,was identified because of its significant upregulation in banana fruit ***-Seq analysis revealed that MabHLH28 bound to the core sequence of'CAYGTG'presented in promoter regions of fruit softening-associated genes,such as the genes related to cell wall modification(MaPG3,MaPE1,MaPL5,MaPL8,MaEXP1,MaEXP2,MaEXPA2,and MaEXPA15)and starch degradation(MaGWD1 and MaLSF2),and these bindings were validated by EMSA and DLR *** overexpression and knockdown of MabHLH28 in banana fruit resulted in up-and down-regulation of softening-related genes,thereby hastening and postponing fruit ***,overexpression of MabHLH28 in tomato accelerated the ripening process by elevating the accumulation of softening-associated *** addition,MabHLH28 showed interaction withMaWRKY49/111 and itself to form protein complexes,which could combinatorically strengthen the transcription of softening-associated *** together,our findings suggest that MabHLH28 mediates fruit softening by upregulating the expression of softening-related genes either alone or in combination with MaWRKY49/111.

关键词： expression genes with banana cooperating fruit independently mabhlh28 mawrky49 mediate

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Comparative assessment of force,temperature,and wheel wear in sustainable grinding aerospace alloy using biolubricant

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Frontiers of Mechanical engineering 2023年第1期18卷 1-33页

作者： Xin CUI Changhe LI Yanbin ZHANG Wenfeng DING Qinglong AN Bo LIU Hao Nan LI Zafar SAID Shubham SHARMA Runze LI Sujan DEBNATH School of Mechanical and Automotive Engineering Qingdao University of TechnologyQingdao 266520China State Key Laboratory of Ultra-precision Machining Technology Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityHong KongChina College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China Sichuan Future Aerospace Industry LLC. Shifang 618400China School of Aerospace University of Nottingham Ningbo ChinaNingbo 315100China College of Engineering University of SharjahSharjah 27272United Arab Emirates Department of Mechanical Engineering IK Gujral Punjab Technical UniversityPunjab 144603India Department of Biomedical Engineering University of Southern CaliforniaLos AngelesCA 90089USA Mechanical Engineering Department Curtin UniversityMiri 98009Malaysia

The substitution of biolubricant for mineral cutting fluids in aerospace material grinding is an inevitable development direction,under the requirements of the worldwide carbon emission ***,serious tool wear and workpiece damage in difficult-to-machine material grinding challenges the availability of using biolubricants via minimum quantity *** primary cause for this condition is the unknown and complex influencing mechanisms of the biolubricant physicochemical properties on *** this review,a comparative assessment of grindability is performed using titanium alloy,nickel-based alloy,and high-strength ***,this work considers the physicochemical properties as the main factors,and the antifriction and heat dissipation behaviours of biolubricant in a high temperature and pressure interface are comprehensively ***,the comparative assessment of force,temperature,wheel wear and workpiece surface for titanium alloy,nickel-based alloy,and high-strength steel confirms that biolubricant is a potential replacement of traditional cutting fluids because of its improved lubrication and cooling ***-viscosity biolubricant and nano-enhancers with high thermal conductivity are recommended for titanium alloy to solve the burn puzzle of the *** with high viscosity and high fatty acid saturation characteristics should be used to overcome the bottleneck of wheel wear and nickel-based alloy surface *** nano-enhancers with high hardness and spherical characteristics are better ***,a different option is available for high-strength steel grinding,which needs low-viscosity biolubricant to address the debris breaking difficulty and wheel ***,the current challenges and potential methods are proposed to promote the application of biolubricant.

关键词： grinding aerospace difficult-to-machine material biolubricant physicochemical property grindability

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Exploring the Intelligence Built Into Noise Instruments and Microwave Design Software [Book/Software Reviews]

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IEEE Microwave Magazine 2022年第9期23卷 27-29页

作者： James Chu Adjunct Professor Southern Polytechnic College of Engineering Kennesaw State University Marietta Georgia USA

The book focuses on intelligence built into noise instruments and microwave design software. It has a total of 22 chapters and an appendix. This book is intended both for engineers working in practice and students at the technical college level. It not only covers the fundamentals of electronic noise and the properties of semiconductor components but also detailed questions of measurement technology in the low-frequency, RF, and microwave ranges. The book shows what is hidden behind the intelligence built into noise instruments and microwave design software. This book presents many noise issues, starting from simple basics, and each step is presented logically in mathematical derivations. The authors always try to maintain clarity and reference to practice and avoid unnecessary abstract presentations.

关键词： Book reviews Microwave circuits Transistors Microwave measurement Microwave amplifiers Phase noise Integrated circuit modeling

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“This Wasn’t Pedagogy, It Was Panicgogy”: Perspectives of the Challenges Faced by Students and Instructors during the Emergency Transition to Remote Learning Due to COVID-19

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college Teaching 2023年第4期71卷 227-243页

作者： Spinks, M’Lyn Metzler, Mike Kluge, Stacy Langdon, Jody Gurvitch, Rachel Smitherman, Marina Esmat, Tiffany Bhattacharya, Sylvia Carruth, Laura Crowther, Katy Denton, Ren Edwards, Ordene V. Shrikhande, Milind Strong-Green, Ashley WellStar College of Health and Human Services Kennesaw State University United States Center for Teaching and Learning Georgia State University United States Instructional Innovation Augusta University United States Georgia Southern University United States Georgia State University United States Department of Life Science Dalton State College United States WellStar College of Health and Human Services Exercise Science Kennesaw State University United States College of Computing and Software Engineer Engineering Technology Kennesaw State University United States Center for Excellence in Teaching and Learning Georgia State University United States Department of English Georgia State University United States Academic Affairs East Georgia State College - Statesboro Campus United States Department of Psychological Science Kennesaw State University United States Department of Finance Georgia State University United States Department of English Augusta Technical College United States

This qualitative study explores the impact of the emergency transition to remote education (ETRE) during the COVID-19 pandemic on instructors and students through the lens of self-determination theory (SDT). A modified thematic analysis of narratives from a cross-sectional survey revealed eight themes: Sense of loss/grief, Role conflict, Helplessness, I had no choice, This felt impossible, Lost connections, Am I safe, and They don’t care about me. Sub-themes expound on their associated themes. Participant narratives shared feelings of trauma and crisis as they related experiences of higher education during the mandated global shutdown. The stories of these experiences are indicative of loss of autonomy, competence, and relatedness, tenets of self-determination. These experiences, for the majority of students, led to a loss of motivation to learn, participate, or produce meaningful work. For most instructors, the experiences led to a similar lassitude and frustration. The authors conclude that the experience of the ETRE negatively impacted both teaching and learning in the higher education setting. Recommendations include further development in higher education to support both instructors’ and students’ self-determination during catastrophic change. © 2021 Taylor & Francis Group, LLC.

关键词： COVID-19 emergency transition instructors qualitative self-determination students

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Deep learning-based prediction of effluent quality of a constructed wetland

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Environmental Science and Ecotechnology 2023年第1期13卷 64-74页

作者： Bowen Yang Zijie Xiao Qingjie Meng Yuan Yuan Wenqian Wang Haoyu Wang Yongmei Wang Xiaochi Feng State Key Laboratory of Urban Water Resource and Environment School of Civil and Environmental EngineeringHarbin Institute of Technology(Shenzhen)ShenzhenGuangdong518055PR China Shenzhen Shenshui Water Resources Consulting CO LTDShenzhenGuangdong518022PR China College of Biological Engineering Beijing PolytechnicBeijing10076PR China State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control School of Environmental Science and EngineeringSouthern University of Science and TechnologyShenzhen518055China

Data-driven approaches that make timely predictions about pollutant concentrations in the effluent of constructed wetlands are essential for improving the treatment performance of constructed ***,the effect of the meteorological condition and flow changes in a real scenario are generally neglected in water quality *** address this problem,in this study,we propose an approach based on multi-source data fusion that considers the following indicators:water quality indicators,water quantity indicators,and meteorological *** this study,we establish four representative methods to simultaneously predict the concentrations of three representative pollutants in the effluent of a practical large-scale constructed wetland:(1)multiple linear regression;(2)backpropagation neural network(BPNN);(3)genetic algorithm combined with the BPNN to solve the local minima problem;and(4)long short-term memory(LSTM)neural network to consider the influence of past results on the *** results suggest that the LSTM-predicting model performed considerably better than the other deep neural network-based model or linear method,with a satisfactory R^(2).Additionally,given the huge fluctuation of different pollutant concentrations in the effluent,we used a moving average method to smooth the original data,which successfully improved the accuracy of traditional neural networks and hybrid neural *** results of this study indicate that the hybrid modeling concept that combines intelligent and scientific data preprocessing methods with deep learning algorithms is a feasible approach for forecasting water quality in the effluent of actual engineering.

关键词： LSTM Constructed wetlands Water quality prediction Deep learning Multi-source data fusion

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AI-Powered IT Project Management: Analyzing the Effectiveness of Advanced Project Management Tools to Ensure Project Efficiency

AI-Powered IT Project Management: Analyzing the Effectivenes...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Das, Jiban Krisna Elegbe, Ifeoluwa Coffie, Lord Khadka, Rojeena Chen, Lei Ji, Yiming Georgia Southern University Dept. of Information Technology StatesboroGA United States College of Computing and Software Engineering Kennesaw State University United States

ISBN: (纸本)9798331504847

关键词： Project management

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Nano-assisted delivery tools for plant genetic engineering: a review on recent developments

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Environmental Science and Pollution Research 2025年第2期32卷 469-484页

作者： Kumar, Pradeep Rajput, Vishnu D. Singh, Amit Kumar Agrawal, Shreni Das, Richa Minkina, Tatiana Shukla, Praveen Kumar Wong, Ming Hung Kaushik, Ajeet Albukhaty, Salim Tiwari, Kavindra Nath Mishra, Sunil Kumar Department of Botany MMV Banaras Hindu University UP Varanasi221005 India Academy of Biology and Biotechnology Southern Federal University Rostov-On-Don Russia Department of Pharmaceutical Engineering & Technology Indian Institute of Technology Banaras Hindu University UP Varanasi221005 India Department of Biotechnology Parul Institute of Applied Science Parul University Gujarat Vadodara391760 India Soil Health Laboratory Southern Federal University Rostov-On-Don Russia The Education University of Hong Kong Tai Po Hong Kong Department of Environmental Engineering Florida Polytechnic University Lakeland United States Department of Chemistry College of Science University of Misan Maysan Amarah62001 Iraq

Conventional approaches like Agrobacterium-mediated transformation, viral transduction, biolistic particle bombardment, and polyethylene glycol (PEG)-facilitated delivery methods have been optimized for transporting specific genes to various plant cells. These conventional approaches in genetically modified crops are dependent on several factors like plant types, cell types, and genotype requirements, as well as numerous disadvantages such as time-consuming, untargeted distribution of genes, and high cost of cultivation. Therefore, it is suggested to develop novel techniques for the transportation of genes in crop plants using tailored nanoparticles (NPs) of manipulative and controlled high-performance features synthesized using green and chemical routes. It is observed that site-specific delivery of genes exhibits high efficacy in species-independent circumstances which leads to an increased level of productivity. Therefore, to achieve these outcomes, NPs can be utilized as gene nano-carriers for excellent delivery inside crops (i.e., cotton, tobacco, rice, wheat, okra, and maize) for desired genetic engineering modifications. As outcomes, this review provides an outline of the conventional techniques and current application of numerous nano-enabled gene delivery needed for crop gene manipulation, the benefits, and drawbacks associated with state-of-the-art techniques, which serve as a roadmap for the possible applicability of nanomaterials in plant genomic engineering as well as crop improvement in the future. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Plant diseases

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