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Articles 211 - 240 of 57897
Full-Text Articles in Physical Sciences and Mathematics
Personalized Driving Using Inverse Reinforcement Learning, Rodrigo J. Gonzalez Salinas
Personalized Driving Using Inverse Reinforcement Learning, Rodrigo J. Gonzalez Salinas
Theses and Dissertations
This thesis introduces an autonomous driving controller designed to replicate individual driving behaviors based on a provided demonstration. The controller employs Inverse Reinforcement Learning (IRL) to formulate the reward function associated with the provided demonstration. IRL is implemented through a dual-feedback loop system. The inner loop utilizes Q-learning, a model-free reinforcement learning technique, to optimize the Hamilton-Jacobi-Bellman (HJB) equation and derive an appropriate control solution. The outer loop leverages this derived control solution to generate parameters for the reward function, which are subsequently integrated into the HJB equation. The ultimate control policy is deduced from the final reward function obtained …
Enhancing Security In Modern Medical Devices: The Medicalharm Methodology And Cyberllama2, Emmanuel Kwarteng
Enhancing Security In Modern Medical Devices: The Medicalharm Methodology And Cyberllama2, Emmanuel Kwarteng
Dissertations (1934 -)
With the rapid growth of Modern Medical Devices (MMDs) and their increasing connectivity to enhance patient care, concerns about security, privacy, and safety are paramount. If compromised, these devices can expose sensitive patient information and harm patients. Therefore, securing MMDs against cyber-attacks is critical. Threat modeling, mandated by the FDA as a premarket submission requirement in the MMD domain, serves as the first defense mechanism. However, our investigation of 119 participants from various MMD manufacturing companies revealed a need for a tailored threat modeling methodology that considers both patient safety and device complexity. To address this, we present MEDICALHARM, a …
Freedom As The Physical Notion. Mechanics Of A Material Point, Michael Vigdorowitsch
Freedom As The Physical Notion. Mechanics Of A Material Point, Michael Vigdorowitsch
Karbala International Journal of Modern Science
This is a novel conceptual attempt to introduce freedom as a consistent physical notion. The present consideration is limited to mechanics of a material point. Adapted to physical representation, freedom is tested throughout the paper to conform to its general perception. It is first tried on such physical notions (but not restricted to) as potency of a set, Lagrangian, action, degrees of freedom. Defined as angular and essentially nonlinear variable, it appears to be dual as that the domain affords and that the material point possesses within the domain, not necessarily equal to one another. Freedom has to degrade if …
Efficient Deep Neural Network Compression For Environmental Sound Classification On Microcontroller Units, Shan Chen, Na Meng, Haoyuan Li, Weiwei Fang
Efficient Deep Neural Network Compression For Environmental Sound Classification On Microcontroller Units, Shan Chen, Na Meng, Haoyuan Li, Weiwei Fang
Turkish Journal of Electrical Engineering and Computer Sciences
Environmental sound classification (ESC) is one of the important research topics within the non-speech audio classification field. While deep neural networks (DNNs) have achieved significant advances in ESC recently, their high computational and memory demands render them highly unsuitable for direct deployment on resource-constrained Internet of Things (IoT) devices based on microcontroller units (MCUs). To address this challenge, we propose a novel DNN compression framework specifically designed for such devices. On the one hand, we leverage pruning techniques to significantly compress the large number of model parameters in DNNs. To reduce the accuracy loss that follows pruning, we propose a …
Network Intrusion Detection Based On Machine Learning Strategies: Performance Comparisons On Imbalanced Wired, Wireless, And Software-Defined Networking (Sdn) Network Traffics, Hi̇lal Hacilar, Zafer Aydin, Vehbi̇ Çağri Güngör
Network Intrusion Detection Based On Machine Learning Strategies: Performance Comparisons On Imbalanced Wired, Wireless, And Software-Defined Networking (Sdn) Network Traffics, Hi̇lal Hacilar, Zafer Aydin, Vehbi̇ Çağri Güngör
Turkish Journal of Electrical Engineering and Computer Sciences
The rapid growth of computer networks emphasizes the urgency of addressing security issues. Organizations rely on network intrusion detection systems (NIDSs) to protect sensitive data from unauthorized access and theft. These systems analyze network traffic to detect suspicious activities, such as attempted breaches or cyberattacks. However, existing studies lack a thorough assessment of class imbalances and classification performance for different types of network intrusions: wired, wireless, and software-defined networking (SDN). This research aims to fill this gap by examining these networks’ imbalances, feature selection, and binary classification to enhance intrusion detection system efficiency. Various techniques such as SMOTE, ROS, ADASYN, …
Enrichment Of Turkish Question Answering Systems Using Knowledge Graphs, Okan Çi̇ftçi̇, Fati̇h Soygazi̇, Selma Teki̇r
Enrichment Of Turkish Question Answering Systems Using Knowledge Graphs, Okan Çi̇ftçi̇, Fati̇h Soygazi̇, Selma Teki̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Recent capabilities of large language models (LLMs) have transformed many tasks in Natural Language Processing (NLP), including question answering. The state-of-the-art systems do an excellent job of responding in a relevant, persuasive way but cannot guarantee factuality. Knowledge graphs, representing facts as triplets, can be valuable for avoiding errors and inconsistencies with real-world facts. This work introduces a knowledge graph-based approach to Turkish question answering. The proposed approach aims to develop a methodology capable of drawing inferences from a knowledge graph to answer complex multihop questions. We construct the Beyazperde Movie Knowledge Graph (BPMovieKG) and the Turkish Movie Question Answering …
A New Approach: Ordinal Predictive Maintenance With Ensemble Binary Decomposition (Opmeb), Ozlem Ece Yurek, Derya Birant
A New Approach: Ordinal Predictive Maintenance With Ensemble Binary Decomposition (Opmeb), Ozlem Ece Yurek, Derya Birant
Turkish Journal of Electrical Engineering and Computer Sciences
Predictive maintenance (PdM), a fundamental element of modern industrial systems, employs machine learning to monitor equipment conditions, estimate failure probabilities, and optimize maintenance schedules. Its core objective is to enhance equipment reliability, extend lifespan, and minimize costs through data-driven insights by enabling efficient maintenance scheduling, reducing downtime, and optimizing resource allocation. In this paper, we propose a novel ordinal predictive maintenance with ensemble binary decomposition (OPMEB) method for the PdM domain, considering the hierarchical nature of class labels reflecting the machine's health status, including categories like healthy, low risk, moderate risk, and high risk. The proposed OPMEB method was validated …
A Real-Time Embedded System Designed For Nilm Studies With A Novel Competitive Decision Process Algorithm, Sai̇d Mahmut Çinar, Rasi̇m Doğan, Emre Akarslan
A Real-Time Embedded System Designed For Nilm Studies With A Novel Competitive Decision Process Algorithm, Sai̇d Mahmut Çinar, Rasi̇m Doğan, Emre Akarslan
Turkish Journal of Electrical Engineering and Computer Sciences
This paper explores the determination of any load or load combination in a power system at any moment. This process requires measurements at the main electric utility service entry of a house, known as nonintrusive measurement. To accurately identify loads, total harmonic distortion, RMS, third harmonic currents, and power consumption are considered their fingerprints. Based on these fingerprints, an algorithm called the competitive decision process is developed and integrated into an embedded system. This algorithm has a two-level decision mechanism. In the first stage, the winner loads with the highest similarity scores from each feature are determined, and the loads …
Ensemble Learning For Accurate Prediction Of Heart Sounds Using Gammatonegram Images, Sinam Ashinikumar Singh, Sinam Ajitkumar Singh, Aheibam Dinamani Singh
Ensemble Learning For Accurate Prediction Of Heart Sounds Using Gammatonegram Images, Sinam Ashinikumar Singh, Sinam Ajitkumar Singh, Aheibam Dinamani Singh
Turkish Journal of Electrical Engineering and Computer Sciences
The analysis of heart sound signals constitutes a pivotal domain in healthcare, with the prediction of imbalanced heart sounds offering critical diagnostic insights. However, the inherent diversity in cardiac sound patterns presents a substantial challenge in predicting imbalanced signals. Many scientific disciplines have focused a great deal of emphasis on the problem of class inequality. We introduce an ensemble learning approach employing a convolutional neural network model-based deep learning algorithm to effectively tackle the challenges associated with predicting imbalanced heart sound signals. We use a Gammatone filter bank to extract relevant features from the heard sound signal. Our approach leverages …
Multi-Label Voice Disorder Classification Using Raw Waveforms, Gökay Di̇şken
Multi-Label Voice Disorder Classification Using Raw Waveforms, Gökay Di̇şken
Turkish Journal of Electrical Engineering and Computer Sciences
Automated voice disorder systems that distinguish pathological voices from healthy ones have been developed with the aid of machine learning methods. Both clinicians and patients can benefit from these systems as they provide many advantages, compared to the invasive techniques. These systems can produce binary (healthy/pathological) or multi-class (healthy/selected pathologies) decisions. However, multiple disorders might exist in an individual’s voice. Multi-label classification should be considered in such cases. By this time, only a single report is available on this topic, where hand-crafted features were used, and a data augmentation technique was utilized to overcome class imbalances. In this study, a …
Detection And Classification Of Unauthorized Use Of Irrigation Motors In Agricultural Irrigation, Önder Ci̇velek, Sedat Görmüş, Hali̇l İbrahi̇m Okumuş, Orhan Gazi̇ Kederoglu
Detection And Classification Of Unauthorized Use Of Irrigation Motors In Agricultural Irrigation, Önder Ci̇velek, Sedat Görmüş, Hali̇l İbrahi̇m Okumuş, Orhan Gazi̇ Kederoglu
Turkish Journal of Electrical Engineering and Computer Sciences
The decarbonisation of electricity generation requires the real-time monitoring and control of grid components in order to efficiently and timely dispatch demand. This highly automated system, known as the Smart Grid, relies on smart or sensor-equipped distribution network components to optimise energy flow and minimise losses. However, energy theft, a major obstacle to efficient resource utilisation, poses a significant challenge to achieving this goal. This study proposes and evaluates a real-time telemetry and control system designed to mitigate energy theft in agricultural irrigation applications. The system increases energy efficiency by tracking the energy use in agricultural irrigation. The key challenge …
A New Dynamic Classifier Selection Method For Text Classification, İsmai̇l Terzi̇, Alper Kürşat Uysal
A New Dynamic Classifier Selection Method For Text Classification, İsmai̇l Terzi̇, Alper Kürşat Uysal
Turkish Journal of Electrical Engineering and Computer Sciences
The primary objective of employing multiple classifier systems (MCS) in pattern recognition is to enhance classification accuracy. Dynamic classifier selection (DCS) and dynamic ensemble selection (DES) are two purposeful forms of multiple classifier systems. While DES involves the selection of a classifier set followed by decision combination, DCS opts for the choice of a single competent classifier, eliminating the necessity for classifier combination. As a consequence, DCS methods exhibit superior efficiency in terms of processing time and memory usage compared to DES methods. Moreover, a substantial performance gap exists between the performance of Oracle and both DES and DCS methods. …
Survey Of Space Professionals’ Perception Of Satellite Cybersecurity From 2012 To 2022: Decision-Makers’ Thoughts On Satellite Cybersecurity Evolving, Rachel C. Jones
Survey Of Space Professionals’ Perception Of Satellite Cybersecurity From 2012 To 2022: Decision-Makers’ Thoughts On Satellite Cybersecurity Evolving, Rachel C. Jones
Aerospace Sciences Student Publications
Cyberattacks on space assets are often portrayed in vague terms of doubt and mystery. Several claims depict satellites being compromised or attacked, but little corroboration has been published or made publicly available. As the commercial space industry grows, increased concern with space cybersecurity will prompt commercial satellite decision-makers to analyze the often-undefined risk of cyberattacks against satellites. This article identifies and characterizes the nature of cybersecurity risks to space assets and postulates why space professionals might not prioritize cybersecurity. Additional information was captured from a decadal survey of space professionals conducted in 2012 and 2022. The results show a rise …
The Potential Influence Of Immune Modulatory Molecules (Tgf-Βiii And Ctla-4) In Pathogenicity Of Pcos, Mustafa Riyadh Abdullah, Hazima Mossa Alabassi
The Potential Influence Of Immune Modulatory Molecules (Tgf-Βiii And Ctla-4) In Pathogenicity Of Pcos, Mustafa Riyadh Abdullah, Hazima Mossa Alabassi
Karbala International Journal of Modern Science
Polycystic ovary syndrome (PCOS) is characterised by chronic anovulation, hyperandrogenism, polycystic ovaries, and immunological dysregulation. Immune homeostasis and inflammation management require immune functions. T-regulatory cells (Tregs) regulate PCOS's immune system, inflammation, insulin resistance, ovarian function, and homeostasis. Transforming growth factor βIII (TGF-βIII) and Cytotoxic-T-lymphocyte-associated-protein-4 (CTLA-4) receptors on the surfaces of Treg cells are important for controlling the immune system. The study included 68 PCOS patients and 22 non-PCOS women controls aged 20–45. The waist-hip ratio (WHR) determines obesity. We evaluated serum levels and gene expression of TGF-βIII and CTLA-4 via ELISA and real-time PCR. Women with PCOS had significantly higher …
Enhanced Optoelectronics Performance Of Hybrid Self Power Photodetectors Go: Tio2- Ad / N-Si Heterojunctions, Mohammed J. Alsultani, Maysoon F. Alias
Enhanced Optoelectronics Performance Of Hybrid Self Power Photodetectors Go: Tio2- Ad / N-Si Heterojunctions, Mohammed J. Alsultani, Maysoon F. Alias
Karbala International Journal of Modern Science
A GO:TiO2/n-Si heterostructure has been submerged in an anthocyanin dye solution that extracted from the red cabbage plant creates a high responsivity, self-powered UV, and visible photodetectors fabricated by the spray pyrolysis technique. The GO concentrations are varied, whereas TiO2 is fixed. Thin films' structure, shape, and optical characteristics were examined using X-ray diffraction, field emission scanning electron microscopy, and UV-Vis spectrophotometers respectively. Island-like polycrystalline film powders with grain boundaries and granular shapes are created. Two direct energy gaps between 3.33-3.02 and 2.39-2.04 eV exist in all films. J-V characteristics were examined. The saturation current density (J …
Transforming Libraries Through Engagement: Lessons From A Library Ai Interest Group, Lily Dubach, Rachel Vacek
Transforming Libraries Through Engagement: Lessons From A Library Ai Interest Group, Lily Dubach, Rachel Vacek
Faculty Scholarship and Creative Works
Learn how one academic library is engaging with its employees to explore the latest trends, tools, and topics in AI through an interest group (IG). Through stimulating discussions, webinars, guest speakers, demos, and sharing of experiences with AI, the IG empowers its library community to explore and become more comfortable with AI. This session caters to varying levels of AI expertise. Challenges, successes, and valuable insights for deeper engagement will be shared so you can learn how to establish a similar initiative in your library.
Empowering Traditional Industries With Digital Intelligence For Transformation And Upgrading, Jiyuan Zang, Huanyong Ji, Qingxue Huang
Empowering Traditional Industries With Digital Intelligence For Transformation And Upgrading, Jiyuan Zang, Huanyong Ji, Qingxue Huang
Bulletin of Chinese Academy of Sciences (Chinese Version)
Traditional industries are the basic support and driving force for the high-quality development of the economy. Digital intelligence is an important lever for traditional industries to achieve the transformation of old and new kinetic energy and the leapfrogging of the global value chain. This study firstly deconstructs the rich connotations of digital intelligence from the perspectives of digitalization, networkization, and intelligentization. Secondly, it analyzes the transformation mechanism and various pathways through which digital intelligence impacts traditional industries. Thirdly, it analyzes the barriers faced by traditional industries in the process of adopting digital intelligence technologies. Finally, this study puts forward four …
Innovation Path At Institute For Protein Design Of Washington University And Its Enlightenment For Construction Of New Life Sciences R&D Institutions, Runzhou Zhao, Ming Ni, Yunzhi Fa, Xiaochen Bo, Jian Jiao
Innovation Path At Institute For Protein Design Of Washington University And Its Enlightenment For Construction Of New Life Sciences R&D Institutions, Runzhou Zhao, Ming Ni, Yunzhi Fa, Xiaochen Bo, Jian Jiao
Bulletin of Chinese Academy of Sciences (Chinese Version)
The Institute for Protein Design (IPD) at the University of Washington is a pioneering local and state-supported non-profit scientific research institution. Since its establishment in 2012, IPD has seized the opportunity of AI for Science and open science, and continuously enhanced its capabilities of fundamental innovations, breakthrough technologies, and industrial impact. We summarized five factors contributing to IPD’s development, including focusing on the cutting-edge issues of basic scientific research to gain a first-mover advantage and then further expand, integrating AI-enhanced digital tools and solid experimental validations, facilitating the integrated development of innovation and industrial chains, giving full play to the …
Constructing Problemology That Is Symmetrical To Methodology—Taking Computer Science As An Example, Yuhang Liu, Yunquan Zhang
Constructing Problemology That Is Symmetrical To Methodology—Taking Computer Science As An Example, Yuhang Liu, Yunquan Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
Institutionalized scientific research encourages free exploration while emphasizing the organization and coordination of research activities. Nevertheless, overcoming dispersion and repetition in the research process is an urgent problem to be addressed. Taking computer science as an example, to implement the problem-oriented concept, this study proposes constructing problemology that is symmetrical to methodology. Methodology is the important manifestation of scientific and technological achievements, and symmetrically, problemology is needed by the scientific research community. The problematique is a crucial component of problemology, representing the level of understanding of problems within the scientific research community. Through problematique as a medium, it connects, bridges, …
Strategic Study On Leading Construction Of Modern Agricultural System By Technology Innovation, Yan Yan, Xurong Mei, Xiudong Wang
Strategic Study On Leading Construction Of Modern Agricultural System By Technology Innovation, Yan Yan, Xurong Mei, Xiudong Wang
Bulletin of Chinese Academy of Sciences (Chinese Version)
Technology innovation is the fundamental solution to build a modern agricultural system, and it is also an important support for building the large base, large enterprise, and large industry of modern agriculture and achieving the modernization of material equipment, technology, management, agricultural informatization, and sustainable resource utilization of agriculture. This paper explains the scientific concepts and logical relationships of the agricultural production system, industrial system and management system, which are the main components of a modern agricultural system. It emphasizes that ensuring food security, promoting industrial integration and upgrading, and cultivating leading enterprises are current key tasks. Nevertheless, from the …
A New Optimization Approach Based On Neural Architecture Search To Enhance Deep U-Net For Efficient Road Segmentation, Narges Saeedizadeh, Seyed Mohammad Jafar Jalali, Burhan Khan, Parham Mohsenzadeh Kebria, Shady Mohamed
A New Optimization Approach Based On Neural Architecture Search To Enhance Deep U-Net For Efficient Road Segmentation, Narges Saeedizadeh, Seyed Mohammad Jafar Jalali, Burhan Khan, Parham Mohsenzadeh Kebria, Shady Mohamed
Research outputs 2022 to 2026
Neural Architecture Search (NAS) has significantly improved the accuracy of image classification and segmentation. However, these methods concentrate on finding segmentation structures for natural or medical applications. In this study, we introduce a NAS approach based on gradient optimization to identify ideal cell designs for road segmentation. To the best of our knowledge, this work represents the first application of gradient-based NAS to road extraction. Taking insight from the U-Net model and its successful variations in different image segmentation tasks, we propose NAS-enhanced U-Net, illustrated by an equal number of cells in both encoder and decoder levels. While cross-entropy combined …
Memetic Memory As Vital Conduits Of Troublemakers In Digital Culture, Alexander O. Smith, Jordan Loewen-Colón
Memetic Memory As Vital Conduits Of Troublemakers In Digital Culture, Alexander O. Smith, Jordan Loewen-Colón
School of Information Studies - Post-doc and Student Scholarship
Recent fears of data capitalism and colonialism often argue using implicit assumptions about cybernetic technology’s ability to automate data about culture. As such, the level of data granularity made possible by cybernetic engineering can be used to dominate society and culture. Here we unpack these implicit assumptions about the datafication of culture through memes, which both act as cultural data and cultural memory. Using Alexander Galloway’s critical method of protocological analysis and descriptions of media tactics, we respond to fears of cybernetic domination. Protocols – the source by which cybernetic technologies enable automated datafication – enables us to respond to …
Using Cache Files To Improve The Efficiency Of The Ucgretina Simulation Code, Blake Mcnulty
Using Cache Files To Improve The Efficiency Of The Ucgretina Simulation Code, Blake Mcnulty
Physics and Astronomy Summer Fellows
UCGretina is a program that is used to simulate the Gretina gamma-ray tracking array used in experiments at the Facility for Rare Isotope Beams (FRIB) to collect gamma rays produced in reactions such as proton scattering. This is done by generating a simulation of the beam particles used and sending them into a simulated recreation that mimics the experimental environment. My job this summer was to tackle a major issue that the program had which is the speed or efficiency at which it ran. The main issue was that it would take days for certain simulation sets to run which …
A Qualitative Study On The Integration Of Artificial Intelligence In Cultural Heritage Conservation, Kholoud Ghaith, James Hutson
A Qualitative Study On The Integration Of Artificial Intelligence In Cultural Heritage Conservation, Kholoud Ghaith, James Hutson
Faculty Scholarship
The widespread adoption of generative artificial intelligence (GAI) technologies heralds an era of expanding possibilities in the domain of cultural heritage conservation. This paradigm shift is marked by a confluence of innovative methodologies, including digital twin mapping, digital archiving, and enhanced preservation strategies, aimed at safeguarding the vestiges of our shared past. The application of AI within this field represents a frontier where technology and tradition intersect, offering new vistas for the preservation of historical structures and artifacts that are at risk of deterioration or oblivion. This article endeavors to elucidate the perspectives of professionals within the conservation domain on …
Empowering Informed Decision-Making In Mental Health Care: A Web-Based Recommendation System For Mobile App Selection, Md Romael Haque
Empowering Informed Decision-Making In Mental Health Care: A Web-Based Recommendation System For Mobile App Selection, Md Romael Haque
Dissertations (1934 -)
In 2022, 23.1% of adults in the United States (77 million individuals) were affected by mental health (MH) concerns. Due to the inaccessibility and high cost of traditional treatment, around 55% of people with severe mental illnesses do not receive treatment. Mental health concerns are prevalent, affecting a significant portion of the population in the United States. Traditional treatment options are often inaccessible and expensive, leaving many people without essential mental healthcare. However, the rise of mobile technologies has given rise to a promising solution: mobile mental health applications (MMHAs). These apps offer greater accessibility and affordability, potentially expanding mental …
Gender-Specific Mental Health Outcomes In Central America: A Natural Experiment, Thea Nagasuru
Gender-Specific Mental Health Outcomes In Central America: A Natural Experiment, Thea Nagasuru
Computer Science Summer Fellows
While COVID lockdown measures have had varying effects on the mental health of different demographics, several bodies of research have noted their disparate effect on women. Why is women's mental health more negatively impacted by lockdown measures, and how much more are they impacted than men? How can we predict and mitigate these negative effects on women? This paper aims to contribute to answering those questions by comparing COVID stringency measures and their effect on the gap in depression rates between men and women in two neighboring countries: Nicaragua and Honduras.
From Classroom Interaction To Academic Success: Tracing The Mediating Role Of Effective Communication In Faculty-Student Dynamics, Nadia Dahmani, Wael Ali, Mohammed Aboelenein, Mohammad A.K. Alsmairat, Mursal Faizi
From Classroom Interaction To Academic Success: Tracing The Mediating Role Of Effective Communication In Faculty-Student Dynamics, Nadia Dahmani, Wael Ali, Mohammed Aboelenein, Mohammad A.K. Alsmairat, Mursal Faizi
All Works
This paper aimed to determine the impact of faculty communication style, student proactiveness, and academic discipline on student academic performance and student-faculty relationship quality in the United Arab Emirates (UAE) higher education context. This study also aimed to contribute to the literature by verifying the mediating impact of communication effectiveness between the selected factors. Using a cross-sectional survey design, the study sample comprised 193 university students, and it was analyzed using partial least squares structural equation modeling (PLS-SEM). The results revealed that academic discipline and the professor’s communication style enhanced communication effectiveness, whereas student proactiveness had a minimal effect. The …
Riesz Particle Markov Chain Monte Carlo Methods, Xiongming Dai
Riesz Particle Markov Chain Monte Carlo Methods, Xiongming Dai
LSU Doctoral Dissertations
Markov chain Monte Carlo (MCMC) methods are simulations that explore complex statistical distributions, while bypassing the cumbersome requirement of a specific analytical expression for the target. This stochastic exploration of an uncertain parameter space comes at the expense of a large number of ``burn-in'' samples, and the computational complexity leads to the curse of dimensionality. Although at the exploration level, some methods have been proposed to accelerate the convergence of the algorithm, such as tempering, Hamiltonian Monte Carlo, Rao-redwellization, and scalable methods for better performance, they cannot avoid the stochastic nature of this exploration. We develop algorithms for the energy …
Using Gamification To Enhance Mastery Of Network Security Concepts, Kevin Hilliard, Xiaohong Yuan, Kelvin Bryant, Jinsheng Xu, Jinghua Zhang
Using Gamification To Enhance Mastery Of Network Security Concepts, Kevin Hilliard, Xiaohong Yuan, Kelvin Bryant, Jinsheng Xu, Jinghua Zhang
Journal of Cybersecurity Education, Research and Practice
Gamification has proven to be effective in engaging and encouraging people to work towards and achieve goals. Many students struggle to focus on schoolwork, due to a lack of interest, lack of understanding, or other factors unique to the student. Applying gamification elements to education can help engage these students in learning their course material and help them excel academically. This study examines the effectiveness of using gamification techniques to enhance the learning experience in college Computer Science courses. A video game application is utilized to review and reinforce cybersecurity concepts that students have already been taught in class. Previous …
Collaborative Pathways To Cybersecurity Excellence: Insights From Industry And Academia In The Southeastern Us, Humayun Zafar, Carole L. Hollingsworth, Tridib Bandyopadhyay, Adriane B. Randolph
Collaborative Pathways To Cybersecurity Excellence: Insights From Industry And Academia In The Southeastern Us, Humayun Zafar, Carole L. Hollingsworth, Tridib Bandyopadhyay, Adriane B. Randolph
Journal of Cybersecurity Education, Research and Practice
This research article examines conversations happening between cybersecurity academics and industry leaders with a goal to improve the development of cybersecurity professionals. We specifically focus on efforts in the Southeast region of the United States. The discussion features insights from a panel consisting of an academic cybersecurity researcher, a Chief Information Officer (CIO) of a leading technology company with over 1,000 employees, and a CIO of a financial services firm, which employs over 3,000 people. The discussion sheds light on the challenges and opportunities involved in aligning cybersecurity programs with industry requirements. This article explores strategies for academia and businesses …