Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

54,951 Full-Text Articles 71,506 Authors 20,935,862 Downloads 376 Institutions

All Articles in Computer Sciences

Faceted Search

54,951 full-text articles. Page 6 of 1996.

Navigating The Digital Frontier: The Intersection Of Cybersecurity Challenges And Young Adult Life, Hannarae Lee 2024 Bridgewater State University

Navigating The Digital Frontier: The Intersection Of Cybersecurity Challenges And Young Adult Life, Hannarae Lee

International Journal of Cybersecurity Intelligence & Cybercrime

Papers from this issue advocate for empowering young adults with knowledge and tools to navigate cyberspace safely, emphasizing the necessity of heightened cybersecurity measures and proactive education. As we advance into the digital abyss, this call becomes imperative, ensuring that the young adults' experience remains a journey of growth and enlightenment, unaffected by the shadows of unseen online threats.


The Need For A Cybersecurity Education Program For Internet Users With Limited English Proficiency: Results From A Pilot Study, Fawn T. Ngo, Rustu Deryol, Brian Turnbull, Jack Drobisz 2024 University of South Florida

The Need For A Cybersecurity Education Program For Internet Users With Limited English Proficiency: Results From A Pilot Study, Fawn T. Ngo, Rustu Deryol, Brian Turnbull, Jack Drobisz

International Journal of Cybersecurity Intelligence & Cybercrime

According to security experts, cybersecurity education and awareness at the user level are key in combating cybercrime. Hence, in the U.S., cybersecurity and Internet safety workshops, classes, and resources targeting children, adolescents, adults, and senior citizens abound. However, most cybercrime prevention programs are only available in English, thus, ignoring a substantial proportion of Internet users and potential cybercrime victims—Internet users with limited English proficiency (LEP). Yet, successfully combating cybercrime requires that all computer and Internet users, regardless of their language abilities and skills, have access to pertinent cybersecurity information and resources to protect themselves online. This paper presents the results …


Book Review: Tracers In The Dark: The Global Hunt For The Crime Lords Of Cryptocurrency, Marion Jones 2024 NA

Book Review: Tracers In The Dark: The Global Hunt For The Crime Lords Of Cryptocurrency, Marion Jones

International Journal of Cybersecurity Intelligence & Cybercrime

Doubleday released Andy Greenberg’s Tracers in the Dark: The Global Hunt for the Crime Lords of Cryptocurrency in November 2022. Through vivid case studies of global criminal investigations, the book dispels myths about the anonymizing power of cryptocurrency. The book details how the ability to identify cryptocurrency users and payment methods successfully brought down several large criminal empires, while also highlighting the continuous cat-and-mouse game between law enforcement officials and criminal actors using cryptocurrency. The book is an excellent resource for law enforcement officials, academics, and general cybersecurity practitioners interested in cryptocurrency-related criminal activities and law enforcement techniques.


The Impact Of Artificial Intelligence And Machine Learning On Organizations Cybersecurity, Mustafa Abdulhussein 2024 Liberty University

The Impact Of Artificial Intelligence And Machine Learning On Organizations Cybersecurity, Mustafa Abdulhussein

Doctoral Dissertations and Projects

As internet technology proliferate in volume and complexity, the ever-evolving landscape of malicious cyberattacks presents unprecedented security risks in cyberspace. Cybersecurity challenges have been further exacerbated by the continuous growth in the prevalence and sophistication of cyber-attacks. These threats have the capacity to disrupt business operations, erase critical data, and inflict reputational damage, constituting an existential threat to businesses, critical services, and infrastructure. The escalating threat is further compounded by the malicious use of artificial intelligence (AI) and machine learning (ML), which have increasingly become tools in the cybercriminal arsenal. In this dynamic landscape, the emergence of offensive AI introduces …


Blockchain Applications In Higher Education Based On The Nist Cybersecurity Framework, Brady Lund Ph.D. 2024 University of North Texas

Blockchain Applications In Higher Education Based On The Nist Cybersecurity Framework, Brady Lund Ph.D.

Journal of Cybersecurity Education, Research and Practice

This paper investigates the integration of blockchain technology into core systems within institutions of higher education, utilizing the National Institute of Standards and Technology’s (NIST) Cybersecurity Framework as a guiding framework. It supplies definitions of key terminology including blockchain, consensus mechanisms, decentralized identity, and smart contracts, and examines the application of secure blockchain across various educational functions such as enrollment management, degree auditing, and award processing. Each facet of the NIST Framework is utilized to explore the integration of blockchain technology and address persistent security concerns. The paper contributes to the literature by defining blockchain technology applications and opportunities within …


Improving Belonging And Connectedness In The Cybersecurity Workforce: From College To The Profession, Mary Beth Klinger 2024 College of Southern Maryland

Improving Belonging And Connectedness In The Cybersecurity Workforce: From College To The Profession, Mary Beth Klinger

Journal of Cybersecurity Education, Research and Practice

This article explores the results of a project aimed at supporting community college students in their academic pursuit of an Associate of Applied Science (AAS) degree in Cybersecurity through mentorship, collaboration, skill preparation, and other activities and touch points to increase students’ sense of belonging and connectedness in the cybersecurity profession. The goal of the project was focused on developing diverse, educated, and skilled cybersecurity personnel for employment within local industry and government to help curtail the current regional cybersecurity workforce gap that is emblematic of the lack of qualified cybersecurity personnel that presently exists nationwide. Emphasis throughout the project …


University Of Johannesburg Institutional Repository Cybersecurity Output: 2015-2021 Interdisciplinary Study, Mancha J. Sekgololo 2024 University of Johannesburg

University Of Johannesburg Institutional Repository Cybersecurity Output: 2015-2021 Interdisciplinary Study, Mancha J. Sekgololo

Journal of Cybersecurity Education, Research and Practice

This study examines cybersecurity awareness in universities by analyzing related research output across different disciplines at the University of Johannesburg. The diffusion of innovation theory is used in this study as a theoretical framework to explain how cybersecurity awareness diffuses across disciplines. The University of Johannesburg Institutional Repository database was the data source for this study. Variations in cybersecurity keyword searches and topic modeling techniques were used to identify the frequency and distribution of research output across different disciplines. The study reveals that cybersecurity awareness has diffused across various disciplines, including non-computer science disciplines such as business, accounting, and social …


Brain-Inspired Continual Learning: Robust Feature Distillation And Re-Consolidation For Class Incremental Learning, Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool 2024 Rowan University

Brain-Inspired Continual Learning: Robust Feature Distillation And Re-Consolidation For Class Incremental Learning, Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool

Henry M. Rowan College of Engineering Faculty Scholarship

Artificial intelligence and neuroscience have a long and intertwined history. Advancements in neuroscience research have significantly influenced the development of artificial intelligence systems that have the potential to retain knowledge akin to humans. Building upon foundational insights from neuroscience and existing research in adversarial and continual learning fields, we introduce a novel framework that comprises two key concepts: feature distillation and re-consolidation. The framework distills continual learning (CL) robust features and rehearses them while learning the next task, aiming to replicate the mammalian brain's process of consolidating memories through rehearsing the distilled version of the waking experiences. Furthermore, the proposed …


Investigations Of The Eutectic Formation And Skin Rejuvenation By Hyaluronan - Kojic Acid Dipalmitate System, Syed Waqar Hussain Shah, Sumbal Imran, Iram Bibi, Kashif Ali, Nadia Bashir 2024 Department of Chemistry, Hazara University, Mansehra, Pakistan

Investigations Of The Eutectic Formation And Skin Rejuvenation By Hyaluronan - Kojic Acid Dipalmitate System, Syed Waqar Hussain Shah, Sumbal Imran, Iram Bibi, Kashif Ali, Nadia Bashir

Karbala International Journal of Modern Science

Eutectic phenomenon has been investigated in binary system based on biopolymer hyaluronan (HN) and kojic acid dipalmitate (KAD). Solid-liquid phase diagram showed a significant dependence of melting points on weight fraction of KAD up to KAD < 0.5. A negligible regain to melting temperature of pure KAD occurred later. Simulations of molecular mechanics using a four-unit segment of HN and KAD revealed the interaction between carbonyl of KAD with 4-OH on N-acetylglucosamine unit of oligomer. Infrared vibrational spectroscopy also endorsed the existence of a weakly interacting system. Such behavior was expected due to steric hinderance and rigidity of biopolymer. The thermal decomposition temperature of HN (i.e., 215 °C) was increased to 322 °C in HK50 having HN and KAD in 1:50 w/w. Bioelectric impedance analysis revealed that these green materials could promote skin health in humans.


Synthesis And Characterization Of Renewable Heterogeneous Catalyst Zno Supported Biogenic Silica From Pineapple Leaves Ash For Sustainable Biodiesel Conversion, Nadila Pratiwi, Suriati Eka Putri, Yulia Shinta, Arya Ibnu Batara, Diana Eka Pratiwi, Abd Rahman, Nur Ahmad, Heryanto Heryanto 2024 Department of Chemistry, Faculty of Mathematics and Natural Science, Universitas Negeri Makassar, Makassar, South Sulawesi, Indonesia;

Synthesis And Characterization Of Renewable Heterogeneous Catalyst Zno Supported Biogenic Silica From Pineapple Leaves Ash For Sustainable Biodiesel Conversion, Nadila Pratiwi, Suriati Eka Putri, Yulia Shinta, Arya Ibnu Batara, Diana Eka Pratiwi, Abd Rahman, Nur Ahmad, Heryanto Heryanto

Karbala International Journal of Modern Science

This study reports on the first case of the low-cost and environmentally friendly ZnO/SiO2 heterogeneous catalyst from pineapple leaves ash (PLA). Catalyst shows excellent performance in catalyzing the transesterification of waste cooking oil (WCO) with methanol for biodiesel conversion. This study focuses on assessing the influence of Zn content on physicochemical characteristics, using XRD, FTIR, SEM, and N2 adsorption-desorption methods. In addition, three different Zn content levels (20, 25, and 30 %wt) were applied. The results showed that all ZnO/SiO2 samples exhibited characteristics suitable for use as catalyst with an average crystallite size of 31.83-34.15 nm, and a surface area …


Ai-Based Investigation And Mitigation Of Rain Effect On Channel Performance With Aid Of A Novel 3d Slot Array Antenna Design For High Throughput Satellite System, Ali M. Al-Saegh, Fatma Taher, Taha A. Elwi, Mohammad Alibakhshikenari, Bal S. Virdee, Osama Abdullah, Salahuddin Khan, Patrizia Livreri, Abdulmajeed Al-Jumaily, Mohamed Fathy Abo Sree, Arkan Mousa Majeed, Lida Kouhalvandi, Zaid A. Abdul Hassain, Giovanni Pau 2024 Middle Technical University

Ai-Based Investigation And Mitigation Of Rain Effect On Channel Performance With Aid Of A Novel 3d Slot Array Antenna Design For High Throughput Satellite System, Ali M. Al-Saegh, Fatma Taher, Taha A. Elwi, Mohammad Alibakhshikenari, Bal S. Virdee, Osama Abdullah, Salahuddin Khan, Patrizia Livreri, Abdulmajeed Al-Jumaily, Mohamed Fathy Abo Sree, Arkan Mousa Majeed, Lida Kouhalvandi, Zaid A. Abdul Hassain, Giovanni Pau

All Works

Rain attenuation poses a significant challenge for high-throughput communication systems. In response, this paper introduces an artificial intelligence (AI) model designed for predicting and mitigating rain-induced impairments in high-throughput satellite (HTS) to land channels. The model is based on three AI algorithms developed using 3D antenna design to characterize, analyze, and mitigate rain-induced attenuation, optimizing channel quality specifically in the United Arab Emirates (UAE). The study evaluates various parameters, including rain-specific attenuation, effective slant path through rain, rain-induced attenuation, signal carrier-to-noise ratio, and symbol error rate, for five conventional modulation schemes: Quadrature Phase-Shift Keying (QPSK), 8-Phase Shift Keying (8-PSK), 16-Quadrature …


Music Genre Classification Capabilities Of Enhanced Neural Network Architectures, Joshua Engelkes 2024 University of Minnesota Morris

Music Genre Classification Capabilities Of Enhanced Neural Network Architectures, Joshua Engelkes

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

With the increase of digital music audio uploads, applications that deal with music information have been widely requested by streaming platforms. Automatic music genre classification is an important function of music recommendation and music search applications. Since the music genre categorization criteria continually shift, data-driven methods such as neural networks have been proven especially useful to music information retrieval. An enhanced CNN architecture, the Bottom-up Broadcast Neural Network, uses mel-spectrograms to push music data through a network where important low-level information is preserved. An enhanced RNN architecture, the Independent Recurrent Neural Network for Music Genre Classification, takes advantage of the …


Analysis And Recommendations For Energy Conservation And Carbon Emission Reduction In Industry Boosted By Digital Energy Management Systems, Duanyang GENG, Tong XU, Qinghua ZHU, Steve EVANS 2024 Institute for Manufacturing, Department of Engineering, University of Cambridge, Cambridge CB3 0FS, UK

Analysis And Recommendations For Energy Conservation And Carbon Emission Reduction In Industry Boosted By Digital Energy Management Systems, Duanyang Geng, Tong Xu, Qinghua Zhu, Steve Evans

Bulletin of Chinese Academy of Sciences (Chinese Version)

Energy consumption during production processes in the industry is a main source of carbon dioxide emissions. Therefore, for China’s dual-carbon goals, industrial enterprises need to focus on reducing energy waste to achieve energy-efficient production, thereby effectively reducing carbon emissions in industrial production. In recent years, with the continuous development and popularization of digital technology, digital energy management systems have played a crucial role in energy saving by visualizing invisible energy in the industry. In this context, this study first analyses the current status of digital energy management system applications in the UK, the US, Germany, and Sweden, summarizes their characteristics …


Key Elements, Mechanism Analysis And Evaluation Indicators Of Digital And Intelligent Integration Transformation And Development Of Manufacturing Industry, Xiaoqiang SUN, Xiuyun GAO, Yumei WANG 2024 College of Economics and Management, Qingdao University of Science and Technology, Qingdao 266061, China

Key Elements, Mechanism Analysis And Evaluation Indicators Of Digital And Intelligent Integration Transformation And Development Of Manufacturing Industry, Xiaoqiang Sun, Xiuyun Gao, Yumei Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The digital and intelligent integration transformation of manufacturing industry has become an important driving force for the high-quality development of traditional manufacturing enterprises. This study clarifies the main research context and key issues of scholars on the digital and intelligent integration transformation of manufacturing industry, refines the goals, main elements, and influencing factors of digital and intelligent integration transformation of manufacturing industry, builds a power network model for the transformation and development of digital and intelligent integration of manufacturing industry according to the system feedback principle of system dynamics, analyzes the mechanism of action between various elements of the system, …


Thoughts On Transformation Of Scientific And Technological Achievements In Field Of Information Technology, Ninghui SUN, Xiaojuan LI 2024 Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China

Thoughts On Transformation Of Scientific And Technological Achievements In Field Of Information Technology, Ninghui Sun, Xiaojuan Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

To promote the transformation of scientific and technological achievements is one of the key points of China’s national science and technology innovation policy. Nevertheless, due to the particularity, complexity, and professionalism of technological achievements, being difficult to transform scientific and technological achievements is a worldwide common problem. There are many issues worth discussing and exploring in China’s transformation of scientific and technological achievements, especially when it comes to whether research institutes can transform their achievements by establishing enterprises, the answers remain controversial. The authors intend to take the field of information technology as an example, by analyzing the advantages, disadvantages, …


Development Path And Policy Guarantee Of China's Advanced Manufacturing Industry Under Background Of Fourth Industrial Revolution, Chang WANG, Siyuan ZHOU, Hongjun GENG 2024 Business School, Central South University, Changsha 410083, China

Development Path And Policy Guarantee Of China's Advanced Manufacturing Industry Under Background Of Fourth Industrial Revolution, Chang Wang, Siyuan Zhou, Hongjun Geng

Bulletin of Chinese Academy of Sciences (Chinese Version)

How to seize the opportunity window opened by the fourth industrial revolution and enhance the international competitive advantage of advanced manufacturing has become an important issue concerned by existing research and policy practitioners. This study analyzes the background, characteristics, and influence of the fourth industrial revolution on the development of advanced manufacturing industry. Based on this, it discusses the development status and problems of four types of advanced manufacturing industries, including digitally empowered new infrastructure industries, intelligent manufacturing high-end equipment industries, brand-oriented new consumption industries, and science-based industries. The development paths of “fusion innovation”, “intelligent manufacturing upgrade”, “quality improvement”, and …


Path And Strategy Of Pollution And Carbon Reduction By Digitization In Electric Power Enterprises, Xiaohong CHEN, Runcheng TANG, Dongbin HU, Xuesong XU, Xiangbo TANG, Guodong YI, Weiwei ZHANG 2024 School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China Business School, Central South University, Changsha 410083, China

Path And Strategy Of Pollution And Carbon Reduction By Digitization In Electric Power Enterprises, Xiaohong Chen, Runcheng Tang, Dongbin Hu, Xuesong Xu, Xiangbo Tang, Guodong Yi, Weiwei Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

With the extensive application and innovation of digital technology in the energy sector, digital technology has become increasingly crucial for the power industry to achieve the goal of reducing pollution and carbon emissions. How digital technology enables electric power enterprises to achieve this goal has attracted much attention. Firstly, the study analyzes the progress of digital technology applications in pollution reduction and carbon reduction in electric power enterprises. Then, it identifies the existing problems in the current application of digital technology in the power industry for reducing pollution and carbon emissions. Finally, it explores the potential ways and approaches of …


Attribution Robustness Of Neural Networks, Sunanda Gamage 2024 Western University

Attribution Robustness Of Neural Networks, Sunanda Gamage

Electronic Thesis and Dissertation Repository

While deep neural networks have demonstrated excellent learning capabilities, explainability of model predictions remains a challenge due to their black box nature. Attributions or feature significance methods are tools for explaining model predictions, facilitating model debugging, human-machine collaborative decision making, and establishing trust and compliance in critical applications. Recent work has shown that attributions of neural networks can be distorted by imperceptible adversarial input perturbations, which makes attributions unreliable as an explainability method. This thesis addresses the research problem of attribution robustness of neural networks and introduces novel techniques that enable robust training at scale.

Firstly, a novel generic framework …


Butterworth Filter To Reduce Reactivity Fluctuations, Daniel Suescún-Díaz, Geraldyne Ule-Duque, Luis E. Cardoso-Páez 2024 Department of Natural Sciences, Avenida Pastrana, Universidad Surcolombiana, Neiva, Huila, Colombia

Butterworth Filter To Reduce Reactivity Fluctuations, Daniel Suescún-Díaz, Geraldyne Ule-Duque, Luis E. Cardoso-Páez

Karbala International Journal of Modern Science

In this study, we introduce the calculation of reactivity in nuclear reactors. The proposed method uses the Euler-Maclaurin series to approximate the integral in the inverse equation of point kinetics. The approximation is done with the first three terms, the first term represents the approximation of a zero-order sum, the second term the trapezoidal rule and the third term the first Bernoulli number. These three terms improve the approximation, along with an estimate of the neutron density using the prompt jump approximation. To reduce neutron density fluctuations, a second-order Butterworth filter for the reactivity calculation was implemented, which offers the …


Optimal Scheduling Strategy Of Virtual Power Plant With Carbon Emission And Carbon Penalty Considering Uncertainty Of Wind Power And Photovoltaic Power, Jijun Shui, Daogang Peng, Yankan Song, Qiang Zhou 2024 College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China

Optimal Scheduling Strategy Of Virtual Power Plant With Carbon Emission And Carbon Penalty Considering Uncertainty Of Wind Power And Photovoltaic Power, Jijun Shui, Daogang Peng, Yankan Song, Qiang Zhou

Journal of System Simulation

Abstract: To better meet the development needs of China's new power system, an optimal scheduling strategy of virtual power plant(VPP) with carbon emission and carbon penalty considering the uncertainty of wind power and photovoltaic power is proposed. The mathematical description of photovoltaic(PV), wind turbine(WT), combined heat and power(CHP) unit and energy storage system (ESS) is carried out, and a wind-solar output model considering the uncertainty is established. The scenario generation and reduction method is used to generate the typical scenario. To maximize the overall operation benefit of VPP, considering carbon emission cost and carbon penalty, an optimal scheduling model of …


Digital Commons powered by bepress