Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Singapore Management University (2245)
- Wright State University (862)
- Edith Cowan University (524)
- Old Dominion University (433)
- Brigham Young University (427)
-
- TÜBİTAK (349)
- Embry-Riddle Aeronautical University (346)
- San Jose State University (303)
- Technological University Dublin (271)
- Nova Southeastern University (269)
- Zayed University (244)
- Air Force Institute of Technology (231)
- University for Business and Technology in Kosovo (223)
- Missouri University of Science and Technology (218)
- Walden University (218)
- University of Nebraska - Lincoln (216)
- Kennesaw State University (212)
- Purdue University (205)
- Dartmouth College (185)
- California Polytechnic State University, San Luis Obispo (172)
- City University of New York (CUNY) (152)
- University of Nebraska at Omaha (151)
- University of Central Florida (150)
- New Jersey Institute of Technology (128)
- Chulalongkorn University (127)
- China Simulation Federation (126)
- Portland State University (123)
- University of South Florida (115)
- LSU New Orleans (111)
- University of Arkansas, Fayetteville (108)
- Keyword
-
- Machine learning (423)
- Artificial intelligence (351)
- Social media (248)
- Cybersecurity (240)
- Machine Learning (224)
-
- Security (198)
- Deep learning (195)
- Computer Science (178)
- Artificial Intelligence (175)
- Privacy (173)
- Twitter (164)
- Natural language processing (145)
- Computer science (133)
- AI (113)
- Education (110)
- Natural Language Processing (99)
- Technology (99)
- Digital forensics (95)
- Deep Learning (94)
- Sentiment analysis (90)
- Social Media (88)
- Data mining (87)
- Big data (86)
- College for Professional Studies (78)
- Generative AI (76)
- School of Computer & Information Science (75)
- Ontology (72)
- Information technology (70)
- Department of Computer Science and Engineering (69)
- Classification (68)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (2056)
- Theses and Dissertations (964)
- Kno.e.sis Publications (540)
- Turkish Journal of Electrical Engineering and Computer Sciences (349)
- CCAC Theses and Dissertations (245)
-
- All Works (243)
- Walden Dissertations and Doctoral Studies (217)
- Master's Projects (206)
- Journal of Digital Forensics, Security and Law (195)
- Computer Science Faculty Publications (179)
- Dissertations (156)
- Electronic Theses and Dissertations (136)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (127)
- Department of Computer Science Technical Reports (127)
- Journal of System Simulation (126)
- Computer Science Faculty Publications and Presentations (124)
- Computer Science and Engineering Faculty Publications (120)
- Computer Science Faculty Research & Creative Works (118)
- Faculty Publications (118)
- Australian Digital Forensics Conference (108)
- Conference papers (105)
- Annual ADFSL Conference on Digital Forensics, Security and Law (103)
- Journal of Informatics and Web Engineering (102)
- Research outputs pre 2011 (102)
- LSU New Orleans Theses and Dissertations (100)
- USF Tampa Graduate Theses and Dissertations (100)
- Theses (95)
- Computer Science & Engineering Syllabi (92)
- Computer Science: Faculty Publications and Other Works (92)
- Browse all Theses and Dissertations (91)
- Publication Type
Articles 1861 - 1890 of 13815
Full-Text Articles in Entire DC Network
Intelligent Algorithm Safety: Concepts, Scientific Problems And Prospects, Xueqi Cheng, Wei Chen, Huawei Shen, Shiguang Shan, Xilin Chen, Guojie Li
Intelligent Algorithm Safety: Concepts, Scientific Problems And Prospects, Xueqi Cheng, Wei Chen, Huawei Shen, Shiguang Shan, Xilin Chen, Guojie Li
Bulletin of Chinese Academy of Sciences (Chinese Version)
Intelligent algorithms refer to the methods embodied in the computational processes that realize intelligence. These methods are often characterized by being data-driven, involving uncertain computations, and with unexplainable model inferences. These characteristics simultaneously introduce potential safety risks to the application of intelligent algorithms and AI. This study firstly explores the concepts of intelligent algorithm safety. Specifically, intelligent algorithm safety, based on the degree of human-machine integration, extends from the univariate safety of the algorithm itself to the bivariate applicational safety when the algorithm serves humans, and finally evolves into the multivariate systemic safety arises within complex socio-technical systems of human-machine …
On Global Security Governance’S New Trends And China’S Responses From Perspective Of Scientific And Technological Revolution, Haoguang Liang, Linman Wu, Zhujun Liu, Yaojun Zhang
On Global Security Governance’S New Trends And China’S Responses From Perspective Of Scientific And Technological Revolution, Haoguang Liang, Linman Wu, Zhujun Liu, Yaojun Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
Due to the new round of sci-tech revolution and industrial transformation, the relation between scientific progress and national security has been upgraded to an unprecedented strategic height. Therefore, it is vitally important to explore the current situation and future trajectory of the relation between the two. This study discusses the new trends between global scientific progress and the security of sovereign countries. It believes that scientific progress has catalyzed the new geopolitical contests, development contradiction and hegemonic tools in global security governance, thereby enlightening China’s approach to national security. To maintain holistic national security, China should formulate an overall strategic …
Mind-Iot: Machine Intelligence And Data-Mining For Iot Threats, Kwabena Aboagye-Otchere, Jorge Castillo
Mind-Iot: Machine Intelligence And Data-Mining For Iot Threats, Kwabena Aboagye-Otchere, Jorge Castillo
Informatics and Engineering Systems Faculty Publications
The use of electric motors drive numerous industries via robust mechanical and electromechanical systems. However, their ubiquitous presence across the industry makes them potential targets for cyber-attackers, raising serious privacy concerns. Prior studies have demonstrated the feasibility of accurately fingerprinting various devices using electromagnetic signals. Yet, the specialized equipment required for those methods remain complex and expensive. This study presents MIND-IoT, a novel approach that captures and analyzes the unintended magnetic emissions surrounding electric motors. Our method achieves precise fingerprinting of motors, and determines their operational parameters by leveraging low-cost IoT devices. By focusing solely on magnetic fields, MIND-IoT offers …
Advanced Hyperthermia Treatment: Optimizing Microwave Energy Focus For Breast Cancer Therapy, Burak Acar, Tuba Yilmaz Abdolsaheb, Ali Yapar
Advanced Hyperthermia Treatment: Optimizing Microwave Energy Focus For Breast Cancer Therapy, Burak Acar, Tuba Yilmaz Abdolsaheb, Ali Yapar
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a fast antenna phase optimization scheme to enable microwave power focusing for breast cancer hyperthermia. The power focusing is achieved through the maximization of the deposited electric field on the target malignant tumor tissue. To do so, a malignant breast tumor, the surrounding breast medium, and the skin of the breast are modeled as a cylindrical structure composed of eccentric cylinders, and electric field distribution is computed analytically in terms of cylindrical harmonics. This approach minimized the computational cost and simplified the breast medium model. To ensure applicability across various breast types, the dielectric properties (DPs) of …
Predicting Gender Of Author Using Large Language Models (Llms), Satya Uday Sanku
Predicting Gender Of Author Using Large Language Models (Llms), Satya Uday Sanku
USF Tampa Graduate Theses and Dissertations
The advent of text data from social media, blogs, movie reviews, and other textual sources has opened new avenues for research, particularly in the domain of Author Profiling. Author Profiling helps in Capturing the Stylistic features and also useful for analyzing the required elements in the written text. This Study addresses one of the tasks in Author Profiling which is termed as gender detection or Classification of Gender from Text. The main goal of this research is to obtain valuable and relevant gender characteristics that will accurately classify the Author’s gender of a review extracted from an Anime Review website. …
Reclaiming The Symbol: Ethics, Rhetoric, And The Humanistic Integration Of Gai - A Burkean Perspective, Daniel Plate, James Hutson
Reclaiming The Symbol: Ethics, Rhetoric, And The Humanistic Integration Of Gai - A Burkean Perspective, Daniel Plate, James Hutson
Faculty Scholarship
This study delves into the intersection of generative artificial intelligence (GAI) and the Humanities, guided by the critical insights of Kenneth Burke, a seminal figure in the study of rhetoric and a vocal critic of scientism and positivism. The skepticism of the American literary theorist towards an uncritical embrace of science and technology, and his concerns over the inclination of the Humanities to adopt scientific methodologies at the expense of traditional forms of inquiry, provide a critical framework for examining the new role played by GAI within the Humanities. By framing these tools in the context of Burkean rhetorical theory, …
“It Is Luring You To Click On The Link With False Advertising” - Mental Models Of Clickbait And Its Impact On User’S Perceptions And Behavior Towards Clickbait Warnings, Ankit Shrestha, Arezou Behfar, Mahdi Nasrullah Al-Ameen
“It Is Luring You To Click On The Link With False Advertising” - Mental Models Of Clickbait And Its Impact On User’S Perceptions And Behavior Towards Clickbait Warnings, Ankit Shrestha, Arezou Behfar, Mahdi Nasrullah Al-Ameen
Computer Science Student Research
Clickbait, a social engineering attack performed through social media, tricks users through sensationalized or misleading posts into clicking on links that direct them to malicious websites. With the recent boom in social media, clickbait has become a substantial security concern, necessitating efforts from platforms and academia to control it. Despite these attempts, clickbait is effective due to the lack of users’ knowledge. Therefore, we explore user mental models (thought processes about how something works) about clickbait to analyze their deficiencies and their influences on users’ behavior towards clickbait warnings. To this end, we conducted an online study with 770 participants …
Exploring The Design Of Low-End Technology To Increase Patient Connectivity To Electronic Health Records, Rens Kievit, Abdullahi Abubakar Kawu, Mirjam Van Reisen, Dympna O'Sullivan, Lucy Hederman
Exploring The Design Of Low-End Technology To Increase Patient Connectivity To Electronic Health Records, Rens Kievit, Abdullahi Abubakar Kawu, Mirjam Van Reisen, Dympna O'Sullivan, Lucy Hederman
Conference papers
The tracking of the vitals of patients with long term health problems is essential for clinicians to determine proper care. Using Patient Generated Health Data (PGHD) communicated remotely allows patients to be monitored without requiring frequent hospital visits. Issues might arise when the communication of data digitally is difficult or impossible due to a lack of access to internet or a low level of digital literacy as is the case in many African countries. The VODAN-Africa project (van Reisen et al., 2021) started in 2020 and has greatly increased the capabilities of clinics in different countries in both Africa and …
Towards The Design And Evaluation Of Clickbait Education Content: Leveraging User Mental Models And Learning Science Principles, A. Shrestha, A. Flood, B. Hackler, Arezou Behfar, M. N. Al-Ameen
Towards The Design And Evaluation Of Clickbait Education Content: Leveraging User Mental Models And Learning Science Principles, A. Shrestha, A. Flood, B. Hackler, Arezou Behfar, M. N. Al-Ameen
Computer Science Student Research
Clickbait refers to sensationalized or misleading post on social networking sites (e.g., Facebook) that can trick users into clicking on malicious links. Clickbait is often used in cyberattacks, especially to conduct 'social engineering attacks' that direct users to malicious websites, resulting in disclosure of users' personal information or installing malicious software (i.e., malware). Thus, clickbait has become a major security concern with the recent boom in social media use. Therefore, security education has become necessary more than ever for the safe and secure use of social media, where there is dearth in security education literature to explore how we could …
Why Do We Not Stand Up To Misinformation? Factors Influencing The Likelihood Of Challenging Misinformation On Social Media And The Role Of Demographics, Selin Gurgun, Deniz Cemiloglu, Emily Arden Close, Keith Phalp, Preslav Nakov, Raian Ali
Why Do We Not Stand Up To Misinformation? Factors Influencing The Likelihood Of Challenging Misinformation On Social Media And The Role Of Demographics, Selin Gurgun, Deniz Cemiloglu, Emily Arden Close, Keith Phalp, Preslav Nakov, Raian Ali
Natural Language Processing Faculty Publications
This study investigates the barriers to challenging others who post misinformation on social media platforms. We conducted a survey amongst U.K. Facebook users (143 (57.2 %) women, 104 (41.6 %) men) to assess the extent to which the barriers to correcting others, as identified in literature across disciplines, apply to correcting misinformation on social media. We also group the barriers into factors and explore demographic differences amongst them. It has been suggested that users are generally hesitant to challenge misinformation. We found that most of our participants (58.8 %) were reluctant to challenge misinformation. We also identified moderating roles of …
Hearing Iterative And Recursive Behavior: Sonification Improves Student Understanding, Joel C. Adams, Hayworth Anderson
Hearing Iterative And Recursive Behavior: Sonification Improves Student Understanding, Joel C. Adams, Hayworth Anderson
University Faculty Publications and Creative Works
Abstract topics such as recursion are challenging for many computer science students to understand. In this experience report, we explore function sonification-the addition of sound to a function to communicate information about the function's behavior in real-time as it runs-as a pedagogical approach for improving students' understanding of recursion. We present several example iterative and recursive function sonifications, plus spectrograms that illustrate their different sonic behaviors. We also present experimental evidence that using these sonifications significantly improved the understanding of recursion for students who used them, compared to students who used silent (i.e., traditional) versions of the same functions. Based …
Community Similarity Based On User Profile Joins, Konstantinos Theocharidis, Hady Wirawan Lauw
Community Similarity Based On User Profile Joins, Konstantinos Theocharidis, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Similarity joins on multidimensional data are crucial operators for recommendation purposes. The classic ��-join problem finds all pairs of points within �� distance to each other among two ��-dimensional datasets. In this paper, we consider a novel and alternative version of ��-join named community similarity based on user profile joins (CSJ). The aim of CSJ problem is, given two communities having a set of ��-dimensional users, to find how similar are the communities by matching every single pair of users (a user can be matched with at most one other user) having an absolute difference of at most �� per …
Application Of Collaborative Learning Paradigms Within Software Engineering Education: A Systematic Mapping Study, Rita Garcia, Christoph Treude, Andrew Valentine
Application Of Collaborative Learning Paradigms Within Software Engineering Education: A Systematic Mapping Study, Rita Garcia, Christoph Treude, Andrew Valentine
Research Collection School Of Computing and Information Systems
Collaboration is used in Software Engineering (SE) to develop software. Industry seeks SE graduates with collaboration skills to contribute to productive software development. SE educators can use Collaborative Learning (CL) to help students develop collaboration skills. This paper uses a Systematic Mapping Study (SMS) to examine the application of the CL educational theory in SE Education. The SMS identified 14 papers published between 2011 and 2022. We used qualitative analysis to classify the papers into four CL paradigms: Conditions, Effect, Interactions, and Computer-Supported Collaborative Learning (CSCL). We found a high interest in CSCL, with a shift in student interaction research …
Superminds At Work: The Promise Of Human-Ai Collaboration, Thomas W. Malone
Superminds At Work: The Promise Of Human-Ai Collaboration, Thomas W. Malone
Asian Management Insights
Massachusetts Institute of Technology (MIT) Center for Collective Intelligence Director Professor Thomas W. Malone’s scholarship offers deep insights into the promise afforded by the synergies between human intelligence and technology. According to Professor Malone, the boundaries between human intellect and technological prowess are becoming increasingly blurred, but this may not be a bad thing for humankind. In Asian Management Insights’ inaugural Pulse Point interview, we get to learn more about the concept of ‘collective intelligence’, which explores how a partnership between humans and Artificial Intelligence (AI) can be catalysed to make ground-breaking advancements in addressing the wicked problems of our …
Developing Singapore As A Smart Nation, Josephine Teo
Developing Singapore As A Smart Nation, Josephine Teo
Asian Management Insights
Mrs Josephine Teo, Singapore’s Minister for Communications and Information, and Minister-in-charge of Smart Nation and Cybersecurity, speaks about leading the country’s Smart Nation drive.
Stability Verification In Stochastic Control Systems Via Neural Network Supermartingales, Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger
Stability Verification In Stochastic Control Systems Via Neural Network Supermartingales, Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger
Research Collection School Of Computing and Information Systems
We consider the problem of formally verifying almost-sure (a.s.) asymptotic stability in discrete-time nonlinear stochastic control systems. While verifying stability in deterministic control systems is extensively studied in the literature, verifying stability in stochastic control systems is an open problem. The few existing works on this topic either consider only specialized forms of stochasticity or make restrictive assumptions on the system, rendering them inapplicable to learning algorithms with neural network policies. In this work, we present an approach for general nonlinear stochastic control problems with two novel aspects: (a) instead of classical stochastic extensions of Lyapunov functions, we use ranking …
On The Effects Of Information Asymmetry In Digital Currency Trading, Kwansoo Kim, Robert John Kauffman
On The Effects Of Information Asymmetry In Digital Currency Trading, Kwansoo Kim, Robert John Kauffman
Research Collection School Of Computing and Information Systems
We report on two studies that examine how social sentiment influences information asymmetry in digital currency markets. We also assess whether cryptocurrency can be an investment vehicle, as opposed to only an instrument for asset speculation. Using a dataset on transactions from an exchange in South Korea and sentiment from Korean social media in 2018, we conducted a study of different trading behavior under two cryptocurrency trading market microstructures: a bid-ask spread dealer's market and a continuous trading buy-sell, immediate trade execution market. Our results highlight the impacts of positive and negative trader social sentiment valences on the effects of …
Improving Automatic Transcription Using Natural Language Processing, Anna Kiefer
Improving Automatic Transcription Using Natural Language Processing, Anna Kiefer
Master's Theses
Digital Democracy is a CalMatters and California Polytechnic State University initia-
tive to promote transparency in state government by increasing access to the Califor-
nia legislature. While Digital Democracy is made up of many resources, one founda-
tional step of the project is obtaining accurate, timely transcripts of California Senate
and Assembly hearings. The information extracted from these transcripts provides
crucial data for subsequent steps in the pipeline. In the context of Digital Democracy,
upleveling is when humans verify, correct, and annotate the transcript results after
the legislative hearings have been automatically transcribed. The upleveling process
is done with the …
Measuring The Presentation Of Supporting Content For A Set Of Learning Objectives Throughout The States Of An Educational Game Tree, Michael L. Hastriter Jr.
Measuring The Presentation Of Supporting Content For A Set Of Learning Objectives Throughout The States Of An Educational Game Tree, Michael L. Hastriter Jr.
Theses and Dissertations
In an era of evolving warfare, the Department of Defense (DoD) recognizes the value of serious games as immersive tools for teaching critical concepts. This thesis introduces a pioneering framework tailored to enhance learning objectives through the presentation of educational game content. This addresses the unique needs of the DoD and other educators who use games by providing measurements to assess educational games. This researches investigates how instructors might assess games as potential teaching tools. It establishes a five-phase process, providing a framework to assess educational games against predefined learning objectives and informing future game development. This thesis demonstrates games …
Artificial Intelligence And Perception: An Empirical Study, Anthony J. Neil
Artificial Intelligence And Perception: An Empirical Study, Anthony J. Neil
Theses and Dissertations
This thesis investigates the impact of adjusting artificial intelligence explainability levels’ outputs on user perception. The overarching study extends within the Explainable Artificial Intelligence (XAI) domain. It examines a spectrum of variables, including performance, cognizance, familiarity, transparency, system bias, and the overall impact of AI, to understand their collective and individual effects that enable effective professional use in an organization. The study aims to illuminate the relationship between the degree of explainability provided by large language models such as ChatGPT, Bard, and Bing AI and the performance of these models when tasked with XAI adjustments.
The Effect Of Internet Firms’ Data Analytics Capability On Their Innovation Speed And Innovation Quality: A Dynamic Capability Perspective, Yeyu Hua
Dissertations and Theses Collection (Open Access)
With the advent of big data era, data plays a pivotal role in sustainingfirms’ competitive advantages. Although a few studies have shown that data analytics capability contributes to firms’ innovative performance, these studies either focus on general innovative performance or specific types of innovation, such as incremental innovation, radical innovation, and supply chaininnovation. In this thesis, I enrich this stream of literature by conducting twostudies to further examine the relationship between data analytics capabilityand innovation speed as well as innovation quality. This thesis consists of twostudies. Study 1 is a survey study, in which I investigate the relationshipbetween data analytics …
Marketing Video Games To Aging Demographics: A Generational Profile Analysis, Brinna Louise Ball
Marketing Video Games To Aging Demographics: A Generational Profile Analysis, Brinna Louise Ball
Theses
Marketing video games to aging demographics like Baby Boomers, Generation X, and Millennials requires a unique approach by video game studios and consumer products divisions alike. The strategies employed for younger generations such as Generation Z and Generation Alpha differ from conventional methods, requiring a fresh outlook and a need for more innovative and inventive approaches. To comprehend the current aging audience more effectively, it's essential to examine four crucial factors: accessibility, exposure, media habits, and motivations to play video games. Examining these factors by generation, we can better grasp how to effectively market video games to these demographics. It's …
Maximizing The Ai Revolution In Southeast Asia, Shoeb Kagda
Maximizing The Ai Revolution In Southeast Asia, Shoeb Kagda
Asian Management Insights
For that, the region must narrow the digital divide.
Generative Ai In Finance: Risks And Potential Solutions, Nydia Remolina Leon
Generative Ai In Finance: Risks And Potential Solutions, Nydia Remolina Leon
Research Collection Yong Pung How School Of Law
Generative Artificial Intelligence captured the attention of academics, policymakers, the private sector, and some regulators in 2022 after the launch of ChatGPT and its widespread adoption worldwide. Then, during the World Economic Forum session in 2023, Microsoft Chairman and Chief Executive Officer Satya Nadella said that the ‘golden age’ of AI is underway and generative AI is set to play a big role in it. Accordingly, Microsoft has invested billions of dollars into OpenAI, the company behind the launch of ChatGPT. Additionally, Google and Meta have also created their own generative AI models. Given the multiplicity of potential use cases …
Decentralized Multimedia Data Sharing In Iov: A Learning-Based Equilibrium Of Supply And Demand, Jiani Fan, Minrui Xu, Jiale Guo, Lwin Khin Shar, Jiawen Kang, Dusit Niyato, Kwok-Yan Lam
Decentralized Multimedia Data Sharing In Iov: A Learning-Based Equilibrium Of Supply And Demand, Jiani Fan, Minrui Xu, Jiale Guo, Lwin Khin Shar, Jiawen Kang, Dusit Niyato, Kwok-Yan Lam
Research Collection School Of Computing and Information Systems
The Internet of Vehicles (IoV) has great potential to transform transportation systems by enhancing road safety, reducing traffic congestion, and improving user experience through onboard infotainment applications. Decentralized data sharing can improve security, privacy, reliability, and facilitate infotainment data sharing in IoVs. However, decentralized data sharing may not achieve the expected efficiency if there are IoV users who only want to consume the shared data but are not willing to contribute their own data to the community, resulting in incomplete information observed by other vehicles and infrastructure, which can introduce additional transmission latency. Therefore, in this paper, by modeling the …
Leveraging Multimodal Features And Item‑Level User Feedback For Bundle Construction, Yunshan Ma, Xiaohao Liu, Yinwei Wei, Zhulin Tao, Xiang Wang, Tat‑Seng Chua
Leveraging Multimodal Features And Item‑Level User Feedback For Bundle Construction, Yunshan Ma, Xiaohao Liu, Yinwei Wei, Zhulin Tao, Xiang Wang, Tat‑Seng Chua
Research Collection School Of Computing and Information Systems
Automatic bundle construction is a crucial prerequisite step in various bundle-aware online services. Previous approaches are mostly designed to model the bundling strategy of existing bundles. However, it is hard to acquire large-scale well-curated bundle dataset, especially for those platforms that have not offered bundle services before. Even for platforms with mature bundle services, there are still many items that are included in few or even zero bundles, which give rise to sparsity and cold-start challenges in the bundle construction models. To tackle these issues, we target at leveraging multimodal features, item-level user feedback signals, and the bundle composition information, …
From Asset Flow To Status, Action And Intention Discovery: Early Malice Detection In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu
From Asset Flow To Status, Action And Intention Discovery: Early Malice Detection In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu
Research Collection School Of Computing and Information Systems
Cryptocurrency has been subject to illicit activities probably more often than traditional financial assets due to the pseudo-anonymous nature of its transacting entities. An ideal detection model is expected to achieve all three critical properties of early detection, good interpretability, and versatility for various illicit activities. However, existing solutions cannot meet all these requirements, as most of them heavily rely on deep learning without interpretability and are only available for retrospective analysis of a specific illicit type. To tackle all these challenges, we propose Intention Monitor for early malice detection in Bitcoin, where the on-chain record data for a certain …
Understanding Newcomers' Onboarding Process In Deep Learning Projects, Junxiao Han, Jiahao Zhang, David Lo, Xin Xia, Shuigang Deng, Minghui Wu
Understanding Newcomers' Onboarding Process In Deep Learning Projects, Junxiao Han, Jiahao Zhang, David Lo, Xin Xia, Shuigang Deng, Minghui Wu
Research Collection School Of Computing and Information Systems
Attracting and retaining newcomers are critical for the sustainable development of Open Source Software (OSS) projects. Considerable efforts have been made to help newcomers identify and overcome barriers in the onboarding process. However, fewer studies focus on newcomers’ activities before their successful onboarding. Given the rising popularity of deep learning (DL) techniques, we wonder what the onboarding process of DL newcomers is, and if there exist commonalities or differences in the onboarding process for DL and non-DL newcomers. Therefore, we reported a study to understand the growth trends of DL and non-DL newcomers, mine DL and non-DL newcomers’ activities before …
Temporal Implicit Multimodal Networks For Investment And Risk Management, Meng Kiat Gary Ang, Ee-Peng Lim
Temporal Implicit Multimodal Networks For Investment And Risk Management, Meng Kiat Gary Ang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Many deep learning works on financial time-series forecasting focus on predicting future prices/returns of individual assets with numerical price-related information for trading, and hence propose models designed for univariate, single-task, and/or unimodal settings. Forecasting for investment and risk management involves multiple tasks in multivariate settings: forecasts of expected returns and risks of assets in portfolios, and correlations between these assets. As different sources/types of time-series influence future returns, risks, and correlations of assets in different ways, it is also important to capture time-series from different modalities. Hence, this article addresses financial time-series forecasting for investment and risk management in a …
Navigating The Digital Frontier: The Intersection Of Cybersecurity Challenges And Young Adult Life, Hannarae Lee
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.