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检索条件"任意字段=2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023"

共 1096 条记录，以下是21-30 订阅

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A Bibliometric View of AI Ethics Development

A Bibliometric View of AI Ethics Development

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Gao, Di Kevin Haverly, Andrew Mittal, Sudip Chen, Jingdao California State University Management Department HaywardCA United States Mississippi State University Computer Science and Engineering Dept Mississippi StateMS39762 United States

ISBN: (纸本)9798350341072

Artificial Intelligence (AI) Ethics is a nascent yet critical research field. Recent developments in generative AI and foundational models necessitate a renewed look at the problem of AI Ethics. In this study, we perform a bibliometric analysis of AI Ethics literature for the last 20 years based on keyword search. Our study reveals a three-phase development in AI Ethics, namely an incubation phase, making AI human-like machines phase, and making AI human-centric machines phase. We conjecture that the next phase of AI ethics is likely to focus on making AI more machine-like as AI matches or surpasses humans intellectually, a term we coin as 'machine-like human'. © 2023 ieee.

关键词： Search engines

来源：评论

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Analysing User Vulnerability to Phishing attacks using Machine Learning Techniques: A Case Study on University data

Analysing User Vulnerability to Phishing attacks using Machi...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Kumar, Ashwani Prasad, Sylvia Kumar, Kunal University of Fiji Department of Computer Science and Mathematics Saweni Lautoka Fiji

ISBN: (纸本)9798350341072

A majority of anti-phishing research has been concentrated on evaluating current anti-phishing solutions and creating more effective detection techniques. No matter how the attacks are launched, they all appear to aim for specific human characteristics to get access to the desired details, and this area lacks adequate research. This study aims to predict user vulnerability to phishing by analyzing user attributes and features such as age, education level, computer knowledge and personality. data was used from phishing simulations periodically carried out on 1774 users by a reputable university in Fiji, which also captures relevant user attributes. Four machine learning algorithms were compared with the use of Python and Google Colaboratory. Support Vector Machine algorithm presented the highest accuracy rate of 94.93%. The results identified some important correlations between user behaviour and phishing attacks which are highlighted in the results and discussion section. © 2023 ieee.

关键词： Logistic regression

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Novel Deep Learning Pipeline for Automatic Weapon Detection

Novel Deep Learning Pipeline for Automatic Weapon Detection

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Sivakumar, Haribharathi Vijay Arvind, R. Pawan Ragavendhar, V. Balamurugan, G. Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Tamil Nadu 603 203 India

ISBN: (纸本)9798350341072

Weapon and gun violence have recently become a pressing issue today. The degree of these crimes and activities has risen to the point of being termed as an epidemic. This prevalent misuse of weapons calls for an automatic system that detects weapons in real-time. Real-time surveillance video is captured and recorded in almost all public forums and places. These videos contain abundant raw data which can be extracted and processed into meaningful information. This paper proposes a novel pipeline consisting of an ensemble of convolutional neural networks with distinct architectures. Each neural network is trained with a unique mini-batch with little to no overlap in the training samples. This paper will present several promising results using multiple datasets associated with comparing the proposed architecture and state-of-the-art (SoA) models. The proposed pipeline produced an average increase of 5% in accuracy, specificity, and recall compared to the SoA systems. © 2023 ieee.

关键词： Pipelines

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Analyzing Cybersecurity Patterns in the pacific Region: Trends and Challenges for 2023

Analyzing Cybersecurity Patterns in the Pacific Region: Tren...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Sharma, Priynka Prakash, Surya Chaudhary, Kaylash The University of the South Pacific Suva Fiji

ISBN: (纸本)9798350341072

This research paper offers an in-depth exploration of the evolving cybersecurity landscape in the pacific region, characterized by rapid economic growth and technological advancements, with an expanding digital ecosystem. While these advancements have steered significant benefits, they have concurrently exposed vulnerabilities susceptible to exploitation by cybercriminals. The study highlights prevailing trends and early challenges projected for 2023, specifically focusing on local infections, ransomware, network attacks, and exploit incidents. The research thoroughly analyzes these aspects and reveals complex insights into the evolving threat scenarios. Furthermore, the study emphasizes the importance of expanding regional collaboration and international cooperation as essential strategies to address the pacific nations' multilayered cybersecurity challenges effectively. Beyond these trends, the paper investigates evolving fundamentals, the impact of technological progress, regulatory dynamics, and collaborative initiatives while exploring emerging technologies' influence on security vulnerabilities besides the complex interaction of cultural norms and geopolitical factors. This comprehensive analysis enhances understanding of the pacific Region's cybersecurity landscape, furnishing a robust foundation for strategic mitigation approaches and contributing substantively to the growth of regional cyber resilience in 2023 and beyond. © 2023 ieee.

关键词： Cybersecurity

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Predicting Heart Disease based on Patient History using Machine Learning Techniques

Predicting Heart Disease based on Patient History using Mach...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Chand, Sheenal Shalini Naidu, Anish Kumar, Kunal The University of Fiji Department of Computer Science and Mathematics Saweni Campus Fiji

ISBN: (纸本)9798350341072

In this information age, more and more data are being produced every day from different sectors. Healthcare is no exception where huge amounts of data is being produced daily. However, this data is not effective. As the phrase goes 'data is the new oil', it is important to acknowledge the importance of data and how it can make work easier for professionals across fields. For the healthcare sector, the various data that are collected can be used to extract knowledge to make diagnosis of certain diseases easier. One such disease which can be predicted is the heart disease which is becoming a top killer amongst the populations across the world. This paper will investigate how machine learning (ML) algorithms can be used to predict heart diseases using heart disease data and will compare the 3 machine learning algorithms - decision tree, naive bayes, and random forest to determine the most accurate model for predicting this deadly condition. © 2023 ieee.

关键词： Diseases

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Metaverse Interview Room Creation With Virtual Interviewer Generation Using Diffusion Model

Metaverse Interview Room Creation With Virtual Interviewer G...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Si, Jongwook Yang, Seongeun Kim, Daemin Kim, Sungyoung Kumoh National Institute of Technology Dept. Computer Ai Convergence Engineering Gumi Korea Republic of Kumoh National Institute of Technology Dept. Computer Engineering Gumi Korea Republic of

ISBN: (纸本)9798350341072

Virtual interviews are an effective way to respond quickly to the changing trends of our time and adapt flexibly to the hiring processes of various organizations. Through this method, applicants have the opportunity to practice their interview skills and receive feedback, greatly aiding their job preparation. Additionally, experiencing a virtual interview environment that is similar to an actual one enables them to adapt more easily to a variety of new interview situations. This paper delves deeply into the virtual interview environment implemented by combining cutting-edge metaverse technology and generative AI. Specifically, it focuses on creating an environment utilizing realistic Diffusion models to generate interviewers, enabling the provision of scenarios that are similar to actual interviews. © 2023 ieee.

关键词： Virtual reality

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Supply Chain Optimization in Cement Industry Using Blockchain Technology

Supply Chain Optimization in Cement Industry Using Blockchai...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Hamood, Rabeya Makhdoom, Imran Iqbal, Waseem Jamil, Tariq National University of Sciences and Technology Department of Information Security Islamabad44000 Pakistan Sultan Qaboos University Department of Electrical and Computer Engineering AlKhod Muscat123 Oman

ISBN: (纸本)9798350341072

The ubiquitous use of Internet of Things devices in supply chain management has facilitated manufacturers and other stakeholders to monitor various aspects of the product or shipment. However, conventional solutions have numerous challenges ranging from data integrity, product provenance, and trust issues to scalability problems. This research demonstrates how scalability and provenance of cement bags can be ensured through a combination of blockchain technology and the Internet of Things devices. The distributed ledger securely records each step, from acquiring raw materials to delivering the finished product. The inherent transparency of blockchain technology promotes confidence among all the stakeholders in the supply chain and makes it easier to comply with legal requirements. The security and performance analysis determines that the proposed solution is secure and efficient with minimal performance overheads. © 2023 ieee.

关键词： Blockchain

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A PSO Based Method to Generate Actionable Counterfactuals for High Dimensional data

A PSO Based Method to Generate Actionable Counterfactuals fo...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Shekhar, Shashank Salim, Asif Jinturkar, Vivaswan Nayak, Anirudha Bansode, Adesh Subex Ltd Bengaluru India

ISBN: (纸本)9798350341072

Counterfactual explanations (CFE) are methods that explain a machine learning model by giving an alternate class prediction of a data point with some minimal changes in its features. It helps the users to identify their data attributes that caused an undesirable prediction like a loan or credit card rejection. We describe an efficient, and an actionable counterfactual (CF) generation method based on particle swarm optimization (PSO). We propose a simple objective function for the optimization of instance-centric CF generation problem. The PSO brings in a lot of flexibility in terms of carrying out multi-objective optimization in large dimensions, capability for multiple CF generation, and setting box constraints or immutability of data attributes. An algorithm is proposed that incorporates these features and it enables greater control over the proximity and sparsity properties over the generated CFs. The proposed algorithm is evaluated with a set of action-ability metrics in real-world datasets, and the results were superior compared to that of the state-of-the-arts. © 2023 ieee.

关键词： Multiobjective optimization

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Decentralized Identifiers Using Distributed Ledger Technologies

Decentralized Identifiers Using Distributed Ledger Technolog...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Alizadeh, Morteza Andersson, Karl Schelén, Olov Luleå University of Technology Department of Computer Science Electrical and Space Engineering Skellefteå Sweden Luleå University of Technology Department of Computer Science Electrical and Space Engineering Luleå Sweden

ISBN: (纸本)9798350341072

Decentralized identification is an interesting topic for Internet-based systems. Although the use of centralized systems for identification is prevalent, there is still a need for decentralized identification systems that do not rely on a centralized entity. We propose using Distributed Ledger Technology (DLT) to fulfill the needs. Although DLT and Distributed Hash Table (DHT) can be used as technologies in Decentralized Identifiers (DIDs), immutability and the growth of transactions are still challenging. This paper investigates DIDs under the W3C standard and DLT-based technology as one of the solutions for verifiable data registries in DIDs. We evaluate our proposed solution by comparing three models wrt. query time for verifiable data registries. Our proposed architecture for data registry achieves better query time by concealing old transactions from the main DLT. © 2023 ieee.

关键词： Distributed ledger

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Extending and Evaluating Usability Heuristics for Educational Website in Fiji

Extending and Evaluating Usability Heuristics for Educationa...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Sami, Monesh Devi, Pritika Ali, A. B. M. Shawkat Kumar, Anal Fiji National University Department of Computer Science and Information Systems Nadi Fiji Fiji National University Department of Office Administration/Library and Information System Nadi Fiji School of Science and Technology The University of Fiji Saweni Fiji

ISBN: (纸本)9798350341072

Learning Management Systems (LMS) has recently gained a lot of popularity as an effective tool for improving education while promoting distance and flexible learning in Fiji. eLearning platforms should be able to possess usability features, including user-friendliness, ease of use and satisfaction of user requirements. With the diverse number of universities and courses globally, LMS websites created revolutionary changes in the educational sector. With these innovations, it is vital to ensure the effectiveness of educational sites by evaluating the usability interfaces, as there is minimal study on the effectiveness of websites, especially for LMS. This research intends to fill this gap by extending and evaluating the usability heuristics of educational website interfaces for better detection of usability problems, simultaneously running a survey to determine Moodle usage on different devices among different users in Fiji. © 2023 ieee.

关键词： Human computer interaction

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