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检索条件"任意字段=2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2021"

共 904 条记录，以下是11-20 订阅

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An Novel Deep Learning Model For Detection Of Agricultural Pests And Plant Leaf Diseases

An Novel Deep Learning Model For Detection Of Agricultural P...

引用

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

作者： Uttarwar, Monica Chetty, Girija Yamin, Mohammad White, Matthew University of Canberra Faculty of Science and Technology Australia University of Canberra Faculty of Science and Technology BruceACT2617 Australia King Abdul Aziz University Management Information Systems Faculty of Economics and Administration Saudi Arabia Iig R& D Pty. Ltd. Melbourne Australia

ISBN: (纸本)9798350341072

In this paper a novel deep learning model for detection of plant leaf disease and agricultural pests. The proposed integreated hybrid model development based on EfficientNetB0 deep learning architecture allows model deployment in low resource settings with limited training data, allowing new and rare plant diseases and agricultural pests to be detected accurately. © 2023 ieee.

关键词： Deep learning

来源：评论

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Exploring Information Security Processes Effectiveness in Educational Institutions: Impacts of Organizational Factors)

Exploring Information Security Processes Effectiveness in Ed...

引用

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

作者： Daneshmandnia, Ali New York City College of Technology Computer System Technology Department City University of New York BrooklynNY United States

ISBN: (纸本)9798350341072

Information security effectiveness has become the focus of organizations whether they manage their own information, or rely on providers. The research literature suggests that organizational characteristics have a significant, positive effect on information security [1]-[4]. This paper examines the impact of organizational characteristics, specifically, the size of the organization, culture, IT budget, frequency of reported IT audits, and executive support, on the effectiveness of information security processes at higher educational institutions (HEI.) Nine information governance processes used in this study include communication of information security roles, the protection of sensitive data, and business agreement audits. Findings suggest that organizational culture, frequency of reported audits, and executive-level support positively influence information effectiveness, but the size of institutions and level of IT budget did not show any significant effect. © 2023 ieee.

关键词： Sensitive data

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MLFBERT: Advancing News Recommendation with Multi-Layer Fusion over DistilBERT

MLFBERT: Advancing News Recommendation with Multi-Layer Fusi...

引用

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

作者： Lin, Shiyu Ye, Xinfeng Manoharan, Sathiamoorthy School of Computer Science University of Auckland Auckland New Zealand

ISBN: (纸本)9798350341072

Traditional news recommendation methods usually encode news text and user interests directly into vectors and then calculate the matching degree of the two. Such approaches may lose low-level matching signals and different levels of textual information. We propose a BERT-based news recommendation model, MLFBERT. This model consists of a BERT-based news encoder and a user encoder. The news encoder uses a PLM Fusion Module and additive attention to generate embeddings of available news items. The user encoder builds a user profile by aggregating the representations of their news browsing history. Recommendations are made by computing matching scores between the user profile and candidate news. Experiments on the MIND news dataset demonstrate that our model outperforms existing methods on multiple evaluation metrics. © 2023 ieee.

关键词： User profile

来源：评论

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Classifying Pitch Types in Baseball Using Machine Learning Algorithms

Classifying Pitch Types in Baseball Using Machine Learning A...

引用

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

作者： Schuh, Jacob Kong, Lan Eastern Kentucky University Department of Computer Science and Information Technology RichmondKY United States

ISBN: (纸本)9798350341072

It is critically important for a college baseball team if the pitch type information is available when the characteristics of a pitch are collected. This information is typically collected by baseball specialists;however, this process can be time-consuming and error-prone due to human nature. To address this issue, multiple machine learning classifiers, including Support Vector Machine (SVM), k-nearest neighbors (kNN), Decision Tree, and Artificial Neural Network (ANN), were examined and compared. Although all tested classifiers achieved at least 0.92 in accuracy, ANN categorized the pitches with the most accuracy (0.96), precision (0.95), and recall (0.95) within a reasonable training time (85.7 seconds). In summary, ANN is the best classifier among the examined models. © 2023 ieee.

关键词： Baseball

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Navigating Cybersecurity Challenges: A Contemporary Analysis of Fiji Islands

Navigating Cybersecurity Challenges: A Contemporary Analysis...

引用

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

作者： Kumar, Raymond Krishnil Sharma, Neeraj Anand The University of Fiji Department of Computer Science and Mathematics Saweni Campus Fiji

ISBN: (纸本)9798350341072

In today's tech-driven landscape, cybersecurity stands out as a pivotal and focal point. This research paper provides an overview of the cybersecurity landscape in Fiji, focusing on the popularity of cyber-related crimes and the need for ethical behavior during online presence. It discusses various types of cyber-attacks, including digital scams, forgery and fraud, and cyberbullying, and acmes importance of confidentiality, integrity, and availability in maintaining a secure online environment. The research also discusses the laws and regulations of cyber security in Fiji and emphasizes the need for new mechanisms and improvements in the regulatory framework to support technological advancements. The research methodology utilized various data collection methods, including analyzing court cases, media articles, and relevant Acts, to address key research questions. The paper concludes by emphasizing the significance of pursuing ethical norms and behaviors to mitigate cyber-related crimes. © 2023 ieee.

关键词： Cybersecurity

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Devised Deephashing Models Through Self-Supervised Learning for Image Retrieval

Devised Deephashing Models Through Self-Supervised Learning ...

引用

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

作者： Kim, Sooin Jeon, Youngjin Kim, Won-Gyum Hwang, Doosung Kim, Donghoon Dankook University Dept. of Software Science Yongin Korea Republic of AiDeep Research Center Seoul Korea Republic of Arkansas State University Dept. of Computer Science JonesboroAR United States

ISBN: (纸本)9798350341072

Many image database systems utilize content-based retrieval technology using perceptual hashing to facilitate image comparison and retrieval. However, conventional hashing functions generate different hash codes for the same image domain even with minor changes, making accurate searches in the image database impossible. To overcome these limitations, a method has been devised to enable the search for images similar to queries synthesizing visual feature information, including texture, shape, and color of images. This paper proposes deephashing models that incorporate both variational autoencoders and vision trans-formers, capable of capturing semantic patterns and preserving the semantic similarity between data points. To validate this proposal, we conduct a comparative evaluation by comparing its performance with widely-used supervised learning-based models. The experimental analysis shows that the proposed approach generates compressed and discriminative hash codes with fixed-length binary representations that maintain semantic similarity and enable the search even for similar images. When evaluating the performance of our proposed model in comparison to the other studies, noticeable improvements are observed across the selected metrics in deephashing based on self-supervised learning. © 2023 ieee.

关键词： Content based retrieval

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Blockchain-Based E-Wallet: A Secure and Transparent Money Management Solution

Blockchain-Based E-Wallet: A Secure and Transparent Money Ma...

引用

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

作者： Buksh, Zain Salahuddin, Md Ali, A.B.M. Shawkat The University of Fiji Department of Computer Science and Mathematics Lautoka Fiji Bangladesh High Commission Department of Labour & Welfare Canberra Australia

ISBN: (纸本)9798350341072

To revolutionize digital money administration, this paper provides an architectural design for an e-wallet platform powered by blockchain technology. The suggested design makes use of the privacy and security capabilities of blockchain to give consumers a safe and user-focused payment method. The system's key parts are described, namely safe payment processing, distributed administration of identities, and smart contracts. The paper discusses the possible advantages of blockchain technology in the field of finance, with an emphasis on resolving security issues and improving consumer privacy. Although the design is still conceptual at this time, it presents an encouraging basis for the creation of a safe and open e-wallet technology that fits the changing decentralized financial environment. © 2023 ieee.

关键词： Smart contract

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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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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

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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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