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检索条件"任意字段=2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2022"

共 960 条记录，以下是121-130 订阅

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Navigating Cybersecurity Challenges: A Contemporary Analysis of Fiji Islands

Navigating Cybersecurity Challenges: A Contemporary Analysis...

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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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Impact of a Batter in ODI Cricket Implementing Regression Models from Match Commentary

Impact of a Batter in ODI Cricket Implementing Regression Mo...

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2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Asad, Ahmad Al Anwar, Kazi Nishat Chowdhury, Ilhum Zia Azam, Akif Ashraf, Tarif Rahman, Tanvir Brac University Department of Computer Science and and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665453059

Cricket, a 'Gentleman's Game,' is a prominent sport rising worldwide. Due to the rising competitiveness of the sport, players and team management have become more professional with their approach. Prior studies predicted individual performance or chose the best team but did not highlight the batter's potential. Our research, on the other hand, aims to evaluate a player's impact while considering his control in various circumstances. This paper seeks to understand the conundrum behind this impactful performance by determining how much control a player has over the circumstances and generating the 'Effective Runs,' a new measure we propose. We first gathered the fundamental cricket data from open source datasets;however, variables like the pitch, weather, and control were not readily available for all matches. As a result, we compiled our corpus data by analyzing the commentary of the match summaries. This gave us an insight into the particular game's weather and pitch conditions. Furthermore, ball-by-ball inspection from the commentary led us to determine the control of the shots played by the batter. We collected data for the entire One Day International career, up to February 2022, of 3 prominent cricket players: Rohit G Sharma, David A Warner, and Kane S Williamson. Lastly, to prepare the dataset, we encoded, scaled, and split the dataset to train and test Machine Learning Algorithms. We used Multiple Linear Regression (MLR), Polynomial Regression, Support Vector Regression (SVR), Decision Tree Regression, and Random Forest Regression on each player's data individually to train them and predict the Impact the player will have on the game. Multiple Linear Regression and Random Forest give the best predictions accuracy of 90.16% and 87.12%, respectively. © 2022 ieee.

关键词： Multiple linear regression

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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...

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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

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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

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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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A Review of Heuristic Approaches to Vehicle Routing Problems

A Review of Heuristic Approaches to Vehicle Routing Problems

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8th ieee asia-pacific conference on computer science and data engineering (ieee csde)

作者： Buyukozdemir, Kerem Yildiz, Kazim Bas, Anil Uslu, Banu Calis Marmara Univ Inst Pure & Appl Sci Comp Engn Istanbul Turkey Marmara Univ Fac Technol Comp Engn Istanbul Turkey Marmara Univ Fac Engn Comp Engn Istanbul Turkey

ISBN: (纸本)9781665495523

This study reviews the approaches that are based on heuristic methods and include processed GPS data in their solutions for vehicle routing problems. Vehicle routing problems are challenging given their constraints and complexity. Due to the nature of vehicle routing, the appropriate solution must be found within a reasonable timeframe. However, it is not possible to scan the entire solution space and find the optimum solution within the ideal timeframe when the problem's complexity increases because of the number of points and the constraints. In order to solve these kinds of situations, the aim is finding the optimum solution, or the optimum solution as close as possible. This situation reveals some scenarios where heuristic and meta-heuristic algorithms are used as solution algorithms to routing problems. GPS data is included in the solution algorithms to increase the performance of heuristic algorithms and routing solutions. As a result of the processed data, environmental factors such as congestion points, average speed on the route and traffic density according to hours are also taken into account. In this way, more consistent solutions are developed for real-life applications.

关键词： Vehicle routing problem heuristic optimization GPS data data processing

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Automatic detection of ironic expressions based on the Implicit Display Theory

Automatic detection of ironic expressions based on the Impli...

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2020 ieee asia-pacific conference on computer science and data engineering, csde 2020

作者： Sato, Akinori Tanev, Ivan Shimohara, Katsunori Doshisha University Graduate School of Science and Engineering Kyotanabe Kyoto Japan

ISBN: (纸本)9781665419741

It is not easy for a computer to automatically detect irony. Because in order to understand the irony in a sentence, it is necessary to infer the meaning hidden behind the word from the branch. Common sense and common understanding of reality are required as background knowledge for detecting irony. The literal meaning and the meaning intended by a speaker do not often match, and this makes it a difficult task in natural language processing. In this research, the effectiveness of automatic detection of irony based on the Implicit Display Theory was verified. The Implicit Display Theory was proposed in 1997 as a comprehensive irony theory, and its validity and superiority have been shown as a theory representing irony research. We selected ironic sentences for which the Implicit Display Theory holds from a large-scale ironic corpus, and performed two-class classification using the deep learning model to evaluate the application of implicit display theory to natural language processing. © 2020 ieee.

关键词： Natural language processing systems

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Predicting Heart Disease based on Patient History using Machine Learning Techniques

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

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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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Rainfall prediction using Artificial Neural Network in the South pacific region

Rainfall prediction using Artificial Neural Network in the S...

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2019 ieee asia-pacific conference on computer science and data engineering, csde 2019

作者： Chand, Ashneel Nand, Ravneil University of the South Pacific College of Science Technology and Environment Suva Fiji University of South Pacific School of Computing Information and Mathematical Sciences Suva Fiji

ISBN: (纸本)9781728163031

Rainfall prediction is one of the most important and at the same time challenging task. Meteorologists can predict weather patterns such as rainfall based on atmospheric parameters such as Humidity, Temperature, etc. This paper presents research on rainfall prediction based on historical dataset through neural network by training a network and testing it. Mean squared error (MSE) is used to generalize the performance of the model. Three different dataset, training algorithm and hidden layer setting is used for prediction. The results obtained reveals that ideally all three training algorithm is producing good results as MSE is closer to zero. Undoubtedly, neural network proves to be most appropriate technique for forecasting various weather phenomena such as rainfall. It can be further alluded that Bayesian Regularization tends to give lower MSE values compare to the other two training algorithms. © 2019 ieee.

关键词： Mean square error

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