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8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023

作者： Huang, Jingjia Huang, Xincheng School of Computing and Data Science Xiamen University Malaysia Sepang Malaysia

ISBN: (纸本)9798350310931

This paper aims to enhance cloud computing security and mitigate privacy risks by investigating optimized compiler models. Through extensive literature review and analysis, we have selected a compiler model based on the Porcupine privacy computing approach and a component called Quill, which translates plain text specifications into equivalent implementations in homomorphic cryptography. Concurrently, we propose additional optimization strategies that improve the efficiency and cost effectiveness of homophobic encryption. Our work signifies a step forward in the realm of secure, private cloud computing © 2023 IEEE.

关键词： Cloud computing

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Food Images Classification Based on Improved Convolutional Neural Network 4

Food Images Classification Based on Improved Convolutional N...

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4th International Conference on Electronic Communication and Artificial Intelligence, ICECAI 2023

作者： He, Yangfan Yin, Siyuan Xiamen University Malaysia School of Computing and Data Science Selangor Malaysia

ISBN: (纸本)9798350314496

Food image classification plays a crucial role in computer vision research and has immense theoretical significance, along with numerous potential applications in various fields such as smart health, smart retail, and smart home. While several studies have been conducted on this topic, there is a lack of consensus on the optimal approach to achieve high accuracy. In this study, the author propose an improved Convolutional Neural Network (CNN) architecture for food image classification. This study aims to enhance the accuracy of food image classification by examining the influence of different optimizers, loss functions, and activation functions on the performance of four neural networks, including VGG19, MobileNet V2, DenseNet, and a traditional CNN architecture, using the ChineseFoodNet dataset. Besides, the paper will improve the performance of the selected model by utilizing data augmentation techniques and transfer learning. The findings of this study can help researchers and practitioners develop more robust and accurate models, facilitating their application in areas such as smart health and smart homes. It also has practical implications for the development of more accurate food image classification models in computer vision field. © 2023 IEEE.

关键词： Image classification

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EXPLORING THE TRANSFORMATIVE POWER OF VISUAL ART: A PRACTITIONER-RESEARCHER'S JOURNEY TOWARDS SELF-REFLECTION 67

EXPLORING THE TRANSFORMATIVE POWER OF VISUAL ART: A PRACTITI...

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67th Annual Meeting of the International Society for the Systems sciences, ISSS 2023

作者： van der Westhuizen, Lerina Goede, Roelien Read, Colin Unit for Data Science and Computing North West University South Africa

ISBN: (纸本)9781713893455

This paper explores how visual art can be utilised as a tool for reflection in the transformative learning process of the practitioner-researcher in chemistry education. It aims to explore the use of visual art as a means of self-reflection and self-transformation by the practitioner-researcher. The goal of this study was to explore the potential use of visual art as a complementary tool for facilitating personal growth and transformation, with a focus on a practitioner-researcher's self-reflection and self-transformation in the context of chemistry education. The researcher used imaginative teaching practices in chemistry as a means of driving self-transformative learning. The study was guided by critical social theory, interpretivism, and a living theory approach within an action research methodology. As part of the reflective process, the researcher made use of pen and ink sketching as a means of self-reflection in her reflective visual diary. By conceptualising emotions and feelings in the form of detailed pen and ink artwork, the researcher was able to express, and visually represent thoughts and emotions in a more tangible and meaningful way. The process of sketching allowed the researcher to explore her inner world and to externalise inner dialogue in a way that traditional writing or verbal expression may not have allowed. Through this process, the researcher was able to better understand her own emotions and thought patterns, and in doing so, was able to drive her self-transformation. The detailed artwork in the reflective visual diary served as a visual reminder of the researcher's growth and transformation throughout the study, providing a tangible representation of progress and a source of motivation to continue the journey towards self-improvement. data was collected through two main action cycles, with sub-cycles addressing imaginative teaching, transformative learning, and personal reflection. The study highlights the potential of visual art as a comp

关键词： Digital storage

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SAND: semi-automated adaptive network defense via programmable rule generation and deployment

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science China(Information sciences) 2022年第7期65卷 121-138页

作者： Haoyu CHEN Deqing ZOU Hai JIN Shouhuai XU Bin YUAN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabHubei Engineering Research Center on Big Data Security School of Cyber Science and EngineeringHuazhong University of Science and Technology Department of Computer Science University of Colorado at Colorado Springs

Cyber security is dynamic as defenders often need to adapt their defense postures. The state-ofthe-art is that the adaptation of network defense is done manually(i.e., tedious and error-prone). The ideal solution is to automate adaptive network defense, which is however a difficult problem. As a first step towards automation, we propose investigating how to attain semi-automated adaptive network defense(SAND). We propose an approach extending the architecture of software-defined networking, which is centered on providing defenders with the capability to program the generation and deployment of dynamic defense rules enforced by network defense tools. We present the design and implementation of SAND, as well as the evaluation of the prototype implementation. Experimental results show that SAND can achieve agile and effective dynamic adaptations of defense rules(less than 15 ms on average for each operation), while only incurring a small performance overhead.

关键词： network defense adaptive defense automated defense programmable defense security services software-defined networking security management

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Optimized Energy Distribution in Smart Grid System Using Hybrid Machine Learning Techniques 8

Optimized Energy Distribution in Smart Grid System Using Hyb...

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8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023

作者： Daorui, Ding Chang, Hong Durga Kumar, Burra Venkata School of Computing and Data Science Xiamen University Malaysia Sepang Malaysia

ISBN: (纸本)9798350310931

Smart Grid systems are becoming increasingly important with the rapid advent of industrial parks and residential areas. The aim of the Smart Grid system is to modernize and enhance the efficiency, reliability, and flexibility of electrical power grids. It integrates network, smart sensors, and time series prediction machine learning algorithms into the existing grid transmission system to collect the data and make predictions for optimizing decisions. With the help of big data techniques, Smart Grid systems can provide on-demand power supplies. However, most of the proposed prediction algorithms for Smart Grid system highly rely on pre-defined parameters and influential factors, such kind of models fail to dynamically update themselves to cater to the changing world especially when emergencies happen. In this paper, we introduce Dynamic Bayesian Network (DBN) concept and propose a new prediction architecture Smart Grid+ to improve the systems' self-adaptability and resilience to power outages, faults, and disruptions. Because of DBN's ability of dynamical expansion and posterior probability calculation from prior data, our proposed Smart Grid+ responds to emergencies more quickly and predicts the electricity load more precisely. And we believe it can better apply to the requirements of Smart Grid system and has a promising future. © 2023 IEEE.

关键词： Bayesian networks

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Multilingual Synopses of Movie Narratives: A dataset for Vision-Language Story Understanding

Multilingual Synopses of Movie Narratives: A Dataset for Vis...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Sun, Yidan Yu, Jianfei Li, Boyang College of Computing and Data Science Nanyang Technological University Singapore School of Computer Science and Engineering Nanjing University of Science and Technology China

ISBN: (纸本)9798891761681

Story video-text alignment, a core task in computational story understanding, aims to align video clips with corresponding sentences in their descriptions. However, progress on the task has been held back by the scarcity of manually annotated video-text correspondence and the heavy concentration on English narrations of Hollywood movies. To address these issues, in this paper, we construct a large-scale multilingual video story dataset named Multilingual Synopses of Movie Narratives (M-SYMON), containing 13,166 movie summary videos from 7 languages, as well as manual annotation of fine-grained video-text correspondences for 101.5 hours of video. Training on the human annotated data from M-SYMON outperforms the SOTA methods by 15.7 and 16.2 percentage points on Clip Accuracy and Sentence IoU scores, respectively, demonstrating the effectiveness of the annotations. As benchmarks for future research, we create 6 baseline approaches with different multilingual training strategies, compare their performance in both intra-lingual and cross-lingual setups, exemplifying the challenges of multilingual video-text alignment. The dataset is released at: https://***/insundaycathy/M-SyMoN. © 2024 Association for Computational Linguistics.

关键词： Visual languages

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Improving quantitative stock trading prediction based on MAD using Q-learning technology

Improving quantitative stock trading prediction based on MAD...

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2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Zhao, Pengcheng Yin, Siyuan Kumar, Burra Venkata Durga Yew, Teh Jia Xiamen University Malaysia School of Computing and Data Science Selangor Malaysia

ISBN: (纸本)9798350322309

Stocks are a proof of shares in a corporate enterprise and represent the ownership of the stockholder in the joint stock company. Stock trading is a dynamic and complicated project, stock history data is a non-linear and highly noisy time series. Considering the risky nature of stock trading, it is essential to provide an optimal prediction method to ensure stock trading security. The accuracy of traditional stock trading prediction is insufficient, so this study attempts to use reinforcement learning models for stock trading change prediction under big data. This paper proposes the median absolute deviation method (MAD) and Q-learning model to build a more effective prediction model. The simulation results based on NASDAQ Composite (^IXIC) data show that the new method can better help predict stocks. The method has some limitations and currently uses a combination of traditional econometric models and reinforcement learning models, which have some efficiency issues. However, the research in this paper provides a good extension to the theoretical aspects of stock prediction analysis and can provide investors with new research methods and perspectives. © 2023 IEEE.

关键词： Forecasting

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An Intelligent Machine Learning Approach to Detect Spam in Social Media 5

An Intelligent Machine Learning Approach to Detect Spam in S...

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5th International Conference on data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Mohandas, R. Prasanna, D.S. John Deva Meenakshi, N. Kaviyaraj, R. Nathiya, S. Arivazhagan, N. Srm Institute of Science and Technology School of Computing Department of Computational Intelligence Kattankulathur India Srm Institute of Science and Technology School of Computing Department of Data Science and Business Systems Kattankulathur India

ISBN: (纸本)9798350389609

Machine learning based intelligent approach is applied to finding spam in YouTube videos. Spam comments are ones that are promotional or unrelated. A growing number of users have been drawn to the idea of making money by placing advertisements on popular social networking platforms over time. These remarks damage a channel's reputation. YouTube has addressed the issue with a limited set of solutions that concentrate on preventing comments from including links. Such heuristics are now futile since spammers have found ways to get around them. Despite the fact that common machine learning classification techniques have demonstrated considerable success, new methods can still increase accuracy. Therefore, this research attempt to identify such statements using machine learning techniques like Random Forest, SVM, and Naive Bayes. In order to convey a clear concept, graphs are used to illustrate data cleaning, data analysis, text preparation, and model building in this research. © 2024 IEEE.

关键词： Adversarial machine learning

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GAME-BASED LEARNING TO IMPROVE CRITICAL THINKING AND KNOWLEDGE SHARING: LITERATURE REVIEW 67

GAME-BASED LEARNING TO IMPROVE CRITICAL THINKING AND KNOWLED...

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67th Annual Meeting of the International Society for the Systems sciences, ISSS 2023

作者： Katual, Daniel Goede, Roelien Drevin, Lynette Unit of Data Science and Computing North-West University South Africa

ISBN: (纸本)9781713893455

Game-based learning is an innovative approach that combines educational content with interactive gameplay, providing students with an engaging and immersive learning experience. By incorporating interactive and engaging elements, games have the potential to create an immersive learning environment that fosters active participation and deep understanding. However, despite the growing interest in this field, there is still a need for further exploration and understanding of how game-based learning can be effectively utilized to improve critical thinking and knowledge sharing. The purpose of this paper is to explore the potential of using games as an effective educational tool. It aims to investigate how game-based learning can enhance knowledge sharing among learners and foster the development of critical thinking abilities. To achieve this purpose, the research conducted in this paper includes a literature review on game-based learning and its impact on knowledge sharing and critical thinking skills. Additionally, the paper presents a case study that demonstrates the effectiveness of a specific game-based learning approach. The findings of this research contribute to the understanding of how games can be utilized to enhance educational outcomes and promote active engagement among learners. The paper provides guidelines for implementing game-based learning in educational settings and offers recommendations for designing effective game-based learning experiences. © Copyright, Author(s) (Creative Commons), 2023.

关键词： Computer aided instruction

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A CRITICAL SYSTEMS APPROACH TO CONFERENCE ORGANISATION 67

A CRITICAL SYSTEMS APPROACH TO CONFERENCE ORGANISATION

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67th Annual Meeting of the International Society for the Systems sciences, ISSS 2023

作者： Coetzee, Marijke Goede, Roelien Unit for Data Science and Computing North-West University South Africa

ISBN: (纸本)9781713893455

The problem this research addresses is organising an academic conference to cater for stakeholders with various worldviews participants successfully. Organising the conference is often placed on an academic with a specific worldview who may fail to consider the limitations they impose on the conference direction. Churchmann's systems approach widens the conference organiser's perspective to ensure all stakeholders are considered. A holistic view of components and how they interact and influence each other is taken by modelling the conference organisation as an open system. The distinction between the 'involved' and the 'affected,' as proposed by Ulrich, is central to this work, requiring a witness to represent the conditioned reality of the affected. Conference organisers are challenged to review their assumptions and those of others involved to identify limitations and opportunities that may have been overlooked. Minimising the uncertainty surrounding the dynamic changes in different conference streams can ensure a conference's survival and growth. The research is practically demonstrated by analysing the objectives and components of the SAICSIT 2023 and ISSS 2023 conferences. Overall, this research highlights the importance of adopting a systems thinking approach to conference organisation to successfully incorporate many perspectives into their conference planning activity to cater to all participants. © Copyright, Author (Creative Commons), 2023.

关键词： Systems thinking

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