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2023 International Conference on Electrical Engineering and Informatics, ICEEI 2023

作者： Illia, Fathonah Nooraeni, Rani Suadaa, Lya Hulliyyatus Politeknik Statistika Stis Department of Statistical Computing Jakarta Indonesia Data Science Research Unit Politeknik Statistika Stis Jakarta Indonesia

ISBN: (纸本)9798350381290

SDGs Goal 6 is one of the crucial objectives within the SDGs framework, making fulfilling this goal highly significant as it determines the achievement of other SDGs. As a serious global issue, this goal can be addressed through scientific research and innovation. However, research on this goal is often not well-known, leading to a need for more connection between the academic world and practitioners in implementing available solutions. Consequently, identifying critical pathways through scientific research is essential to attain this goal effectively. One of the expedient approaches is the utilization of topic modeling, which also facilitates the analysis of research topic trends related to SDGs Goal 6. This study employs topic modeling on data sourced from SemanticScholar using the BERTopic method, which captures the comprehensive context of research articles. The research results indicate that studies focusing on SDGs Goal 6 are interconnected with other SDGs. The default BERTopic model, chosen as the optimal model, illustrates that there is a prevailing topic tendency in target 6.3 related to water quality. © 2023 IEEE.

关键词： Water quality

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Always Provide Context: The Effects of Code Context on Programming Error Message Enhancement 2023

Always Provide Context: The Effects of Code Context on Progr...

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2nd ACM Conference on Global computing Education, CompEd 2023

作者： Santos, Eddie Antonio Prasad, Prajish Becker, Brett A. School of Computer Science University College Dublin Dublin Ireland School of Computing & Data Sciences Flame University Maharashtra Pune India

ISBN: (纸本)9798400700484

Programming error messages (PEMs) are notoriously difficult for novice programmers to utilise. Many efforts have been made to enhance PEMs such that they are reworded to explain problems in terms that novices can understand. However, the effectiveness of these efforts to enhance PEMs has been weak or inconclusive. This work seeks to determine the role that code context has on programming error message enhancement. Erroneous Java code written by novices was sampled from the Blackbox Mini dataset. The erroneous code was presented to expert raters with four different PEM variants: javac (control), Decaf - an error message enhancing IDE - and two variants generated using GPT-4: one that enhanced just the javac error message alone, and one that incorporates the code context in the prompt. We find that providing code context to LLMs increases the likelihood of correct explanations for underlying errors, produces more specific fixes for erroneous programs, and produces fixes that are more likely to be correct. In large language models, the community now has a resource that is capable of taking code context into account, to the benefit of novice programmers. © 2023 Owner/Author.

关键词： Feedback

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Guardians of Truth: Exploring Techniques for Veracity Identification in social media during an Infodemic 3

Guardians of Truth: Exploring Techniques for Veracity Identi...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Suthanthiradevi, P. Revathy, G. Sathish Kumar, P. Karthikeyan, B. Muthu, Lakshmi.V SRM institute of Science and Technology Data Science and Business Systems School of Computing India Vels Institute of science Technology and Advanced studies Department of Computer science and engineering India Rajalakshmi institute of technology Computer and Communication Engineering India SASTRA Deemed University School of Computing India St. Joseph's Institute of Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798350372120

With the recent advent of technology, social networks are accessible 24/7 using mobile devices. During covid-19 pandemic the propagation of misinformation are mostly related to the disease, its cures and prevention. With Twitter as the medium this information was spreaded to millions of people who lack domain specific knowledge. This can lead to bloster fear and direct damage to the people. This research focuses on identifying the veracity of the Twitter posts behind pandemic situation. The authors have proposed a Transformer Model using Bat Algorithm for identifying the fake news. This model is trained and evaluated using infodemic metadata. Our experimental results shows by which proposed model accurately detected the fake news and achieved 96.5% of f1-score. © 2024 IEEE.

关键词： Social networking (online)

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Network2U: Cloud Business Templates 13

Network2U: Cloud Business Templates

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13th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2022

作者： Bohan, Nolan Manzi, Miranda Yun, Mira Wentworth Institute of Technologuy School of Computing and Data Science BostonMA United States

ISBN: (数字)9781665463164

ISBN: (纸本)9781665463164

Businesses are transitioning towards using cloud services for many of their networking and system needs. However, designing and implementing these cloud services can be costly for business owners. In this paper, we propose Network2U, a business cloud network infrastructure service built upon Google Cloud. Network2U can be fit into several types of business by extending two sample templates. Current templates include a school system where hundreds of students will connect to a network, with strict security requirements regarding student data. The other template is a hybrid workforce finance company, where its users will connect to the network from different locations, and customer data security is key. These templates provide the different business types with all the systems, networking and security services needed to run their business. Network2U is for small or medium business owners who cannot invest in the large cost of getting a business cloud network infrastructure implemented. © 2022 IEEE.

关键词： Web services

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RokuControl-Conducting MITM Attacks on Roku 13

RokuControl-Conducting MITM Attacks on Roku

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13th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2022

作者： Coles, Devin Peterson, Michael Park, Sunjae Yun, Mira Wentworth Institute of Technology School of Computing and Data Science BostonMA United States

ISBN: (数字)9781665463164

ISBN: (纸本)9781665463164

Smart TVs are increasingly common in many house-holds as an alternative to traditional cable television. Smart TVs utilize high-speed Internet and allow people to watch streaming video services in a TV format. Man-in-the-middle attacks (MITM) insert the attacker between two devices that are communicating with each other. In this paper, we implement a MITM attack on a Roku device by capturing packets and replaying them using a packet crafter. Through such unauthorized control, this paper shows how the security of these devices can be impacted. © 2022 IEEE.

关键词： Network security

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EmoSync: Facial Emotion Detection for Adaptive Music Playback 3

EmoSync: Facial Emotion Detection for Adaptive Music Playbac...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Devarajan, Devikanniga Rajkumar, K. GITAM Deemed to be University Computer Science and Engineering Nagadenahalli Doddabalpur Karnataka Bangalore561203 India SRM Institute of Science and Technology Department of Data Science and Business Systems School of Computing Tamil Nadu Kattankulathur603 203 India

ISBN: (纸本)9798350372120

This work investigates using Convolutional Neural Networks (CNN) and VGGNet architecture, for realtime emotion detection. Raw data from the FER-2013 dataset is transformed from CSV format into organized image directories, segmented by distinct emotions. The resulting model, equipped with convolutional, pooling, and dense layers, effectively classifies emotions from 48x48 grayscale images. In application, the model overlays detected emotions onto a webcam stream. An integrated music player module synchronizes music with the subject's emotions. Overall, this research explores a comprehensive interactive system focused on recognizing and responding to human emotions. Without further training data, our model, to the best of our understanding, achieves modern single-network accuracy of 74.57% on FER2013 © 2024 IEEE.

关键词： Python

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Exploring Iterative Manifold Constraint for Zero-shot Image Editing

arXiv

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arXiv 2025年

作者： Li, Maomao Li, Yu Liu, Yunfei Xu, Dong School of Computing and Data Science The University of Hong Kong Hong Kong

Editability and fidelity are two essential demands for text-driven image editing, which expects that the editing area should align with the target prompt and the rest remain unchanged separately. The current cutting-edge editing methods usually obey an"inversion-then-editing" pipeline, where the input image is inverted to an approximate Gaussian noise zT , based on which a sampling process is conducted using the target prompt. Nevertheless, we argue that it is not a good choice to use a near-Gaussian noise as a pivot for further editing since it would bring plentiful fidelity errors. We verify this by a pilot analysis, discovering that intermediate-inverted latents can achieve a better trade-off between editability and fidelity than the fully-inverted zT. Based on this, we propose a novel zero-shot editing paradigm dubbed ZZEdit, which first locates a qualified intermediate-inverted latent marked as zp as a better editing pivot, which is sufficient-for-editing while structure-preserving. Then, a ZigZag process is designed to execute denoising and inversion alternately, which progressively inject target guidance to zp while preserving the structure information of p step. Afterwards, to achieve the same step number of inversion and denoising, we execute a pure sampling process under the target prompt. Essentially, our ZZEdit performs iterative manifold constraint between the manifold of Mp and Mp−1, leading to fewer fidelity errors. Extensive experiments highlight the effectiveness of ZZEdit in diverse image editing scenarios compared with the"inversion-then-editing" pipeline. Copyright © 2025, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

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Diversify, Rationalize, and Combine: Ensembling Multiple QA Strategies for Zero-shot Knowledge-based VQA

arXiv

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arXiv 2024年

作者： Li, Miaoyu Li, Haoxin Du, Zilin Li, Boyang College of Computing and Data Science Nanyang Technological University Singapore

Knowledge-based Visual Qustion-answering (K-VQA) often requires the use of background knowledge beyond the image. However, we discover that a single knowledge generation strategy is often insufficient for all K-VQA questions. To this end, we propose Diversification, Evidence Truncation, and Combination for Knowledge-based Elucidation (DIETCOKE), which utilizes a bundle of complementary question-answering tactics and aggregates their answers using textual rationales. DIETCOKE comprises of three stages: diversification, rationalization, and ensemble. The diversification stage generates three distinctive decision contexts, each leading to its own answer candidate. The rationalization stage generates two rationales, the automatic rationale and the mechanistic rationale, for each answer candidate using decorrelated techniques. Finally, in the ensemble stage, an LLM informed by the rationales selects one answer from the three candidates. Experiments show that DIETCOKE significantly outperforms state-of-the-art LLM-based baselines by 2.8% on OK-VQA and 4.7% on A-OKVQA and that the strategies in the ensembles are highly complementary. Code is available at: https://***/limiaoyu/DietCoke Copyright © 2024, The Authors. All rights reserved.

关键词： Question answering

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Mining Evidence about Your Symptoms: Mitigating Availability Bias in Online Self-Diagnosis 25

Mining Evidence about Your Symptoms: Mitigating Availability...

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2025 CHI Conference on Human Factors in computing Systems, CHI 2025

作者： Zhang, Junti Zhu, Zicheng Li, Jingshu Lee, Yi-Chieh Institute of Data Science National University of Singapore Singapore Singapore School of Computing National University of Singapore Singapore Singapore Computer Science School of Computing National University of Singapore Singapore Singapore Computer Science National University of Singapore Singapore Singapore

ISBN: (纸本)9798400713941

People frequently exposed to health information on social media tend to overestimate their symptoms during online self-diagnosis due to availability bias. This may lead to incorrect self-medication and place additional burdens on healthcare providers to correct patients' misconceptions. In this work, we conducted two mixed-method studies to identify design goals for mitigating availability bias in online self-diagnosis. We investigated factors that distort self-assessment of symptoms after exposure to social media. We found that availability bias is pronounced when social media content resonated with individuals, making them disregard their own evidences. To address this, we developed and evaluated three chatbot-based symptom checkers designed to foster evidence-based self-reflection for bias mitigation given their potential to encourage thoughtful responses. Results showed that chatbot-based symptom checkers with cognitive intervention strategies mitigated the impact of availability bias in online self-diagnosis. © 2025 Copyright held by the owner/author(s).

关键词： Diagnosis

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Multi-View Dynamic Kernelized Evidential Clustering

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2435-2450页

作者： Jinyi Xu Zuowei Zhang Ze Lin Yixiang Chen Weiping Ding the Software Engineering Institute East China Normal UniversityShanghai 200062 Shanghai Key Laboratory of Trustworthy Computing East China Normal UniversityShanghai 200062China IEEE the School of Automation Northwestern Polytechnical UniversityXi’an 710072China the School of Artificial Intelligence and Computer Science Nantong UniversityNantong 226019 the Faculty of Data Science City University of MacaoMacao 999078China

It is challenging to cluster multi-view data in which the clusters have overlapping *** multi-view clustering methods often misclassify the indistinguishable objects in overlapping areas by forcing them into single clusters,increasing clustering *** solution,the multi-view dynamic kernelized evidential clustering method(MvDKE),addresses this by assigning these objects to meta-clusters,a union of several related singleton clusters,effectively capturing the local imprecision in overlapping *** offers two main advantages:firstly,it significantly reduces computational complexity through a dynamic framework for evidential clustering,and secondly,it adeptly handles non-spherical data using kernel techniques within its objective *** on various datasets confirm MvDKE's superior ability to accurately characterize the local imprecision in multi-view non-spherical data,achieving better efficiency and outperforming existing methods in overall performance.

关键词： Evidential clustering imprecision characterizing kernel technique multi-view clustering

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