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31st International Conference on Computational Linguistics, COLING 2025

作者： Zhang, Yanyue Li, Pengfei Lai, Yilong He, Yulan Zhou, Deyu School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China Department of Informatics King's College London United Kingdom The Alan Turing Institute United Kingdom

ISBN: (纸本)9798891761964

As more than 70% of reviews in the existing opinion summary data set are positive, current opinion summarization approaches are hesitant to generate negative summaries given the input of negative texts. To address such sentiment bias, a direct approach without the reliance on a specific structure is to generate additional data based on large language models to balance the emotional distribution of the dataset. However, large-scale data augmentation based on large language models faces an apparent disadvantage, the expensive costs. Therefore, in this paper, we propose LASS, a novel data augmentation framework based on both LArge and Small language models for debiaSing opinion summarization. Specifically, a small number of synthesized negative reviews is obtained by rewriting the positive text via a large language model. Then, a disentangle reconstruction model is trained based on the generated data. After training, a large amount of synthetic data can be obtained by decoding the new representation obtained from the combination of different sample representations and filtering based on perplexity degree and sentiment classification. Experiments have proved that LASS can effectively alleviate emotional bias, similar to using only large models, but in a more economical way. © 2025 Association for Computational Linguistics.

关键词： Data assimilation

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Using GPT and authentic contextual recognition to generate math word problems with difficulty levels

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Education and Information Technologies 2024年第13期29卷 1-29页

作者： Hwang, Wu-Yuin Utami, Ika Qutsiati Graduate Institute of Network Learning Technology National Central University Taoyuan 320317 Taiwan Department of Computer Science and Information Engineering National Dong Hwa University Hualien 974301 Taiwan Data Science Technology Engineering Department Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia

Automatic generation of math word problems (MWPs) is a challenging task in Natural Language Processing (NLP), particularly connecting it to real-life problems because it can benefit students in developing a higher level of mathematical thinking. However, most of the MWPs are presented within a scholastic setting in a decontextualized way. This paper describes a prototype system that generates authentic math word problems (i.e., real-life problems) using authentic contextual recognition with controlled difficulty levels. Our innovative approach includes the acquisition of authentic contextual information through recognition technology, an instructional-based prompt generator for three different difficulty levels, and question generation through the Generative Pre-trained Transformer (GPT) model. We evaluated the performance of the system in terms of the quality of generated questions using automatic evaluation and human evaluation. Further, we assessed the usability of the system using heuristic evaluation. The automatic evaluation showed our generated MWPs were relevant for geometry topics and varied in sentence generation. The human evaluation found our system generated more realistic problems with satisfactory language quality and mathematical validity. Our system also produced more questions with higher difficulty levels based on human evaluation. Heuristic evaluation captured the usability of the system and highlighted the potential to be applied in a pedagogical context for mathematics learning. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Authentic context Difficulty level Math word problems Natural language processing Primary school Question generation Technology education

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Collaborative image compression and classification with multi-task learning for visual Internet of Things

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Chinese Journal of Aeronautics 2022年第5期35卷 390-399页

作者： Bing DU Yiping DUAN Hang ZHANG Xiaoming TAO Yue WU Congchong RU School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China School of Computer Science and Technology Xidian UniversityXian 710071China Smart Network Computing Lab Cross-strait Tsinghua Research InstitutionBeijing 100084China

Widespread deployment of the Internet of Things(Io T)has changed the way that network services are developed,deployed,and *** onboard advanced Io T devices are equipped with visual sensors that form the so-called visual Io ***,the sender would compress images,and then through the communication network,the receiver would decode images,and then analyze the images for ***,image compression and semantic inference are generally conducted separately,and thus,current compression algorithms cannot be transplanted for the use of semantic inference directly.A collaborative image compression and classification framework for visual Io T applications is proposed,which combines image compression with semantic inference by using multi-task *** particular,the multi-task Generative Adversarial networks(GANs)are described,which include encoder,quantizer,generator,discriminator,and classifier to conduct simultaneously image compression and *** key to the proposed framework is the quantized latent representation used for compression and *** with perceptual quality can achieve low bitrate compression and reduce the amount of data *** addition,the design in which two tasks share the same feature can greatly reduce computing resources,which is especially applicable for environments with extremely limited *** extensive experiments,the collaborative compression and classification framework is effective and useful for visual IoT applications.

关键词： Deep learning Generative Adversarial network(GAN) Image classification Image compression Internet of Things

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The Proof is in the Pudding: Decision-Oriented Machine-Type Wireless Video Transmission

The Proof is in the Pudding: Decision-Oriented Machine-Type ...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Song, Jie Gao, Yun Wu, Dan Zhou, Liang Qian, Yi Nanjing University of Posts and Telecommunications Ministry of Education Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing China Army Engineering University of Pla Institute of Communications Engineering Nanjing China University of Nebraska-Lincoln Department of Electrical and Computer Engineering Lincoln United States

ISBN: (纸本)9798350351255

With the rise of the Internet of Everything, machine-type wireless video applications like intelligent surveillance are increasingly becoming mainstream network services. However, the massive transmission of video streams heavily burdens wireless networks. Existing methods typically establish a correlation between the transmitted content and the quality of experience or service, making it challenging to balance trade-offs among decision quality, bandwidth utilization, and latency requirements. To address this issue fundamentally, this paper proposes a novel perspective by designing wireless video transmission strategies from the angle of decision quality, where only the content that impacts the decision outcomes is transmitted. The highlight of this paper is designing a lightweight yet efficient binary classifier that predicts whether the current content will change decision outcomes based on content discrepancies, measured only through pixel-level differences and macroblock-level similarity. Furthermore, these discrepancies can be used to distinguish the background, thereby further saving bandwidth by reusing the background information. Additionally, a fine-tuning module is incorporated to flexibly update the classifier model, ensuring adaptability across various scenarios. Extensive results demonstrate that the proposed strategy achieves over 81% redundant bandwidth savings while maintaining decision quality and catering to strict latency requirements on computation-constrained devices. © 2024 IEEE.

关键词： Television transmission

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CONDITION ASSESSMENT OF 150 KV OUTDOOR COMPOSITE INSULATORS FOLLOWING A VEGETATION FIRE EVENT 23

CONDITION ASSESSMENT OF 150 KV OUTDOOR COMPOSITE INSULATORS ...

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23rd International Symposium on High Voltage engineering, ISH 2023

作者： Mavrikakis, Nikolaos C. Siderakis, Kiriakos Mouratis, Kiriakos Koudoumas, Emmanouel Section of Crete-Rhodes Transmission System Islands Network Operation Department Hellenic Electricity Distribution Network Operator S.A. Heraklion Greece High Voltage Laboratory Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Greece Center of Materials Technology and Photonics Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Greece

ISBN: (纸本)9781839539954

In electric power transmission and distribution systems, the use of overhead lines instead of underground cables is preferred by power utilities mainly due to the lower construction cost and the easier maintenance access. On the other hand the equipment used in overhead lines is stressed by several factors, such as weather conditions, lightning, vegetation fires, etc. In particular, vegetation fires under the overhead transmission lines could have catastrophic results for the installed equipment and can cause long-lasting electricity interruptions. In this study, condition assessment results are presented for eighteen 150 kV composite insulators exposed to a forest fire event, occurred in the August 2021, in the island of Rhodes, Greece. The evaluation of the fire effects on composite insulators was performed by employing several macroscopic and microscopic diagnostic techniques including visual inspection, hydrophobicity classification, Fourier Transform Infrared spectroscopy (FTIR) and optical microscopy analysis. © The Institution of engineering & Technology 2023.

关键词： Construction equipment

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Probabilistic Analysis and Optimization of Packet Losses in Dense LoRa networks

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SN computer Science 2022年第1期3卷 25页

作者： Sa-Ingthong, Jirapon Phonphoem, Anan Jansang, Aphirak Jaikaeo, Chaiporn Intelligent Wireless Network Group Department of Computer Engineering Faculty of Engineering Kasetsart University 50 Ngamwongwan Rd. Ladyao Jatujak Bangkok Thailand

LoRa is a low-power wide area network technology capable of delivering data over very long distances. Due to its wider range, a LoRa network may be subject to a higher probability of packet collisions when deployed with a large number of end devices. To help LoRa network planners analyze the performance in terms of packet losses, and adjust communication parameters to improve reliability, a proper mathematical model is needed. In this paper, we develop a packet loss model that takes into account individual end devices’ packet arrival rates, transmission powers, and distances from a gateway. The derived model is applied to an optimization problem to find appropriate transmission powers in form of a linear program. Experiments show that packet loss probabilities predicted by the model mostly conform with the results from simulations and the model accurately predicts the aggregated interference, along with the expected loss rate, under moderate to heavy data traﬃc. In addition, the proposed optimization technique allows lowering the overall transmission powers while maintaining comparable signal-to-interference ratio and packet loss rate. © The Author(s).

关键词： Linear programming LoRa LPWAN Overlapped collision Packet loss model Reliability

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High Performance of Smart Refrigerator System Based on IoT Technique 16

High Performance of Smart Refrigerator System Based on IoT T...

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16th International Conference on Developments in eSystems engineering, DeSE 2023

作者： Alsanad, Hamid R. Al-Askari, Mohanad A. Omar, Khaldoon A. Almashhadany, Yousif Algburi, Sameer Yaseen, Taisir A. University of Anbar Department of Electrical Engineering Anbar Iraq University of Anbar Information Systems Department Anbar Iraq Al-Kitab University College of Engineering Kirkuk Iraq University of Anbar Computer Network Department Anbar Iraq

ISBN: (纸本)9798350381344

The Internet of Things (IoT) has made a significant impact on improving human life in the modern era, offering convenience and ease. Smart appliances, which are connected to the Internet, have become increasingly popular due to their improved efficiency, robustness, power consumption, and connectivity. The main objective of this paper is to convert a conventional refrigerator into an intelligent appliance by integrating computational intelligence using a microcontroller and a range of sensors. The proposed approach aims to improve food management capabilities by introducing automated techniques and cost-effective intelligence to the refrigerator. The resulting smart refrigerator is designed to be user-friendly and improve the overall quality of life. The system includes a mobile or web application that acts as a bridge between the refrigerator and the user, allowing for remote control and monitoring. The smart refrigerator employs sensors to detect shortages of items and can automatically place orders online or send messages to grocery stores for item delivery. Additionally, the smart module continuously monitors temperature and humidity levels, uploading real-time updates to a cloud platform for user access. The integration of IoT technology into refrigerators offers numerous features and benefits, ultimately enhancing convenience and efficiency in managing food storage and consumption. © 2023 IEEE.

关键词： Internet of things

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Accountable Distributed Access Control With Privacy Preservation for Blockchain-Enabled Internet of Things Systems: A Zero-Trust Security Scheme

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IEEE Internet of Things Journal 2025年第11期12卷 17936-17947页

作者： Fang, He Xu, Li Nan, Guoshun Zheng, Danyang Zhao, Haitao Wang, Xianbin Fujian Normal University College of Computer and Cyber Security Fuzhou350007 China Beijing University of Posts and Telecommunications National Engineering Research Center for Mobile Network Technologies Beijing100876 China Southwest Jiaotong University School of Computing and Artificial Intelligence Chengdu610031 China Nanjing University of Posts and Telecommunications Department of Wireless Communication Key Lab of Jiangsu Province Nanjing210003 China Western University Department of Electrical and Computer Engineering LondonONN6A 5B9 Canada

While being able to avoid single point failures, emerging decentralized security techniques are facing new challenges of reliability, robustness, and privacy preservation in blockchain-enabled Internet-of-Things (IoT) systems. To circumvent these issues, a zero-trust security scheme is proposed through distributed access control, enhanced authentication, dynamic authorization, and privacy preservation enabled by the consortium blockchain. The proposed scheme integrates three key components, i.e., a distributed recommendation mechanism, where multiple authorized nodes are utilized as referrers to efficiently confer their trust on a new public entity for enhanced authentication;an anonymous credential generation strategy, which is developed for the new entity to further protect its privacy from linking attacks;and an adaptive reputation update strategy, which is proposed for evaluating the nodes' behaviors in the system for accountability and dynamic multiple-level authorization. The proposed scheme is implemented in a Hyperledge Fabric and the results show that it significantly enhances security and protects private information. © 2014 IEEE.

关键词： Differential privacy

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Empowering Software engineering Students: The Role of Gamification in Promoting Learning Independence 7

Empowering Software Engineering Students: The Role of Gamifi...

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7th International Conference on Vocational Education and Electrical engineering, ICVEE 2024

作者： Hidayat, Wahyu Nur Hamdan, Achmad Ichwanto, Muhammad Aris Muslihati Cakir, Gulsun Kurubacak Sari, Rahajeng Kartika Afni, Nur Hisyam, Mochammad Raffi Fadhil Universitas Negeri Malang Faculty of Engineering Department of Electrical Engineering and Informatics Malang Indonesia Universitas Negeri Malang Faculty of Vocational Department of Electronic Systems Engineering Technology Malang Indonesia Universitas Negeri Malang Faculty of Engineering Department of Civil Engineering and Planning Malang Indonesia Universitas Negeri Malang Faculty of Education Science Department of Guidance and Counseling Malang Indonesia Ankara Haci Bayram Veli University College of Communication Department of Journalism Ankara Turkey Smk Negeri 10 Malang Department of Computer Network and Telecommunication Engineering Malang Indonesia

ISBN: (纸本)9798331505103

The role of learning media greatly supports the learning process, increasing motivation and interest in the process. Learning media can also be a place to improve competence optimally through bootcamp training menus and the like with more specific training objectives. The main objective of this study is to develop a gamification-based website to enhance students' preparedness for their Final Competency Test by tackling challenges in comprehending programming absent practical experience. The learning method implemented in this website is case-based learning that integrates dynamic coding activities. The research method uses the Plomp approach with 3 main stages, namely preliminary research, prototyping, and assessment stage. The trial of the gamification website began with media and content validation followed by small group testing and large group testing. Validation by media and material experts led to the execution of small group trials (95.7%) and large group trials (91.7%), producing exceptionally positive outcomes. The results of the small group test with 12 respondents produced a very suitable value with a score of 95.7 and the large group test with 27 respondents produced a score of 9 1. 7 % with very suitable criteria. This indicates that the web-based platform is highly viable for assisting vocational students in acquiring software development skills, enhancing their preparedness for practical IT positions such as software developers and system analysts. Subsequent study involved the incorporation of gamification, such as computer-supported collaborative learning. © 2024 IEEE.

关键词： Software testing

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Large-scale Satellite Optical network Simulation Architecture and Performance Evaluation

Large-scale Satellite Optical Network Simulation Architectur...

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2024 Asia Communications and Photonics Conference, ACP 2024 and International Conference on Information Photonics and Optical Communications, IPOC 2024

作者： Wang, Xinjun Zhang, Zhenrong Zhu, Kangqi Hua, Nan School of Computer Electronic and Information Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi University Nanning China Department of Electronic Engineering Tsinghua University Beijing China

We evaluate the accuracy and performance of different simulation modes in MegaStarSim, analyze end-to-end routing strategies in large-scale satellite optical networks, and assess link quality across various inter-sate... 详细信息

ISBN: (纸本)9798350379266

关键词： Satellite links

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