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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Chang, Ting-Jui Lin, Lydia Hsiao-Mei Tsai, Richard Tzong-Han National Central University Department of Computer Science and Information Engineering Taoyuan Taiwan National Taipei University of Technology Department of Interaction Design Taipei Taiwan Research Center for Humanities and Social Sciences Academia Sinica Taipei Taiwan

ISBN: (纸本)9798350360721

It is expected to deploy chatbots as sales assistants on e-commerce platforms soon. In recent years, the capabilities demonstrated by large language models (LLMs) indicate their suitability for this role. However, a dialogue process is not fully established. Most existing works concentrate on searching for ideal products, such as Retrieval-Augmented Generation (RAG) and product search. Many proposed methods rely on product reviews. However, in the case of some e-commerce platform products, valuable reviews are often lacking, rendering these approaches impractical. Thus, we studied how to assist users and select a set of candidate products. Accordingly, we simulated sales conversations based on the product features provided by the seller, using LLM and reliable content while addressing the cold-start problem. Specifically, we used product features to generate customer persona for user simulation. LLM was used to play the role of sales assistant in giving recommendations. The experimental results showed that practical conversation was created between customers and chatbots in Traditional Chinese. The code and results are available at: https://***/terryobe-ncu/CPR_LLM © 2024 IEEE.

关键词： Sales

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Fingerprint Liveness Detection Using Denoised-Bayes Shrink Wavelet and Aggregated Local Spatial and Frequency Features 21

Fingerprint Liveness Detection Using Denoised-Bayes Shrink W...

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21st International Conference on Machine Learning and Cybernetics, ICMLC 2022

作者： Raswa, Farchan Hakim Kinarta, Indra Yusuf Pulungan, Reza Harjoko, Agus Lee, Chungting Li, Yung-Hui Wang, Jia-Ching National Central University Department of Computer Science and Information Engineering Taiwan Universitas Gadjah Mada Department of Computer Science and Electronics Indonesia Hon Hai Research Institute Ai Research Center Taiwan

ISBN: (数字)9781665488327

ISBN: (纸本)9781665488327

Fingerprint has a competent level of uniqueness because the various features can form different patterns in humans. It is a verification requirement in various aspects, such as mobile phone, banking accounts, attendance, etc. One of the preventive measures in maintaining performance is liveness detection. We deep exploited the handcrafted method to achieve adequate performance. To encapsulate the noise possibility, we added the Bayes shrink-wavelet transform as the noise removal. So, the noise obtained in the fingerprint image can be minimized but keep the quality of the fingerprint image is in good condition. Then, we conjugated the spatial and frequency domain in pixel neighborhood distribution using the local binary pattern (LBP) and local phase quantization (LPQ) feature. Finally, we mapped the learning stage using a prominent classifier, i.e., a support vector machine (SVM). Our experiment was evaluated with LivDet 2015 dataset. The proposed method has achieved sustainable results regarding average error rate (AER). © 2022 IEEE.

关键词： Local binary pattern

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Relevance Queries for Interval Data

Proceedings of the ACM on Management of Data

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Proceedings of the ACM on Management of Data 2025年第3期3卷 1-26页

作者： Panagiotis Bouros Nikos Mamoulis Institute of Computer Science Johannes Gutenberg University Mainz Mainz Germany Department of Computer Science and Engineering University of Ioannina Ioannina Greece and Archimedes Athena Research Center Athens Greece

A wide range of applications manage large collections of interval data. For instance, temporal databases manage validity intervals of objects or versions thereof, while in probabilistic databases attribute values of records are associated with confidence or uncertainty intervals. The main search operation on interval data is the retrieval of data intervals that intersect (i.e., overlap with) a query interval (e.g., find records which were valid in September 2020, find temperature readings with non-zero probability to be within [24, 26] degrees). As query results could be many, we need mechanisms that filter or order them based on how relevant they are to the query interval. We define alternative relevance scores between a data and a query interval based on their (relative) overlap. We define relevance queries, which compute only a subset of the most relevant intervals that intersect a query. Then, we propose a framework for evaluating relevance queries that can be applied on popular domain-partitioning interval indices (interval tree and HINT). We present experiments on real datasets that demonstrate the efficiency of our framework over baseline approaches.

关键词： interval data range query ranking query selection query top-k

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Wireless Sensor Networks and Green Networking for 6G communication- An Overview 1

Wireless Sensor Networks and Green Networking for 6G communi...

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Bordoloi, Dibyahash Yadav, Satya Prakash Near East University Ai and Robotics Institute Research Center for Ai and IoT Department of Computer Engineering Nicosia Turkey Near East University Ai and Robotics Institute Artificial Intelligence Engineering Dept. Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Turkey Graphic Era Hill University Dehradun Rs Cse Graphic Era University Dept. of Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

Wireless sensor networks and green networking have been major research areas in the field of communication technology for the past few decades. In particular, the development of 6G communication systems has brought renewed focus on these areas, as the demands for higher data rates, more diverse applications, and lower energy consumption continue to increase. The use of wireless sensor networks in 6G communication systems has been widely explored in the literature, and has shown great potential for a wide range of applications, including environmental monitoring, industrial process control, and healthcare. However, a key challenge in the deployment of these networks is ensuring their energy efficiency, as the demands on the network will be much higher than in previous generations. To address this challenge, researchers have proposed various green networking techniques, such as energy harvesting and low-power communication protocols, which have been shown to significantly reduce the energy consumption of the sensors. In addition to improving the energy efficiency of wireless sensor networks, researchers have also studied their reliability, scalability, and adaptability. These properties are important in 6G communication systems, as the demands on the network are expected to be much higher than in previous generations. researchers have proposed various methods to improve the reliability, scalability, and adaptability of wireless sensor networks, including the use of error-correction codes, redundant communication channels, and machine learning algorithms. © 2023 IEEE.

关键词： Wireless sensor networks

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Detecting Users Prone to Spread Fake News on Arabic Twitter 5

Detecting Users Prone to Spread Fake News on Arabic Twitter

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5th Workshop Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur'an QA and Fine-Grained Hate Speech Detection, OSACT 2022

作者： Ali, Zien Sheikh Al-Ali, Abdulaziz Elsayed, Tamer Computer Science and Engineering Department Qatar University Qatar KINDI Center for Computing Research Qatar University Qatar

ISBN: (纸本)9791095546757

The spread of misinformation has become a major concern to our society, and social media is one of its main culprits. Evidently, health misinformation related to vaccinations has slowed down global efforts to fight the COVID-19 pandemic. Studies have shown that fake news spreads substantially faster than real news on social media networks. One way to limit this fast dissemination is by assessing information sources in a semi-automatic way. To this end, we aim to identify users who are prone to spread fake news in Arabic Twitter. Such users play an important role in spreading misinformation and identifying them has the potential to control the spread. We construct an Arabic dataset on Twitter users, which consists of 1,546 users, of which 541 are prone to spread fake news (based on our definition). We use features extracted from users’ recent tweets, e.g., linguistic, statistical, and profile features, to predict whether they are prone to spread fake news or not. To tackle the classification task, multiple learning models are employed and evaluated. Empirical results reveal promising detection performance, where an F1 score of 0.73 was achieved by the logistic regression model. Moreover, when tested on a benchmark English dataset, our approach has outperformed the current state-of-the-art for this task. © European Language Resources Association (ELRA).

关键词： COVID-19

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Network Intrusion Detection Based on Hybrid Network Model and Federated Learning 7th

Network Intrusion Detection Based on Hybrid Network Model an...

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7th International Conference on Information science, Communication and Computing, ISCC 2023

作者： Kou, Yuqing Cheng, Jieren Yang, Yue Wu, Hao Li, Yajing Sheng, Victor S. Hainan Blockchain Engineering Research Center Hainan China School of Computer Science and Technology Hainan University Haikou570228 China School of Cyberspace Security Hainan University Haikou570228 China Department of Computer Science Texas Tech University LubbockTX79409 United States

ISBN: (纸本)9789819971602

Data is a valuable strategic resource for the development of modern society. However, with the increasingly complex network environment, privacy leaks and malicious attacks emerge in endlessly. For example, blockchain has also begun to become a new outlet for network black production, which poses a huge security threat to cryptocurrency. In this paper, we propose a hybrid network model (Cb Net), which uses Convolutional Neural Networks (CNN) and Bidirectional recurrent neural networks (BiGRU) to fully extract the space-time characteristics of network data traffic. Then, we propose an intrusion detection method (FLD), which introduces federated learning to collect traffic data from different network institutions, analyze network traffic and identify network attacks. We have fully evaluated the performance of the proposed model and method on the public dataset NSL-KDD. Experiments show that the proposed hybrid network model can achieve high detection accuracy, and the FLD method can effectively identify network attacks on the premise of ensuring the privacy of the local data of the users involved, and its performance is better than other methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Complex networks

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高质量的AlGaN外延结构和UVC垂直腔面发射激光器的实现

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science China Materials 2023年第5期66卷 1978-1988页

作者：郑重明王玉坤胡建正郭世平梅洋龙浩应磊莹郑志威张保平 Department of Electronic Engineering Optoelectronics Engineering Research CenterSchool of Electronic Science and Engineering(National Model Microelectronics College)Xiamen UniversityXiamen 361005China Advanced Micro-Fabrication Equipment Inc. Shanghai 201201China

AlGaN基垂直腔面发射激光器(VCSEL)因其优越的材料性质和器件优点吸引了很多关注.然而,由于材料外延生长和器件制备工艺的局限,AlGaN基VCSEL制备很困难.本工作通过侧向外延生长技术制备了高质量的AlGaN多量子阱(MQWs)结构的外延片,并通... 详细信息

AlGaN基垂直腔面发射激光器(VCSEL)因其优越的材料性质和器件优点吸引了很多关注.然而,由于材料外延生长和器件制备工艺的局限,AlGaN基VCSEL制备很困难.本工作通过侧向外延生长技术制备了高质量的AlGaN多量子阱(MQWs)结构的外延片,并通过X射线衍射(XRD)和光致发光(PL)实验对外延片进行了分析.XRD测量显示,外延片中的AlN模板层几乎是弛豫的,刃位错密度为10^(9)cm^(-2).随后,生长的AlGaN/AlN超晶格(SL)层被用来减少刃位错密度,使得量子阱中的位错密度为10^(8)cm^(-2).根据PL测试结果,MQWs的内量子效率(IQE)为62%,且在室温下的发光以辐射复合为主.通过激光剥离(LLO)和化学机械抛光(CMP)技术,将这些外延片制备成UVC VCSEL.经过这些工艺,MQWs的晶体质量没有受到影响,还在抛光之后的表面观察到了UVC波段的受激辐射.这些AlGaN基UVC VCSEL在275.91,276.28和277.64 nm实现了激射,最小激射阈值为0.79 MW cm^(-2).

关键词： AlGaN vertical-cavity surface-emitting lasers epitaxial lateral overgrowth laser lift-off UVC

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A novel cooperative collision avoidance system for vehicular communication based on deep learning

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International Journal of Information Technology (Singapore) 2024年第3期16卷 1661-1675页

作者： Farhat, Wajdi Ben Rhaiem, Olfa Faiedh, Hassene Souani, Chokri Laboratory of Microelectronics and Instrumentation University of Monastir Monastir Tunisia Higher Institute of Applied Sciences and Technology Sousse University Sousse Tunisia Computer Science Department College of Science Northern Border University Arar Saudi Arabia Digital Research Center of SFax (CRNS) SM@RTS (Laboratory of Signals systeMs aRtificial Intelligence and neTworkS) Sfax Tunisia

Global road traffic injuries represent a significant safety challenge, with the highest fatality rates worldwide stemming from a combination of drivers' reckless behavior and the ever-expanding number of vehicles on the roads. In light of these factors, Autonomous Vehicles (AVs) have received a lot of attention as a technology that has the potential to revolutionize various industries and solve a lot of problems. The rise of the Internet of Vehicles (IoV) and Connected Vehicles (CVs) enables AVs to perceive and react swiftly in complex road scenarios, prioritizing safety. These vehicles prioritize individual safety in all situations, significantly enhancing road safety. Mobile Edge Computing (MEC) plays a crucial role thanks to its capacity for minimal latency and high bandwidth capabilities, enabling critical vehicular applications. In this paper, we introduce a cooperative collision avoidance system based on MEC, named 2CAS-MEC, that proactively identifies and locates road hazards. Our system is based on MEC servers positioned alongside roads, it consistently analyzes traffic and hazard data, issuing targeted alerts to nearby vehicles regarding potential risks. Particularly, our work introduces an advanced deep learning system that utilizes 5G, mobile edge computing, and cloud intelligence to prevent vehicle collisions. The experimental results show that our system outperforms the existing related works and exhibits the anticipated performance, effectively helping drivers in accident avoidance. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Cloud Connected and autonomous vehicles Deep learning IOV MEC Vehicle to-everything (V2X)

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Blockchain Security Threats and Collaborative Defense:A Literature Review

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computers, Materials & Continua 2023年第9期76卷 2597-2629页

作者： Xiulai Li Jieren Cheng Zhaoxin Shi Jingxin Liu Bin Zhang Xinbing Xu Xiangyan Tang Victor S.Sheng School of Computer Science and Technology Hainan UniversityHaikou570228China School of Cyberspace Security Hainan UniversityHaikou570228China Hainan Blockchain Technology Engineering Research Center Hainan UniversityHaikou570228China Hainan Hairui Zhong Chuang Technol Co.Ltd. Haikou570228China Department of Computer Science Texas Tech UniversityLubbock79409USA

As a distributed database,the system security of the blockchain is of great significance to prevent tampering,protect privacy,prevent double spending,and improve *** to the decentralized and trustless nature of blockchain,the security defense of the blockchain system has become one of the most important *** paper comprehensively reviews the research progress of blockchain security threats and collaborative defense,and we first introduce the overview,classification,and threat assessment process of blockchain security ***,we investigate the research status of single-node defense technology and multi-node collaborative defense technology and summarize the blockchain security evaluation indicators and evaluation ***,we discuss the challenges of blockchain security and future research directions,such as parallel detection and federated *** paper aims to stimulate further research and discussion on blockchain security,providing more reliable security guarantees for the use and development of blockchain technology to face changing threats and challenges through continuous updating and improvement of defense technologies.

关键词： Blockchain threat assessment collaborative defense security evaluation

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Internet of Intelligent Things (IoT) - An Overview 1

Internet of Intelligent Things (IoT) - An Overview

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Aeri, Manisha Yadav, Satya Prakash Ai and Robotics Institute Research Center for Ai and IoT Near East University Nicosia Department of Computer Engineering Mersin10 Turkey Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept. Mersin Nicosia10 Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Mersin10 Turkey Graphic Era Hill University Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

The basic goal of the IoT is to permit the online connection and communication of everyday physical objects like appliances, vehicles, and other gadgets. This paves the way for effortless and automated data collection and exchange, as well as interaction between the objects themselves and with humans. The Internet of Everything (IoE) is an expansion of the Internet of Things (IoT) that aims to maximize and improve human life by connecting and making the most of all available resources (humans, information, and technology). The transportation, healthcare, agricultural, energy, and manufacturing sectors are all examples. The IoIT aims to incorporate AI and ML within the IoT's interconnected network of physical items. These objects can then independently behave in response to the information they have gathered and the instructions they have been given. This has the potential to lead to smarter, more efficient systems that can react to new information and human input in real time. The Internet of Things, the Internet of Everything, and the Industrial Internet of Things all have the same overarching goal: to pave the way for the development of more efficient and intelligent systems and processes that can enhance a wide range of human endeavors. However, in order to make sure that these technologies are used in a responsible and ethical way, it will be necessary to carefully analyze their consequences and the issues they provide. © 2023 IEEE.

关键词： Internet of things

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