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International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Appala Hari Narayana Karthik B Venkat Vinod Kumar Bejji Bharadwaj Sree Sai Karthikeya Meena Belwal Department of Computer Science and Engineering Amrita School Of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505479

This study offers a thorough analysis of bottom-up parsing techniques, necessary for the creation and execution of compilers. Parsers such as SLR (Simple LR), LR (Canonical LR), LR(k) and LALR (Look-Ahead LR) are bottom-up and known for their efficiency and robustness in constructing parse trees from root to leaves during syntax analysis. This paper follows the evolution throughout history, theoretical bases, and real-world uses of these parsers. We examine the formal characteristics, contrast different bottom-up parsing methods, and investigate advanced subjects like error handling and optimization techniques. Furthermore, there is a review of recent developments and upcoming research paths in bottom-up parsing to provide a comprehensive grasp of their significance in syntactic analysis.

关键词： Surveys Reviews Semantics Syntactics Robustness Grammar Error correction History Information technology Optimization

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Smart Steps to Sporting Success: IoT-Driven Footwear Innovations

Smart Steps to Sporting Success: IoT-Driven Footwear Innovat...

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International Conference on computing and Networking Technology (ICCNT)

作者： S Thangam Gadi Joshith S Santhosh V Harish J Jesy Janet Kumari Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Using the cloud platform Blynk IoT, smart sneakers with built-in step and calorie monitoring were created with athletes in mind. The primary characteristic of the smart shoe is its ability to detect early signals of cramping in the muscles during athletic exercises. This allows for prompt response to protect the athlete’s foot and performance. It also acknowledges the vulnerabilities that athletes may encounter during training; this feature guarantees that athletes can notify the user by sending them messages in the event of any potential hazard. Beyond features for health and safety, the smart shoe calculates steps and tracks activity, giving athletes useful information for their training and recuperation regimens. With a focus on safety first, this project tackles important issues like sensor accuracy, device longevity, user comfort, and data security to produce a solution that improves athletic performance. By providing athletes with a comprehensive tool for health monitoring and personal safety, the smart shoe seeks to redefine wearable technology in sports.

关键词： Training Performance evaluation Heating systems Technological innovation Footwear Muscles Hazards Health and safety Monitoring Sports

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Can you pass that tool?: Implications of Indirect Speech in Physical Human-Robot Collaboration 25

Can you pass that tool?: Implications of Indirect Speech in ...

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

作者： Zhang, Yan Ratnayake, Tharaka Sachintha Sew, Cherie Knibbe, Jarrod Goncalves, Jorge Johal, Wafa School of Computing and Information Systems University of Melbourne MelbourneVIC Australia University of Melbourne Melbourne Australia School of Electrical Engineering and Computer Science The University of Queensland St LuciaQLD Australia

ISBN: (纸本)9798400713941

Indirect speech acts (ISAs) are a natural pragmatic feature of human communication, allowing requests to be conveyed implicitly while maintaining subtlety and flexibility. Although advancements in speech recognition have enabled natural language interactions with robots through direct, explicit commands - providing clarity in communication - the rise of large language models presents the potential for robots to interpret ISAs. However, empirical evidence on the effects of ISAs on human-robot collaboration (HRC) remains limited. To address this, we conducted a Wizard-of-Oz study (N=36), engaging a participant and a robot in collaborative physical tasks. Our findings indicate that robots capable of understanding ISAs significantly improve human's perceived robot anthropomorphism, team performance, and trust. However, the effectiveness of ISAs is task- and context-dependent, thus requiring careful use. These results highlight the importance of appropriately integrating direct and indirect requests in HRC to enhance collaborative experiences and task performance. © 2025 Copyright held by the owner/author(s).

关键词： Collaborative robots

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Combinatorial Incentive Mechanism for Bundling Spatial Crowdsourcing with Unknown Utilities

Combinatorial Incentive Mechanism for Bundling Spatial Crowd...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Hengzhi Wang Laizhong Cui Lei Zhang Linfeng Shen Long Chen College of Computer Science and Software Engineering Shenzhen University China School of Computing Science Simon Fraser University Canada

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

Incentive mechanisms in Spatial Crowdsourcing (SC) have been widely studied as they provide an effective way to motivate mobile workers to perform spatial tasks. Yet, most existing mechanisms only involve single tasks, neglecting the presence of complementarity and substitutability among tasks. This limits their effectiveness in practice cases. Motivated by this, we consider task bundles for incentive mechanism design and closely analyze the mutual exclusion effect that arises with task bundles. We then develop a combinatorial incentive mechanism, including three key policies: In the offline case, we propose a combinatorial assignment policy to address the conflict between mutual exclusion and assignment efficiency. We next study the conflict between mutual exclusion and truthfulness, and build a combinatorial pricing policy to pay winners that yields both incentive compatibility and individual rationality. In the online case with unknown workers’ utilities, we present an online combinatorial assignment policy that balances the exploration-exploitation trade-off under the mutual exclusion constraints. Through theoretical analysis and numerical simulations using real-world mobile networking datasets, we demonstrate the effectiveness of the proposed mechanism.

关键词： Crowdsourcing Mechanism design Pricing Numerical simulation Task analysis

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Automated Tooth Segmentation in X-ray Images using Attention Integrated U-Net++ Model

Automated Tooth Segmentation in X-ray Images using Attention...

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International Symposium on Advanced computing and Communication (ISACC)

作者： Julakanti Sai Yaswanth Kanderi Johith Kumar Rimjhim Padam Singh Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

Oral functioning, the ability to perform various oral functions, pain-free and without being ill, is one of the indicators of overall well-being and life satisfaction. Even though these diseases are mostly preventable, a majority of individuals all over the world suffer from periodontal disease, dental caries, and oral malignancies to an estimated of 5 billion people worldwide. However, there are still use of traditional radiographic techniques like periapical and panoramic radiography that assist in diagnosis. A better diagnosis is enhanced through the use of modern techniques in imaging such as MRI, ultrasonography and CBCT imaging. Deep learning-based solutions enhance diagnostic capabilities through dental segmentation in images since they learn from unmodified data in contrast to traditional machine learning and deep learning techniques which produce inferior results when dealing with massive datasets. Therefore, in an effort to solve the problem of efficient dental segmentation, anencoder-decoder basedtooth segmentation model based on U-Net++ architecture modified using Efficient Channel Attention Network is proposed that aims at enhancing the accuracy of dental diagnosis. The paper also focus of the performance of different state-of-art CNN techniques namely, U-Net, FCNs, ENet, U-Net++, U-Net 3+, SwiftNet on the standard Tuffs Dental dataset for model selection and comparisons. The proposed model outperforms other segmentation models and achieves the best mean average precision of 96.4% and a dice coefficient of 90%.

关键词： Deep learning Image segmentation Computational modeling Magnetic resonance imaging Ultrasonography Dentistry Convolutional neural networks Diagnostic radiography X-ray imaging Diseases

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A Performance Study of Block Proposing Mechanism in Ethereum 2.0

A Performance Study of Block Proposing Mechanism in Ethereum...

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IEEE International Conference on Blockchain (Blockchain)

作者： Zijie Liu Qinglin Zhao Shuhan Qi Li Feng Xiaofen Wang Sun Yi School of Computer Science and Engineering Macau University of Science and Technology Macau China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Chinese Academy of Sciences Institute of Computing Technology Beijing China

ISBN: (数字)9798350351590

ISBN: (纸本)9798350351606

Ethereum 2.0 (ETH2) marks a significant evolution from Ethereum 1.0 (ETHl), playing a central role in the Web3.0 infrastructure. At its core, the consensus protocol Gasper greatly affects system performance. Given that Gasper's parameters are empirically determined, there is a clear necessity for parameter tuning. This paper presents a simulation-based study that models the performance of the block proposing mechanism within Gasper. Our simulation results illustrate the impact of design parameters (e.g., block proposing interval) on throughput and non-forking probability. They may enable us to find optimal parameter configure to balance the two-performance metrics. These findings help enhance the system performance of ETH2.

关键词： System performance Simulation Smart contracts Throughput Cryptocurrency Consensus protocol Proposals

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Optimizing Drone Delivery Management: An Algorithmic Framework for Collision Detection and Avoidance with Resource Management

Optimizing Drone Delivery Management: An Algorithmic Framewo...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Paramkusam Sriharsha Yelipe Gowtham Geda Tejesh Chowdary Sreebha Bhaskaran Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

The revolutionary impact of drones on delivery services encounters major challenges, such as collision with other obstacles and other drones when operating inside crowded areas. This research introduces a Collision Detection and Avoidance (CDA) algorithm which performs effective path identification together with altitude reservation to prevent mid-air collisions. The system improves operational safety together with generating effective delivery routes that deliver both operational safety and efficiency. The system optimizes resource allocation through its ability to arrange drones for the purpose of meeting delivery requirements without excessive congestion. Performance measurement facilitates continuous system improvement. The research implements Dijkstra, A* and Bellman Ford shortest path algorithms to the CDA system for evaluating their transport safety and productivity and resource utilization performance. The analysis checks appropriate drone usage in diverse drone applications. The system proves its capability in the incorporation of real-time data for improving drone operations that leads to effective resource use in challenging delivery settings.

关键词： Productivity Performance evaluation Integrated circuits Continuous time systems Real-time systems Path planning Safety Resource management Collision avoidance Drones

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Unmasking Digital Deceptions: A Comprehensive Survey of Synthetic Reality Analysis Across Multimedia Domains

Unmasking Digital Deceptions: A Comprehensive Survey of Synt...

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2024 IEEE International Conference on Electronic Systems and Intelligent computing, ICESIC 2024

作者： Chaudhary, Sneha Chaurasiya, Komal Sriram, Suthir Ravikumar, S. Nivethitha, V. Thangavel, M. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology India United Arab Emirates University College of Information and Technology United Arab Emirates

ISBN: (纸本)9798331522988

The general accessibility of social networking sites like Facebook, Myspace and TikTok has transformed the way information is communicated, but it has also made it simpler to spread misleading information, thanks to cutting-edge technologies like deepfakes. The use of artificial intelligence in deepfake technology produces material that is remarkably life- like but fake, making it difficult to identify and remove fraudulent content. The evolution of deepfake technology is reviewed in this study, starting with early breakthroughs like the Video Rewrite Program and continuing with more current developments like the Synthesizing Obama and Face2Face projects. We provide a comprehensive analysis of the state-of-the-art detection strategies, namely Region-based CNNs (RCNNs), Conventional Neural Networks (CNNs), and hybrid approaches that combine various deep learning techniques. Though these methods have advanced, there are still issues with accuracy, integration complexity, and adaptability to new deepfake techniques. This paper suggests a novel approach that integrates image, video, and audio analysis into a single detection framework in order to overcome these difficulties. The new approach is directed towards improvement of detection accuracy and the lowering of the false alarm using advanced and deep learning engines along with the real time processing requirements. Early results indicate that the detection capabilities have significantly improved compared to existing solutions operating in real time environment while having less latency and higher recall and precision rates. This method is more effective for deepfake detection and at the same time helps in augmenting the comprehensiveness and efficiency of the system there by making it suitable for wider uses. The study emphasizes the presence of the need for the evolution of static approaches towards the effective defection of sophisticated false information and the justification of new possibilities in the fight a

关键词： Economic and social effects

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Securing Networks: Advanced Detection and Prevention of Address Resolution Protocol Cache Spoofing Attack 3

Securing Networks: Advanced Detection and Prevention of Addr...

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3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Sriharsha, V.V.S. Daule, Viraj Kisan Surya, R. Thangam, S. Amrita Vishwa Vidyapeetham Amrita School of Computing Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331508456

As the technology advances, an increase in the attacks to manipulate or extract data illegally has also risen. This also includes one such attack known as Address Resolution protocol cache spoofing attack. The Address Resolution protocol Spoofer conducts an in-depth exploration into one of the most significant security vulnerabilities identified in local networks, namely Address resolution protocol cache poisoning. The study implements a system which uses a Python based tool which is able to simulate Address Resolution protocol spoofing attacks on the network traffic of two hosts through a Python library known as the Scapy library. This tool allows the execution of Man In The Middle attacks by forging Address Resolution protocol replies and changing the stream of traffic without setting off any alarm by the user. The tool also has a detection mechanism that alerts the users as soon as it detects attempted spoofing;which hence identifies both the offender and the defensive capabilities in Address Resolution protocol spoofing. Additionally, another layer of security is added by user-defined encryption and decryption of the message being delivered. The study has resulted in a secure network, protecting the data from ARP spoofing. © 2025 IEEE.

关键词： HTTP

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

arXiv

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arXiv 2024年

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

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, CC BY.

关键词： Video analysis

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