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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Lungu, Nelson Dash, Bibhuti Bhusan De Chandra, Utpal Dash, Bibek Bikram Pattanayak, Binod Kumar Patra, Sudhansu Shekhar Electrical and Electronical Engineering University of Zambia Lusaka Zambia School of Computer Applications Kiit Deemed to be University Bhubaneswar India HealthWorksAI Bangalore India Iter Siksha 'O' Anusandhan University Department of Computer Science & Engineering Odisha Bhubaneswar India

ISBN: (纸本)9798350376425

Graphics processing units (GPUs) have become ubiquitous in computing systems, from personal devices to data centres. Their massively parallel architecture delivers tremendous performance for graphics and general-purpose workloads. However, the open nature of GPUs also introduces security vulnerabilities that can be exploited through side-channel attacks. Defending against such threats often incurs performance overhead, creating tradeoffs between security and speed. This article examines recent research analysing and mitigating GPU side channel attacks while maintaining acceptable performance and presented a multi-faceted defence strategy combining compiler transformations, runtime monitoring, and microarchitectural techniques to balance security and performance. The methodology integrates formal threat models, empirical side-channel evaluations, and rigorous benchmarking. It implements and evaluates prototypes demonstrating security improvement with minimal impact on representative workloads. The results provide promising directions for practical GPU security defences. © 2024 IEEE.

关键词： Program compilers

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A Whispering Widgets and Wireless Wonders Pioneering Change in the World of IoT 7th

A Whispering Widgets and Wireless Wonders Pioneering Change ...

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7th International Conference on Communication, Device and Networking, ICCDN 2024

作者： Tripathi, Amit Kumar Islam, Baharul Murugan, R. Adhvaryu, Rachit Department of Electronical and Electronics Engineering Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Department of Engineering Assam Down Town University Assam Guwahati India Karnataka Bangalore India Faculty of Engineering and Technology Department of Computer Science and Engineering Parul Institute of Engineering and Technology Parul University Gujarat Vadodara India

ISBN: (纸本)9789819753369

The IoT has made it possible to connect and control more devices than ever before, opening up new avenues for efficiency and creativity. However, new problems have emerged as a result of this explosion of linked devices, notably concerning the security and privacy of personal information. To meet these difficulties, we provide a new approach within the context of "Whispering Widgets and Wireless Wonders: Ushering in a New Era for the Internet of Things." Our suggested approach safeguards data during transit and storage by using state-of-the-art cryptographic methods including Elliptic Curve Cryptography (ECC) and the Advanced Encryption Standard (AES). Furthermore, we use blockchain technology to guarantee the immutability and transparency of data by creating a public and unchangeable ledger of all data exchanges. Our research shows that our suggested strategy for securing IoT data is superior to more conventional methods. We test how well our system protects sensitive information, keeps data intact, keeps users anonymous, and how efficient it is overall. When compared to conventional approaches, the "Proposed Method" regularly performs better, demonstrating its strength and applicability for protecting IoT data. High security is guaranteed by the combination of ECC and AES, and data integrity is improved by blockchain technology. Furthermore, our approach places a premium on user privacy, giving people more say over their data inside the IoT ecosystem. Finally, we believe that our suggested solution is a major advancement in achieving more data security and privacy in the IoT context. To the problems caused by the proliferation of linked gadgets, it provides a thorough and effective answer. Our approach prioritizes security, data integrity, and user privacy to let people and businesses get the benefits of the Internet of Things (IoT) without compromising on data privacy or security. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025

关键词： Data integrity

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The System Design and Robotic Manipulation Skills of Dualarm Autonomous Mobile Robot for Bomb Removing

The System Design and Robotic Manipulation Skills of Dualarm...

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2021 International Joint Conference on Robotics and Artificial Intelligence, JCRAI 2021

作者： Zhao, Dan Sun, Fuchun Li, Linxiang Department of Computer Science and Technology Tsinghua University Haidian Distinct Beijing100083 China Institute of Electronical Engineering Yanshan University Qinhuangdao China

Bomb removing is a very challenging but valuable task in urban anti-terrorist or military applications. With the rapid development of technologies of intelligent robots in these years, the intelligence and security level of bomb removing process can be largely improved by using the autonomous mobile robotic systems. In this paper, a dual-arm autonomous mobile robot for bomb removing is proposed which is designed by Tsinghua University. The system design is introduced which mainly consists of the structure and multimodal perception module of the designed system. Besides, manipulation performance is one of the most important functional attributes in bomb removing. Therefore, the manipulation skills for the bomb removing applications are analyzed which adopt the idea of primitives, and skill decomposition and synthesis. Moreover, a knowledge graph for bomb removing is established in the paper and a knowledge based method for the manipulation skills learning is presented. Finally, simulations and experiments have been carried out in the platform to validate the proposed method in the paper and designed bomb removing mobile robot. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Military applications

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Navigation On Mobile Computing Devices with A Walking Using Object-Oriented Techniques to Communicate Stick

Navigation On Mobile Computing Devices with A Walking Using ...

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Communication, Control and Intelligent Systems (CCIS)

作者： Ramesh Prabhakaran R Guhan P E George Dharma Prakash Raj Karthika K Angel Maanu P Department of Computer Engineering Mizoram University Mizoram India Department of Electrical and Electronical Engineering Panimalar Engineering College Chennai India School of Computer Science and Engineering Bharathidasan University Trichy India Department of Information Technology Karpagam College of Engineering Coimbatore India Department of Computer Science and Engineering Panimalar Engineering College Chennai India

ISBN: (数字)9798331528201

ISBN: (纸本)9798331528218

Moving around in their surroundings is challenging for elderly people and people with visual impairments. The majority of functional sticks in use today are not intelligent and lack an innate ability to recognize obstacles. In an effort to address this issue, mobility and orientation specialists who assist the blind by teaching them to move freely and safely using their remaining senses are brought in. They can navigate around obstacles with the aid of guidance dogs as well. These techniques have drawbacks, such as the dogs' inability to comprehend complicated instructions, the high cost of maintaining these trained dogs, and the need to hire an expert. In light of the aforementioned difficulties, the "Smart walking stick" has become a potential answer. The "Mobile based walking stick" is a useful mobility aid with the capacity to call a relative who can help in the event of an accident, detect obstacles above ground level and pits using ultrasonic sensors, recognize when a collision has occurred, and call the user's mobile phone if it has been misplaced to share the location's GPS for use with GSM connectivity and to share with the user's mention contacts. With some visually disabled people as test subjects, a test case was run, and 95% of the time it was successful.

关键词： Legged locomotion GSM Navigation Visual impairment Dogs People with disabilities Acoustics Sensor systems Intelligent sensors Global Positioning System

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A Terse Review of Heart Diseases Estimation Using Machine Learning Practices

A Terse Review of Heart Diseases Estimation Using Machine Le...

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Communication, computer sciences and engineering (IC3SE), International Conference on

作者： Rahul Pawar Amit Kumar Dash Gaurav Mittal Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Department of Electronical & Electronics Engineering Noida Institute Of Engineering and Technology Greater Noida Uttar Pradesh India Department of Computer Science and Engineering Tula's Institute Dehradun India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

Heart diseases, a primary cause of global fatalities, represent a growing social matter on a worldwide scale. The integration of machine learning with advancing technology has greatly benefited the medical field, resulting in the provision of seamless solutions characterized by high accuracy, consistency and toughness. These advancements help the patient society through early detection and reduced medical care costs. They also offer the medical fraternity capable, accessible, precise and consistent prediction systems. This paper provides a comprehensive enquiry of machine learning algorithms engaged for the prediction and classification of several cardiovascular diseases, we explore several modalities, including physiological signals, heart sounds and electronic health records, to achieve effective heart disease recognition. We also provide insights into popular machine learning systems, hybrid systems and fuzzy systems in this context. It is noted in this review that Support Vector Machines (SVM) have gained popularity and widespread usage, with neural networks and ensemble techniques following closely behind in terms of their application. All these approaches are compared based on accuracy metrics.

关键词： Heart Support vector machines Measurement Accuracy Machine learning algorithms Reviews Neural networks

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Influence of AI and MAS in Enhancing Energy Efficiency of 6G Communications

Influence of AI and MAS in Enhancing Energy Efficiency of 6G...

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Communication, computer sciences and engineering (IC3SE), International Conference on

作者： Divya Negi Febin Prakash Anjali Gupta Department of Computer Science and Engineering Tula's Institute Dehradun India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Department of Electronical and Electronics Engineering Noida Institute of Engineering and Technology Greater Noida Uttar Pradesh India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

Next-generation Internet of Things (IoT) is progressing rapidly due to the introduction of beyond 5G (B5G) and the approaching arrival of 6G, which have improved the dependability, productivity, and profitability of both industrial and personal operations. Nevertheless, data overload is frequently caused by the abundance of wireless sensors in commercial 6G devices. Data mining gathers useful information in order to solve this. Meanwhile, in the 6G architecture, edge computing enables automated equipment operations and intelligent decision-making in real-time. Even so, despite the drawbacks of sensor-based energy sources, the integration of many technologies has led to an increase in energy. Using a multi-agent system (MAS) approach, a system model for industrial wireless sensor networks in 6G applications has been presented in order to combat this. Sensor node clustering locates and forecasts the locations of principal nodes by employing distributed artificial intelligence (DAI). Convolutional neural networks (CNN) and back-propagation neural networks (BPNN) are used in optimisation. Allocating resources to individual nodes efficiently is made possible by the analysis of inter-cluster correlations. The outcomes of the simulation show how well the approach works to reduce resource waste, increase overall energy efficiency, and protect important data. This strategy improves network performance in industrial 6G applications while simultaneously addressing concerns about energy consumption.

关键词： 6G mobile communication Wireless communication Productivity Wireless sensor networks Profitability Energy efficiency Real-time systems

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Investigating Machine Learning (ML) in Augmented and Virtual Reality: A Comprehensive Analysis in Prawn Farming

Investigating Machine Learning (ML) in Augmented and Virtual...

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Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI), International Conference on

作者： Vaibhavi Painuly Kavitha R Ratna Raju Ravela Department of Computer Science and Engineering Tula's Institute Dehradun India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Department of Electronical & Electronics Engineering Noida Institute Of Engineering and Technology Greater Noida Uttar Pradesh India

ISBN: (数字)9798350355338

ISBN: (纸本)9798350355345

Commercial lakes ought to be kept up well in arrange to meet the expanding request for prawns universally and create at their best. This think about addresses the challenge by combining present day sensor innovation, expanded reality interfacing, and machine learning calculations. The plan employments state-of-the-art sensors to ceaselessly screen water quality, empowering proactive decision-making. Machine learning calculations analyze collected information to expect lake conditions, giving agriculturists with a see of potential future occasions. Increased reality representation encourages way better information collection and real-time decision-making through intuitively interfaces. This all-encompassing approach progresses efficiency, maintainability, and effectiveness within the prawn cultivating industry by revolutionizing current hones.

关键词： Technological innovation Decision making Employment Machine learning Water quality Virtual reality Lakes Real-time systems Farming

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Mix of Experts Language Model for Named Entity Recognition

Mix of Experts Language Model for Named Entity Recognition

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International Conference on Communications, Information System and computer engineering (CISCE)

作者： Xinwei Chen Kun Li Tianyou Song Jiangjian Guo Department of Electronical and Computer Engineering University of Illinois at Urbana Champaign Urbana IL USA Department of Computer Science University of Illinois at Urbana Champaign Urbana IL USA Department of Computer Science Columbia University New York USA Department of Computer Science and Engineering University of California San Diego La Jolla US

ISBN: (数字)9798350353174

ISBN: (纸本)9798350353181

Named Entity Recognition (NER) is an essential steppingstone in the field of natural language processing. Although promising performance has been achieved by various distantly supervised models, we argue that distant supervision inevitably introduces incomplete and noisy annotations, which may mislead the model training process. To address this issue, we propose a robust NER model named BOND-MoE based on Mixture of Experts (MoE). Instead of relying on a single model for NER prediction, multiple models are trained and ensembled under the Expectation-Maximization (EM) framework, so that noisy supervision can be dramatically alleviated. In addition, we introduce a fair assignment module to balance the document-model assignment process. Extensive experiments on real-world datasets show that the proposed method achieves state-of-the-art performance compared with other distantly supervised NER.

关键词： Training Annotations Computational modeling Named entity recognition Predictive models Noise measurement Information systems

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Few-Shot Name Entity Recognition on StackOverflow

Few-Shot Name Entity Recognition on StackOverflow

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6th International Conference on Intelligent Computing and Signal Processing (ICSP)

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

StackOverflow, with its vast question repository and limited labeled examples, raise an annotation challenge for us. We address this gap by proposing RoBERTa+MAML, a few-shot named entity recognition (NER) method leveraging meta-learning. Our approach, evaluated on the StackOverflow NER corpus (27 entity types), achieves a 5% F1 score improvement over the baseline. We improved the results further domain-specific phrase processing enhance results.

关键词： Metalearning Annotations Named entity recognition Signal processing

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Mix of Experts Language Model for Named Entity Recognition

arXiv

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arXiv 2024年

作者： Chen, Xinwei Li, Kun Guo, Jiangjian Song, Tianyou Department of Electronical and Computer Engineering University of Illinois at Urbana Champaign Urbana United States Department of Computer Science University of Illinois at Urbana Champaign Urbana United States Department of Computer Science and Engineering University of California La Jolla San Diego United States Department of Computer Science Columbia University New York United States

关键词： Natural language processing systems

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