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Manhole dept. Analysis and Logistics Planning using TA-Enabled IoT Cloud 7

Manhole Depth Analysis and Logistics Planning using TA-Enabl...

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7th IEEE International conference for Convergence in Technology, I2CT 2022

作者： Bhagyalakshmi, M. Benedict, Shajulin Indian Institute of Information Technology Kottayam Dept. of Computer Science and Engineering Kerala 686635 India

ISBN: (纸本)9781665421683

Smart cities have marked an incessant push to modernize technologies for easing citizens. Smarter manholes and planning the associated logistics have become a crucial component for assisting city authorities while coining decisions. This article proposes an automatic manhole dept. analysis system using sensors mounted on manhole units. The sensor data collected in cloud services are utilized to schedule logistics using the proposed Threshold Acceptance (TA) algorithm. The algorithm attempts to minimize the distance between manhole operation sites and to improve the cost efficiencies associated with the operations. The proposed method was experimented at the IoT Cloud Research laboratory;the proposed TA-enabled logistics schedule produced a faster logistics plan to rectify manhole issues of streets based on the IoT-enabled monitoring system. The experiments manifested the cost efficiency improvement of over 38 percent and distance efficiency of over 78 percent when compared to the traditional approaches of handling manhole issues. © 2022 IEEE.

关键词： Internet of things

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Mobile Charger Scheduling Algorithm for Energy Recharging in Wireless Sensor Networks

Mobile Charger Scheduling Algorithm for Energy Recharging in...

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2022 International Conference on Electronic Systems and Intelligent Computing, ICESIC 2022

作者： Dande, Bhargavi Chang, Chih-Yung Fan, Cheng-De Tamkang University Dept. of Computer Science and Information Engineering New Taipei City Taiwan Tamkang University Dept. of Electrical and Computer Engineering New Taipei City Taiwan

ISBN: (纸本)9781665483858

In wireless sensor networks (WSNs), the finite battery capacity of the sensor nodes restricts the lifetime of the network. With the wireless power transfer (WPT) technology, the mobile chargers can transmit energy to the sensor nodes, which provides a solution for recharging the sensors. Therefore, this paper proposed a mobile charger scheduling (MCS) algorithm, which maximizes the coverage quality of the network. The proposed MCS algorithm formulated an adaptive recharging request threshold for the sensor nodes. Then the coverage benefit (CB) of the requested sensors is considered to dynamically adjust the path. Finally, through the experimental analysis, it is shown that the proposed MCS algorithm gains the best performance than the existing works. © 2022 IEEE.

关键词： Scheduling algorithms

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Mitigating DDoS Attacks using SDN-based Network Security Measures 2

Mitigating DDoS Attacks using SDN-based Network Security Mea...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Vadakkethil Somanathan Pillai, Sanjaikanth E Polimetla, Kiran University Of North Dakota Grand Forks School of Electrical Engineering and Computer Science North Dakota United States Adobe Inc Dept. of Information Technology AustinTX United States

ISBN: (纸本)9798350317558

Distributed denial-of-service attacks represent a significant threat to the delivery and integrity of network services. The attacks inundate a specific community or tool with excessive internet traffic, making it impossible for legitimate users to access. Given their intricate and ever-changing characteristics, conventional community safety functions, firewalls, and intrusion detection structures cannot effectively mitigate these threats. Consequently, it may be necessary to implement inexperienced and flexible solutions to counter DDoS attacks. A practical approach is the implementation of software-defined networking solutions for network security. Software-defined networking (SDN) prioritizes the ability of a community to have control over and efficiently manage the flow of data, as well as the capacity to manipulate centrally and program network devices. By utilizing SDN, community safety capabilities can dynamically alter the network's structure, routing, and location of net traffic to mitigate DDoS attacks. The feature allows for redirecting malicious internet traffic to a designated scrubbing centre, where these harmful websites can be filtered out before they reach the intended network or device. © 2024 IEEE.

关键词： Complexity Denial-of-carrier Dynamically Firewalls Malicious Websites SDN

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Smart Traffic Management in Green VANETs: Ant-Inspired Routing Strategies with Local Search Optimization

Smart Traffic Management in Green VANETs: Ant-Inspired Routi...

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2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Thangam, S. Jahnavi, M. Chandana, K. Dheeraj, K. Janet Kumari, J Jesy Saleem Raja, A. Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India University of Technology and Applied Sciences-Shinas College of Computing and Information Sciences It Department Oman

ISBN: (纸本)9798350309140

Green Vehicular Ad-hoc Networks (VANETs) are gaining significance in smart mobility because of growing concerns about the environment. The research introduces a novel method for managing traffic in such networks by combining ant-inspired routing methods with local search optimization approaches. The solution, which draws inspiration from the efficient path-finding abilities of ants, facilitates decentralized communication and sharing of traffic data among cars. It allows rapid adaptation to changing traffic circumstances and environmental elements. Local search optimization enhances routing decisions by considering the near vicinity of each vehicle. Extensive simulations demonstrate notable enhancements in traffic efficiency, decreased congestion, and improved energy conservation as compared to conventional routing methods. The suggested solutions also enhance the development of environmentally friendly and enduring transportation networks. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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iSFA: Intelligent SF Allocation Approach for LoRa-Based Mobile and Static End Devices

iSFA: Intelligent SF Allocation Approach for LoRa-Based Mobi...

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IEEE Conference on Wireless Communications and Networking

作者： Anakhi Hazarika Nikumani Choudhury Dept. of Electrical & Electronics Engineering India Dept. of Computer Science & Information Systems India

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

LoRaWAN (Long Range Wide Area Network) is a low-power, wide-area wireless communication protocol designed specifically for the Internet of Things (IoT) and machine-to-machine (M2M) applications that enable long-range, bidirectional communication between low-power devices. Lo-RaWAN employs Adaptive Data Rate (ADR) technology to dynamically adjust the data rate for each device based on its signal quality and distance from the gateway. ADR enables improved network performance, extends device battery life, and simplifies network management, making LoRaWAN suitable for various IoT deployments. However, the end devices' inefficient utilization of radio resources (e.g., spreading factor and transmission power) significantly degrades network performance, device battery life, and adaptability to changing network conditions. Machine Learning (ML) algorithms analyze and optimize the real-time network conditions to enhance network performance. This work aims to develop an ML-based approach that adaptively selects the most suitable Spreading Factor (SF) for end devices (ED). Two independent ML algorithms such as K-means and Reinforcement Learning (RL) have been applied to EDs and Gateways, respectively, to dynamically allocate SF for both static and mobile EDs. Through simulations, the performance of the proposed mechanism is analyzed in terms of packet success rate, convergence time, energy consumption, latency, and throughput.

关键词： Performance evaluation Wireless communication Wide area networks Machine learning algorithms Reinforcement learning Logic gates Throughput

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A Machine Learning Approach to Identifying Employees at Risk of Workplace Injury

A Machine Learning Approach to Identifying Employees at Risk...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Bablu Pramanik Santanu Modak Dept. of Computer Science & Engineering Brainware University Dept. of Information Technology Bengal College of Engineering and Technology

Workplace injuries are a critical concern, with millions occurring annually, leading to substantial human and economic costs. This study focuses on a qualitative analysis based on statistics from 2013 to 2017, with a specific emphasis on fatal and non-fatal workplace accidents within the European Union (EU) and Romania. The primary objective is to assess Romania's workplace safety status in the context of the EU and to propose strategic measures for improvement. To achieve this goal, four key indicators and statistical datasets are utilized, sourced from the National Institute of Statistics (NIS) of Romania, the Eurostat database of the European Commission, and the Romanian Labor Inspection. These indicators include the rate of incidence frequency index for occupational accidents, the average duration index, the frequency index for fatal accidents, and the severity index, enabling a comprehensive evaluation of accident frequency and severity. The rate of incidence, measuring injuries per 100,000 workers, is a pivotal indicator. Additionally, the study calculates the frequency index of non-fatal accidents (injuries per 1,000 employees) and the fatal accident frequency index (injuries per 1,000 workers). Statistical findings are rigorously validated through ANOVA analysis and T-tests. Following data evaluation, the study offers strategic recommendations informed by national and European strategies, including the National Occupational Safety and Health (OSH) Strategy for 2017–2020 and the "EU Strategic Framework on Health and Safety at Work" spanning 2014 to 2020. These recommendations aim to guide efforts for workplace accident control and prevention in Romania and the broader European *** summary, this study's core objective is to comprehensively analyze workplace accidents in Romania and the EU, employing various indicators and statistical data. Its primary aim is to assess the current status and propose evidence-based strategies for improvement, aligning wit

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RadioModRec-l: A Large Scale Radio Frequency Dataset for Automatic Modulation Recognition Research 4

RadioModRec-l: A Large Scale Radio Frequency Dataset for Aut...

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4th International Conference on Emerging Trends in Networks and computer Communications, ETNCC 2024

作者： Adetiba, Emmanuel Olasina, Jamiu R. Obiyemi, Obiseye Covenant University Covenant Applied Informatics and Communication Africa Center of Excellence Dept. of Electrical and Information Engineering Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban4001 South Africa Federal Polytechnic Ilaro Dept. of Computer Engineering Ilaro Nigeria Durban University of Technology Space Science Centre Dept. of Electrical Power Engineering Durban South Africa

ISBN: (纸本)9798350353266

Access to well-curated large datasets remains a significant bottleneck in AI-based research within wireless communication. Rapid advancements in neighbouring fields, such as computer vision and natural language processing, are largely due to the availability of extensive open-access datasets. However, similar progress has not been observed in wireless communication. To address this gap, we curated a comprehensive dataset for fifteen digital modulation schemes, including 4QAM, 16QAM, 64QAM, 256QAM, 8PSK, 16PSK, 32PSK, 64PSK, 128PSK, 256PSK, CPFSK, DBPSK, DQPSK, GFSK, and GMSK. Our dataset considers Rayleigh and Rician channel models under Additive White Gaussian Noise (A WGN) with SNRs ranging from -20dB to + 20dB in 5dB increments. The data samples were converted to constellation signal images and carefully pre-processed. Named RadioModRec, this dataset provides a valuable resource for researchers to train and evaluate AI models. It is freely accessible on Kaggle, promoting further innovation in the wireless communication domain. © 2024 IEEE.

关键词： Signal to noise ratio

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DViTPolyp: Small Polyp Detection in Colonoscopy Videos based on Deep Vision Transformer 4

DViTPolyp: Small Polyp Detection in Colonoscopy Videos based...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Ma, Ming Xia, Likun Seo, Hyunseok Katz School of Science and Health Yeshiva University Dept. of Graduate Computer Science and Engineering New York United States College of Information Engineering Capital Normal University Beijing China Biomedical Research Institute Korea Institute of Science and Technology Seoul Korea Republic of

ISBN: (纸本)9798350395914

Early detection of colorectal polyps and removal play a crucial role in the prevention of colon cancer. computer-aided detection (CAD) methods can be employed to help endoscopists reduce the polyp miss-rates. Numerous automatic polyp detection methods have been explored. However, it is still challenging to automatically detect colon polyps in small size in colonoscopy videos. This paper presents a method termed DViTPolyp for detecting small colorectal polyp in colonoscopy videos. The proposed method leverages the power of the deep vision transformer as the detection head in the network to aggregate rich global features, and uses the re-attention mechanism to regenerate attention maps to capture the features from the backbone model and DViT block. Also, we propose to use a power regularized Intersection Over Union (IoU) as the loss function to further enhance the accuracy of detection. Experiments are conducted on a mix of several public polyp datasets. Comparative results show that our proposed method has a better performance than other methods. © 2024 IEEE.

关键词： colonoscopy videos loss function polyp detection vision transformer

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Obmaaq: Ontology-Based Model for Automated Assessment of Short-Answer Questions 1

Obmaaq: Ontology-Based Model for Automated Assessment of Sho...

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1st International Conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

作者： Ramnarain-Seetohul, Vidasha Bassoo, Vandana Rosunally, Yasmine University of Mauritius Dept. of Information and Communication Technologies Reduit Mauritius University of Mauritius Dept. of Electrical and Electronic Engineering Reduit Mauritius University of the West of England Dept. of Computer Science and Creative Technology London United Kingdom

ISBN: (纸本)9798350342796

Automated scoring of short answers is becoming increasingly important nowadays, as more classes are taking place online due to COVID-19 outbreaks. Over the past 50 years, different techniques have been applied to develop ways of assessing short answers automatically. The automated assessment of short answer questions has been used with varying kinds of questions in different domains. However, no interoperable tools have been developed to facilitate the automated assessment of short answers for common modules across educational institutions. In this paper, we present a novel system called OBMAAQ, which grades short answers for questions designed according to Bloom's revised taxonomy remember category. The proposed system uses publicly available domain ontologies to grade short answers in different subject areas. This method is unique as it does not use model answers since it relies solely on the domain ontologies by utilizing an ontology-based pruning technique to grade the students' responses. The purpose of the system is to allow teachers from different educational institutions to use a similar approach when assessing the short answers for common modules automatically. Two publicly available domain ontologies in the field of security and computer networks have been used to validate students' answers. Experimental results based on both datasets indicate some promising results even though it is less than the set thresholds. This paper discusses the lessons learned and future recommendations based on the OBMAAQ model. © 2023 IEEE.

关键词： Assessment Automated marking Ontology Short answer Text mining

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Adaptive Privacy and Lightweight Security in Healthcare IoT: Challenges, Solutions and Future Directions

Adaptive Privacy and Lightweight Security in Healthcare IoT:...

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Innovation in Computing and engineering (ICE), International Conference on

作者： Mukul Chauhan Tayyab Khan Dept. of Computer Science & Engineering Indian Institute of Information Technology Sonepat India

ISBN: (数字)9798350380460

ISBN: (纸本)9798350380477

IoT in healthcare has transformed patient care by enabling and implementing the real-time monitoring for the end patients or users. However, the development of connected devices introduces significant privacy and security challenges, especially while securing the healthcare data. In this paper, a comparative review of adaptive privacy and lightweight security mechanisms in the area of healthcare IoT is shown. A comparison of current methods based on criteria including data security, privacy preservation, scalability, resource efficiency, and real-time implementation is one of the major contributions. Furthermore, this review recognizes the research gaps in the recent researches and highlights promising techniques, including advanced encryption, federated learning, and the edge computing. By addressing these challenges, the study aims to guide the development of robust, efficient, and scalable solutions that ensure privacy and security in dynamic healthcare IoT environments.

关键词： Privacy Data privacy Technological innovation Reviews Scalability Medical services Real-time systems Encryption Security Edge computing

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