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检索条件"任意字段=2014 IEEE International Conference on Progress in Informatics and Computing"

共 1842 条记录，以下是81-90 订阅

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TSPeer - Trust model for spherical Peer-to-Peer overlay networks 24

TSPeer - Trust model for spherical Peer-to-Peer overlay netw...

引用

24th international conference on Control Systems and Computer Science, CSCS 2023

作者： Mocanu, Alexandra-Elena Mocanu, Bogdan-Costel Apostol, Gabriel-Cosmin Negru, Catalin Petre, Ionut Pop, Florin University Politehnica of Bucharest Department of Computer Science Romania National Institute for Research and Development in Informatics Ici Bucharest Romania

ISBN: (纸本)9798350313390

The rise of mobile devices has revolutionized the way we interact with technology, enabling us to carry powerful computing devices in our pockets. However, with the increasing amount of sensitive information stored on these devices, trust has become a crucial factor in mobile security. Fingerprinting, which utilizes sensors embedded in mobile devices to recognize the unique characteristics of the user, has emerged as a promising approach to enhancing trust in mobile devices. Rapid response capability is crucial for the structure of a Peer-to-Peer system, as the nodes within the network have the flexibility to enter or exit at any moment without prior notification. This paper presents a novel approach to trust and reputation of mobile devices that use sensor fingerprinting techniques. Our approach uniquely identifies the nodes in a Peer-to-Peer network based on a spherical overlay such as TSPeer. We also discuss the challenges and limitations of this approach and evaluate it through simulation with real-life data sets. © 2023 ieee.

关键词： Fault tolerance

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Advanced Predictive Modelling for Bitcoin and Ethereum Price Dynamics

Advanced Predictive Modelling for Bitcoin and Ethereum Price...

引用

international conference on Contemporary computing and informatics (IC3I)

作者： Mohd Waseem Shailendra Narayan Singh Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Noida Uttar Pradesh India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Over the last decade, Bitcoin and Ethereum have become cryptocurrencies that have attracted the attention of the financial world with their potential for business transactions and the use of new blockchain technology. This study is dedicated to predicting Bitcoin and Ethereum price trends from 2014 to 2024, covering the main period of growth and change in the cryptocurrency market. This research aims to develop a good forecasting model through a comprehensive analysis of historical price data, market trends, economic progress and macroeconomy. It uses techniques such as machine learning, time series analysis, and sentiment analysis to try to predict future price movements of Bitcoin more accurately and Ethereum. By revealing the fundamental principles influencing cryptocurrency prices, this research leads to a deeper understanding of the dynamics driving digital assets and their impact on the financial sector.

关键词： Economics Sentiment analysis Time series analysis Bitcoin Machine learning Predictive models Market research Blockchains informatics Forecasting

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Optimizing Traffic Controllers along the MLK Smart Corridor Using Reinforcement Learning and Digital Twin 2

Optimizing Traffic Controllers along the MLK Smart Corridor ...

引用

2nd ieee international conference on Digital Twins and Parallel Intelligence, DTPI 2022

作者： Saroj, Abhilasha Trant, Toan V. Guin, Angshuman Hunter, Michael Sartipi, Mina School of Civil and Environmental Engineering Georgia Institute of Technology GA United States University of Tennessee at Chattanooga Center for Urban Informatics and Progress TN United States

ISBN: (纸本)9781665492270

With advancements in Intelligent Transportation Systems (ITS), sensors, and computing resources, several cities across the world are investing in the development of smart/connected corridors. These corridors are being equipped with advanced sensors that provide real-time, high-resolution data from the corridor and enable vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communications. The objective of this study is to optimize signal timings for one such smart corridor - MLK Smart Corridor - in Chattanooga, Tennessee, USA with respect to fuel and energy consumption (represented by Fuel Consumption Intersection Control Performance Index, EcoPI, that determines the excess fuel consumption due to stops and delays caused by traffic controllers). © 2022 ieee.

关键词： Reinforcement learning

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Visual Facial Paralysis Detection using InceptionResNetV2

Visual Facial Paralysis Detection using InceptionResNetV2

引用

ieee international conference on Automatic Control and Intelligent Systems (I2CACIS)

作者： Nurul Natasha Razlan Raihah Aminuddin Nurbaity Sabri Shafaf Ibrahim Anis Amilah Shari College of Computing Informatics and Mathematics Universiti Teknologi MARA College of Computing Informatics and Mathematics Universiti Teknologi MARA Shah Alam Malaysia

ISBN: (数字)9798350372106

ISBN: (纸本)9798350372113

Facial paralysis, stemming from nerve issues, results in the inability to control facial muscles, leading to asymmetry and weakness. This condition not only affects appearance but also disrupts daily activities. Diagnosis is time-consuming and requires specialized expertise and equipment. To address these challenges, a deep learning-based is proposed to analyze facial expressions and distinguish between normal and paralyzed states. The Facial Paralysis Detection leveraging InceptionResNetV2 by including preprocessing, augmentation, and classification on facial images. Evaluation on dataset of 2000 images of facial paralysis and normal face, these images are divided into training, validation, and testing sets with a ratio of 5:1:1, achieves 92.7% accuracy in distinguishing normal and paralyzed facial expressions, marking significant progress in healthcare diagnostics. Further experimentation will be carried out on alternative deep-learning structures in order to attain the highest precision.

关键词： Training Analytical models Visualization Accuracy Medical services Paralysis Planning

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LWN Simulator - A LoRaWAN Network Simulator

LWN Simulator - A LoRaWAN Network Simulator

引用

2023 ieee international conference on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE 2023

作者： Santoro, Corrado Santoro, Federico Fausto University of Catania Department of Mathematics and Informatics Catania Italy

ISBN: (纸本)9798350350432

The Internet of Things is rapidly evolving, thanks also to technological innovations, in particular to new technologies of radio communication with low energy consumption. Nevertheless, testing a possible complex infrastructure to verify the management of several devices and their communication could be difficult to implement and especially wasteful. LWN Simulator is a LoRaWAN network simulator, able to simulate device nodes and gateway and it is equipped with a web interface with which to interact with the simulation in real-time. The simulator lets the user create and interact with Virtual Gateways, changing their status, geographical position and other network information or adding a Real Gateway already present in a real network. Also, the simulator allows the simulation of all device classes, supporting the Adaptive Data Rate, MAC commands and the personalisation of the payloads. Finally, the entire simulation environment, devices and gateways, runs on a real LoRaWAN infrastructure, such as Chirpstack or The Things Stack. This feature allows a real network design that can be implemented using real devices with the same settings and configurations. © 2023 ieee.

关键词： Cloud computing architecture

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Enhancing Semantic Segmentation Through a Targeted Approach to Hard-to-Classify Examples

Enhancing Semantic Segmentation Through a Targeted Approach ...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Ganesh Ravindra Padalkar Madhuri B. Khambete Department of Electronics and Telecommunications MKSSS's Cummins College of Engineering for Women Pune India

ISBN: (数字)9798350363203

ISBN: (纸本)9798350363210

This research paper examines the effectiveness of semantic segmentation utilizing a weighted cross-entropy loss function. A modified version of cross-entropy loss is implemented to address data imbalance and improve predictions for hard-to-classify classes. Hyperparameters of the deep learning model are adjusted based on this modified loss function. The performance of the proposed loss function is evaluated through standard metrics.

关键词： Measurement Deep learning Visualization Accuracy Semantic segmentation Computational modeling Semantics Focusing informatics Standards

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An Evolutionary Algorithm for Adversarial SQL Injection Attack Generation

An Evolutionary Algorithm for Adversarial SQL Injection Atta...

引用

ieee international conference on Intelligence and Security informatics, ISI

作者： Maryam Issakhani Mufeng Huang Mohammad A. Tayebi Arash Habibi Lashkari Behaviour-Centric Cybersecurity Center (BCCC) School of Information Technology York University Toronto Canada School of Computing Science Simon Fraser University Burnaby Canada

Web application security poses ongoing challenges for organizations, and researchers have increasingly turned to machine and deep learning techniques to address vulnerabilities such as SQL injection and Cross Site Scripting. While these studies have made notable progress, the vulnerability to adversarial attacks remains a significant challenge. In this work, we aim to explore the impact of adversarial examples on machine and deep learning applications for detecting web vulnerabilities. We propose an evolutionary algorithm to create effective adversarial samples for bypassing various detection systems by iterative exploration of the search space. The effectiveness of our proposed approach is validated through rigorous testing on different diverse SQL injection detection systems.

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Enhanced Particle Swarm Optimization for Workflow Scheduling in Clouds 8

Enhanced Particle Swarm Optimization for Workflow Scheduling...

引用

ieee international conference on progress in informatics and computing (ieee PIC)

作者： Lu, Chang Feng, Dayu Zhu, Jie Huang, Haiping Nanjing Univ Posts & Telecommun Nanjing Peoples R China Jiangsu Key Lab Big Data Secur & Intelligent Proc Nanjing Peoples R China Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture Beijing Peoples R China Jiangsu High Technol Res Key Lab Wireless Sensor Nanjing Peoples R China

ISBN: (纸本)9781665426558

As a NP-hard problem, it is always baffling to figure out a scheduling strategy to arrange the interconnected tasks of a workflow on the infinite number of resources in the cloud environment so that the workflow can be addressed efficiently and robustly. This paper focuses on scheduling the workflow's tasks on the cloud resources with less rental cost of resources while the whole schedule length (makespan) will not exceed the given deadline. As one of the most popular evolutionary algorithms, particle swarm optimization (PSO) has been successfully applied for the workflow scheduling problem. Inspired by the idea of multiple groups and the distributed parallel computing, we develop an enhanced PSO algorithm for the workflow scheduling problem in clouds. Besides, a pretreatment strategy is adopted to simplify the workflow's structure. The experimental results demonstrate that our proposal has good performance on improving the algorithm's searching ability and finding better solutions.

关键词： Workflow scheduling cloud computing particle swarm optimization multiple groups

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progress of Nursing informatics for Mental Health Initiatives 2

Progress of Nursing Informatics for Mental Health Initiative...

引用

2nd international conference on Interdisciplinary Cyber Physical Systems, ICPS 2022

作者： Alenezi, Atallah Alghamdi, Abdulrahman A Shaqra University Applied Medical Science-Department of Nursing Shaqra Saudi Arabia Shaqra University College of Computing and Information Technology Shaqra Saudi Arabia

ISBN: (数字)9781665470223

ISBN: (纸本)9781665470223

While there is significant evidence linking information technology (IT) to enhanced safety of patients, quality of care, availability, and effectiveness, nursing staff must clearly show computer, information systems, and digital skills capabilities in order to utilise IT for practise, training, as well as research. The nurse practitioner has developed IT skills and knowledge for all stages of nurses, both novice and veteran. In addition, latest approved standards eloquent role-specific anticipations for advanced training. Regrettably, there is major worry that several nurses may lack these skills and that professional nurses are unprepared to instruct them. Often these students and faculty have newbie levels of skill, according to IT competency assessments that have primarily concentrated on nursing curriculum. Various researches, primarily in nursing education, have found that only focused interventions result in significant improvements in IT capabilities. This study contains medical and mental health nursing staff with a refresh on the literary works on IT capabilities, recent technological progress to establish and inventions, and their repercussions for the area of expertise. The mental health care that are now available are inextricably connected to the innovation that has been available to us for years of research and practise. Web, smartphone, sensor, as well as informatics technical advances can do more than just improve existing support systems. New technologies may further assist us better comprehend the information about mental disorder and challenge our underlying assumptions about the configuration, limitations, and modes of psychiatric treatment. © 2022 ieee.

关键词： Students

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LoRa™ Lab: Laboratory Network for Educational Purposes 21

LoRa™ Lab: Laboratory Network for Educational Purposes

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21st international conference on Emerging eLearning Technologies and Applications, ICETA 2023

作者： Valach, A. Zemko, L. Cicak, P. Jelemenska, K. Slovak University of Technology Faculty of Informatics and Information Technologies Bratislava Slovakia

ISBN: (纸本)9798350370690

The Internet of Things describes scenarios in which Internet connectivity and computing capabilities are extended to everyday objects. Those devices have limited computational power and are often battery-powered or energy-harvesting. Many communication technologies specifically designed for the Internet of Things environment have emerged. Low-Power Wide-Area networks are popular as they provide a long communication range and are energy efficient. Despite many advantages, the Internet of Things faces several challenges, which need to be addressed shortly. To provide research opportunities and additional training, it is important to have a dedicated network, which is flexible enough, and thus allows modifications and network stack manipulation. In this paper, the Low-Power Wide-Area Networks are explored, with the main focus on LoRa™ technology. Next, current research performed at the Faculty of informatics and Information Technologies is presented. And finally, a private LoRa™ laboratory network is described in detail. © 2023 ieee.

关键词： Laboratories

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