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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

共 1532 条记录，以下是831-840 订阅

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Edge-assisted Puncturable Fine-grained Task Distribution for the IoT-oriented Crowdsensing 15

Edge-assisted Puncturable Fine-grained Task Distribution for...

引用

2022 ieee Congress on Cybermatics: 15th ieee international conferences on Internet of things, ithings 2022, 18th ieee international conferences on Green Computing and Communications, GreenCom 2022, 2022 ieee international conference on Cyber, Physical and Social Computing, CPSCom 2022 and 8th ieee international conference on Smart Data, SmartData 2022

作者： Jiang, Liquan Qin, Zhiguang University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu610054 China

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

Internet of things (IoT)-based mobile crowdsensing system has been increasingly widely deployed in data-driven smart city construction for its high efficiency, participation and flexibility. However, the mobile crowdsensing system may suffer unauthorized access to the task during the task distribution, thus imposing a threat to the city security and personal privacy. To deal with this threat, in this paper we propose an edge-assisted puncturable attribute-based access control scheme. this scheme provides efficient, one-to-many secure data sharing and delegates most of the computational overhead of resource-constrained terminal devices to the edge device. then we design and integrate the Bloom filter into the proposed scheme to cope with the key exposure without key update. We provide rigorous security proof and the analysis of security properties. theoretical comparison and experimental results demonstrate the feasibility and practicality of our scheme. © 2022 ieee.

关键词： Internet of things

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Development of Visual Dashboard for River Monitoring System 8

Development of Visual Dashboard for River Monitoring System

引用

8th ieee international conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2022

作者： Ahmad, Yasser Asrul Gunawan, Teddy Surya Munir, Muhd Hisyamuddin Mohd Rasidi Al Yusoff, Nelidya Md. Kartiwi, Mira Mansor, Hasmah International Islamic University Malaysia Electrical and Computer Engineering Dept Kuala Lumpur53100 Malaysia Razak Faculty of Tech. and Informatics Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia Information Systems Department International Islamic University Malaysia Kuala Lumpur53100 Malaysia

ISBN: (数字)9781665488006

ISBN: (纸本)9781665488006

Monitoring a tributary's water depth and velocity can provide a wealth of information for ecological systems. Typically, tributaries are located deep within the jungle, and manual measurement is the norm. the research aims to develop a real-time remote monitoring system for measuring water depth and velocity. the system uses ultrasonic and water flow sensors to measure velocity and river depth. the data will be transmitted to the back-end software, including Arduino IDE and Node-RED, for data collection. the data is then stored in the cloud database InfluxDB for future use. the data can be set to be automatically deleted every 1 hour, 1 day, 1 month, or at other time intervals. the Grafana platform can produce an interactive Graphical User Interface (GUI), and the administrator can modify the visual dashboard using either their program code or existing features. It can then be made available to the general public as an observer for the online visual dashboard via the Uniform Resource Locator (URL). © 2022 ieee.

关键词： Remote control

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A Proposed Architecture of Mobile Service Provider Based Interactive systems

A Proposed Architecture of Mobile Service Provider Based Int...

引用

international conference for Convergence of Technology (I2CT)

作者： Chandni Magoo Manjeet Singh Department of Computer Science and Engineering J.C. Bose University of Science and Technology Manav Rachna University Faridabad Department of Computer Science and Technology Manav Rachna University Faridabad

Chatbots are basically designed to imitate any human interaction to automate interaction and support. Numerous benefits of chatbots has led to its increased usage by different organizations to provide essential assistance to its various customers. the current interactive systems are mainly developed from two main concepts namely NLP and Machine Learning. Despite of this, there are certain challenges and limitations of current chatbots. In this paper we will review some of the current chatbots with their limitations and highlight some of the errors identified through survey analysis of different chatbots of some companies like Airtel, Vodafone and Jio etc. A survey is done to analyze the chatbots on various metrics.

关键词： Surveys Measurement Interactive systems Atmospheric modeling Oral communication Machine learning Companies

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Deep Learning-Based Automatic Modulation Classification with Prediction Combination in OFDM systems

Deep Learning-Based Automatic Modulation Classification with...

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ieee international conference on Network Infrastructure and Digital Content (IC-NIDC)

作者： Geonho Song Onyekwelu Michael Chisom Yooncheol Choi Mingyu Jang Dongweon Yoon Department of Electronic Engineering Hanyang University Seoul Korea

Automatic modulation classification (AMC) is one of the important tasks in cognitive radios and spectrum surveillance. this paper proposes a deep learning (DL)-based AMC with prediction combination method for orthogonal frequency division multiplexing (OFDM) systems. We first predict the subcarrier modulation scheme of the transmitted OFDM signal with different DL models and then combine those predictions using the proposed prediction combination method to make the final decision. through computer simulations, we show that the classification performance can be improved by the proposed prediction combination method in terms of classification accuracy.

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Proof of Greatest Number Program and Find 8

Proof of Greatest Number Program and Find

引用

8th international conference on Dependable systems and their Applications, DSA 2021

作者： Shan, Zhihui Han, Qiang Han, Meng North Minzu University School of Computer Science and Engineering Ningxia China

ISBN: (纸本)9781665443913

It is very difficult for software testing to enumerate all possible situations. this method can't guarantee the correctness of the program, so strict mathematical formulas are needed to prove the correctness of the program. this article takes the Greatest number and Find programs as examples to prove their correctness. the methods of snapshot and Logical notation are used to prove the two algorithms to prevent the entry of logic errors. the proof of termination of the algorithm is regarded as an independent exercise. Finally, the two proof methods are summarized. © 2021 ieee.

关键词： software testing

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Preventing Frequency Instability Using Large-Scale Photovoltaic Resources

Preventing Frequency Instability Using Large-Scale Photovolt...

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Technology and Energy Management (ICTEM), international conference on

作者： Siavash Yari Hamid Khoshkhoo Kumars Rouzbehi S. M. Ale Emran Faculty of Electrical Engineering Sahand University of Technology Sahand Iran Department of System Engineering and Automatic Control University of Seville Seville Spain Faculty of Engineering University of Quebec at Chicoutimi (UQAC)

Various control methods have been presented to prevent the occurrence of instability in power systems, among which, it seems that methods based on the special protection system (SPS) are more effective and efficient than other ones. In this article, a SPS using the capabilities of large-scale photovoltaic power plants (LSPVPPs) is presented to prevent frequency increase and instability in power systems. According to the presented algorithm, when frequency increases, the proposed SPS uses the ability of photovoltaic power plants to quickly change their generation powers based on the operating point and frequency changes to prevent frequency instability. To confirm the proposal, LSPVPPs along with their controllers are modeled in the DSL environment of DIgSILENT PowerFactory software. the proposed SPS is implemented and tested on the ieee 39-bus test system and the results of dynamic simulations show that this SPS prevents frequency instability in different conditions by taking timely measures.

关键词： Photovoltaic systems Time-frequency analysis Power system dynamics software algorithms Power system stability Stability analysis software

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A Simple End-to-End computer-Aided Detection Pipeline for Trained Deep Learning Models 8th

A Simple End-to-End Computer-Aided Detection Pipeline for Tr...

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8th international conference on engineering of computer-Based systems, ECBS 2023

作者： Kahraman, Ali Teymur Fröding, Tomas Toumpanakis, Dimitrios Fridenfalk, Mikael Gustafsson, Christian Jamtheim Sjöblom, Tobias Department of Immunology Genetics and Pathology Uppsala University Uppsala Sweden Department of Radiology Nyköping Hospital Nyköping Sweden Neuroradiology Karolinska University Hospital Stockholm Sweden Department of Surgical Sciences Uppsala University Uppsala Sweden Department of Game Design Uppsala University Gotland Visby Sweden Department of Hematology Oncology and Radiation Physics Skåne University Hospital Lund Sweden Department of Translational Medicine Medical Radiation Physics Lund University Malmö Sweden

ISBN: (纸本)9783031492518

Recently, there has been a significant rise in research and development focused on deep learning (DL) models within healthcare. this trend arises from the availability of extensive medical imaging data and notable advances in graphics processing unit (GPU) computational capabilities. Trained DL models show promise in supporting clinicians with tasks like image segmentation and classification. However, advancement of these models into clinical validation remains limited due to two key factors. Firstly, DL models are trained on off-premises environments by DL experts using Unix-like operating systems (OS). these systems rely on multiple libraries and third-party components, demanding complex installations. Secondly, the absence of a user-friendly graphical interface for model outputs complicates validation by clinicians. Here, we introduce a conceptual computer-Aided Detection (CAD) pipeline designed to address these two issues and enable non-AI experts, such as clinicians, to use trained DL models offline in Windows OS. the pipeline divides tasks between DL experts and clinicians, where experts handle model development, training, inference mechanisms, Grayscale Softcopy Presentation State (GSPS) objects creation, and containerization for deployment. the clinicians execute a simple script to install necessary software and dependencies. Hence, they can use a universal image viewer to analyze results generated by the models. this paper illustrates the pipeline's effectiveness through a case study on pulmonary embolism detection, showcasing successful deployment on a local workstation by an in-house radiologist. By simplifying model deployment and making it accessible to non-AI experts, this CAD pipeline bridges the gap between technical development and practical application, promising broader healthcare applications. © 2024, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Pipelines

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Message from the General Chair CHASE 2023

Proceedings - 2023 IEEE/ACM International Conference on Conn...

引用

Proceedings - 2023 ieee/ACM international conference on Connected Health: Applications, systems and engineering Technologies, CHASE 2023 2023年 XI-XII页

作者： Mao, Shiwen Auburn University United States

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engineering Large Wearable Sensor Data towards Digital Measures

Engineering Large Wearable Sensor Data towards Digital Measu...

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ieee international conference on Big Data Analysis (ICBDA)

作者： Hui Zhang Guangchen Ruan Regan Giesting Leah Miller Neel Patel Ju Ji Yi Lin Yang Jian Yang Eli Lilly & Company Indianapolis Digital Health Office Indiana USA Eli Lilly & Company Indianapolis Advanced Analytics and Data Science Indiana USA Carmel High School Carmel Indiana USA

Developing digital biomarkers requires handling unprecedented quantities of digital data generated from digital health technologies that utilize a combination of computing platforms, connectivity, software, and sensors. these collected data need to be transformed and transported into a meaningful and useful format before further being derived into health indicators for understanding disease state and life quality. the unique challenges for this class of data engineering tasks are due to the complexity and volume of the digital data we are handling, the data quality and fidelity required to enable subsequent analysis, and the repeated cycles of trial and error to achieve the desired results. this paper presents a family of systems, pipelines, and methods we have designed and built to facilitate these tasks in a typical digital data engineering lifecycle in the context of digital biomarker development.

关键词： Data integrity Pipelines Data visualization Biomarkers Data engineering software Electronic healthcare

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Driving Behavior Classification Using Smartphone Sensor Data

Driving Behavior Classification Using Smartphone Sensor Data

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international conference on computer Science and engineering (UBMK)

作者： Deniz Dikbıyık Fatih Alagöz Dept. of Software Engineering Boğaziçi University İstanbul Türkiye Dept. of Computer Engineering Boğaziçi University İstanbul Türkiye

Given the substantial number of accidents because of human error, the development of automatic driver behavior monitoring systems has become a pressing need. By providing real-time monitoring and analysis of driving behavior, these systems have the potential to decrease the incidence of accidents and improve overall road safety. this study presents a novel analysis framework for classifying driving behavior based on data gathered from passengers' smartphones. the data were collected using our mobile application installed on the smartphones and processed using machine learning algorithms. the study utilized several machine learning classification t echniques, w ith a focus on developing a Long Short Term Memory (LSTM) algorithm for improved accuracy. A Federated Learning algorithm was also developed to collect the data not into one area and train a global model to apply for labeling the driving behavior. the results show the efficacy of the proposed approach in accurately classifying driving behavior based on data obtained from smartphones.

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