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检索条件"任意字段=2023 International Conference on Algorithms, Computing and Data Processing, ACDP 2023"

共 6956 条记录，以下是701-710 订阅

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UbiComp/ISWC 2023 Adjunct - Adjunct Proceedings of the 2023 ACM international Joint conference on Pervasive and Ubiquitous computing and the 2023 ACM international Symposium on Wearable computing

UbiComp/ISWC 2023 Adjunct - Adjunct Proceedings of the 2023 ...

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2023 ACM international Joint conference on Pervasive and Ubiquitous computing and the 2023 ACM international Symposium on Wearable computing, UbiComp/ISWC 2023

ISBN: (纸本)9798400702006

The proceedings contain 161 papers. The topics discussed include: towards detecting tonic information processing activities with physiological data;captivating the senses: crafting a multisensory virtual experience for enhanced realism;exploring the impact of virtual reality-based simulated symptoms towards schizophrenia on public empathy;preliminary study on effect of secretly increasing or decreasing predicted number of steps to promote walking;binary social game: a principle for enhancing desired behaviors through asynchronous social interactions;an experimental video conference platform to bridge the gap between digital and in-person communication;departure time prediction using smartphone data for delayed-full charging BMS algorithm;Lightron: a wearable sensor system that provides light feedback to improve punching accuracy for boxing novices;and Sandbox AI: we don’t trust each other but want to create new value efficiently through collaboration using sensitive data.

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Application of Improved PilotNet Intelligent Traffic Algorithm Based on Baidu PaddlePaddle 6

Application of Improved PilotNet Intelligent Traffic Algorit...

引用

6th international conference on Information Communication and Signal processing, ICICSP 2023

作者： He, Huifang Zhuang, Tingting School of Information Engineering Guangdong Engineering Polytechnic Guangzhou China School of Data Science and Engineering Xingzhi College South China Normal University Shanwei China

ISBN: (纸本)9798350339994

In view of the complexity of current traffic scenes, the rapid development of intelligent transportation applications and the improvement of domestic platforms, this paper combines the current mainstream deep learning algorithms to recognize the road line with the PilotNet model improved by BatchNorm and Dropout technologies under the Baidu PaddlePaddle framework, and to detect the traffic signs with the YOLOv3 Tiny model. Due to the limited hardware system resources and the real-time nature of automatic driving, finally, the two types of models are deployed to the Edge Board computing box. In the application of intelligent transportation, single-thread technology cannot respond to the real-time nature of automatic driving, and thread blocking has a great impact. After comparison, dual-thread technology is adopted. data processing is carried out by capturing the moving image of the car and the control value, and the experiment is completed. In the experiments, the smart car can recognize the traffic signs at a speed of around 0.01s per frame and finish model loading and making decision after the recognition of traffic scenes in 34.86s, which shows that the trained neural network models all have lightweight characteristics and can meet the system application with limited resources. © 2023 IEEE.

关键词： Baidu PaddlePaddle Edge board intelligent transportation PiiotNet YOLOv3 Tiny

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data Protection Between IoT Devices and Cloud computing: Using PRINCE Lightweight Algorithm 6

Data Protection Between IoT Devices and Cloud Computing: Usi...

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6th Iraqi international conference on Engineering Technology and its Applications, IICETA 2023

作者： Hilal, Anaam Ghanim Manaa, Mehdi Ebady University of Babylon Department of Information Networks Babylon Iraq

ISBN: (纸本)9798350303339

The Internet of Things (loT) is a fast-growing field that involves connecting a wide variety of devices and sensors to the Internet to collect and share data. The vast amount of data generated by these devices requires secure storage and processing, which is where cloud computing comes in. Cloud computing provides scalable, on-demand storage and processing resources that can handle the massive amount of data that loT devices produce. By integrating loT and cloud computing, organizations can effectively store, manage, and analyze the data generated by loT devices, leading to more efficient and effective operations. The main disadvantage is security, which is the most important issue nowadays The primary goal of this paper is to make data more secure and reduce latency when data is transported from loT devices to cloud computing, must using efficient lightweight cryptography algorithm suitable in loT environment. In this paper, we will focus on the PRINCE lightweight encryption algorithm. evaluating the proposed system using main parameters so that one can understand the security and performance aspects of the suggested system such as Execution time, and Entropy. The result showed in the last reading as the following execution time is 0.202994713Sec and Entropy is 7.97083942. © 2023 IEEE.

关键词： Internet of things

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Comparative Analysis of Cryptographic algorithms for data Security in Cloud computing: A Performance Evaluation 3

Comparative Analysis of Cryptographic Algorithms for Data Se...

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3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Rajan, Ishu Kumar, Lave Srivastava, Vanshika Singhal, Manoj Singh, Rajani Gl Bajaj Institute of Technology and Management Department of Information Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350342338

In the modern era, people are sharing their data online. securing this data in today's world is a crucial task i.e., anyone can get the data without the concern of the respective authority. Users store their sensitive/non-sensitive data on the cloud only by trusting the Terms & Conditions and the user agreement offered by the service provider. Cloud service providers are known to reject the responsibility for any data breaches that may happen. This paper proposes a method to strengthen the confidentiality of data in cloud. We have done comparative study between several cryptographic algorithms on the basis of their encryption and decryption time, performing ondifferent data formats like text, image, and videos. © 2023 IEEE.

关键词： AES Blowfish Cryptography data Confidentiality Fully Homomorphic Encryption

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Exploratory data Analysis and Customer Churn Prediction for the Telecommunication Industry 3

Exploratory Data Analysis and Customer Churn Prediction for ...

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3rd international conference on Advances in computing, Communication, Embedded and Secure Systems, ACCESS 2023

作者： Singh, Kiran Deep Deep Singh, Prabh Bansal, Ankit Kaur, Gaganpreet Khullar, Vikas Tripathi, Vikas Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350346169

The telecommunications business is one of the key industries with a higher risk of revenue loss owing to client turnover and environmental impact. Thus, efficient and effective churn management includes targeted marketing campaigns, special promotions, or other incentives to keep the customer engaged in technological progress. There are a lot of machine learning algorithms available now, but very few of them can effectively take into account the asymmetrical structure of the telecommunications dataset. The efficiency of machine learning algorithms may also vary depending on how closely they approximate the real-world telecommunications data rather than the publicly available dataset. As a result, the researchers used various predictive models, including XGBoost, for this dataset. The accuracy achieved on the native dataset is 82.80%. Results show the effectiveness of the predictive model with great technological capabilities. © 2023 IEEE.

关键词： Machine learning

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Technical Analysis of Stock Market using data Science and its tools 7

Technical Analysis of Stock Market using Data Science and it...

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2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Pagar, Shrawani Jaiswal, Aditya Auti, Atharva Purohit, Vansh Mishra, Vivek Shah and Anchor Kutchhi Engineering College Department of Cybersecurity Mumbai India Shah and Anchor Kutchhi Engineering College Department of Computer Science Mumbai India

ISBN: (纸本)9798350304268

This paper presents a technical analysis approach for the stock market using data science and its associated tools. The objective is to develop a systematic framework that leverages data science techniques to analyze stock market data and make informed investment decisions. The proposed methodology involves data collection, preprocessing, feature engineering, and the application of various machine learning algorithms for predicting stock prices and identifying potential trading opportunities. The study demonstrates the effectiveness of data science in enhancing traditional technical analysis methods and provides insights into the potential benefits of integrating data-driven approaches into stock market analysis. Experimental results on historical stock data validate the proposed approach's accuracy and highlight its potential for improving investment strategies. © 2023 IEEE.

关键词： dataframe demand and supply zone explosive candles jupyter notebook python sql yfinance

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Otter: Simplifying Embedded Sensor data Collection and Analysis using Large Language Models 23

Otter: Simplifying Embedded Sensor Data Collection and Analy...

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29th Annual international conference on Mobile computing and Networking, MobiCom 2023

作者： Waskito, Steven Leow, Kai Jie Medaranga, Pramuka Gupta, Tejas Chakrabarty, Shantanu Gulati, Manoj Varshney, Ambuj National University of Singapore Singapore60017161 Singapore School of Computing National University of Singapore Singapore60017161 Singapore Iit Kanpur Kanpur60021988 India Ncs Group Singapore Singapore

ISBN: (纸本)9781450399906

Wireless embedded systems assist us in collecting data from the physical world, through sensor data analysis, such systems allow us to understand our environment. However, deploying wireless embedded systems and analyzing the collected data remains significantly challenging. This is due to the steep learning curve required to implement custom machine-learning models and other algorithms for data analysis. Furthermore, it is also challenging to program individual embedded devices. The diversity of the available platforms and their capabilities further compounds this problem. In response, we introduce an end-to-end system, called the Otter. It facilitates simple sensor data collection using commodity-embedded platforms. Moreover, it employs a large language model to design a natural language interface for the analysis and extraction of useful information from the sensor data. We present our preliminary work on prototyping this system, applying it to a specific use case of hand gesture detection. Otter represents one of the first systems to leverage the enhanced capabilities of large language models for simplifying wireless embedded system deployments. © 2023 Owner/Author(s).

关键词： data acquisition

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Research on the design of a target control platform for engineering projects under big data 2

Research on the design of a target control platform for engi...

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2nd IEEE international conference on Electrical Engineering, Big data and algorithms, EEBDA 2023

作者： Song, Jieru Tianjin University of Technology Tianjin China

ISBN: (纸本)9781665462532

Big data has great advantages in scientific management, and this technical means also provides new space for the improvement of engineering project management. From the perspective of system analysis and design, the core architecture and big data application framework of the engineering project target control platform under the environment of big data are studied. Through identifying project risk factors and analyzing and processing project data, the target control platform of big data in three aspects of project progress, quality and cost is constructed. The engineering project target control platform based on big data can effectively warn the problems such as delayed progress, hidden quality and excessive cost, and provide project managers with decision-making ideas, so as to promote the reasonable realization of the basic project goals. © 2023 IEEE.

关键词： Big data

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Construction of Intelligent Health Management Cloud Platform Based on Big data

Construction of Intelligent Health Management Cloud Platform...

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2023 international conference on Evolutionary algorithms and Soft computing Techniques, EASCT 2023

作者： Ma, Rui Zhou, Fengjiao Chengdu University of Traditional Chinese Medicine Health and Rehabilitation College Chengdu China Affiliated Hospital of Chengdu University of Traditional Chinese Medicine Acupuncture School Chengdu China

ISBN: (纸本)9798350313413

With the advent of the era of big data, more and more people get the information they need and are interested in through various channels in daily life, and the traditional medical model can no longer meet the needs of human health management. In order to solve this problem, this paper builds an intelligent health management cloud platform based on big data, and uses big data and cloud computing technology to provide users with a new health management platform, which can provide health records, health checks, health monitoring and other functional services. The platform carries out health risk assessment from three aspects: information collection, risk calculation and assessment report, and carries out risk assessment on human health. The average abnormal detection rate of volunteers after intervention is about 23.2%. Based on the application of the big data intelligent health management cloud platform, the detection rate of abnormal diseases among volunteers decreased by about 5%. It can be seen that the application of the intelligent health management cloud platform based on big data has significantly reduced the detection rate of abnormal diseases in volunteers. The construction of such a platform can help individuals maintain their health, provide users with a more personalized and humanized service experience, and meet the diverse needs of people at different levels. This advance in smart medicine helps to improve healthcare delivery and outcomes across the board. © 2023 IEEE.

关键词： big data intelligence cloud platform disease abnormalities health management health risk assessment

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Analyzing the Effect of Edge computing on Real-time data processing and Latency Reduction 10

Analyzing the Effect of Edge Computing on Real-time Data Pro...

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10th IEEE Uttar Pradesh Section international conference on Electrical, Electronics and Computer Engineering, UPCON 2023

作者： Deepthi, K. Sahu, Dillip Narayan Rana, Kuldeep Singh Asha, V. Sumalatha, Ippa Nijhawan, Ginni School of Cs & Ai Sr University Telangana Warangal India Gangadhar Meher University Department of Mca Odisha India Invertis University Computer Applications Uttar Pradesh Bareilly India New Horizon College of Engineering Department of Computer Applications Bangalore India Institute of Aeronautical Engineering Hyderabad India Lovely Professional University Phagwara India

ISBN: (纸本)9798350382471

Edge computing platforms offer multiple advantages to information technology, like lower latency, increased connectivity, longer battery duration, and so on. Despite their many advantages, edge computing platforms have some flaws that could severely impair the functioning of specific programs. Indeed, present edge computing platforms do not guarantee latency reduction for real-time data processing and suffer from data overload concerns. To address the above difficulties, this research offers Household Edge Computation (HEC), a novel 3-level edge computation design that delivers real-time data storing and processing near consumers. This 3-level design includes a Residential, a Central, Edge Server, all of which are common in typical edge computation designs. The Residence Server is positioned close to the consumers, allowing for latency reduction for real-time data processing that can be handled by the servers;this also helps minimize the quantity of data that may be handled in the Edge Server and the centralized Cloud. This research uses the Edge-Cloud-Sim simulated system to show the viability of the proposed design. The research findings suggest that this solution may assist in attaining extremely low latency and eliminate overloading difficulties. © 2023 IEEE.

关键词： and Real-time data processing Edge computing Information technology Latency reduction

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