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

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Probabilistic data Association Performance During Launch Vehicle Tracking

Probabilistic Data Association Performance During Launch Veh...

引用

Range Technology (ICORT), international conference on

作者： Challa Ravindra S Rajkumar A Vaidhyanathan SDSC-SHAR ISRO Sriharikota India

Probabilistic data Association (PDA) is Bayesian approach of deriving likelihood function for all measurements reported by radar. Tracking of Launch Vehicle with skin mode radar involves processing of multiple returns from rocket, separated stages and rocket plumes, which makes association of track measurements more uncertain. Using PDA we bring down the uncertainty of measurements by computing posterior probability for all measurements reported by radar during real time. Measurement with highest posterior probability is selected and given as input to processing filter. In this paper we analyze Probabilistic data Association (PDA) performance during tracking of Launch Vehicle by Multi Object Tracking Radar.

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data Analysis and Machine Learning Observation on Production Losses in the Food processing Industry

Data Analysis and Machine Learning Observation on Production...

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Contemporary computing and Communications (InC4), IEEE international conference on

作者： Kukatlapalli Pradeep Kumar Hari Murthy Vinay Jha Pillai Boppuru Rudra Prathap Michael Moses Yogeshraj Urs Department of Computer Science and Engineering CHRIST Deemed to be University Bengaluru Karnataka INDIA Department of Electronics and Communication Engineering CHRIST Deemed to be University Bengaluru Karnataka INDIA Department of Civil Engineering CHRIST Deemed to be University Bengaluru Karnataka INDIA

Food wastage and capturing lineage from production to consumption is a bigger concern. Yielding, storage and transportation areas have evolved to a great extent associated to manufacturing and automation which lead to technical advancements in food processing industry. In such situation, losses are generally observed in the crop production which are sometimes minimal and ignored. However, in some cases these losses are huge and are becoming a threat to the both producers and consumers. Here we considered data related to dairy products and analysed the production losses especially while processing them in the treating unit. Literature on parameters and associated data analysis in the form of graphical representation are provided in the appropriate sections of the paper. Linear regression and correlation were envisaged in view of incorporating machine learning techniques understanding production losses. Karl Pearson’s correlation provides an observation related to association of parameters which are desired to be less coupled in terms of employing proposed newer methodology.

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Research on Cloud data Storage Security Privacy Protection System under Digital Campus

Research on Cloud Data Storage Security Privacy Protection S...

引用

Image processing and Computer Applications (ICIPCA), IEEE international conference on

作者： Lingling Li Rongsheng Cai Tieling Normal College Tieling Liaoning China Faculty of Data Science City University of Macau Macau China Quanzhou College of Technology Quanzhou Fujian China

This paper proposes a digital campus cloud data storage security and privacy protection strategy under the Internet of Things environment. Campus users first apply for the attribute key from the trust center and then outsource the encrypted private data to the cloud server. The authorized user generates keyword traps through attribute keys. Only when the attributes of the authorized user meet the specified access control tree, the authorized user is allowed to search the cloud encrypted data through this trap door. A homomorphic encryption algorithm based on ECC is proposed based on the advantages of high security performance and low computational complexity. The algorithm is applied to cloud storage ciphertext processing and cloud computing data aggregation privacy protection. The results show that the scheme cannot only ensure the security of data storage but also protect the identity privacy of campus users.

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Leveraging Smart Meter data for Adaptive Consumer Profiling 18th

Leveraging Smart Meter Data for Adaptive Consumer Profiling

引用

Proceedings of the 18th international conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2023

作者： González, Ana Bernardos, Ana M. Gallego, Carlos J. Casar, José R. Information Processing and Telecommunications Center Universidad Politécnica de Madrid ETSI Telecomunicación Madrid28040 Spain

ISBN: (纸本)9783031425288

The growing availability of smart meter data from households is contributing to the digitalization of the energy sector and driving its transformation into new business concepts, such as flexibility markets. This data allows for more precise consumer profiling than ever before, which can be beneficial for demand response modeling, dynamic tariff models… While profiling customers based on time-series consumption data has been extensively studied in the literature, this article offers a different approach by examining the feasibility of profiling new customers using their early data, with varying amounts of smart meter data available (from one month to one year) and considering different approaches of frequency of data (daily, weekly, bi-weekly or monthly). By using an existing dataset (Low Carbon London project, spearheaded by UK Power Networks) for modeling validation and test purposes, the data pipeline in our study employs Dynamic Time Warping K-Means clustering. We compare the similarity of clusters obtained with different data lengths against ground-truth clusters built on all the data by using Rand Index. Results indicate that, on average, one month of data is enough for accurate profiling for a small number of consumer types, although for a larger number it is recommended to use a slot of 6 months. The approach enables effective profiling even on limited data for new customers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Smart meters

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Review of New data Center Network Structure

Review of New Data Center Network Structure

引用

international conference on Advanced Communication Technology (ICACT)

作者： Weiqiang Xue Zhijie Han Xiaoyu Du School of Computer and Information Engineering Henan University Henan China School of Software Henan University Henan China

Nowadays, people ’s lives are increasingly inseparable from big data. The development of big data has a profound impact on human society. At the same time, the generation of massive data has promoted the transformation of data processing methods. In this development trend, cloud computing came into being. Cloud computing is to provide online cloud services to network users by building a large shared platform, so as to achieve on demand allocation of resources. data centers are the core infrastructure of cloud computing, Therefore, the performance of the data center network determines the quality of service provided by cloud computing. However, traditional data center networks have long been unable to meet the needs of today ’s society for large data centers. This paper summarizes the new data center network structure pro-posed in recent years from the aspects of switch-centric, server-centric, wireless data center, wired and wireless combination, introduces its performance, fault tolerant routing efficiency and other advantages, and looks forward to the future development of data center network structure.

关键词： Wireless communication Wiring data centers Cloud computing Horn antennas Transmitting antennas Switches

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iTrace-Toolkit: A Pipeline for Analyzing Eye-Tracking data of Software Engineering Studies

iTrace-Toolkit: A Pipeline for Analyzing Eye-Tracking Data o...

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international conference on Software Engineering - Companion, ICSE, Companion

作者： Joshua Behler Praxis Weston Drew T. Guarnera Bonita Sharif Jonathan I. Maletic Department of Computer Science Kent State University Kent Ohio USA Department of Mathematical and Computer Sciences College of Wooster Wooster Ohio USA School of Computing University of Nebraska-Lincoln Lincoln Nebraska USA

iTrace is community eye-tracking infrastructure that enables conducting eye-tracking studies within an Integrated Development Environment (IDE). It consists of a set of tools for gathering eye-tracking data on large real software projects within an IDE during studies on source code. Once the raw eye-tracking data is collected, processing is necessary before it can be used for analysis. Rather than provide the raw data for researchers to analyze and write their own customize scripts, we introduce iTrace-Toolkit - a suite of tools that assists with combining different data files generated from iTrace and its IDE plugins (namely Visual Studio, Atom, and Eclipse). iTrace-Toolkit also provides the crucial mapping of the valid raw eye-tracking data to source code tokens and finally generates fixations (an important metric in eye-tracking for comprehension) using three commonly used algorithms based on distance and velocity of eye movements. iTrace-Toolkit keeps track of all participant data and tasks during a given study and produces a complete lightweight database of the raw, mapped, and fixation data that is standardized and ready to be used by statistical tools. A simple GUI interface is provided for quick access to filter the data after an eye-tracking study. iTrace-Toolkit also allows for the export of the data or subset of the data to text formats for further statistical processing. YouTube Video: https://***/watchv9j20sOANh8w

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A Modified EXP3 in Adversarial Bandits with Multi-user Delayed Feedback 29th

A Modified EXP3 in Adversarial Bandits with Multi-user Del...

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29th international computing and Combinatorics conference, COCOON 2023

作者： Li, Yandi Guo, Jianxiong Advanced Institute of Natural Sciences Beijing Normal University Zhuhai519087 China Hong Kong Baptist University Hong Kong Guangdong Key Lab of AI and Multi-Modal Data Processing Department of Computer Science BNU-HKBU United International College Zhuhai519087 China

ISBN: (纸本)9783031491924

For the adversarial multi-armed bandit problem with delayed feedback, we consider that the delayed feedback results are from multiple users and are unrestricted on internal distribution. As the player picks an arm, feedback from multiple users may not be received instantly yet after an arbitrary delay of time which is unknown to the player in advance. For different users in a round, the delays in feedback have no latent correlation. Thus, we formulate an adversarial multi-armed bandit problem with multi-user delayed feedback and design a modified EXP3 algorithm named MUD-EXP3, which makes a decision at each round by considering the importance-weighted estimator of the received feedback from different users. On the premise of known terminal round index T, the number of users M, the number of arms N, and upper bound of delay dmax, we prove a regret of O(TM2lnN(Ne+4dmax)). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： E-learning

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Query performance optimization method for blockchain carbon footprint data

Query performance optimization method for blockchain carbon ...

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Electrical Engineering, Big data and algorithms (EEBDA), IEEE international conference on

作者： Tiantian Xu Tianmei Chen Ying Zhang Xiaocao Zuo Menghao Liu Linghe Zhang Yingwen Feng Yu Wang Chenxi Yu Yuezhu Zhao State Grid Zhejiang Producement Company Zhejiang China Hangzhou Industry Chain Digital Technology Co. Ltd Zhejiang China Zhejiang University Zhejiang China

Block chain can be used as a new kind of distributed database system, can be applied in areas such as carbon footprint. However, its practical application generally faces problems such as simple query function and low query performance due to the limitation of data storage mode. Therefore, for the application scenario of blockchain in carbon footprint, query performance optimization is a research topic that cannot be ignored. In this paper, we first introduce the current popular blockchain query schemes. Then we adopt a query optimization method based on MySQL, an external database, to support more complex and efficient query requirements. Finally, we verify the effectiveness and feasibility of the proposed scheme through experiments.

关键词： Electrical engineering Query processing Memory Big data Blockchains Carbon footprint Optimization

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A 5G-Based Big data Security Access processing Method and Device

A 5G-Based Big Data Security Access Processing Method and De...

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Electrical Engineering, Big data and algorithms (EEBDA), IEEE international conference on

作者： Abduani Abduklimu Peng Yan Gang Wang Hu Liu Junpeng Xie State Grid Kashi Electric Power Supply Company Kashi China

With the opportunity of the digital transformation of the vertical industry represented by the power grid in the 5G era, in order to meet the communication needs of all kinds of new services in the power grid application scene, in order to adapt to the comprehensive perception and intelligent interconnection development of the future power grid under the new situation, the intelligence of the power Internet of things supporting Yunbian collaboration needs to be improved urgently. Under the 5G architecture, how to effectively protect the business data of communication terminals has become the focus of relevant developers in the security industry. In order to solve the problem of illegal intrusion of equipment and secure data transmission, a big data security access processing device based on 5G is designed in this paper. In this device, the access terminal authentication module authenticates the user identity information through audio and video, two-dimensional code and other technologies; the data trust verification module confirms the data security through whitelist, data scanning and other methods; the data software and hardware encryption module encrypts the data through encryption chip and IPSEC protocol and other technologies. Combining these technologies, the secure transmission of network data is realized. In addition, by testing the throughput of the encryption algorithm, it is found that the smaller the key value of the encryption algorithm, the greater the throughput.

关键词： Industries 5G mobile communication Software algorithms Authentication Big data Throughput Power grids

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Advancements in AI-Assisted Plant Disease Diagnosis

Advancements in AI-Assisted Plant Disease Diagnosis

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international conference on computing, Communication, and Intelligent Systems (ICCCIS)

作者： Anmol Chhabra Tarun Saroch Ruchika Gupta Aditya Shukla Raghav Computer Science & Engineering Department Centre of Excellence - Data Science and Cognitive Computing Chandigarh University Mohali India

Plant disease detection is a crucial task in agriculture to ensure healthy crop production. It is vital to identify plant diseases early in order to avert economic and environmental damages. A Machine learning-based approach including Deep Learning techniques for identifying plant disease was developed using Grape leaf images in this work. Inception v3, Squeezenet, VGG-16, and VGG-19 are some embedders that are used in the suggested method to convert raw image data into a fixed-length vector representation, also known as a “embedding” or “feature vector.” Our research concludes that CNN stands out with exceptional accuracy above 99.70% compared to classifiers like Naive Bayes, Logistic Regression, and SVM. Additionally, Inception V3 proved to be an efficient feature extractor, enhancing feature representation and reducing processing time.

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