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检索条件"任意字段=8th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023"

共 155 条记录，以下是61-70 订阅

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Design of 5G private network quality monitoring System based on edge computing 8

Design of 5G private network quality monitoring System based...

引用

8th international conference on Intelligent computing and Signal Processing, ICSP 2023

作者： Wang, Zheng Wang, Xiaoni Beijing Information Science and Technology University School of Applied Science Beijing China

ISBN: (纸本)9798350302455

In order to ensure the continuous, secure, and reliable network connection and coverage of the private network environment, the quality assurance requirements of different network states in different 5G private network scenarios are addressed. this paper proposes a 5G private network quality monitoring system based on edge computing. By connecting the 5G acquisition module to the private network environment, the system uses edge computing technology to carry out preliminary cleaning, integration, encryption and other processing of the collected data, unload the computing tasks originally needed to be carried out in the cloud to the terminal, and realize data transmission between the terminal and the big data cloud platform based on MQTT protocol. Finally, the system provides real-time monitoring of the private network environment through visual display on the front-end interface. the experimental results show that the system remains stable after pressure testing and has good reliability, which can provide real-time security protection and traceability basis for the private network environment. © 2023 ieee.

关键词： big data

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Research on the Construction of Secondary Psychological Counseling Station in Colleges and Universities under the "Internet+" Environment by data Analysis 8

Research on the Construction of Secondary Psychological Coun...

引用

8th ieee international conference on Smart cloud, Smartcloud 2023

作者： Xu, Haolun College of Computer Science and Technology Wuhan University Of Science And Technology WuHan China

ISBN: (纸本)9798350313505

With the rapid development of Internet technology, psychological education in colleges and universities is facing unprecedented challenges. the characteristics of the "Internet +" era have affected the mental health of college students to a certain extent. At the same time, teachers’ understanding and application of "Internet +" is far from enough. therefore, under this new situation, how to use the power of cloud computing and data analysis to optimize the construction of secondary psychological counseling stations in colleges and universities and play their unique role in mental health education has become a new topic. Overall, the "Internet +" era has brought challenges as well as opportunities. the secondary psychological counseling stations in colleges and universities should actively apply new technologies such as cloud computing and data analysis to optimize services, improve work efficiency, and better serve college students’ mental health. Based on the mental health data of college students obtained from big data, this paper adopts mean clustering and C4.5 algorithm to find out the factors leading to the mental health problems of college students through data analysis, and propose feasible solutions to the problems. ©2023 ieee.

关键词： cloud computing

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Improving Network Intrusion Detection Using Supervised Learning for Feature Selection

Improving Network Intrusion Detection Using Supervised Learn...

引用

big data, cloud computing, data science & Engineering (bcd)

作者： Hamed Sanusi Zheni Utic Jongyeop Kim Department of Mathematical Science Georgia Southern University Statesboro GA U.S.A Department of Information Technology Georgia Southern University Statesboro GA U.S.A

Detecting network intrusions is a crucial area of study in computer security research, with the goal of identifying malicious activities in computer networks. Prior research has concentrated on utilizing machine learning methods to spot network intrusions, typically by training models on distinct attack categories. In our study, we suggest a revised method that merges three attack categories into a unified category through supervised learning. this approach seeks to streamline the classification procedure and enhance the precision of network intrusion detection.

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A Consideration of Trust Evaluation for Individual System Developers

A Consideration of Trust Evaluation for Individual System De...

引用

big data, cloud computing, data science & Engineering (bcd)

作者： Takuya Iwami Motoi Iwashita Graduate School of Social Systems Science Chiba Institute of Technology Chiba Japan Dept. of Management Information Science Chiba Institute of Technology Chiba Japan

In recent years, with the proliferation of cloud computing technology, companies have increasingly adopted cloud services. In particular, the need for DX business in the software industry has led to an increase in job vacancies. the use of freelancers is a possible response to the shortage of jobs. An important consideration when a company chooses a freelancer is whether he or she can be trusted to get the job done on time. Such information cannot be derived from the submitted profile. this paper proposes a method to objectively assess the trustworthiness of freelancers. Moreover, a mechanism that prevents falsification of the evaluation is also considered. As a result, in the evaluation of the trust of freelancers, it was qualitatively shown that it is desirable to have a mechanism that prevents unauthorized use and falsification by applying digital signature with cloud environment to a third party's reference letter.

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Addressing data Misalignment in Image-LiDAR Fusion on Point cloud Segmentation

Addressing Data Misalignment in Image-LiDAR Fusion on Point ...

引用

big data, cloud computing, data science & Engineering (bcd)

作者： Wei-Jong Yang Li-Yang Ho Department of Artificial Intelligence and Computer Engineering National Chin-Yi University of Technology Taichung Taiwan Department of Electrical Engineering National Cheng Kung University Tainan Taiwan

With the advent of advanced multi-sensor fusion models, there has been a notable enhancement in the performance of perception tasks within in terms of autonomous driving. Despite these advancements, the challenges persist, particularly in the fusion of data from cameras and LiDAR sensors. A critial concern is the accurate alignment of data from these disparate sensors. Our observations indicate that the projected positions of LiDAR points often misalign on the corresponding image. Furthermore, fusion models appear to struggle in accurately segmenting these misaligned points. In this paper, we would like to address this problem carefully, with a specific focus on the nuScenes dataset and the SOTA of fusion models 2DPASS, and providing the possible solutions or potential improvements.

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Tourist Route Recommendation Framework with Potential Travel Purposes

Tourist Route Recommendation Framework with Potential Travel...

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big data, cloud computing, data science & Engineering (bcd)

作者： Hiroaki Tsukamoto Motoi Iwashita Graduate School of Social Systems Science Chiba Institute of Technology Chiba Japan Dept. of Management Information Science Chiba Institute of Technology Chiba Japan

Japan has recently been experiencing an ageing society, and the population of local areas is declining. therefore, it is necessary to promote local revitalization. the purpose of this research is to develop the tourism industry, which is one of the local revitalization measures. At the stage of tourism planning, it takes a lot of effort to build a tourist route by oneself. Namely, it is necessary to specify the purpose of travel from vague interest in travel and select tourist destinations accordingly. It is important to improve the satisfaction level according to the interests of individual tourists, considering the synergy effect that can be obtained by visiting and experiencing related tourist spots. this paper analyses the relationship between travel purposes based on vague interest in travel and proposes the framework of tourist route recommendation with these relationships as the synergy effect.

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A Consideration on countermeasure for avoiding congestion at tourist sites

A Consideration on countermeasure for avoiding congestion at...

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big data, cloud computing, data science & Engineering (bcd)

作者： Kohki Inaba Motoi Iwashita Graduate School of Social Systems Science Chiba Institute of Technology Chiba Japan Dept. of Management Information Science Chiba Institute of Technology Chiba Japan

In preparation for the post-coronavirus era, overseas exchanges are being revived. As a result, the potential desire to travel overseas will suddenly explode, and an increase in the number of tourists is expected in all regions. However, congestion at famous tourist destinations can lead to lower tourist satisfaction and missed opportunities from an economic perspective. the aim of our research is to guide people to nearby attractive tourist sites as a way of avoiding crowding at tourist sites. Specifically, from an economic perspective, the method is proposed to comprehensively evaluate alternative sites as candidates for the tourist sites one originally wants to visit, based on the similarity of tourist resources, interest, popularity and travel distance.

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An Efficient Algorithm for Secure Key Management in cloud Environment 8

An Efficient Algorithm for Secure Key Management in Cloud En...

引用

8th ieee international conference on science, Technology, Engineering and Mathematics, ICONSTEM 2023

作者： Jospin Jeya, J. Raja Ratna, S. Ganga Devi, G. Priya, M. Sivasankar, C. Srm Institute of Science and Technology Department of Computer Science and Engineering India Simats Cse Saveetha School of Engineering Chennai India

ISBN: (纸本)9798350347791

cloud infrastructure is efficient and scalable in all aspects;hence an enhanced method of safety measures is needed for secured data transfer. Security solution for cloud centric PC's was reliable in providing the on-demand cloud services. the common way to protect file before sending the file is encrypting the file. So safe key generation and allocation to the client for file decryption is a big task. the significant method we proposed is to receive the secret key secretly by the allowed user. We proposed wellorganized algorithm to share out the secret key in cloud computing environment. In this paper the safety method used depends on two things. One is improving the security by using secure socket shell channel and the second one is sharing the secret key to the allocated user using well organized key distribution algorithm. © 2023 ieee.

关键词： data transfer

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HNSW-based DBSCAN for Large-scale Point cloud computing

HNSW-based DBSCAN for Large-scale Point Cloud Computing

引用

big data, cloud computing, data science & Engineering (bcd)

作者： Jiwan Park Seongjin Oh Tae-yong Kim Jieun Lee Jaebin Lee Jongpil Jeong Dept. of Smart Factory Convergence Sungkyunkwan University Suwon Republic of Korea School of Civil Architecture Engineering Sungkyunkwan University Suwon Republic of Korea

this research aims to introduce an innovative algorithm for processing point cloud data, a key technology in the Fourth Industrial Revolution. Point cloud data, which is used to accurately represent real-world objects and environments, is often noisy due to environmental factors, which affects the accuracy and reliability of the data. the proposed algorithm effectively solves the noise problem to achieve high accuracy in data analysis and information extraction. the framework also combines the HNSW (Hierarchical Navigable Small World) index and the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm for efficient data retrieval and management in large data sets. these tools can be applied to various domains and have demonstrated robust performance in experiments. therefore, this research has the potential to drive innovation in the Fourth Industrial Revolution and is expected to serve as a practical tool for accurate data analysis and information extraction from large data sets.

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PRIVATE-AI: A Hybrid Approach to privacy-preserving AI

PRIVATE-AI: A Hybrid Approach to privacy-preserving AI

引用

big data, cloud computing, data science & Engineering (bcd)

作者： Siddanth Krishna Siri S Saif Kamalsha Sai Amruth Shruti Jadon Computer Science Engineering PES University Bangalore India

Machine learning algorithms based on Deep Neural Networks (NN) have achieved remarkable results and are being extensively used in different domains. A crucial enabler for Artificial Intelligence is the quantum of data, and these models are as good as the quality of data that is used to train them. However, gathering data and using them to prognosticate behaviours presents great challenges to the privacy of individuals and organizations, such as data breaches, privacy loss, and the corresponding financial and reputational damages. Privacy-preserving machine learning (PPML) aims at bridging the gap between preserving privacy and reaping the benefits of ML. It is a key enabler for privatizing collected data and complying with data protection regulations. the goal of the project is to implement a hybrid approach to Privacy Preserving AI by using these three Privacy Preserving techniques namely: Federated Learning, Differential Privacy, and Homomorphic Encryption to achieve maximum user data privacy while not affecting the overall accuracy of the predictions and computations made by the AI model.

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