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检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1358 条记录，以下是361-370 订阅

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An Empirical Analysis of Python Programming for Advance computing 2

An Empirical Analysis of Python Programming for Advance Comp...

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2nd international conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2022

作者： Baliyan, Anupam Kaswan, Kuldeep Singh Dhatterwal, Jagjit Singh Chitkara University Chitkara University Institute of Engineering & Technology Punjab India Koneru Lakshmaiah Education Foundation Department of Artificial Intelligence & Data Science AP Vaddeswaram522002 India

ISBN: (纸本)9781665437899

Python is an object-oriented, scripting, and interpretive programming language that may be used for mentoring and real-world applications. This paper focusses primarily on Python software packages used in data science, pattern recognition, and IoT. This paper will first explain Python as a language, then introduce data Science, Machine learning, and IOT, describing prominent packages in the data Science and Machine learning community, such as NumPy, SciPy, TensorFlow, Keras, Matplotlib. This paper will also demonstrate the significance of Python in the development of the industry. Throughout, we shall utilize many code samples. We review so many research papers to analyze the usage of python in different fields and easily import packages in the programming software. © 2022 IEEE.

关键词： big data

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Research on the Construction of Performance Evaluation System of Financial Shared Service Center of Enterprise Group under 'big intelligence Moving Cloud'

Research on the Construction of Performance Evaluation Syste...

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2022 international conference on Machine Learning and Knowledge Engineering, MLKE 2022

作者： Li, Wenjing Zhang, Zhiwei Peng, Yunlong Xiao, Jiahao Southwest Petroleum University Intelligent Financial Technology and System Key Laboratory of Nanchong City Nanchong China Southwest Petroleum University Nanchong China

ISBN: (纸本)9781665495677

With the rapid development of information technologies such as big data, artificial intelligence, mobile Internet and cloud computing, the financial sharing service center of enterprise groups has ushered in a new stage of development. From the perspective of value creation, based on the characteristics of enterprise groups and the concept that financial sharing centers should develop with the times, this paper preliminarily establishes the framework of the performance evaluation system of enterprise groups' financial sharing service centers on the basis of the balanced scorecard, and determines the weight of each index affecting the performance evaluation system by combining expert scoring method and analytic hierarchy process. Finally, the performance evaluation system of enterprise groups' financial sharing service centers in line with the intelligent era is obtained. © 2022 IEEE.

关键词： Analytic hierarchy process

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Coded Distributed computing Schemes via Grouping Method 22

Coded Distributed Computing Schemes via Grouping Method

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8th international conference on computing and Artificial intelligence, ICCAI 2022

作者： Jiang, Jing Zhou, Lingling Qu, Lingxiao Guangxi Key Laboratory of Multi-Source Information Mining and Security Guangxi Normal University China

ISBN: (纸本)9781450396110

Coded distributed computing introduced by Li et al. in 2015 is an efficient approach to reduce the communication load in general distributed computing frameworks such as MapReduce. But there is a big disadvantage in this scheme, that is, the numbers of required input files and output functions increase exponentially with the increase of the number of computing nodes. In this paper, we make an attempt to overcome these problems by constructing some new coded distributed computing schemes. We demonstrate that when the number of computing nodes becomes large, 1) the number of input files in the proposed scheme is much smaller than that of input files in the scheme derive by Li et al.;2) the required number of output functions is reduced exponentially. Meanwhile, the ratio of the communication load to that of the scheme derived by Li et al. is less than 3. © 2022 ACM.

关键词： Computer programming

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Supervised learning and unsupervised learning on music data with different genres 7

Supervised learning and unsupervised learning on music data ...

引用

7th IEEE international conference on big data intelligence and computing, datacom 2021

作者： Liu, Chunang Chao, Zehan Jining China Beijing China

ISBN: (纸本)9781665420716

As the digital music datasets evolve fast in the past decades, researchers start to focus on the machine learning tasks on music datasets with music content analysis. Both supervised learning and unsupervised learning have become increasingly popular as searching and recommending are the major tasks for digital music datasets. In this work, we are interested in exploring automatic classification of music with different genres. In this paper, we visualize and embed Spotify music in 3 dimension space with principal component analysis techniques;classifying different music genres via MFCC related algorithms and various machine learning algorithms. We use the method of PCA to determine the relationship between each feature of those songs in the data including 154932 songs and utilize different visualization techniques to obtain insight into the dataset. Thus, we could get the similarity of the songs by analyzing the two clusters of points on the graph. Additionally, we use numerous supervised learning techniques to perform classification on those songs in ten genres and evaluating their performance. Experimental results show the feasibility of automatic management of music databases and the potential to improve. © 2021 IEEE.

关键词： Supervised learning

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Design of student behavior characteristics analysis platform based on K-means clustering algorithm in local universities 3

Design of student behavior characteristics analysis platform...

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3rd international conference on big data, Artificial intelligence and Internet of Things Engineering, ICBAIE 2022

作者： Xiao, Kun Duan, Zhongyi Li, Mingen Yao, Jinkui East China University of Technology School of Geophysics and Measurement-control Technology Nanchang China

ISBN: (数字)9781665451604

ISBN: (纸本)9781665451604

Student behavior characteristic data can fully reflect the behavior law of college students, which is of great significance to the educational management and decision-making of local universities. With the gradual acceleration of information construction in colleges and universities, most colleges and universities have developed the campus information management system. Facing the massive campus management data, how to effectively mine valuable information from it has become an important content to improve the level of student information management. This paper uses big data processing and analysis technology to comprehensively analyze the current big data of local universities. Moreover, a distributed computing platform based on K-means clustering algorithm is constructed based on the behavioral characteristics of college students, and a prediction model between student behavior and talent quality cultivation is constructed. This research can guide teaching management, student management, employment guidance and other related work in local universities. © 2022 IEEE.

关键词： big data

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Impact of Mobility Speed and Network Density on the Performance of Vehicular Ad Hoc Network Routing Protocols 5

Impact of Mobility Speed and Network Density on the Performa...

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5th international conference on Artificial intelligence, big data, computing and data Communication Systems (ICABCD)

作者： Osifeko, Martins O. Hancke, Gerhard P. Abu-Mahfouz, Adnan M. Univ Pretoria Dept Elect Elect & Comp Engn Pretoria South Africa Nanjing Univ Posts & Telecommun Coll Automat & Artificial Intelligence Nanjing Peoples R China Council Sci & Ind Res CSIR Pretoria South Africa

ISBN: (数字)9781665484220

ISBN: (纸本)9781665484220

Vehicular Ad Hoc Network (VANET) is a type of network that facilitates communication between vehicles usually on highways or in any environment with vehicular traffic such as a parking space. The dynamic nature of vehicular movements makes VANETs' topology highly unstable and prone to transmission unreliability. Hence, to achieve its major goal of traffic safety and enhanced traffic flow, the research community has identified the need for solutions that address efficient data transmission, ultrafast connectivity, reliable handovers, security, and privacy for vehicles. To achieve this, several routing protocols have been developed in the literature. Some of which include Ad hoc on-demand Distance Vector (AODV), Optimized Link State Routing (OLSR), Destination-Sequenced Distance-Vector (DSDV), and Dynamic Source Routing Protocol (DSR). In this paper, a performance analysis of four of these routing protocols in a realistic environment is carried out. Specifically, this work investigated the effect of mobility speed and network density on the efficiency of four VANET protocols using the metrics of packet loss rates, delivery ratio, and average end to end delay. For the evaluated cases, results reveal that OLSR had the best performance for having the lowest average delay, while the DSDV had the best performance in packet loss rates and delivery ratio.

关键词： VANET AODV OLSR DSDV Packet Delivery Rates

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The Implication of data Lake in Enterprises: A Deeper Analytics 8

The Implication of Data Lake in Enterprises: A Deeper Analyt...

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8th international conference on Advanced computing and Communication Systems, ICACCS 2022

作者： Singh, Jaspreet Singh, Gurpreet Bhati, Bhoopesh Singh Computer Science and Engineering Chandigarh University Mohali India

ISBN: (纸本)9781665408165

Everyday enormous amounts of information are produced from computerized advancements and handling these gigantic complex data requires a decent knowledge on the most proficient method to deal with this data. With a purpose to make the most from this multiform data for determined benefits, the data lake emerge as idea for enhanced adaptability and strong data analytics. data Lake terminology signify a storage space for storing heterogeneous data, both organized as well as unstructured, bringing about an adaptable association that permits data lake customers incorporate data dynamically which they request. big data innovation offer help to enterprises in business intelligence process yet there exists lack of empirical study on utilization of data lake technique in enterprises. This paper gives an exploratory review on data lake implication by portraying its concept, functional architecture, development stages involved and numerous research challenges and direction;which will improve the effective utilization of the data lake approach in enterprises. © 2022 IEEE.

关键词： Lakes

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An Overview of the Internet of Things (IoT) Applications in the Health Sector in Saudi Arabi

An Overview of the Internet of Things (IoT) Applications in ...

引用

international conference on big data intelligence and computing, datacom 2022

作者： Masmali, Feisal Hadi Miah, Shah Jahan Noman, Nasimul School of Electrical Engineering and Computing The University of Newcastle NewcastleNSW Australia College of Business Administration Jazan University Jazan Saudi Arabia Newcastle Business School The University of Newcastle Newcastle City Campus NewcastleNSW Australia School of Information and Physical Sciences University of Newcastle NewcastleNSW Australia

ISBN: (纸本)9789819922321

The Internet of Things (IoT) makes it possible for integrating medical information services with multiple sources. Government’s information technology solutions often include sensing devices that measure health information in real time. IoT has a significant impact on the healthcare industries by helping to manage medical operations and healthcare such as for reducing effects of chronic diseases. Effective information dissemination could save lives by offering real time information to take certain precautions or by letting doctors know when something alarming happens. Internet of Things (IoT) mobile apps for medical treatment were just released in Saudi Arabia. During the COVID-19 pandemic, people in the country used IoT a lot because it helped doctors keep an eye on patients from far away. A reliable IoT platform makes it easy to connect devices, manage them in bulk through cloud services, and use analytics to make changes. The vast majority of healthcare data is kept in separate places called "silos." It is hoped that one day, Saudi Arabia’s new healthcare system will be able to connect patients in different parts of the country. Giving this background, it is important to conduct research to outline a overview of the IoT applications in healthcare for early-career researchers and students who may have benefits of understanding the body of the knowledge trends. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Center-Based Approximation of a Drifting Distribution 36

Center-Based Approximation of a Drifting Distribution

引用

36th international conference on Algorithmic Learning Theory, ALT 2025

作者： Mazzetto, Alessio Ceccarello, Matteo Pietracaprina, Andrea Pucci, Geppino Upfal, Eliezer Brown University United States University of Padova Italy

We present a novel technique for computing a center-based approximation of a drifting distribution. Given k ≥ 1 and a stream of data, whose distribution is changing over time, the goal is to compute, at each step, the best k centers representation of the current distribution, despite possibly having only a single sample from the most recent distribution. In data mining, this is traditionally attempted through the sliding-window mechanism, where the analysis is performed on the most recent fixed-size segment of the data. The problems with this approach are twofold: (1) setting the correct window size is challenging;and (2) a fixed window size cannot effectively track changes in the distribution happening at variable speed. In this paper, we propose a new methodology that dynamically adjusts the window size based on the recent drift of the data. The challenge is that it is not possible to explicitly estimate the drift, as we may have only a single data point from each distribution. Our main contribution lies in providing a rigorous mathematical analysis, establishing both an upper bound via a dynamic window size algorithm, and a lower bound that shows the tightness of our approach. © 2025 A. Mazzetto, M. Ceccarello, A. Pietracaprina, G. Pucci & E. Upfal.

关键词： data mining

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Establishing a Knowledge Base of an Expert System for Criminal Investigation 3

Establishing a Knowledge Base of an Expert System for Crimin...

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3rd international conference on big data, Artificial intelligence and Internet of Things Engineering, ICBAIE 2022

作者： Liao, Mancheng People's Public Security University of China School of Criminal Investigation Beijing China

ISBN: (数字)9781665451604

ISBN: (纸本)9781665451604

In the information era, knowledge is becoming increasingly significant for all industries, especially criminal investigation that deeply relies on intelligence and strategies. Therefore, there is an urgent need for effective management and utilization of criminal investigation knowledge. As an important branch of knowledge engineering, the expert system can simulate the thinking pattern of an expert, proposing strategies and solutions based on the knowledge stored in the knowledge base. A crucial step in building the expert system is to construct the knowledge base, which determines the function and capability of the expert system. This paper establishes a practical knowledge base for criminal investigation, combining the technologies of cloud computing with traditional method of manual entry to acquire and process knowledge. The knowledge base covers data information and expert knowledge with detailed classification of rules and cases, providing answers through comparison and reasoning. The knowledge becomes more accurate and reliable after repeated inspection and verification by human experts. © 2022 IEEE.

关键词： Cloud computing

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