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Slicing-Based Enhanced Method for Privacy-Preserving in Publishing Big Data

computers, Materials & Continua 2022年第8期72卷 3665-3686页

作者： Mohammed BinJubier Mohd Arfian Ismail Abdulghani Ali Ahmed Ali Safaa Sadiq Faculty of Computing Universiti Malaysia PahangKuantanPahangMalaysia School of Computer Science and Informatics De Montfort UniversityLeicesterLE19BHUnited Kingdom School of Engineering Computing and Mathematical SciencesUniversity of WolverhamptonWulfruna Street WolverhamptonWV11LYUnited Kingdom

Publishing big data and making it accessible to researchers is important for knowledge building as it helps in applying highly efficient methods to plan,conduct,and assess scientific ***,publishing and processing big data poses a privacy concern related to protecting individuals’sensitive information while maintaining the usability of the published *** anonymization methods,such as slicing and merging,have been designed as solutions to the privacy concerns for publishing big ***,the major drawback of merging and slicing is the random permutation procedure,which does not always guarantee complete protection against attribute or membership ***,merging procedures may generatemany fake tuples,leading to a loss of data utility and subsequent erroneous knowledge *** study therefore proposes a slicingbased enhanced method for privacy-preserving big data publishing while maintaining the data *** particular,the proposed method distributes the data into horizontal and vertical *** lower and upper protection levels are then used to identify the unique and identical attributes’*** unique and identical attributes are swapped to ensure the published big data is protected from disclosure *** outcome of the experiments demonstrates that the proposed method could maintain data utility and provide stronger privacy preservation.

关键词： Big data big data privacy preservation anonymization data publishing

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Interval Partitioning for Packet Classification in OpenFlow vSwitch

IEEE Networking Letters

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IEEE Networking Letters 2020年第3期2卷 128-131页

作者： Akkoc, Mertkan Canberk, Berk Department of Computer Engineering Faculty of Computer and Informatics Istanbul Technical University İstanbul34469 Turkey

Packet classification is a key factor for choosing proper action for incoming packet and has to be done fast and effectively, especially in OpenFlow. But OpenFlow vSwitch technology doesn't always allow to use some fast hardware technology for packet classification like TCAM (Ternary Content Addressable Memory). Instead of TCAM, decision tree methods are preferred solutions for fast classification in OpenFlow vSwitch in the literature. But most of these methods can cause the rule replication problem. As a result, while the duration of packet classification decreases, rule update duration increases. There are also rule partitioning methods in the literature to solve this problem, but the running time of these methods mostly depends on the number of rule fields. Also, some of these solutions don't overcome the rule replication problem. At that point, the main question of this letter is that how can we make the rule partitioning fast by both preventing the rule replication and allowing fast packet classification and rule update in OpenFlow vSwitch? To solve the rule partitioning problem, we propose a greedy based interval partitioning strategy. Here, the running time of the partitioning algorithm only depends on the rule number. After partitioning, we propose to use HyperCuts to construct decision trees for fast packet classification and rule update. According to performance evaluation results, we do the rule partitioning and rule updates faster than the PartitonSort method with the percentage of 88, 15, respectively. Also, we classify packet faster than the TupleMerge method with the percentage of 40 for online and 50 for offline scenarios. © 2019 IEEE.

关键词： Decision trees

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Dynamic Load Frequency Control for Small Signal Stability Analysis in Steam Plant with Reheater 21

Dynamic Load Frequency Control for Small Signal Stability An...

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21st IEEE International Symposium on Intelligent Systems and informatics, SISY 2023

作者： Shahgholian, Ghazanfar Fathollahi, Arman Mosavi, Amirhosein Islamic Azad University Smart Microgrid Research Center Najafabad Branch Najafabad Iran Aarhus University Department of Electrical and Computer Engineering Aarhus Denmark John von Neumann Faculty of Informatics Budapest Hungary Ludovika University of Public Service Budapest Hungary

ISBN: (纸本)9798350343366

Steam energy plants are the fundamental source of electricity in the world, which has a large share of renewable energy. Load changes impact the frequency of electrical networks. Frequency stabilization is very important based on the boosting influence of renewable power sources in energy systems. The main task of load frequency control is to keep the system frequency according to the determined nominal value and to maintain the correct amount of exchange energy between the control areas. Maintaining the output power and actual frequency of the interconnected energy system and controlling the variation in power along the connection link between control areas are the central objectives of load frequency control (LFC). In this work, the purpose is to analyze and investigate load frequency control in a two-area energy system. Each area contains a steam turbine with a reheater. The system equations are expressed in state space and analyzed in MATLAB software. The simulation outcomes demonstrate the impact of changes in the gain parameters of the equivalent power system model and high-pressure coefficient in an area. © 2023 IEEE.

关键词： Thermoanalysis

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Application of Serverless Computing in Blockchain Distributed Technology

Application of Serverless Computing in Blockchain Distribute...

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2023 International Conference on Disruptive Technologies, ICDT 2023

作者： Chellasamy, Natarajan Akram, Faiz Rajesh, Nichenametla Umamaheswari, R. Assosa University Department of Electrical and Computer Engineering Assosa Ethiopia Jimma University Jimma University Faculty of Computing and Informatics Jimma Ethiopia Department of Cse Andhra Pradesh Guntur India Gnanamani College of Technology Department of Cse Tamil Nadu Namakkal India

ISBN: (纸本)9798350323887

Serverless is a peer-to-peer system that is associated with the cloud architecture that aims to reduce the efforts required by the cloud manager to provide an efficient service. Blockchain enable collaborative distributed mechanism to enable a decentralized management of resource allocation. The resource allocation is been a major concern when blockchain is enabled in the serverless computing. In this paper, we develop a serverless computing model that is embedded with blockchain manner in a distributed fashion. The formulation is made in such a way that if fulfils the task allocation in a better way with increased makespan and reduced latency while a resource is allocated for required operation. © 2023 IEEE.

关键词： Cloud computing architecture

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Data Analytics for Volunteer-Based Educational Application

Data Analytics for Volunteer-Based Educational Application

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AFRICON Conference

作者： Omar Sherif Yasmine Zaghloul Nada Sharaf Informatics and Computer Science The German International University Cairo Egypt Faculty of Engineering German International University Cairo Egypt

In the world of technology, data have been available easily and in huge amounts. Because of the large amounts of data, Educational Data Mining (EDM) is increasingly gaining more importance. Educational data mining is trending as it is the analysis method for analyzing educational data. It involves checking the relationship between the characteristics of students and which features affect their final grades the most. It can also involve predictive modeling by predicting the final grades of students in the future to help educational institutes rescue failing students before they actually fail. Predictive analysis was the main focus in past years where most researchers targeted predicting grades of students. However, not all educational institutes are able to collect the amount of data suitable for machine learning models to achieve good accuracy. That is why the main target of the work presented in this paper is to develop an interactive interface that gives the ability to educational institutes to check by themselves the relation between different factors using correlation mining. The output of the tool is visual with message boxes to make it understandable by users. That is the best way to discover hidden patterns and trends without the need for a large amount of data in addition to removing the cost of deploying machine learning models. The second goal of the work is to give teachers the ability to check the quality of the content of their slides to help them provide a better learning process.

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Digital Technology in Health Education Trend Mapping through Bibliometrics Analysis 4

Digital Technology in Health Education Trend Mapping through...

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4th International Conference on informatics, Multimedia, Cyber and Information System, ICIMCIS 2022

作者： Maulana, Fairuz Iqbal Lestari, Dian Widartha, Vandha Pradwiyasma Haidar, Nirwana Dirgantara, Wahyu School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Airlangga University Faculty of Medicine Surabaya60132 Indonesia Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia University of Madura Informatics Engineering Study Program Pamekasan Indonesia University of Merdeka Malang Department of Electrical Engineering Malang Indonesia

ISBN: (纸本)9781665473279

This study examines the mapping of research data on digital technology in the field of health education using bibliometric analysis method. Data was collected by identifying keywords in the Scopus database and sorting them out to sort the studies from the last 10 years (2012-2021). Through this step, a total of 1482 documents were obtained (articles, journals, proceedings, books, and others). The data is then processed using the VOSViewer instrument to obtain a visualization of the mapping analysis. This study also analyzes the network types of authors and co-authors through the VOSViewer instrument. The result of this study indicates that the most document types published within ten years are Articles (66.5%), Review (22.9%), Conference Paper (4.2%), and others. The most studied subjects are Medicine (55.7%), Nursing (9.0%), Health Professions (8.2%), Social Sciences (7.8%), engineering (3.9%), computer Science (2.6%), Environmental Science (2.6%), Biochemistry-Genetics and Molecular Biology (2.2%), Psychology (1.6%), and Dentistry (1.3%). This study offers a written communication process and the nature and direction of developing descriptive means of counting and analyzing the various phases of communication as well as recognizing the authorship and direction of its symptoms in documents on the subject of digital technology in the health sector. © 2022 IEEE.

关键词： Mapping

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Exploring the Impact of Real and Synthetic Data in Image Classification: A Comprehensive Investigation Using CIFAKE Dataset

Exploring the Impact of Real and Synthetic Data in Image Cla...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Amila Akagic Emir Buza Medina Kapo Mahdi Bohlouli Department of Computer Science and Informatics Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina Research and Innovation Department Petanux GmbH Bonn Germany

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This research explores into the utilization of synthetic data within image classification tasks and evaluates its efficiency in comparison to the utilization of real data. To facilitate this investigation, we employ the CIFAKE dataset, comprising the well-established CIFAR10 dataset and an equivalent number of images synthetically generated using the Latent Diffusion Model (LDM). The increasing demand for diverse and abundant labeled datasets has prompted the emergence of synthetic data as a potential solution to address data scarcity. Within this study, we scrutinize the performance of image classification models trained on both real and synthetic datasets. To ensure a comprehensive evaluation, we alternately apply test data across different models. Our analysis encompasses diverse factors, including classification accuracy, generalization capabilities, and robustness in various scenarios. The findings provide valuable insights into the efficacy of synthetic data as a viable alternative or complement to real data in the realm of image classification.

关键词： Training Measurement Neural networks Process control Data models Robustness Information technology Synthetic data Image classification Testing

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Pipeline Representation Using Generic Parallel Algorithms in Heterogeneous Parallel Computing. A comparative analysis 36

Pipeline Representation Using Generic Parallel Algorithms in...

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36th European Modeling and Simulation Symposium, EMSS 2024, Held at the 21st International Multidisciplinary Modeling and Simulation Multiconference, I3M 2024

作者： Rossainz-López, Mario Sánchez-Rinza, Bárbara López-Sosa, Zuriel Capel-Tuñon, Manuel Faculty of Computer Science Autonomous University of Puebla Av. San Claudio and 14 Sur Street San Manuel PueblaC.P. 72570 Mexico Software Engineering Department College of Informatics and Telecommunications ETSIIT University of Granada Daniel Saucedo Aranda s/n Granada18071 Spain

ISBN: (纸本)9791281988026

Using Parallel Objects and Structured Parallel Programming, the parallel representation of the Communication Pattern between Processes called Pipeline is shown, whose implementation is carried out through different models of Generic Parallel Algorithms within Heterogeneous Parallel Computing (HPC): As a Parallel Design Pattern or PDP, as High-Level Parallel Composition or HLPC and as Flow Graph Interfaces or FGI through programming with message passing. An original and effective development methodology for new programmers in parallelism is proposed for each of them. In these three proposals for Generic Parallel Algorithms, the same problem-example is solved as a case study, and a comparative analysis of their models and designs is carried out, as well as the performance obtained in the execution of said proposals and demonstrate their usefulness, programmability, and performance. The objective of this work is to provide the programmer and/or novice user with different multicore programming approaches so that without much effort they can develop their programs according to a sequential programming style, obtaining automatically, easily and the counterpart parallelization of your code with the help of a specific programming environment like the one proposed. © 2024 The Authors.

关键词： Structured programming

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A Novel Optimized Resource Allocation Algorithm using GWO Optimization Technique for WBAN 23

A Novel Optimized Resource Allocation Algorithm using GWO Op...

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Proceedings of the 2023 12th International Conference on Software and Information engineering

作者： Amira Olayan Albashir Adel Youssef Mohamed Samir Abou El-Seoud Faculty of Informatics and Computer Science The British University (BUE) Egypt Department of Electronics and Communication Engineering Arab Academy for Science Technology and Maritime Transport Egypt

ISBN: (纸本)9798400708107

Wireless Body Area Networks have severe challenges in energy management to enhance the longevity of the system. Specifically, for a WBAN system that operates by ambient energy sources. The system combines energy scavenging modules integrated into the sensors carried by patients, enabling data transmission to a personal device. Our approach does not rely on previous information as the characteristics of the scavenged and consumed energy are stochastic. To optimize user utility, a formulation of an optimization problem by employing the Grey Wolf Optimization technique (GWO) compared to previous works that used different optimization techniques, to decompose it into three sub-problems: battery management, collecting rate control, and transmission power allocation. To achieve our goals, we apply the GWO to the introduced online resource allocation algorithm that serves two primary purposes: (1) balancing energy scavenging and consumption of network nodes to ensure system stability, and (2) maximizing user utility. Through simulation results, we validate the effectiveness and optimization capabilities of the algorithm while applying a different optimization technique from the previous works maintained.

关键词： Energy management GWO WBAN

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Analysis of Enterprise Resource Planning (ERP) system implementation for manufacturing in Indonesia 2

Analysis of Enterprise Resource Planning (ERP) system implem...

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2nd UPY International Conference on Applied Science and Education, UPINCASE 2020

作者： Sari, Marti Wdya Santoso, Banu Department of Informatics Faculty of Science and Technology Universitas PGRI Yogyakarta Yogyakarta Indonesia Department of Computer Engineering Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia

The purpose of this study is to analyze the success of ERP systems in Indonesia for companies that have implemented ERP systems. There are various kinds of companies with different business fields, such as manufacturing, mining, oil and gas, information technology and construction companies. The method used to achieve this research goal is through the study of literature, by selecting ERP references that support, starting from the theory, framework and information resources. The population involved is the end-user ERP, which consists of various types of industries that have implemented an ERP system. The results of this study indicate the measurement of system quality, service quality, information quality, benefits obtained, user satisfaction and ERP system benefits. © Published under licence by IOP Publishing Ltd.

关键词： Enterprise resource planning

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