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22nd International Conference on Hybrid Intelligent Systems, HIS 2022 and the 18th International Conference on Information Assurance and Security, IAS 2022

作者： Turki, Houcemeddine Hadj Taieb, Mohamed Ali Ben Aouicha, Mohamed Data Engineering and Semantics Research Unit Faculty of Sciences of Sfax University of Sfax Sfax Tunisia

ISBN: (纸本)9783031274084

During the last years, many computer systems have been developed to track and monitor COVID-19 social network interactions. However, these systems have been mainly based on robust probabilistic approaches like Latent Dirichlet Allocation (LDA). In another context, health recommender systems have always been personalized to the needs of single users instead of regional communities. Such applications will not be useful in the context of a public health emergency such as COVID-19 where general insights about local populations are needed by health policy makers to solve critical issues in a timely basis. In this research paper, we propose to modify LDA by letting it be driven by knowledge resources and we demonstrate how we can apply our topic modeling method to local social network interactions about COVID-19 to generate precise topic clusters reflecting the social trends about the pandemic at a low cost. Then, we outline how terms in every topic cluster can be converted into a search query to generate scholarly publications from PubMed Central for adjusting COVID-19 trendy thoughts in a population. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： COVID-19

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Improving the supply chain management via Blockchain: an olive oil case study

Improving the supply chain management via Blockchain: an oli...

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2023 Tunisian-Algerian Joint Conference on Applied Computing, TACC 2023

作者： Lahami, Mariam Chaabane, Faten ReDCAD Laboratory ENIS University of Sfax Tunisia DESLAB Data Engineering and Semantics Research Unit Faculty of Sciences of Sfax University of Sfax Sfax Tunisia

One of consumers' primary concerns is verifying the traceability of sensitive foods, such as olive oil. Henceforth, recently, ensuring that olive oil supply chain is reliable and safe has become highly required. The current state of this supply chain involves a variety of stakeholders with different interests, often reticent to share traceability information. In this paper, we present BOOSCh, a fully decentralized olive oil traceability solution built on Ethereum blockchain. Compared to the existing approaches, the proposed work uses both the secure InterPlanetary File System (IPFS) for off-chain data storage, and smart contracts to manage interactions among stakeholders, insuring transparency and efficiency Through this combination, BOOSCh eliminates intermediaries, ensuring an immutable and trusted transaction history. We provide implementation details of the approach to show its effectiveness, offering a template for improving supply chain processes in other industries. © 2023 CEUR-WS. All rights reserved.

关键词： Smart contract

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A Core Domain Ontology for Specifying the Business View of Enterprise Information Systems 1

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Ben Hassen, Mariam Zahaf, Sahbi Gargouri, Faïez ISIMS MIRACL Laboratory University of Sfax B.P. 242 Sfax3021 Tunisia Data Engineering and Semantics Research Unit Faculty of Sciences of Sfax University of Sfax Sfax Tunisia

ISBN: (数字)9783031647796

ISBN: (纸本)9783031647789

Enterprise Information Systems (EIS) supporting Business Processes (BPs), particularly Sensitive Business Processes (SBPs), should be characterized by integrity, flexibility, and interoperability. However, the urbanization approach, which we rely on to implement these systems, must address the "three fit" problems that hinder the realization of these desired features at both the business and technical infrastructures: "vertical fit" problems – concerning the business infrastructure;"horizontal fit" problems and "transversal fit" problems – concerning the technical infrastructure. We argue that for overcoming those problems, it is necessary to define an explicit framework for specifying BPs/SBPs. We present in this paper our conceptual specification for the BPs/SBPs modeling domain in the form of a core domain ontology, in order to overcome "horizontal fit" and "transversal fit" problems. Specifically, we introduce (i) our reference ontological framework and (ii) provide an overview of our Core Ontology of Sensitive Business Processes (COSBP). Our focus lies in the representation of SBPs in order to overcome "vertical fit" problems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Knowledge management

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Blockchain for data Traceability in the Agricultural Sector 23th

Blockchain for Data Traceability in the Agricultural Sector

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Talha, Amira Frikha, Tarek Data Engineering and Semantics Research Unit Faculty of Sciences of Sfax University of Sfax Sfax Tunisia Higher Management Institute of Gabes University of Gabes Gabes Tunisia ENIS University of Sfax Sfax Tunisia

ISBN: (纸本)9783031646492

Blockchain technology attracts a lot of attention in various agricultural applications. These applications could meet the diverse needs of the agricultural product ecosystem, for example by increasing the transparency of food safety and food quality control based on IoT, traceability of origin, improving contract exchanges and transaction efficiency. This article presents an innovative approach integrating blockchain technology, specifically Ethereum, to ensure the traceability of agricultural data. As part of this research, an advanced mobile application, developed in Flutter, is presented as an essential tool for the early detection of diseases in plants. The mobile app offers a user-friendly interface, offering users the ability to quickly diagnose agricultural diseases, facilitating early and effective intervention. At the same time, the Ethereum Blockchain is implemented to ensure the integrity, security and traceability of the data generated by the application. This study contributes to the convergence of emerging technologies, paving the way for more sustainable, reliable, and responsible agricultural practices. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Smart contract

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Application of Machine Learning Techniques to Enhance Decision Making Lifecycle

Application of Machine Learning Techniques to Enhance Decisi...

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International Conference on Advanced Intelligent Systems for Sustainable Development, AI2SD 2022

作者： Trabelsi, Salma Zahaf, Sahbi Aouicha, Mohamed Ben Data Engineering and Semantics Research Unit Faculty of Sciences of Sfax University of Sfax Sfax Tunisia Institut Supérieur d‘Informatique University of Tunis El-Manar Hiboun Tunisia

ISBN: (纸本)9783031263835

In recent years, machine learning has been mainly used to simplify various tasks in the intelligent automation of IT. Because when these various tasks are automated, organizations can save money and time in achieving or maintaining accurate and efficient results. Additionally, these organizations gain complete control over the IT infrastructure and reduce problem resolution time. It provides organizations with better IT automation and allows them to focus on their customers and grow their business by providing a more comprehensive fraud detection system. In the business world, the problem of "three matches" in Bidding Process Information Systems (BPIS) is still an open topic. BPIS must: be integrated, flexible and interoperable to accommodate urbanization approaches. Therefore, the operational, organizational, decision-making, and collaboration dimensions are the four dimensions that have been identified to deal with such failures. By the way, decisions in any area of your business should be made after analyzing the situation. It should be the first step in planning a project or establishing a new program. Therefore, in this work, we are particularly interested in addressing this error by using a machine learning approach to detail the three first steps in the decision life cycle to effectively obtain a better life cycle that gives us the best decision making. This improves on the end of the domain and takes into account the user’s knowledge by focusing on the company’s needs. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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STM32 miner : A lightweight blockchain mining system 1

STM32 miner : A lightweight blockchain mining system

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1st IEEE International Conference on Design, Test and Technology of Integrated Systems, DTTIS 2023

作者： Ktari, Jalel Choura, Hedi Frikha, Tarek Baklouti, Mouna Mejdi, Dhia Kotti, Molka Zribi, Ahmed Touil, Hassine Oueslati, Ghaith National Engineering School of Sfax Computer Embedded Systems Lab Sfax Tunisia National Engineering School of Sfax Data Engineering and Semantics Unit Sfax Tunisia National Engineering School of Sfax Computer Sciences and Applied Mathematiques Departement Sfax Tunisia

ISBN: (纸本)9798350316957

Despite being a promising area of exploration, the application of embedded systems in blockchain technology, particularly with FFGA or Raspberry technology, remains relatively limited. Despite the advantages offered by FPGAs, such as high-speed memory, parallel computing blocks, and a flexible architecture, their use in blockchain has primarily been focused on Proof of Work (PoW) consensus *** this paper, our goal is to address this gap by presenting the implementation of a blockchain application specifically tailored for the STM32 platform. By leveraging the capabilities of the STM32 microcontroller, we aim to demonstrate the practicality and effectiveness of embedded systems in blockchain technology, overcoming the limitations observed with previous platforms. © 2023 IEEE.

关键词： Blockchain

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Leveraging Blockchain for Secure Water Meter Reading 23th

Leveraging Blockchain for Secure Water Meter Reading

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Mohamed, Shams Adhouha Ben Ktari, Jalel Frikha, Tarek Data Engineering and Semantics Research Unit Faculty of Sciences of Sfax University of Sfax Sfax Tunisia Higher Management Institute of Gabes Gabes Tunisia CES Lab ENIS University of Sfax Sfax Tunisia ENIS University of Sfax Sfax Tunisia

ISBN: (纸本)9783031646492

Currently, Blockchain technology represents a modern and a promising innovation capable of revolutionizing various sectors by fostering innovative solutions and establishing trust in multi-party corporate networks. This paper explores real-world applications of blockchain and its potential to streamline water meter reading processes through the development of an Android App. By harnessing the power of blockchain, this application allows users to conveniently input water meter readings using their smartphones. The recorded data is securely stored on the Ethereum blockchain utilizing smart contracts, ensuring data integrity and transparency. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Blockchain

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Toward Optimal Periodic Crowd Tracking via Unmanned Aerial Vehicle

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Computer Modeling in engineering & Sciences 2023年第10期137卷 233-263页

作者： Khalil Chebil Skander Htiouech Mahdi Khemakhem Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlKharj11942Saudi Arabia Data Engineering and Semantics Research Unit Faculty of Sciences of SfaxUniversity of SfaxSfaxTunisia Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Mathematics and Business Intelligence College of Electronics and Telecommunications Engineering of SfaxUniversity of SfaxSfaxTunisia

Crowd management and analysis(CMA)systems have gained a lot of interest in the vulgarization of unmanned aerial vehicles(UAVs)*** tracking using UAVs is among the most important services provided by a *** this paper,we studied the periodic crowd-tracking(PCT)*** consists in usingUAVs to follow-up crowds,during the life-cycle of an open crowded area(OCA).Two criteria were considered for this *** first is related to the CMA initial investment,while the second is to guarantee the quality of service(QoS).The existing works focus on very specified assumptions that are highly committed to CMAs applications *** study outlined a new binary linear programming(BLP)model to optimally solve the PCT motivated by a real-world application study taking into consideration the high level of *** closely approach different real-world contexts,we carefully defined and investigated a set of parameters related to the OCA characteristics,behaviors,and theCMAinitial infrastructure investment(e.g.,UAVs,charging stations(CSs)).In order to periodically update theUAVs/crowds andUAVs/CSs assignments,the proposed BLP was integrated into a linear algorithm called PCTs *** main objective was to study the PCT problem fromboth theoretical and numerical *** prove the PCTs solver effectiveness,we generated a diversified set of PCTs instances with different scenarios for simulation *** empirical results analysis enabled us to validate the BLPmodel and the PCTs solver,and to point out a set of new challenges for future research directions.

关键词： Unmanned aerial vehicles periodic crowd-tracking problem open crowded area optimization binary linear programming crowd management and analysis system

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A Decade of Scholarly Research on Open Knowledge Graphs 30

A Decade of Scholarly Research on Open Knowledge Graphs

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Turki, Houcemeddine Owodunni, Abraham Toluwase Taieb, Mohamed Ali Hadj Bile, René Fabrice Aouicha, Mohamed Ben Data Engineering and Semantics Research Unit University of Sfax Sfax Tunisia Masakhane Abuja Nigeria National Polytechnic School of Maroua University of Maroua Maroua Cameroon SisonkeBiotik Research Community Johannesburg South Africa University of the People PasadenaCA United States

ISBN: (纸本)9782493814104

The proliferation of open knowledge graphs has led to a surge in scholarly research on the topic over the past decade. This paper presents a bibliometric analysis of the scholarly literature on open knowledge graphs published between 2013 and 2023. The study aims to identify the trends, patterns, and impact of research in this field, as well as the key topics and research questions that have emerged. The work uses bibliometric techniques to analyze a sample of 4445 scholarly articles retrieved from Scopus. The findings reveal an ever-increasing number of publications on open knowledge graphs published every year, particularly in developed countries (+50 per year). These outputs are published in highly referred scholarly journals and conferences. The study identifies three main research themes: (1) knowledge graph construction and enrichment, (2) evaluation and reuse, and (3) fusion of knowledge graphs into NLP systems. Within these themes, the study identifies specific tasks that have received considerable attention, including entity linking, knowledge graph embedding, and graph neural networks. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Knowledge graph

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Machine Learning Models for Early Prediction of COVID-19 Infections Based on Clinical Signs

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SN Computer Science 2024年第1期5卷 1-10页

作者： Ben Ammar, Boulbaba Salem, Ali Ben Said, Mouna Ben Aouicha, Mohamed Data Engineering and Semantics Research Unit Faculty of Science University of Sfax Sfax Tunisia Digital Research Center of Sfax Ministry of Higher Education and Scientific Research Sfax Tunisia Signals systeMs aRtificial intelligence and neTworkS Laboratory (SM@RTS) Digital Research Center of Sfax Sfax Tunisia

Nowadays, the appearance of common symptoms, such as cough, fever, and loss of smell and taste, is the starting point of a battle against the coronavirus. The first standard method of COVID-19 infection assertion has become the RT-PCR test, which is however an uncomfortable solution for both patients and medical staff due to its high cost, timeliness, and false-negative result issue. This has raised the need for reliable automatic detection systems that aid in the early prediction of the COVID-19 infections with a lower cost. In this work, we aim at profiting from the Machine Learning (ML) advances to provide a reliable and low-cost COVID-19 prediction system. This system is based on the disease starting point, which is the patients’ clinical symptoms, that are still under-explored. We developed seven predictive models using traditional ML classification algorithms using a public dataset of obvious high-risk factors from patients’ clinical signs. The dataset has first undergone a pre-processing phase consisting of feature engineering and dataset resampling to deal with imbalanced dataset issue. Our best classification model is able to detect true positives and true negatives and weed out false positive and false negatives with an accuracy of 93%. © 2024, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Clinical signs COVID-19 Early diagnosis Machine learning

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