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18th International Conference on Software Technologies, ICSOFT 2023

作者： Maamar, Zakaria Benna, Amel Xu, Yang Serhani, Mohamed Adel Li, Minglin Huang, Huiru Benadjel, Wassim Sitouah, Nacereddine College of Computing and IT University of Doha for Science and Technology Doha Qatar Department of Multimedia and Information Systems CERIST Algiers Algeria School of Computer Science Fudan University Shanghai China College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Computer Science Faculty USTHB Algiers Algeria Department of Electronics Information and Bioengineering Polytechnic University of Milan Milan Italy

ISBN: (纸本)9789897586651

Despite the multiple advantages of the Internet-of-Things (IoT), many users are still skeptical considering IoT as another disruptive information and communication technology that is "silently" invading their privacy with the risk of having their habits, preferences, and choices exposed publicly. To mitigate this silent invasion, this paper looks into innovative ways of making IoT sensitive to privacy by first, allowing users to explicitly express what is permitted, forbidden, and obliged over their personal data using the Open Digital Rights Language (ODRL), and second, adjusting things’ specifications like theWeb-of-Things Thing Description (WoT TD), so that things would act according to these users’ permissions, prohibitions, and obligations. A system implementing and demonstrating the blend of ODRL with WoT TD is presented based on a case study capturing privacy concerns in a center for elderly people. © 2023 by SCITEPRESS-Science and Technology Publications, Lda.

关键词： Differential privacy

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Analyzing video footage from security cameras using the Amped FIVE professional tool specifically for the identification of vehicle license plates

Analyzing video footage from security cameras using the Ampe...

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computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA), International Conference on

作者： Mišel Gvozdanović Damir Delija Domagoj Tuličić Goran Sirovatka Marinko Žagar Krunoslav Bilić Department of Informatics and Computing Zagreb University of Applied Science Zagreb Croatia Department of Computer Systems and Networks University of Applied Sciences in Information Technology Zagreb Croatia

This paper describes problems of improving security cameras’ video footage for forensic investigation. When processing records, one encounters problems with low resolution, poor lighting, or excessive distance of a key object in an image or video. Using the Amped FIVE Professional tool, forensic scientists create videos and analyze and process the record itself using various filters. Record quality demands a choice of video filters. The use and selection of filters show the improvement of the record itself to the level to which useful information can be obtained in this case of vehicle license plates. The presented roadmap can be used as the base for further video forensic research.

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Ontological Model for Cohesive Smart Health Services Management

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Computers, Materials & Continua 2023年第2期74卷 3679-3695页

作者： Muhammad Raza Naqvi Muhammad Waseem Iqbal Syed Khuram Shahzad M.Usman Ashraf Khalid Alsubhi Hani Moaiteq Aljahdali Le Laboratoire Génie de Production de l’École Nationale d’Ingénieurs de Tarbes(LGP-INP-ENIT) Universitéde ToulouseCEDEXTarbes65016France Department of Software Engineering Superior UniversityLahore53700Pakistan Department of Informatics&Systems University of Management&TechnologyLahore54000Pakistan Department of Computer Science University of Management and TechnologySialkot51310Pakistan Department of Computer Science King Abdul-Aziz UniversityJeddah21577Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21577Saudi Arabia

Health care has become an essential social-economic concern for all stakeholders(e.g.,patients,doctors,hospitals etc.),health needs,private care and the elderly class of *** massive increase in the usage of health care Internet of things(IoT)applications has great technological evolvement in human *** are various smart health care services like remote patient monitoring,diagnostic,disease-specific remote treatments and *** applications are available in a split fashion and provide solutions for variant diseases,medical resources and remote service *** main objective of this research is to provide a management platform where all these services work as a single unit to facilitate the *** ontological model of integrated healthcare services is proposed by getting requirements from various existing healthcare *** were 26 smart health care services and 26 smart health care services to classify the knowledge-based ontological *** proposed ontological model is derived from different classes,relationships,and constraints to integrate health care *** model is developed using Protégébased on each interrelated/correlated health care service having different *** querying SPARQL protocol and RDF query language(SPARQL)were used for knowledge *** Pellet Reasoner is used to check the validity and relations coherency of the proposed ontology *** to other smart health care services integration systems,the proposed ontological model provides more cohesiveness.

关键词： Ontology internet of things smart health services integration

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Towards Optimizing the Logistic Transportation Selection in Hajj

Towards Optimizing the Logistic Transportation Selection in ...

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2024 1st International Conference on Logistics (ICL)

作者： Marwa F. Mohamed Samiha M. Elsherif Mohamed Meselhy Eltoukhy Computer Sciences Department Faculty of Computers and Informatics Suez Canal University Ismailia Egypt Information Systems Department Faculty of Computers and Informatics Suez Canal University Ismailia Egypt Department of Information Technology College of Computing and Information Technology at Khulais University of Jeddah Jeddah Saudi Arabia

ISBN: (数字)9798331518844

ISBN: (纸本)9798331518851

The Hajj is an international Islamic event that takes place in Mecca, Saudi Arabia, annually and attracts millions of pilgrims. One of the most important services during the Hajj period is pilgrims' transportation services, they transport pilgrims between the holy sites (e.g., walking facilities, traditional buses, shuttle buses, and the holy sites train). The shuttle bus, among these services, is the busiest for Hajj. It operates during the Hajj and transports most of the pilgrims. For example, during the first Muzdalifah holiday, when on the ninth-day pilgrims move from Arafat to Muzdalifah, the transportation serves more than one million pilgrims. Therefore, there are many transportation companies, and choosing an appropriate company is one of the most important challenges facing Hajj organizers. There are many criteria for selecting transportation companies, such as cost and service quality; therefore, this paper presents a framework that uses the NSGA-III optimization algorithm to choose the best companies based on two objectives (e.g., costs and quality of service). The results of NSGA-III have been compared with heuristic algorithms (e.g., best fit and first fit), and NSGA-III outperformed these algorithms.

关键词： Legged locomotion Costs Heuristic algorithms Transportation Companies Quality of service Safety Time factors Optimization Logistics

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Investigation of the separation zone for split-domain light field visualization 28

Investigation of the separation zone for split-domain light ...

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2024 28th International Conference on Information Technology, IT 2024

作者： Javidi, Kamran Martini, Maria G. Kara, Peter A. School of Computer Science and Mathematics Faculty of Engineering Computing and the Environment Kingston University Wireless Multimedia and Networking Research Group Department of Computer Science Penrhyn Road Campus Kingston upon Thames LondonKT1 2EE United Kingdom Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services Budapest1111 Hungary

ISBN: (纸本)9798350369618

Light field visualization commonly provides a single content over the entire field of view. However, the angularly-selective nature of the technology enables the simultaneous visualization of different contents at different viewing angles. Yet segmenting the valid viewing area comes with content interference as well in forms of separation zones, resulting invalid viewing domains. In this paper, we introduce a study on the separation zone of split-domain light field visualization. We created a static-content-based scenario in which we split the valid viewing area into two distinct domains, with a separation zone in between them. This was achieved by merging two light field contents in the middle with an instantaneous switch. The resulting visualization on a light field display was captured by a DSLR camera from two viewing distances, and it was compared to the crosstalk effect caused by insufficient angular resolution. © 2024 IEEE.

关键词： Visualization

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Medical Insurance Premium Prediction Using Linear Support Vector Machine

Medical Insurance Premium Prediction Using Linear Support Ve...

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2023 Winter Summit on Smart computing and Networks, WiSSCoN 2023

作者： Linija, K.P. Geetha, S. Mavaluru, Dinesh Ravali, Sahithya Mary, S Angel Latha Sri Sairam College of Engineering Department of Aiml Bangalore India Sri Sairam College of Engineering Department of Electronics and Communication Engineering Bangalore India College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia Srm College of Pharmacy Department of Pharmacy Practice Chennai India Sri Eshwar College of Engineering Department of Computer Science and Business Systems Coimbatore India

ISBN: (纸本)9798350334050

In healthcare, data mining algorithms are utilized to make people's lives better by predicting diseases and trying to diagnose them faster than most doctors. When the middleman is eliminated, as it is with computerized medical insurance, there is an unbroken line of communication between the insurance company and the insured. Predicting the premium of medical insurance is a major source of worry. The only way for a health insurance provider to turn a profit is to receive more in premium payments than it pays out in claims. Linear Support Vector Machines (LSVM)are developed for Premium Prediction in the Well-beingAssurance Sector. Eleven different criteria were used to train and evaluate LSVM. Experimental results showed a 99% accuracy, and the researchers analysed the effectiveness of the algorithm using success metrics. © 2023 IEEE.

关键词： Health insurance

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Risk Assessment of Sustainable Supplier Selection: Systematic Review

Risk Assessment of Sustainable Supplier Selection: Systemati...

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Advances in Technology and computing (ICATC), International Conference on

作者： Sapthiha Priyatharshini Jeevaraj Withanaarachchi A.S Annista Wijayanayake Jinendri Prasadika Department of Industrial Management Faculty of Science University of Kelaniya Dalugama Sri Lanka Department of Information Systems and Business Analytics Faculty of Business and Law Deakin University Australia Department of Information Systems Engineering and Informatics Faculty of Computing University of Sri Jayewardenepura Sri Lanka

ISBN: (数字)9798331518219

ISBN: (纸本)9798331518226

This systematic literature review focuses on the risk assessment aspect of sustainable supplier selection within supply chains. Spanning peer-reviewed journal articles published between 2008 and 2024, a total of 42 papers were meticulously selected and analyzed in line with PRISMA guidelines. As businesses increasingly prioritize sustainability, the integration of environmental, social, and economic dimensions—commonly referred to as the Triple Bottom Line (TBL)—into supplier selection processes has become imperative. This review examines the evolution of decision-making techniques, highlighting the transition from traditional supplier selection methods to more comprehensive, sustainability-oriented approaches. Multi-Criteria Decision-Making (MCDM) methods, particularly those incorporating fuzzy-based approaches, are identified as essential tools in conducting thorough assessments. The paper also discusses the challenges associated with risk assessment in supply chains, emphasizing the need to address both visible and hidden risks. The findings underscore the importance of adopting advanced decision-making frameworks that integrate sustainability with risk assessment, thereby enhancing supply chain resilience and ensuring long-term corporate competitiveness.

关键词： Economics Employee welfare Supply chains Decision making Water conservation Complexity theory Risk management Sustainable development Systematic literature review Resilience

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Secure and Reliable 6G Communications with BCH-Based GLDPC and Kyber

Secure and Reliable 6G Communications with BCH-Based GLDPC a...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Linh Nguyen Cheol-Hong Min Hanho Lee Tuy Tan Nguyen School of Informatics Computing and Cyber Systems Northern Arizona University USA Department of Electrical. and Computer Engineering University of St. Thomas USA Department of Electrical and Computer Engineering Inha University Republic of Korea

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Channel coding in sixth-generation (6G) networks must attain exceptionally low bit error rate (BER), typically in the range of 10– 6 to 10– 9 , to ensure the requisite level of reliability. While fifth-generation (5G) New Radio (NR) coding techniques have made substantial progress, the inherent limitations of the low error floor impede the attainment of such stringent BER targets. Compared to the low-density parity check (LDPC) codes employed in 5G communications, generalized low-density parity check (GLDPC) codes offer a more advantageous tradeoff between computational complexity and error correction performance in 6G networks. GLDPC codes enhance traditional LDPC structures by incorporating more complex local decoding units within their check nodes. When coupled with cryptographic techniques, GLDPC codes can establish a robust information security framework. In this paper, we propose a new security-based GLDPC that uses a number of BCH matrices for the GLDPC decoding process combined with the Kyber algorithm (BCH-based KyGLDPC) before transmitting data to increase reli-ability and solve the security problem against quantum computer attacks. The system's performance is assessed using both image data and data encrypted prior to transmission in a white additive Gaussian noise environment. The results indicate that the system provides strong error correction and data security.

关键词： 6G mobile communication Quantum computing Computer network reliability System performance Bit error rate Parity check codes Error correction codes Decoding Reliability Channel coding

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach 7

Minimizing the Number of Stunting Prevalence Using the Eucli...

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7th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2023

作者： Zarlis, Muhammad Oktavia, Tanty Buaton, Relita Ernawan, Ferda Andrian, Kevin Bina Nusantara University Information System Management Department BINUS Graduate Program - Master of Information System Management Jakarta11480 Indonesia STMIK Kaputama Informatics Engineering Binjai20714 Indonesia Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan26600 Malaysia BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350360752

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city. © 2023 IEEE.

关键词： Classification (of information)

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Towards an Integrated Rat Llm Framework for Contextually Appropriate Complex Clinical Recommendations

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SSRN 2024年

作者： Mukalazi, Serugunda Henry Jianquan, Ouyang Namatovu, Hasifah K. Kimbugwe, Nasser Department of Networks China Department of Information Systems Department of Information Technology Uganda School of Computer Science Xiangtan University Hunan Province Xiangtan China School of Computing and Informatics Technology Makerere University Uganda Uganda

The coexistence of multiple chronic diseases, known as multimorbidity or complex chronic conditions, still poses a global challenge and contributes to a significant portion of worldwide deaths. Managing complex chronic diseases is challenging both for patients and healthcare providers, as patients are required to adhere to long-term treatments and monitor their ever-changing health status and potential adverse drug effects. Medical practitioners face difficulties due to a lack of integrated clinical guidelines, often resulting in patients receiving recommendations from disintegrated healthcare providers. This disintegration puts patients at risk of confusing and conflicting information, hence increasing their vulnerability to errors and adverse drug reactions. Given the complexity of managing complex chronic conditions, there is a need for innovative solutions that can be utilized and harnessed by healthcare practitioners and patients. Large language models (LLMs) such as ChatGPT, PaLM, LaMDA, Bing Chat, and Llama have emerged as powerful tools presenting new healthcare transformative opportunities with the potential to enhance clinical decision-making. Despite their promise, leveraging LLMs for contextually accurate clinical recommendations faces challenges such as a lack of domain-specific knowledge, lack of up-to-date information, and biases in training data, with limitations in representing low-income settings perspectives. This article proposes an Integrated Retrieval-Augmented and Tuned (RAT) LLM framework to enhance LLMs' ability to generate contextually accurate clinical recommendations. © 2024, The Authors. All rights reserved.

关键词： Decision making

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