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innovative Research in Applied science, Engineering and Technology (iRAsET),Conference on

作者： Wissal Nahairy Omar Bouattane Abdellah Zamma Naoual Belouaggadia Laboratory of Modeling and Simulation of Intelligent Industrial Systems (M2S2I) ENSET University Hassan II of Casablanca Morocco Laboratory of Electrical Engineering and Intelligent Systems (IESI) ENSET University Hassan II of Casablanca Morocco Builders Lab Builders École d’ingénieurs COMUE Normandie Université Epron France

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Artificial intelligence (Ai) is a fast-growing technology that has enormous potential to transform many industries, including building energy management. Phase change materials in buildings, which regulate temperature by absorbing or releasing heat during changes in state, can be optimized by Ai to improve their efficiency and environmental impact. This study presents the results of a bibliometric analysis of 244 research articles on the integration of artificial intelligence in phase-change materials, from the scopus database. The analysis was carried out to identify current trends in research in this area, the most studied topics, the most productive authors and the most active countries. The R studio and VOsviewer tools were used to analyze the publications on the use of artificial intelligence in the optimization of phase change materials and its impact on the thermal management of buildings. This bibliometric analysis makes it possible to visualize the links between publications, keywords, authors and countries, and to identify the main research themes, as well as the most influential authors and sources in this field.

关键词： Phase change materials Technological innovation Databases Bibliometrics Thermal management market research Thermal analysis Artificial intelligence Optimization Building management systems

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Comparative analysis of the thermomechanical properties of soft PVC used in the automotive industry and bio-composite: A sustainable alternative

Comparative analysis of the thermomechanical properties of s...

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innovative Research in Applied science, Engineering and Technology (iRAsET),Conference on

作者： Hamza Ennadafy mustapha Jammoukh Naoual Belouaggadia Hassan II University of Casablanca Laboratory: Signals Distributed Systems and Artificial Intelligence (SSDIA) Casablanca MOROCCO Hassan II University of Casablanca Laboratory: Modeling and Simulation of Intelligent Industrial Systems (M2S2I) Casablanca MOROCCO

The automotive industry is highly impacted by technological advances, especially in the field of materials science and their impact on the environment. most of the materials used in the automotive industry are of fossil source, such as PVC. Our research project aims to reduce the use of fossil materials in the automotive industry by using bio loade. Our study will compare the thermomechanical properties of soft PVC and a PVC bio-composite, and evaluate the environmental impact of PVC. Our results indicate that the bio-composite, composed of 90% soft PVC and 10% biomaterials, outperforms the soft PVC traditionally used in the automotive industry in terms of thermomechanical performance. in addition, the use of bio-composite can help reduce the environmental impact of the automotive industry.

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Ai-Optimized Genetic Algorithm for Enhancing Resource Recovery in the Circular Economy

AI-Optimized Genetic Algorithm for Enhancing Resource Recove...

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innovative Research in Applied science, Engineering and Technology (iRAsET),Conference on

作者： Abderrahman mansouri Bellat Abdelouahad idriss Bennis Ali siadat Fatiha Akef Modeling and Simulation of Intelligent Industrial Systems Laboratory (M2S2I) ENSET Mohammedia Hassan II University Casablanca Morocco Laboratory of Design Manufacturing and Control Arts et Metiers ParisTech Metz France Laboratory of Mechanical and Thermal Processes and Control (PCMT) ENSAM Rabat Mohammed V University in Rabat Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

This paper presents a Genetic Algorithm (GA)- based optimization approach aimed at improving circular economy strategies by optimizing recyclability and economic value, while minimizing disassembly complexity and environmental impact. A multi-objective function is established, incorporating essential parameters such recyclability rate, component reuse value, disassembly expenses, carbon footprint, and waste minimization. The GA investigates an optimal balance between sustainability and economic viability using an evolutionary search method that identifies and enhances solutions throughout several generations. The dataset comprises 50 components of end-of-life products, categorized as metals (40%), plastics (30%), and electronic materials (30%), exhibiting recyclability rates between 35% and 95%. The results indicate that the GA attains a 25% enhancement in recyclability, a 30% reduction in disassembly complexity, and a 20% decrease in carbon footprint relative to traditional approaches. The suggested method offers a versatile and scalable decision-making instrument for manufacturers, recyclers, and policymakers, enhancing a more sustainable resource recovery system.

关键词： systematics instruments Computational modeling search methods Decision making Complexity theory sustainable development Optimization Carbon footprint Genetic algorithms

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Towards a new data transmission model for smart farms

Towards a new data transmission model for smart farms

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innovative Research in Applied science, Engineering and Technology (iRAsET),Conference on

作者： Afaf Bounajra Kamal El Guemmat Khalifa mansouri Laboratory of Modelling and Simulation of Intelligent Industrial Systems (M2S2I) Ecole Normale Supérieure de l’Enseignement Technique (ENSET) Mohammedia Morocco Laboratory of Informatique Artificial Intelligence and Cyber Security (2IACS) Ecole Normale Supérieure de l’Enseignement Technique (ENSET) Mohammedia Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

in today's world, smart farming has become a necessity in the light of climate change and demographic evolution. With the emergence of the term smart Farm, this goal has become increasingly achievable. The use of the internet of Things and artificial intelligence technologies has enabled great strides to be made with promising results in terms of increasing productivity while minimizing the use of natural resources. in this context, a number of studies have taken advantage of new technologies to propose intelligent irrigation scheduling systems, but taking into consideration only soil water properties as a basis of their research. A recently published study has shown that good agricultural management must take into account the climatic, physical, chemical, biological and hydrological properties of a crop field, and has shown that the detection of each property is possible through the use of new technologies. Based on this research, in this article we have proposed a new conceptual model for data transmission in a smart farm. The proposed model combines the use of internet of Things technologies, artificial intelligence and intelligent agents to enable holistic, real-time, sustainable and efficient farm management. The results found in this article have also helped to shed light on several lines of research and thus open the way for further studies.

关键词： smart agriculture Biological system modeling Real-time systems Data models Data communication internet of Things intelligent agents Artificial intelligence Water resources Climate change

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Effect of glycerol content on the thermal properties of a whey protein isolate biodegradable film for food packaging purposes

Effect of glycerol content on the thermal properties of a wh...

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innovative Research in Applied science, Engineering and Technology (iRAsET),Conference on

作者： Goudali Lina Akkouri Nacer Latifa Elfarissi mustapha Jammoukh Abdellah Zamma Laboratory: Modeling and Simulation of Intelligent Industrial Systems (M2S2I) Higher Normal School of Technical Education of Mohammedia Hassan II University of Casablanca Casablanca Morocco R&D Department Technical Center for Plastics and Rubber (CTPC) Complex of Moroccan Industrial Technical Centers Casablanca Morocco

A wide part of scientific research in the food-packaging sector has shown interesting challenges in assuring food shelf-life extension. Conventional plastic is mostly used for food packaging, hence has major environmental drawbacks by being non-degradable and accumulating over the years due to its elimination process. Biodegradable food packaging polymers have contributed to overcoming these challenges and diverted from the environmental concern. in the light of the sustainable development goals, implementing green technology in current industries help secure the consumer's safety by minimizing food loss and reducing plastic waste, thus attaining environmental sustainability. Whey protein isolate (WPi) has been considerably investigated lately and used in packaging formulation for its functional properties. This work aims to produce a biopolymer film destined for food packaging based on the crosslinking of whey protein isolate using glycerol as a plasticizer. The thermal properties of the film samples were investigated. Other aspects of the WPi biopolymer can be studied for other potential uses, more additives can be added to develop further properties depending on the final use of the film. The developed polymer can potentially be used in the food packaging industry under various conservation conditions.

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modeling CO2 Emissions in morocco: A support Vector Regression Approach

Modeling CO2 Emissions in Morocco: A Support Vector Regressi...

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innovative Research in Applied science, Engineering and Technology (iRAsET),Conference on

作者： Dani Yassine Jammoukh mustapha Belouaggadia Naoual Ennadafy Hamza Modeling and Simulation of Intelligent Industrial Systems laboratory (M2S2I) École Normale Supérieure de l'Enseignement Technique de Mohammedia Hassan II University Casablanca Morrocco University of Hassan II Casablanca Centre Technique de plasturgie et de caoutchouc (CTPC) Casablanca Morocco Signals Distributed Systems and Artificial Intelligence laboratory (SSDIA) École Normale Supérieure de l'Enseignement Technique de Mohammedia Hassan II University Casablanca Morrocco

ISBN: (数字)9798350309508

ISBN: (纸本)9798350309515

This research employs support Vector Regression (sVR) to analyze CO2 emissions in morocco, incorporating a dataset spanning 1965 to 2021 and featuring energy consumption, GDP, industrial production, population and urbanization—categorized as economical, demographical, and energetical factors. The sVR model, optimized via Grid search, predicts emissions accurately, yielding an R-squared of 0.99, msE of 0.04, and mAE of 0.19. With 80% of data allocated to training, the model aligns effectively with historical trends, demonstrating proficiency in predicting emissions beyond 2010. The study's implications for policy, industry, and sustainability underscore the importance of renewable energy and sustainable practices in morocco's environmental goals. These findings not only highlight the critical role of mL models in CO2 prediction but also offer actionable insights for informed decision-making and environmental management.

关键词： support vector machines Training Renewable energy sources solid modeling Urban areas Production Predictive models

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innovative whey protein isolate-based biopolymer film with glycerol for sustainable food packaging applications

Hybrid Advances

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Hybrid Advances 2025年

作者： Lina Goudali Naoual Belouaggadia Basha shaik Nagoor Abdellah Zamma Latifa Elfarissi Modeling and Simulation of Intelligent Industrial Systems laboratory (M2S2I) of ENSET Mohammedia Hassan II University Casablanca - MOROCCO Centre Technique de Plasturgie et de Caoutchouc (CTPC) Sidi Maarouf Casablanca – MOROCCO Unité de recherche « Builders Lab » ComUE NE Builders Ecole d’ingénieurs Campus de Caen Epron France Department of Mining and Petroleum Faculty of Engineering Chulalongkorn University Bangkok 10330 Thailand

The food packaging industry faces significant challenges in extending the shelf life of products while addressing the environmental concerns associated with traditional plastic use. Conventional plastics, although effective in food preservation, are non-degradable and contribute to long-term pollution, including microplastics entering the food chain. While biodegradable alternatives have been explored, many biobased polymers suffer from limitations in their mechanical and thermal properties, restricting their practical application in food packaging. This study addresses this gap by developing an innovative, eco-friendly whey protein isolate (WPi)-based biopolymer film, crosslinked with glycerol as a plasticizing agent. The incorporation of glycerol significantly enhances the film’s thermal stability, making it suitable for food packaging applications under varying storage conditions. The developed WPi film combines biodegradability with improved food preservation capabilities, offering a promising alternative to conventional plastics. This research contributes to the development of functional biobased films and supports the need for sustainable packaging solutions that reduce plastic waste and mitigate environmental harm. it provides a significant contribution to biopolymer development for food packaging, paving the way for future innovations in sustainable packaging materials.

关键词： sustainability whey protein isolate (WPi) films biodegradable food packaging glycerol plasticizer thermal stability sustainable materials

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