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Revolutionizing Road Safety and Optimization with AI: Insights from Enterprise Implementation

International Journal of Advanced Computer science and Applications 2025年第4期16卷 1008-1019页

作者： Ouahbi, Younesse Ziti, Soumia Intelligent Processing and Security of Systems Informatics Department Faculty of Science Mohammed V University Rabat Morocco

This study explores the key factors influencing the adoption of artificial intelligence (AI) in the logistics sector, with a particular emphasis on road logistics management. It examines the technological, organizational, and environmental contexts that shape AI integration, as well as the challenges faced by logistics managers, including the need for digital transformation, carbon emissions reduction, and advanced parcel tracking management. The objective is to identify technological and human-related barriers to AI adoption and to assess the level of interest and readiness among logistics companies, especially in the Moroccan context. A quantitative research approach was adopted, based on an online survey targeting logistics professionals and decision-makers, mainly from European and Moroccan small and medium-sized enterprises (SMEs). The collected data were analyzed using statistical methods, including linear regression and ANOVA, to evaluate the relationships between company characteristics, perceived complexity of AI tools, and the availability of qualified human resources. The findings indicate that perceived complexity and limited access to specialized skills significantly hinder AI adoption. Moreover, the perception of tangible performance benefits—such as increased operational efficiency and reduced CO2 emissions—emerges as a major driver for acceptance. These insights offer practical implications for logistics companies seeking to leverage AI technologies to optimize operations, reduce environmental impact, and enhance parcel tracking systems. A strategic roadmap is proposed to overcome the identified barriers and promote effective AI integration. © (2025), (science and Information Organization). All rights reserved.

关键词： Risk perception

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NW Logistics: System Architecture and Design for Sustainable Road Logistics

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International Journal of Advanced Computer science and Applications 2025年第4期16卷 1096-1104页

作者： Younesse, Ouahbi Soumia, Ziti Intelligent Processing and Security of Systems-Informatics Department-Faculty of Science Mohammed V University Rabat Morocco

The logistics industry is under increasing pressure to reduce carbon emissions and enhance efficiency in response to environmental and regulatory demands. However, optimizing road logistics to achieve these goals requires innovative solutions that balance operational efficiency with sustain-ability. This study addresses this need by introducing NW Logistics, an AI powered platform that optimizes road logistics to lower CO2 emissions and improve fleet performance. In order to achieve these objectives, real-time CO2 tracking, route optimization, and driver behavior monitoring were integrated into NW Logistics. The system enables precise, real-time tracking of deliveries and vehicle locations, allowing logistics managers to monitor fleet performance with enhanced accuracy. Additionally, onboard cam eras and sensors generate individualized driver reports, tracking infractions and fostering safer driving behaviors. Initial simula tions of NW Logistics indicate a significant reduction in carbon emissions, along with improvements in route efficiency, delivery tracking ac-curacy, and driver safety. These results demonstrate the transformative potential of AI to advance sustainable and efficient logistics management. © (2025), (science and Information Organization). All Rights Reserved.

关键词： Supply chain management

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The Role of Generative AI in Deepfake Detection: A Systematic Literature Review

The Role of Generative AI in Deepfake Detection: A Systemati...

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International Conference on Smart Business and technology, ICSBT 2024

作者： Acim, Btissam Kharmoum, Nassim Lagmiri, Souad Najoua Ziti, Soumia Department of Computer Science Intelligent Processing & Security of Systems Faculty of Sciences Mohammed V University in Rabat Rabat Morocco Rabat Morocco IT Networking Security and Management Laboratory Higher Institute of Management Administration and Computer Engineering Rabat Morocco

ISBN: (纸本)9783031866975

There is a possibility that deepfakes will increase a great deal of false information in a very realistic way, but it seems that today such technology appears to be extremely dangerous. While generative Artificial Intelligence (AI) does expand possibilities and give an opportunity to achieve terrific outcomes and has innumerable potential uses. This systematic literature review focuses on the role of generative AI in the improvement of deepfake detection technologies, providing a comparison between different methods and assessing their effectiveness. By analyzing recent studies, it depicts the techniques employed most frequently in deepfake detection, such as the ones concentrating on the intricacies between the visual and auditory elements, the temporal domains, as well as any minor signs of alteration. Due to the fact that generative AI is rapidly improving, the methods that are used to detect its use are often inadequate, which calls for more studies on the subject matter. Besides, by combining audio and visual elements when performing the analysis, calling it as a method that can be useful in focusing the detection growth potential with diverse and unstructured data. Also, this study evaluates the advantages and limitations of the techniques existing today and demonstrates their relative effectiveness in controlled and real conditions. Clarifying that measures aimed at detecting AI generated content should be preoccupied with a technique that is able to keep pace with changes in generative AI. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Generative adversarial networks

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Data Migration from Relational to NoSQL Database: Review and Comparative Study

Data Migration from Relational to NoSQL Database: Review a...

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International Conference on Advanced intelligent systems for Sustainable Development, AI2SD 2022

作者： Saadouni, Chaimae El Bouchti, Karim Reda, Oussama Mohamed Ziti, Soumia Department of Computer Science Intelligent Processing Systems and Security Team Mohammed V University Rabat Morocco Algorithms Networks Intelligent Systems and Software Engineering Research Team Faculty of Sciences Mohammed V University Rabat Morocco

ISBN: (纸本)9783031263835

New storage requirements, analysis, and visualization of Big Data, which includes structured, semi-structured, and unstructured data, have caused the developers in the past decade to begin preferring Big Data databases, such as NoSQL, that comes to overcome the boundaries of relational Databases such as unlimited scalability, high performance, data modeling, data distribution, and continuous availability. Due to those benefits ensured by this new technology, quite recently, considerable attention has been paid to data migration from relational Database to NoSQL Database. So, in this context, the purpose of this paper is to provide a comparative study of some recent approaches proposed by various researchers to migrate data from relational to NoSQL databases, as well as discussing and analyzing the results of those proposed techniques. This research allowed us to gain a basic understanding of the contributions and approaches that have already been made, as well as the benefits and limits of each proposal. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Artificial Intelligence for Fake News 1

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International Conference on Advanced intelligent systems for Sustainable Development, AI2SD 2022

作者： Ennejjai, Imane Ariss, Anass Kharmoum, Nassim Rhalem, Wajih Ziti, Soumia Ezziyyani, Mostafa Department of Computer Science Intelligent Processing Systems and Security Team Faculty of Sciences Mohammed V University in Rabat Rabat Morocco Rabat Morocco E2SN Research Team ENSAM Rabat Mohammed V University in Rabat Rabat Morocco Mathematics and Applications Laboratory Faculty of Sciences and Techniques of Tangier Abdelmalek Essaadi University Tetouan Morocco

ISBN: (数字)9783031263842

ISBN: (纸本)9783031263835

Fake news is a severe problem on social media networks, with confirmed detrimental consequences for individuals and organizations. As a result, detecting false news is a significant difficulty. In this way, the topic of new fakes and their proper detection are crucial. General knowledge states that the receiver of information must verify the sources. However, the creation of new information can be a difficult problem that requires more than a single viewpoint based on a news source. The objective of this paper is to evaluate the performance of six deep learning models for fake news detection including CNN, LSTM, Bi-LSTM, HAN, Conv-Han and Bert. We find that BERT and similar pre-trained models perform the best for fake news detection, the models are described below with their experimental *** models are examined against ISOT [22, 30] datasets. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Long short-term memory

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Tracking Methods: Comprehensive Vision and Multiple Approaches 1

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International Conference on Advanced intelligent systems for Sustainable Development, AI2SD 2022

作者： Ariss, Anass Ennejjai, Imane Kharmoum, Nassim Rhalem, Wajih Ziti, Soumia Ezziyyani, Mostafa Department of Computer Science Intelligent Processing Systems and Security Team Faculty of Sciences Mohammed V University in Rabat Rabat Morocco Rabat Morocco E2SN Research Team ENSAM Rabat Mohammed V University in Rabat Rabat Morocco Mathematics and Applications Laboratory Faculty of Sciences and Techniques of Tangier Abdelmalek Essaadi University Tétouan Morocco

ISBN: (数字)9783031352515

ISBN: (纸本)9783031352508

Tracking of human beings, as well as objects, becomes a great challenge currently presented, it aims to understand the fundamental principles of objects and human beings detected to associate them with robust systems for treaties and draw the desired conclusions. Tracking generally uses several methods such as graph theory, technological tools, Internet of Things (IoT), Big Data, and artificial intelligence, where it maintains several hypotheses to help tracking objects or human beings. In this article, we propose the tracking methods proposed in this direction, and finally, we analyze and discuss the various results obtained. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graph theory

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IoT-Enabled Smart Greenhouse for Robotic Enhancement of Tomato Production: Leveraging 5G and Edge Computing for Advanced Data-Driven Automation, Precision Irrigation, and Scalable Zoning Principles

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2024年第21期18卷 88-116页

作者： Ariss, Anass Ennejjai, Imane Lamjid, Asmaa Mabrouki, Jamal Kharmoum, Nassim Ziti, Soumia Department of Computer Science Intelligent Processing Systems & Security Team Faculty of Sciences Mohammed V University in Rabat Rabat Morocco Laboratory of Spectroscopy Molecular Modeling Materials Nanomaterial Water and Environment CERNE2D Faculty of Science Mohammed V University in Rabat Rabat Morocco

There are many difficulties in growing tomatoes, such as erratic weather patterns, variable yields, and short shelf lives. Tomatoes are a staple food that is grown all throughout the world, particularly in climate-friendly areas such as Morocco. These areas are not free from the difficulties that present major obstacles for farmers, though. Modern agricultural techniques are increasingly using cutting-edge technologies, such as Internet of Things (IoT)-enabled smart greenhouses, to address these problems. In order to improve tomato output, this study presents an enhanced smart greenhouse model that incorporates the zoning principle. The method provides optimal plant growth and resource efficiency by separating the greenhouse into various zones, each tailored for specific growth stages and environmental circumstances. Precision farming and sustainable practices are made possible by the suggested systems real-time monitoring and control, which integrates sensors, actuators, and data analytics. The automatic irrigation system of the intelligent greenhouse prototype is additionally set up to offer the best possible support for the growth of tomato plants. The functionality and efficacy of the prototype are investigated through extensive laboratory testing and experimentation, providing insight into its potential influence on agricultural practices and practical practicality. The greenhouse that has been created with the help of IoT capabilities and the zoning concept has proven to be an effective instrument in assisting farmers in their attempts to grow tomatoes in an efficient and sustainable manner. Our comprehensive testing yielded data that demonstrate the zoning principle-integrated IoT-enabled smart greenhouse greatly improves tomato quality and production. This system demonstrates the benefits and practical applicability of sophisticated data-driven automation in agriculture by providing a scalable and sustainable solution to the problems encountered by tomato pr

关键词： Fruits

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Towards a Disciplined Methodology to Generate the E-Business Information System Models from the Business Value Model 2nd

Towards a Disciplined Methodology to Generate the E-Business...

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2nd International Conference on Advanced intelligent systems for Sustainable Development, AI2SD 2019

作者： Kharmoum, Nassim Ziti, Soumia Omary, Fouzia Department of Computer Science Intelligent Processing Systems and Security Team Faculty of Sciences Mohammed V University in Rabat Rabat Morocco

ISBN: (纸本)9783030366704

Nowadays, the software industry has known significant growth, while the end-users have become very demanding. In this sense, many approaches have appeared among them we have the Model Driven Architecture (MDA) approach, which is initiative of the Object Management Group (OMG), considering the model as the central entity in the software systems development process. Our contribution in this paper is to suggest the idea of a new disciplined methodology based on the MDA approach to generate the whole of E-business Information System (IS) models from the business value model automatically. The purpose is to facilitate and automate the development process of any E-business IS, passing from a level of abstraction to another of the software development life cycle, via the transformation models key. © Springer Nature Switzerland AG 2020.

关键词： Software design

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A Novel Automatic Transformation Method from the Business Value Model to the UML Use Case Diagram 1

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2nd International Conference on Advanced intelligent systems for Sustainable Development, AI2SD 2019

作者： Kharmoum, Nassim Retal, Sara Ziti, Soumia Omary, Fouzia Department of Computer Science Intelligent Processing Systems & Security Team Faculty of Sciences Mohammed V University in Rabat Rabat Morocco

ISBN: (数字)9783030366711

ISBN: (纸本)9783030366704

Currently, in the field of the software engineering industry, end-users have become extremely requiring;consequently, this industry knew a critical evolution. In this vein, the model generation becomes an awakening and an essential step for many approaches among them we cite the Model Driven Architecture (MDA) approach. The Object Management Group (OMG), the founder of the MDA approach, proposes three different abstraction levels;which are the higher level, average level, and lower level. Until now, most research deal with the transformation at the average and the lowest MDA levels, while ignoring the higher level, which precisely contains the requirements’ models. Therefore, our aim in this paper is to construct a sound and more consistent higher MDA level for e-business information systems by automatically generating a higher level of functional requirements model from the Business Value model. Our source Business Value model is represented by the E3value model, whereas the UML Use Case diagram expresses the generated model. The transformation is performed automatically using ATLAS Transformation Language (ATL). © Springer Nature Switzerland AG 2020.

关键词： Software design

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Enhancing Bioactivity and Corrosion Resistance of Laser Powder Bed-Fused Ti6al4v Using Titania-Reinforced Hydroxyapatite Nanocomposite Coatings Through Electrophoretic Deposition

SSRN

引用

SSRN 2024年

作者： Sohrabpoor, Hamed Salarvand, V. Torabpour, M. Yazdi, M. Saghafi Asadi, P. Brabazon, Dermot Stein, B.D. Raghavendra, R. Department of Intelligent Systems Engineering Luddy School of Informatics Computing and Engineering Indiana University Bloomington BloomingtonIN United States Department of Materials Science and Engineering Imam Khomeini International University Qazvin Iran Department of Mechanical Engineering Engineering Faculty Gebze Technical University Kocaeli Gebze41400 Turkey I-Form Advanced Manufacturing Research Centre & Advanced Processing Technology Research Centre School of Mechanical & Manufacturing Engineering Dublin City University Dublin Ireland Electron Microscopy Center Department of Biology Indiana University BloomingtonIN United States SEAM Research Center South East Technological University Ireland

Hydroxyapatite (HA) coatings are commonly used on titanium alloy substrates for orthopedic and dental implants because of their excellent osteoconductivity and biocompatibility. The disparity in the coefficient of thermal expansion (CTE) between the coating and substrate can result in the formation of cracks in the HA coatings during the coating process. This study examined the effect of titania (TiO2) nanoparticle additions in HA coatings to enhance their properties and prevent cracking. Using electrophoretic deposition (EPD), HA and HA-TiO2 composite coatings were applied to laser powder bed fused Ti6Al4V substrates. Optimal EPD conditions of 45 volts and 120 s were identified to produce consistent, crack-free coatings. Increasing the TiO2 nanoparticle concentration (≥50 wt.%) decreased the coatings' CTE, mitigating cooling-induced cracking. The microstructural analysis confirmed the uniform distribution of HA and TiO2 in the coatings. X-ray diffraction and Fourier-transform infrared spectroscopy data revealed that the HA structure remained intact even with the addition of TiO2. Higher TiO2 reduced the average surface roughness, with the HA-40%TiO2 coating exhibiting the lowest roughness (approximately 50 nm). Electrochemical tests corroborated the surface roughness findings. Incorporating TiO2 into the HA coatings decreased the thermal expansion coefficient, reducing tensile stresses. © 2024, The Authors. All rights reserved.

关键词： Titanium dioxide

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