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10th International Conference on Optimization and Applications, ICOA 2024

作者： Sadraoui, Youssef Er-Ratby, Mohamed Kadiri, Moulay Saddik Kobi, Abdessamad National School of Applied Sciences Sultan Moulay Slimane University LIPIM Laboratory of Process Engineering Computer Science and Mathematics Khouribga Morocco National School of Applied Sciences Sultan Moulay Slimane University LASTI Laboratory of Science and Engineering Techniques Khouribga Morocco Polytech Angers University of Angers LARIS Angevin Laboratory for Systems Engineering Research France

ISBN: (纸本)9798350387353

The studied process is a grinding and hydroclassification unit designed to ensure that the grain size it processes is in line with the specifications for the pipe's transport mode. Obstacles to the unit's operational process include frequent stops, plant's low reliability, product delivery with an inappropriate grain size, and a lack of control over operating parameters. These factors have a significant impact on the unit's relevance and, consequently, its performance. We created a quality culture among operators with '0 grain quality loss' through the implementation of the quality and processes control study, which was essential to improve the situation. Thus, by completing the seven project stages, we were able to enhance and optimize the grinding and hydroclassification unit's overall performance and capability to regulate the grain size quality. We noticed a notable improvement in regulating the several parameters that affect the targeted particle size after we established tools for unit quality control, such as control and monitoring charts, reaction matrices, intervention flow charts and operational standards. The unit has seen a great deal of satisfaction from the project in terms of quality, process control and resources optimization. Moreover, the incorporation of preventive maintenance into this process has shown to be crucial in guaranteeing the reliability and durability of the installation, thereby substantially improving the unit's overall efficiency. © 2024 IEEE.

关键词： Preventive maintenance

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Enhancing Crime Scene Investigations Through Virtual Reality and Deep Learning Techniques 3

Enhancing Crime Scene Investigations Through Virtual Reality...

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3rd IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2024

作者： Zappalà, Antonino Guarnera, Luca Rinaldi, Vincenzo Livatino, Salvatore Battiato, Sebastiano University of Catania Department of Mathematics and Computer Science Catania Italy Leverhulme Research Centre for Forensic Science School of Science and Engineering University of Dundee Dundee United Kingdom School of Physics Engineering and Computer Science University of Hertfordshire Hatfield United Kingdom

ISBN: (纸本)9798350378009

The analysis of a crime scene is a pivotal activity in forensic investigations. Crime Scene Investigators and forensic science practitioners rely on best practices, standard operating procedures, and critical thinking, to produce rigorous scientific reports to document the scenes of interest and meet the quality standards expected in the courts. However, crime scene examination is a complex and multifaceted task often performed in environments susceptible to deterioration, contamination, and alteration, despite the use of contact-free and non -destructive methods of analysis. In this context, the documentation of the sites, and the identification and isolation of traces of evidential value remain challenging endeavours. In this paper, we propose a photogrammetric reconstruction of the crime scene for inspection in virtual reality (VR) and focus on fully automatic object recognition with deep learning (DL) algorithms through a client-server architecture. A pre-trained Faster-R CNN model was chosen as the best method that can best categorize relevant objects at the scene, selected by experts in the VR environment. These operations can considerably improve and accelerate crime scene analysis and help the forensic expert in extracting measurements and analysing in detail the objects under analysis. Experimental results on a simulated crime scene have shown that the proposed method can be effective in finding and recognizing objects with potential evidentiary value, enabling timely analyses of crime scenes, particularly those with health and safety risks (e.g. fires, explosions, chemicals, etc.), while minimizing subjective bias and contamination of the scene. © 2024 IEEE.

关键词： Forensic science

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An Energy-Efficient Optimal Routing Model for Mobile Ad Hoc Network Using Mine Blast Algorithm

An Energy-Efficient Optimal Routing Model for Mobile Ad Hoc ...

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2023 International Conference in Advances in Power, Signal, and Information Technology, APSIT 2023

作者： Goswami, Subhrananda Mondal, Sukumar Johardar, Subhankar Das, Chandan Bikash Research Centre of Natural and Applied Sciences Raja Narendra Lal Khan Women's College Department of Computer Science India Raja Narendra Lal Khan Women's College Department of Mathematics India Haldia Institute of Technology Department of Computer Science India Tamralipta Mahavidyalaya Department of Mathematics India

ISBN: (纸本)9798350339369

The collection of wireless mobile nodes dynamically in a temporary network is termed a Mobile Ad Hoc Network (MANET). Here, energy consumption is an important complication in MANET because the mobile node doesn't offer a permanent power supply to the network, and they highly depend on batteries. The lifetime of the batteries is exhausted quickly as the nodes are traveled and change their positions frequently in the MANET network. The key factor for MANET is efficient energy to improve the network lifetime. Moreover, the efficacies of MANET are increased by different criteria like residual energy and link stability, which are always required to optimize. The major goal of multi-objective optimization issues is to reduce the energy consumption rate and also enhance the lifetime of the network. Based on the battery-dependent nodes, the efficacy of MANET is reduced. So, it is more need to select multiple optimal node disjoint paths among the destination and source to transfer the data. Further, multi-objective functions are utilized to choose the optimal path that offers the optimum outcome regarding traffic load, hop and energy consumption. So, efficient routing protocols for energy efficiency improvement in MANET are developed by utilizing the Mine Blast Algorithm (MBA). All the sensor nodes of the MANET are taken for experimentation purposes. The shortest paths in the MANET model are optimized by implementing the MBA. The parameters optimized by MBA are link cost, path loss, consumption of energy, an energy that is still available in the battery, throughput, packet energy cost, end-to-delay, routing overhead ratio, and packet delivery ratio to evaluate the overall efficiency of the network. Parametric studies of the proposed MBA are done. The developed energy-efficient MBA-MANET systems are compared with various existing techniques to verify the improved energy efficiency of the developed MBA-MANET model. © 2023 IEEE.

关键词： Sensor nodes

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Analysis of Feature Parameters and Their Time-Transition for Shockable Arrhythmia and Prediction of the Effect of Electrical Defibrillation 3

Analysis of Feature Parameters and Their Time-Transition for...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Noguchi, Shunta Yoshikawa, Yuta Okai, Takayuki Oya, Hidetoshi Rahman, Md. Masudur Yoshida, Minoru Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Tokyo City University Department of Computer Science Tokyo Japan Noakhali Science and Technology University Department of Information and Communication Engineering Bangladesh Kanagawa University Department of Applied Systems and Mathematics Kanagawa Japan

ISBN: (纸本)9798331540319

In this paper, we propose a prediction system of the effect of electrical defibrillation. In order to develop the proposed system, we firstly analyze from pre-shock (immediately before defibrillation) ECGs (ElectroCardioGrams) by using Gabor Wavelet Transform, Poincaré plot analysis, Spectral entropy, and feature parameters are extracted by those extracted analysis results, we focus on time-transition feature parameter. Next, effective feature parameters are selected based on χ2 -test. Finally, 'Effective' and 'Ineffective' for electrical defibrillation are classified by using SVM (Support Vector Machine) with three kernels (Linear, Gaussian, and Polynomial) and regularization. In this way, we shows the effectiveness of the proposed feature extraction methods and prediction system. © 2024 IEEE.

关键词： Support vector machines

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A spatiotemporal datamining approach for road profile estimation using low-cost device 26

A spatiotemporal datamining approach for road profile estima...

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26th International Conference on Knowledge-Based and Intelligent Information and engineering Systems, KES 2022

作者： Taktak, Mariem Triki, Slim Higher Institute of Applied Sciences and Technologies of Sousse Department of Computer Science and Applied Mathematics Sousse Tunisia National Engineering School of Sfax Tunisia

In this paper, we address the problem of the spatiotemporal data mining in the field of the road conditions estimation. We demonstrate that road condition estimation can be defined as a problem of dynamic discovering of different classes of road profile during training phase. We focus on the road profile classification from time series data collected by a low-cost inertial sensor embedded into smartphone devices. Data used in this work are composed of three datasets which treat real asphalt pavement problems. The first, called Asphalt-obstacle, address the identification problem of obstacles in the pavement where data are collected. The second, called Asphalt pavement-type, aims at identifying three types of pavements namely flexible pavement, cobblestone street and dirt roads. The third and final dataset, called Asphalt pavement-regularity, treat the pavement quality effect on the driver comfortability. In order to estimate the road conditions, we conduct an evaluation of four spatiotemporal algorithms which combine concepts from machine learning and data-driven. With uniform parameters setting and on-line implementation property, we find that Markov spatiotemporal dynamic model achieve the best average classification accuracy of 90.5% ± 0.01 in 4-class Asphalt obstacles, 84% ± 0.006 in 3-class Asphalt pavement-type and 94.9%±0.005 in 2-class Asphalt pavement-regularity. © 2022 The Authors. Published by Elsevier B.V.

关键词： Smartphones

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Optimization of Quality Process Control and Preventive Maintenance Strategy: A Case Study

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Operations research Forum 2024年第4期5卷 84页

作者： Sadraoui, Youssef Er-ratby, Mohamed Kadiri, Moulay Saddik Kobi, Abdessamad Laboratory of Process Engineering Computer Science and Mathematics LIPIM National School of Applied Sciences of Khouribga Sultan Moulay Slimane University Beni Mellal Morocco Laboratory of Science and Engineering Techniques LaSTI National School of Applied Sciences of Khouribga Sultan Moulay Slimane University Beni Mellal Morocco LARIS Angevin Laboratory for Systems Engineering Research Polytech Angers University of Angers Angers France

The studied process concerns a wet grinding and cycloning unit, set up to ensure that the particle size it processes complies with the requirements in terms of pipe transport mode. Frequent shutdowns, low reliability, the risk of delivering a product with inappropriate particle size, and the lack of operational parameters’ control are all obstacles for the unit, having enormous repercussions on its relevance and performance. To improve this situation, the implementation of an innovative 5-month quality and process control study has proven crucial to establish a culture of quality among operators, aiming to achieve the targeted grain size. However, the innovative aspects of our approach lie in its thoroughness and inclusiveness since it addresses the process both qualitatively and quantitatively, focusing not only on theoretically modeling and simulating the grinding circuit but also providing an integrated method to address every component of the unit. By going through the seven stages of this study, we were able to enhance the overall performance of the unit controlling the particle size at the output. After establishing a set of quality control tools, we observed a remarkable development in mastering various parameters influencing the targeted particle size. The benefits generated by the study are extremely satisfying for the unit at different levels, particularly in terms of quality, process control, and resource optimization. Furthermore, the integration of maintenance management into the process has proven essential to ensure the reliability and sustainability of the installation, thereby contributing significantly to the overall efficiency of the unit. Graphical Abstract: (Figure presented.) © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Optimization Preventive maintenance Process capability Quality Statistical process control SPC Wet grinding

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Analyzing the impact of conversation structure on predicting persuasive comments online

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Journal of Ambient Intelligence and Humanized Computing 2024年第11期15卷 3719-3732页

作者： Capuano, Nicola Meyer, Marco Nota, Francesco David Department of Information Engineering Electrical Engineering and Applied Mathematics University of Salerno Via Giovanni Paolo II 132 Fisciano84084 Italy Faculty of Humanities University of Hamburg Mittelweg 177 Hamburg20148 Germany Center for Higher Defence Studies Defence Analysis and Research Institute Piazza della Rovere 83 Rome00165 Italy

The topic of persuasion in online conversations has social, political and security implications;as a consequence, the problem of predicting persuasive comments in online discussions is receiving increasing attention in the literature. Following recent advancements in graph neural networks, we analyze the impact of conversation structure in predicting persuasive comments in online discussions. We evaluate the performance of artificial intelligence models receiving as input graphs constructed on the top of online conversations sourced from the "Change My View" Reddit channel. We experiment with different graph architectures and compare the performance on graph neural networks, as structure-based models, and dense neural networks as baseline models. Experiments are conducted on two tasks: (1) persuasive comment detection, aiming to predict which comments are persuasive, and (2) influence prediction, aiming to predict which users are persuasive. The experimental results show that the role of the conversation structure in predicting persuasiveness is strongly dependent on its graph representation given as input to the graph neural network. In particular, a graph structure linking only comments belonging to the same speaker in the conversation achieves the best performance in both tasks. This structure outperforms both the baseline model, which does not consider any structural information, and structures linking different speakers’ comments with each other. Specifically, the F1 score of the best performing model is 0.58, which represents an improvement of 5.45% over the baseline model (F1 score of 0.55) and 7.41% over the model linking different speakers’ comments (F1 score of 0.54). © The Author(s) 2024.

关键词： Prediction models

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Comparative Analysis of Machine Learning Algorithms for Email Phishing Detection Using TF-IDF, Word2Vec, and BERT

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computers, Materials & Continua 2024年第11期81卷 3395-3412页

作者： Arar Al Tawil Laiali Almazaydeh Doaa Qawasmeh Baraah Qawasmeh Mohammad Alshinwan Khaled Elleithy Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan College of Engineering Abu Dhabi UniversityAbu DhabiAl AinP.O.Box 1790United Arab Emirates Faculty of Artificial Intelligence Al-Balqa Applied UniversitySalt19117Jordan Department of Civil and Construction Engineering Western Michigan UniversityKalamazooMI 49008USA MEU Research Unit Middle East UniversityAmman11831Jordan Department of Computer Science and Engineering University of BridgeportBridgeportCT 06604USA

Cybercriminals often use fraudulent emails and fictitious email accounts to deceive individuals into disclosing confidential information,a practice known as *** study utilizes three distinct methodologies,Term Frequency-Inverse Document Frequency,Word2Vec,and Bidirectional Encoder Representations from Transform-ers,to evaluate the effectiveness of various machine learning algorithms in detecting phishing *** study uses feature extraction methods to assess the performance of Logistic Regression,Decision Tree,Random Forest,and Multilayer Perceptron *** best results for each classifier using Term Frequency-Inverse Document Frequency were Multilayer Perceptron(Precision:0.98,Recall:0.98,F1-score:0.98,Accuracy:0.98).Word2Vec’s best results were Multilayer Perceptron(Precision:0.98,Recall:0.98,F1-score:0.98,Accuracy:0.98).The highest performance was achieved using the Bidirectional Encoder Representations from the Transformers model,with Precision,Recall,F1-score,and Accuracy all reaching *** study highlights how advanced pre-trained models,such as Bidirectional Encoder Representations from Transformers,can significantly enhance the accuracy and reliability of fraud detection systems.

关键词： Attacks email phishing machine learning security representations from transformers(BERT) text classifeir natural language processing(NLP)

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Hydrocephalic cerebrospinal fluid flowing rotationally with pulsatile boundaries:A mathematical simulation of the thermodynamical approach

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Theoretical & applied Mechanics Letters 2023年第1期13卷 79-86页

作者： Hemalatha Balasundaram Senthamilselvi Sathyamoorthi Unai Fernandez-Gamiz Samad Noeiaghdam Shyam Sundar Santra Department of Mathematics VISTASVels UniversityZamin PallavaramChennaiTamilnadu Nuclear Engineering and Fluid Mechanics Department University of the Basque Country UPV/EHUNieves Cano 1201006Vitoria-GasteizSpain Industrial Mathematics Laboratory Baikal School of BRICSIrkutsk National Research Technical UniversityIrkutsk664074Russia Department of Applied Mathematics and Programming South Ural State UniversityLenin prospect 76Chelyabinsk454080Russia Department of Mathematics Applied Science ClusterUniversity of Petroleum and Energy StudiesDehradunUttarakhand248007India Department of Mathematics JIS College of EngineeringKalyaniWest Bengal 741235India

To study the kinematics of flow rate and ventricular dilatation,an analytical perturbation approach of hydrocephalus has been *** research provides a comprehensive investigation of the characteristics of cerebrospinal fluid(CSF)flow and pressure in a hydrocephalic *** influence of hydrocephalic CSF,flowing rotationally with realistic dynamical characteristics on pulsatile boundaries of subarachnoid space,was demonstrated using a nonlinear controlling system of *** analytical perturbation method of hydrocephalus has been developed to investigate the biomechanics of fluid flow rate and the ventricular *** this paper presents a detailed analysis of CSF flow and pressure dynamics in a hydrocephalic *** was elaborated with a nonlinear governing model of CSF to show the influence of hydrocephalic CSF,flowing rotationally with realistic dynamical behaviors on pulsatile boundaries of subarachnoid *** accordance with the suggested model,the elasticity factor changes depending on how much a porous layer,in this case the brain parenchyma,is *** was improved to include the relaxation of internal mechanical stresses for various perturbation orders,modelling the potential plasticity of brain *** initial geometry that was utilised to create the framework of CSF with pathological disease hydrocephalus and indeed the output of simulations using this model were compared to the actual progression of ventricular dimensions and shapes in *** to this observation,the non-linear and elastic mechanical phenomena incorporated into the current model are probably *** modelling of ventricular dilation at a normal pressure may benefit from the existence of a valid model whose parameters approximate genuine mechanical characteristics of the cerebral cortex.

关键词： Brain parenchyma Cerebrospinal fluid Hydrocephalus Ventricular elasticity Intracranial pressure differences

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An Integrated Bipolar Picture Fuzzy Decision Driven System to Scrutinize Food Waste Treatment Technology through Assorted Factor Analysis

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computer Modeling in engineering & Sciences 2024年第9期140卷 2665-2687页

作者： Navaneethakrishnan Suganthi Keerthana Devi Samayan Narayanamoorthy Thirumalai Nallasivan Parthasarathy Chakkarapani Sumathi Thilagasree Dragan Pamucar Vladimir Simic Hasan Dinçer Serhat Yüksel Department of Mathematics Bharathiar UniversityCoimbatore641046India Department of Mathematics Sri Ramakrishna Mission Vidyalaya College of Arts and ScienceCoimbatore641020India Department of Operations Research and Statistics Faculty of Organizational SciencesUniversity of BelgradeBelgrade11000Serbia College of Engineering Department of Industrial Engineering and ManagementYuan Ze UniversityTaoyuan City320315TaiwanChina Faculty of Transport and Traffic Engineering University of BelgradeVojvode Stepe 305Belgrade11000Serbia Department of Computer Science and Engineering College of InformaticsKorea UniversitySeoul02841Republic of Korea School of Business Istanbul Medipol UniversityIstanbul34083Turkey Department of Economics and Management Khazar UniversityBakuAzerbaijan

Food Waste(FW)is a pressing environmental concern that affects every country *** one-third of the food that is produced ends up as waste,contributing to the carbon ***,the FW must be properly treated to reduce environmental *** study evaluates a few available Food Waste Treatment(FWT)technologies,such as anaerobic digestion,composting,landfill,and incineration,which are widely used.A Bipolar Picture Fuzzy Set(BPFS)is proposed to deal with the ambiguity and uncertainty that arise when converting a real-world problem to a mathematical model.A novel Criteria Importance Through Intercriteria Correlation-Stable Preference Ordering Towards Ideal Solution(CRITIC-SPOTIS)approach is developed to objectively analyze FWT selection based on thirteen criteria covering the industry’s technical,environmental,and entrepreneurial *** CRITIC method is used for the objective analysis of the importance of each criterion in FWT *** SPOTIS method is adopted to rank the alternative hassle-free,following the *** proposed model offers a rank reversal-free model,i.e.,the rank of the alternatives remains unaffected even after the addition or removal of an *** addition,comparative and sensitivity analyses are performed to ensure the reliability and robustness of the proposed model and to validate the proposed result.

关键词： Fuzzy food waste treatment selection bipolar picture fuzzy set and decision-making

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