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Self Sustainable Artificial Intelligence Systems (ICSSAS), International Conference on

作者： Ashish Govindrao Deshpande Ramakrishnan Raman Vipul Vekariya Nilamadhab Mishra Sundaram Arumugam C. Srinivasan Symbiosis Law School (SLS) Pune Symbiosis International (Deemed University) Pune Vimannagar Pune Maharashtra India Symbiosis Institute of Business Management Pune Symbiosis International (Deemed University) Pune Maharashtra India Faculty of Engineering and Technology Parul Institute of Engineering and Technology Parul University Vadodara Gujarat India School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh India Department of Electrical Engineering Navajo Technical University Crown point NM USA Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798350368413

ISBN: (纸本)9798350368420

Sustainable agriculture has significant challenges from sheet and rill erosion for effective techniques. A new way to accurately identify and classifier sheet and rill erosion in agricultural landscapes with the combination of cloud computing and Naïve Bayes. To differentiate between these erosion patterns work proposes a technique that uses ground truth data and high-resolution satellite images. The technique gets results by using the Naïve Bayes algorithm, which is famous for being simple and successful in classification problems. More efficient and accurate and advanced methods by conducting comprehensive experiments and validations. This technology takes use of the scalability and accessibility of cloud computing to conduct erosion risk assessments in real-time, providing agricultural stakeholders with valuable information to enhance soil conservation initiatives. It highlights the revolutionary power of new technology to improve agricultural land management methods and address environmental issues. Sustainable agricultural practices mitigate the adverse implications of soil erosion by offering exact detection and classification of erosion events, which lead to better informed decision-making.

关键词： Cloud computing Accuracy Decision making Soil Agriculture Bayes methods Satellite images Stakeholders Risk management Erosion

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Exploring the integration of multi criteria decision analysis in the clean energy biodiesels applications: A systematic review and gap analysis

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Engineering Applications of Artificial Intelligence 2024年 133卷

作者： Alamoodi, A.H. Garfan, Salem Al-Zuhairi, Omar Zaidan, B.B. Zaidan, A.A. Albahri, O.S. Y.Y. Ahmaro, Ibraheem Albahri, A.S. Yussof, Salman Magableh, Aws A. Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Malaysia Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan Perak Malaysia Applied Science Research Center Applied Science Private University Amman Jordan Low Dimensional Materials Research Centre Department of Physics Faculty of Science Universiti Malaya Kuala Lumpur50603 Malaysia SP Jain School of Global Management Lidcombe SydneyNSW2141 Australia International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Douliu Taiwan Victorian Institute of Technology Australia Computer Techniques Engineering Department Mazaya University College Nasiriyah Iraq Computer Science Department College of Information Technology Hebron University Hebron Palestine Technical College Imam Ja'afar Al-Sadiq University Baghdad Iraq Department of Information Systems Yarmouk University Irbid Jordan Baghdad Iraq Department of Computing College of Computing and Informatics Universiti Tenaga Nasional Malaysia Departments of Software Engineering Prince Sultan University Riyad Saudi Arabia

Biodiesel has gained tremendous attention from researchers due to its environmentally friendly and renewable fuel manufactured domestically from vegetable oils or animal fats. Multiple factors, including emission and fuel efficiency, measure the performance of biodiesel. These characteristics make the process of evaluation and benchmarking a multi-criteria decision-making (MCDM) problem. This research attempts to survey the literature for multi-criteria decision-making applications on biodiesel. This systematic review was carried out on four scientific databases: PubMed, scienceDirect, IEEE Xplore, and WoS. The collected articles were summarized and mapped into a coherent taxonomy, while the main challenges, motivations, and recommendations were collected and categorized for better understanding and finding out essential characteristics. The final set of included articles was 33, and they were categorized into six different categories. Most articles (n=15/33) investigated the evaluation and selection of biodiesel alternatives using MCDM. Furthermore, a state-of-art bibliometric analysis is provided. The analysis demonstrates several challenges in this area, such as source selection, optimum fuel blending, and uncertainty. This article is expected to assist future researchers in addressing the current gaps and contribute to advancing this area. © 2024 Elsevier Ltd

关键词： Biodiesel

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Technological Machines Diagnostics of Grain Processing Enterprises as the Object of Automation

Technological Machines Diagnostics of Grain Processing Enter...

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Automatics and Informatics (ICAI), International Conference

作者： Palvan I. Kalandarov Shakhnoza R. Ubaydullayeva Nikola N. Nikolov Aziz Hayitov Husen Sharifov Department “Automation and control of technology process in production” «Tashkent institute of irrigation and agricultural mechanization engineers» National Research University Tashkent Uzbekistan Department of Automation Faculty of Computer Science and Automation Technical University of Varna Varna Bulgaria Bukhara Institute of Natural Resource Management of the National Research University «Tashkent Institute of Irrigation and Agricultural Mechanization institute» Tashkent Uzbekistan

The article gives the basic concepts of reliability, performance, durability, considers the issues of changing the technical state of the machine during operation. The models under consideration have the ability to introduce various perturbations in order to simulate physical defects, and numerical simulation on a computer made it possible to obtain solutions in the form of temporary realizations of oscillations for different states of the simulation object. The cooperative use of the full-scale method and mathematical modeling made it possible to reduce the volume of full-scale experiments and apply statistical methods of analysis in the problem of classifying the technical condition by constructing mathematical models of the probability of failure and uptime during their operating time. The content of the main types of machine states is revealed, considerable attention is paid to the issues of identifying and influencing failures and the causes of failures in the machine, the reasons for the loss of performance during operation.

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Efficient Photocatalytic Degradation Towards Tetracycline Triggered by Z-Scheme Znsno3/Agi Composites: The Synergistic Effect of Oxygen Vacancies, Lewis Acid Sites, and Interfacial Chemical Bonds

SSRN

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SSRN 2024年

作者： Sun, Jing Chang, Ting Liu, Qian Wang, Zhuoyue Huo, Xiaoqi Li, Meifeng Wang, Yafeng Zhao, Zhilei Zhao, Xin Wang, TingXin Liu, Jue National&Local Joint Engineering Research Center of Metrology Instrument and System College of Quality and Technical Supervision Hebei University Baoding071002 China Department of Chemical and Materials Engineering University of Alberta EdmontonT6G2R3 Canada Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control Faculty of Environmental Science & Engineering Kunming University of Science &Technology Kunming650500 China

Chemically bonded Z-scheme ZnSnO3/AgI composites rich in oxygen vacancies (OVs) and Lewis acid sites were prepared successfully and showed excellent photocatalytic activities. Especially, ZnAg-2 degraded 96.1% tetracycline under visible light irradiation for 15 min. OVs contributed to Lewis acid sites production and interfacial chemical bonds formation through weakening the metal-O bonding. Lewis acid sites favored the adsorption of electron-rich tetracycline. Interfacial chemical bonds together with Z-scheme structure accelerated electron transfer and retained the high redox ability of ZnSnO3 and AgI. OVs contributed to singlet oxygen (1O2) production through facilitating the energy transfer from triplet exciton to O2. ZnSnO3/AgI composites realized efficient removal towards tetracycline after five consecutive cycles utilization as well as in different environmental conditions and water matrices, showing practical application potential. Based on ROSs generation and photoreduction experiment, the photocatalytic mechanism of the ZnAg composites was proposed. Possible degradation pathway was deduced according to the detected main degradation intermediates. The biological toxicity in solution was reduced after tetracycline degradation. This work highlights the significant roles of OVs, Lewis acid sites, and chemical bonding in improving the photocatalytic activity of Z-scheme composites and provides new insight into designing high efficient photocatalysts for visible light induced organic pollutants removal. © 2024, The Authors. All rights reserved.

关键词： Zinc compounds

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Adaptive Non-Maximum Suppression to Improve Performance of Rumex Detection

SSRN

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SSRN 2022年

作者： Al-Badri, Ahmed Husham Ismail, Nor Azman Al-Dulaimi, Khamael Salman, Ghalib Ahmed Salam, Md Sah Bin Haji Al-Sabaawi, Aiman School of Computing Faculty of Engineering Universiti Teknologi Malaysia Johor Bahru Malaysia Computer Science Department College of Science Al-Nahrain University Baghdad Iraq School of Electrical Engineering and Robotics Queensland University of Technology BrisbaneQLD4000 Australia Department of Computer Science Middle Technical University Baghdad Iraq School of Computer Science Queensland University of Technology BrisbaneQLD4000 Australia

Weed detection methods based on Region-Convolutional Neural Network (R-CNN) frameworks still suffer from a lack of detection rate due to overlapping and occlusion leaves issues. This paper presents an Ensemble-Region Convolutional Neural Networks (E-RCNN) model of three state-of-the-art networks to detect Rumex obtusifolius L. ( R. obtu .) weeds under various condition especially overlapping. The proposed E-RCNN model is used due to its novelty of using ensemble classifiers with the combination of three extractors at its backbone. The Adaptive Non-Maximum Suppression (ANMS) is proposed with the Region Proposal Network (RPN) to enhance the detection performance of overlapping and occluded objects by overcoming the drawbacks of the conventional Non-Maximum Suppression (NMS). Three main stages are proposed as a framework to achieve the classification and detection goals, including pre-processing stage, classification stage, and detection stage. A hybrid model of three CNN extractor networks is used as the backbone in the classification stage. Thus, integrating three networks into one robust model increases the recognition capability by extracting additional useful features more efficiently than those from an individual network. For detection, RPN is used to generate multi-proposed boxes, whereas ANMS is used to select the best box that has a high score rate to match the target object. Our proposed model has trained and tested two standard benchmarking datasets of Rumex weeds under real-world data. The proposed model tested each dataset separately to evaluate the detection rate in terms of Intersection over Union (IoU). To evaluate the detection rate, AlexNet, Single-Shot Detector (SSD), DetectNet and Faster R-CNN with conventional NMS models are used to compare the results. The evaluation performances of AlexNet, SSD, DetectNet, and Faster R-CNN on the IoU metric are 0.81, 0.83, 0.84, and 0.88, respectively. The proposed model achieves the highest score in localization

关键词： Convolutional neural networks

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Imaging dynamic water invasion behavior in microfractures based on microfluidics

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Journal of Central South University 2022年第12期29卷 3986-4001页

作者： ZHANG Ji-cheng CHEN Shao-jie JI Song-tao FENG Fan ALEKSEY A.Khoreshok ZAKI M.Mohammed College of Energy and Mining Engineering Shandong University of Science and TechnologyQingdao 266590China School of Civil Engineering The University of QueenslandBrisbane 4067Australia State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and TechnologyHuainan 232001China College of Mining Engineering T.F.Gorbachev Kuzbass State Technical UniversityKemerovo 65000Russia Faculty of Engineering Mining and Petroleum Engineering DepartmentAzhar UniversityCairo 11884Egypt

Fluid invasion through fractures is frequently observed in subsurface engineering. To elucidate the microkinetic behavior of fracture fluids, the microfracture structure of coal from the Surat Basin was reconstructed using a 3D morphometric system and stitching algorithm, then the transparent models characterizing the fracture structure were produced using microfluidics, and water invasion in the microfracture model was measured via visualization experiments under various conditions. High flow rate facilitated the invasion of the water phase into the closed channel, improving the efficiency of water invasion in the neutral wetting system. Wettability reversal changed the dominant channel for water invasion in the hydrophobic system. The invasion efficiency in closed and small aperture bypass channels was *** reduction of effective seepage channels led to the fastest breakthrough time. Higher surface tension and interfacial curvature promoted the hysteresis effect. The reduction of effective seepage channels led to the fastest breakthrough time. The larger surface tension and interfacial curvature make the hysteresis effect more significant. These results will enable a better understanding of the rock-gas-liquid multiphase interaction mechanisms under unsaturated conditions of rocks.

关键词： microfracture visualized models microfluidics phase distribution capillary hysteresis

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Hardware-in-the-Loop Simulation of Vehicle-Manipulator Systems for Physical Interaction Tasks

Hardware-in-the-Loop Simulation of Vehicle-Manipulator Syste...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Hemjyoti Das Bjørn Kåre Sæbø Kristin Y. Pettersen Christian Ott Faculty of Electrical Engineering and Information Technology Automation and Control Institute (ACIN) Technical University of Vienna TU Wien Vienna Austria Department of Engineering Cybernetics Centre for Autonomous Marine Operations and Systems (NTNU AMOS) NTNU Norwegian University of Science and Technology Trondheim Norway German Aerospace Center Institute of Robotics and Mechatronics Wessling Germany

Hardware-in-the-loop simulation (HILS) allows a more realistic evaluation of control approaches than what is possible with pure software simulations, but without the actual complexity of the complete system. This is important for some complex systems such as orbital robots, where testing of the system is typically not possible after its launch, and an on-ground replica is used to validate the performance of such a system. In this article, an impedance-matching approach is presented to match the end-effector dynamics of a fixed-base robot manipulator with that of a target vehicle-manipulator system (VMS), while taking into account the redundant nullspace dynamics in a connected real-time simulation framework. This approach ensures that the forces and torques exerted by the system on the environment matches with that of the simulated system. The contact wrenches used in our approach are not obtained from numerical simulations, but rather from real physical interaction, which is one of the main advantages of our approach. The effectiveness of our method is validated by demonstrating various physical interaction tasks with the environment, using a suspended aerial manipulator as the target system.

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Airborne pathogen monitoring and dispersion modelling on passenger ships: A review

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science of the Total Environment 2025年 980卷 179571页

作者： Kumar, Prashant Hama, Sarkawt Cheung, Ho Yin Wickson Hadjichristodoulou, Christos Mouchtouri, Varvara A. Anagnostopoulos, Lemonia Kourentis, Leonidas Wang, Zhaozhi Galea, Edwin R. Ewer, John Grandison, Angus Jia, Fuchen Siilin, Niko School of Engineering Civil and Environmental Engineering Faculty of Engineering and Physical Sciences University of Surrey GuildfordGU2 7XH United Kingdom Institute for Sustainability University of Surrey Surrey GuildfordGU2 7XH United Kingdom Laboratory of Hygiene and Epidemiology Faculty of Medicine University of Thessaly Larissa41222 Greece Fire Safety Engineering Group School of Computing and Mathematical Sciences Faculty of Engineering and Science University of Greenwich GreenwichSE10 9LS United Kingdom VTT Technical Research Centre of Finland Ltd Espoo02150 Finland Aalto University Department of Civil Engineering Espoo00076 Finland

The COVID-19 pandemic demonstrated a profound inability of pre-pandemic passenger ship policies implemented by both ship operators and governmental authorities to detect and address newly emerging diseases. The essentiality of maritime transport puts into focus the risk of approach to address known and new emerging airborne infectious diseases that, due to increasing capacity, are likely to occur on passenger ships. In order to enhance the passenger experience, prepare shipping for pandemics like COVID-19, and improve the resilience and safety of the industry, this review critically synthesises existing literature on (1) monitoring ventilation conditions and aerosol dispersion, linking them to airborne transmission risk using airborne aerosols and ventilation performance as input parameters for computational fluid dynamics (CFD) simulations, and (2) modelling airborne disease transmission risk in controlled passenger ship environments. This review analysed 39 studies on aerosol monitoring, thermal comfort, and infection risk modelling on passenger ships (2000−2023). Additionally, 55 papers on CFD modelling of airborne pathogen dispersion were reviewed: 22 included validation, with most focused on built environments and only four specifically addressing ship environments. Two major challenges relate to the complexity and poorly characterised ventilation boundary conditions on passenger ships, and the other is the lack of suitable validation data. For this reason, ship experimental studies are required for CFD model validation. Only a handful of studies were found that have measured aerosol concentrations on board passenger ships. To the best of our knowledge, there have been no studies conducted on aerosol mass or airborne transmission sampling on board passenger ships or other types of vessels. The results of this review have the potential to create synergistic connections between experimental and modelling studies to inform, characterise and improve the development

关键词： Risk assessment

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Trust-Based Blockchain for Improving Supply Chain Communication in Internet of Vehicles

Trust-Based Blockchain for Improving Supply Chain Communicat...

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Interdisciplinary Humanitarian Conference for Sustainability (IIHC), International

作者： H. Shaheen MohanRaj A Meesala Shobha Rani Sreeraj S M Amutha S. Kannadhasan Faculty of Computing and Engineering UWL-RAK UAE Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore India Department of Computer Science and Engineering MVJ College of Engineering Bangalore India Department of Computer Science and Engineering Sri Krishna College of Engineering and Technology Coimbatore India Department of Computer Science and Engineering Hindusthan College of Engineering Technical Campus Coimbatore India Department of Electronics and Communication Engineering Study World Collge of Engineering Coimbatore

The motto behind the keenness of urban areas has become unmistakable in current cities because of the rise of installed and associated shrewd gadgets, frameworks, and innovations. It is possible to connect every object to the Internet. As a result, in the impending Internet of Things era, the “Internet of Vehicles-IoV” will play a critical role in newly developed dazzling urban communities. The IoV can possibly address different traffic and street wellbeing issues successfully to forestall deadly crashes. In any case, a specific test of IoV, particularly in “Vehicle-to-Vehicle” as well as “Vehicle-to-Infrastructure” communications, guarantees quick, in order to transmit securely and exact performance of the information. The above effort is modifying Blockchain innovation for continuous application called RTA to meet “Vehicle-to-Every thing-V2x” communications problems in order to overcome these challenges. As a result, the main goal of the study is to develop a Blockchain-based IoT framework for establishing communication security and creating a completely decentralized computing platform. Research methodology used here is divided into two major sections. In the part 1 presented below, authors discuss the traceability and optimization over Merkle trees. The second section deals with implementing an actual blockchain with our optimized Merkle tree as the underlying technology to represent a distributed trust based ledger.

关键词： Technological innovation Large Hadron Collider Vehicle-to-infrastructure Urban areas Supply chains Vehicular ad hoc networks Blockchains

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Integrating Deep Learning in Project Management: Improving Efficiency and Effectiveness in Project Planning and Execution

Integrating Deep Learning in Project Management: Improving E...

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Innovation in Technology (ASIANCON), Asian Conference on

作者： Sunil Shukla Jagendra Singh Hemant Sahu Shilpa Kanthalia Taufikin Muniyandy Elangovan School of Computing Graphic Era Hill University Dehradun India School of Computer Science Engineering & Technology Bennett University Greater Noida India Department of CS & IT Janardan Rai Nagar Rajasthan Vidyapeeth (Deemed to be University) Udaipur India Faculty of Management Studies Janardan Rai Nagar Rajasthan Vidyapeeth (Deemed to be University) Udaipur India Department of Postgraduate State Islamic Institute (IAIN) Kudus Kudus Indonesia Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (数字)9798350354218

ISBN: (纸本)9798350354225

The purpose of this research is to explore the use of deep learning technologies, namely the K-Nearest Neighbors model within the textile manufacturing process to test the improvement of the said process. To properly implement the model, we must use real-time data from the process and evaluate the improvement depending on a number of factors: how much does the maintenance cost decrease, how accurate is the inventory management, and how well the program forecasts demand, all of which should lead to an improvement of profit. First, the analysis of the results proved that the implementation of KNN model leads to a significant decrease of maintenance costs: while without the model the reduction was 15%, with it cost maintenance cost a 25% decrease. Second, the usage of a model improves inventory management accuracy: before the use of KNN, it was 85%, while after it rose to 95%. Third, demand forecasting becomes more accurate, as the difference was 75% to the positive without the model and 90% with it. The use of a model improved all aspects, and the most improved was profit: before the implementation of the KNN model, profit was 10%, and it was 40% after, which led to the conclusion that the implementation of deep learning models, namely the KNN model, improves the effectiveness of textile manufacturing process and positively affects the profitability and the production process as a whole.

关键词： Deep learning Analytical models Costs Accuracy Manufacturing processes Production Nearest neighbor methods Predictive models Maintenance Textiles

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