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An Optimized Algorithm for Renewable Energy Forecasting Based on Machine Learning

Intelligent Automation & Soft Computing 2023年第1期35卷 755-767页

作者： Ziad M.Ali Ahmed M.Galal Salem Alkhalaf Imran Khan College of Engineering at Wadi Addawaser Prince Sattam bin Abdulaziz UniversityWadi Aldawaser11991Saudi Arabia Electrical Engineering Department Aswan Faculty of EngineeringAswan UniversityAswan81542Egypt Production Engineering and Mechanical Design Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer College of Science and Arts in Ar RassQassim UniversityAr RassSaudi Arabia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan

The large-scale application of renewable energy power generation technology brings new challenges to the operation of traditional power grids andenergy management on the load side. Microgrid can effectively solve this problemby using its regulation and flexibility, and is considered to be an ideal *** traditional method of computing total transfer capability is difficult due tothe central integration of wind farms. As a result, the differential evolutionextreme learning machine is offered as a data mining approach for extractingoperating rules for the total transfer capability of tie-lines in wind-integratedpower systems. K-medoids clustering under the two-dimensional “wind power-load consumption” feature space is used to define representative operational scenarios initially. Then, using stochastic sampling and repetitive power flow, aknowledge base for total transfer capability operating rule mining is ***, a novel method is used to filter redundant characteristics and find featuresthat are closely associated to the total transfer capability in order to decrease theultra-high dimensionality of operational features. Finally, by feeding the trainingdata into the proposed algorithm, the total transfer capability operation rules arederived from the knowledge base. It can be seen that, the proposed algorithmcan optimize the system performance with good accuracy and generality, according to numerical data.

关键词： Load forecasting distribution network machine learning renewable energy

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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Computer Modeling in engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize Computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Effect of Tensile Loading on the Residual Stress Relaxation Behavior of Induction Hardened SCM440 Steel with a Shallow Hardened Layer

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ISIJ International 2025年第2期65卷 308-314页

作者： Aoki, Tomofumi Hayama, Motoaki Takesue, Shogo Ezura, Atsushi Tsukahara, Masahiro Misaka, Yoshitaka Kikuchi, Shoichi Komotori, Jun School of Integrated Design Engineering Graduate School of Science and Technology Keio University 3-14-1 Hiyoshi Yokohama Kohoku-ku Kanagawa223-8522 Japan Department of Mechanical Engineering Faculty of Science and Technology Keio University 3-14-1 Hiyoshi Yokohama Kohoku-ku Kanagawa223-8522 Japan Department of Mechanical Engineering Kyoto Institute of Technology Matsugasakigoshokaido-cho Sakyo-ku Kyoto Kyoto606-8585 Japan Faculty of Engineering Sanjo City University 5002-5 Kamisugoro Sanjo Niigata955-0091 Japan Neturen Co. Ltd 7-4-10 Tamura Kanagawa Hiratsuka245-0013 Japan Department of Mechanical Engineering Faculty of Engineering Shizuoka University 3-5-1 Johoku Chuo-ku Shizuoka Hamamatsu432-8561 Japan

Fatigue tests under axial loading were conducted on steel with a shallow hardened layer induced by induction hardening, and in situ X-ray stress measurements were performed to investigate the relaxation of residual stresses during fatigue. The residual stresses were relaxed owing to tensile loading and not compressive loading. The two conditions that bring about this phenomenon are (i) a high peak of tensile residual stress just below the hardened layer, and (ii) the hardened layer coinciding with the compressive residual stress field that prevents the yielding of the compressive residual stress field under compressive loading. In this case, tensile yielding occurred just below the hardened layer under tensile loading, the residual stresses are redistributed, and the compressive residual stress on the material surface is relaxed. The experimental results also showed that the fatigue fracture morphology changed depending on the residual stress relaxation behavior. © 2025 The Iron and Steel Institute of Japan.

关键词： Stress relaxation

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Layer-7 and 5-Tuple Information Analysis Framework for Providing Positional Flexibility In Location Determination for Service Provision 49

Layer-7 and 5-Tuple Information Analysis Framework for Provi...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Sato, Yuri Namba, Yohei Nishi, Hiroaki Graduate School of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku Yokohama Kanagawa223-8522 Japan Keio University Faculty of Science and Technology Department of System Design Kanagawa223-8522 Japan

ISBN: (纸本)9798350331820

In a smart community, which is an initiative to create an efficient regional society by leveraging information and communications technology (ICT), various data exchanges and data processing are performed. Owing to the demand for network transparency in data processing, packet rewriting is required at network edges. In the packet rewriting process, packets need to be analyzed after obtaining the necessary permissions. A conventional method for packet analysis is using a 5-tuple. While this method can analyze packets by a service user, it cannot analyze packets by a service. Moreover, service provision needs to take place at the appropriate locations with respect to the privacy level, and service provision locations need to be flexible enough to change even subsequent to the commencement of services. To address this issue, there is a need to enable positional flexibility in determining the location for service provision between the data source and cloud. In this study, assuming that the permission to analyze packets had been obtained within the smart community, we implemented a framework that could analyze not only 5-tuple but also layer-7 (L7) information and rewrite packet contents based on the analysis results. The process performed at the edge first analyzed the header of the incoming packet to determine whether the packet was subject to L7 information analysis. If the packet was subject to analysis, the L7 information was analyzed to determine whether the packet was subject to rewriting. A packet subject to rewriting were rewritten and forwarded accordingly. For this series of packet process, we used the Data Plane Development Kit (DPDK), a tool that could speed up packet processing. The framework was applied to the anonymization process, and the delay due to the anonymization process was 0.195 ms. With this framework, it is possible to achieve the packet content rewriting process at any point between the IoT device and the cloud by modifying the location of the

关键词： Location

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Studying of an Adaptive Unscented Kalman Filter as a Target Tracking Algorithm with Matlab Simulation 2

Studying of an Adaptive Unscented Kalman Filter as a Target ...

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2nd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and Computer engineering, MI-STA 2022

作者： Ammar, Abdussalam Masaud Ellafi, Amira Youssef Bozed, Kenz Amhmed Zerek, Amer R. Faculty of Electronic Technology Tripoli Libya Benghazi University Faculty of Information Technology Department of Computer System Design Libya Zawia University Faculty of Engineering EE Department Zawia Libya

ISBN: (数字)9781665479189

ISBN: (纸本)9781665479189

The radar is considered as one of tracking application which we need to tracking unknown targets. This application is using a kalman filter. Also the extended and unscented kalman filter has been created to deal with nonlinear systems such as multidimensional radar tracking. If wideband radar is used, multiple return signals may be obtained by scattering on a single target in a single pulse. It is important to monitor multiple dispersions on an undefined number of artifacts in the specific problem considered, with a standard wideband radar model, whose motion involves a nonlinear rotational velocity component. The measurements used are scattered range, range-rate (in analogy to Doppler), nonlinear functions of the scattered position and velocity, with parameters in the state-space model. In order to evaluate the scene and observe its progression over time, the tracker design uses a Kalman Filter type to model the nonlinear dynamics and measurement items and a multi-pronged association scheme. © 2022 IEEE.

关键词： Mean square error

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Evaluation of various properties of ribbons of Mg-9%Al-3%Ca-based anode material for magnesium batteries produced by single-roll rapid solidification

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Keikinzoku/Journal of Japan Institute of Light Metals 2024年第10期74卷 455-462页

作者： Kirimoto, Yuichi Tsukeda, Tadayoshi Aida, Tetsuo Tabata, Hironobu Kurihara, Hideki Suzuki, Mayumi Haga, Toshio Department of Nano and Functional Material Science Graduate School of Science and Engineering for Education University of Toyama 3190 Gofuku Toyama-shi Toyama930-8555 Japan Faculty of Sustainable Design Academic Assembly University of Toyama Toyama-shi Toyama Japan Chuetsu Metal Works Co. Ltd. Nakaniikawa-gun Toyama Japan Saitama Industrial Technology Center Kawaguchi-shi Saitama Japan Department of Mechanical Systems Engineering Faculty of Engineering Toyama Prefectural University Imizu-shi Toyama Japan Department of Mechanical Engineering Osaka Institute of Technology Osaka-shi Osaka Japan

There is an urgent need to develop next-generation rechargeable batteries for a carbon-neutral society. In this context, our research team is focusing on magnesium, which is abundant in the earth's crust and inexpensive. Ribbons of Mg-9%Al-3%Ca, a magnesium alloy, were prepared as anode material for rechargeable batteries by a single-roll rapid solidification method. The fabricated ribbons were subjected to various manufacturing conditions, and various properties such as surface properties, microstructure, mechanical properties, and electrochemical activity of the fabricated ribbons were evaluated. As a result, it was found that a peripheral speed of 25 m/s and an injection pressure of 0.05 MPa or less were desirable to fabricate ribbons with good surface and mechanical properties. It was also confirmed that electrochemical activity contributes significantly to the orientation of magnesium and that production conditions with a peripheral velocity of 30 m/s or higher resulted in low electrochemical activity. © 2024 The Japan Institute of Light Metals.

关键词： Magnesium alloys

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Propose a Recommender system to Dynamically Align Higher Education Curriculums With 4IR Market Needs

Propose a Recommender System to Dynamically Align Higher Edu...

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2023 International Conference on IT Innovation and Knowledge Discovery, ITIKD 2023

作者： Hasan, Zainab Baskaran, Subhashini S. Bahrain Polytechnic Faculty of Engineering Design and Ict Manama Bahrain College of Information Technology Ahlia University Multimedia Science Department Manama Bahrain

ISBN: (纸本)9781665463720

The Fourth Industrial Revolution (4IR) era leads to significant economic shifts due to technological advancement. The changes introduced by 4IR raise concern about its impact on employment due to jobs automation, or lack of workforce equipped with the required skills. It is essential to reshape the curriculums according to 4IR requirements to mitigate unemployment risks. The objective of this paper is to automatically identify the rapidly changing 4IR jobs skills and identify the gap between curriculums and modern industry jobs as well. In addition, the proposed solution has the capability of delivering efficient gap analysis recommendations that could be used in the curriculum enhancement decision-making process. The proposed recommender system clusters jobs based on K-Means and TF-IDF algorithms and then identifies the similarity and dissimilarity by utilizing the Cosine Similarity algorithm. The solution utilizes the algorithm's result to construct gap analysis recommendations that curriculum developers can use to align curriculums with 4IR requirements. The results of the classification report indicated that the system was effectively capable of clustering jobs based on skills similarity and identifying the 4IR gap. © 2023 IEEE.

关键词： Recommender systems

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Practical k-Anonymization Approach for Multiple Faces in Photographs 50

Practical k-Anonymization Approach for Multiple Faces in Pho...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Takusagawa, Takeshi Nishi, Hiroaki Graduate School of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku Kanagawa Yokohama223-8522 Japan Department of System Design Faculty of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku Kanagawa Yokohama223-8522 Japan

ISBN: (纸本)9781665464543

Recently, the increased utilization of data has led to the development of various services. However, using data necessitates anonymization techniques for privacy. multi-input k-anonymizer unit (MIKU)[1], a facial image anonymization method proposed by Nakamura et al., anonymizes images by averaging the latent vectors of facial images in the latent space of StyleGAN[2]. However, MIKU has two limitations: (1) it only targets single-face images, and (2) it merely calculates the centroid of the latent vectors between the original images, thus not preserving the statistical information of the original image dataset. Therefore, this paper proposes a framework to realize a k-anonymization method for photos containing multiple faces. The anonymization process uses a proposed framework comprising multiple modified artificial intelligence applications. First, identifiers, quasi-identifiers, and sensitive attributes are specified for a photo with multiple faces. This paper proposes three methods for generalizing age, one of the quasi-identifiers. The first is the random method, which replaces the age of the original image with the age of a random individual. The second is the uniform distribution method, which assigns ages based on the uniform distribution of age ranges after anonymization. The third is a kernel method that assigns ages using random numbers obtained from a probability density function computed by kernel density estimation. The experiments resulted in an Fréchet inception distance (FID)[2] equivalent to MIKU without any observed difference for the specified sensitive attributes. Furthermore, the most effective results were obtained using the kernel method, indicating that the proposed method is effective for the k-anonymization of facial images. © 2024 IEEE.

关键词： Anonymity

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Development of self-cleaning and antibacterial properties on cotton fabric using silver nanoparticles and PFOTS

SPE Polymers

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SPE Polymers 2024年第4期5卷 568-575页

作者： Khan, Mahnoor Saeed, Muhammad Adnan Ullah, Sultan Repon, Md. Reazuddin Pranta, Arnob Dhar Yunusov, Nurzod Hossain, Md Monir Centre of Excellence in Solid State Physics University of the Punjab Lahore Pakistan Department of Mechanical Engineering Gazi University Ankara Turkey Department of Mechanical Engineering Faculty of Mechanical Engineering and Design Kaunas University of Technology Kaunas Lithuania Department of Textile Engineering Daffodil International University Dhaka Bangladesh Department of Bioproducts and Biosystems School of Chemical Engineering Aalto University Espoo Finland Department of Production Engineering Faculty of Mechanical Engineering and Design Kaunas University of Technology Kaunas Lithuania ZR Research Institute for Advanced Materials Sherpur Bangladesh Department of Textile Engineering Mawlana Bhashani Science and Technology University Tangail Bangladesh Department of Technological Education Fergana State University Fergana Uzbekistan Department of Wet Process Engineering Textile Engineering College Noakhali Bangladesh

The demand for superhydrophobic fabric with self-cleaning and antibacterial features as potential practical applications has been rising steadily with the passage of time. In this research work, the wet chemical method is used to manufacture cotton with a superhydrophobic coating. Thus, Nanoparticles of silver were produced by using an in situ method. Afterward, the fabric is treated with a solution of perfluorooctyltriethoxysilane to make it superhydrophobic. The cotton fabric performs remarkably with exceptional hydrophobicity as it had a contact angle of 157 ± 1° and less than 10° in sliding angle. Water droplet's dynamic behavior is also studied so that the superhydrophobic fabric development can be proven. The fabric shows excellent chemical durability by performing chemical tests. The antimicrobial and self-cleaning properties are greatly enhanced by the superhydrophobic coating on cotton. Particle density on the superhydrophobic cotton before and after self-cleaning was found 5.1 and 0.4 mg/cm². In addition, the treated cotton fabric also exhibited superior antibacterial properties against Escherichia coli bacteria. Therefore, the developed multifunctional cotton fabric can be used in real-life applications. Highlights: Cotton fabric enables to repelling of dirt, oil, and water-based stains more effectively. Silver nanoparticles possess potent antibacterial properties. Incorporation of PFOTS controls the release of silver into the environment. Versatile applications from healthcare and hospitality to outdoor and athletic apparel. © 2024 The Author(s). SPE Polymers published by Wiley Periodicals LLC on behalf of Society of Plastics Engineers.

关键词： in situ method medical applications multifunctional properties nanoparticles superhydrophobic

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Operations planning in outpatient chemotherapy with hybrid simulation modelling

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International Journal of Simulation and Process Modelling 2022年第4期18卷 296-303页

作者： Heshmat, Mahmoud Eltawil, Amr B. Abdelghany, Mohammed Department of Mechanical Design and Production Engineering Faculty of Engineering Assiut University Egypt Industrial and Manufacturing Engineering Egypt-Japan University of Science and Technology New Borg El-Arab City Alexandria21934 Egypt Mechanical Engineering Department Faculty of Engineering Fayoum University Egypt

Outpatient chemotherapy clinics (OCCs) are a crucial medical units where cancer is diagnosed, and treatment is provided. However, they face planning and scheduling challenges. In this paper, two problems in OCCs are addressed: how to accurately compute the utilisation of the nurses, and the patient appointment scheduling problem. An agent-based simulation is used to simulate the nurse activities and thus the nurse utilisation is computed. A discrete event simulation model is developed to evaluate the performance of the current patient appointment practice. However, the resulted nurse utilisation could not be accurately computed. Therefore, a hybrid discrete event and agent-based simulation model is developed to simulate the whole system including the nurse activities. Moreover, the proposed simulation model is used to determine the best patient appointment scenario. The results can be used to accurately compute the nurse utilisation in the OCCs beside the other key performance indicators (KPIs) in OCCs. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Discrete event simulation

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