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7th International Conference on Smart and Sustainable Technologies, SpliTech 2022

作者： Bilandzic, Josip Pelin, Denis Brandis, Andrej Topic, Danijel Knezcvic, Goran Simic, Zvonimir Technology Osijek Faculty of Electrical Engineering Computer Science and Information Department of Power Engineering Osijek Croatia

ISBN: (纸本)9789532901160

In this paper, battery charge and discharge simulation are shown for one battery energy storage system. For this purpose, the two-stage bidirectional power converter is used to achieve power conversion from battery storage to the grid in one, and from the grid to the battery storage in another case. Operation principles of a full bridge rectifier and full bridge three-phase AC/DC converter are explained, and the waveforms for both, battery charge and discharge modes are shown. The simulation model is done in MATLAB SIMULINK software, where simulation results are obtained and analyzed for both operation modes of the system. © 2022 University of Split, FESB.

关键词： MATLAB

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Simulation of Subgouge Sand Deformations Using Robust Machine Learning Algorithms

Simulation of Subgouge Sand Deformations Using Robust Machin...

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Offshore Technology Conference, OTC 2022

作者： Azimi, Hamed Shiri, Hodjat Mahdianpari, Masoud Civil Engineering Department Faculty of Engineering and Applied Science Memorial University of Newfoundland Canada Department of Electrical and Computer Engineering Faculty of Engineering and Applied Science Memorial University of Newfoundland Canada

ISBN: (纸本)9781613998526

Ice gouging is one of the major menaces to the subsea pipelines crossing the Arctic (e.g., Beaufort Sea) or the non-Arctic (e.g., Caspian Sea) shallow waters. Burial of the sea-bottom-founded infrastructures is regarded as a feasible method for protection of the subsea assets against the ice gouging threat. These pipelines are commonly embedded underneath the deepest ice-scoured records in the area, whereas the pipeline system is still threatened by the ice-induced soil displacement developed into the ice tip owing to the shear resistance of the seabed soil. Determination of the sub-gouge soil displacements is a governing design factor for the subsea structures in the Arctic offshore that commonly need costly laboratory studies and long-running finite element (FE) analyses to guarantee the operational integrity of the subsea pipeline against the ice-gouging event. Thus, the industry is still seeking more cost-effective, reliable, and faster alternative approaches for simulation of the iceberg-seabed-pipeline interaction process to minimize the collision risk of ice keels with the subsea structures. Recently, the application of machine learning (ML) in different fields has witnessed impressive growth since the ML technology is sufficiently precise, quick, reliable, and cost-effective to model various linear and non-linear problems. In this study, three robust ML algorithms comprising the Decision Tree Regression (DTR), Random Forest Regression (RFR), and Extra Tree Regression (ETR) models were used for the first time to simulate the iceberg-seabed interaction process in the sandy seabed. Using the parameters governing the ice-seabed interaction mechanism, a set of the DTR, RFR, and ETR models were developed. To verify the ML models, a comprehensive dataset was constructed and the data was divided into two sub-samples including the training (70% of data) and testing (the remaining 30% of the data) datasets. Subsequently, for the DTR, RFR, and ETR models, several analy

关键词： Uncertainty analysis

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Zero-Emission Mobile Carbon Capture Facility Powered by Decay Heat of Nuclear Spent Fuels 20

Zero-Emission Mobile Carbon Capture Facility Powered by Deca...

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20th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2023

作者： Li, Muyue Fei, Zhenyu Bao, Kunzhe Ke, Boren Sun, Xiaodong Wang, Lumin Department of Nuclear Engineering and Radiological Sciences University of Michigan Ann ArborMI United States Department of Electrical and Computer Engineering University of Michigan Ann ArborMI United States Department of Computer Science and Engineering University of Michigan Ann ArborMI United States

ISBN: (纸本)9780894487934

To reach carbon neutrality by 2050 with initiatives under the Paris Agreement on climate change, atmospheric greenhouse gas emission, primarily carbon dioxide emission, is under *** capture and storage systems are being developed to reduce carbon dioxide emissions produced by factory operations and fossil fuel-based energy generation.A system design for direct air carbon capture using the decay heat from nuclear-spent fuels is proposed in this study to capture and store dissociated carbon dioxide to reduce global carbon dioxide concentration in the atmosphere.A carbon capture reactor with an aqueous amino acid solution is applied to adsorb atmospheric air, and that accompanies by a desorption reactor separating carbon dioxide and recycling the capture solution with decay *** on the decay heat rate value from spent Westinghouse 17×17 pressurized water reactor (PWR) fuel assemblies, a gas-coolant vertical dry storage cask with a canister containing 32 high-burnup PWR spent fuel assemblies is proposed to provide energy for carbon dioxide *** spent fuels replace conventional electric heaters to avoid the need for external energy for desorption ***, compared with previous studies with the natural gas application, this design could decrease the energy consumption by about 20% and eliminate 1.5 kg CO2 emission per kg carbon captured by using decay heat from spent fuel. © 2023 Proceedings of the 20th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2023. All rights reserved.

关键词： Desorption

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On Supervised Class-Imbalanced Learning: An Updated Perspective and Some Key Challenges

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第6期3卷 973-993页

作者： Das, Swagatam Mullick, Sankha Subhra Zelinka, Ivan Indian Statistical Institute Electronics and Communication Sciences Unit Kolkata700108 India VŠB-TUO Department of Computer Science Faculty of Electrical Engineering and Computer Science Czech Republic IT4Innovations National Supercomputing Centre Ostrava70800 Czech Republic

The problem of class imbalance has always been considered as a significant challenge to traditional machine learning and the emerging deep learning research communities. A classification problem can be considered as class imbalanced if the training set does not contain an equal number of labeled examples from all the classes. A classifier trained on such an imbalanced training set is likely to favor those classes containing a larger number of training examples than the others. Unfortunately, the classes that contain a small number of labelled instances usually correspond to rare and significant events. Thus, poor classification accuracy on these classes may lead to severe consequences. In this article, we aim to provide a comprehensive summary of the rich pool of research works attempting to combat the adversarial effects of class imbalance efficiently. Specifically, following a formal definition of the problem of class imbalance, we explore the plethora of traditional machine learning approaches aiming to mitigate its adversarial effects. We further discuss the state-of-the-art deep-learning-based approaches for improving a classifier's resilience against class imbalance and highlight the need for techniques tailored for such a paradigm. Moreover, we look at the emerging applications where class imbalance can be a major concern. Finally, we outline a few open problems along with the various challenges emerging with the advent of modern applications, deep learning paradigm, and new sources of data. © 2020 IEEE.

关键词： Object detection

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Advancements in Control Systems: Sliding Motion Control, Integrating PID Control, and Machine Learning for Precision and Robustness 3

Advancements in Control Systems: Sliding Motion Control, Int...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Dawane, Mahendra K. Malwatkar, G.M. Deshmukh, Suhas P. Chouhan, Devendra Govt. College of Engineering Department of Instrumentation Engineering Jalgaon India Govt. College of Engineering Department of Mechanical Engineering Karad India School of Computer Science & It Symbiosis University of Applied Sciences Indore India

ISBN: (纸本)9798350343274

To improve the precision and robustness of control systems, this paper investigates the integration of three different control methodologies: Proportional-Integral-Derivative (PID) control, sliding motion control, and machine learning. The introduction starts by outlining the historical progression of control systems and highlighting their growing significance in contemporary technology. These integrated control strategies are at the centre of the research. The effectiveness of PID control as a solid foundation is first demonstrated through real-world applications and success stories, which provide insights into its principles, advantages, and disadvantages. The next step is to introduce sliding motion control to improve the adaptability of control systems, particularly in handling complex dynamics and uncertainties. It is presented as an addition to PID control, and real-world examples show how adaptable and responsive it is. The importance of machine learning's ability to learn from data and adapt to changing environments is emphasised as the role of machine learning in control systems is thoroughly examined. It is viewed as a tool for performance improvement and optimisation, supported by real-world examples that show the sophistication of control systems. The integration of these three methodologies, emphasising the theoretical underpinnings and methodologies of this approach, forms the core of the research. Through case studies spanning numerous industries, such as industrial automation, robotics, aerospace, and autonomous vehicles, it elaborates on the advantages of such integration, particularly in terms of achieving precision and robustness. © 2023 IEEE.

关键词： Motion control

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Experimental Evaluation of a Secured Phrase Searching Model Using Cipher Principles Over Cloud Computing Platform

Experimental Evaluation of a Secured Phrase Searching Model ...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Geetha, R. Parameshwari, M. Kanniga Praveena, V. Venkatesan, T. Sindhu, M. Bhuvana, S. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Rmk Engineering College Department of Information Technology Tamil Nadu Chennai India Tamil Nadu Chennai India R. M. D. Engineering College Department of Mathematics Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Sriram Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350375237

For many cloud-based IoT device learning applications, including sensible clinical data analytics, phrase search - which allows retrieval of files containing a given term - plays a crucial role. In order to prevent sensitive information from being exposed by third-party providers, data owners typically encrypt files (such as medical records) before sending them to the cloud. Having said that, this does make the search operation quite challenging and current searchable encryption systems for multiple keyword searches can't do word searches because they can't determine the location connection of multiple key phrases in a query word using encrypted data stored on the cloud server side. This study presents a model called MCLPS, which stands for 'Modified Cyber Law for Phrase Searching.' Its purpose is to identify specific phrases in a cloud environment. To test how well the model works, it is cross-validated with the traditional BET. The safety of information in the cloud has long been an important concern for cloud service providers and their clients, despite the fact that there are several elements that could affect data security during searches. The reason behind this is the presence of dangers posed by both external data sources and internal partners, namely, their employees. Therefore, due to its massive structure, maintaining this security perfect is an ongoing headache and difficult effort in the cloud. In most cases, this is achieved by encrypting data at all times and taking extra precautions to ensure that data is not compromised during the audition or any other internal exercises. For safe phrase search in cloud IoT, this study suggested the MCLPS model and the BET encryption technique. The data integration, recovery, indexing, sliding, encryption, decryption, and transfer processes are all encompassed in the suggested works. This proposed study introduces a new approach to encrypted searching that allows encrypted phrase searches, and the MCLPS ad BET proced

关键词： Cryptography

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Oral Cancer Classification Using a Hybrid Attention-Aided Deep Learning Model 5th

Oral Cancer Classification Using a Hybrid Attention-Aided D...

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5th International Conference on Medical Imaging and computer Aided Diagnosis, MICAD 2024

作者： Dutta, Srinjan Roy, Jibesh Mandal, Diptarka Kaplun, Dmitrii Shpakovskaya, Irina Sarkar, Ram Department of Computer Science and Engineering Jalpaiguri Government Engineering College Jalpaiguri India School of Computer Engineering and Mathematical Sciences Defence Institute of Advanced Technology Pune India Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China Department of Automation and Control Process Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia Department of Computer Science and Engineering Jadavpur University West Bengal Kolkata India I.P. Pavlov Saint Petersburg First State Medical University St. Petersburg Russia

ISBN: (纸本)9789819638628

Oral cancer remains a critical global health challenge, characterized by high morbidity and mortality due to late-stage diagnosis. This paper addresses the need for improved diagnostic accuracy by introducing a novel hybrid-attention aided deep learning model for oral cancer classification. Our approach integrates the EfficientNetB0 model for feature extraction with a customized hybrid attention module, combining self, spatial, and soft attention mechanisms to emphasize crucial features. The model has been trained and evaluated on both microscopic and macroscopic oral cancer datasets, demonstrating its generalizability. Our proposed model achieves an accuracy of 96.97% on a macroscopic dataset and 92% on a microscopic dataset, with respective F1-scores of 0.97 and 0.89, outperforming baseline models. This hybrid attention-aided deep learning model shows significant potential in improving early detection and treatment planning of oral cancer. Source code and additional results of this work can be found at the GitHub repository. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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Sustainable Learning of computer Programming Languages Using Mind Mapping

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Intelligent Automation & Soft Computing 2023年第5期36卷 1687-1697页

作者： Shahla Gul Muhammad Asif Zubair Nawaz Muhammad Haris Aziz Shahzada Khurram Muhammad Qaiser Saleem Elturabi Osman Ahmed Habib Muhammad Shafiq Osama E.Sheta Department of Computer Science National Textile University Faisalabad37610Pakistan Department of Data Science University of the PunjabLahore54590Pakistan Department of Mechanical Engineering University of SargodhaSargodha40100Pakistan Faculty of Computing The Islamia University of BahawalpurBahawalpur63100Pakistan College of Computer Science and Information Technology Al Baha UniversityAl Baha1988Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea College of Science Zagazig UniversityZagazig44511Egypt

In the current era of information technology,students need to learn modern programming languages efﬁ*** art of teaching/learning program-ming requires many logical and conceptual *** it’s a challenging task for the instructors/learners to teach/learn these programming languages effectively and efﬁ*** mapping is a useful visual tool for establishing ideas and connecting them to solve *** research proposed an effective way to teach programming languages through visual *** experimental study uses a mind mapping tool to teach two programming environments:Text-based Programming and Blocks-based *** performed the experiments with one hundred and sixty undergraduate students of two public sector universities in the Asia Paciﬁc *** different instructional approaches,including block-based language(BBL),text-based languages(TBL),mind map with text-based language(MMTBL)and mind mapping with block-based(MMBBL)are used for this *** results show that instructional approaches using a mind mapping tool to help students solve given tasks in their critical thinking are more effective than other instructional techniques.

关键词： Text programming blocks programming novice programmer

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MLA:A New Mutated Leader Algorithm for Solving Optimization Problems

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computers, Materials & Continua 2022年第3期70卷 5631-5649页

作者： Fatemeh Ahmadi Zeidabadi Sajjad Amiri Doumari Mohammad Dehghani Zeinab Montazeri Pavel Trojovsky Gaurav Dhiman Department of Mathematics and Computer Sciences Sirjan University of TechnologySirjanIran Graduate of Department of Electrical and Electronics Engineering Shiraz University of TechnologyShirazIran Department of Electrical and Electronics Engineering Shiraz University of TechnologyShirazIran Department of Mathematics Faculty of ScienceUniversity of Hradec Králové50003Hradec KrálovéCzech Republic Department of Computer Science Government Bikram College of CommercePatialaPunjabIndia

Optimization plays an effective role in various disciplines of science and *** problems should either be optimized using the appropriate method(i.e.,minimization or maximization).Optimization algorithms are one of the efficient and effective methods in providing quasioptimal solutions for these type of *** this study,a new algorithm called the Mutated Leader Algorithm(MLA)is *** main idea in the proposed MLA is to update the members of the algorithm population in the search space based on the guidance of a mutated *** addition to information about the best member of the population,themutated leader also contains information about the worst member of the population,as well as other normal members of the *** proposed MLA is mathematically modeled for implementation on optimization problems.A standard set consisting of twenty-three objective functions of different types of unimodal,fixed-dimensional multimodal,and high-dimensional multimodal is used to evaluate the ability of the proposed algorithm in ***,the results obtained from theMLA are compared with eight well-known *** results of optimization of objective functions show that the proposed MLA has a high ability to solve various optimization ***,the analysis and comparison of the performance of the proposed MLA against the eight compared algorithms indicates the superiority of the proposed algorithm and ability to provide more suitable quasi-optimal solutions.

关键词： Optimization metaheuristics leader benchmark objective function

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Isolation of Microcrystalline Cellulose from Wood and Fabrication of Polylactic Acid(PLA)Based Green Biocomposites

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Journal of Renewable Materials 2024年第8期12卷 1455-1474页

作者： Selwin Maria Sekar Rajini Nagarajan Ponsuriyaprakash Selvakumar Ismail Sikiru Oluwarotimi Kumar Krishnan Faruq Mohammad Mohammed Rafi Shaik Nadir Ayrilmis Department of Mechanical Engineering Kalasalingam Academy of Research and EducationKrishnankoil626126India Department of Mechanical Engineering SSM Institute of Engineering and TechnologyDindigul624002India Department of Engineering Centre for Engineering ResearchSchool of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK INTI International University Persiaran Perdana BBNNilai71800Malaysia Department of Chemistry College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Kingdom of Saudi Arabia Department of Wood Mechanics and Technology Faculty of ForestryIstanbul University–CerrahpasaBahcekoySariyerIstanbul34473Turkey

An innovative microcrystalline cellulose(MCC)natural fibre powder-reinforced PLA biocomposite was investigated using the hand lay-up *** polymer matrix composite(PMC)samples were prepared by varying the weight percentages(wt.%)of both PLA matrix and MCC reinforcement:pure PLA/100:0,90:10,80:20,70:30,60:40 and 50:50 wt.%,*** the results obtained,MCC powder,with its impressive aspect ratio,proved to be an ideal reinforcement for the PLA,exhibiting exceptional mechanical *** was evident that the 80:20 wt.%biocomposite sample exhibited the maximum improvement in the tensile,flexural,notched impact,compressive strength and hardness by 28.85%,20.00%,91.66%,21.53%and 35.82%,respectively compared to the pure PLA ***,during the thermogravimetric analysis(TGA),the same 80:20 wt.%biocomposite sample showed a minimum weight loss of 20%at 400℃,among *** morphological study using Field Emission Scanning Electron Microscopy(FE-SEM)revealed that the uniform distribution of cellulose reinforcement in the PLA matrix actively improved the mechanical properties of the biocomposites,especially the optimal 80:20 wt.%***,it was evident that the optimal PLA/cellulose biocomposite sample could be a suitable and alternative sustainable,environmentally friendly and biodegradable material for semi/structural applications,replacing synthetic and traditional components.

关键词： Polylactic acid micro crystalline cellulose biocomposite characterizations FESEM environmental pollution

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