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6th International Conference on Microelectronics, Electromagnetics, and Telecommunications, ICMEET 2021

作者： Patnala, Satish Kumar Rachapudi, Venubabu Devi, S Anjali Pappu, Sasibhushana Rao Rao, T. Subha Mastan Department of Information Technology Anil Neerukonda Institute of Technology & Sciences Andhra Pradesh Visakhapatnam India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram Guntur India Department of Computer Science and Engineering Aditya Institute of Technology and Management Andhra Pradesh Tekkali India Department of Computer Science and Engineering CMR Technical Campus Telangana Hyderabad India

ISBN: (纸本)9789811685491

In the mobile ad-hoc networks (MANETS), route failure is one of the reasons for route rediscovery, and the route failure may be caused by frequent mobility of nodes. The route failures in route discovery mechanisms lead to loss of data and overheads in communication. So, mobility is to be considered, while routing is performed in the MANETs. In this paper, a hybrid optimization based on the lifetime prediction algorithm, for route recovery in MANET, is being proposed. Hybrid optimization (MCMMF) is a combination of modified cuckoo and modified moth flame optimization algorithm. This algorithm considers the parameters, expiration time of a link (LET), signal strength of a link (LRSS), residual energy (RE/RS), and the availability of the bandwidth (ABW) to predict the lifetime of the node and the link. Using the predictions to decide a node status, the limits have been fuzzified, the fuzzy rules have been formulated, and all nodes in the network exchange this information. Thus, every node’s status is verified before the transmission of data. The route recovery performance is found in a way that the respective routes are redirected to the stronger nodes or normal nodes in the case of a weak node. Simulation results using MATLAB2019b have shown that the modified cuckoo-modified moth flame (MCMMF) hybrid optimization algorithm produces the better results by comparing with the modified cuckoo search and modified moth flame optimization algorithms. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Optimization

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Deep Learning based Financial management with Decision Support Systems for Adaptive Organization 7

Deep Learning based Financial Management with Decision Suppo...

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7th International Conference on Inventive Computation technologies, ICICT 2024

作者： Shanmuga Prabha, P. Rao, Kamarajugadda Tulasi Vigneswara Ravivarman, G. Prasad, K.V.S. Rajendiran, M. Maranan, Ramya Sathyabama Institute of Science And Technology Department of Computer Science And Engineering Tamil Nadu Chennai India Nicmar University School of Project Management Maharashtra Pune India Karpagam Academy of Higher Education Department of Electrical And Electronics Engineering Tamil Nadu Coimbatore India Gmr Institute of Technology Deparment of Basic Sciences And Humanities Andhra Pradesh Vizianagaram India Panimalar Engineering College Department of Computer Science And Engineering Chennai Tamil Nadu Poonamallee India Saveetha School of Engineering SIMATS Department of Research And Innovation Tamil Nadu Chennai India

ISBN: (纸本)9798350359299

The complexities of dynamic business platforms are overcome using the aid of strategic utilization of decision support systems (DSS) for financial management in adaptive organizations. Adaptive organizations are the ones that proactively respond to changes in their internal and external environments. Decision support systems are an important part of providing analytical tools with modelling strategies. This helps the financial managers to make informed decisions. The proposed system used deep learning with a genetic algorithm for decision support in financial management within adaptive organizations. They are used for various parameters such as resource allocation and risk assessment. The adaptability of genetic algorithms helps in obtaining optimum solutions with aligning perfectly with the dynamic structure of the adaptive organizations. The integration of genetic algorithms provides numerous advantages in financial management. The genetic algorithm discovers huge solution space which helps the organization for the identification of optimal financial strategies in dynamic environments. They play an important role in financial decision-making. The use of genetic algorithms in financial decision support systems improves the adaptability of the organization. The iterative phenomena of genetic algorithms help the system to adapt to the changing financial environment. Thus the proposed system helps in achieving optimum resource allocation with automatic decision-making techniques. © 2024 IEEE.

关键词： Risk assessment

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Interfacial modification using the cross-linkable tannic acid for highly-efficient perovskite solar cells with excellent stability

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Journal of Energy Chemistry 2024年第4期91卷 236-244页

作者： Xing Gao Lirong Rong Fei Wu Yen-Hung Lin Ye Zeng Junhong Tan Rongxing He Cheng Zhong Linna Zhu Chongqing Key Laboratory for Advanced Materials and Technologies of Clean Energy School of Materials&EnergySouthwest UniversityChongqing 400715China Hubei Key Lab on Organic and Polymeric Optoelectronic Materials Department of ChemistryWuhan UniversityWuhan 430072HubeiChina Key Laboratory of Luminescence Analysis and Molecular Sensing Ministry of EducationSchool of Chemistry and Chemical EngineeringSouthwest UniversityChongqing 400715China Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloon 999077Hong KongChina State Key Laboratory of Advanced Displays and Optoelectronics Technologies The Hong Kong University of Science and TechnologyClear Water BayKowloon 999077Hong KongChina

Although the performance of perovskite solar cells(PSCs)has been dramatically increased in recent years,stability is still the main obstacle preventing the PSCs from being *** device instability can be caused by a variety of reasons,including ions diffusion,surface and grain boundary defects,*** this work,the cross-linkable tannic acid(TA)is introduced to modify perovskite film through post-treatment *** numerous organic functional groups(–OH and C=O)in TA can interact with the uncoordinated Pb^(2+)and I^(-)ions in perovskite,thus passivating defects and inhibiting ions *** addition,the formed TA network can absorb a small amount of the residual moisture inside the device to protect the perovskite ***,TA modification regulates the energy level of perovskite,and reduces interfacial charge ***,following TA treatment,the device efficiency is increased significantly from 21.31%to 23.11%,with a decreased hysteresis ***,the treated device shows excellent air,thermal,and operational *** light of this,the readily available,inexpensive TA has the potential to operate as a multipurpose interfacial modifier to increase device efficiency while also enhancing device stability.

关键词： Tannic acid Defect passivation lons diffusion Hydrophilic Stability Perovskite solar cells

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Impact of outbound training on student engagement in management education: An AI based computer vision approach 3

Impact of outbound training on student engagement in managem...

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3rd IEEE North Karnataka Subsection Flagship International Conference, NKCon 2024

作者： Desai, Sumanth P Hanji, Sanjay V Munshi, M.M. Chakradhar, P. Naik, Shreekant Pare, Sushil Kumar VisveswarayaTechnological University Kls Institute of Management Education and Research Karnataka Belagavi India Vishwaprayag University Mit Maharashtra Solapur India Visveswaraya Technological University Karnataka Belagavi India Anurag University Department of Computer Science and Engineering Hyderabad India Mangalore Institute of Technology and Engineering Dept of Mba Karnataka Mangaluru India Kls Institute of Management Education and Research Karnataka Belagavi India

ISBN: (纸本)9798350364569

This study explores the impact of outbound training on student engagement within management education. Outbound training fosters teamwork, leadership, and problem-solving skills and is increasingly incorporated into MBA programs to promote holistic student development. Previous research highlights the benefits of outdoor education in enhancing academic performance and various interpersonal skills. However, evidence demonstrating its effect on student engagement remains limited. This research addresses this gap by evaluating changes in student engagement levels before and after outbound training. The study employs an innovative computer vision-based method to impartially measure student engagement through facial expressions and head pose estimation. The results indicate a significant increase in engagement levels post-training, suggesting that outbound training effectively enhances student enthusiasm and participation in academic tasks. This study provides valuable insights for educators on the importance of integrating outbound training into management curricula and demonstrates the potential of advanced technologies in educational research. © 2024 IEEE.

关键词： Students

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Multi Objective Optimization Based Land Cover Classification Using NSGA-II 6

Multi Objective Optimization Based Land Cover Classification...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Singh, Ajay Kumar Jain, Arpit Divya Kumar Sharma, Yogesh Athithan, Senthil Sachi, Savya University Institute of Engineering & Technology Chandigarh University Punjab Mohali India Koneru Lakshmaiah Education Foundation Department of Computer Science & Engineering Andhra Pradesh Vaddeswaram India Shah Satnam Ji girls'College Affiliated to Chaudhary Devi Lal University Department of Computer Science Haryana Sirsa India Lalit Narayan Mishra College of Business Management Department of Information Technology Bihar Muzaffarpur India

ISBN: (纸本)9798350304480

The current investigation makes use of a technique referred to as with multiple goals ounces-based land cover classification in order to identify the several forms of land use that are present in a certain area. For the purpose of forecasting the characteristics, the NSGA-II framework is going to be used, and it is going to offer accurate findings. The K-means Clustering method is applied for determining how the Land should be categorized. The tried and true strategy of Pareto Search was utilized for the land cover classification that was carried out in order to make comparisons more straightforward. The data revealed that NSGA-II attained an acceptable degree of performance when contrasted with the results of the Pareto Search. © 2023 IEEE.

关键词： classification K-means Clustering NSGA-II Pareto Search

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Data Centric Blockchain Based Evaluation Approach to Analyze E-Commerce Reviews Using Machine and Deep Learning Techniques 20

Data Centric Blockchain Based Evaluation Approach to Analyze...

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20th International computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2023

作者： Acheampong, Edward Mensah Zhou, Shijie Liao, Yongjian Atandoh, Peter Addo, Daniel Antwi-Boasiako, Emmanuel Nkrumah, Rose Aggrey, Esther Stacy E.B. Appiah-Twum, Michael School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Ghana Institute of Management and Public Administration Department of Computer Science Ghana University of Cape Coast Department of Basic Education Ghana School of Resource and Environment University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350318982

Machine and deep learning techniques are now essential for many different kinds of solutions in many areas, applications, and businesses. Analyzing e-commerce reviews using machine and deep learning techniques can motivate a company to make more wise decisions regarding the quality and services it offers. But issues can occur if there is insufficient high-quality data for the training, scalability, and upkeep of learning models. To address these important issues, we suggest a data-centric learning architecture that makes use of a blockchain and Interplanetary File System (IPFS)-based storage. Our architecture provides secure and cost-effective data storage and an incentive mechanism. Our experiment shows that as the dataset gets bigger, the Naïve Bayes (NB) and the Support Vector Machine (SVM) models get 2% more accurate, the Convolutional Neural Network (CNN) model gets 4% more accurate, and the Long Short-Term Memory (LSTM) model gets 3 % more accurate. The deep learning models exhibited higher accuracy rates than the machine learning models because hidden layers of deep learning possess the ability to extract intricate syntactic features from the review text. © 2023 IEEE.

关键词： Customer satisfaction

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Role of Data Mining Across Different Formats of Multimedia

Role of Data Mining Across Different Formats of Multimedia

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2023 International Conference on Sustainable Computing and Smart Systems, ICSCSS 2023

作者： Velmurugan, A.K. Rajalingam, A. Dhawaleswar Rao, C.H. Balasubadra, K. Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering andhra Pradesh Vijayawada India University of Technology and Applied Sciences-Shinas Department of Electronics and Communication Engineering Oman Centurion University of Technology and Management Department of Computer Science and Engineering Paralakhemundi Campus Alluri Sitapur Odisha Gajapati India R.M.D Engineering College Department of Information Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350333602

In today's world, mining data from videos plays a significant role in the process of information retrieval. The generation of information pertaining to moving images is straightforward for many users. As a result of this, obtaining the required material, particularly the unstructured datasets is a challenging process. There are a number of factors it might contribute to this level of complication, including recordings captured by individuals without professional training, subpar cameras, inadequate lighting, and many more. There were several other algorithms it had been presented to recover useful video footage, but none of them achieved the results it was anticipated. It is, and will likely always be, the most difficult area for scholars to work in. A brand-new method for extracting video images is presented in this article, and it makes use of the image feature value as its primary tool. At first, the picture is grouped, and then the image input extract feature for particular information and then is used to get rid of undesirable image frames inside the grouped image. The results of the experiments demonstrate the procedure suitable for all kinds of moving pictures. © 2023 IEEE.

关键词： Data mining

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Automated Reporting Module in the Academic Staff Performance Appraisal System 14

Automated Reporting Module in the Academic Staff Performance...

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14th International Conference on Advanced computer Information technologies, ACIT 2024

作者： Pukas, Andriy Simak, Andrii Yushko, Andriy Nadvynychnyy, Sergiy Shandruk, Serhii Vatslavskyi, Oleh West Ukrainian National University Department of Computer Science Ternopil Ukraine West Ukrainian National University Department of Management Public Administration and Personnel Ternopil Ukraine West Ukrainian National University Department of Psychology and Social Work Ternopil Ukraine West Ukrainian National University Department of Financial Technologies and Banking Business Ternopil Ukraine

ISBN: (纸本)9798350350036

This research paper proposes the architecture of an automated reporting module in the academic staff performance appraisal system, designed to collect and process data on the activities of academic staff at a higher education institution. This module will be integrated into the existing university academic staff performance appraisal system, and it solves the problem of automating the process of generating employee rating reports and filling out reports with collected data. It automates the collection of information on the scientific activities of employees, including articles, publications, journals, and other works. The module can integrate with a variety of sources, including designated and external web resources, and analyze the data using artificial intelligence tools. Once the data is collected, the automated reporting module is used as a data warehouse and a basis for automatically filling in the criteria in the rating reports of employees, which allows optimizing and simplifying the process of reporting and evaluating their scientific activity. © 2024 IEEE.

关键词： Personnel rating

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A Novel Method for Categorizing Brain Tumors using the Hybrid ALO-ELM Model 7

A Novel Method for Categorizing Brain Tumors using the Hybri...

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7th International Conference on Trends in Electronics and Informatics, ICOEI 2023

作者： Anushkannan, N.K. Balde, Govind Hanmantrao Suganthi, D. Pandian, P. Muthu Kaur, Balwinder Sagar, K.V. Daya Kathir College of Engineering Department of Electronics and Communication Engineering Tamilnadu Coimbatore India NTVS'S G.T.Patil Arts Commerce and Science College Department of Zoology Maharashtra Nandurbar India Saveetha College of Liberal Arts and Sciences SIMATS Thandalam Department of Computer Science Tamilnadu Chennai India Saveetha Engineering College Thandalam Department of Chemistry Tamilnadu Chennai India Punjabi University Regional Centre for It and Management Department of Computer Science Punjab Mohali India Koneru Lakshmaiah Education Foundation Vaddeswaram Department of Electronics and Computer Engineering Andhra Pradesh Guntur India

ISBN: (纸本)9798350397284

Brain tumors, like many other disorders, can cause brain injury through the formation of clots. The MRI picture clearly shows the brain tumor. Healthy brain tissue and brain tumor tissue seem quite similar under the microscope, making it easy to confuse the two. The brain tumor must be properly diagnosed. When assessing brain tumors, segmentation is the gold standard. Brain tumor segmentation is conducted to get around this difficulty by isolating tumor tissue from normal brain tissue, edematous brain tissue, and cerebrospinal fluid. However, this cannot be accomplished until the MRI picture has been median filtered to preserve its edges. An iterative thresholding approach is required to extract the greatest area from the tumor segmentation. After using the watershed method to separate the brain from the rest of the head, the cropping procedure is used to remove any remaining skull tissue. After ALO has improved the settings of ELM, a brain tumor detection system based on the ALO-ELM combination will have been created by identifying the input nodes, hidden layer nodes, and output nodes. The technique outperforms both the ALO and ELM models, with an accuracy of around 98.8%. © 2023 IEEE.

关键词： Magnetic resonance imaging

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Modeling of computer Virus Propagation with Fuzzy Parameters

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computers, Materials & Continua 2023年第3期74卷 5663-5678页

作者： Reemah M.Alhebshi Nauman Ahmed Dumitru Baleanu Umbreen Fatima Fazal Dayan Muhammad Rafiq Ali Raza Muhammad Ozair Ahmad Emad E.Mahmoud Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Mathematics and Statistics University of LahoreLahore54590Pakistan Department of Mathematics Cankaya UniversityBalgatAnkara06530Turkey Department of Medical Research China Medical UniversityTaichung406040TaiwanChina Institute of Space Sciences Magurele-Bucharest077125Romania Department of Computer Science University of LahoreLahore54590Pakistan Department of Mathematics School of ScienceUniversity of Management and TechnologyLahore54000Pakistan Department of Mathematics Faculty of Science and TechnologyUniversity of Central PunjabLahore54000Pakistan Department of Mathematics Near East University TRNCMersin10Turkey Department of Mathematics Government Maulana Zafar Ali Khan Graduate College WazirabadPunjab Higher Education Department(PHED)Lahore5400Pakistan Department of Mathematics and Statistics College of ScienceTaif UniversityP O Box11099Taif21944Saudi Arabia

Typically,a computer has infectivity as soon as it is *** is a reality that no antivirus programming can identify and eliminate all kinds of viruses,suggesting that infections would persevere on the *** understand the dynamics of the virus propagation in a better way,a computer virus spread model with fuzzy parameters is presented in this *** is assumed that all infected computers do not have the same contribution to the virus transmission process and each computer has a different degree of infectivity,which depends on the quantity of *** this,the parametersβandγbeing functions of the computer virus load,are considered fuzzy *** fuzzy theory helps us understand the spread of computer viruses more realistically as these parameters have fixed values in classical *** essential features of the model,like reproduction number and equilibrium analysis,are discussed in fuzzy ***,with fuzziness,two numerical methods,the forward Euler technique,and a nonstandard finite difference(NSFD)scheme,respectively,are developed and *** the evidence of the numerical simulations,the proposed NSFD method preserves the main features of the dynamic *** can be considered a reliable tool to predict such types of solutions.

关键词： SIR model fuzzy parameters computer virus NSFD scheme stability

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