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Robotic Process Automation for Automating Business Processes: A use case 7

Robotic Process Automation for Automating Business Processes...

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7th International Conference on Computing Methodologies and Communication, ICCMC 2023

作者： Bhardwaj, Vivek Virender Kumar, Mukesh Thakur, Deepak Lamba, Vikas School of Computer Science and Engineering Lovely Professional University Jalandhar India Chandigarh University Punjab India School of Computer Application Lovely Professional University Jalandhar India Chitkara University Institute of Engineering and Technology Chitkara University Punjab 140401 India

ISBN: (纸本)9781665464086

Numerous advances and changes have been brought about by digitalization in both our daily lives and the business world. RPA is an all-purpose technology for developing specialized agents, or "bots," that communicate with GUI components to carry out routine, rule-based operations. Anyone can utilize the RPA to automate digital operations. RPA deployment in business processes can help to provide better service and guarantee that processes adhere to more efficiency and accuracy. The objective of this study is to enable human workers to assign their regular generic repetitive tasks to a software bot, freeing them up to concentrate on more challenging and difficult activities. This study presents a methodology for implementing RPA to extract employee information from the XMLpages. © 2023 IEEE.

关键词： Automation Anywhere Business Processes RPA Software BOT

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Heart Disease Evaluation with Deep Learning and Machine Learning

Heart Disease Evaluation with Deep Learning and Machine Lear...

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International Conference on Information Systems and computer Networks (ISCON)

作者： Sachin Upadhyay Sanjiv Kumar Singh Jayati Krishna Goswami Shiv Shanker Singh Department of Computer Engineering & Application GLA University Mathura

All over the world is affected by the disease which is named as heart disease. The main reason behind the heart disease is our busy life, as the person is affected not only by office work but also by personal problems. This mortality rate is too high. We can predict this disease with the help of Machine Learning (ML) and Deep Learning (DL) prediction models. In this paper, to reach the accuracy we worked on three ML & DL models. For this paper we use ML models named as: SVM (Support Vector Machine), LR (Logistic Regression) & Naïve Bayes. DL models named as: CNN (Convolutional Neural Network), RNN (Recurrent Neural Network) & LSTM (Long Short Term Memory). The accuracy obtained in this study is made up of the 85% accuracy of Logistic Regression, the 89% accuracy of SVM, and the 85% accuracy of Naive Bayes. LSTM has an accuracy of 83%, RNN has an accuracy of 91%, and CNN has an accuracy of 83%. The study’s findings indicate that the RNN model is the most accurate, coming in at 90%, and from this we can say that it is the best at predicting heart disease.

关键词： Heart Support vector machines Deep learning Recurrent neural networks Machine learning algorithms Computational modeling Predictive models

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Video Encryption Using Optimization Lightweight Algorithm for Secure Internet of Things

Video Encryption Using Optimization Lightweight Algorithm fo...

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International Conference on Data Analytics and Insights, ICDAI 2023

作者： Nayak, Manoja Kumar Dash, Dinesh Kumar Swain, Prasanta Kumar Sahu, Abhimanyu Department of Computer Application MSCB University Baripada India Department of ETCE PMEC Berhampur Berhampur India Department of CSE Seemanta Engineering College Mayurbhanj India

ISBN: (纸本)9789819938773

Video encryption based on lightweight algorithm has grew in importance as a research problem in the areas of Internet of things (IoT). Traditional encryption techniques rely on long keys and more rounds, which are ineffective for small and low-power battery-operated devices. In this paper, we propose an effective approach for video encryption which is suggested in response to the popularity of lightweight encryption techniques created specifically for IoT environments. An effective video encryption technique based on optimization lightweight key generation method is proposed which uses two important approaches such as genetic algorithm for key generation and + 2 function for encryption and decryption. In this scenario, the most significant bit addition’s carry is mitigated by the binary addition, which presents as + 2. Correlation, entropy, and the image histogram of video frames have all been used to evaluate the suggested work. Experimental evaluation on a standard video, named Xylophone, clearly demonstrates the outcomes of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cryptography

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Brain Tumor Radiogenomic Classification using multilevel contrastive information fusion 6

Brain Tumor Radiogenomic Classification using multilevel con...

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6th International Conference on Futuristic Trends in Networks and Computing Technologies, FTNCT 2024

作者： Asmita Mittal, Praveen Department of Computer Engineering Application GLA University Uttar Pradesh Mathura281406 India

Brain tumors present significant challenges in diagnosis and treatment due to their complex and diverse nature. Radiogenomic analysis, which combines genomic and radiological data, has become important for advancing brain tumor research, with deep learning methods, particularly fusion-based approaches, making notable progress. However, current approaches face challenges in capturing both sequential and spatial features, as well as selecting effective fusion techniques. The research introduces a multi-fusion framework that combines Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and transformers using contrastive learning to enhance feature representation. This approach processes medical images through a neural network alongside a transformer backbone, merging outputs at various stages to improve dark knowledge differentiation between classes. While CNNs extract spatial features, transformers focus on patch-specific information, collectively boosting the model's discriminative power. The method demonstrates a 2-3% performance improvement over state-of-the-art models, with significant advancements in glioblastoma diagnosis and treatment. An ablation study further confirms that each component positively contributes to the classification task. © 2025 The Author(s). Published by Elsevier B.V.

关键词： Convolutional neural networks

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Challenge and Analysis of System Simulation Platform Construction for Product Resilient Design

Challenge and Analysis of System Simulation Platform Constru...

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第42届中国控制会议

作者： Baoran An Qinghe Zhou Huai Wu Sifeng Zeng Weijian Huang Institute of Computer Application China Academy of Engineering Physics

The traditional and relatively static rigid product design mode is difficult to meet the diversified needs of *** all levels of products in the whole equipment system,the development of resilient design mode will realize the rapid generation of equipment mission *** resilient design mode of high-value products needs to seamlessly carry the design rules of continuous evolution,and output the improvement,modification and change schemes *** construction of system simulation platform for product resilient design is discussed and analyzed in this paper from three aspects:challenges,countermeasures and ecology.A platform based software R&D(research and development) solution is presented,which can realize independent R&D of high value product resilient design software.

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Play Store App Analysis & Rating Prediction Using Classical ML Models & Artificial Neural Network 7

Play Store App Analysis & Rating Prediction Using Classical ...

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2023 7th International Conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Moharana, Bhimasen Biswal, Bhramara Bar Dey, Snehasis Rath, Manas Kumar Banerjee, Shobhan Lovely Professional University Department of Computer Science and Engineering Punjab India College of Engineering P.G. Department of Computer Science & Applications Bhubaneswar India College of Engineering Electronics & Telecommunication Engineering Bhubaneswar India Maharaja Sriram Chandra Bhanja Deo University Department of Computer Application Baripada India Birla Institute of Technology and Science Department of Engineering Technology Pilani India

ISBN: (纸本)9798350304268

Each app available in the App Store or Play Store has various aspects linked to it such as its version, category, number of installations, genre, etc. which makes it unique, robust & popular. The reviews and ratings given by end users play an important role for both the developers and other users for the performance and survival of the app in the marketplace. Reviews are just a description for justification of the rating given by a user & the rating plays an important role in the first look. In this paper, we have used the Play Store Analysis Dataset to descriptively analyze the various attributes present in it and create models that predict the rating of an app, given its specifications. The models have been compared based on a common accuracy metric based on which their reliability can be judged and used in real-time rating predictions for a new application in the store for which a certain amount of data is available over some period. © 2023 IEEE.

关键词： Descriptive Statistics ML Classification Models Model Comparison Play Store App Analysis Rating Prediction

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SteadySketch: Finding Steady Flows in Data Streams 31

SteadySketch: Finding Steady Flows in Data Streams

引用

31st IEEE/ACM International Symposium on Quality of Service, IWQoS 2023

作者： Li, Xiaodong Fan, Zhuochen Li, Haoyu Zhong, Zheng Guo, Jiarui Long, Sheng Yang, Tong Cui, Bin School of Computer Science Peking University National Engineering Laboratory for Big Data Analysis Technology and Application Beijing China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9798350399738

In this paper, we study steady flows in data streams, which refers to those flows whose arrival rate is always non-zero and around a fixed value for several consecutive time windows. To find steady flows in real time, we propose a novel sketch, SteadySketch, aiming to accurately report steady flows with limited memory. To the best of our knowledge, this is the first work to define and find steady flows in data streams. The key novelty of SteadySketch is our proposed reborn technique, which reduces the required memory space by 75%. Experimental results show that SteadySketch improves the Precision Rate (PR) by 81.1% and reduces the Average Relative Error (ARE) by 955.3× compared with the strawman solution. Finally, we provide a concrete case: cache prefetch, and prove that SteadySketch can effectively improve the cache hit ratio. All related codes of SteadySketch are open-source and available at GitHub. © 2023 IEEE.

关键词： Steady flow

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Research on Coding and Decoding Scheme for 5G Terminal Protocol Conformance Test Based on TTCN-3 6th

Research on Coding and Decoding Scheme for 5G Terminal Proto...

引用

6th International Conference on Innovative Computing and Communication, ICICC 2023

作者： Jingyao, Cao Yadav, Amit Khan, Asif Ansar, Sharmin School of Computer and Software Chengdu Neusoft University Chengdu China College of Engineering IT and Environment Charles Darwin University NT Australia Department of Computer Application Integral University Lucknow India Department of Biological Sciences and Bioengineering Indian Institute of Technology Kanpur India

ISBN: (纸本)9789819940707

Protocol conformance testing is an indispensable part of the marketization of commercial terminals. This paper elaborates and studies the architecture, test model, and design scheme of the 5G terminal protocol conformance testing system and proposes a 5G terminal protocol based on TTCN-3 Conformance test codec solution. The outcome of research shows that this solution has a positive role in promoting the industrialization of 5G. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： 5G mobile communication systems

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Evaluation of Optimum Batting Order Based on Partnership Analysis Using Ant Colony Optimization Technique

Evaluation of Optimum Batting Order Based on Partnership Ana...

引用

International Conference on Advances in Data Science and Computing Technologies, ASDC 2022

作者： Tarafder, Mousumi Santra, Soumen Sharma, Sweta Deyasi, Arpan Department of Computer Application Techno International Newtown Kolkata700156 India Department of Electronics and Communication Engineering RCC Institute of Information Technology Kolkata700015 India

ISBN: (纸本)9789819936557

Based on the recent partnership data as available in authentic database, optimum batting order of various batters is evaluated using Ant Colony Optimization technique. Assuming batters as nodes of ant system and partnership scores is weightage of edges situated at the connecting nodes of ant paths;optimum batting order is computed for various external conditions. Cautiousness factor of the batters is considered which is most settled in the game and playing with maximum time. Un-normalized dataset over last 40 years of one-day performance is normalized by applying several conditions, where single big weight between two batters are neglected due to lack of consistency. Result will be immensely helpful for future performance optimization depending on available batters in the team. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Ant colony optimization

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Enhancing Facial Expression Recognition with a Directional Attentive Neural Network 3

Enhancing Facial Expression Recognition with a Directional A...

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3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024

作者： Singh, Jagendra Shelke, Nitin Arvind Masson, Palak Agrawal, Rishi Sharma, Amit Parashar, Amit Bennett University School of Computer Science Engineering & Technology Greater Noida India Raj Kumar Goel Institute of Technology Greater Noida India Gla University Department of Computer Engineering & Applications Mathura India Lovely Professional University School of Computer Application Phagwara India Pranveer Singh Institute of Technology Basic Science & Humanities-Chemistry Kanpur India

ISBN: (纸本)9798350384598

The proposed DANN was developed for better recognition of facial expression. The proposed DANN combines the attention and directional filters, which filter out features that focus on the informative facial regions while capturing the directional patterns in the facial queue. The average accuracy after benchmarking all the 10 experiment trials was in the very high level with the proposed DANN on datasets combining CK+, FER2013, and RAF-DB, with an average accuracy of 88.04%. The model showed a good trade-off between precision and recall: its average weighted F1 score was 0.881, while the average precision and recall were 0.883. This implies that the model will maximize the identification of true positive samples while, at the same time, minimizing that of false positives and false negatives. All these results are indicative of the robustness and reliability of the DANN architecture in classifying the facial expressions correctly across the different datasets and different experimental settings. The results suggest the high potential of DANN in furthering the state-of-the-art facial expression recognition with prosperous affective computing, human-computer interaction, and psychology. © 2024 IEEE.

关键词： Affective computing Attention mechanisms Deep learning Directional Attentive Neural Network Facial expression recognition

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