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检索条件"任意字段=7th IASTED International Conference on Advances in Computer Science and Technology"

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Robotic Process Automation for Automating Business Processes: A use case

Robotic Process Automation for Automating Business Processes...

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international conference on Computing Methodologies and Communication (ICCMC)

作者： Vivek Bhardwaj Virender Mukesh Kumar Deepak thakur Vikas Lamba School of Computer Science and Engineering Lovely Professional University Jalandhar India University Center for Research & Development (UCRD) Chandigarh University Punjab India School of Computer Application Lovely Professional University Jalandhar India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

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 XML pages.

关键词： Intelligent automation XML Chatbots Software Reliability Data mining Task analysis

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Voice-Enabled Vision for the Visually Disabled 7

Voice-Enabled Vision for the Visually Disabled

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7th IEEE international conference on advances in Computing, Communication and Control, ICAC3 2021

作者： Deshmukh, Sujata Rede, Praditi Sharma, Sheetal Iyer, Sahaana Fr. Conceicao Rodrigues Coe Computer Science Department Mumbai India

ISBN: (纸本)9781665426343

We have proposed a single system for analyzing text from an image and converting it into an audio track in the desired language. the visually handicapped can utilize this approach to sense the attitude and demeanor of the person they are dealing with. All of the aforementioned tasks linked with this application are executed by simply issuing commands. the peculiarity of this system is that it reads a handwritten paper, analyses personality based on it, and provides audio output to the blind. this technology makes it possible for the visually impaired to read and understand First Information Reports (FIRs), business cards, chats, doctor's prescriptions, invoices, addresses, and other papers. © 2021 IEEE.

关键词： computer vision

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A CNN-Based Semi-supervised Self-training Method for Robust Underwater Fish Recognition 23

A CNN-Based Semi-supervised Self-training Method for Robust ...

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Proceedings of the 2023 7th international conference on Electronic Information technology and computer Engineering

作者： Tanqing Li Zhili Zhao Hengyu Zhang Kun Li Wenjun Lv School of Information science and Engineering Lanzhou University China University College London the United Kingdom Department of Automation Institute of Advanced Technology University of Science and Technology of China China

ISBN: (纸本)9798400708305

Recent AI advances have revolutionized automation in diverse fields. However, despite object detection research progress, underwater fish species identification remains underexplored. Underwater fish recognition is challenged by the unique underwater environment, fish diversity, and limited labeled data. this study introduces a semi-supervised self-training method, using YOLOv5 as the foundation. Our approach iteratively refines the model with labeled and unlabeled data, enhancing accuracy in data-scarce scenarios. Random data augmentation is also adopted to bolsters model robustness, addressing the complexities of underwater environments.

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Data Encryption: A Compiler Based Approach

Data Encryption: A Compiler Based Approach

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international conference on Computation System and Information technology for Sustainable Solutions (CSITSS)

作者： Kunisetty Jaswanth S Sruthi Pranav Ramachandrula Meena Belwal Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

In today's age, where data security's a growing concern it is crucial to develop strong encoding and decoding models. In our research paper we introduce a model that combines concepts, from compiler design with diverse hashing algorithms. this model aims to offer an efficient solution for transforming and retrieving data. As technology advances rapidly and the need for data security becomes more prominent in real world scenarios our model tackles the challenges of safeguarding information while ensuring integrity and confidentiality. By utilizing hashing algorithms like SHA, BLAKE2 and MD5 we achieve data encryption. Our experiments demonstrate that our model outperforms approaches showcasing its effectiveness across industries where protecting data privacy is of utmost importance. With its user interface our model provides a solution for secure data transmission and storage contributing significantly to advancements in data security and encryption techniques.

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An innovative islanding detection scheme in distributed generation using rate of change of the ratio of negative and positive sequence superimposed voltage components.

An innovative islanding detection scheme in distributed gene...

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international conference on computer Applications In Electrical Engineering-Recent advances (CERA)

作者： Javeed Bashir Mohammad Sajid Aalam Mir Uzair Kanth Premalata Jena Department of Electrical Engineering Islamic University of Science and Technology Kashmir Awantipora India Department of Electrical Engineering IIT Roorkee Roorkee India

this article presents a unique method for detecting localized islanding in distributed generation (DG) system which connected to the main power grid, using a passive approach. the proposed methodology involves calculating the cumulative sum of rate of change of ratio of negative and positive sequence superimposed voltage components (RCR21) at the distributed generation (DG) side, which is then employed to detect the occurrence of islanding. the current active methodologies deliberately introduce disruptions to the power system, posing potential issues concerning stability, power quality, and overall reliability of the prevailing grid. Passive methods, on the other hand, has a considerable non-detection zone (NDZ). the technique recommended in this article successfully addresses the NDZ issue without introducing any disturbances. To evaluate its effectiveness, PSCAD/EMTDC is employed for simulating a system. the proposed method undergoes several tests on the said system to assess its performance. the results demonstrate that the suggested approach exhibits the minimum NDZ and can distinguish islanding within a remarkably short period of time, significantly faster than a recloser which typically requires 150 ms for detection.

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An Evaluative Investigation of Deep Learning Models by Utilizing Transfer Learning and Fine-Tuning for Cervical Cancer Screening of Whole Slide Pap-Smear Images

An Evaluative Investigation of Deep Learning Models by Utili...

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international conference on computer Applications In Electrical Engineering-Recent advances (CERA)

作者： Nitin Kumar Chauhan Krishna Singh Shravan Namdeo Ankit Muley Department of ECE USICT GGS Indraprastha University Delhi India Department of ECE Indore Institute of Science and Technology Indore India Department of ECE DSEU Okhla Campus-I Formerly G. B. Pant Engineering College New Delhi India

Deep learning (DL) is a prominent tool utilized today in many applications across many industries, including the healthcare realm. DL methods can manage several problems that traditional artificial intelligence (AI) methods find challenging. In this paper, we analyzed the performance of nine prevalent DL models i.e. VGG-16, DenseNet-121, ResNet50, VGG-19, DenseNet-169, Xception, EfficientNetB0, InceptionV3, and ResNet-152 pre-trained on ImageNet dataset for cervical cancer screening. these previously trained models are fine-tuned by utilizing transfer learning (TL) for 5-class and 2-class classification of whole slide pap-smear images (WSI). Two-step data augmentation is being used for the preprocessing of data to enhance the efficacy and robustness of classifiers by increasing the amount of the training data and reducing overfitting. Among the aforementioned DL methods, VGG-16 performs best among all with an accuracy of 94.89% for 5-class and 97.16% for 2-class classification.

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A Bibliometrics-Based Systematic Review on Automated Essay Scoring in Education 7

A Bibliometrics-Based Systematic Review on Automated Essay S...

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7th international conference on Information technology Systems and Innovation, ICITSI 2022

作者： Efendi, Toni Lubis, Fetty Fitriyanti Mutaqin Putri, Atina Waskita, Dana Sulistyaningtyas, Tri Rosmansyah, Yusep Sembiring, Jaka School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (数字)9781665465557

ISBN: (纸本)9781665465557

advances in information technology and computer science have brought significant changes to various sectors of human life. In education, computers have helped ease a variety of human tasks, especially for large-scale and repetitive tasks such as essay grading. Current's computer capabilities make it possible to do essay scoring automatically. Research related to automatic essay scoring continues to develop by trying certain techniques and methods to improve the accuracy of automatic scoring close to that of human scoring. this systematic review aims to explore the 21st century applications of automated essay grading used in education. We carried out a bibliometric analysis of the meta data obtained from the SCOPUS database using the Bibliometrix and VOSviewer software reporting the main themes of implementing automated essay scoring applications in educational studies, providing an overview of the current state of the art and future directions of research and applications. Based on bibliometric analysis, we found that research related to automatic essay assessment in education has a fluctuating development trend and the current direction of AES research has used deep learning techniques such as long short-term memory, transfer learning and bert to build a better AES. © 2022 IEEE.

关键词： Grading

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Revolutionizing Human–computer Interaction: Unraveling the Power of Deep Learning Convolutional Neural Networks in Face Recognition 4th

Revolutionizing Human–Computer Interaction: Unraveling the ...

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4th international conference on advances in Computational science and Engineering, ICACSE 2023

作者： Baharum, Aslina Halamy, Suhaida Ismail, Rozita Abdul Rahim, Emelia Mat Noor, Noorsidi Aizuddin Deris, Farhana Diana Department of Computing and Information Systems School of Engineering and Technology Sunway University Bandar Sunway Selangor Malaysia School of Information Science College of Computing Informatics and Mathematics Universiti Teknologi MARA Cawangan Sarawak Kota Samarahan Malaysia College of Computing and Informatics Universiti Tenaga Nasional Putrajaya Campus Kajang Malaysia Faculty of Business Management Universiti Teknologi MARA Cawangan Sarawak Sarawak Kota Samarahan94300 Malaysia Mass Appraisal Housing and Planning Research Group Centre for Real Estate Studies Real Estate Department Faculty of Built Environment and Surveying Universiti Teknologi Malaysia Johor Johor Bahru Malaysia Faculty of Social Sciences and Humanities Universiti Teknologi Malaysia Johor Johor Bahru Malaysia

ISBN: (纸本)9789819729760

Face recognition, being one of the most effective applications of image analysis, has recently received a lot of attention due to the huge implication in human–computer interaction (HCI). As the availability and eligibility to detect a person’s facial features, face recognition technology has been used in biometric detection applications as uses certain aspects of a person’s physiology to identify them. In addition, Deep Learning, under the subset of machine learning, can solve various problems, especially in image processing and face recognition. the advancement and development of Deep Learning can also enhance the use of the Convolution Neural Network (CNN) as the predominant model in the field of face recognition. the paper discusses the systems based on CNN approaches and algorithms and provides a review of the CNN face recognition approach. Furthermore, each paper’s details, such as used datasets, techniques, architecture, and obtained findings, hence the application are fully summarized and analyzed. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

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PVC Waste Plastic Bottle Strip Used for Improvement of Engineering Properties of Clayey Soil 7

PVC Waste Plastic Bottle Strip Used for Improvement of Engin...

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7th international Technical conference on Frontiers of Hydraulic and Civil Engineering technology, HCET 2022

作者： Kumar, Amrendra Singh, Ajay Roy, Bishwajit Bhattacharjee, Shiladitya Bhowmik, Tanmay Department of Civil Engineering Roorkee Institute of Technology Roorkee India School of Computer Science UPES Uttarakhand Dehradun India School of CSE Pandit Deendayal Energy University Gandhinagar India

ISBN: (纸本)9781643683546

the influence of scrap plastic drinking bottles on the strength and swelling qualities of lean clay is investigated in this paper. Before use, waste plastic bottles (WPB) were cut into 4 mm strips and mixed with soil in proportions of 1, 2, 3, 4, and 5% (dry weight of soil). the prepared materials were subjected to three standard tests: Proctor test, swelling, and strength penetration test California Bering Ratio (CBR). the results of tests revealed that WPB have a substantial impact on the clay's compaction, swelling, and strength qualities. © 2022 the authors and IOS Press.

关键词： Soils

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Stereotactic Needle Path Planning for Brain Biopsy Based on Volumetric Segmentation of MRI and Heuristic Approach 5th

Stereotactic Needle Path Planning for Brain Biopsy Based on ...

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5th international conference on advances in Information Communication technology and Computing, AICTC 2024

作者： Krishnan, Sushil Bhogale, Atharva Gawande, Aarya Jaisankar, N. School of Computer Science and Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9789819761050

Any abnormal growth in brain cells refers to brain tumor. With large variety of tumors reported, accurate diagnosis is very essential for appropriate intervention. Traditionally, biopsies are preferred diagnostic tool, where a small piece of tissue or some cells are collected from suspected region and tested in a laboratory. Brain being the control and coordination center, biopsy in brain requires utmost precision and accuracy to avoid any damage to healthy tissues. Stereotactic needle biopsies are specialized minimally invasive technique for collecting the required samples. In such cases precise path planning is very essential. Availability of large medical image datasets and enormous computational capability encourages to train deep learning models that can accurately delineate and identify the tumor’s location, shape, size, and borders within the patient's brain. Volumetric segmentation combined with heuristic path planning algorithm can play a synergistic role in increasing the success rates of brain biopsies. the main objective of the work is to propose a framework for precise needle insertion for brain tumor biopsies. the work proceeds by comparing performances of various model for volumetric segmentation of brain MRI scans and identifying shortest path to the tumor, utilizing the segments obtained. this approach minimizes blood loss and the need for extensive medical intervention. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Biopsy

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