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Automated Resume Parsing: A Natural Language processing Approach 7

Automated Resume Parsing: A Natural Language Processing Appr...

引用

7th IEEE international conference on Computational Systems and information technology for Sustainable Solutions, CSITSS 2023

作者： Sougandh, thatavarthi Giri Sai Snehith, K. Reddy, Nithish Sagar Belwal, Meena Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350343144

the extraction of critical information from resumes, such as contact information, skills, education, and job experience, requires the use of resume parsing. In this work, we propose a resume parser that integrates two methodologies: a Named Entity Recognition (NER) model approach and a Keyword and Pattern Matching model approach using Regular Expressions (Regex), utilizing certain NLP libraries and methods. the NER model makes use of NLP libraries to precisely recognize and categorize named entities-such as names, phone numbers, and email addresses-in the resume text. In order to provide a thorough profile overview, it also organizes the parts on talents, education, and job experience. In addition, the Keyword and Pattern Matching model makes use of Regex and pre-established rules to extract certain information, such job titles, firm names, and years of experience. Our resume parser uses NLP-based approaches to increase accuracy and performance, allowing it to handle various resume formats and deliver trustworthy results. Performance assessments show how well the parser extracts crucial information, even from resumes with various layouts and formats. Our resume parser seems to be a useful tool for processing huge numbers of resumes in real-world applications due to its use of NLP libraries and methodologies, together with excellent accuracy and processing speed. © 2023 IEEE.

关键词： Pattern matching

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Cloud Computing Infrastructure in Smart Home Devices 7

Cloud Computing Infrastructure in Smart Home Devices

引用

7th international conference on Image information processing, ICIIP 2023

作者： Roy, Rajarshi Sharma, Nidhi Lovely Professional University Dept of Computer Science And Engineering Punjab India

ISBN: (纸本)9798350371406

Cloud computing has transformed how we engage with technology. computer users now have easy access to computing resources via the internet. this inclination is not limited to smart home devices. Smart home devices have become more dominant by means and the use of technology. Internet of things (IoT) takes grown the popularity, makes our daily lives easier and more efficient. Cloud computing technology provides a chance to increase the performance, usefulness of smart home devices with integration in smart home gadgets. the author has worked and emphasizes the assistances of cloud computing, like as scalability, cost-efficiency, greater storage capacity, along with covering the drawbacks, such as security threats, data privacy concerns, and latency issues. Recent research studies imply that cloud computing can considerably progress the performance of smart home devices by providing greater storage, processing power, and data analytics capabilities. the possible risks associated with cloud computing must be carefully handled to maintain the security and privacy of users' data has discussed in the paper. © 2023 IEEE.

关键词： Internet of things

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A Comparative Analysis on Various Machine Learning Methods for GAN Based Video Anomaly Detection 7th

A Comparative Analysis on Various Machine Learning Methods f...

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data Science, ICCIDS 2024

作者： Chiranjeevi, Rahul Shyam, C. Hirthik Kaushiik, K. Kumar, P. Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9783031699818

In recent years, surveillance has undergone tremendous change and developed into an essential instrument for maintaining security and keeping an eye on sensitive areas. this essay investigates the idea of what defines surveillance. It explores the crucial topic of anomaly detection, which is a vital component of contemporary surveillance systems. the expanding importance of the use of deep learning methods is highlighted in this paper’s discussion of current developments in surveillance technology. through the processing of massive volumes of data, deep learning has transformed surveillance by allowing more precise and effective anomaly detection. Examining several kinds of deep learning techniques, their special qualities and uses are highlighted. this study concludes with an in-depth analysis of the monitoring, highlighting the role of deep learning in improving anomaly detection. It is an invaluable tool for researchers, professionals and decision makers interested in the development of surveillance technology and its use in different contexts. © IFIP international Federation for information processing 2024.

关键词： Contrastive Learning

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Jamming Waveform Designed in Focused Energy Delivery for Precision Electronic Warfare Scenario 7

Jamming Waveform Designed in Focused Energy Delivery for Pre...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Zhang, Kedi Wang, Jing Zhou, Qingsong Zhang, Jianyun National University of Defense Technology College of Electronic Engineering Hefei China National University of Defense Technology College of Computer Changsha China

ISBN: (纸本)9781665478571

Precision electronic warfare (PREW) is an application to solve many problems that are difficult to solve with current electronic warfare methods. However, the current issues related to designing jamming waveforms suitable for ultra-sparse used in PREW scenarios are still worthy of further study. this paper addresses this problem by employing sequential cone programming (SCP) in convex optimization techniques to design constant-modulus jamming waveforms suitable for the PREW scenarios. In a standard PREW scenario, the spatial energy focusing effect of the waveforms generated by the proposed algorithm is verified. the waveforms designed by the proposed algorithm based on the verification results are more suitable for the PREW scenario deployment than the previous method. © 2022 IEEE.

关键词： Convex optimization

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Increasing Efficiency in Counting Number of Motorcycle with Object Relation Matching 7

Increasing Efficiency in Counting Number of Motorcycle with ...

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7th international conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, NCON 2022

作者： Tongmonwit, Boonyakon Tamee, Kreangsak Naresuan University Faculty of Science Department of Computer Science and Information Technology Phitsanulok65000 Thailand Naresuan University Research Center for Academic Excellence in Nonlinear Analysis and Optimization Faculty of Science Department of Computer Science and Information Technology Phitsanulok65000 Thailand

ISBN: (纸本)9781665495103

Counting number of object is very important for data collection. this research had experimented in counting number of motorcycle with object detection and tracking technology by using YOLOv4 model for object detection and Deepsort model for object tracking. However, the experiment showed several errors in counting number of object detection and tracking. therefore, the object relation matching concept was applied in an attempt to solve these errors. It was found that, after applying object relation matching concept, precision in counting number of object rose from 68.29 percent to 80.99 percent, or 12.7 percent increase © 2022 IEEE.

关键词： Object detection

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Research on the test method of AFDX end system 7

Research on the test method of AFDX end system

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Wang, KuiSheng Li, WanShan Wang, Li Zhang, Yao Xi'an Shiyou University School of Computer Science Xi'an China Airborne Network Bus Xiangteng Microelectronics Technology CO. LTD Xi'an China

ISBN: (纸本)9781665478571

With the wide application of the AFDX (Avionics Full Duplex Switched Ethernet) network, the demand for AFDX terminal system testing increases daily. However, the content of AFDX is complex, the testing-related work is tedious, and the testing work of the system puts a significant burden on the testers. therefore, it is essential to implement the research of AFDX terminal system testing methods to improve the efficiency of terminal system testing. this paper analyzes the AFDX network protocol and proposes a test method by studying the terminal system test requirements. © 2022 IEEE.

关键词： Ethernet

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Pedestrian and Object Detection using Image processing by YOLOv3 and YOLOv2 7

Pedestrian and Object Detection using Image Processing by YO...

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7th international conference on Trends in Electronics and Informatics, ICOEI 2023

作者： Chatrasi, Amar Lokesh Venkata Siva Sai Batchu, Anush Gupta Kommareddy, Leela Satya Garikipati, Jyotsna Velagapudi Ramakrishna Siddhartha Engineering College Dept.of Information Technology Vijayawada India

ISBN: (纸本)9798350397284

Detecting instances of semantic objects of a specific class, such humans and other things, in digital photos and videos is the goal of object detection, a branch of computer vision and image processing. It is frequently used for activities including picture annotation, vehicle counting, and object tracking, such as tracing a ball during a football game, a cricket bat's movement, or primarily a person in a movie. In this study OpenCV is used with YOLOv3 neural network to detect pedestrians and objects from an input video or a real time webcam. In order to determine how accurately the pedestrians and objects are recognized using the You Only Look Once (YOLO) algorithm, a box is produced along its boundaries with its name and Intersection Over Union (IOU) value, which is determined using the formula area of Intersection/Area of Union. the pre-trained model and the weights of the COCO dataset of YOLOv3 tiny algorithm are used for the detection and compared with YOLOv2 algorithm. © 2023 IEEE.

关键词： computer vision

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Exploring Taiwan Monkeypox Virus (MPOX/MPXV) Clade IIb by Establishing Dataset and Clustering by using Sequence and Image Similarity Comparisons 24

Exploring Taiwan Monkeypox Virus (MPOX/MPXV) Clade IIb by Es...

引用

7th international conference on Computational Intelligence and Intelligent Systems, CIIS 2024

作者： Wang, Tzung-Wei Li, Ming-Kuang Lou, Der-Chyuan Lin, Chun-Yuan Dept. of Electronics Engineering Chang Gung University Taoyuan Taiwan Dept. of Computer Science and Information Engineering Asia University Taiwan Taichung Taiwan Dept. of Computer Science and Information Engineering Chang Gung University Taoyuan Taiwan

ISBN: (纸本)9798400717437

Based on the MPXV Clade IIb cases in Taiwan, 175 segments were identified from OPG001 to OPG210. the first focus of this paper is on sequence analysis of the MPXV cases in Taiwan, detailing the procedures, including semi-automated segmentation and dataset creation from a large number of MPXV Clade IIb nucleotide sequences found in the NCBI and GISAID databases. the second feature highlights the pioneering establishment of an MPXV Clade IIb RNA 2nd structure image dataset in Taiwan, as such a dataset does not yet exist globally. the third characteristic involves the use of unsupervised learning methods for the rapid clustering of MPXV Clade IIb RNA 2nd structure images. this approach allows not only for the quick detection and clustering of unknown MPXV Clade IIb cases but also for the rapid identification of new MPXV mutations and structural changes. Compared to traditional sequence analysis, this new hybrid systematic method significantly enhances overall efficiency, improving processing speed by at least 24 hours when handling the alignment of 10 MPXV sequences from Taiwan. Future plans include using this prototype analytical model and method to accelerate the analysis of critical lethal factors in MPXV Clade IIb, such as D14L, ultimately helping biologists reduce the time required for analysis and antiviral drug development. © 2024 Copyright held by the owner/author(s).

关键词： Nucleotides

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STEP UP: Systematically Motivating the Children with Low Psychological Maturity Level and Disabled Children using Gamification and Human computer Interaction 7

STEP UP: Systematically Motivating the Children with Low Psy...

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7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Dharmarathne, R.S.C.K. Medagedara, K.A. Madhubashinee, N.B.W.N. Maitipe, P.T. Sriyaratna, Disni Abeywardena, Kavinga Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9781665421683

Children are the future of this world. therefore, teaching them to have a better future is very important. Also, as the adults we have to motivate them to overcome the obstacles and challenges they face throughout their lifetime. When considering about the children, there are various types of children in our society. As examples there are children with special needs and there are children who are mentally and physically stable. Children with special needs require special attention than the other children. these kinds of children with special needs have various types of development disabilities. they are children with low psychological maturity level, autism, down syndrome, genetic disorders etc. We have proposed a system to motivate these children who are with low psychological maturity level named as 'STEP-UP'. this system is a combination of four individual modules that have the common goal to motivate these kinds of children which were implemented using gamification, Image processing, machine learning and Human computer Interaction. One individual module is focused on disabled children, and it will motivate those children using gamification. Another two modules are focusing on the children who are with low psychological maturity level. And that will motivate those kinds of children using gamification and HCI based technologies like Virtual Reality. the other module is a protocol to secure the data sent between the system and the database. the common goal of this overall STEP-UP system is to motivate the children with low psychological maturity level and disabled children. © 2022 IEEE.

关键词： Machine learning

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Understanding Employees' Capability Towards Workload Clustering From E-Portfolio Data 7

Understanding Employees' Capability Towards Workload Cluster...

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7th international conference on information technology, InCIT 2023

作者： Paramee, Piyawat Rueangsirarak, Worasak Uttama, Surapong Mae Fah Luang University Digital Transformation Technology School of Information Technology Chiang Rai Thailand Mae Fah Luang University Center of Excellence in Computer and Communication Engineering for Capacity Building School of Information Technology Chiang Rai Thailand Mae Fah Luang University Center of Excellence in Ai and Emerging Technologies School of Information Technology Chiang Rai Thailand

ISBN: (纸本)9798350358698

this paper proposed the workload clustering method for extracting a frequent task assigned to the employees. the data was exported from an Electronic Portfolio (e-Portfolio) system. In this work an investigation on the effectiveness of workload clustering through various clustering algorithms and dimension-reduction techniques were conducted. this research deployed Natural Language processing for word tokenizing and feature engineering. the Silhouette scores was adopted to measure across different clustering algorithms such as K-means, Hierarchical, Gaussian Mixture Model (GMM), Fuzzy C-means (FCM), and DBSCAN. As a result, the hierarchical clustering on three clusters achieved the best Silhouette score of 0.442. Subsequently, after performing the Principal Component Analysis (PCA) and visualizing the clustering results in 2-dimensional space, the criteria on clear separation, and distinct employees' capability were observed. © 2023 IEEE.

关键词： Personnel

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