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检索条件"任意字段=Conference on Visual Data Exploration and Analysis V"

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Formation of a Student’s Digital Profile for Presentation in the Labor Market

Formation of a Student’s Digital Profile for Presentation i...

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International conference on Innovative Approaches to the Application of Digital Technologies in Education and Research, SLET 2022

作者： Panyukova, Svetlana v. Russian State Social University Moscow Russia

ISBN: (纸本)9783031787751

The significance of the current research stems from employers’ demands for an objective evaluation of a young specialist’s competencies and potential, including both hard skills and soft skills. The digital transformation of the economy ensures openness and reliability of evidence of professional level and personal qualities of applicants presented in resumes and portfolios. The education system and employers are actively seeking effective digital tools and services to gather digital footprints and learning outcomes of students. This initiative aims to facilitate multifactorial analysis of the collected data by stakeholders, enabling them to identify and accurately assess talented graduates. The article discusses the issues of creating and using new digital tools and services for a visual and demonstrative presentation to employers of the achievements of young specialists who are not represented on the labor market, provides an example of the implementation of a web portfolio and digital profile of a graduate on the portal ***, the formation of a unified digital environment through accessibility digital portal services for employers and teachers. The problems of integrating the education system and the labor market to promote the employment of university and college graduates are explored. IT solutions are considered for the formation of a digital profile of a young specialist, including, firstly, the hard skills presented in the web portfolio, with assessment and confirmation by teachers of the level of work performed. Secondly, the results of diagnostics of universal, personal skills (soft skills) of young specialists. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Students

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SEAL: Interactive Tool for Systematic Error analysis and Labeling

SEAL: Interactive Tool for Systematic Error Analysis and Lab...

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2022 conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Rajani, Nazneen Liang, Weixin Chen, Lingjiao Mitchell, Meg Zou, James Hugging Face United States Department of Computer Science Stanford University United States

ISBN: (纸本)9781959429418

With the advent of Transformers, large language models (LLMs) have saturated well-known NLP benchmarks and leaderboards with high aggregate performance. However, many times these models systematically fail on tail data or rare groups not obvious in aggregate evaluation. Identifying such problematic data groups is even more challenging when there are no explicit labels (e.g., ethnicity, gender, etc.) and further compounded for NLP datasets due to the lack of visual features to characterize failure modes (e.g., Asian males, animals indoors, waterbirds on land etc.). This paper introduces an interactive Systematic Error analysis and Labeling (SEAL) tool that uses a two-step approach to first identify high error slices of data and then in the second step introduce methods to give human-understandable semantics to those under-performing slices. We explore a variety of methods for coming up with coherent semantics for the error groups using language models for semantic labeling and a text-to-image model for generating visual features. SEAL toolkit and demo screencast is available at https://***/spaces/nazneen/seal. © 2022 Association for Computational Linguistics.

关键词： Natural language processing systems

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2022 Global Reliability and Prognostics and Health Management conference, PHM-Yantai 2022

2022 Global Reliability and Prognostics and Health Managemen...

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2022 Global Reliability and Prognostics and Health Management conference, PHM-Yantai 2022

ISBN: (纸本)9781665496315

The proceedings contain 267 papers. The topics discussed include: reliability growth model based on Bayesian parameter inference;adaptive maximum cyclostationarity blind deconvolution and its application on incipient fault diagnosis of bearing;a flexible battery capacity estimation method using a portion of charging curve;application of a method of identifying instantaneous shaft speed from spectrum in aeroengine vibration analysis;a monocular visual inertial odometer based on weighted median pre-integration;improved vMD method based on nonlinear Hoyer for abnormal impact interference;application exploration of digital twin in rail transit health management;a subsystem data based reliability acceptance test plan derivation method;fault feature extraction of rolling-element bearing based on neighborhood rough set;safety design and analysis method of single event effects for civil aircraft;auxiliary detection method of illegal actions in football teaching based on binocular vision;robust motion pose capture method of aerobics based on visual simulation imaging;and application of sparse representation method based on K-SvD-ADMM in anomaly detection of satellite telemetry.

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Comparative analysis of the Effect of Circular and Horseshoe Underground Tunnel Shapes on the Required Support Pressure in the General Geological Context of Kandy City 14th

Comparative Analysis of the Effect of Circular and Horseshoe...

引用

14th International conference on Sustainable Built Environment, ICSBE 2023

作者： Warnakulasooriya, M.A.K.v. Fernando, U.B.S. Department of Civil Engineering and Build Environment Liverpool John Moores Univercity Liverpool United Kingdom

ISBN: (纸本)9789819737369

Rapidly expanding cities like Kandy in Sri Lanka frequently encounter obstacles linked to traffic congestion, sustainability concerns, and constraints on infrastructure expansion when it comes to urban development. Subway systems can be proposed as a sustainable remedy to tackle these issues. This research employs a multidisciplinary approach, encompassing geotechnical engineering, environmental science, urban planning, and transportation engineering methods to explore the correlation between the required support pressure to maintain the structural integrity of the tunnel shapes of circular and horseshoe in the general geological context of Kandy city with PLAXIS-3D. At this point, Tunnel Boring Machine (TBM) and New Austrian Tunneling Method (NATM) are used to investigate these circular and horseshoe-shaped tunnel designs respectively. In the field of underground construction, PLAXIS-3D software can be called a successful tool for its ability to simulate complex soil-structure interactions. The data collected geologically for this purpose includes information on soil types, groundwater levels, soil properties, and other relevant material and equipment parameters. Then using finite element analysis software PLAXIS-3D, the detailed 3D models of the common geological strata of Kandy city were constructed to facilitate the tunnel geometry, stress and deformation analysis, visual representation, and to run the tunnel performance analysis. Based on stress distribution and deformation pattern analysis of these 3D models, it was possible to evaluate how tunnel shapes affect the surrounding soil and subsurface environment. Circular and horseshoe-shaped tunnels exhibit distinct support pressure patterns and stress distributions, affecting structural responses and displacement values in Plaxis-3D analysis under fed Kandy geological context. Finally, these findings contribute to optimizing the design and construction of appropriate tunnel shapes by exploring the correlation be

关键词： Stress concentration

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Understanding Plant Leaf Diseases: A Review, analysis, exploration of Techniques and Technologies

Understanding Plant Leaf Diseases: A Review, Analysis, Explo...

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visual Analytics and data visualization (ICvADv), International conference on

作者： Thirumalasetty Nagalakshmi M Sambasivudu Thota Siva Ratna Sai Dept. of CSE Malla Reddy College of Engineering and Technology (A) Telangana India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Modern agriculture relies on plant leaf disease detection to reduce crop losses and guarantee food security. This study takes a look at the three main types of methods used to identify plant leaf diseases: conventional methods, techniques based on Machine Learning (ML), and methodology based on Deep Learning (DL). Although they provide essential insights, the scalability and precision of traditional methods-which depend on chemical analysis, image processing, and human inspection-are severely lacking. ML techniques, which make use of algorithms such as Random Forests (RF) and Support vector Machines (SvM), automate feature-based categorization, which improves detection. Automated disease identification with high accuracy has recently been made possible by DL, which uses sophisticated methods like semantic segmentation, object recognition, and transfer learning in conjunction with architectures like Convolutional Neural Networks (CNNs). This study examines all of these approaches in detail, comparing and contrasting their advantages, disadvantages, and possible uses. Emerging developments, such as eXplainable Artificial Intelligence (XAI) and Internet of Things (IoT)-based systems, are also highlighted in the discussion, with an emphasis on how they will influence smart and sustainable agriculture in the future.

关键词： Support vector machines Deep learning Reviews Explainable AI Semantic segmentation Plants (biology) Transfer learning Food security Object recognition Diseases

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4th International conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2023

4th International Conference on IoT Based Control Networks a...

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4th International conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2023

ISBN: (纸本)9789819965854

The proceedings contain 52 papers. The special focus in this conference is on IoT Based Control Networks and Intelligent Systems. The topics include: Development of IoT-Based vehicle Speed Infringement and Alcohol Consumption Detection System;phonocardiogram Identification Using Mel Frequency and Gammatone Cepstral Coefficients and an Ensemble Learning Classifier;Automatic Conversion of Image Design into HTML and CSS;Customizing Arduino LMiC Library Through LEAN and Scrum to Support LoRaWAN v1.1 Specification for Developing IoT Prototypes;prevention of Wormhole Attack Using Mobile Secure Neighbour Discovery Protocol in Wireless Sensor Networks;Comparison of Feature Extraction Methods Between MFCC, BFCC, and GFCC with SvM Classifier for Parkinson’s Disease Diagnosis;a Comprehensive Study on Artificial Intelligence-Based Face Recognition Technologies;design of IoT-Based Smart Wearable Device for Human Safety;Detection of Artery/vein in Retinal Images Using CNN and GCN for Diagnosis of Hypertensive Retinopathy;vehicle Information Management System Using Hyperledger Fabric;An Evolutionary Optimization Based on Clustering Algorithm to Enhance vANET Communication Services;visual Sentiment analysis: An analysis of Emotions in video and Audio;design and Functional Implementation of Green data Center;patient Pulse Rate and Oxygen Level Monitoring System Using IoT;ioT-Based Solution for Monitoring Gas Emission in Sewage Treatment Plant to Prevent Human Health Hazards;Evaluation of the Capabilities of LDPC Codes for Network Applications in the 802.11ax Standard;parallel Optimization Technique to Improve the Performance of Lightweight Intrusion Detection Systems;Enhancement in Securing Open Source SDN Controller Against DDoS Attack;proposal of a General Model for Creation of Anomaly Detection Systems in IoT Infrastructures;green IoT-Based Automated Door Hydroponics Farming System.

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The Research of Shaolin Wushu in China: data analysis Based on Citespace v 2

The Research of Shaolin Wushu in China: Data Analysis Based ...

引用

2nd International conference on Statistics, Applied Mathematics, and Computing Science, CSAMCS 2022

作者： Wang, Xiaobing Huang, Dongxiang School of physical education Shaoguan University Shaoguan China

ISBN: (纸本)9781510663183

In order to overall examine the Chinese research of the development dynamic, hotspots and trends of Shaolin Wushu, this paper used Citespace v software to made a scientometric and visual analysis on 160 papers regarding Shaolin Wushu. The papers were selected from core journals, CSSCI and CSCD of CNKI database from 1992 to 2021. Conclusions: (1) The number of published papers in Shaolin Wushu showed a normal distribution, reaching a peak in 2013, and then gradually declining. Based on the research institutions, the top three in terms of published papers were Henan University, Zhengzhou University, and Anyang Normal University, all of that were in Henan Province which was the main province for publishing Shaolin Wushu research. (2) The research in the field of Shaolin Wushu was relatively scattered, and a stable groups of journals were not formed. (3) A stable groups of authors publishing the papers of Shaolin Wushu were not made, and most of the current researches were privately written. (4) The hotspot in the field of Shaolin Wushu were consisted of Shaolin Temple, Wushu culture, Chinese Wushu, sports tourism and sports history. The focus of Shaolin Wushu research is to be expanding, and the research topics tend is to be diversified and integrated. © 2023 SPIE.

关键词： Normal distribution

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Autism Spectrum Disorder Detection Using Convolutional Neural Network

Autism Spectrum Disorder Detection Using Convolutional Neura...

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visual Analytics and data visualization (ICvADv), International conference on

作者： v. Angel Petricia Jacksy M Bhavadharani R Dept. of Computer Science and Engineering St. Joseph's Institute of Technology Chennai

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Autism Spectrum Disorder(ASD) is a complex neurodevelopmental condition marked by challenges in social interaction, communication, and repetitive behaviors. Early detection is critical to enable timely intervention and improve outcomes for individuals with ASD. This research proposes an innovative framework that integrates Convolutional Neural Networks (CNNs) with advanced data preprocessing techniques, facial imaging, and behavioral analysis to enhance the accuracy and efficiency of ASD diagnosis. Leveraging data augmentation and transfer learning, the model achieves robust performance with high sensitivity and specificity. The novelty of this approach lies in its ability to identify subtle facial and behavioral patterns indicative of ASD, using a multidisciplinary strategy that combines neuroimaging, machine learning, and real-time diagnostic feedback. By advancing beyond traditional methods, this comprehensive framework holds the potential to revolutionize early ASD detection, making it more accessible, scalable, and precise.

关键词： Neuroimaging Autism visual analytics Face recognition Transfer learning Imaging data visualization Sensitivity and specificity Real-time systems Convolutional neural networks

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Skin Lesion Detection Using Partial Differential Equations

Skin Lesion Detection Using Partial Differential Equations

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visual Analytics and data visualization (ICvADv), International conference on

作者： D. Sree Lakshmi A. Divya Gayathri Yadav Mugada Tanusha Koduru Mownika Bingi Ishwarya Madupu Department of Computer Science and Engineering Prasad V Potluri Siddhartha Institute of Technology Vijayawada India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

The technique used for image interest segmentation is known as segmentation. Processing pixels with matching attributes helps to accomplish this segmentation. Regions of this image become easier to process through part-based methods while avoiding complete image processing. The standard use of segmentation in pictures involves detecting objects as well as their edges. Technical image segmentation functions to break images into basic elements before creating a simplified understanding for easy analysis. A version of the image with reduced dimensions composed of uniform areas displaying similar visual patterns would serve as the best preference. Every image region must have a smooth intensity value that changes abruptly only at the region boundaries. The main segmentation approaches include one method for detecting original image objects and their contours. Edge detection systems produce matching results through the comparison of deformable curves with object contours by defining energy functional principles.

关键词： Image segmentation Accuracy Partial differential equations Image edge detection visual analytics Feature extraction Wavelet analysis Skin Mathematical models Lesions

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COvID-19 Patterns Identification using Advanced Machine Learning and Deep Neural Network Implementation 2

COVID-19 Patterns Identification using Advanced Machine Lear...

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2nd International conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Rao, v. Chandra Shekhar venkatramulu, S. Phridviraj, M.S.B. Pratapagiri, Sreenivas Madugula, Sujatha Kiran, Siripuri Kakatiya Institute of Technology and Science Department of Cse Warangal Telangana India Jyothishmathi Institute of Technology and Science Department of Cse Karimnagar Telangana India

ISBN: (纸本)9781665400527

Predictive analysis and Therapeutic analysis are solitaries in the field of investigation with huge dimensions, which predict a range of diseases. Recently, the effect of the Covid-19 is massive and the virus constantly is mutating. The Generative Adversarial Network (GAN) is the modern efficiency technique used by advanced neural networks to analyze data in cavernous environment. This paper reviews the issues in datasets of Covid, that enables patients to be diagnosed and predicted. The GANs are used to produce, transform, and view datasets profound that trends in medical database. The general prediction research can be highly performing with the incorporation of GANs in comparison with classical neural networks in multiple layers. This research manuscript is projected so that the prediction of mining and the exploration of information can be done more effectively. © 2022 IEEE.

关键词： data Analytics

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