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检索条件"任意字段=2021 10th International Conference on Computing and Pattern Recognition"

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Simulation Based Protocols Comparison for Vehicular Ad-hoc Network Routing 10

Simulation Based Protocols Comparison for Vehicular Ad-hoc N...

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10th international conference on System Modeling and Advancement in Research Trends, SMART 2021

作者： Shukla, Ravi Shankar Ather, Danish Saudi Electronic University College of Computing and Informatics Department of Computer Science Tabuk Saudi Arabia Sharda University Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9781665439701

VANETs (vehicular ad hoc networks) are a rapidly developing technology that allows communication between moving cars and roadside devices without the need for infrastructure. Although MANET has a subtype called VANET, it is distinguished by the inclusion of automobiles as nodes. ITS makes extensive use of self-organizing networks. Because of the VANET's extremely dynamic topology and frequent disconnection, developing an efficient approach is difficult. Since no one routing protocol is suitable for all VANET applications, it is essential to evaluate the benefits and drawbacks of each. this research project is focused on the VANET and its protocols for routing. this paper discusses the benefits and drawbacks of the DYMO, DSR, AODV and VANET routing protocols. © 2021 IEEE.

关键词： Vehicular ad hoc networks

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Hidden pattern: Toward Decision Support Fuzzy Systems 10th

Hidden Pattern: Toward Decision Support Fuzzy Systems

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10th EAI international conference on Context-Aware Systems and Applications, ICCASA 2021

作者： Han, Nguyen Van Vinh, Phan Cong Phung, Bui Minh Dan, Tran Ngoc Faculty of Information Technology Nguyen Tat Thanh University 300A Nguyen Tat Thanh Street Ward 13 District 4 Ho Chi Minh City Viet Nam Faculty of Information Technology Van Lang University 45 Nguyen Khac Nhu Street Ward Co Giang District 1 Ho Chi Minh City Viet Nam 1018 To Ky Tan Chanh Hiep Ward District 12 Ho Chi Minh City Viet Nam

ISBN: (纸本)9783030931780

In this paper, we introduce a method for computing with words to find linguistic hidden pattern (LHP ) as well as decision support system (DSS ) based on hedge algebra (HA ) using linguistic cognitive map (LCM ). Our model consists of a set of vertices and edges whose values are linguistic variables that are constrained by a linguistic lattice. the algorithm for the system studied will convert to hidden pattern. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Wooden fences

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Screening Child's Screen Time 16

Screening Child's Screen Time

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16th IEEE international conference on Industrial and Information Systems, ICIIS 2021

作者： Madushani, Kaushalya Edirisinghe, Navoda Koralage, Kaushalya Sahabandu, Rashini Samarasinghe, Pradeepa Wickremesinghe, Lumini SLIIT Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9781665426374

the Child iGuardian (CiG) is a mobile application to monitor the child's screen-time and physical activities. the speciality of CiG is that users can capture their children's emotional changes, sleepiness, web browsing behaviors, mouse movements, keyboard patterns when using digital devices and also assess physical activities. We used CNN, LSTM, XG Boost, Multinomial Naive Bayes, FFNN, SVM and Multiple Linear Regression algorithms to implement the models. For the facial expression and sleepiness recognition models, we used CNN and LSTM algorithms with 80% and 82% accuracies respectively. Web tracking and relationship between academic performance and web usage model implemented using Multinomial Naive Bayes and Decision Tree algorithms with 94% and 82% accuracies. XG Boost with 81% and FFNN with 97% accuracies are used to implement mouse movement and key pattern recognition models. Physical activity recognition and sleepiness analysis models are implemented using Logistic Regression and Multiple Linear Regression algorithms with 98% and 96% accuracies respectively. © 2021 IEEE.

关键词： Multiple linear regression

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A Review on Phishing Websites Revealing through Machine Learning 10

A Review on Phishing Websites Revealing through Machine Lear...

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10th international conference on System Modeling and Advancement in Research Trends, SMART 2021

作者： Singh Sengar, Alok Bhola, Abhishek Shukla, Ratnesh Kumar Gupta, Anurag College of Computing Science Information Technology Computer Science Engineering UP Moradabad India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering AP Vaddeswaram India

ISBN: (纸本)9781665439701

Phishing is a frequent assault in which unsuspecting people's unique, private, and sensitive information is stolen through fake websites. the primary objective of phishing websites'consistent resource allocators isto steal unique, private, and sensitive information such as user login passwords and online financial transactions. Phishers construct phony websites that look and sound just like genuine things. With the advent of technology, there are protecting users significantly increased in phishing methods. It necessitates the development of an anti-phishing technology to identify phishing and protect users. Machine learning is a useful technique for combating phishing attempts. these articles were utilized to examine Machine learning for detection strategies and characteristics. © 2021 IEEE.

关键词： Machine learning

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Proceedings CSERC 2021 - 10th Computer Science Education Research conference

Proceedings CSERC 2021 - 10th Computer Science Education Res...

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10th Computer Science Education Research conference, CSERC 2021

ISBN: (纸本)9781450385763

the proceedings contain 16 papers. the topics discussed include: test informed learning with examples;reaching everyone by integrating computing everywhere;a quest to engage computer science students: using dungeons & dragons for developing soft skills;using an assessment tool to create sandboxes for computer graphics teaching in an online environment;personal prof: automatic code review for java assignments;portraits of programmer behavior in a frame-based language;what do they note? an exploratory investigation into the characteristics of CS students’ notes;cooperative gamification in a computer science introductory module;and what does this python code do? an exploratory analysis of novice students’ code explanations.

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10th international conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021 held as Part of EvoStar 2021

10th International Conference on Artificial Intelligence in ...

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10th international conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021 held as Part of EvoStar 2021

ISBN: (纸本)9783030729134

the proceedings contain 31 papers. the special focus in this conference is on Artificial Intelligence in Music, Sound, Art and Design. the topics include: Identification of Pure Painting Pigment Using Machine Learning Algorithms;evolving Neural Style Transfer Blends;evolving Image Enhancement Pipelines;Genre recognition from Symbolic Music with CNNs;axial Generation: A Concretism-Inspired Method for Synthesizing Highly Varied Artworks;interactive, Efficient and Creative Image Generation Using Compositional pattern-Producing Networks;preface;sculpture Inspired Musical Composition: One Possible Approach;aesthetic Evaluation of Cellular Automata Configurations Using Spatial Complexity and Kolmogorov Complexity;auralization of three-Dimensional Cellular Automata;chord Embeddings: Analyzing What they Capture and their Role for Next Chord Prediction and Artist Attribute Prediction;convolutional Generative Adversarial Network, via Transfer Learning, for Traditional Scottish Music Generation;the Enigma of Complexity;SerumRNN: Step by Step Audio VST Effect Programming;parameter Tuning for Wavelet-Based Sound Event Detection Using Neural Networks;raga recognition in Indian Classical Music Using Deep Learning;the Simulated Emergence of Chord Function;incremental Evolution of Stylized Images;network Bending: Expressive Manipulation of Deep Generative Models;dissecting Neural Networks Filter Responses for Artistic Style Transfer;a Fusion of Deep and Shallow Learning to Predict Genres Based on Instrument and Timbre Features;a Multi-objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation;exploring the Effect of Sampling Strategy on Movement Generation with Generative Neural Networks;"A Good Algorithm Does Not Steal – It Imitates": the Originality Report as a Means of Measuring When a Music Generation Algorithm Copies Too Much.

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Temporal Analysis for the Identification of Extreme Rainfall Events Recorded in Uruguay Over a 30-Year Period (1991–2021)

Temporal Analysis for the Identification of Extreme Rainfall...

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pattern recognition Systems (ICPRS), international conference on

作者： Luana Frias-Telesca Nelcy N. Atehortua-Sanchez Fernando Pasini Artificial Intelligence Applications Group - ARIA Universidad Tecnológica de Uruguay Durazno Uruguay

Uruguay is a country susceptible to extreme events (heavy rainfall or drought) due to the large variation in rainfall. the identification of extreme events at a regional scale is essential since the impact due to climate change could become devastating and extended. Significant changes in climate trends make it difficult to predict extreme events. In this study, the variability of precipitation from 1991 to 2021 was analyzed at five meteorological stations of the National Institute of Agricultural Research (INIA). the data used are publicly available in open sources. the statistical analysis of the accumulated precipitation at each station shows that the stations of Tacuarembó and Salto Grande, located in the country's northern region, have a higher annual accumulated precipitation. Due to the nature of the precipitation records, a classical decomposition was performed to analyze the time series, revealing better results for the additive model and showing the seasonality in the data. this information is used to describe the behavior of the precipitation records with the possibility of making projections of the extreme events identified. the decomposition results revealed the presence of extreme events, such as heavy rainfall and prolonged periods of drought. For heavy rain events, the maximum rainfall values were determined for each station and the return periods were calculated using the Gumbel probability. the Salto Grande station is the station with the highest seasonal precipitation records for spring, summer and fall for a return period of 10 years.

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10th international Workshop on Clinical Image-Based Procedures, CLIP 2021, 2nd MICCAI Workshop on Distributed and Collaborative Learning, DCL 2021, 1st MICCAI Workshop, LL-COVID19, 1st Secure and Privacy-Preserving Machine Learning for Medical Imaging Workshop and Tutorial, PPML 2021, held in conjunction with 24th international conference on Medical Image computing and Computer Assisted Intervention, MICCAI 2021

10th International Workshop on Clinical Image-Based Procedur...

引用

10th international Workshop on Clinical Image-Based Procedures, CLIP 2021, 2nd MICCAI Workshop on Distributed and Collaborative Learning, DCL 2021, 1st MICCAI Workshop, LL-COVID19, 1st Secure and Privacy-Preserving Machine Learning for Medical Imaging Workshop and Tutorial, PPML 2021, held in conjunction with 24th international conference on Medical Image computing and Computer Assisted Intervention, MICCAI 2021

ISBN: (纸本)9783030908737

the proceedings contain 17 papers. the special focus in this conference is on Clinical Image-Based Procedures. the topics include: DCL preface;LL-COVID-19 preface;PPML preface;intestine Segmentation with Small Computational Cost for Diagnosis Assistance of Ileus and Intestinal Obstruction;multi-task Federated Learning for Heterogeneous Pancreas Segmentation;federated Learning in the Cloud for Analysis of Medical Images - Experience with Open Source Frameworks;on the Fairness of Swarm Learning in Skin Lesion Classification;Lessons Learned from the Development and Application of Medical Imaging-Based AI Technologies for Combating COVID-19: Why Discuss, What Next;the Role of Pleura and Adipose in Lung Ultrasound AI;DuCN: Dual-Children Network for Medical Diagnosis and Similar Case Recommendation Towards COVID-19;data Imputation and Reconstruction of Distributed Parkinson’s Disease Clinical Assessments: A Comparative Evaluation of Two Aggregation Algorithms;defending Medical Image Diagnostics Against Privacy Attacks Using Generative Methods: Application to Retinal Diagnostics;generation of Patient-Specific, Ligamentoskeletal, Finite Element Meshes for Scoliosis Correction Planning;Bayesian Graph Neural Networks for EEG-Based Emotion recognition;ViTBIS: Vision Transformer for Biomedical Image Segmentation;Attention-Guided Pancreatic Duct Segmentation from Abdominal CT Volumes;development of the Next Generation Hand-Held Doppler with Waveform Phasicity Predictive Capabilities Using Deep Learning;learning from Mistakes: An Error-Driven Mechanism to Improve Segmentation Performance Based on Expert Feedback.

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Prediction of pH of Soil Using Linear Regression, Decision Tree, GPR, and Gaussian SVM 10

Prediction of pH of Soil Using Linear Regression, Decision T...

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10th international conference on Internet of Everything, Microwave Engineering, Communication and Networks, IEMECON 2021

作者： Sunori, Sandeep Kumar Negi, Pushpa Bhakuni Mittal, Amit Arora, Shweta Sharma, Somesh Maurya, Sudhanshu Juneja, Pradeep Graphic Era Hill University Department of ECE Bhimtal Campus Bhimtal India Graphic Era Hill University Department of Chemistry Bhimtal Campus Bhimtal India Graphic Era Hill University Department of PDP Bhimtal Campus Bhimtal India School of Management Graphic Era Hill University Bhimtal Campus India School of Computing Graphic Era Hill University Bhimtal Campus India

ISBN: (纸本)9781665426862

the major part of Uttarakhand is economically dependent on agriculture as here, the soil is very rich in minerals and nutrients, and has a balanced pH value, due to which it has remarkable fertility. this is because of very perfect climatic conditions over here. In solving the classification and regression problems, machine learning techniques are well known to exhibit a remarkable accuracy. In this paper, an attempt is made to perform prediction of soil pH using various machine learning methods in Regression Learner App of MATLAB. Finally, the prediction error for all the developed models is compared. © 2021 IEEE.

关键词： Decision trees

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Promo-Zen: A Natural Language Processing Based Promotional Text Message Management System

Promo-Zen: A Natural Language Processing Based Promotional T...

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Advancements in computing (ICAC), international conference on

作者： Chamath Udugampola Nethmi Weerasingha Department of Computer and Data Science NSBM Green University Homagama Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

Promotional Short Message Service (SMS) messages, which provide frequent updates about deals and discounts to consumers, are crucial in developing countries like Sri Lanka, as they help alleviate financial pressure during economic crises. However, poor practices by the brands, SMS technology limitations and human memory limitations challenge the ability of consumers to make effective use of this facility. As a solution, this project aimed to develop an Android application to organize and enhance the readability of promotional messages, while also providing mechanisms to prevent users from forgetting promotions. these objectives were achieved by creating a Kotlin app that displays promotional information in a date-sorted weekly dashboard, offers deal-expiration reminders, and optimizes message content for readability. the system utilizes a novel workflow/pipeline combining a Natural Language Processing (NLP) model with Named Entity recognition (NER) capabilities, Regular Expressions and custom logic, to understand the context of and extract the crucial information from the promotional messages. User-acceptance testing carried out demonstrates positive results, reducing traditional access times to promotions of 8–10 seconds to approximately 2 seconds through this application. Additionally, user-testers reported multiple occurrences of the reminders feature ensuring that promotions weren't forgotten before use.

关键词： Named entity recognition Developing countries Message services Feature extraction Logic Data mining pattern matching Testing Context modeling

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