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,...
详细信息
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 ...
详细信息
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...
详细信息
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 allocato...
详细信息
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 &...
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.
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...
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.
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 clim...
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 withthe 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 withthe highest seasonal precipitation records for spring, summer and fall for a return period of 10 years.
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 Computa...
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.
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 o...
详细信息
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 du...
详细信息
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.
暂无评论