Titlebook: ICT Innovations 2020. Machine Learning and Applications; 12th International C Vesna Dimitrova,Ivica Dimitrovski Conference proceedings 2020

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Ilija Vishinov,Marjan Gusev,Lidija Poposka,Marija Vavlukisfollow practical project.Written by experienced authors usedLearn how to use lightweight CSS framework alternatives to build intuitive websites. This book presents five project examples that use Skeleton, Miligram, UI Kit, Material Design Lite and Susy. .This no-nonsense introduction will help you u

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Temperature Dependent Initial Chemical Conditions for WRF-Chem Air Pollution Simulation Model,ent stations. The importance of the problem brought the need to develop accurate air prediction models. The coupled meteo-chemical simulation systems have already been demonstrated to correctly predict the episodes of high pollution events. Due to the complexity of these models, which simulate the e

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Smart City Air Pollution Monitoring and Prediction: A Case Study of Skopje,on. Citizens often remain unaware of the pollution in their immediate surrounding which usually has strong correlation with the local environment and micro-climate. This paper presents an Internet of Things based system for real-time monitoring and prediction of air pollution. First, a general layer

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Cloud Based Personal Health Records Data Exchange in the Age of IoT: The Cross4all Project,ed cross border healthcare systems that introduce a PHR concept and support effort of introducing an e-health strategy where the patient is owner of data and the key point of data collection, using different manners of data acquiring, sometimes not connected with hospitals and country of living. The

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Towards Cleaner Environments by Automated Garbage Detection in Images,he problem of littering and garbage is severe, particularly in developing countries. The problem of littering is that it has a compounding effect, and unless the litter is reported and cleaned right away, it tends to compound and become an even more significant problem. To raise awareness of this pr

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,Fine – Grained Image Classification Using Transfer Learning and Context Encoding,r, this is not an easy task, and difficult tasks require a plethora of tools and creative solutions. In this paper, we present a solution to one fine - grained classification problem, combining deep learning and transfer learning for best end results by using featurization layers of a pretrained neu