In this paper, we propose deep learning architectures (FNN, CNN and LSTM) to forecast a regression model for time dependent data. These algorithm’s are designed to handle Floating Car Data (FCD) historic speeds to predict road traffic data. For this we aggregate the speeds into the network inputs in an innovative way. We compare the RMSE thus obtained with the results of a simpler physical mode...

The benefits of Free Space Optics (FSO) motivate to use it for future high data rate demanding communication applications. However, widespread growth of the technology has been hampered by reduced availability due to weather influences on the link. The fog has been analyzed as the most detrimental for FSO communication. There are some models that predict fog attenuation in terms of visibility. ...

This paper presents the corpus-driven approach in building the computational model of fundamental frequency, or F0, for Lithuanian language. The model was obtained by training the HMM-based speech synthesis system HTS on six hours of speech coming from multiple speakers. Several gender specific models, using different parameters and different contextual factors, were investigated. The models we...

هدف: پژوهش حاضر با هدف ساخت برنامه داربست‌سازی انگیزشی و تعیین اثربخشی آن بر جهت‌گیری‌های هدفی ارزیابی‌های شناختیوالدین انجام شد. روش: پس از طراحی آموزشی داربست سازی اساس نقشه نگاری مداخله، به منظور بررسی شبه‌آزمایشی طرح پیش‌آزمون ـ پس‌آزمون همراه پیگیری گروه گواه استفاده جامعه آماری شامل تمامی والدین ­دانش‌آموزان پایه هشتم منطقة 4 آموزش پرورش شهر تهران نمونة نیز 30 مادر دارای فرزند کلاس هفتم ب...

هدف: آینده­ نگری مجموعه ­ای از توانایی­ های شناختی است. که شامل پیش­ بینی حالت­ ممکن آینده و نیازهای خود این مهارت برای برنامه­ ریزی، غلبه بر موانع رسیدن به موفقیت افراد کمک می­کند. یکی جدیدترین ابزارهای سنجش توانایی تفکر آینده­نگر در کودکان، مقیاس کودکان (مازاچووسکای مهی، 2020) است ویژگی­ روان­سنجی آن استفاده جمعیت ایرانی مورد مطالعه قرار نگرفته روش: روش پژوهش حاضر توصیفی مقطعی بود. تعداد 200 ...

We describe a submission to the WMT12 Quality Estimation task, including an extensive Machine Learning experimentation. Data were augmented with features from linguistic analysis and statistical features from the SMT search graph. Several Feature Selection algorithms were employed. The Quality Estimation problem was addressed both as a regression task and as a discretised classification task, b...

6 Providing real-time bus arrival times can enhance the experience of riders using 7 public transit, but errors in the predictions can cause a decrease in ridership. 8 Using data collected from a local transit agency, we created models to predict 9 arrival times using K-Nearest Neighbors and Kernel Regression and seven sets 10 of features. The best feature set had a RMSE of 34 seconds, a large ...

Random sample selection method in backpropagation results in convergence on the error (root of mean squared error, RMSE) surface. These problems, which are caused by the extreme (worst-case) errors, can be solved by a different sample selection strategy. A sample selection strategy has been proposed, which provides lower maximal errors and a higher confidence level on the expense of slightly in...

We propose a method for medical image denoising using calculus of variations and local variance estimation by shaped windows. This method reduces any additive noise and preserves small patterns and edges of images. A pyramid structure-texture decomposition of images is used to separate noise and texture components based on local variance measures. The experimental results show that the proposed...

A gaze tracking system, based on a novel neural approach, is proposed. The work is part of a wider research project concerning the development of human computer interfaces (HCI) addressed to disabled people, that could overcome the drawbacks of most of the existing methods for gaze tracking that require either intrusive devices or expensive equipment. This work, instead, aims at developing a lo...