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In recent years the development of autonomous vehicles has increased tremendously and a variety of methodologies had been applied to make them more safe and secure. This work shows a multilevel approach combining Failure Mode, Effects and Criticality Analysis of an autonomous railway system with sociological and technical aspects to support safe operations and human-machine…

Aging is considered to be a complex process in almost every species’ life, which can be studied at a variety of levels of abstraction as well as in different organs. Not surprisingly, biometric characteristics from facial images play a significant role in predicting human’s age. Specifically, automatic age estimation in real-time situation has begun to…

Bird watchers and people obsessed with raising and taming birds make a kind of motivation about our subject. It consists of the creation of an Android application called ”Birds Images Predictor” which helps users to recognize nearly 210 endemic bird species in the world. The proposed solution compares the performance of the python script, which…

In the time past, virtually all the contemporary communication systems depend on distinct source and channel encoding schemes for data transmission. Irrespective of the recorded success of the distinct schemes, the new developed scheme known as joint source channel coding technique has proven to have technically outperformed the conventional schemes. The aim of the study…

Estimation of energy demand has important implications for economic and social stability leading to a more secure energy future. One-year-ahead energy demand estimation for Turkey has been proposed in this paper, using the metaheuristics method with GDP, the total population, and the quantities of imports and exports, as inputs variables. The records obtained from historical…

DNN implementation and deployment is quite a challenge within a resource constrained environment on real-time embedded platforms. To attain the goal of DNN tailor made architecture deployment on a real-time embedded platform with limited hardware resources (low computational and memory resources) in comparison to a CPU or GPU based system, High Performance SqueezeNext (HPS) architecture…

The novel coronavirus infection (COVID-19), which appeared at the end of 2019 has developed into a global pandemic with numerous deaths, and has also become a serious social concern. The most important and basic measure for preventing infection is hand hygiene. In this study, by photographing palm images of nursing students after hand-washing, using fluorescent…

This work proposes a new unsupervised learning approach to detect and locate the risks “abnormal event” in video scenes using Faster R-CNN and Bidirectional LSTM autoencoder. The approach proposed in this work is carried out in two steps: In the first step, we used a bidirectional LSTM autoencoder to detect the frames containing risks. In…

The persistent difficulties in reading and spelling acquisition are a risk factor for learning motivation. Play-like intervention tools have been developed to face these difficulties. “I read” is a software that seeks to develop and introduce systematic reading and spelling skills training in a playful and complementary way. This software is intended for children at…

The article identifies an alternative style of thinking as one of the important components of human intellectual development. It is shown that it can be effectively implemented in mathematics lessons at school. The purpose of this study is to develop and substantiate a strategy for the formation of an alternative style of thinking among students…

The data distribution used in model training is assumed to be similar with that when the model is applied. However, in some applications, data distributions may change over time. This situation is called the concept drift, which might decrease the model performance because the model is trained and evaluated in different distributions. To solve this…

Serious games (SGs) are interactive and entertaining digital games with a special educational purpose. Studies have shown that SGs are effective in enhancing educational skills. Cognitive skills training through serious games have been used in improving students learning outcomes. In this article, we introduce the ‘plants kingdom’ serious game for improving adolescents’ cognitive skills, mainly…

In this investigation, an integrated physics-informed deep learning and topology optimization approach for solving density-based topology designs is presented to accomplish efficiency and flexibility. In every iteration, the neural network generates feasible topology designs, and then the topology performance is evaluated using the finite element method. Unlike the data-driven methods where the loss functions are…

Research focused on training and testing of dataset after Optimizing Software Component with the help of deep neural network mechanism. Optimized components are selected for training and testing to improve the accuracy at the time of software selection. Selected components are required to be attuned and accommodating as per requirement. Soft computing mechanism such as…

We propose a novel framework exploiting domain-aware aspect similarity for solving the multi- source cross-domain sentiment classification problem under the constraint of little labeled data. Existing works mainly focus on identifying the common sentiment features from all domains with weighting based on the coarse-grained domain similarity. We argue that it might not provide an accurate…

Collaborative E-learning is highly dependent on the well functioning of a complex socio-technical system that comprises information technology and various social processes. Large-scale infrastructures like the National Research and Education Networks (NRENs) provide access to research and educational resources and provide collaboration between educational and research organizations, thus providing a set of essential services for…

The article further extends the researched issue of the unmanned aircraft use in the pre-flight and post-flight visual check of aircraft. Procedures of pre-flight inspection are fulfilled by the aircraft maintenance certified staff or the crew member before flight. The process is similar for all categories of aircraft, but its implementation differs for individual specific…

In recent days, the fast growth of populations leading to an increase in medically complicated cases, especially fast spread viral cases around the world. These phenomena increased demand on auto-diagnose systems to speed up the diagnosis process and reduce human contacts, especially for the COVID-19 pandemic using deep learning (DL). DL methods can successfully carry…

With a view to detecting whether economic activity deterioration for elderly people at age of sixty-five or over could be observed, anonymous data (AD) were used as analysis data, which were obtained from the National Survey of Family Income and Expenditure (NSFIE) conducted by the Ministry of Internal Affairs and Communications (MIC). We have developed…

Haze removal is an extremely challenging task, and object detection in the hazy environment has recently gained much attention due to the popularity of autonomous driving and traffic surveillance. In this work, the authors propose a multiple linear regression haze removal model based on a widely adopted dehazing algorithm named Dark Channel Prior. Training this…

Coronavirus pandemic and transition to distance learning have significantly accelerated the introduction of Education 3.0 – 4.0 technologies into traditional educational process. This paper discusses questions of training of IT- specialists in context of Education 4.0. Based on our experience, approaches to the organization of the educational process of IT- students are considered. It is…

European counties continue to receive an increasing number of migrants and refugees from an also increasing number of both European and non-European countries. This results in a huge societal challenge which is societal inclusion of people speaking different languages and of diverse backgrounds. Key for their inclusion is job finding which comes with hurdles like…

For systems using rotating machinery, diagnosing the faults of the rotating machinery is critical for system maintenance. Recently, a machine learning algorithm has been employed as one of the methods for diagnosing the faults of rotating machinery. This algorithm has an advantage of automatically classifying faults without an expert knowledge. However, despite a good training…

Modulation type classification is a part of waveform estimation required to employ spectrum sharing scenarios like dynamic spectrum access that allow more efficient spectrum utilization. In this work multiple classification features, feature extraction, and classification algorithms for modulation type classification have been studied and compared in terms of classification speed and accuracy to suggest the…

“This paper is an extension of work originally presented in the 4th International Conference on Systems of Collaboration, Big Data, Internet of Things & Security -SysCoBIoTS’19”. The use of complex and dynamic systems modelling to social systems is quite recent and its pertinence in the case of an educational system is continually increasing. For the…