A transition towards electrification of the public transport sector is ongoing in many cities around the world, as a response to global warming and pollution. However, the question is whether the current state of technology is already sufficient to replace the conventional buses with electric ones and if the existing charging facilities are appropriate to…

Internet addiction (IA) has adverse effects on psychophysiological responses, interpersonal relationships, and academic and occupational performance. IA detection has received increasing attention. Although questionnaires enable long-term assessment (over 6 months) and physiological measurements to aid the short-term evaluation (over 2 min) of IA, the lack of algorithms results in an inability to detect IA in…

The Internet of Things (IoT) is at a face paced growth in the advanced Industrial Revolution (IR) 4.0 in the modern digital world. Considering the current network security challenges and sophistication of attacks in the heavily computerized and interconnected systems, such as an IoT ecosystem, the need for an innovative, robust, intelligent and adaptive malware…

Gate driver has been applied in many ways, exemplified by that, by using the DC-isolated and AC-pass characteristics of gate driver’s primary and secondary sides, the problem of floating endpoint in semiconductor power switch can be solved. However, the conventional design of isolated gate driver provides circuit voltage blocking by optically coupled components. Due to…

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…

This paper reports the algorithm, the input data and the result of the numeric simulation on the flows of the waves emitted from a rotating object that forms the artificial anti-gravity. First, an object with a heavy mass is placed in the 4-dimensional time and space, which is described by a fundamental tensor. Then the…

The remarkable presence of side lobes levels in ultrasound B-mode imaging significantly decreases the image quality. Therefore, the use of an apodization function is of great importance. Linear windowing functions are among the most efficient techniques used to optimize antenna directivity by suppression of the side lobes. However, the apodization causes the degradation of lateral…

The Conv-TasNet and Demucs algorithms, can differentiate between two mixed signals, such as music and speech, the mixing operation proceed without any support information. The network of convolutional time-domain audio separations is used in Conv-TasNet algorithm, while there is a new waveform-to-waveform model in Demucs algorithm. The Demucs algorithm utilizes a procedure like the audio…

Real-world applications modelled by time-dependent dynamical systems with specific properties such as long-range dependence or self-similarity are usually described by fractional Brownian motion. The investigation of the qualitative behaviour of its realisations is an important topic. For this purpose, efficient mappings from realisations of the dynamical system, i.e., time series, to a set of scalar-valued…

Affective states, a dimension of attitude, have a critical role in the learning process. In the educational setting, affective states are commonly captured by self-report tools or based on sentiment analysis on asynchronous textual chats, discussions, or students’ journals. Drawbacks of such tools include: distracting the learning process, demanding time and commitment from students to…

Novelty detection affords to identify data patterns that stray strikingly from the normal behavior. it allows a good identification and classification of objects which were not known during the learning phase of the model. In this article, we will introduce an organized and comprehensive review of the study on novelty detection. We have grouped existing…

Background: Today, Enterprise Resource Planning (ERP) software is a major tool for strengthening competitiveness. They are an asset that is changing work practices through the rapid circulation of information, the coordination of action and the development of new ways of doing things, rapid access to a wide range of knowledge and the opening up of…

The daily treats model reduction finite frequency (FFMR) design for Takagi Sugeno (T S) systems. This work is to FFMR design in such a way whether augmented model is steady get a reduced H? index in FF areas with noise is established as a prerequisite. To highlight the importance of suggested process, a practical application…

Chatbot operates task-oriented customer services in special and open domains at different mobile devices. Its related products such as knowledge base Question-Answer System also benefit daily activities. Chatbot functions generally include automatic speech recognition (ASR), natural language understanding (NLU), dialogue management (DM), natural language generation (NLG) and speech synthesis (SS). In this paper, we proposed…

With increases in technological usage, cyber incidents are also on the rise and have become a major concern in schools across the globe. What is of significant concern is that cyber incidents in South African schools are also on the rise. Existing evidence suggests that, in South Africa there are no clear procedures that are…

In this research we developed an BIM-based system to monitor and visualize the real-time building users information. Concentrating on building in-use stages, advantages in tracking facial recognition should be revealed through the availability of real-time information. In this way could explore the possibility of how BIM and IoT could improve data-oriented facility management. The integration…

The study aims to assess the machine learning techniques in predicting students’ associated factors that affect their academic performance. The study sample consisted of 5084 middle and high school students between the ages of 10 and 17, attending public and UNRWA schools in the West Bank. The ‘Health Behaviors School Children’ questionnaire for the 2013-2014…

Presently, individuals generate tremendous volumes of information on the internet. As a result, sentiment analysis is a critical tool for automating a deep understanding of user-generated information. Of late, deep learning algorithms have shown endless promises for a variety of sentiment analysis. The purpose of sentiment analysis is to categorize different descriptions as good, bad,…

With the advent of Big Data, we are witnessing a rapid and varied production of huge amounts of sequential data that can have multiple dimensions, we speak of data streams. The characteristics of these data streams make their processing and storage very difficult and at the same time reduce the possibilities of querying them a…

The development of Machine Learning methods and approaches offers enormous growth opportunities in the Healthcare field. One of the most exciting challenges in this field is the automation of clinical treatment selection for patient state optimization. Using necessary medical data and the application of Machine Learning methods (like the Genetic Algorithm and the Analytic Hierarchy…

Technical safety and health are especially important for mining-extracting industry. Even though the respective lows and good engineering practices exist, technologies develop and could address even better security for humans and equipment. The research question is to survey microclimate sensors in underground mining and to find whether they are ready for automation. The article is…

In devices using Windows operating system based on x86 system, the real-time performance is not guaranteed by Windows. It is because Windows is not a real-time operating system. Users who develop applications in such a Windows environment generally use commercial solutions such as the RTX or the INtime to provide real-time performance to the system.…

The intention of this research is to study and design an automated agriculture commodity price prediction system with novel machine learning techniques. Due to the increasing large amounts historical data of agricultural commodity prices and the need of performing accurate prediction of price fluctuations, the solution has largely shifted from statistical methods to machine learning…

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…

Stepping-stone intrusion has been widely used by professional hackers to launch their attacks. Unfortunately, this important and typical offensive skill has not been taught in most colleges and universities. In this paper, after surveying the most popular detection techniques in stepping-stone intrusion, we develop 10 hands-on labs to enhance student-learning experience in cybersecurity education. The…