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The article is devoted to the methods of monitoring and control of vibration processes occurring in the structure and units of complex and unique electromechanical equipment. The monitoring object is considered as a dynamic multidimensional information object, for the study of which analytical and numerical methods of modeling and simulation of multidimensional chaotic systems are…

Various interruptions to the daily lives of researchers have necessitated the usage of simulations in projects which may not have initially relied on anything other than physical inquiry and experiments. The programs and algorithms introduced in this paper, which is an extended version of research initially published in ARAIG And Minecraft: A COVID-19 Workaround, create…

This paper presents the design and implementation of a low-cost basket based on an ARM system on chip architecture using Raspberry Pi single board computer. The inspiration of this research is how to support the traditional low-income retail store in Thailand driving the local micro-business deal with the economic impacts of survival business from the…

Redundant robotic systems provide great challenges in solving kinematics and control problems, that are yet also open opportunities for exploring new, diverse and intelligent ideas and methods. In this paper, an advanced control method is proposed for position control problems of redundant robots with output constraints. The controller is structured with two control layers. In…

The Internet of Things (IoT) is the evolving paradigm of interconnectedness of objects with varied architectures and resources to provide ubiquitous and desired services. The popularization of IoT-connected devices facilitating evolution of IoT applications does come with security challenges. The IoT with the integration of wireless sensor networks possess a number of unique characteristics, so…

The use of decentralized reinforcement learning (RL) in the context of multi-agent systems (MAS) poses some difficult problems. The speed of the learning process for example. Indeed, if the convergence of these algorithms has been widely studied and mathematically proven, they suffer from being very slow. In this context, we propose to use RL in…

Predicting the credit card default is important to the bank and other lenders. The credit default risk directly affects the interest charged to the borrower and the business decision of the lenders. However, very little research about this problem used the Generalized Linear Model (GLM). In this paper, we apply the GLM to predict the…

The main purpose in this work is to explore the fact that chaos, as a biological characteristic in the brain, should be used in an Artificial Neural Network (ANN) system. In fact, as long as chaos is present in brain functionalities, its properties need empirical investigations to show their potential to enhance accuracies in artificial…

The present work develops an estimator for thermal conductivity using a simple exper- iment implemented in a simulated solid metallic bar. The bar is sectioned in a finite number of segments, lately called nodes, and a discretization of the Fourier heat equation is applied in each node to generate a timed-spaced model of the temperature…

C programming is taught in a lot of universities across the world as the first computer programming language. Then, for novice students, it is important to read many simple C source codes and understand their behaviors to be familiar to the programming paradigm. Unfortunately, effective tools to support independent code reading study at home have…

The Japanese writing system is unique due to the number of characters employed and the methods used to write words. It consists of three different ’alphabets’, which may result in the methods used to process Latin script not being sufficient to obtain satisfactory results when attempting to apply them to a recognition of the Japanese…

Data stream gained obvious attention by research for years. Mining this type of data generates special challenges because of their unusual nature. Data streams flows are continuous, infinite and with unbounded size. Because of its accuracy, decision tree is one of the most common methods in classifying data streams. The aim of classification is to…

The deep learning-based URL classification approach using massive observations has been verified especially in the field of phishing attack detection. Various improvements have been achieved through the modeling of character and word sequence of URL based on convolutional and recurrent neural networks, and it has been proven that an ensemble approach of each model has…

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 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…

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…

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,…

Quantum logic gates represent certain quantum operations to perform quantum computations. Of those quantum gates, there is a category of classical behavior gates called quantum permutation gates. As a quantum algorithm, quantum permutation pad or QPP consists of multiple quantum permutation gates to be implemented both in a quantum computing system as a quantum circuit…

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…

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…

To effectively implement the social distancing or digital contact tracing in epidemic using an RSSI-based localization approach through Bluetooth beacon is one of the most widely used technologies, but simply using RSSI measurement is not more relevant because the RF signal is affected by several factors and the environment of usage. Traditional distance or positioning…

Identification of Kamphaeng Saen beef cattle is important of the registration and traceability purposes. For a traditional identification methods, Hot Branding, Freeze Branding, Paint Branding, and RFID Systems can be replaced by genius human. This paper proposed a Kamphaeng Saen beef cattle identification approach using muzzle print images as an Animal Biometric approach. There are…

The Hamming neural network is an effective tool for solving problems of recognition and classification of objects, the components of which are encoded using a binary bipolar alphabet, and as a measure of the objects’ proximity the difference between the number of identical bipolar components which compared include objects and the Hamming distance between them…