Floating-point arithmetic is a common computational method, used to represent large or infinite space in software, such as game engines. This paper explores floating-point arithmetic in the game engine Unity, as it renders an infinitely falling objec...
The arithmetic optimization algorithm (AOA) is a new metaheuristic algorithm inspired by arithmetic operators (addition, subtraction, multiplication, and division) to solve arithmetic problems. The algorithm is characterized by simple principles, few...
To overcome the challenges posed by the underwater environment and restore the true colors of marine objects’ surfaces, a novel underwater image illumination estimation model, termed the iterative chaotic improved arithmetic optimization algori...
This article presents a machine vision system for measuring the arithmetic average roughness of shot- and sand-blasted surfaces. In the developed system, a digital microscope was used for capturing surface images after shot- and sand-blasting process...
Precise water quality forecasting is vital for sustainable resource management and public health, especially in semi-arid environments. This study investigates the predictive capabilities of ten Machine Learning (ML) algorithms using a dataset of 308...
In this paper, we consider the application of brute force computational techniques (BFCTs) for solving computational problems in mathematical analysis and matrix algebra in a floating-point computing environment. These techniques include, among other...
The Moving Picture Experts Group (MPEG) is developing the Video Coding for Machines (VCM) standard to support efficient video compression for machine vision tasks. The VCM standard primarily targets object detection, tracking, and semantic segmentati...
Mental fatigue is a widely studied topic on account of its serious negative effects. But how the neural mechanism of task switching before and after mental fatigue remains a question. To this end, this study aims to use brain functional network featu...
Background/Objectives: This article addresses the challenge of stress detection across diverse contexts. Mental stress is a worldwide concern that substantially affects human health and productivity, rendering it a critical research challenge. Althou...
Currently, mental stress is a common social problem affecting people. Stress reduces human functionality during routine work and may lead to severe health defects. Detecting stress is important in education and industry to determine the efficiency of...
Multimaterial hybrid compounds formed from lightweight structural materials have been acquiring great importance in recent years in the aeronautical and automotive sectors, where they are replacing traditional materials to reduce the mass of vehicles...
Complex systems are usually affected by various sources of uncertainty, and it is essential to account for mechanisms that ensure the proper management of such disturbances. This paper introduces a novel approach to solve symbolic regression problems...
In recent years, people’s quality of life has increased, and the requirements for fruits have also become higher; blueberries are particularly popular because of their rich nutrients. In the blueberry industry chain, sensory evaluation is an im...
Feature selection is a well-known prepossessing procedure, and it is considered a challenging problem in many domains, such as data mining, text mining, medicine, biology, public health, image processing, data clustering, and others. This paper propo...
This paper focused on the maintenance or repair of holes made using hybrid Mg–Al–Mg components by drilling, using two sustainable cooling techniques (dry machining and cold compressed air) and taking surface roughness on the inside of the...
Approximate computation has emerged as a promising alternative to accurate computation, particularly for applications that can tolerate some degree of error without significant degradation of the output quality. This work analyzes the application of...
To improve the accuracy of coal and gas prominence prediction, an improved sparrow search algorithm (ISSA) and an optimized support vector machine (SVM) based on the Markov chain Monte Carlo (MCMC) filling algorithm prediction model were proposed. Th...
Mental workload assessment using physiological signals has gained increasing attention for applications in human–computer interaction and occupational monitoring. Among these signals, electrodermal activity (EDA) is widely recognised as a relia...
Surface quality is one of the most important indicators of the quality of machined parts. The analytical method of defining the arithmetic mean roughness is not applied in practice due to its complexity and empirical models are applied only for certa...
Single-valued neutrosophic numbers (SVNNs) can express incomplete, indeterminate, and inconsistent information in the real world. Then, the common weighted aggregation operators of SVNNs may result in unreasonably aggregated results in some situation...
K9 optical glass has superb material properties used for various industrial applications. However, the high hardness and low fracture toughness greatly fluctuate the cutting force generated during the grinding process, which are the main factors affe...
Approximate arithmetic circuits are an attractive alternative to accurate arithmetic circuits because they have significantly reduced delay, area, and power, albeit at the cost of some loss in accuracy. By keeping errors due to approximate computatio...
Vector normalization is an important process in several algorithms. It is used in classical physical calculations, mathematical techniques, and machine learning, which has witnessed significant advancements in recent years. Normalization and regulari...
With the fast advances in computational sciences, there is a need for more accurate computations, especially in large-scale solutions of differential problems and long-term simulations. Amid the many numerical approaches to solving differential probl...
Interest in surface integrity has grown in the manufacturing industry; indeed, it has become an integral part of the industry. It can be studied by examining surface roughness parameters, hardness variations, and microstructure. However, evaluating a...
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In order to perform quantitative analysis and predict the wear of the forming channel, this study makes biomass pellets as experimental samples. The surface morphology was scanned by a scanning electron microscope (SEM), and the surface morphology da...
Sago palm (Metroxylon sagu) is a palm tree species originating in Indonesia. In the future, this starch-producing tree will play an important role in food security and biodiversity. Local governments have begun to emphasize the sustainable developmen...
Data-driven models used for predictive classification and regression tasks are commonly computed using floating-point arithmetic and powerful computers. We address constraints in distributed sensor networks like the IoT, edge, and material-integrated...
Bringing out brain activity through the interpretation of EEG signals is a challenging problem that involves combined methods of signal analysis. The issue of classifying mental states induced by arithmetic tasks can be solved through various classif...
Electrochemical milling is an ideal technique for machining large-scale 3D structures that consist of aerospace aluminum alloys. The distribution of the electric and flow fields are vital to the quality of the machined surface, and the structures of...
This article presents the results of a comprehensive study of the performance of zirconia-toughened and mixed-alumina ceramic tools in CNC turning of 42CrMo4 steel with hardnesses of 35, 40, and 45 HRC. Empirical models have been developed for the cu...
Access to clean drinking water is crucial for any region’s social and economic growth. However, rapid urbanization and industrialization have significantly deteriorated water quality, posing severe pollution threats from domestic, agricultural,...
The purpose of this study was to determine the effect of selected vibratory strengthening machining factors on the properties of CuZn30 brass. Vibratory strengthening machining was carried out using metal media dedicated to polishing processes, which...
This article shows the three-dimensional (3D) modelling and virtual reconstruction of the first mechanical calculating machine used for accounting purposes designed by Blaise Pascal in 1642. To obtain the 3D CAD (computer-aided design) model and the...
In optical computing machines, data can be transmitted by optical vortices, and the information can be encoded by their topological charges. Thus, some optical mechanisms are needed for performing simple arithmetic operations with the topological cha...
We present Hyperbolic Symmetric Hypermodular Neural Operators (ONHSH), a novel operator learning framework for solving partial differential equations (PDEs) in curved, anisotropic, and modularly structured domains. The architecture integrates three c...
The emergence of artificial intelligence (AI) driven keyword spotting (KWS) technologies has revolutionized human to machine interaction. Yet, the challenge of end-to-end energy efficiency, memory footprint and system complexity of current neural net...
This study proposes a dual-statistical and gradient-based framework to evaluate the machinability of five engineering alloys under CNC turning. Cutting force and surface deformation were measured across five machining zones. Finite difference-based g...
The paper outlines a methodology for validating the accuracy of a control system’s runtime implementation. The runtime takes the form of a virtual machine executing portable code compliant with IEC 61131-3 standards. A formal model, comprising...
The number of Artificial Intelligence (AI) and Machine Learning (ML) designs is rapidly increasing and certain concerns are raised on how to start an AI design for edge systems, what are the steps to follow and what are the critical pieces towards th...
The article presents a methodology for multi-objective compromise optimization of the process of turning on CNC machines with robotic loading by the methods of determining the optimum compromise area and carrying out optimization, using the generaliz...
Elliptic Curve Cryptography (ECC) is a technology based on the arithmetic of elliptic curves used to build strong and efficient cryptosystems and infrastructures. Several ECC systems, such as the Diffie–Hellman key exchange and the Elliptic Cur...
The surface of machine elements is changed to improve their mechanical properties. Ceramic-metal composite coatings are mainly used to increase the durability of machine parts. Therefore, new materials are constantly searched for application in the f...
Following trends that emphasize neural networks for machine learning, many studies regarding computing systems have focused on accelerating deep neural networks. These studies often propose utilizing the accelerator specialized in a neural network an...
The most recent generations of graphics processing units (GPUs) boost the execution of convolutional operations required by machine learning applications by resorting to specialized and efficient in-chip accelerators (Tensor Core Units or TCUs) that...
This article deals with electrical discharge machining (EDM) of an alnico alloy, focusing on how key process parameters affect the surface finish. The experiments were conducted using a BP93L EDM machine. The Box–Behnken design was employed to...
Image convolution is a commonly required task in machine vision and Convolution Neural Networks (CNNs). Due to the large data movement required, image convolution can benefit greatly from in-memory computing. However, image convolution is very comput...
This paper presents the research results of one of the main technological parameters of belt grinding, i.e., the cutting speed while machining corrosion- and heat-resistant, structural carbon and structural alloy steels, aluminum, and heat-resistant...
As it is urgent to change the traditional audit sampling method that is based on manpower to meet the growing audit demand in the era of big data. This study uses empirical methods to propose a full population auditing method based on machine learnin...
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