Due to the penetration of renewable energy and load variation in the microgrid, the diagnosis of power quality disturbances (PQD) is important to the operation stability and safety of the microgrid system. Once the power imbalance is present between...
A quickly growing location-based services area has led to increased demand for indoor positioning and localization. Undoubtedly, Wi-Fi fingerprint-based localization is one of the promising indoor localization techniques, yet the variation of receive...
Facial expression serves as the primary means for humans to convey emotions and communicate social signals. In recent years, facial expression recognition has become a viable application within medical systems because of the rapid development of arti...
Exploring the intention to prepare for mitigation among Filipinos should be considered as the Philippines is a country prone to natural calamities. With frequent earthquakes occurring in the country, “The Big One” has been predicted to da...
Vortex beams carry orbital angular momentum (OAM), and their inherent infinite dimensional eigenstates can enhance the ability for optical communication and information processing in the classical and quantum fields. The measurement of the OAM of vor...
Classification techniques, reliant on annotated data for autonomous decision training, have become pivotal tools in diverse domains. These techniques rely on models like Backpropagation Neural Networks (BPNNs). However, BPNNs frequently trap local op...
Brake forces and maximum static road friction coefficients for each wheel of the vehicle are essential information for vehicle safety systems including adaptive cruise control, electronic stability control (ESC), and collision avoidance system, etc....
29 June 2022
With the constant mutation of COVID-19 variants, the need to reduce the spread should be explored. MorChana is a mobile application utilized in Thailand to help mitigate the spread of the virus. This study aimed to explore factors affecting the actua...
In this paper, we evaluate different popular voting strategies for fusion of classifier results. A convolutional neural network (CNN) and different variants of random forest (RF) classifiers were trained to discriminate between 15 tree species based...
One of the central aspects of science is systematic problem-solving. Therefore, problem and solution statements are an integral component of the scientific discourse. The scientific analysis would be more successful if the problem–solution claims in...
The identification of maritime objects is crucial for ensuring navigational safety, enabling effective environmental monitoring, and facilitating efficient maritime search and rescue operations. Given its ability to provide detailed spectral informat...
This study proposes a lightweight classification framework for anomaly traffic detection in edge computing environments. Thirteen packet- and flow-level features extracted from the CIC-IDS2017 dataset were compressed into 4-dimensional latent vectors...
Holographic memory offers high-capacity optical storage with rapid data readout and long-term durability. Recently, read data pages have been classified using digital deep neural networks (DNNs). This approach is highly accurate, but the prediction t...
A reliable land cover (LC) map is essential for planners, as missing proper land cover maps may deviate a project. This study is focusing on land cover classification and prediction using three well known classifiers and remote sensing data. Maximum...
Side effects occur when excessive or low doses of analgesics are administered compared to the required amount to mediate the pain induced during surgery. It is important to accurately assess the pain level of the patient during surgery. We proposed a...
Objective neural network-based two-phase flow regime classifiers are developed for vertical, narrow, rectangular channels and a 1 inch round pipe using Kohonen Self-Organizing Maps. In the rectangular channel, the classifier uses five geometric input...
With an increasing number of mechanical components produced in the production pipeline, the need to classify past and new elements efficiently has been increasing. However, past methods of classifying elements have relied on traditional methods that...
In this paper, the aim is to classify torque signals that are received from a 3-DOF manipulator using a pattern recognition neural network (PR-NN). The output signals of the proposed PR-NN classifier model are classified into four indicators. The fir...
One of the modern trends in the design of human–machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms. In parti...
Classification of steel surface defects in steel industry is essential for their detection and also fundamental for the analysis of causes that lead to damages. Timely detection of defects allows to reduce the frequency of their appearance in the fin...
The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE) signals. To address this issue, a new approach is prop...
In this research, new modeling strategy based hierarchical growing neural gas network (HGNG)-semicooperative for feature classifier of intrusion detection system (IDS) in a vehicular ad hoc network (VANET). The novel IDS mainly presents a new design...
The complexity of brain tissue requires skillful technicians and expert medical doctors to manually analyze and diagnose Glioma brain tumors using multiple Magnetic Resonance (MR) images with multiple modalities. Unfortunately, manual diagnosis suffe...
Various defects are formed on the workpiece surface during the production process. Workpiece surface defects are classified according to various characteristics, which includes a bumped surface, scratched surface and pit surface. Suppliers analyze th...
Mammography is a first-line imaging examination that employs low-dose X-rays to rapidly screen breast tumors, cysts, and calcifications. This study proposes a two-dimensional (2D) spatial and one-dimensional (1D) convolutional neural network (CNN) to...
Some bands in the frequency spectrum have become overloaded and others underutilized due to the considerable increase in demand and user allocation policy. Cognitive radio applies detection techniques to dynamically allocate unlicensed users. Coopera...
In this study, we automate tree species classification and mapping using field-based training data, high spatial resolution airborne hyperspectral imagery, and a convolutional neural network classifier (CNN). We tested our methods by identifying seve...
The slowdown of Moore’s law and the existence of the “von Neumann bottleneck” has led to electronic-based computing systems under von Neumann’s architecture being unable to meet the fast-growing demand for artificial intellige...
Poor-quality sleep substantially diminishes the overall quality of life. It has been shown that sleep arousal serves as a good indicator for scoring sleep quality. However, patients are conventionally asked to perform overnight polysomnography tests...
When identifying the key features of the network intrusion signal based on the GA-RBF algorithm (using the genetic algorithm to optimize the radial basis) to identify the key features of the network intrusion signal, the pre-processing process of the...
This paper presents NeuroAdaptiveNet, an FPGA-based neural network framework that dynamically self-adjusts its architectural configurations in real time to maximize performance across diverse datasets. The core innovation is a Dynamic Classifier Sele...
Accurate prediction of the impact of genetic variants on human health is of paramount importance to clinical genetics and precision medicine. Recent machine learning (ML) studies have tried to predict variant pathogenicity with different levels of su...
Palpitations, chest tightness, and shortness of breath are early indications of cardiomegaly, which is an asymptomatic disease. Their causes and treatment strategies are different due to differing indications. Hence, early screening of cardiomegaly l...
Detecting instruments in a music signal is often used in database indexing, song annotation, and creating applications for musicians and music producers. Therefore, effective methods that automatically solve this issue need to be created. In this pap...
This paper develops a primitive gas recognition system for discriminating between industrial gas species. The system under investigation consists of an array of eight micro-hotplate-based SnO2 thin film gas sensors with different selectivity patterns...
In today’s world, a brain tumor is one of the most serious diseases. If it is detected at an advanced stage, it might lead to a very limited survival rate. Therefore, brain tumor classification is crucial for appropriate therapeutic planning to...
One of the current focuses of modern bioinformatics is the development of hybrid models to process gene expression data, in order to create diagnostic systems for various diseases. In this study, we propose a solution to this problem that combines an...
17 May 2022
The continuous rise of the COVID-19 Omicron cases despite the vaccination program available has been progressing worldwide. To mitigate the COVID-19 contraction, different contact tracing applications have been utilized such as Thai Chana from Thaila...
Background: Accurate and reliable classification models play a major role in clinical decision-making processes for prostate cancer (PCa) diagnosis. However, existing methods often demonstrate limited performance, particularly when applied to small d...
Binarized convolutional neural networks (bCNNs) are favored for the design of low-storage, low-power cardiac arrhythmia classifiers owing to their high weight compression rate. However, multi-class classification of ECG signals based on bCNNs is chal...
Rapid urbanization in cities can result in a decrease in green urban areas. Reductions in green urban infrastructure pose a threat to the sustainability of cities. Up-to-date maps are important for the effective planning of urban development and the...
In aerospace, marine, and other heavy industries, bearing fault diagnosis has been an essential part of improving machine life, reducing economic losses, and avoiding safety problems caused by machine bearing failures. Most existing bearing fault dia...
Deep neural networks (DNNs) face many problems in the very high resolution remote sensing (VHRRS) per-pixel classification field. Among the problems is the fact that as the depth of the network increases, gradient disappearance influences classificat...
This paper presents a novel, autonomous learning system working in real-time for face recognition. Multiple convolutional neural networks for face recognition tasks are available; however, these networks need training data and a relatively long train...
The assignment of secondary structure elements in protein conformations is necessary to interpret a protein model that has been established by computational methods. The process essentially involves labeling the amino acid residues with H (Helix), E...
Predictions of cutting vibrations are necessary for improving the operational efficiency, product quality, and safety in the machining process, since the vibration is the main factor for resulting in machine faults. “Cutting vibration” may be caused...
Speech signals carry various bits of information relevant to the speaker such as age, gender, accent, language, health, and emotions. Emotions are conveyed through modulations of facial and vocal expressions. This paper conducts an empirical comparis...
Since the rules and regulations strongly emphasize environmental preservation and greenhouse gas GHG reduction, researchers have progressively noticed a shift in the transportation means toward electromobility. Several challenges must be resolved to...
This paper first studies the generalization ability of the convolutional layer as a feature mapper (CFM) for extracting image features and the classification ability of the multilayer perception (MLP) in a CNN. Then, a novel generalized hybrid probab...
This paper presents an interpretable, spiking neural classifier (IpT-SNC) with time-varying weights. IpT-SNC uses a two-layered spiking neural network (SNN) architecture in which weights of synapses are modeled using amplitude-modulated, time-varying...
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