The measurement of reverberation time is an essential procedure for the characterization of the acoustic performance of rooms. The values returned by these measurements allow us to predict how the sound will be transformed by the walls and furnishing...
A pharmaceutical supply chain (PSC) is a system of processes, operations, and organisations for drug delivery. This paper provides a new PSC mathematical cost model, which includes Blockchain technology (BT), that can improve the safety, performance,...
In this work, the quantum random walk search algorithm with a walk coin constructed by generalized Householder reflection and phase multiplier has been studied. The coin register is one qudit with an arbitrary dimension. Monte Carlo simulations, in c...
Chinese medical texts contain a large number of medically named entities. Automatic recognition of these medical entities from medical texts is the key to developing medical informatics. In the field of Chinese medical information extraction, annotat...
Existing stream data learning models with limited labeling have many limitations, most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data, which is called concept drift. Hence, the algorithm must ove...
Cost prediction can provide a pharma supply chain industry with completing their projects on schedule and within budget. This paper provides a new multi-function Blockchain Technology-enabled Pharmaceutical Supply Chain (BT-enabled PSC) mathematical...
Background: Oro-antral communication (OAC) is a common complication following the extraction of upper molar teeth. The Archer and the Root Sinus (RS) systems can be used to classify impacted teeth in panoramic radiographs. The Archer classes B-D and...
This work investigated machine-learning algorithms for remote-control and autonomous operation of the Very-Small, Long-Life, Modular (VSLLIM) microreactor. This walk-away safe reactor can continuously generate 1.0–10 MW of thermal power for 92...
Recently, various sophisticated methods, including machine learning and artificial intelligence, have been employed to examine health-related data. Medical professionals are acquiring enhanced diagnostic and treatment abilities by utilizing machine l...
Reactive oxygen species (ROS) are compounds that readily transform into free radicals. Excessive exposure to ROS depletes antioxidant enzymes that protect cells, leading to oxidative stress and cellular damage. Nanomaterials (NMs) exhibit free radica...
This study presents the development and validation of a robust semi-supervised learning framework specifically designed for the automated segmentation and classification of sandstone thin section images from the Yanchang Formation in the Ordos Basin....
In this paper, two improvements in precipitation classification have been performed. Supervised machine learning has demonstrated considerable performances in classification tasks. However, supervised machine learning can only be applied to labeled d...
26 June 2020
The emergence of new technologies to incorporate and analyze data with high-performance computing has expanded our capability to accurately predict any incident. Supervised Machine learning (ML) can be utilized for a fast and consistent prediction, a...
Remote sensing data proved to be a valuable resource in a variety of earth science applications. Using high-dimensional data with advanced methods such as machine learning algorithms (MLAs), a sub-domain of artificial intelligence, enhances lithologi...
Semi-supervised learning algorithms have become a topic of significant research as an alternative to traditional classification methods which exhibit remarkable performance over labeled data but lack the ability to be applied on large amounts of unla...
The traditional spectrum sensing algorithm based on deep learning requires a large number of labeled samples for model training, but it is difficult to obtain them in the actual sensing scene. This paper applies self-supervised contrast learning in o...
Rolling bearing is of great importance in modern industrial products, the failure of which may result in accidents and economic losses. Therefore, fault diagnosis of rolling bearing is significant and necessary and can enhance the reliability and eff...
Science seeks strategies to mitigate global warming and reduce the negative impacts of the long-term use of fossil fuels for power generation. In this sense, implementing and promoting renewable energy in different ways becomes one of the most effect...
Over time, human beings have built increasingly large astronomical observatories to increase the number of discoveries related to celestial objects. However, the amount of collected elements far exceeds the human capacity to analyze findings without...
The introduction of a consortium blockchain-based agricultural machinery scheduling system will help improve the transparency and efficiency of the data flow within the sector. Currently, the traditional agricultural machinery centralized scheduling...
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares pro...
Efficient toll processing is critical for mitigating traffic congestion and enhancing transportation network efficiency at toll stations. This study explores the Neelamangala Toll Plaza on India’s National Highway 48, employing artificial intelligenc...
Convolution neural networks usually require large labeled data-sets to construct accurate models. However, in many real-world scenarios, such as global illumination, labeling data are a time-consuming and costly human intelligent task. Semi-supervise...
The plywood industry is one of the most significant sub-sectors of the forestry industry and serves as a cornerstone of sustainable construction within a bioeconomy framework. Plywood is a panel composed of multiple layers of wood sheets bonded toget...
Change detection is an essential and widely utilized task in remote sensing that aims to detect and analyze changes occurring in the same geographical area over time, which has broad applications in urban development, agricultural surveys, and land c...
Early diagnosis and classification of arrhythmia from an electrocardiogram (ECG) plays a significant role in smart healthcare systems for the health monitoring of individuals with cardiovascular diseases. Unfortunately, the nonlinearity and low ampli...
Structured Query Language injection (SQLi) remains a persistent threat to web applications due to the obfuscation, diversity, and evolving structure of malicious payloads, which limit the effectiveness of conventional rule and signature-based Web App...
To address the decision-making requirements for drainage gas recovery in horizontal gas wells within low-permeability tight reservoirs, this study proposes an intelligent classification approach that integrates supervised and unsupervised learning te...
Image matting methods based on deep learning have made tremendous success. However, the success of previous image matting methods typically relies on a massive amount of pixel-level labeled data, which are time-consuming and costly to obtain. This pa...
The aim of this study is to identify and classify the most important factors affecting patient satisfaction in the COVID-19 pandemic crisis considering economic effects. This is an analytical study using the analytic hierarchy process (AHP) method an...
We propose a novel approach for time series forecasting with many predictors, referred to as the GO-sdPCA, in this paper. The approach employs a variable selection method known as the group orthogonal greedy algorithm and the high-dimensional Akaike...
The parametric fault diagnosis of analog circuits is very crucial for condition-based maintenance (CBM) in prognosis and health management. In order to improve the diagnostic rate of parametric faults in engineering applications, a semi-supervised ma...
The evaluation of car drivers’ stress condition is gaining interest as research on Autonomous Driving Systems (ADS) progresses. The analysis of the stress response can be used to assess the acceptability of ADS and to compare the driving styles...
Urban freight transport is an essential component of urban mobility, playing a key role in supporting the economic and social development of cities. However, the growth of freight and delivery activities can intensify energy consumption and increase...
This study aims to provide a method that will assist decision makers in managing large datasets, eliminating the decision risk and highlighting significant subsets of data with certain weight. Thus, binary decision tree (BDT) and genetic algorithm (G...
Classification is a core supervised learning task in data analysis, and six classical classifier families (k-Nearest Neighbors, Support Vector Machine, Decision Tree, Random Forest, Logistic Regression, and Naïve Bayes) remain widely used in pra...
The annotation of magnetic resonance imaging (MRI) images plays an important role in deep learning-based MRI segmentation tasks. Semi-automatic annotation algorithms are helpful for improving the efficiency and reducing the difficulty of MRI image an...
Deep learning-based object detection technology is rapidly developing, and underwater object detection, an important subcategory, plays a crucial role in various fields such as underwater structure repair and maintenance, as well as marine scientific...
Human motion recognition based on wearable devices plays a vital role in pervasive computing. Smartphones have built-in motion sensors that measure the motion of the device with high precision. In this paper, we propose a human lower limb motion capt...
Introducing computational thinking at elementary school can develop students’ capabilities and interest in Computing skills. In this study, we introduced the Computer Science unplugged (CS-unplugged) technique in Pakistan. We use paper-based ac...
Supervisory Control and Data Acquisition (SCADA) systems play a significant role in providing remote access, monitoring and control of critical infrastructures (CIs) which includes electrical power systems, water distribution systems, nuclear power p...
Crops and ecosystems constantly change, and risks are derived from heavy rains, hurricanes, droughts, human activities, climate change, etc. This has caused additional damages with economic and social impacts. Natural phenomena have caused the loss o...
Although Kyphosis, an excessive forward rounding of the upper back, can occur at any age, adolescence is the most common time for Kyphosis. Surgery is frequently performed on Kyphosis patients; however, the condition may persist after the operation....
This study presents a decision tree model-based approach to classify rural net migration across Colombian departments using sociodemographic and economic variables. In the model formulation, immigration is considered the movement of people to a desti...
Modern approaches to computing consumer price indices include the use of various data sources, such as web-scraped data or scanner data, which are very large in volume and need special processing techniques. In this paper, we address one of the main...
Oil drilling is the core process of oil and natural gas resources exploitation. Well overflow is one of the biggest threats to safety drilling. Prediction of the overflow in advance can effectively avoid the occurrence of this kind of accident. Howev...
At present, machine sense of smell has shown its important role and advantages in many scenarios. The development of machine sense of smell is inseparable from the support of corresponding data and algorithms. However, the process of olfactory data c...
Intrusion detection systems face significant challenges, including the inability to detect unknown threats and imbalances between normal and anomalous traffic. To address these limitations, we propose a semi-supervised intrusion detection algorithm b...
We propose a generalized supervised learning algorithm for multilayer photonic spiking neural networks (SNNs) by combining the spike-timing dependent plasticity (STDP) rule and the gradient descent mechanism. A vertical-cavity surface-emitting laser...
Due to the high cost of annotating dense fruit images, annotated target images are limited in some ripeness detection applications, which significantly restricts the generalization ability of small object detection networks in complex environments. T...
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