Nowadays, cloud computing is one of the important and rapidly growing services; its capabilities and applications have been extended to various areas of life. Cloud computing systems face many security issues, such as scalability, integrity, confiden...
Aviation is characterized by many stakeholders, long lifespans of its assets, and high requirements regarding safety, security, and documentation. To meet these requirements as well as customer needs, aircraft are regularly retrofitted with new cabin...
(1) Background: Properties and descriptors are two forms of molecular in silico representations. Properties can be further divided into functional, e.g., catalyst or drug activity, and material, e.g., X-ray crystal data. Millions of real measured fun...
This paper presents a mission data-handling algorithm that provides a data link interface between a flight control computer (FCC) and a ground control station (GCS) using the protocol standard STANAG 4586, AEP-84 Volume II. A subset of defined messag...
Permeability is an important petrophysical parameter that controls the fluid flow within the reservoir. Estimating permeability presents several challenges due to the conventional approach of core analysis or well testing, which are expensive and tim...
As one of the key technologies in spacecraft data-handling networks mounting high-resolution payloads, the multi-lane native SpaceFibre standard is designed to meet the demands for the high-speed and reliable interconnections between satellite payloa...
This paper utilizes computational fluid dynamics as well as a group method of data handling (GMDH) method to predict the mean velocity of intake. Firstly, the three dimensional flow pattern in a 90-degree intake is simulated with ANSYS-CFX at a trans...
Iron is one of the most applicable metals in the world. The global price of iron ore is determined based on demand and supply. There are numerous parameters (e.g., price of steel, steel production, oil price, gold price, interest rate, inflation rate...
The purpose of this study was to develop a data-driven predictive model that can predict the supply air temperature (SAT) in an air-handling unit (AHU) by using a neural network. A case study was selected, and AHU operational data from December 2015...
Fiber-reinforced polymer (FRP) is widely used in the field of structural engineering, for example, as a confining material for concrete. The ultimate conditions (i.e., compressive strength and ultimate axial strain) are key factors that need to be co...
Although the group method of data handling (GMDH) is a self-organizing metaheuristic neural network capable of developing a classification function using influential input variables, the results can be improved by using some pre-processing steps. In...
Disruptive failures threaten the reliability of electric supply in power branches, often indicated by the rise of leakage current in distribution insulators. This paper presents a novel, hybrid method for fault prediction based on the time series of...
In this article, two techniques that are congruous with the principle of control theory are utilized to estimate the state of health (SOH) of real-life plug-in hybrid electric vehicles (PHEVs) accurately, which is of vital importance to battery manag...
Nowadays, breast cancer is the most frequent cancer among women. Early detection is a critical issue that can be effectively achieved by machine learning (ML) techniques. Thus in this article, the methods to improve the accuracy of ML classification...
Electric load forecasting is indispensable for the effective planning and operation of power systems. Various decisions related to power systems depend on the future behavior of loads. In this paper, we propose a new input selection procedure, which...
The present research focuses on the machining of grade 2 titanium material using the Wire Electric Discharge Machining (WEDM) process by means of L16 Orthogonal Array (OA). This study investigates numerous process parameters, including pulse on time,...
SpaceFibre is an upcoming on-board high-speed communication protocol for space applications. It has been developed in collaboration with the European Space Agency to answer the growing data-rate requirement of satellite payloads such as Synthetic Ape...
Big geospatial raster data pose a grand challenge to data management technologies for effective big data query and processing. To address these challenges, various big data container solutions have been developed or enhanced to facilitate data storag...
Imbalanced data situations exist in most fields of endeavor. The problem has been identified as a major bottleneck in machine learning/data mining and is becoming a serious issue of concern in food processing applications. Inappropriate analysis of a...
Handling complexity in the data of information systems has emerged into a serious challenge in recent times. The typical relational databases have limited ability to manage the discrete and heterogenous nature of modern data. Additionally, the comple...
In road cycling, developing bike handling skills can prevent crashes and falls. Nevertheless, bike handling remains largely unexplored in the world of road cycling. The goal of this research was to develop a methodology to assess bike handling during...
The paper focuses on the identification of “bottlenecks” in the passenger handling process at the airports. In the current era of digital transformation and the emergence of Industry 4.0 and 5.0 concepts, optimizing passenger flows throug...
In supervised Activities of Daily Living (ADL) recognition systems, annotating collected sensor readings is an essential, yet exhaustive, task. Readings are collected from activity-monitoring sensors in a 24/7 manner. The size of the produced dataset...
The landscape of food analysis is being reshaped by the transformative power of data handling tools, including chemometrics, machine learning, and artificial intelligence (AI) [...]
In today’s era of increased food consumption, consumers have become more demanding in terms of safety and the quality of products they consume. As a result, food authorities are closely monitoring the food industry to ensure that products meet...
This paper presents data-driven modeling and a results analysis. Group method data handling (GMDH), multivariable regression (MVR), artificial neuron network (ANN), and new proposed GMDH-featured ANN machine learning algorithms were implemented to mo...
Medical data usually have missing values; hence, imputation methods have become an important issue. In previous studies, many imputation methods based on variable data had a multivariate normal distribution, such as expectation-maximization and regre...
Real-time emotion recognition from video poses significant challenges in handling large-scale and continuously growing datasets. Traditional relational databases often fail to meet the scalability and efficiency requirements of such applications. Mon...
The cargo handling capacity of a port is the most basic and important indicator of port size. Based on the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) nighttime light data and panel model, this study attempts to es...
As the field of data science grows, document analytics has become a more challenging task for rough classification, response analysis, and text summarization. These tasks are used for the analysis of text data from various intelligent sensing systems...
Addressing data anomalies (e.g., garbage data, outliers, redundant data, and missing data) plays a vital role in performing accurate analytics (billing, forecasting, load profiling, etc.) on smart homes’ energy consumption data. From the litera...
The developments in the fields of industrial Internet of Things (IIoT) and big data technologies have made it possible to collect a lot of meaningful industrial process and quality-based data. The gathered data are analyzed using contemporary statist...
Landslides can cause considerable loss of life and damage to property, and are among the most frequent natural hazards worldwide. One of the most fundamental and simple approaches to reduce damage is to prepare a landslide hazard map. Accurate predic...
Business information required for applications and business processes is extracted using systems like business rule engines. Since the advent of Big Data, such rule engines are producing rules in a big quantity whereas more rules lead to more complex...
Distracted driving leads to a significant number of road crashes worldwide. Smartphone use is one of the most common causes of cognitive distraction among drivers. Available data on drivers’ phone use presents an invaluable opportunity to ident...
This paper introduces the EGTL (extract, generate, transfer, load) model, a theoretical framework designed to enhance the traditional ETL processes by integrating a novel ‘generate’ step utilizing generative artificial intelligence (GenAI...
The Air Quality Index (AQI) dataset contains information on measurements of pollutants and ambient air quality conditions at certain location that can be used to predict air quality. Unfortunately, this dataset often has many missing observations and...
This manuscript addresses the problem of modeling an industrial (Sartorius) bioreactor using process data. In the context of the Sartorius Bioreactor, it is important to appropriately address the problem of dealing with a large number of variables, w...
The sudden increase in containerization volumes around the globe has increased the overall number of cargo losses, infrastructure damage, and human errors. Most critical losses occur during handling procedures performed by port cranes while sliding t...
25 April 2014
Objectives: To clarify the views of the general population of two countries (US and Japan), concerning the handling of their medical records electronically. Methods: We contacted people nationwide in the United States at random via Random Digit Diali...
22 June 2021
(1) Background: Propensity score methods gained popularity in non-interventional clinical studies. As it may often occur in observational datasets, some values in baseline covariates are missing for some patients. The present study aims to compare th...
It is getting popular to implement an environment where communications are performed remotely among IoT edge devices, such as sensory devices and the cloud servers due to applying, for example, artificial intelligence algorithms to the system. In suc...
The stable operation of air handling units (AHU) is critical to ensure high efficiency and to extend the lifetime of the heating, ventilation, and air conditioning (HVAC) systems of buildings. In this paper, an online data-driven diagnosis method for...
Background: The healthcare sector is currently undergoing a significant transformation, driven by an increased utilization of data. In this evolving landscape, surveys are of pivotal importance to the comprehension of patient needs and preferences. M...
In clinical datasets, missing data often occur due to various reasons including non-response, data corruption, and errors in data collection or processing. Such missing values can lead to biased statistical analyses, reduced statistical power, and po...
High-quality data are foundational to reliable environmental monitoring and urban planning in smart cities, yet challenges like missing values and outliers in air pollution and meteorological time series data are critical barriers. This study develop...
The Issue Tracking System (ITS) repositories are rich sources of software development documentation that are useful in assessing the status and quality of software projects. An original model is proposed for tracing issue handling activities and thei...
Due to the mechanical nature of container handling operations, as well as natural factors, container and handling infrastructure suffers various types of damage during use, especially within the tight and enclosed environments of a ship’s hull....
Identifying regions with similar meteorological features is of both socioeconomic and ecological importance. Towards that direction, useful information can be drawn from meteorological stations, and spread in a broader area. In this work, a time seri...
River discharge is an essential input to hydrosystem projects. This paper aimed to modify the group method of data handling (GMDH) to create a new artificial intelligent forecast model (abbreviated as MGMDH) for predicting discharges at river cross-s...
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