In order to improve the efficiency of the “last-mile” distribution in urban logistics and solve the problem of the difficult charging of electric logistics vehicles (ELVs), this paper proposes a charging station location optimization sche...
The world has adopted so many IoT devices but it comes with its own share of security vulnerabilities. One such issue is ARP spoofing attack which allows a man-in-the-middle to intercept packets and thereby modify the communication. Also, this allows...
Due to the gradual improvement of urban traffic network construction and the increasing number of optional paths between any two points, how to optimize a vehicle travel path in a multi-path road network and then improve the efficiency of urban distr...
Reliable estimation of the air change rate from CO2 decay measurements is essential for ventilation assessment, but results may strongly depend on the assumed background concentration and the selected analysis window. This study compares the ISO 1256...
In recent years, machine learning, a popular artificial intelligence technique, has been successfully applied to monthly runoff forecasting. Monthly runoff autoregressive forecasting using machine learning models generally uses a sliding window algor...
Uncertainty analysis is considered to be a necessary step in the process of vessel traffic risk assessment. The purpose of this study is to propose the uncertainty analysis algorithm which can be used to investigate the reliability of the risk assess...
China’s freshwater resources are relatively small per capita, and the traditional passive control of hydrographic outbreaks can no longer meet modern water management needs. Data-driven models, such as Long Short-Term Memory Networks (LSTMs), h...
This paper considers vital signs (VS) such as respiration movement detection of human subjects using an impulse ultra-wideband (UWB) through-wall radar with an improved sensing algorithm for random-noise de-noising and clutter elimination. One filter...
In the algorithm selection problem, where the task is to identify the most suitable solving technique for a particular situation, most methods used as performance mapping mechanisms have been relatively simple models such as logistic regression or ne...
Antiviral pulse dosing is shaped by discrete dosing events, two-compartment pharmacokinetics, nonlinear pharmacodynamics, and resistance evolution. To characterize sustained suppression, resistance accumulation, and risk-cost tradeoffs within a unifi...
Aiming at the problem of multimodal transport path planning under uncertain environments, this paper establishes a multi-objective fuzzy nonlinear programming model considering mixed-time window constraints by taking cost, time, and carbon emission a...
This paper presents an adaptive noise-aware bearing fault diagnosis framework that integrates Fast Fourier Transform (FFT)-windowed feature extraction, wavelet-based Signal-to-Noise Ratio (SNR) estimation, and Long Short-Term Memory (LSTM) classifica...
To address the multi-objective conflicts among cost, time, and carbon emissions in Guangxi cross-border container multimodal transport—under the influence of factors such as tariffs, fluctuating customs clearance efficiency, and carbon emission...
X-rays emitted by the Sun can damage electronic devices of spaceships, satellites, positioning systems and electricity distribution grids. Thus, the forecasting of solar X-rays is needed to warn organizations and mitigate undesirable effects. Traditi...
A 90-year-old woman developed a severe stroke (National Institutes of Health Stroke Scale Score (NIHSS) 24) due to an occlusion of the left carotid T. Computed tomography 60 min after symptom onset showed a large area of tissue at risk with a relativ...
The streamflow of the upper reaches of the Yangtze River exhibits different timing and periodicity characteristics in different quarters and months of the year, which makes it difficult to predict. Existing sliding window-based methods usually use a...
The synchronization of time between devices is one of the more important and challenging problems in wireless networks. We discuss the problem of maximization of the probability of receiving a message from a device using a limited listening time wind...
This paper studies the multi-trip vehicle routing problem with multiple time windows, which extends the multi-trip vehicle routing problem by deciding not only the sequence of customers that each vehicle serves but also the service time window of eac...
Hard disk failure prediction is an important proactive maintenance method for storage systems. Recent years have seen significant progress in hard disk failure prediction using high-quality SMART datasets. However, in industrial applications, data lo...
In this paper, the window-opening behavior in a three-star green building with an operation mark in Ningbo was investigated. Four single offices facing south were selected, and the measurement lasted 20–40 days in the cooling season. An analysi...
Background: Blood-accessible biomarkers may support future personalization of prostate cancer radiotherapy, but their interpretation depends on sampling timing relative to radiotherapy, androgen deprivation therapy, and post-treatment recovery. We ma...
Order picking is a crucial operation in the storage industry, with a significant impact on storage efficiency and cost. Responding quickly to customer demands and shortening picking time is crucial given the random nature of order arrival times and q...
In autonomous manufacturing systems, the performance of time-series-based anomaly detection and fault diagnosis is highly sensitive to window size selection. Conventional approaches rely on empirical rules or fixed window settings, which often fail t...
To meet power quality requirements, it is necessary to classify and identify the power quality of the power grid connected with renewable energy generation. S-transform (ST) is an effective method to analyze power quality in time and frequency domain...
MODerate resolution Imaging Spectroradiometer (MODIS) data are largely used in multitemporal analysis of various Earth-related phenomena, such as vegetation phenology, land use/land cover change, deforestation monitoring, and time series analysis. In...
Algal blooms in freshwater ecosystems can negatively impact aquatic and human health. Satellite remote sensing of chlorophyll a (Chl-a) is often used to help determine the severity of algal blooms. However, satellite revisit flyover schedules may not...
Multivariate time series prediction models perform the required operation on a specific window length of a given input. However, capturing complex and nonlinear interdependencies in each temporal window remains challenging. The typical attention mech...
The properties of the Gabor and Morlet transforms are examined with respect to the Fourier analysis of discretely sampled data. Forward and inverse transform pairs based on a fixed window with uniform sampling of the frequency axis can satisfy numeri...
Leak detection is nowadays an important task for water utilities as leakages in water distribution systems (WDS) increase economic costs significantly and create water resource shortages. Monitoring data such as pressure and flow rate of WDS fluctuat...
Modern lifestyles result in people spending 90% of their time indoors, where windows serve as a unique component providing an outdoor view and enabling visual experiences. Chromogenic windows, which adjust both thermal and visual conditions, represen...
Modal parameters can reflect the dynamic characteristics of the structure and can be used to control vibration. To identify the operational modal parameters of linear slow-time-varying structures only from non-stationary vibration response signals, a...
This study proposes electrocardiogram (ECG) identification based on non-fiducial feature extraction using window removal method, nearest neighbor (NN), support vector machine (SVM), and linear discriminant analysis (LDA). In the pre-processing stage,...
For gait phase estimation, time-series data of lower-limb motion can be segmented according to time windows. Time-domain features can then be calculated from the signal enclosed in a time window. A set of time-domain features is used for gait phase e...
As inverter-based renewable generation increases, load modeling from ambient measurements is important for power-system stability assessment. Under ambient conditions, voltage and frequency variations are small, whereas time-varying nominal power can...
The international crude oil market plays an important role in the global economy. This paper uses a variable time window and the polynomial decomposition method to define the trend term of time series and proposes a crude oil price forecasting method...
By combining the spectral and texture features of images captured by unmanned aerial vehicles (UAVs), the accurate and timely detection of wheat Fusarium head blight (FHB) can be realized. This study presents a methodology to select the optimal windo...
Human detection using visible surveillance sensors is an important and challenging work for intruder detection and safety management. The biggest barrier of real-time human detection is the computational time required for dense image scaling and sca...
In modern electrical power distribution systems, the effective operation of inverter-based arc suppression devices relies on the accuracy of faulty phase selection. In the traditional methods of faulty phase selection for single-phase-to-ground fault...
In this study, we analyzed angular-selective absorption in a guest–host liquid crystal (GHLC) cell for its application in smart windows. For reducing the energy consumption, angular-selective absorption is desired because the light transmitted...
Background/Objectives: Genomic selection (GS) has improved accuracy compared to traditional methods. However, accuracy tends to plateau beyond a certain marker density. Prioritizing influential SNPs could further enhance the accuracy of GS. The fixat...
High time resolution spectrum occupancy measurements and analysis are presented for 2.4 GHz WLAN signals. A custom-designed wideband sensing engine records the received power of signals, and its performance is presented to select the decision thresho...
Ultra-short-term HRV features assess minor autonomous nervous system variations such as variations resulting from cognitive stress peaks during demanding tasks. Several studies compare ultra-short-term and short-term HRV measurements to investigate t...
We propose a new methodology to transform a time series into an ordered sequence of any entropic and information functionals, providing a novel tool for data analysis. To achieve this, a new algorithm has been designed to optimize the Probability Den...
This paper presents a new sensory system based on advanced algorithms and machine learning techniques that provides sensory gloves with the ability to ensure real-time connection of all connectors in the cabling of a cockpit module. Besides a microph...
Monitoring the genetic variance of traits is a key priority to ensure the sustainability of breeding programmes in populations under directional selection, since directional selection can decrease genetic variation over time. Studies monitoring chang...
Background: Industrial power time-series exhibit strong daily/weekly periodicities and nonstationary behaviors that challenge generic deep autoencoders. Methods: We take first differences of the signal, compute the FFT spectrum, and map top spectral...
In the 2.4 GHz band, the channel of a short-range link is usually selected at one end; in Bluetooth Low Energy, a peripheral’s channel classification is advisory. This paper examines, for one instrumented case, whether the two ends of a link pe...
Digital holographic microscopy has significant advantages over traditional 3D measurements. In order to obtain a reconstructed image of superior quality, the zero-order-term spectrum and the −1 term spectrum must be eliminated during the digita...
Thermochromic windows can dynamically modulate solar radiation to optimize indoor thermal and visual comfort. However, their performance is strongly influenced by window geometry parameters, while the optimal geometrical conditions for evaluating the...
This paper investigates an improved noise reduction method and its application on gearbox vibration signal de-noising. A hybrid de-noising algorithm based on local mean decomposition (LMD), sample entropy (SE), and time-frequency peak filtering (TFPF...
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