This study compares the effectiveness of three methods—Fréchet Distance, Dynamic Time Warping (DTW), and Convolutional Neural Networks (CNNs)—in detecting similarities and pattern recognition in time series. It proposes a Pattern-D...
Land Surface Temperature (LST) is a critical component to understand the impact of urbanization on the urban thermal environment. Previous studies were inclined to apply only one snapshot to analyze the pattern and dynamics of LST without considering...
The traditional sequential pattern mining method is carried out considering the whole time period and often ignores the sequential patterns that only occur in local time windows, as well as possible periodicity. Therefore, in order to overcome the li...
The futures market plays a significant role in hedging and speculating by investors. Although various models and instruments are developed for real-time trading, it is difficult to realize profit by processing and trading a vast amount of real-time d...
Well pattern infilling optimization is a crucial measure to enhance gas recovery, especially in tight gas reservoirs with low permeability and small-scale sand bodies. Traditional methods of determining well pattern density rely on qualitative analys...
Competing patterns are compound patterns that compete to be the first to occur a pattern-specific number of times, known as a stopping rule. In this paper, we study a higher-order Markovian dependent Bernoulli trials model with competing patterns. Th...
Time irreversibility, i.e., the lack of invariance of a system under the operation of time reversal, has long attracted the attention of the statistical physics community, and has been shown to be a relevant marker of altered dynamics in many real-wo...
Technological evolution in the remote sensing domain has allowed the acquisition of large archives of satellite image time series (SITS) for Earth Observation. In this context, the need to interpret Earth Observation image time series is continuously...
The language inclusion checking of timed automata is described as the following: given two timed automata M and N, where M is a system model and N is a specification model (which represents the properties that the system needs to satisfy), check whet...
Anomaly detection across critical infrastructures is not only a key step towards detecting threats but also gives early warnings of the likelihood of potential cyber-attacks, faults, or infrastructure failures. Owing to the heterogeneity and complexi...
A spatial co-location pattern denotes a subset of spatial features whose instances frequently appear nearby. High influence co-location pattern mining is used to find co-location patterns with high influence in specific aspects. Studies of such patte...
Anomalous patterns are common phenomena in time series datasets. The presence of anomalous patterns in hydrological data may represent some anomalous hydrometeorological events that are significantly different from others and induce a bias in the dec...
Mining spatiotemporal mobility patterns is crucial for optimizing urban planning, enhancing transportation systems, and improving public safety by providing useful insights into human movement and behavior over space and time. As an unsupervised lear...
In this paper, we present a novel method for change-pattern mining in Synthetic Aperture Radar (SAR) image time series based on a distance matrix clustering algorithm, called K-Matrix. As it is different from the state-of-the-art methods, which analy...
In this paper, we investigate waiting time problems for a finite collection of patterns in a sequence of independent multi-state trials. By constructing a finite GI/M/1-type Markov chain with a disaster and then using the matrix analytic method, we c...
The sustainable development goals of the United Nations, as well as the era of pandemics have introduced serious challenges for agricultural production and management. Precise management of agricultural practices based on satellite-borne remote sensi...
Deviations in execution from the prescribed drug intake schedules (timing non adherence) are frequent and may pose a substantial risk for therapeutic failure. Simple methods to monitor timing adherence with multiple drugs are missing. A new technolog...
Similar to the rainfall depth, duration and intensity, the temporal pattern is also an important characteristic of rainstorm events. Studies have shown that temporal patterns will influence runoff modelling, flash flood warning thresholds as well as...
Modern positioning and sensor technology enable the acquisition of movement positions and attributes on an unprecedented scale. Therefore, a large amount of trajectory data can be used to analyze various movement phenomena. In cartography, a common w...
The study of order patterns of three equally-spaced values x t , x t + d , x t + 2 d in a time series is a powerful tool. The lag d is changed in a wide range so that the differences of the frequencies of order patterns become autoc...
Resistance, resilience, and recovery time are critical for quantifying the stability of grasslands in response to drought disturbances. Few studies have simultaneously considered both drought intensity and duration to analyze the stability of differe...
In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers’ detection and p...
This article provides a solution based on statistical methods (ARIMA, ETS, and Prophet) to predict monthly power demand, which approximates the relationship between historical and future demand patterns. The energy demand time series shows seasonal f...
7 March 2019
Considering the association between the neighborhood food environment and individual eating behaviors, this study aimed to assess the association between parents’ reported use of food facilities by their children, and parental perceived travel time t...
Forecasting and modeling building energy profiles require tools able to discover patterns within large amounts of collected information. Clustering is the main technique used to partition data into groups based on internal and a priori unknown scheme...
Electricity consumption patterns reveal energy demand behaviors and enable strategY implementation to increase efficiency using monitoring systems. However, incorrect patterns can be obtained when the time-series components of electricity demand are...
Artificial intelligence (AI) is widely used in pattern recognition and positioning. In most of the geological exploration applications, it needs to locate and identify underground objects according to electromagnetic wave characteristics from the gro...
26 October 2020
Today, the time spent actively is increasingly being replaced by screen-based media, although in some teenagers, a high level of physical activity (PA) and longer time spent in front of a screen (screen time, ST) may coexist as a mixed behavioral pat...
In many industrial domains, there is a significant interest in obtaining temporal relationships among multiple variables in time-series data, given that such relationships play an auxiliary role in decision making. However, when transactions occur fr...
Investigating how the productivity dynamics of planted forests vary over time is important for understanding the resilience of forests against disturbance and for maximizing ecological restoration and replanting efforts. In this study, the patterns o...
Tracheal, bronchus, and lung cancer (TBLC) remains a major public health concern. Knowledge about geographic patterns and time trends in TBLC could give insights to better address this problem. This study aimed to evaluate the geographic patterns and...
In this paper, we simultaneously use two different scales in the analysis of ordinal patterns to measure the complexity of the dynamics of heartbeat time series. Rényi entropy and weighted Rényi entropy are the entropy-like measures pro...
The use of satellite image time series analysis and machine learning methods brings new opportunities and challenges for land use and cover changes (LUCC) mapping over large areas. One of these challenges is the need for samples that properly represe...
Time-restricted eating (TRE) can facilitate weight loss, yet its effect on eating patterns remains unknown. Twenty adults with BMI ≥ 25 kg/m2 underwent a 12-week randomized trial, examining the effect of an 8-h, time-restricted eating intervention...
In this work, a lightweight adaptive hybrid gait detection method with two inertial measurement units (IMUs) on the foot and thigh was developed and preliminarily evaluated. An adaptive detection algorithm is used to eliminate the pre-training phase...
Land use and land cover change (LULCC) can influence giant panda distributions by altering landscape structure and configuration. However, the spatial impacts and potential time lag effects of landscape pattern changes on giant pandas remain underexp...
Accurate and timely information on crop planting patterns is crucial for research on sustainable agriculture, regional resources, and food security. However, existing spatial datasets have few high-precision and wide-range planting pattern maps. The...
Rapid cropland reclamation is underway in Cold China in response to increases in food demand, while the lack analyses of time series cropping pattern mappings limits our understanding of the acute transformation process of cropland structure and asso...
Agricultural land use and cropping patterns are closely related to food production, soil degradation, water resource management, greenhouse gas emission, and regional climate alterations. Methods for reliable and cost-efficient mapping of cropping pa...
19 February 2014
Estimation of population exposure is a main component of human health risk assessment for environmental contaminants. Population-level exposure assessments require time-activity pattern distributions in relation to microenvironments where people spen...
Different types of partial discharge (PD) in gas-insulated switchgear (GIS) cause different damage to GIS insulation, correctly identifying the PD type is very important for evaluating the insulation status of GIS. This paper proposes a PD pattern re...
Pattern projection-based 3D measurement systems are widely used for contactless, non-destructive optical 3D shape measurements. In addition, many robot-operated automation tasks require real-time reconstruction of accurate 3D data. In previous works,...
In the paper, a digital clock stopping technique for gain and offset correction in time-mode analog-to-digital converters (ADCs) has been proposed. The technique is dedicated to imagers with massively parallel image acquisition working in the time mo...
An ability of lensless titanium-based antenna coupled microbolometers (Ti-μbolometers) operating at room temperature to monitor precisely radiation patterns in terahertz time-domain spectroscopy (THz-TDS) systems are demonstrated. To provide comprehe...
Product quality is a major concern in manufacturing. In the metal processing industry, low-quality products must be remanufactured, which requires additional labor, money, and time. Therefore, user-controllable variables for machines and raw material...
This paper proposes a new method to detect bursts in District Metering Areas (DMAs) in water distribution systems. The methodology is divided into three steps. Firstly, Dynamic Time Warping was applied to study the similarity of daily water demand, e...
Pattern recognition algorithms have been widely used to map surface electromyographic signals to target movements as a source for prosthetic control. However, most investigations have been conducted offline by performing the analysis on pre-recorded...
Based on the coupling coordination model, this paper intends to use the panel data of 31 provinces in China from 2000 to 2019, analyze the coupling and coupling coordination relationship between environmental regulation and green water resource effic...
The forecasting of future values is a very challenging task. In almost all scientific disciplines, the analysis of time series provides useful information and even economic benefits. In this context, this paper proposes a novel hybrid algorithm to fo...
Unlike previous regionalized studies on a worldwide crisis, this study aims to analyze spatial distribution patterns and evolution characteristics of the COVID-19 pandemic, using space-time aggregation and spatial statistics from a global perspective...
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