Measure Of Irregularity Research Articles

Irregularity Measure of Graphs

A simple graph G is said to be regular if its vertices have the same number of neighbors. Otherwise, G is nonregular. So far, various formulas, such as the Albertson index, total Albertson index, and degree deviation, have been introduced to quantify the irregularity of a graph. In this paper, we present sharp lower bounds for these indices in terms of the order, size, maximum degree, minimum degree, and forgotten and Zagreb indices of the underlying graph. We also prove that if G has the minimum value of degree deviation, among all nonregular n , m -graphs, then Δ G − δ G = 1 .

Experimental Studies of Welded Joints in Structures Subject to High Impact Vibrations Using Destructive and Non-Destructive Methods

This article presents the issues of control and quality assurance of high-strength railway rail joints. Selected test results and requirements for rail joints made by welding with stationary welders on the basis of the requirements included in the PN-EN standards have been described. In addition, destructive and non-destructive tests of weld quality were performed, including visual tests, geometrical measurements of irregularities, magnetic particle and penetration tests, fracture tests, observations of micro- and macro-structure and hardness measurements. The scope of these studies included conducting tests, monitoring the process and evaluating the results obtained. Laboratory tests on the rail joints confirmed the good quality of the rail joints from the welding shop. Increasingly less damage to the track in places of new welded joints is proof that the methodology of laboratory qualification tests is correct and fulfils its task. The presented research will help educate engineers on the welding mechanism and the importance of quality control of rail joints during their design. The results of this study are of key importance for public safety and will improve knowledge on the correct implementation of the rail joint and how to conduct quality control tests in accordance with the requirements of the currently applicable standards. It will help engineers choose the right welding technique and choose solutions to minimize cracks.

Sleep irregularity and the association with hypertension and blood pressure levels: the ELSA-Brasil study.

To evaluate the associations of sleep irregularity with hypertension (HTN) and blood pressure (BP) levels. Adult participants from the ELSA-Brasil performed a clinical evaluation including objective sleep duration (actigraphy), insomnia, and a sleep study for defining obstructive sleep apnoea (OSA). To quantify sleep irregularity, we used two parameters obtained through actigraphy: 7-day standard deviation (SD) of sleep duration and 7-day SD of sleep-onset timing. A multivariate analysis was used to determine the independent associations of sleep irregularity with HTN and SBP/DBP values. We studied 1720 participants (age 49 ± 8 years; 43.4% men) and 27% fulfilled the HTN diagnosis. After adjustments for age, gender, race, BMI, excessive alcohol consumption, physical activity intensity, urinary sodium excretion, insomnia, objective sleep duration and OSA (apnoea-hypopnoea index ≥15 events/h), we found that the continuous analysis of 7-day SD of sleep duration was modestly associated with prevalent HTN. However, 7-day SD of sleep duration more than 90 min was independently associated with SBP [ β : 1.55; 95% confidence interval (CI) 0.23-2.88] and DBP ( β : 1.07; 95% CI 0.12-2.01). Stratification analysis excluding participants with OSA revealed that a 7-day SD of sleep duration greater than 90 min was associated with a 48% higher chance of having HTN (OR: 1.48; 95% CI: 1.05-2.07). No significant associations were observed for the SD of sleep-onset timing. Objective measurement of sleep irregularity, evaluated by SD of sleep duration for 1 week, was associated with HTN and higher BP levels, especially in participants without OSA.

Measurement and Processing of Road Irregularity for Surface Generation and Tyre Dynamics Simulation in NVH Context

Nowadays, finite element tyre models are often used to perform vehicle NVH (noise, vibration, harshness) simulations. To account for the specific operating conditions, a road surface must be properly included in the model. This paper deals with a methodology to experimentally evaluate and process road irregularity measurements, so as to generate a road surface input. These surfaces are used to simulate the tyre/road interaction at the footprint, which is modelled as a contact surface in finite element tyre models. For this reason, a linear profile of the road surface is not suitable for these simulations and the whole surface must be considered. Starting from the measurements taken through a test equipment specifically designed to carry laser sensors and scan road profiles, the Power Spectral Density (PSD) of a specific track is estimated and then interpolated considering piecewise functions. Finally, a model to generate a road surface starting from the measured PSD is developed, discussed and validated.

ZPasteurAIzer: An AI-Enabled Solution for Product Quality Monitoring in Tunnel Pasteurization Machines

In the food and beverage industry, many foods, beers, and soft drinks need to be pasteurized in order to minimize the effect of micro-organisms on the physical stability, quality, and flavour of the product. Although modern tunnel pasteurizers provide integrated solutions for precise process monitoring and control, a great number of packaging plants continue to operate with legacy pasteurizers that require irregular manual measurements to be performed by shop floor operators in order to monitor the process. In this context, the present paper presents zPasteurAIzer, an end-to-end system that provides real-time quality monitoring for legacy tunnel pasteurization machines and constitutes a low-cost alternative to replacement or the upgrading of installed equipment by leveraging IoT technologies and AI-enabled virtual sensing techniques. We share details on the design and implementation of the system, which is based on a microservice-oriented architecture and includes functionalities such as configuration of the pasteurizer machine, data acquisition, and preprocessing methodology as well as machine learning-based estimation and live dashboard monitoring of the process parameters. Experimental work has been conducted in a real-world use case at a large brewing manufacturing plant in Greece, and the results indicate the value and potential of the proposed system.

Longitudinal individual predictions from irregular repeated measurements data

Intensive longitudinal data can be used to explore important associations and patterns between various types of inputs and outcomes. Nonlinear relations and irregular measurement occasions can pose problems to develop an accurate model for these kinds of data. This paper focuses on the development, fitting and evaluation of a prediction model with irregular intensive longitudinal data. A three-step process for developing a prediction tool for (daily) monitoring and prediction is outlined and illustrated for intensive weight measurements in piglets. Step 1 addresses a nonlinear relation in the data by developing and applying a normalizing transformation. Step 2 addresses the intermittent nature of the time points by aligning the measurement times to a common time grid with a broken-stick model. Step 3 addresses the prediction problem by selecting and evaluating inputs and covariates in the model to obtain accurate predictions. The final model predicts future outcomes accurately, while allowing for nonlinearities between input and output and for different measurement histories of individuals. The methodology described can be used to develop a tool to deal with intensive irregular longitudinal data that uses the available information in an optimal way. The resulting tool demonstrated to perform well for piglet weight prediction and can be adapted to many different applications.

A Method of Generating Real-Time Natural Light Color Temperature Cycle for Circadian Lighting Service.

The light intensity and color temperature of natural light periodically change and promote the circadian entrainment of the human body. In addition, the color temperature cycle of natural light that is unique to each region is formed by its location and geographic and environmental factors, affecting the health of its residents. Research on lighting and construction to provide the color temperature of real-time natural light has continued to provide the beneficial effect of natural indoor lighting. However, lighting technology that provides the real-time color temperature of natural light could not be realized since it is challenging to select a color temperature cycle zone due to abrupt color temperature changes at sunrise and sunset. Such drastic shifts cause an irregular measurement of color temperature over time due to general weather or atmospheric conditions. In a previous study, a method of generating a color temperature cycle using deep learning was introduced, but the performance at the beginning and end of the color temperature cycle was unreliable. Therefore, this study proposes generating a real-time natural light color temperature cycle for the circadian lighting service. The characteristics of the daily color temperature cycle were analyzed based on the measured natural light characteristics database, and a data set for learning was established. To improve the color temperature cycle generation performance, a deep learning (TadGAN) model was implemented by searching for the lowest point of the color temperature at the start and end points of the color temperature cycle and applying the boot and ending datasets to these points. The color temperature cycle zone was accurately detected in real-time in the experiment, and the generation performance of the color temperature cycle was maintained at the beginning and end of the color temperature cycle. The mean absolute error decreased by about 67%, confirming the generation of a more accurate real-time color temperature cycle.

ClusterMLD: An Efficient Hierarchical Clustering Method for Multivariate Longitudinal Data

Longitudinal data clustering is challenging because the grouping has to account for the similarity of individual trajectories in the presence of sparse and irregular times of observation. This paper puts forward a hierarchical agglomerative clustering method based on a dissimilarity metric that quantifies the cost of merging two distinct groups of curves, which are depicted by B-splines for the repeatedly measured data. Extensive simulations show that the proposed method has superior performance in determining the number of clusters, classifying individuals into the correct clusters, and in computational efficiency. Importantly, the method is not only suitable for clustering multivariate longitudinal data with sparse and irregular measurements but also for intensely measured functional data. Towards this end, we provide an R package for the implementation of such analyses. To illustrate the use of the proposed clustering method, two large clinical data sets from real-world clinical studies are analyzed.

Permanent Magnet Guideway Irregularity Measurement and Characterization by Single Dewar HTS Pinning Maglev System

Permanent Magnet Guideway Irregularity Measurement and Characterization by Single Dewar HTS Pinning Maglev System

Non-Archimedean Koksma Inequalities, Variation, and Fourier Analysis

Abstract We examine four different notions of variation for real-valued functions defined on the compact ring of integers of a non-Archimedean local field, with an emphasis on regularity properties of functions with finite variation, and on establishing non-Archimedean Koksma inequalities. The first version of variation is due to Taibleson, the second due to Beer, and the remaining two are new. Taibleson variation is the simplest of these, but it is a coarse measure of irregularity and it does not admit a Koksma inequality. Beer variation can be used to prove a Koksma inequality, but it is order-dependent and not translation invariant. We define a new version of variation which may be interpreted as the graph-theoretic variation when a function is naturally extended to a certain subtree of the Berkovich affine line. This variation is order-free and translation invariant, and it admits a Koksma inequality which, for a certain natural family of examples, is always sharper than Beer’s. Finally, we define a Fourier-analytic variation and a corresponding Koksma inequality which is sometimes sharper than the Berkovich-analytic inequality.

On the σt-irregularity and the inverse irregularity problem

The σ-irregularity index is a natural variant of the well-established Albertson irregularity index. Here, we introduce an irregularity measure based on the σ-irregularity, which is a graph invariant with respect to a given degree sequence. We define it as σt(G)=12∑v,w∈V(G)(dG(v)−dG(w))2, where dG(v) is the degree of a vertex v of G, and named it the total σ-irregularity. We characterize irregular graphs with minimal σt-irregularity. In addition, we consider the so-called inverse problem for the Albertson irregularity index, the total irregularity, and the σt-irregularity. For those irregularity measures, we study the problem for general graphs, trees, and c-cyclic graphs.

On ve-Degree Irregularity Index of Graphs and Its Applications as Molecular Descriptor

Most of the molecular graphs in the area of mathematical chemistry are irregular. Therefore, irregularity measure is a crucial parameter in chemical graph theory. One such measure that has recently been proposed is the ve-degree irregularity index (irrve). Quantitative structure property relationship (QSPR) analysis explores the capability of an index to model numerous properties of molecules. We investigate the usefulness of the irrve index in predicting different physico-chemical properties by carrying out QSPR analysis. It is established that the irrve index is efficient to explain the acentric factor and boiling point of molecules with powerful accuracy. An upper bound of irrve for the class of all trees is computed with identifying extremal graphs. We noticed that the result is not correct. In this report, we provide a counter example to justify our argument and determine the correct outcome.

Measurement and analysis of the longitudinal level irregularity of the track beam in monorail tour-transit systems

Notable effects on the vertical dynamic response of vehicle-bridge systems are introduced by longitudinal level irregularity (LLI). However, in monorail systems, the measured data and associated spectrum of the LLI, i.e., the distribution curve of power spectral density versus wavelength, have not been reported in detail. To address this issue, we propose the inclination correction method (ICM) to measure the LLI in monorail tour-transit systems and further estimate and fit the spectral curves for the first time. The measuring principle of ICM is thoroughly described, and ICM is compared with conventional chord-based methods. In addition, the trend components of the measured LLI are eliminated through an adaptive method preceding spectral estimation to avoid potential errors. Notably, a simulation program is designed, and the results from existing methods are adopted to verify the proposed ICM. Based on an analysis of the results, the accuracy and robustness of ICM are demonstrated, and the applicability and advantages of autoregressive models and the proposed fractional functions in spectral analysis are revealed. Finally, combining qualitative and quantitative calculations, an evaluation approach for the generic spectra of monorail LLI is established.

Experimental Study on the Potential of Vehicle’s Attitude Response to Railway Track Irregularity in Precise Train Localization

Railway track is never perfect, as rail distortions, namely, geometric irregularities, exist at all locations along the track. However, these distortions can be regarded as valuable indicators for train localization, since track irregularities present location-dependent characteristics, the measurements of which using onboard sensors are repeatable for the same track. In this research, we study the possibility of determining a train’s position by matching the track irregularity measurements to a predefined map. A train-borne experiment on a real track is used to preliminarily demonstrate the feasibility, evaluate the performance and determine the key parameters for practical implementation. The results show that a submeter longitudinal localization accuracy can be achieved even when using a low-cost cabin-mounted microelectromechanical system (MEMS) inertial measurement unit (IMU), which measures the train’s responses to track irregularities. The proposed method can enhance the positioning accuracy and improve the robustness of multisensory train localization systems.

Is parental socioeconomic status associated with irregularity of energy intake among children?

Abstract Background The timing of eating, chrono-nutrition, is a relatively new research area, where the focus is not on only what we eat but also when we eat and of irregularity between days. Chrono-nutrition have been associated with cardiovascular risk factors among adults. Societal factors influence the chrono-nutrition, but there is limited research on how different socioeconomic factors are associated with chrono-nutrition, especially among children. The aim of this study is to examine the association between parental socioeconomic status and irregularity of children’s energy intake. Methods We used data from the DAGIS (Increased Health and Wellbeing in Preschools) study in years 2015-2016, in which 864 preschool children participated (age 3-6 years old). Childreńs dietary intake was measured by a 3-day food record. We included only children that had complete data from all three days and the child was at day care on two of those days and one day was a weekend day (n = 568). To calculate the irregularity score, the absolute difference between the daily energy intake and 3-day mean intake for each three days was divided by the 3-day mean energy intake, multiplied by 100 and then averaged over the 3 days; this served as a measure of irregularity of energy intake, with a low score indicating a more regular energy intake and a higher more irregular energy intake. The parents reported highest parental educational level and household income on a questionnaire. The associations were tested by general linear models on SPSS. Results No association was found between parental educational level or household income with irregularity of children’s energy intake. Conclusions There was no association between parental socioeconomic status and children’s irregularity of energy intake. Other aspects of children’s chrono-nutrition should also be tested to be able to conclude that children’s chrono-nutrition is not influenced by parental socioeconomic status. Key messages • We found no association between parental socioeconomic status and irregularity in children’s energy intake. • Chrono-nutrition among children is under-examined.

The automated preprocessing pipe-line for the estimation of scale-wise entropy from EEG data (APPLESEED): Development and validation for use in pediatric populations

It is increasingly understood that moment-to-moment brain signal variability – traditionally modeled out of analyses as mere “noise” – serves a valuable functional role related to development, cognitive processing, and psychopathology. Multiscale entropy (MSE) – a measure of signal irregularity across temporal scales – is an increasingly popular analytic technique in human neuroscience calculated from time series such as electroencephalography (EEG) signals. MSE provides insight into the time-structure and (non)linearity of fluctuations in neural activity and network dynamics, capturing the brain’s moment-to-moment complexity as it operates on multiple time scales. MSE is emerging as a powerful predictor of developmental processes and outcomes. However, differences in data preprocessing and MSE computation make it challenging to compare results across studies. Here, we (1) provide an introduction to MSE for developmental researchers, (2) demonstrate the effect of preprocessing procedures on scale-wise entropy estimates, and (3) establish a standardized EEG preprocessing and entropy estimation pipeline that adapts a critical modification to the original MSE algorithm, and generates reliable scale-wise entropy estimates capable of differentiating developmental stages and cognitive states. This novel pipeline – the Automated Preprocessing Pipe-Line for the Estimation of Scale-wise Entropy from EEG Data (APPLESEED) is fully automated, customizable, and freely available for download from https://github.com/mhpuglia/APPLESEED.

Three-Dimensional Cooperative Positioning for Internet of Things Provenance

A large number of Internet of Things (IoT) devices have been interconnected for information collection and exchange. The data are only meaningful if it is captured at the expected location (i.e., the IoT devices or sensors are not removed accidentally or intentionally). This article presents a new algorithm, which cooperatively locates multiple IoT devices deployed in a 3-D space based on pairwise Euclidean distance measurements. When the distance measurement noises are negligible, a new feasibility problem of rank-3 variables is formulated. We solve the problem using the difference-of-convex (DC) programming to preserve the rank-3 constraints, rather than relaxing the constraints, using semidefinite relaxation (SDR). When the distance measurements are corrupted by additive noises and nonlight-of-sight (NLOS) propagation, a maximum-likelihood estimation (MLE) problem is formulated and transformed to a DC program solved with the rank-3 constraints preserved. Simulation results indicate that the proposed approach can achieve satisfactory accuracy results with a low complexity and strong robustness to the irregular topology, poor connectivity, and measurement errors, as compared to existing SDR-based alternatives.

Assessing the Performance of the Satellite-Based Precipitation Products (SPP) in the Data-Sparse Himalayan Terrain

Located on the south-facing slope of the Himalayas, Nepal receives intense, long-lasting precipitation during the Asian summer monsoon, making Nepal one of the most susceptible countries to flood and landslide hazards in the region. However, sparse gauging and irregular measurement constrain the vulnerability assessments of floods and landslides, which rely highly on the accuracy of precipitation. Therefore, this study evaluates the performance of Satellite-based Precipitation Products (SPPs) in the Himalayas region by comparing different datasets and identifying the best alternative of gauge-based precipitation for hydro-meteorological applications. We compared eight SPPs using statistical metrics and then used the Multi-Criteria Decision-Making (MCDM) technique to rank them. Secondly, we assessed the hydrological utility of SPPs by simulating them through the GR4J hydrological model. We found a high POD (0.60–0.80) for all SPPs except CHIRPS and PERSIANN; however, a high CC (0.20–0.40) only for CHIRPS, IMERG_Final, and CMORPH. Based on MCDM, CMORPH and IMERG_Final rank first and second. While SPPs could not simulate daily discharge (NSE < 0.28), they performed better for monthly streamflow (NSE > 0.54). Overall, this study recommends CMORPH and IMERG_Final and improves the understanding of data quality to better manage hydrological disasters in the data-sparse Himalayas. This study framework can also be used in other Himalayan regions to systematically rank and identify the most suitable datasets for hydro-meteorological applications.

Experimental and numerical investigation of fatigue failure for metro bogie cowcatchers due to modal vibration and stress induced by rail corrugation

This paper describes the high-frequency vibration fatigue failure of metro bogie cowcatchers due to short-pitch track irregularities through field testing and numerical simulations. Firstly, the dynamic stress and vibrational environment of bogie cowcatchers are investigated by full-scale testing. The acceleration spectrum density and fatigue strength of cowcatchers are evaluated. Secondly, the internal and external contributors to this issue are preliminarily analyzed through modal experiments and track irregularity measurements. Then, the rigid-flexible coupled dynamic model of the vehicle is established based on the modal synthesis method and stress recovery technique. The calculated and measured vibration and stress of the bogie cowcatchers are compared for model verification. Finally, potential solutions, i.e. rail grinding and new structure design, are proposed and verified to solve the fatigue failure issue. It is found that the modal stress at hot spot locations around the weld lines of cowcatchers can be easily excited in operations and even coincides with the frequency of the rail corrugation. One efficient treatment of this issue is the rail grinding, another one is to increase the modal frequency and eliminate stress concentration with a new structure design.

A parametric study on the structural noise radiation characteristics of a steel spring floating slab track

It is a common experience that the interior noise of an underground train vehicle increases suddenly when it just runs into a track section with steel spring floating slabs, significantly reducing passengers’ comfort. This paper investigates the reasons, and control, of such noise through field tests and model simulations. The effect of rail surface irregularity on interior noise was investigated first by analysing data collected from interior noise tests, rail surface irregularity measurement and by analysing the modal behaviour of the slab. Noise radiation of the track slab was then analysed using the acoustic boundary element method while the vibration of the steel spring floating slab track is predicted based on an infinitely long periodic structure model; And finally with the prediction models, a parameter study was performed for the steel spring floating slab, on the purpose of improving the parameters to make the track less noisy. The research presented in this paper may provide a reference for the design of steel spring floating slabs in terms of noise control.