scholarly journals Studying and Clustering Cities Based on Their Non-Emergency Service Requests

Information ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 332
Author(s):  
Mahdi Hashemi
Keyword(s):  
Baton Rouge ◽  
Emergency Service ◽  
Las Vegas ◽  
Principal Component ◽  
Washington Dc ◽  
Two Dimensional ◽  
Mobility Devices ◽  
Shared Mobility ◽  
New Perspective ◽  
Low Rate

This study offers a new perspective in analyzing 311 service requests (SRs) across the country by representing cities based on the types of their SRs. This not only uncovers temporal patterns of SRs in each city over the years but also detects cities with the most or least similarity to other cities based on their SR types. The first challenge is to gather 311 SRs for different cities and standardize their types since they differ in various cities. Implementing our analyses on close to 42 million SR records in 20 cities from 2006 to 2019 is the second challenge. Representing clusters of cities and outliers effectively, and providing justifications for them, is the last challenge. Our attempt resulted in 79 standardized SR types. We applied the principal component analysis to depict cities on a two-dimensional canvas based on their standardized SR types. Among our main findings are the following: many cities are observing a fall in requests regarding the condition of roads and sidewalks but a rise in requests concerning transportation and traffic; requests regarding garbage, cleaning, rodents, and complaints have also been rising in some cities; new types of requests have emerged and soared in recent years, such as requests for information and regarding shared mobility devices; requests about parking meters, information, sidewalks, curbs, graffities, and missed garbage pick up have the highest variance in their rates across different cities, i.e., they have a large rate in some cities while a low rate in others; the most consistent outliers, in terms of SR types, are Washington DC, Baltimore, Las Vegas, Philadelphia, Chicago, and Baton Rouge.

scholarly journals Influences of Smoking in Traditional and Industrial Conditions on Flavour Profile of Harbin Red Sausages by Comprehensive Two-Dimensional Gas Chromatography Mass Spectrometry

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1180
Author(s):  
Xiaoyu Yin ◽  
Qian Chen ◽  
Qian Liu ◽  
Yan Wang ◽  
Baohua Kong
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Volatile Compounds ◽  
Solid Phase ◽  
Meat Products ◽  
Principal Component ◽  
Quality Characteristics ◽  
Gas Chromatography Mass Spectrometry ◽  
Two Dimensional ◽  
Chromatography Mass Spectrometry

Smoking is mainly used to impart desirable flavour, colour and texture to the products. Various food smoking methods can be divided into traditional and industrial methods. The influences of three different smoking methods, including traditional smouldering smoke (TSS), industrial smouldering smoke (ISS) and industrial liquid smoke (ILS), on quality characteristics, sensory attributes and flavour profiles of Harbin red sausages were studied. The smoking methods had significant effects on the moisture content (55.74–61.72 g/100 g), L*-value (53.85–57.61), a*-value (11.97–13.15), b*-value (12.19–12.92), hardness (24.25–29.17 N) and chewiness (13.42–17.32). A total of 86 volatile compounds were identified by headspace solid phase microextraction combined with comprehensive two-dimensional gas chromatography mass spectrometry (GC × GC-qMS). Among them, phenolic compounds were the most abundant compounds in the all sausages. Compared with sausages smoked with smouldering smoke, the ILS sausages showed the highest content of volatile compounds, especially phenols, alcohols, aldehydes and ketones. Principal component analysis showed that the sausages smoked with different methods had a good separation based on the quality characteristics and GC × GC-qMS data. These results will facilitate optimising the smoking methods in the industrial production of smoked meat products.

scholarly journals Multi-objective parametrization of interatomic potentials for large deformation pathways and fracture of two-dimensional materials

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Xu Zhang ◽  
Hoang Nguyen ◽  
Jeffrey T. Paci ◽  
Subramanian K. R. S. Sankaranarayanan ◽  
Jose L. Mendoza-Cortes ◽  
...  
Keyword(s):  
Large Deformation ◽  
Functional Form ◽  
Principal Component ◽  
Interatomic Potentials ◽  
Two Dimensional ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Two Dimensional Materials ◽  
Definition Of

AbstractThis investigation presents a generally applicable framework for parameterizing interatomic potentials to accurately capture large deformation pathways. It incorporates a multi-objective genetic algorithm, training and screening property sets, and correlation and principal component analyses. The framework enables iterative definition of properties in the training and screening sets, guided by correlation relationships between properties, aiming to achieve optimal parametrizations for properties of interest. Specifically, the performance of increasingly complex potentials, Buckingham, Stillinger-Weber, Tersoff, and modified reactive empirical bond-order potentials are compared. Using MoSe2 as a case study, we demonstrate good reproducibility of training/screening properties and superior transferability. For MoSe2, the best performance is achieved using the Tersoff potential, which is ascribed to its apparent higher flexibility embedded in its functional form. These results should facilitate the selection and parametrization of interatomic potentials for exploring mechanical and phononic properties of a large library of two-dimensional and bulk materials.

Spatial clustering analysis of green economy based on knowledge graph

2021 ◽  
pp. 1-10
Author(s):  
Shiyuan Zhou ◽  
Xiaoqin Yang ◽  
Qianli Chang
Keyword(s):  
Spatial Data ◽  
Clustering Analysis ◽  
Spatial Clustering ◽  
Evaluation Model ◽  
Principal Component ◽  
Green Economy ◽  
Membership Degree ◽  
Two Dimensional ◽  
Dimensional Graph ◽  
Improved Algorithm

By organically combining principal component analysis, spatial autocorrelation algorithm and two-dimensional graph theory clustering algorithm, the comprehensive evaluation model of regional green economy is explored and established. Based on the evaluation index system of regional green economy, this paper evaluates the development of regional green economy comprehensively by using principal component analysis, and evaluates the competitive advantage of green economy and analyzes the spatial autocorrelation based on the evaluation results. Finally, the green economy and local index score as observed values, by using the method of two-dimensional graph clustering analysis of spatial clustering. In view of the fuzzy k –modes cluster membership degree measure method without considering the defects of the spatial distribution of object, double the distance and density measurement of measure method is introduced into the fuzzy algorithm of k –modes, thus in a more reasonable way to update the membership degree of the object. Vote, MUSH-ROOM and ZOO data sets in UCI machine learning library were used for testing, and the F value of the improved algorithm was better than that of the previous one, indicating that the improved algorithm had good clustering effect. Finally, the improved algorithm is applied to the spatial data collected from Baidu Map to cluster, and a good clustering result is obtained, which shows the feasibility and effectiveness of the algorithm applied to spatial data. Results show that the development of green economy using the analysis method of combining quantitative analysis and qualitative analysis, explores the connotation of green economy with space evaluation model is feasible, small make up for the qualitative analysis of the green economy in the past, can objective system to reflect the regional green economic development level, will help policy makers scientific formulating regional economic development strategy, green integrated development of regional green economy from the macroscopic Angle, the development of network system.

scholarly journals On the Nonlinearity of Winter Northern Hemisphere Atmospheric Variability

2019 ◽  
Vol 76 (1) ◽  
pp. 333-356 ◽  
Author(s):  
A. Hannachi ◽  
W. Iqbal
Keyword(s):  
North Atlantic ◽  
Polar Vortex ◽  
Principal Component ◽  
Empirical Orthogonal Functions ◽  
The Arctic ◽  
Climate Change Signal ◽  
Two Dimensional ◽  
Orthogonal Functions ◽  
Local Flow ◽  
The North

Abstract Nonlinearity in the Northern Hemisphere’s wintertime atmospheric flow is investigated from both an intermediate-complexity model of the extratropics and reanalyses. A long simulation is obtained using a three-level quasigeostrophic model on the sphere. Kernel empirical orthogonal functions (EOFs), which help delineate complex structures, are used along with the local flow tendencies. Two fixed points are obtained, which are associated with strong bimodality in two-dimensional kernel principal component (PC) space, consistent with conceptual low-order dynamics. The regimes reflect zonal and blocked flows. The analysis is then extended to ERA-40 and JRA-55 using daily sea level pressure (SLP) and geopotential heights in the stratosphere (20 hPa) and troposphere (500 hPa). In the stratosphere, trimodality is obtained, representing disturbed, displaced, and undisturbed states of the winter polar vortex. In the troposphere, the probability density functions (PDFs), for both fields, within the two-dimensional (2D) kernel EOF space are strongly bimodal. The modes correspond broadly to opposite phases of the Arctic Oscillation with a signature of the negative North Atlantic Oscillation (NAO). Over the North Atlantic–European sector, a trimodal PDF is also obtained with two strong and one weak modes. The strong modes are associated, respectively, with the north (or +NAO) and south (or −NAO) positions of the eddy-driven jet stream. The third weak mode is interpreted as a transition path between the two positions. A climate change signal is also observed in the troposphere of the winter hemisphere, resulting in an increase (a decrease) in the frequency of the polar high (low), consistent with an increase of zonal flow frequency.

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