scholarly journals Acceptance Tendency of High-Level Taxis: From the Passengers’ Perspective

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Rong-Chang Jou ◽  
Ke-Hong Chen
Keyword(s):  
Stated Preference ◽  
Explanatory Power ◽  
Multinomial Logit Model ◽  
Model Estimation ◽  
Service Levels ◽  
Explanatory Variables ◽  
Taxi Service ◽  
High Level ◽  
Taiwan Region

In the present study, we used the stated preference approach to design different situations, including appearance, different services, and different times to further explore passengers’ acceptance of and expected price to be paid for taxi service levels. In addition to using general ordered models, the results of this study were also compared with the multinomial logit model and the partial proportional odds (PPO) model. The results of comparison between the models ultimately revealed that the PPO model statistically had a better explanatory power. In the model estimation results, the key explanatory variables included the ability to recognize the appearance, seating space, honorable service, the development of user payment concepts, and demographic grouping, all of which could increase acceptance. The results obtained in this study could provide a key reference for the classification of taxis in the Taiwan region and serve as a basis for the development of strategies by operators in the future.

scholarly journals Identifying and Quantifying Factors Determining Dynamic Vanpooling Use

Smart Cities ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 1243-1258
Author(s):  
Konstantinos Tsiamasiotis ◽  
Emmanouil Chaniotakis ◽  
Moeid Qurashi ◽  
Hai Jiang ◽  
Constantinos Antoniou
Keyword(s):  
Travel Time ◽  
Public Transportation ◽  
Travel Behavior ◽  
Stated Preference ◽  
Probit Model ◽  
Multinomial Logit Model ◽  
Sustainable Transportation ◽  
Model Estimation ◽  
Private Car ◽  
Vehicle Travel Time

Nowadays, the growth of traffic congestion and emissions has led to the emergence of an innovative and sustainable transportation service, called dynamic vanpooling. The main aim of this study is to identify factors affecting the travel behavior of passengers due to the introduction of dynamic vanpooling in the transportation system. A web-based mode choice survey was designed and implemented for this scope. The stated-preference experiments offered respondents binary hypothetical scenarios with an ordered choice between dynamic vanpool and the conventional modes of transport, private car and public transportation. In-vehicle travel time, total travel cost and walking and waiting time or searching time for parking varies across the choice scenarios. An ordered probit model, a multinomial logit model and two binary logit models were specified. The model estimation results indicate that respondents who are aged between 26 and 35 years old, commute with PT or are members of bike-sharing services were significantly more likely to choose dynamic vanpool or PT than private car. Moreover, respondents who are worried about climate change and are willing to spend more for environmentally friendly products are significantly more likely to use dynamic vanpool in comparison with private cars. Finally, to indicate the model estimation results for dynamic vanpool, the value of in-vehicle travel time is found to be 12.2€ per hour (13.4€ for Munich subsample).

scholarly journals El sector privado del deporte en España: Relación con población, producción y renta (The private sector of sport in Spain. Relationship with population, production and income)

Retos ◽  
2015 ◽  
pp. 71-77 ◽  
Author(s):  
Iván Martínez-Lemos ◽  
Vicente Romo-Pérez
Keyword(s):  
Private Sector ◽  
Descriptive Analysis ◽  
Explanatory Power ◽  
Total Production ◽  
Economic Activities ◽  
Autonomous Communities ◽  
Non Profit ◽  
Explanatory Variables ◽  
Per Capita

El objetivo general del presente trabajo fue describir el sector privado de actividades deportivas de naturaleza asociativa y mercantil en España y analizar su relación con indicadores de población, producción y renta de las comunidades autónomas (CA). Se utilizaron como fuentes estadísticas el directorio central de empresas (DIRCE) del Instituto Nacional de Estadística (INE) y la clasificación nacional de actividades económicas (CNAE). La muestra estuvo compuesto por el total de unidades productivas censadas en el DIRCE como grupo 931 del CNAE (Actividades Deportivas) para el año 2012 (n=18167). Se llevó a cabo un análisis descriptivo, de correlación parcial y de regresión lineal para analizar la capacidad explicativa de alguno de los indicadores analizados (población, producción y renta) sobre el tamaño y distribución del grupo 931. Los resultados reflejan que el 74.5 % del sector corresponde a personas jurídicas y que el 56.7% a empresas con asalariados, de las cuales el 79% tiene una plantilla inferior a los 10 trabajadores. El 70% del sector está concentrado en torno a las seis CA con mayor población y producto interior bruto (PIB). Dos indicadores, población y producción, han resultado variables explicativas del número de unidades productivas. Sin embargo el indicador de renta ó PIB per cápita (PIBP) no ha mostrado ninguna relación con el tamaño y distribución de la muestra analizada.Abstract. The general aim of this study was to describe the private sector of non-profit and profit sports in Spain, and analyse its relationship with population, production and income indicators from autonomous communities (AC). The Central Enterprise Directory (CED) of the National Statistics Institute (NSI) and the National Classification of Economic Activities (NCEA) were used as statistical sources. The sample consisted of the total production units surveyed in the CED as the NCEA group 931 (Sports Activities) for the year 2012 (n = 18167). A descriptive analysis, partial correlation and linear regression was conducted to analyse the explanatory power of indicators (population, production and income) on the size and distribution of the group 931. The results showed that 74.5% of the sector were legal persons and 56.7% companies with employees, of which 79% has a staff of less than 10 workers. The 70% of the sector is concentrate around the six AC with larger population and Gross Domestic Product (GDP). Two indicators, population and production, have resulted in an explanatory variables on the number of production units. However, the income indicator GDP per capita did not shown any association with sample size and distribution.

Explanatory Power for Medical Expert Systems: Studies in the Representation of Causal Relationships for Clinical Consultations

1982 ◽  
Vol 21 (03) ◽  
pp. 127-136 ◽  
Author(s):  
J. W. Wallis ◽  
E. H. Shortliffe
Keyword(s):  
Explanatory Power ◽  
Prototype System ◽  
Inference Rules ◽  
Medical Expert ◽  
Comprehensive Knowledge ◽  
Different Types ◽  
Medical Expert Systems ◽  
Explanation System ◽  
Systems Studies

This paper reports on experiments designed to identify and implement mechanisms for enhancing the explanation capabilities of reasoning programs for medical consultation. The goals of an explanation system are discussed, as is the additional knowledge needed to meet these goals in a medical domain. We have focussed on the generation of explanations that are appropriate for different types of system users. This task requires a knowledge of what is complex and what is important; it is further strengthened by a classification of the associations or causal mechanisms inherent in the inference rules. A causal representation can also be used to aid in refining a comprehensive knowledge base so that the reasoning and explanations are more adequate. We describe a prototype system which reasons from causal inference rules and generates explanations that are appropriate for the user.

scholarly journals Correlating elements content in mosses collected in 2015 across Germany with spatially associated characteristics of sampling sites and their surroundings

2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Stefan Nickel ◽  
Winfried Schröder
Keyword(s):  
Land Use ◽  
Population Density ◽  
Atmospheric Deposition ◽  
Vegetation Structure ◽  
Urban Areas ◽  
Explanatory Power ◽  
Spatial Density ◽  
Area Index ◽  
Explanatory Variables ◽  
Tree Layer

Abstract Background The aim of the study was a statistical evaluation of the statistical relevance of potentially explanatory variables (atmospheric deposition, meteorology, geology, soil, topography, sampling, vegetation structure, land-use density, population density, potential emission sources) correlated with the content of 12 heavy metals and nitrogen in mosses collected from 400 sites across Germany in 2015. Beyond correlation analysis, regression analysis was performed using two methods: random forest regression and multiple linear regression in connection with commonality analysis. Results The strongest predictor for the content of Cd, Cu, Ni, Pb, Zn and N in mosses was the sampled species. In 2015, the atmospheric deposition showed a lower predictive power compared to earlier campaigns. The mean precipitation (2013–2015) is a significant factor influencing the content of Cd, Pb and Zn in moss samples. Altitude (Cu, Hg and Ni) and slope (Cd) are the strongest topographical predictors. With regard to 14 vegetation structure measures studied, the distance to adjacent tree stands is the strongest predictor (Cd, Cu, Hg, Zn, N), followed by the tree layer height (Cd, Hg, Pb, N), the leaf area index (Cd, N, Zn), and finally the coverage of the tree layer (Ni, Cd, Hg). For forests, the spatial density in radii 100–300 km predominates as significant predictors for Cu, Hg, Ni and N. For the urban areas, there are element-specific different radii between 25 and 300 km (Cd, Cu, Ni, Pb, N) and for agricultural areas usually radii between 50 and 300 km, in which the respective land use is correlated with the element contents. The population density in the 50 and 100 km radius is a variable with high explanatory power for all elements except Hg and N. Conclusions For Europe-wide analyses, the population density and the proportion of different land-use classes up to 300 km around the moss sampling sites are recommended.

scholarly journals Semi-automated classification of colonial Microcystis by FlowCAM imaging flow cytometry in mesocosm experiment reveals high heterogeneity during seasonal bloom

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yersultan Mirasbekov ◽  
Adina Zhumakhanova ◽  
Almira Zhantuyakova ◽  
Kuanysh Sarkytbayev ◽  
Dmitry V. Malashenkov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Flow Cytometry ◽  
Spatial Resolution ◽  
Mesocosm Experiment ◽  
Imaging Flow Cytometry ◽  
Leibler Divergence ◽  
Temporal And Spatial ◽  
High Level ◽  
Training Sets

AbstractA machine learning approach was employed to detect and quantify Microcystis colonial morphospecies using FlowCAM-based imaging flow cytometry. The system was trained and tested using samples from a long-term mesocosm experiment (LMWE, Central Jutland, Denmark). The statistical validation of the classification approaches was performed using Hellinger distances, Bray–Curtis dissimilarity, and Kullback–Leibler divergence. The semi-automatic classification based on well-balanced training sets from Microcystis seasonal bloom provided a high level of intergeneric accuracy (96–100%) but relatively low intrageneric accuracy (67–78%). Our results provide a proof-of-concept of how machine learning approaches can be applied to analyze the colonial microalgae. This approach allowed to evaluate Microcystis seasonal bloom in individual mesocosms with high level of temporal and spatial resolution. The observation that some Microcystis morphotypes completely disappeared and re-appeared along the mesocosm experiment timeline supports the hypothesis of the main transition pathways of colonial Microcystis morphoforms. We demonstrated that significant changes in the training sets with colonial images required for accurate classification of Microcystis spp. from time points differed by only two weeks due to Microcystis high phenotypic heterogeneity during the bloom. We conclude that automatic methods not only allow a performance level of human taxonomist, and thus be a valuable time-saving tool in the routine-like identification of colonial phytoplankton taxa, but also can be applied to increase temporal and spatial resolution of the study.

scholarly journals Human Hand Anatomy-Based Prosthetic Hand

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 137
Author(s):  
Larisa Dunai ◽  
Martin Novak ◽  
Carmen García Espert
Keyword(s):  
3D Printing ◽  
Degrees Of Freedom ◽  
Use Of Force ◽  
Hand Movements ◽  
Human Hand ◽  
Prosthetic Hand ◽  
Object Surface ◽  
Hand Phalanges ◽  
High Level

The present paper describes the development of a prosthetic hand based on human hand anatomy. The hand phalanges are printed with 3D printing with Polylactic Acid material. One of the main contributions is the investigation on the prosthetic hand joins; the proposed design enables one to create personalized joins that provide the prosthetic hand a high level of movement by increasing the degrees of freedom of the fingers. Moreover, the driven wire tendons show a progressive grasping movement, being the friction of the tendons with the phalanges very low. Another important point is the use of force sensitive resistors (FSR) for simulating the hand touch pressure. These are used for the grasping stop simulating touch pressure of the fingers. Surface Electromyogram (EMG) sensors allow the user to control the prosthetic hand-grasping start. Their use may provide the prosthetic hand the possibility of the classification of the hand movements. The practical results included in the paper prove the importance of the soft joins for the object manipulation and to get adapted to the object surface. Finally, the force sensitive sensors allow the prosthesis to actuate more naturally by adding conditions and classifications to the Electromyogram sensor.

scholarly journals Testing Todd: family types and development

2021 ◽  
pp. 1-18
Author(s):  
Jerg Gutmann ◽  
Stefan Voigt
Keyword(s):  
Rule Of Law ◽  
Civil Society Organizations ◽  
The Rule Of Law ◽  
State Fragility ◽  
Family Types ◽  
Low Levels ◽  
Parsimonious Model ◽  
The One ◽  
High Level

Abstract Many years ago, Emmanuel Todd came up with a classification of family types and argued that the historically prevalent family types in a society have important consequences for its economic, political, and social development. Here, we evaluate Todd's most important predictions empirically. Relying on a parsimonious model with exogenous covariates, we find mixed results. On the one hand, authoritarian family types are, in stark contrast to Todd's predictions, associated with increased levels of the rule of law and innovation. On the other hand, and in line with Todd's expectations, communitarian family types are linked to racism, low levels of the rule of law, and late industrialization. Countries in which endogamy is frequently practiced also display an expectedly high level of state fragility and weak civil society organizations.

scholarly journals Space Precession Target Classification Based on Radar High-Resolution Range Profiles

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Yizhe Wang ◽  
Cunqian Feng ◽  
Yongshun Zhang ◽  
Sisan He
Keyword(s):  
Parameter Extraction ◽  
Classification Performance ◽  
Support Vector ◽  
Electromagnetic Data ◽  
Feature Extractor ◽  
Different Types ◽  
Radar Echo ◽  
High Level ◽  
Cone Target

Precession is a common micromotion form of space targets, introducing additional micro-Doppler (m-D) modulation into the radar echo. Effective classification of space targets is of great significance for further micromotion parameter extraction and identification. Feature extraction is a key step during the classification process, largely influencing the final classification performance. This paper presents two methods for classifying different types of space precession targets from the HRRPs. We first establish the precession model of space targets and analyze the scattering characteristics and then compute electromagnetic data of the cone target, cone-cylinder target, and cone-cylinder-flare target. Experimental results demonstrate that the support vector machine (SVM) using histograms of oriented gradient (HOG) features achieves a good result, whereas the deep convolutional neural network (DCNN) obtains a higher classification accuracy. DCNN combines the feature extractor and the classifier itself to automatically mine the high-level signatures of HRRPs through a training process. Besides, the efficiency of the two classification processes are compared using the same dataset.

Classification of a Granular Product using High-Level Fusion of Vision Features

1997 ◽  
Vol 68 (2) ◽  
pp. 115-124 ◽  
Author(s):  
F. Ros ◽  
S. Guillaume ◽  
V. Bellon-Maurel
Keyword(s):  
High Level ◽  
Level Fusion

MBAR Models: A Test of ARIMAX Modelling

2011 ◽  
Vol 14 (02) ◽  
pp. 347-366
Author(s):  
Anastasia Maggina
Keyword(s):  
Loss Function ◽  
Stock Exchange ◽  
Explanatory Power ◽  
Accounting Earnings ◽  
Explanatory Variables ◽  
Minimum Value ◽  
Standard Models ◽  
Athens Stock Exchange ◽  
Squared Residuals ◽  
Earnings Change

The main purpose of this paper is to provide evidence on some of the standard models of accounting earnings and returns relations mainly collected through the literature. Standard models such as earnings level and earnings changes, among others, have been investigated in this study. Models that correspond better to the data drawn from the Athens Stock Exchange have been selected. Models I, II, V, VII and IX have statistically significant coefficients of explanatory variables. In addition, model II with the MSE (minimum value of squared residuals) loss function in ARIMAX (2,0,2) is prevalent. Models that include prior earnings in various forms using levels, changes in price and changes in earnings, change in price to beginning price, lagged parameters and differentiated price models have statistically significant explanatory power.

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