scholarly journals Evaluating Correlations between a Seaport and Its Dry Ports: Case Study of Xiamen Port in China

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Jihong Chen ◽  
Yijie Fei ◽  
Fangwei Zhang ◽  
Chutao Jing
Keyword(s):  
Indicator System ◽  
Economic Indicators ◽  
Port Development ◽  
Quantitative Studies ◽  
Ocean Shipping ◽  
Study Results ◽  
Fast Development ◽  
Absolute Correlation ◽  
Grey Relational ◽  
Dry Ports

As bridges connecting seaports and their hinterland, dry ports serve to expand the hinterland and increase cargo sources of seaports, rendering efficient international logistics circulation in hinterland areas possible. The roles of dry ports have attracted increasing attention from various ocean shipping countries. Seaports and dry ports possess complementary functions and increasingly close interactions. The paper builds an assessment indicator system on correlations between seaports and dry ports and a two-stage grey relational analysis (GRA) method through collating dry port-related literature to facilitate quantitative studies on the correlations between seaports and dry ports, namely, using two quantitative indicators of Deng’s correlation and absolute correlation to assess and determine the correlations in the development of seaports and dry ports. The paper then carries out case studies on Xiamen Port and its six dry ports to verify the effectiveness of the method and model in the paper. The study results show that Xiamen Port has very high region-varying correlations with its hinterland dry ports. Dry port development not only depends on their shipment volume indicators, but also significantly correlated with their economic indicators, and the hinterland economic indicators become key factors driving the fast development of a seaport. The analyzing method in the paper is conducive for government departments and relevant stakeholders to formulate superior policies and provide theoretical bases for the development of correlations between seaports and their dry ports.

scholarly journals Risk assessment of ice dams for water diversion projects based on fuzzy fault trees

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Mengkai Liu ◽  
Xiaoxia Dong ◽  
Hui Guo
Keyword(s):  
Risk Assessment ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Northern China ◽  
Indicator System ◽  
Water Diversion ◽  
Risk Indicators ◽  
Scoring Method ◽  
Study Results ◽  
Dam Risk

AbstractIce dams are among the important risks affecting the operational safety and water conveyance efficiency of water diversion projects in northern China. However, no evaluation indicator system for ice dam risk assessment of water diversion projects has been proposed. Therefore, in this paper, based on the formation mechanism of ice dams, the risk assessment indicator system and the possibility calculation model of ice dams were both proposed for water diversion projects based on the fuzzy fault tree analysis method. The ice dam risk fault tree constructed in this study mainly includes three aspects: ice production, ice transport, and ice submergence conditions. Eighteen basic risk indicators were identified, and 72 minimum cut sets were obtained by using the mountain climb method. Eight risk indicators were determined as the key risk indicators for ice dams, including meteorological conditions, narrowed cross section, sluice incident, erroneous scheduling judgment, ice cover influence, flat bed slope, control structures, and ice flow resistance of piers. Then, the canal from the Fenzhuanghe sluice to the Beijumahe sluice of the Middle Route of the South-to-North Water Diversion Project was taken as the research object. Combined with the expert scoring method, the ice dam risk probability of the canal was determined to be 0.2029 × 10−2, which was defined as a level III risk, which is an occasionally occurring risk. The study results can support ice dam risk prevention and canal system operation in winter for water diversion projects.

Analyzing the Sustainability of Water-Cultural Industry and Their Influencing Factors in China

2021 ◽  
Author(s):  
Shubing Qiu ◽  
Yong Liu ◽  
Yang Ye
Keyword(s):  
Sustainable Development ◽  
Factor Analysis ◽  
Influencing Factors ◽  
Indicator System ◽  
Cultural Industry ◽  
The Sustainable Development ◽  
Relational Analysis ◽  
Analysis Theory ◽  
Cultural Ideology ◽  
Grey Relational

This study is an empirical analysis of China’s “sustainable development ability of water cultural industry” based on the attributes of water cultural industry (economic attribute and cultural ideology). First, using “factor analysis” and “grey relational analysis theory,” establish an indicator-system for the level of sustainable development of the cultural industry, then quantify the relationships between the water cultural industry and its influencing factors, and finally, propose some solutions for enhancing the sustainable development of the water cultural industry from the perspective of “improving resiliency.”

scholarly journals A Grey-BPNN Model for Evaluating the Competitiveness of Chinese Contractors in the High-Speed Rail Market in Europe

2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
Yi-Hsin Lin ◽  
Biling Shi ◽  
Po-Han Chen ◽  
Zhao Xu ◽  
Huimin Liu
Keyword(s):  
High Speed ◽  
Rolling Stock ◽  
High Speed Rail ◽  
The Sustainable Development ◽  
Advantages And Disadvantages ◽  
Management Ability ◽  
Study Results ◽  
Grey Relational ◽  
Technology Level ◽  
Bpnn Model

With the planning and progress of the construction of the trans-Eurasian high-speed rail (HSR) network, it becomes an important issue for Chinese contractors to enter the European HSR market. Facing the world’s most competitive contractors and their high technology levels, Chinese contractors will need to know their advantages and disadvantages, so as to make necessary improvements. In this study, contractors for HSR are divided into two groups: construction contractors and rail equipment suppliers. In order to evaluate the competitiveness of HSR contractors, a Grey-BPNN model that combines the grey relational analysis and backpropagation neural network (BPNN) is proposed. The Grey-BPNN model is expected to analyze the overall competitiveness of Chinese contractors in the European HSR market and provide informative decision support for them. The study results show the following: (1) in the field of HSR construction, the competitiveness gap between the top-tier Chinese contractors and the most competitive international contractors is small. Chinese contractors’ competitive advantages lie in medium- and low-technology-level projects, with a strong development potential. However, they highly depend on Chinese domestic market and lack in intangible resources, like management ability and market development ability; (2) for rail equipment suppliers, China Railway Rolling Stock Corporation (CRRC) ranks among the top-tier leaders of the international market. CRRC’s greatest competitor in the European HSR market is Siemens, and CRRC is much more competitive than others in the sustainable development capability. However, CRRC needs to increase the quantity of patents and Research and Development (R&D) expenditures in transportation. As a weak transportation patent holder, CRRC has a potential risk of getting intellectual property litigations in the European HSR market.

Using grey relational analysis to evaluate resource configuration and service ability for hospital on public private partnership model in China

2014 ◽  
Vol 4 (2) ◽  
pp. 260-272 ◽  
Author(s):  
Xiaoning Li ◽  
Xinbo Liao ◽  
Xuerui Tan ◽  
Haijing Wang
Keyword(s):  
Public Hospital ◽  
Private Hospital ◽  
Analysis Method ◽  
Resource Configuration ◽  
Private Partnership ◽  
Content Type ◽  
Relational Analysis ◽  
Correlation Degree ◽  
Absolute Correlation ◽  
Grey Relational

Purpose – The purpose of this paper is to evaluate resource configuration and service ability in hospital on public private partnership (PPP) model (Chaonan Minsheng Hospital of Guangdong Province), supplying decision-making reference for participants of hospital on PPP model. Design/methodology/approach – Four model of grey relational analysis (GRA) (Deng's correlation degree, grey absolute correlation degree, grey relative correlation degree and grey comprehensive correlation degree) are applied to evaluate resource configuration and service ability, a total of 11 indicators of hospital on PPP model public hospital and private hospital from 2007 to 2011. Findings – The paper finds that different GRA models have different results when the paper applied them to evaluate resource configuration and service ability in hospital on PPP model. More than 60 per cent indicators of resource configuration (total six indicators) and service ability (total six indicators) are assessed as “hospital on PPP model ≻ public hospital” or “hospital on PPP model≻ private hospital” from three models of Deng's correlation degree, grey absolute correlation degree and grey comprehensive correlation degree. Practical implications – Evaluation of resource configuration and service ability for hospital on PPP model with GRA makes results quantified objective and provides reference for decision making and management. GRA makes the comparison of resource configuration and service ability between hospital on PPP model and other model hospitals becoming possible. Originality/value – The shortcoming for data analysis method of “large sample” is overcome and data analysis method of “small sample” is realized by using GRA, which broaden the method of evaluating hospital on PPP model.

scholarly journals Romanian Roma: An Institutional Ethnography of Labour Market Exclusion

2016 ◽  
Vol 4 (1) ◽  
pp. 116-126
Author(s):  
Janne Paulsen Breimo ◽  
Loreni Elena Baciu
Keyword(s):  
Labour Market ◽  
Ethnic Group ◽  
Institutional Ethnography ◽  
Economic Indicators ◽  
Structural Barriers ◽  
Bottom Up ◽  
Social Inquiry ◽  
Quantitative Studies ◽  
Occupational Integration

Roma individuals are struggling to access the formal labour market in Romania. Previous research occupied with this issue has traditionally been dominated by quantitative studies of socio-economic indicators that cling to the characteristics of the ethnic group. The study presented here, however, uses institutional ethnography as a method of social inquiry to demonstrate that this issue needs to be studied from a bottom-up perspective. The article illustrates that there are factors connected to how the system of occupational integration operates that must be taken into consideration in order to explain the difficulties Roma individuals face when trying to enter the labour market in Romania. We argue that these structural barriers create and reinforce processes of minoritising that increase marginalization and discrimination and thereby hinder work inclusion for Roma individuals.

scholarly journals Atmega Microcontroller 2560 Based Safety System of Monitor Panel and Controller on a Small Excavator

2020 ◽  
Vol 11 (3) ◽  
pp. 367-374
Author(s):  
Randis Baharuddin ◽  
◽  
Taufik Hidayat
Keyword(s):  
Light Emitting Diode ◽  
Indicator System ◽  
Safety System ◽  
Light Emitting ◽  
Standard Testing ◽  
Study Results ◽  
Testing Tool ◽  
Infra Red ◽  
The Right

This study aimed to design and build an Atmega Microcontroller 2560 based safety system on a monitor panel and a controller on a small excavator. Atmega 2560 Microcontroller-based alarm technology is the right choice as a solution to prevent theft of monitor panels and controllers on small excavator units, using Passive Infra-Red (PIR) sensor number 1 in the cabin room, PIR sensor number 2 on the battery, and door switch that is between the cabin and the door, if there is theft in the cabin room, then the alarm will be active, if a theft occurs in the battery then the alarm will be active. The alarm indicator system uses a buzzer (horn) unit, and there is additional lighting in the cabin room with a 24V Light Emitting Diode (LED) lamp if the alarm is active. Using an alarm, the risk of losing the monitor panel and controller due to theft on the unit can be prevented. The study results showed that the tool could work appropriately according to the standard testing tool, PIR sensors number 1 and 2 could detect movement or radiation so that the alarm would be active for 15 seconds. The door switch was tested by looking at the alarm condition, if the cabin door were closed when it was in the locked position, the alarm would not be active, but if the door was locked and forcibly opened, then the alarm would be active continuously without stopping until the door was closed again.

scholarly journals The Development and Design of Engineering Economic Indicator System for Nanotechnology Industry Product Manufacturing: A Case Study of Latvia / Inženierekonomisko Rādītāju Sistēmas Attīstība Un Izveide Nanotehnoloģiju Industrijas Produktu Ražošanai: Latvijas Pieredze

2015 ◽  
Vol 52 (5) ◽  
pp. 3-19 ◽  
Author(s):  
I. Geipele ◽  
T. Staube ◽  
G. Ciemleja ◽  
S. Geipele ◽  
N. Zeltins ◽  
...  
Keyword(s):  
Economic Indicator ◽  
Scientific Paper ◽  
Indicator System ◽  
Manufacturing Industries ◽  
Economic Indicators ◽  
Theoretical Justification ◽  
Product Manufacturing ◽  
Nanotechnology Industry

Abstract The current scientific paper is developed to continue the research on further commercialisation of the nanotechnology products of manufacturing industries in Latvia. To create the system of engineering economic indicators for multifunctional nanocoating technologies, the scientific indicators and their theoretical justification have been used, the issues from the experts’ analysis and survey of the Latvian companies operating in the nanotechnology industry have been summarised.

scholarly journals The Development of Nanotechnologies and Advanced Materials Industry in Science and Entrepreneurship: Socioeconomic and Technical Indicators. A Case Study of Latvia (Part One)

2016 ◽  
Vol 53 (4) ◽  
pp. 3-13 ◽  
Author(s):  
I. Geipele ◽  
S. Geipele ◽  
T. Staube ◽  
G. Ciemleja ◽  
N. Zeltins
Keyword(s):  
Scientific Research ◽  
Economic Indicator ◽  
Scientific Paper ◽  
Indicator System ◽  
Economic Indicators ◽  
Advanced Materials ◽  
Technical Indicators

Abstract The present scientific paper is the first part of two publications, where the authors obtain results from the scientific research presented in a series of works on the development of the nanotechnologies and advanced materials industry in science and entrepreneurship in Latvia. The study has a focus on finding proper socioeconomic and technical indicators. It provides resume on a scope of the study. The paper contains the developed structure of engineering economic indicator system, determined groups of indicators for assessment of the development of nanotechnologies and advanced materials industry in Latvia and results of the evaluation of the obtained statistics on the economic indicators.

scholarly journals Early Warning of Financial Risk Based on K-Means Clustering Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zhangyao Zhu ◽  
Na Liu
Keyword(s):  
Data Processing ◽  
Early Warning ◽  
Financial Risk ◽  
Clustering Algorithm ◽  
Indicator System ◽  
Scientific Basis ◽  
Risk Prevention ◽  
Cluster Center ◽  
Risk Indicator ◽  
Study Results

The early warning of financial risk is to identify and analyze existing financial risk factors, determine the possibility and severity of occurring risks, and provide scientific basis for risk prevention and management. The fragility of financial system and the destructiveness of financial crisis make it extremely important to build a good financial risk early-warning mechanism. The main idea of the K-means clustering algorithm is to gradually optimize clustering results and constantly redistribute target dataset to each clustering center to obtain optimal solution; its biggest advantage lies in its simplicity, speed, and objectivity, being widely used in many research fields such as data processing, image recognition, market analysis, and risk evaluation. On the basis of summarizing and analyzing previous research works, this paper expounded the current research status and significance of financial risk early-warning, elaborated the development background, current status and future challenges of the K-means clustering algorithm, introduced the related works of similarity measure and item clustering, proposed a financial risk indicator system based on the K-means clustering algorithm, performed indicator selection and data processing, constructed a financial risk early-warning model based on the K-means clustering algorithm, conducted the classification of financial risk types and optimization of financial risk control, and finally carried out an empirical experiments and its result analysis. The study results show that the K-means clustering method can effectively avoid the subjective negative impact caused by artificial division thresholds, continuously optimize the prediction process of financial risk and redistribute target dataset to each cluster center for obtaining optimized solution, so the algorithm can more accurately and objectively distinguish the state interval of different financial risks, determine risk occurrence possibility and its severity, and provide a scientific basis for risk prevention and management. The study results of this paper provide a reference for further researches on financial risk early-warning based on K-means clustering algorithm.

scholarly journals Economic Indicators Selection for Property Crime Rates using Grey Relational Analysis and Support Vector Regression

2022 ◽  
Vol 16 ◽  
pp. 1-8
Author(s):  
Razana Alwee ◽  
Siti Mariyam Hj Shamsuddin ◽  
Roselina Sallehuddin
Keyword(s):  
Support Vector Regression ◽  
Grey Relational Analysis ◽  
Crime Rate ◽  
Consumer Price Index ◽  
Property Crime ◽  
Economic Indicators ◽  
Support Vector ◽  
Features Selection ◽  
Relational Analysis ◽  
Grey Relational

Features selection is very important in the multivariate models because the accuracy of forecasting results produced by the model are highly dependent on these selected features. The purpose of this study is to propose grey relational analysis and support vector regression for features selection. The features are economic indicators that are used to forecast property crime rate. Grey relational analysis selects the best data series to represent each economic indicator and rank the economic indicators according to its importance to the property crime rate. Next, the support vector regression is used to select the significant economic indicators where particle swarm optimization estimates the parameters of support vector regression. In this study, we use unemployment rate, consumer price index, gross domestic product and consumer sentiment index as the economic indicators, as well as property crime rate for the United States. From our experiments, we found that the gross domestic product, unemployment rate and consumer price index are the most influential economic indicators. The proposed method is also found to produce better forecasting accuracy as compared to multiple linear regressions.

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