The Research of Energy Efficiency Construction Design with Pollution Control Consideration

2014 ◽  
Vol 986-987 ◽  
pp. 786-789
Author(s):  
Hai Qing Guo
Keyword(s):  
Pollution Control ◽  
Target Location ◽  
Distribution Model ◽  
Optimal Distribution ◽  
Simulation Experiments ◽  
Construction Design ◽  
Proposed Model ◽  
Low Energy Consumption ◽  
Relationship Model ◽  
The Relationship

Focusing on the architectural proper distribution problems with low energy consumption, this paper analyzes the architectural distribution model and builds the architectural landscape target location distribution model with pollution control consideration. According to the features of the architectural landscape pollution control, the paper analyzes the architectural landscape target location distribution model with differentiations and finds the optimal distribution with less pollution for the architectural landscapes. The Oealcle spatial is used to describe the relationship model of the vegetation objects in the landscapes in order to obtain the optimal distribution model for the architectures with differentiations. The simulation experiments illustrate the proposed model can appropriate distribute the architectural landscapes with differentiations with better pollution control effects.

scholarly journals Fuel Consumption Using OBD-II and Support Vector Machine Model

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Tamer Abukhalil ◽  
Harbi AlMahafzah ◽  
Malek Alksasbeh ◽  
Bassam A. Y. Alqaralleh
Keyword(s):  
Support Vector Machine ◽  
Fuel Consumption ◽  
Support Vector ◽  
Machine Model ◽  
Proposed Model ◽  
Relationship Model ◽  
Multiple Vehicles ◽  
Test Route ◽  
Vehicle Information ◽  
The Relationship

This paper presents a method to estimate gasoline fuel consumption using the onboard vehicle information system OBD-II (Onboard Diagnoses-II). Multiple vehicles were used on a test route so that their consumption can be compared. The relationships between fuel consumption and both of the engine speed are measured in RPM (revolutions per minute), and the throttle position sensor (TPS). The relationships are expressed as polynomial equations. The method which is composed of an SVM (support vector machine) classifier combined with Lagrange interpolation, is used to define the relationship between the two engine parameters and the overall fuel consumption. The relationship model is plotted using a surface fitting tool. In the experimental section, the proposed method is tested using the vehicles on a major highway between two cities in Jordan. The proposed model gets its sample data from the engine’s RPM, TPS, and fuel consumption. The method successfully has given precise fuel consumption with square root mean difference of 2.43, and the figures are compared with the values calculated by the conventional method.

scholarly journals AN AHP BASED OPTIMAL DISTRIBUTION MODEL AND ITS APPLICATION IN COVID-19 VACCINATION

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Arpan Garg ◽  
Y D Sharma ◽  
Subit Kumar Jain
Keyword(s):  
Geometric Mean ◽  
State Level ◽  
Healthcare Management ◽  
Distribution Model ◽  
Optimal Distribution ◽  
Indian States ◽  
Proposed Model ◽  
Vaccine Distribution ◽  
Vaccine Availability ◽  
Preference Weights

COVID-19 is causing a large number of causalities and producing tedious healthcare management problems at a global level. During a pandemic, resource availability and optimal distribution of the resources may save lives. Due to this issue, the authors have proposed an Analytical Hierarchy Process (AHP) based optimal distribution model. The proposed distribution model advances the AHP and enhances real-time model applicability by eliminating judgmental scale errors. The model development is systematically discussed. Also, the proposed model is utilized as a state-level optimal COVID-19 vaccine distribution model with limited vaccine availability. The COVID-19 vaccine distribution model used 28 Indian states and 7 union territories as the decision elements for the vaccination problem. The state-wise preference weights were calculated using the geometric mean AHP analysis method. The optimal state-level distribution of the COVID-19 vaccine was obtained using preference weights, vaccine availability and the fact that a patient requires exactly vaccine doses to complete a vaccination schedule. The optimal COVID-19 vaccine distribution along with state and union territory rank, and preference weights were compiled. The obtained results found Kerala, Maharashtra, Uttarakhand, Karnataka, and West Bengal to be the most COVID-19 affected states. In the future, the authors suggest using the proposed model to design an optimal vaccine distribution strategy at the district or country level, and to design a vaccine storage/inventory model to ensure optimal use of a vaccine storage center covering nearby territories.

Influence factors and process stages of knowledge transfer between NPD teams

2014 ◽  
Vol 31 (3) ◽  
pp. 222-237 ◽  
Author(s):  
Alejandro Germán Frank ◽  
José Luis Duarte Ribeiro
Keyword(s):  
Knowledge Transfer ◽  
New Product Development ◽  
Influence Factors ◽  
Content Type ◽  
Practical Applications ◽  
Proposed Model ◽  
Relationship Model ◽  
Relationship Of ◽  
The Relationship ◽  
Main Influence

Purpose – This paper aims to present a model that maps the relationship between factors and process stages of the knowledge transfer (KT) between new product development (NPD) teams. Design/methodology/approach – The model was constructed through a quantitative evaluation with scholars and practitioners of the NPD field. To evaluate the model and its usefulness, a practical application was carried out in two large Brazilian companies. Findings – A relationship model between 16 main influence factors and 11 stages of the KT process was obtained. It could be seen through the practical applications that the model helps companies to identify and prioritize improvement opportunities in the KT between NPD teams. Research limitations/implications – Prior studies had been concerned with the analysis of KT factors, but considering KT as an isolated act. So, this work has advanced in the deployment of the KT stages and the relationship of those with different influence factors. Practical implications – This paper brings an important practical contribution, once several academic works have been concerned with to demonstrate relationships among factors, but few have shown how these results could help to solve practical issues observed in companies. Originality/value – Results presented in this paper enable the extension of comprehension about the KT phenomena in the NPD process. Furthermore, this paper shows how the proposed model can be used as a decision tool to guide a diagnosis and detect improvement opportunities in KT between NPD teams.

The Influence of Cognitive and Affective Reactions to Feedback on Subsequent Goals

2010 ◽  
Vol 15 (2) ◽  
pp. 121-131 ◽  
Author(s):  
Remus Ilies ◽  
Timothy A. Judge ◽  
David T. Wagner
Keyword(s):  
Performance Feedback ◽  
Business School ◽  
Structural Equation ◽  
Emotional Reactions ◽  
Equation Model ◽  
Proposed Model ◽  
And Performance ◽  
Dispositional Measure ◽  
The Relationship ◽  
Reactions To Feedback

This paper focuses on explaining how individuals set goals on multiple performance episodes, in the context of performance feedback comparing their performance on each episode with their respective goal. The proposed model was tested through a longitudinal study of 493 university students’ actual goals and performance on business school exams. Results of a structural equation model supported the proposed conceptual model in which self-efficacy and emotional reactions to feedback mediate the relationship between feedback and subsequent goals. In addition, as expected, participants’ standing on a dispositional measure of behavioral inhibition influenced the strength of their emotional reactions to negative feedback.

scholarly journals Decoupling Analysis between Economic Growth and Air Pollution in Key Regions of Air Pollution Control in China

2021 ◽  
Vol 13 (12) ◽  
pp. 6600
Author(s):  
Jing Li ◽  
Lipeng Hou ◽  
Lin Wang ◽  
Lina Tang
Keyword(s):  
Economic Growth ◽  
Air Pollution ◽  
Economic Development ◽  
Pollution Control ◽  
Environmental Policies ◽  
River Delta ◽  
Chinese Government ◽  
Air Pollution Control ◽  
The Relationship ◽  
No2 Pollution

The Chinese government has implemented a number of environmental policies to promote the continuous improvement of air quality while considering economic development. Scientific assessment of the impact of environmental policies on the relationship between air pollution and economic growth can provide a scientific basis for promoting the coordinated development of these two factors. This paper uses the Tapio decoupling theory to analyze the relationship between regional economic growth and air pollution in key regions of air pollution control in China—namely, the Beijing–Tianjin–Hebei region and surrounding areas (BTHS), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD)—based on data of GDP and the concentrations of SO2, PM10, and NO2 for 31 provinces in China from 2000 to 2019. The results show that the SO2, PM10, and NO2 pollution in the key regions show strong and weak decoupling. The findings additionally indicate that government policies have played a significant role in improving the decoupling between air pollution and economic development. The decoupling between economic growth and SO2 and PM10 pollution in the BTHS, YRD, and PRD is better than that in other regions, while the decoupling between economic growth and NO2 pollution has not improved significantly in these regions. To improve the relationship between economic growth and air pollution, we suggest that the governments of China and other developing countries should further optimize and adjust the structure of industry, energy, and transportation; apply more stringent targets and measures in areas of serious air pollution; and strengthen mobile vehicle pollution control.

Comprehensive Pricing Model of Urban Traffic Air Pollution Based on Bi-Level Programming

2012 ◽  
Vol 253-255 ◽  
pp. 1913-1917
Author(s):  
Ze Bin Zhao
Keyword(s):  
Air Pollution ◽  
Negative Impact ◽  
Urban Traffic ◽  
Vehicle Speed ◽  
Pricing Model ◽  
The Sustainable Development ◽  
Transport Services ◽  
Relationship Model ◽  
The Relationship

In order to reduce the negative impact of urban traffic air pollution, this paper firstly analyzes the relationship between urban traffic air pollution and vehicle speed, after providing the relationship model, the paper establishes a comprehensive pricing model of urban traffic air pollution based on bi-level programming, the model considers the traffic air pollution pricing, and includes the factors of congestion pricing, bus fee, pricing revenue redistribution on improvement of public transport services and the expansion of road capacity. The case study shows that the implementation of comprehensive pricing of urban traffic air pollution can reduce traffic pollution and unreasonable traffic flow, which is conducive to the sustainable development of the city.

scholarly journals Context-Aware Neural Machine Translation for Korean Honorific Expressions

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1589
Author(s):  
Yongkeun Hwang ◽  
Yanghoon Kim ◽  
Kyomin Jung
Keyword(s):  
Machine Translation ◽  
Deep Neural Networks ◽  
Contextual Information ◽  
Context Aware ◽  
Neural Machine Translation ◽  
Translation Quality ◽  
Sentence Level ◽  
Proposed Model ◽  
The Given ◽  
The Relationship

Neural machine translation (NMT) is one of the text generation tasks which has achieved significant improvement with the rise of deep neural networks. However, language-specific problems such as handling the translation of honorifics received little attention. In this paper, we propose a context-aware NMT to promote translation improvements of Korean honorifics. By exploiting the information such as the relationship between speakers from the surrounding sentences, our proposed model effectively manages the use of honorific expressions. Specifically, we utilize a novel encoder architecture that can represent the contextual information of the given input sentences. Furthermore, a context-aware post-editing (CAPE) technique is adopted to refine a set of inconsistent sentence-level honorific translations. To demonstrate the efficacy of the proposed method, honorific-labeled test data is required. Thus, we also design a heuristic that labels Korean sentences to distinguish between honorific and non-honorific styles. Experimental results show that our proposed method outperforms sentence-level NMT baselines both in overall translation quality and honorific translations.

scholarly journals An Attention-Based Model Using Character Composition of Entities in Chinese Relation Extraction

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 79 ◽  
Author(s):  
Xiaoyu Han ◽  
Yue Zhang ◽  
Wenkai Zhang ◽  
Tinglei Huang
Keyword(s):  
Language Processing ◽  
Large Scale ◽  
Named Entity Recognition ◽  
Relation Extraction ◽  
Entity Recognition ◽  
Additional Information ◽  
Named Entity ◽  
Proposed Model ◽  
The Relationship ◽  
Crucial Part

Relation extraction is a vital task in natural language processing. It aims to identify the relationship between two specified entities in a sentence. Besides information contained in the sentence, additional information about the entities is verified to be helpful in relation extraction. Additional information such as entity type getting by NER (Named Entity Recognition) and description provided by knowledge base both have their limitations. Nevertheless, there exists another way to provide additional information which can overcome these limitations in Chinese relation extraction. As Chinese characters usually have explicit meanings and can carry more information than English letters. We suggest that characters that constitute the entities can provide additional information which is helpful for the relation extraction task, especially in large scale datasets. This assumption has never been verified before. The main obstacle is the lack of large-scale Chinese relation datasets. In this paper, first, we generate a large scale Chinese relation extraction dataset based on a Chinese encyclopedia. Second, we propose an attention-based model using the characters that compose the entities. The result on the generated dataset shows that these characters can provide useful information for the Chinese relation extraction task. By using this information, the attention mechanism we used can recognize the crucial part of the sentence that can express the relation. The proposed model outperforms other baseline models on our Chinese relation extraction dataset.

Loyalty program in Africa: risk-seeking and risk-averse adventurers

2014 ◽  
Vol 69 (2) ◽  
pp. 137-157 ◽  
Author(s):  
Shogo Mlozi
Keyword(s):  
Consumer Behavior ◽  
Consumer Products ◽  
Loyalty Programs ◽  
Risk Averse ◽  
Loyalty Program ◽  
Content Type ◽  
Risk Seeking ◽  
Proposed Model ◽  
First Time ◽  
The Relationship

Purpose – This article aims to test the relationship between expected attractiveness-satisfaction-loyalty for international adventure tourists visiting Tanzania. The proposed model is based on travel consumer behavior theoretical constructs extracted from the literature. Design/methodology/approach – This article aims to test the relationship between expected attractiveness-satisfaction-loyalty for international adventure tourists visiting Tanzania. The proposed model is based on travel consumer behavior theoretical constructs extracted from the literature. Findings – The findings for overall model differed from the moderating factors of high risk, low risk, first-time visit and repeat visit. Also, the results are interesting when satisfaction is tested as a mediator. Practical implications – Practitioners could consider the fact that repeat visits may change tourists’ perceptions toward destination and may even increase their inclination to take on risks. This may impact innovation of consumer products in tourism. Also, policy makers could benefit on how loyalty programs can be developed to increase performance. Originality/value – The study offers specific strategic recommendations toward different groups of tourists (i.e. first-time, repeat visitors, risk averse, risk seeking) and proposes logic for setting up a loyalty program as a long-term strategy for success.

scholarly journals The Integrated Networks Model: Explaining Resource Allocations in Network Markets

2003 ◽  
Vol 67 (1) ◽  
pp. 29-45 ◽  
Author(s):  
Judy K. Frels ◽  
Tasadduq Shervani ◽  
Rajendra K. Srivastava
Keyword(s):  
Resource Allocation ◽  
Value Added ◽  
Information Technology Professionals ◽  
Integrated Networks ◽  
Windows Nt ◽  
Proposed Model ◽  
Network Markets ◽  
Business Customers ◽  
The Relationship ◽  
Allocation Decisions

The last decade has witnessed a shift from a focus on the value created by a single firm and product to an examination of the value created by networks of firms (or product ecosystems) in which assets are comingled with external entities. The authors examine these market-based assets in the context of network markets and propose an Integrated Networks model in which three types of networks—user, complements, and producer—add value or enhance the attractiveness of the associated focal product. The authors empirically test the proposed model by surveying information technology professionals on their resource allocation decisions regarding the Unix and Windows NT operating systems. The findings suggest that the value added by these three networks is significantly and positively associated with resources allocated by business customers to competing products. The results also show that the three networks mediate the relationship between stand-alone product performance and resource allocation.

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