An integrated model combining random forests and WRF/CMAQ model for high accuracy spatiotemporal PM2.5 predictions in the Kansai region of Japan

2021 ◽  
pp. 118620
Author(s):  
Tin Thongthammachart ◽  
Shin Araki ◽  
Hikari Shimadera ◽  
Shinnosuke Eto ◽  
Tomohito Matsuo ◽  
...  
Keyword(s):  
Random Forests ◽  
High Accuracy ◽  
Integrated Model ◽  
Model Combining

Modeling of Piezo-Actuated Stick-Slip Micro-Drives: An Overview

2012 ◽  
Vol 81 ◽  
pp. 39-48 ◽  
Author(s):  
Ha Xuan Nguyen ◽  
Christoph Edeler ◽  
Sergej Fatikow
Keyword(s):  
Mechanical Model ◽  
Integrated Model ◽  
Friction Model ◽  
Fundamental Importance ◽  
Future Research ◽  
Stick Slip ◽  
Research Activities ◽  
Model Combining ◽  
Friction Models

This paper gives an overview about problems of modeling of piezo-actuated stick-slip micro-drives. It has been found that existing prototypes of such devices have been investigated empirically. There is only few research dealing with the theory behind this kind of drives. By analyzing the current research activities in this field, it is believed that the model of the drive depends strongly on the friction models, but in most cases neglecting any influences of the guilding system.These analyses are of fundamental importance for an integrated model combining friction model and mechanical model offering promising possibilities for future research.

Children as customers in luxury hotels

2020 ◽  
Vol 32 (5) ◽  
pp. 1813-1835
Author(s):  
Béchir Ben Lahouel ◽  
Nathalie Montargot
Keyword(s):  
Integrated Model ◽  
Three Dimensions ◽  
Service Encounters ◽  
Content Type ◽  
Luxury Hotels ◽  
Model Combining ◽  
Child Experience ◽  
Key Issues ◽  
Hotel Managers ◽  
Luxury Hotel

Purpose This purpose of this study was to explore two key issues in experiential marketing from an organizational perspective: the management of “strategic experiential modules” and the management of “service encounters” specific to a memorable experience for children in urban luxury hotels. Design/methodology/approach An integrated model combining managerial and practice-oriented frameworks was used to study how luxury hotel managers design and create memorable experiences for children. The study took a qualitative approach in collecting in-depth data and interviewed 35 managers of five-star luxury hotels in Paris. The data were processed using the Alceste software, an automated lexical program that analyzed the co-occurrence of words and sentences. Findings With regard to the integrated model, the analysis of the interviews distinguished four main dimensions, which accounted for more than 84 per cent of the original textual data. Three dimensions, related to emotional-sensorial-physical experiential modules, described how managers strategically managed the child experience and journey while at their hotel. A fourth dimension was also identified in relation to the upstream of the service encounter. The findings highlighted a significant gap in how hotel managers were managing the experiences of children under 12 years of age and that further incorporation of various touchpoints is needed to improve the management of the service design. Research limitations/implications This study demonstrated the applicability of the proposed integrated model, which offers valuable marketing implications for luxury hotel managers. It is suggested that more research on the management of the child experience and journey is conducted in the future. Originality/value To the best of the researchers’ knowledge, this is the first empirical study to combine these two frameworks to study the management of the child experience and journey in the luxury hospitality sector.

scholarly journals Identification of Core Suppliers Based on E-Invoice Data Using Supervised Machine Learning

2018 ◽  
Vol 11 (4) ◽  
pp. 70 ◽  
Author(s):  
Jung-sik Hong ◽  
Hyeongyu Yeo ◽  
Nam-Wook Cho ◽  
Taeuk Ahn
Keyword(s):  
Machine Learning ◽  
Random Forests ◽  
Area Under The Curve ◽  
High Accuracy ◽  
Supervised Machine Learning ◽  
Machine Learning Method ◽  
Learning Method ◽  
Machine Learning Technique ◽  
Novel Approach ◽  
Learning Technique

Since not all suppliers are to be managed in the same way, a purchasing strategy requires proper supplier segmentation so that the most suitable strategies can be used for different segments. Most existing methods for supplier segmentation, however, either depend on subjective judgements or require significant efforts. To overcome the limitations, this paper proposes a novel approach for supplier segmentation. The objective of this paper is to develop an automated and effective way to identify core suppliers, whose profit impact on a buyer is significant. To achieve this objective, the application of a supervised machine learning technique, Random Forests (RF), to e-invoice data is proposed. To validate the effectiveness, the proposed method has been applied to real e-invoice data obtained from an automobile parts manufacturer. Results of high accuracy and the area under the curve (AUC) attest to the applicability of our approach. Our method is envisioned to be of value for automating the identification of core suppliers. The main benefits of the proposed approach include the enhanced efficiency of supplier segmentation procedures. Besides, by utilizing a machine learning method to e-invoice data, our method results in more reliable segmentation in terms of selecting and weighting variables.

Modeling and Design of an Optically Powered Microactuator for a Microfluidic Dispenser

2004 ◽  
Author(s):  
Mandar Deshpande ◽  
Laxman Saggere
Keyword(s):  
Solar Cell ◽  
Microfluidic Device ◽  
Piezoelectric Layer ◽  
Silicon Layer ◽  
Integrated Model ◽  
Retinal Prosthesis ◽  
Application Performance ◽  
Performance Requirements ◽  
Model Combining ◽  
Ongoing Project

This paper presents the modeling and design of an optically powered piezolectric microactuator for application in actuating and dispensing small amounts of fluid from a novel microfluidic device. This work is motivated by an ongoing project towards the development of a novel retinal prosthesis that requires such a device. The microactuator treated in this paper comprises of a solar cell integrated with a piezoelectric microactuator consisting of an active piezoelectric layer and a passive silicon layer. An integrated model combining various components of the dispenser is derived and optimal dimensions of the microactuator are obtained so that the microfluidic dispenser meets the estimated application performance requirements.

scholarly journals Overview, Formulation and Current Situation for Precession-Nutation

1998 ◽  
Vol 11 (1) ◽  
pp. 153-157
Author(s):  
N. Capitaine
Keyword(s):  
Earth Rotation ◽  
High Accuracy ◽  
Current Situation ◽  
Model Combining ◽  
Conventional Models ◽  
Definition Of ◽  
New Formulation ◽  
Improved Model ◽  
Celestial Reference System ◽  
Current Procedure

Abstract This paper describes the conventional models for precession and nutation, the current procedure for taking them into account in the reduction of highly accurate observations, the recent IAU recommendations on this topic, as well as the current situation for theory and observations. This emphasizes the imperfections in the conventional models and in the current procedure which are not in consistency either with the adoption of the new International Conventional Celestial Reference System (ICRS) or with the high accuracy and resolution of the current observations of Earth rotation. This addresses the question of the adoption of a new formulation and of an improved model combining precession and nutation of the equator with respect to the ICRS as well as the adoption of a revised definition of the Celestial Ephemeris Pole.

Internet of Things Based Occupancy Detection Using Ensemble Classifier for Smart Buildings

2020 ◽  
Vol 17 (1) ◽  
pp. 505-512
Author(s):  
Sanket Mishra ◽  
Sarthak Rajwanshi ◽  
Chittaranjan Hota
Keyword(s):  
Random Forests ◽  
Ensemble Classifier ◽  
High Accuracy ◽  
Support Vector ◽  
Large Share ◽  
Energy Aware ◽  
Occupancy Detection ◽  
Test Sets ◽  
Detection Mechanisms ◽  
The Given

Buildings account for a large share in energy consumption in day to day life. Occupancy based models can help in modeling whether the building or the particular room is occupied or not. Occupancy detection mechanisms can help in automating the electrical appliances and make them operational only in presence of the person in the room. This helps in creating energy aware scenarios which can contribute to the energy efficiency and reduction in power tariff. In this work, we take the approach of occupancy modeling by the help of Ensemble Models constructed using Random Forests, Logistic Regression and Support Vector Machine classifiers. The ensemble approach undertaken in this work is Voting and the weights of classifiers to the meta-model are fine-tuned using a Differential Evolution optimization algorithm. The results were found to be of high accuracy, i.e., 98.8% and 98.7% on the given test sets.

scholarly journals An integrated model combining ECM and UTAUT to explain users’ post-adoption behaviour towards mobile payment systems

2020 ◽  
Vol 24 ◽  
Author(s):  
Sindhu Singh
Keyword(s):  
Integrated Model ◽  
Mobile Payment ◽  
Payment Systems ◽  
Time Saving ◽  
Mobile Payments ◽  
Use Of Technology ◽  
Model Combining ◽  
Effort Expectancy ◽  
Perceived Security ◽  
Significant Factors

Technological progression in mobile phones has increased the popularity of mobile payments. Users can shop online through a mobile device, which is time saving and convenient. Mobile payment systems involve ongoing interactions between users and payment providers. The initial acceptance of mobile payment systems has been studied extensively, but few studies have attempted to understand users’ post-adoption behaviour. This study employs an integrated model with the unified theory of acceptance and use of technology (UTAUT) framework and the expectation confirmation model (ECM), along with two additional constructs: perceived security and trust. The empirical results show that the integrated model has a higher predictive power to explain continuance intentions for using mobile payment systems with significant factors of satisfaction, trust, performance expectancy, and effort expectancy. This study confirmed that the UTAUT model could be extended to explain post-adoption behaviour towards mobile payment systems. The study’s findings have theoretical and practical value to further the understanding of pre- and post-adoption behaviour towards mobile payment systems.

Sign in / Sign up

Export Citation Format

Share Document