An Improved Model for Acoustic Particle Concentration - A Case Study in Piezo-Tubes

2018 ◽  
Author(s):  
Akshay Kale ◽  
Nan Li ◽  
Adrian Stevenson
Keyword(s):  
Particle Concentration ◽  
Improved Model

scholarly journals AN INVESTIGATION ON THE IMPROVEMENT OF CONSTRUCTION EXPENDITURE FORECASTING

2013 ◽  
Vol 19 (5) ◽  
pp. 759-711 ◽  
Author(s):  
Andrew Ross ◽  
Katie Dalton ◽  
Begum Sertyesilisik
Keyword(s):  
Cash Flow ◽  
Construction Projects ◽  
Case Study Research ◽  
Research Strategy ◽  
Flow Models ◽  
Improved Model ◽  
Work Affect ◽  
Cash Flow Forecast ◽  
Parameter Values

This study aims to determine the accuracy of the cash flow models and to investigate if these models could be more accurate if they accounted for the potentially influential variables specific to individual construction projects. An analytical case study research strategy has been implemented in collecting data for the construction projects. The data collected has been tested against recognised models. Statistical analyses have been carried out on the data for the specified variables, culminating in the potential proposal of an improved model with respect to these identified variables. The results revealed that the independent variables (type of construction, procurement route and type of work) affect the cash flow forecast. The findings suggested that a model could be more accurate with the input of more job-specific variables and that Hudson's DHSS model is best suited to a construction project procured traditionally. Adopting the ‘trial and error’ approach, Hudson's DHSS model has been recognised as an accurate model that could be adapted slightly, through changing the parameter values. The clients and the contractors are the main beneficiaries approached for this study.

Developing Blue Ocean Strategy in Construction Industries Using an Improved Model of Kano

2017 ◽  
pp. 192-207
Author(s):  
Mohammad Abdolshah ◽  
Fariborz Ahmadzadeh ◽  
Afshin Abbaspour
Keyword(s):  
Construction Industry ◽  
Hybrid Model ◽  
Psychological Factors ◽  
Strategic Thinking ◽  
Consistent Pattern ◽  
Economic Factors ◽  
Library Research ◽  
Improved Model ◽  
Selection Of

Blue ocean strategy includes a consistent pattern of strategic thinking in the creation of new markets in various industries. This chapter examines how to create a blue ocean and its role in improving the construction industry. This is library research alongwith case study. It has been prepared based on information gathered from articles published in international journals and referring to large and reputable builder companies. In the concept of strategy, “Blue Ocean” is referred to two overall scope of blue and red ocean. In this chapter, we used the Kano method for evaluation and selection of the features in the construction industry and then, through a four-step approach, it was decided what features should be removed, innovated, enhanced or improved. Finally, using improved hybrid model of Kano and the pillars of the blue ocean strategy, we concluded that economic factors and psychological factors that impact on the consumers need investment and more attention.

Data-Driven Inventory Management in the Healthcare Supply Chain

2020 ◽  
pp. 1390-1403
Author(s):  
Shuojiang Xu ◽  
Kim Hua Tan
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Inventory Management ◽  
Data Driven ◽  
Forecasting Model ◽  
Market Demand ◽  
Improved Model ◽  
Future Work ◽  
Statistic Approach

From 21st century, enterprises combine supply chain management with big data to improve their products and services level. In China healthcare industry, supply chain decisions are made based on experience, due to the environment complexities, such as changing policies and license delay. A flexible and dynamic big data driven analysis approach for supply chain decisions is urgently required. This report demonstrates a case study on CRT forecasting model of inventory data to predict the market demand based on pervious transaction data. First a basic statistic approach has been applied to represent the superficial patterns and suggest some decisions. After that a CRT model has been built based on the several independent variables. And there is also a comparison between CRT and CHAID models to choose a better one to further build an improved model. Finally some limitations and future work have been proposed.

scholarly journals The Improved Canopy Shading Model Based on the Apple Intercropping System (Case Study: Loess Plateau, China)

2018 ◽  
Vol 10 (10) ◽  
pp. 3486
Author(s):  
Jingjing Wang ◽  
Huaxing Bi ◽  
Yubo Sun ◽  
Hangqi Duan ◽  
Ruidong Peng
Keyword(s):  
Apple Tree ◽  
Temporal Distribution ◽  
Agroforestry Systems ◽  
Measured Data ◽  
Apple Trees ◽  
Simulation Accuracy ◽  
Actual Measurement ◽  
Similarity Principle ◽  
Improved Model

The canopy shading model is widely used in agroforestry systems. However, the canopy shading model cannot be verified by the measured shading distribution of an apple tree due to the uneven ground and adjacent apple trees. This paper measures the spatial‒temporal distribution of the shading of apple trees based on the similarity principle of parallel solar light combined with 3D printing technology to improve the canopy shading model. The following results are drawn: (1) The current widely used canopy shading model does not consider the effect of the canopy penumbra, resulting in poor simulation accuracy in the shading distribution compared to the actual measurement; (2) The effect of canopy penumbra causes the deflection of sunlight. Hence, the paper presents the deflection equation of sunlight with statistically defined parameters derived using measured data of the shading distribution. The deflection equation of sunlight is added to the improved canopy shading model. The improved model can accurately simulate the shading distribution of an apple tree, and the simulation accuracy exceeds 94.12% when compared with the shading distribution of an apple tree; (3) The improved canopy shading model is applied to simulate the spatial‒temporal distribution of the shading of apple trees in a conventional arrangement (4 m × 5 m), and the simulation accuracy exceeds 89%. Thus, the improved canopy shading model can be applied to simulate the spatial‒temporal distribution of shading of apple trees.

scholarly journals Improved Model for Generating Incremental Product Innovation Schemes

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lisha Geng ◽  
Jinge Xing ◽  
Xiaofei Shi ◽  
Liran Zu ◽  
Meiqun Chai
Keyword(s):  
Problem Solving ◽  
Product Innovation ◽  
Quality Function Deployment ◽  
Evaluation Process ◽  
Decision Makers ◽  
Generation Process ◽  
House Of Quality ◽  
Cone Model ◽  
Improved Model

To realize incremental product innovation, the key problems of existing products need to be identified and solved with feasible innovation schemes. This study examines the generation process of innovation schemes by integrating Quality Function Deployment (QFD) and the Theory of Inventive Problem Solving (TRIZ). This study has the following advantages: first, this study proposes new rules for distinguishing physical conflicts with technical conflicts and the method for calculating conflict importance after building House of Quality (HoQ) in QFD. Second, an improved integrated model of QFD and TRIZ is constructed, which generates innovation schemes by solving not only the conflicts between technical characteristics but also the problems of product parts. Third, the uncertainty and subjectivity of the data provided by decision-makers in the evaluation process of innovation schemes are processed by interval grey numbers. Moreover, a cone model is built to make the evaluation results more reliable. Last, a case study of water purifiers is conducted to illustrate the validity of the generation process of incremental product innovation schemes.

Predicting Buying Behavior using CPT+: A Case Study of an E-commerce Company

2020 ◽  
Vol 14 ◽  
Author(s):  
Nguyen Thon Da ◽  
Tan Hanh ◽  
Ho Trung Thanh
Keyword(s):  
Business Management ◽  
Critical Issue ◽  
Sequence Database ◽  
Buying Behavior ◽  
Sequence Prediction ◽  
Online Systems ◽  
Stage Process ◽  
Improved Model ◽  
Buying Behaviour

: Recently, predicting the buying behaviour of customers on e-commerce websites is a very critical issue in business management. This could help merchants understand the tendencies of consumers in choosing and buying products. It has become increasingly common these days that predicting buying behaviour on online systems. Although this is a challenging task, it is an exciting and hot topic about researchers. This article intends to be proposed as a predictive model for buying behaviour on online systems. This model may be represented as a two-stage process. First, a sequence database is built from a shopping cart. Second, the prediction will be performed by using the CPT+, which is an improved model of CPT (Compact Prediction Tree)). The main contribution of this paper is that we proposed a solution for predicting buying behaviour in the e-commerce context (a case study of an e-commerce company). The core prediction is mainly based on sequence prediction, in particularly, CPT+ (Compact Prediction Tree).

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