Yi Tang, Xue Li, Yongli Fang and Hao Liu
Significant amount of harmonics and inter-harmonics are being injected into the power system because of the increasing use of power electronics and large non-liner loads…
Abstract
Purpose
Significant amount of harmonics and inter-harmonics are being injected into the power system because of the increasing use of power electronics and large non-liner loads. Therefore, analyzing their contents in real time is necessary.
Design/methodology/approach
The frequency and phase of an electric power harmonic or inter-harmonic can be estimated by using the discrete spectrum energy center of symmetric windows, the amplitude calculation of an electric power harmonic or inter-harmonic can be calculated by using the Pasival theorem, and their relative estimation error is only decided by the distribution of windows’ energy in the frequency domain, which equals the proportion of the spectrum energy occupied in the side lobe to the whole.
Findings
The results of the digital simulation and experimental tests show that the method proposed in this paper has the same measurement precision as and more advantages in computational complexity and burden over other methods, which are based on multipoint interpolation or interpolation polynomial windowed.
Originality/value
The method is very suitable to be used to real-time measurement in a single chip DSP micro-processor.
Zhi-Ping Fan, Yang Xi and Yongli Li
Online product ratings play an important role in the decision-making process of consumers, which are not only sources of information used by consumers to understand the function…
Abstract
Purpose
Online product ratings play an important role in the decision-making process of consumers, which are not only sources of information used by consumers to understand the function and quality of a product or service but also sources of information used to find desirable products. The purpose of this paper is to develop a decision-based method for supporting the purchase decisions of consumers based on not only the online product ratings but also the actual product attributes.
Design/methodology/approach
First, two types of utility values are designed to measure the preference of the consumer based on either online ratings or actual product attributes. Then, the traditional TOPSIS method is adopted to achieve a comprehensive value by integrating the two types of utility values so that all of the alternative products can be ranked. Further, a product selection support system prototype is designed and developed to support the purchase decisions of consumers.
Findings
To help consumers select desirable products efficiently, it is necessary to develop a product selection method based on the online ratings of alternative products and consumer expectations.
Practical implications
The research shows that the proposed method can not only support consumers’ purchase decisions based on a large number of online product ratings but also help manufacturers to find out consumers’ demands or requirements on products so as to facilitate the design of new products or the improvement of products. On the basis of the proposed method, the developed system prototype is helpful for consumers to select desirable products.
Originality/value
To support the purchase decisions of consumers, a new decision-based method for selecting desirable online products is proposed.
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Beibei Xiong, Yongli Li, Ernesto D.R. Santibanez Gonzalez and Malin Song
The purpose of this paper is to measure Chinese industries’ eco-efficiency during 2006-2013. The Chinese industry attained rapid achievement in recent decades, but meanwhile…
Abstract
Purpose
The purpose of this paper is to measure Chinese industries’ eco-efficiency during 2006-2013. The Chinese industry attained rapid achievement in recent decades, but meanwhile, overconsumption of energy and environmental pollution have become serious problems. To solve these problems, many research studies used the data envelopment analysis (DEA) to measure the Chinese industry’s eco-efficiency. However, because the target set by these works is usually the furthest one for a province to be efficient, it may hardly be accepted by any province.
Design/methodology/approach
This paper builds a new “closest target method” based on an additive DEA model considering the undesirable outputs. This method is a mixed-integer programming problem which can measure the ecological efficiency of provinces and more importantly guide the province to perform efficiently with minimum effort.
Findings
The results show that the eco-efficiency of Chinese provinces increased at the average level, but the deviations remained at a larger value. Compared to the “furthest” target methods, the targets by the approach proposed by this study are more acceptable for a province to improve its performance on both economy and environment counts.
Originality/value
This study is the first attempt to introduce the closest targets concept to measure the eco-efficiency and set the target for each provincial industry in China.
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Abstract
Purpose
In order to study granularity, this paper aims to discuss how to construct granules from the view of panweighted field of pansystem.
Design/methodology/approach
By changing the panweights of panweighted field – subdivision of panweights, increase/decrease of panweights and reallocating panweights, to construct proper granules is the approach taken.
Findings
This paper provides a new method of studying granularity. If the weights of panweighted field are subdivided, then the granularity diminishes; if the panweights of panweighted field are increased, then the corresponding granularity diminished. Contrarily, the decrease of panweights of panweighted field results in the corresponding granularity increased; by reallocating panweights, use different method to construct different granules, such as compatible class, neighbor operator, compatible core, s‐s core and so on.
Research limitations/implications
How to reallocate panweights is the main limitation.
Practical implications
A very useful advice for studying granularity.
Originality/value
This paper combines the granularity with panweighted field of pansystem, and studies granularity from the view of panweighted field of pansystems.
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Peng Luo, Eric W.T. Ngai, Yongli Li and Xin Tian
This study examines the dynamic relationships of visit behavior in the multiple channels [personal computer (PC) and mobile channels] on online store sales performance.
Abstract
Purpose
This study examines the dynamic relationships of visit behavior in the multiple channels [personal computer (PC) and mobile channels] on online store sales performance.
Design/methodology/approach
The empirical data were from an online store for the period between August 14, 2015 and May 15, 2016. The data consisted of consumer visit behavior and online store sales performance. Vector autoregression with an exogenous variables model was adopted to investigate the dynamic relationships.
Findings
The empirical results show significant relationships between visit behavior metrics (number of visitors, average number of visits per visitor and average length of each visit) in the two channels and online store sales performance. The number of visitors through the PC and mobile channels strongly and positively affects online store sales performance both in the short term and in the longer term. Moreover, the number of visitors in the PC channel has the strongest influence on sales performance metrics, followed by the number of visitors and the average number of visits in the mobile channel. The PC channel's visit behavior metrics explain a larger proportion of the sales performance variance than that in the mobile channel.
Originality/value
The previous literature on consumer behavior in multichannel marketing mainly focuses on channel selection or migration, and examines the different factors affecting channel choice behavior. Little is known about the impacts of visit behavior in the multiple channels. This study adopts the heuristic-systematic information processing theory to unveil the impacts of visit behavior metrics in the PC and mobile channels on online store sales performance.
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Binghua Zhou, Yiguo Xue, Mingtian Li, Zhiqiang Li, Xueliang Zhang and Yufan Tao
When a vehicle passes through a long highway tunnel, the smoke it discharges accumulates in the tunnel. High smoke concentration has an important influence on the driver’s health…
Abstract
Purpose
When a vehicle passes through a long highway tunnel, the smoke it discharges accumulates in the tunnel. High smoke concentration has an important influence on the driver’s health and driving safety. The use of numerous jet fans to diffuse the smoke causes excessive energy consumption, so it is of significant practical value to design suitable tunnel ventilation.
Design/methodology/approach
The study is based on the continuum hypothesis, incompressible hypothesis, steady flow hypothesis and similar hypothesis of gas in a long highway tunnel. These hypotheses calculate the gas emissions and wind demand in a long highway tunnel given the deployment of the jet fan program.
Findings
This program selects each of the two 1120-type jet machine group and sets up 13 groups; each group has an interval of 184.5 m in the end. The analysis of air test results when the tunnel is in operation shows that CO and smoke concentrations meet the design requirements, which can provide reference for a similar engineering design later.
Originality/value
At present, a highway tunnel is recognized at home and abroad by means of clearance of longitudinal ventilation, which is 2,000 m. In view of this, this paper is based on the theory of longitudinal jet ventilation of a highway tunnel, whose length is more than 2,000 m, to calculate the ventilation and apply it to a tunnel’s ventilation design.
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Abstract
Purpose
Rating, as a common way of evaluation, is a significant exercise and plays a major role in managerial decision-making in general and in particular online purchasing. The paper aims to discuss these issues.
Design/methodology/approach
This study utilizes the theory of social network analysis (SNA) to make a comprehensive evaluation model for rating commodities. Specifically, the paper shows how to apply the network analysis, how it works and what the advantage is. The paper further presents the new model's properties and validates the model's applicability. The paper finally analyzes the results with respect to various dimensions of a movie rating database and report on the insights generated by the model.
Findings
Through the designed comparison analysis and the empirical analysis, the model is showed to be better than the traditional ones such as averaging, analytic hierarchy process (AHP) and several mentioned dimension-reduction techniques (DRTs) in terms of consistency and its ability to deal with the missing data.
Practical implications
The new model is solvable in polynomial time and proper for the large-scale data set. Furthermore, this model can also be seen as a data mining method which would be useful to improve insights into customer behavior.
Originality/value
The proposed method enables to give comprehensive rating results which can preserve the rankings implied by all the customers’ ratings, adapt to the database with the missing data and cost a low algorithm time and space.
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Yong Li, Yingchun Zhang, Gongnan Xie and Bengt Ake Sunden
This paper aims to comprehensively clarify the research status of thermal transport of supercritical aviation kerosene, with particular interests in the effect of cracking on heat…
Abstract
Purpose
This paper aims to comprehensively clarify the research status of thermal transport of supercritical aviation kerosene, with particular interests in the effect of cracking on heat transfer.
Design/methodology/approach
A brief review of current research on supercritical aviation kerosene is presented in views of the surrogate model of hydrocarbon fuels, chemical cracking mechanism of hydrocarbon fuels, thermo-physical properties of hydrocarbon fuels, turbulence models, flow characteristics and thermal performances, which indicates that more efforts need to be directed into these topics. Therefore, supercritical thermal transport of n-decane is then computationally investigated in the condition of thermal pyrolysis, while the ASPEN HYSYS gives the properties of n-decane and pyrolysis products. In addition, the one-step chemical cracking mechanism and SST k-ω turbulence model are applied with relatively high precision.
Findings
The existing surrogate models of aviation kerosene are limited to a specific scope of application and their thermo-physical properties deviate from the experimental data. The turbulence models used to implement numerical simulation should be studied to further improve the prediction accuracy. The thermal-induced acceleration is driven by the drastic density change, which is caused by the production of small molecules. The wall temperature of the combustion chamber can be effectively reduced by this behavior, i.e. the phenomenon of heat transfer deterioration can be attenuated or suppressed by thermal pyrolysis.
Originality/value
The issues in numerical studies of supercritical aviation kerosene are clearly revealed, and the conjugation mechanism between thermal pyrolysis and convective heat transfer is initially presented.
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Joana Baleeiro Passos, Daisy Valle Enrique, Camila Costa Dutra and Carla Schwengber ten Caten
The innovation process demands an interaction between environment agents, knowledge generators and policies of incentive for innovation and not only development by companies…
Abstract
Purpose
The innovation process demands an interaction between environment agents, knowledge generators and policies of incentive for innovation and not only development by companies. Universities have gradually become the core of the knowledge production system and, therefore, their role regarding innovation has become more important and diversified. This study is aimed at identifying the mechanisms of university–industry (U–I) collaboration, as well as the operationalization steps of the U–I collaboration process.
Design/methodology/approach
This study is aimed at identifying, based on a systematic literature review, the mechanisms of university–industry (U–I) collaboration, as well as the operationalization steps of the U–I collaboration process.
Findings
The analysis of the 72 selected articles enabled identifying 15 mechanisms of U–I collaboration, proposing a new classification for such mechanisms and developing a framework presenting the operationalization steps of the interaction process.
Originality/value
In this paper, the authors screened nearly 1,500 papers and analyzed in detail 86 papers addressing U–I collaboration, mechanisms of U–I collaboration and operationalization steps of the U–I collaboration process. This paper provides a new classification for such mechanisms and developing a framework presenting the operationalization steps of the interaction process. This research contributes to both theory and practice by highlighting managerial aspects and stimulating academic research on such timely topic.
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Prabhdeep Singh and Rajbir Kaur
The purpose of this paper is to provide more accurate structure that allows the estimation of coronavirus (COVID-19) at a very early stage with ultra-low latency. The machine…
Abstract
Purpose
The purpose of this paper is to provide more accurate structure that allows the estimation of coronavirus (COVID-19) at a very early stage with ultra-low latency. The machine learning algorithms are used to evaluate the past medical details of the patients and forecast COVID-19 positive cases, which can aid in lowering costs and distinctively enhance the standard of treatment at hospitals.
Design/methodology/approach
In this paper, artificial intelligence (AI) and cloud/fog computing are integrated to strengthen COVID-19 patient prediction. A delay-sensitive efficient framework for the prediction of COVID-19 at an early stage is proposed. A novel similarity measure-based random forest classifier is proposed to increase the efficiency of the framework.
Findings
The performance of the framework is checked with various quality of service parameters such as delay, network usage, RAM usages and energy consumption, whereas classification accuracy, recall, precision, kappa static and root mean square error is used for the proposed classifier. Results show the effectiveness of the proposed framework.
Originality/value
AI and cloud/fog computing are integrated to strengthen COVID-19 patient prediction. A novel similarity measure-based random forest classifier with more than 80% accuracy is proposed to increase the efficiency of the framework.