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Having read previous literature about vortex pump, we noticed that mechanisms of circulating flow and its relationship with energy transition remain unclear yet. However, this mechanism, which should be clarified, significantly influences the pump’s efficiency. To comply with the aim of investigating it, the 150WX-200-20 type pump is selected as study object in our present work.

Numerical simulation is conducted to formulate interactions between flow rate and geometric parameters of circulating flow with certain types of blade while experiments on inner flow are served as a witness to provide experimental confirmation of numerical results. Based on these, we coupled some parameters with the pump’s external performance to study their internal connections.

It is concluded that separatrix between circulating flow and other turbulent forms is not that clear under low flow rate. With flow increases, hydraulic losses coming of it will be dominant within the front chamber. Besides, we analogized circulating flow to vortices so as to make a quantitative analysis on its progressive evolution with changing flow, and vortices speaking for circulating flow can be divided into two groups. One is called main circulating flow vortex (hereinafter referred to as MCFV), which occurs all the time while subsidiary circulating flow vortices (hereinafter referred to as SCFV) appear in certain conditions. This context discusses the primary phase of our work with intent to follow up further with circulating flow characterized by vortices (hereinafter referred to as CFV). We confirmed that MCFV Vortex 1 (Vor1) directly influences the efficiency while SCFVs only play helping. As the flow goes to the given working condition, fluids in this pump tend to be steady with the size of CFVs getting larger and their shape being regular. Meanwhile, for MCFV Vor2 and Vor4, their geometric parameters are the key factors for efficiency. When CFVs become steady, they absorb other vortices nearby, as they have higher viscosity with the efficiency reaching its maximum.

The research results explore a new way to measure the circulating flow and help work out the causation of this flow pattern, which may be used to improve the vortex pump’s efficiency.

The special structure of the vortex pump contributes to its complex internal flow pattern. A type of horizontal 150WX-200-20 vortex pump is taken as a research subject to deeply study the progression and distribution of flow pattern in its channel. To explain the mechanism of flow in this pump, numerical analysis of the whole flow and experiment have been conducted.

The authors studied and analyzed the distribution and evolution of flow pattern under different flow, such as circulating-flow, through-flow and other forms. Finally, a model of flow pattern in the vortex pump has been built, which has more perfectly fit the reality.

They are through-flow affected by circulating-flow, main and subsidiary circulating-flow, vortices between vanes and other vortices (or liquid impingement) in volute. Entering the pump, part of the flow stays in vanes and turn into vortices while the other goes into the front chamber. The flow that runs into the front chamber will be divided into two parts. One part will be collected by viscosity into a vortex rope when it passing through the interface between the impeller and the vaneless chamber, which closely relates to the circulating-flow, and the rest directly goes out of the field through the diffuser. Besides, a fraction of circulating-flow joins the through-flow when it goes through the section V and leaves the pump.

The research results build a theoretical foundation for working out the flow mechanism of the vortex pump, improving its efficiency and optimizing its hydraulic design.

Medical errors cause a significant number of deaths. Providing training to medical staff can improve the quality of medical care. Hospitals have traditionally used face‐to‐face modality to train staff but they are beginning to adopt e‐learning systems that can easily deliver training at work or to other convenient locations. The purpose of this paper is to investigate factors leading to e‐learning adoption in hospitals.

A framework of factors leading to the adoption decision of e‐learning systems is first proposed. Survey data are collected to empirically test the proposed framework. The samples consist of senior executives and managers in hospitals.

It is found that three factors including managerial, organizational, and technological exhibit significant influences on the adoption decision. One novel result is that the organizational variable of hospital specialization significantly influences the decision to adopt e‐learning systems.

This study is one of the first to propose a model of adoption of e‐learning specifically in the context of hospitals. Limitations and strengths of the study and possible future research direction are also discussed.

From a practitioner's standpoint, the results of this study can help hospital administrators to accelerate the adoption of e‐learning systems.

This study is one of the first to propose a model of adoption of e‐learning specifically in the context of hospitals. It is expected that the model developed can assist to further understand the e‐learning adoption in hospitals.

The purpose of this paper is to analyze regional correlation contributions of urbanization rate and tourism revenue, based on the dynamic panel data from 2000 to 2010 of 31 provinces in China.

Based on the Modified Cobb-Douglas and fixed effect regression models, the study analyzes the dynamic panel data of 31 provinces in China from 2000 to 2010. The paper conducts tests on the correlation and the economic influence between urbanization rate and tourism revenue in different regions.

The empirical results show that on the national scale, the urbanization rate has a positive contribution to the increase rate of tourism revenue with 3.1 percent. The influence of urbanization on tourism revenue in different regions has considerable non-equilibrium characteristics. In the central region, the correlation contributing potential is even stronger than in the eastern and western regions. Different regions have significant regional disparities in the tourism growth pattern.

On the national scale, the urbanization rate has a positive correlation contribution to the development of tourism economics. Urbanization has made remarkable achievements, and has played an important role in propelling the development of tourism industry. In the process of deepening the urbanization trend, the urbanization rate has a positive contribution to the increase rate of tourism revenue with 3.1 percent.

Among the growing number of data mining (DM) techniques, outlier detection has gained importance in many applications and also attracted much attention in recent times. In the past, outlier detection researched papers appeared in a safety care that can view as searching for the needles in the haystack. However, outliers are not always erroneous. Therefore, the purpose of this paper is to investigate the role of outliers in healthcare services in general and patient safety care, in particular.

It is a combined DM (clustering and the nearest neighbor) technique for outliers’ detection, which provides a clear understanding and meaningful insights to visualize the data behaviors for healthcare safety. The outcomes or the knowledge implicit is vitally essential to a proper clinical decision-making process. The method is important to the semantic, and the novel tactic of patients’ events and situations prove that play a significant role in the process of patient care safety and medications.

The outcomes of the paper is discussing a novel and integrated methodology, which can be inferring for different biological data analysis. It is discussed as integrated DM techniques to optimize its performance in the field of health and medical science. It is an integrated method of outliers detection that can be extending for searching valuable information and knowledge implicit based on selected patient factors. Based on these facts, outliers are detected as clusters and point events, and novel ideas proposed to empower clinical services in consideration of customers’ satisfactions. It is also essential to be a baseline for further healthcare strategic development and research works.

This paper mainly focussed on outliers detections. Outlier isolation that are essential to investigate the reason how it happened and communications how to mitigate it did not touch. Therefore, the research can be extended more about the hierarchy of patient problems.

DM is a dynamic and successful gateway for discovering useful knowledge for enhancing healthcare performances and patient safety. Clinical data based outlier detection is a basic task to achieve healthcare strategy. Therefore, in this paper, the authors focussed on combined DM techniques for a deep analysis of clinical data, which provide an optimal level of clinical decision-making processes. Proper clinical decisions can obtain in terms of attributes selections that important to know the influential factors or parameters of healthcare services. Therefore, using integrated clustering and nearest neighbors techniques give more acceptable searched such complex data outliers, which could be fundamental to further analysis of healthcare and patient safety situational analysis.

Behavioral pattern mining for intelligent system such as SmEs sensor data are vitally important in many applications and performance optimizations. Sensor pattern mining (SPM) is also dynamic and a hot research issue to pervasive and ubiquitous of smart technologies toward improving human life. However, in large-scale sensor data, exploring and mining pattern, which leads to detect the abnormal behavior is challenging. The paper aims to discuss these issues.

Sensor data are complex and multivariate, for example, which data captured by the sensors, how it is precise, what properties are recorded or measured, are important research issues. Therefore, the method, the authors proposed Sequential Data Mining (SDM) approach to explore pattern behaviors toward detecting abnormal patterns for smart space fault diagnosis and performance optimization in the intelligent world. Sensor data types, modeling, descriptions and SPM techniques are discussed in depth using real sensor data sets.

The outcome of the paper is measured as introducing a novel idea how SDM technique’s scale-up to sensor data pattern mining. In the paper, the approach and technicality of the sensor data pattern analyzed, and finally the pattern behaviors detected or segmented as normal and abnormal patterns.

The paper is focussed on sensor data behavioral patterns for fault diagnosis and performance optimizations. It is other ways of knowledge extraction from the anomaly of sensor data (observation records), which is pertinent to adopt in many intelligent systems applications, including safety and security, efficiency, and other advantages as the consideration of the real-world problems.

The purpose of this paper is to study the architecture of holographic personalized portal, user modeling, commodity modeling and intelligent interaction.

In this paper, the authors propose crowd-science industrial ecological system based on holographic personalized portal and its interaction. The holographic personality portal is based on holographic enterprises, commodities and consumers, and the personalized portal consists of accurate ontology, reliable supply, intelligent demand and smart cyberspace.

The personalized portal can realize the information acquisition, characteristic analysis and holographic presentation. Then, the intelligent interaction, e.g. demand decomposition, personalized search, personalized presentation and demand prediction, will be implemented within the personalized portal.

The authors believe that their work on intelligent interaction based on holographic personalized portal, which has been first proposed in this paper, is innovation focusing on the interaction between intelligence and convenience.

Collective intelligence has drawn many scientists’ attention in many centuries. This paper shows the collective intelligence study process in a perspective of crowd science.

After summarizing the time-order process of related researches, different points of views on collective intelligence’s measurement and their modeling methods were outlined.

The authors show the recent research focusing on collective intelligence optimization. The studies on application of collective intelligence and its future potential are also discussed.

This paper will help researchers in crowd science have a better picture of this highly related frontier interdiscipline.

This paper aims to study the material conscious information network (MCIN) to present new models of clothing products and persons and propose new crowd-designing patterns to reconstruct an improved supply–demand relationship in clothing industry.

This paper aims to study the MCIN to present new models of clothing products and persons and propose new crowd-designing patterns to reconstruct an improved supply–demand relationship in clothing industry.

At last, this paper implements a prototype system of novel e-commerce platform based on the CDCI to illustrate the effectiveness and soundness of the CDCI modeling.

Different from most related works just focusing on the physiology dimension in the matching of customer and clothing, this paper proposes that the dimension of physiology, character, knowledge and experience should be synthetically considered.

The division of labor of e-commerce transaction system is an important research topic. However, there is a certain disparity between the current mainstream research model and the reality, which leads to a biased result. This paper aims to find the effects of transaction efficiency on the evolution of e-commerce transaction system’s division of labor and the relationships between the results and other parameters.

This paper puts forward a definition of transaction efficiency based on transaction services and establishes a model of middleman’s specialized production decision of transaction services on this basis.

The research results show that the transaction efficiency plays an important role on the change of middlemen’s division of labor level. The degree of economic specialization, price of commodities and transaction services and other associated factors also affect middlemen’s division of labor.

This paper is of great significance for evaluating the development level and forecast the development direction of e-commerce.