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In this paper, the authors take an amorphous flattened air-ground wireless self-assembling network system as the research object and focus on solving the wireless self-assembling network topology instability problem caused by unknown control communication faults during the operation of this system.

In the paper, the authors propose a neural network-based direct robust adaptive non-fragile fault-tolerant control algorithm suitable for the air-ground integrated wireless ad hoc network integrated system.

The simulation results show that the system eventually tends to be asymptotically stable, and the estimation error asymptotically tends to zero with the feedback adjustment of the designed controller. The system as a whole has good fault tolerance performance and autonomous learning approximation performance. The experimental results show that the wireless self-assembled network topology has good stability performance and can change flexibly and adaptively with scene changes. The stability performance of the wireless self-assembled network topology is improved by 66.7% at maximum.

The research results may lack generalisability because of the chosen research approach. Therefore, researchers are encouraged to test the proposed propositions further.

This paper designs a direct, robust, non-fragile adaptive neural network fault-tolerant controller based on the Lyapunov stability principle and neural network learning capability. By directly optimizing the feedback matrix K to approximate the robust fault-tolerant correction factor, the neural network adaptive adjustment factor enables the system as a whole to resist unknown control and communication failures during operation, thus achieving the goal of stable wireless self-assembled network topology.

Propose a more comprehensive explanation on the determinants and fluctuations of China’s exchange rate policy in the past decade (2005–2015).

Case study on China’s exchange rate policies in three respective stages since 2005 and then a comparative study on these three stages.

Put forward a two-pronged explanation on the determinants and fluctuations of China’s exchange rate policy in the past decade and arrive at three specific conclusions. First, external pressure is only one factor among many influencing the formation of China’s national interests (Guojia Liyi in Chinese) and the decision-making process on exchange rate policy. Second, national interest is the fundamental driving force and substratum for making China’s exchange rate policy. Third, in the short term, the specific exchange rate policies in different periods were not always in accordance to the national interests (or Guojia Liyi), due to the influences of some factors on the decision-making environment.

The comprehensive view is conducive to better explaining the formation and fluctuations of China’s exchange rate policy and consequently contributes to understanding and even predicting future policies.

This paper aims to investigate how knowledge sharing influences technological innovation capability (TIC) of the software small- and medium-sized enterprises (SSMEs).

Based on the theories regarding knowledge management, TIC, software engineering and open innovation, this paper constructed a research model comprising factors affecting knowledge sharing, knowledge sharing and TIC, and then tested the model quantitatively. The study focuses on SSMEs in China collecting 457 online questionnaires and uses a structural equation model to test the hypotheses.

The knowledge sharing culture, organizational structure, middle-level leadership and management system have significantly positive effects on tacit knowledge sharing; management system and IT support have significantly positive effects on explicit knowledge sharing; both explicit and tacit knowledge sharing have significantly positive effects on TIC.

The study enriches the research on knowledge sharing and TIC. However, it does not consider factors affecting knowledge sharing at the non-organizational level or the interaction between explicit and tacit knowledge sharing.

The study offers several recommendations/suggestions for helping SSMEs to promote and implement explicit or tacit knowledge sharing and TIC.

This paper examines the impact of knowledge sharing on TIC from the perspective of knowledge management deconstructing knowledge sharing from the epistemological dimension and the TIC of software companies on the basis of software engineering theory. It provided a new theoretical perspective for the research of knowledge management and technological innovation management in SSMEs.

With the rapid development of modern economy and the process of urbanization is faster, a large number of historical relics have been mercilessly destroyed in the urban reconstruction. In order to balance the contradiction between urban development and historical heritage and promote the harmonious development of new and old urban areas, it is necessary to research on the old urban areas from the perspective of historical landscape. Old urban area of Jingdezhen is taken as an example in this paper, the present situation of the reconstruction of the old city in Jingdezhen is analyzed. Then, by using the methodology of urban historical landscape, some specific methods for updating and designing the old urban area reconstruction of Jingdezhen is put forward, such as the elements of spatial form, urban texture, historical and cultural landscape elements, streets and alleys, the Changjiang River, public facilities and landscape sketches, and so on. A new design method of landscape transformation of old urban area is established. As the renewal method of respecting the urban history and cultural heritage is a very intelligent urban renewal model, it is found that the application of urban historical landscape in the old urban city is reasonable and effective, which is based on the development of the old urban area and pursues the coexistence of protection and development.

This paper aims to explore the developing trend of higher pedagogy, to promote the research of higher pedagogy to be more canonical and scientific and to improve the higher education theory.

The utility research uses a method of quantitative study, namely “content analysis”, to estimate and analyze the higher education theory literature on ten dimensionalities which include theme, author, abstract, keywords, subject, proposing of the issue, definition of key terms, research methods, conclusion, reference and annotations from 1996 to 2006 in China.

The analysis of the selected 250 academic theses and reports in the field of higher education shows that academic research and theoretical standard have been improved, meanwhile academic criterion have been formed by degrees in higher pedagogy within ten years. At the same time, there are still some problems in the papers and reports the authors have selected such as title, key words, proposing of the issue, researching method and conclusion.

This paper sums up the trend of research on higher education in China for the past ten years, and points out the problems in this trend and then proposes ways to improve the research of higher education in China.

This paper aims to investigate the reason for natural gas leakage from transmission pipelines between Linyi and Shouguang in China during sealing tests, explore the failure mechanism and provide a reference for taking reasonable measures to prevent such accidents.

Failure analysis for the steel pipe has been addressed with different methods, such as microstructure analysis, inclusion analysis, corrosion product analysis, macro- and micro-morphology analyses and bacterially catalyzed experiments.

Several bulges were observed, especially at the bottom of the steel pipe sample, with the distribution and positioning not related to the weld. The inner surface of the steel pipe was severely corroded, and the oxide scale was flaking in many places. The greatest corrosion area was identified at the bottom of the steel pipe near the gas leakage point. Severe pitting and perforation corrosion in the pipeline were observed, and the main corrosion reaction products were Fe3O4, FeO and FeS. The grain orientation distribution near the crack (coarse grains <101> and fine grains <111> at the microcrack tip) indicates that fine grains may be beneficial in hindering crack propagation.

The principal mechanism for the corrosion failure is supposed to be due to the interaction of chloride ions with the sulfate-reducing microorganisms present and the stress corrosion cracking by chloride and sulfide formed by the sulfate-reducing microorganisms.

The purpose of this paper is to improve the customer satisfaction by offering online personalized recommendation system.

By employing an innovative associative classification method, this paper is able to predict a customer’s pleasure during the online while-recommending process. Consumers can make an active decision to recommended products. Based on customer’s characteristics, a product will be recommended to the potential buyer if the model predicts that he/she will click to view the product. That is, he/she is satisfied with the recommended product. Finally, the feasibility of the proposed recommendation system is validated through a Taobao shop.

The results of the experimental study clearly show that the online personalized recommendation system maximizes the customer’s satisfaction during the online while-recommending process based on an innovative associative classification method on the basis of consumer initiative decision.

Conventionally, customers are considered as passive recipients of the recommendation system. However, customers are tired of the recommendation system, and they can do nothing sometimes. This paper designs a new recommendation system on the basis of consumer initiative decision. The proposed recommendation system maximizes the customer’s satisfaction during the online while-recommending process.

The time series forecasting is an essential methodology which can be used for analysing time series data in order to extract meaningful statistics based on the information obtained from past and present. These modelling approaches are particularly complicated when the available resources are limited as well as anomalous. The purpose of this paper is to propose a new hybrid forecasting approach based on unbiased GM(1,1) and artificial neural network (UBGM_BPNN) to forecast time series patterns to predict future behaviours. The empirical investigation was conducted by using daily share prices in Colombo Stock Exchange, Sri Lanka.

The methodology of this study is running under three main phases as follows. In the first phase, traditional grey operational mechanisms, namely, GM(1,1), unbiased GM(1,1) and nonlinear grey Bernoulli model, are used. In the second phase, the new proposed hybrid approach, namely, UBGM_BPNN was implemented successfully for forecasting short-term predictions under high volatility. In the last stage, to pick out the most suitable model for forecasting with a limited number of observations, three model-accuracy standards were employed. They are mean absolute deviation, mean absolute percentage error and root-mean-square error.

The empirical results disclosed that the UNBG_BPNN model gives the minimum error accuracies in both training and testing stages. Furthermore, results indicated that UNBG_BPNN affords the best simulation result than other selected models.

The authors strongly believe that this study will provide significant contributions to domestic and international policy makers as well as government to open up a new direction to develop investments in the future.

The new proposed UBGM_BPNN hybrid forecasting methodology is better to handle incomplete, noisy, and uncertain data in both model building and ex post testing stages.

Within the service sectors, Knowledge Intensive Business Services (KIBS) play an important role in local and regional economies as sources of competitive advantages and providing knowledge-intensive inputs to the business process of small and medium-sized enterprises. This study aims to analyze the changes in financial performance of KIBS industry in Italy over the period from 2012 to 2017.

This paper examines the efficiency of the KIBS firms by applying data envelopment analysis (DEA) to compute the Malmquist Productivity Index for the period under investigation. The DEA-based Malmquist productivity analysis is applied at firm level using a sample consisting 1.674 companies, representative of the Italian KIBS sector and related to three different NACE activity code (72-computing services; 73-research and development; 74 other professional business activities). The efficiency measures are then used to characterize KIBS firm financial performance through the analysis of average productivity patterns grouped by Italian geographical regions. The Malmquist productivity measures are decomposed into two components: efficiency change and technical change index. The overall analysis is coupled with a financial ratio analysis approach, selecting return on equity (ROE) and leverage ratio as descriptor to validate the results and better characterize differences in efficiency patterns among geographic-based groups of KIBS companies.

Over the period 2015-2017, the results show that the average annual growth of the overall Malmquist productivity index was positive in nine Italian regions that represent only 17 per cent of the total KIBS firms selected. On the other side, a decrease of the average performance measure is observed for the five geographic areas that contribute to 75.7 per cent of the total sample. In general, the technological change component, as a measure of innovation, strongly limits the productivity growth behavior of KIBS industry for all geographic regions. The use of selected financial ratio does not provide additional insight to the performance investigation and further in-depth studies are needed to better evaluate the correlation between average productivity results and regional business dynamics.

The study investigates the applicability of DEA-based Malmquist indices to the analysis of the productivity behavior of KIBS industry at regional level. It will be of value to provide first evidence to the policymakers to understand industry growth pattern in time frame selected and relate them to additional business factors to detect specific industry constraints.

The analysis in this paper contributes to the existing body of knowledge on industry performance measurement by applying specific analytical techniques to the productivity of Italian KIBS companies. The paper also contributes to the limited body of academic literature investigating KIBS industry at national level proposing a methodological framework that constitutes a first attempt to track average productivity behavior at regional level.