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Nuclear waste tanks need to be cut into pieces before they can be safely disposed of, but the cutting process produces a large amount of aerosols with radiation, which is very harmful to the health of the operator. The purpose of this paper is to establish an intelligent strategy for an integrated robot designed for measurement and cutting, which can accurately identify and cut unknown nuclear waste tanks and realize autonomous precise processing.

A robot system integrating point cloud measurement and plasma cutting is designed in this paper. First, accurate calibration methods for the robot, tool and hand-eye system are established. Second, for eliminating the extremely scattered point cloud caused by metal surface refraction, an omnidirectional octree data structure with 26 vectors is proposed to extract the point cloud model more accurately. Then, a minimum bounding box is calculated for limiting the local area to be cut, the local three-dimensional shape of the nuclear tank is fitted within the bounding box, in which the cutting trajectories and normal vectors are planned accurately.

The cutting precision is verified by changing the tool into a dial indicator in the simulation and the experiment process. The octree data structure with omnidirectional pointing vectors can effectively improve the filtering accuracy of the scattered point cloud. The point cloud filter algorithm combined with the structure calibration methods for the integrated measurement and processing system can ensure the final machining accuracy of the robot.

Aiming at the problems of large measurement noise interference, complex transformations between coordinate systems and difficult accuracy guarantee, this paper proposes structure calibration, point cloud filtering and point cloud-based planning algorithm, which can greatly improve the reliability and accuracy of the system. Simulation and experiment verify the final cutting accuracy of the whole system.

In gearbox fault diagnosis, identifying the fault type and severity simultaneously, as well as the compound fault containing multiple faults, is necessary.

To diagnose multiple faults simultaneously, this paper proposes a multichannel and multi-task convolutional neural network (MCMT-CNN) model.

Experiments were conducted on a bearing dataset containing different fault types and severities and a gearbox compound fault dataset. The experimental results show that MCMT-CNN can effectively extract features of different tasks from vibration signals, with a diagnosis accuracy of more than 97%.

Vibration signals at different positions and in different directions are taken as the MC inputs to ensure the integrity of the fault features. Fault labels are established to retain and distinguish the unique features of different tasks. In MCMT-CNN, multiple task branches can connect and share all neurons in the hidden layer, thus enabling multiple tasks to share information.

The purpose of this paper is to further explore the co-citation and bibliographic-coupling relationship among the core authors in the field of Chinese information science (IS), to expose research activity and author impact, and to make induction analyses about Chinese IS research patterns and theme evolution.

The research data include 8,567 papers and 70,947 cited articles in the IS field indexed by Chinese Social Sciences Citation Index from 2000 to 2009. Author co-citation analysis, author bibliographic-coupling analysis, social network analysis, and factor analysis were combined to explore co-citation and bibliographic-coupling relationships and to identify research groups and subjects.

Scholars with greatest impact are different from the most active scholars of Chinese IS; there is no uniform impact pattern forming since authors’ impact subjects are scattered and not steady; while authors’ research activities present higher independence and concentration, there is still no steady research pattern due to no deep research existing. Furthermore, Chinese IS studies can be delineated by: foundation or extension. The research subjects of these two parts, as well as their corresponding/contributing authors, are different under different views. The general research status of core authors is concentrated, while their impact is broad.

The combined use of some related methods could enrich the development and methodology research of the discipline, and the results establish a reference point on the development of IS research.

This study aims to explore the relationship between folk religious place-making and the development of urban public spaces and summarize its influence on community network construction and daily behavior to discover the authentic practices and role of folk faith culture in social space.

Taking Macau's Shi Gandang Temple and its belief culture as an example, on-site research, historical evidence and interviews were used to elaborate and analyze the processes of place-making, social functions, management mechanisms and folk culture to establish a new perception of folk religious place-making in contemporary urban spaces.

The article argues that the culture of folk beliefs profoundly influences urban spaces and the social management system of Macau and has a positive significance in building the local community and geopolitical relations. In addition, it suggests that the participation of folk religious places in local practices is important as key nodes and emotional hubs of local networks, reconciling conflicts between communities of different backgrounds and driving urban spaces toward diversity while forming a positive interaction and friendly cooperation between regional development and self-contained management mechanisms, governance models and cultural orientations.

This study takes an architectural and anthropological perspective of the impact of faith on urban spaces and local governance, using the Shi Gandang Temple in Macau as an example, to complement related studies.

The purpose of this paper is to carry out numerical modeling of single-blow transient analysis using FLUENT porous media model for estimation of heat transfer and pressure drop characteristics of offset and wavy fins.

A computational fluid dynamics program FLUENT has been used to predict the design data in terms of j and f factors for plate-fin heat exchanger wavy and offset strip fins, which are widely used in aerospace applications.

The suitable design data in terms of Colburn j and Fanning friction f factors is generated and presented correlations for wavy fins covering the laminar, transition and turbulent flow regimes.

The correlations for the friction factor f and Colburn factor j have been found to be good by comparing with other references. The correlations can be used by the heat exchanger designers and can reduce the number of tests and modification of the prototype to a minimum for similar applications and types of fins.

This paper applies a volume-price probability wave differential equation to propose a conceptual theory and has innovative behavioral interpretations of intraday dynamic market equilibrium price, in which traders' momentum, reversal and interactive behaviors play roles.

The authors select intraday cumulative trading volume distribution over price as revealed preferences. An equilibrium price is a price at which the corresponding cumulative trading volume achieves the maximum value. Based on the existence of the equilibrium in social finance, the authors propose a testable interacting traders' preference hypothesis without imposing the invariance criterion of rational choices. Interactively coherent preferences signify the choices subject to interactive invariance over price.

The authors find that interactive trading choices generate a constant frequency over price and intraday dynamic market equilibrium in a tug-of-war between momentum and reversal traders. The authors explain the market equilibrium through interactive, momentum and reversal traders. The intelligent interactive trading preferences are coherent and account for local dynamic market equilibrium, holistic dynamic market disequilibrium and the nonlinear and non-monotone V-shaped probability of selling over profit (BH curves).

The authors will understand investors' behaviors and dynamic markets through more empirical execution in the future, suggesting a unified theory available in social finance.

The authors can apply the subjects' intelligent behaviors to artificial intelligence (AI), deep learning and financial technology.

Understanding the behavior of interacting individuals or units will help social risk management beyond the frontiers of the financial market, such as governance in an organization, social violence in a country and COVID-19 pandemics worldwide.

It uncovers subjects' intelligent interactively trading behaviors.

This paper aims to reveal how different types of events and top management teams' (TMTs’) cognitive frames affect the generation of breakthrough innovations.

Drawing on the event system theory and upper echelon theory, this study chose a Chinese manufacturing enterprise as the case firm and conducted an exploratory single-case study to unpack how breakthrough innovation generates over time.

By conducting the in-depth case analysis, the study revealed that firms do not produce breakthrough innovation in the catch-up stage and parallel-running stage but achieve it in the leading stage. It also indicated that when facing proactive events in the catch-up stage, TMTs often adopt a contracted lens, being manifested as consistency orientation, less elastic organizational identity and narrower competitive boundaries. In addition, they tend to adopt a contracted lens when facing reactive and proactive events in the parallel-running stage. In the face of reactive and proactive events in the leading stage, they are more inclined to adopt an expanded lens, being manifested as a coexistence orientation, more elastic organizational identity and wider competitive boundaries.

First, by untangling how TMT's cognitive frame functions in breakthrough innovations, this paper provides a micro-foundation for producing breakthrough innovations and deepens the understanding of upper echelon theory by considering the cognitive dimension of TMTs. Second, by teasing out several typical events experienced by the firm, this paper is the first attempt to reveal how events affect the generation of breakthrough innovation. Third, the work extends the application of the event system theory in technological innovation. It also provides insightful implications for promoting breakthrough innovations by considering the role of proactive and reactive events a firm experiences and TMT's perceptions.

This paper investigates and compares the impact of foreign direct investment (FDI) inflows (flow and stock) on bank off-balance sheet (OBS) activities in aggregate as well as at the level of conventional and Islamic banks in GCC countries. It also tests hypotheses of direct and indirect impacts of FDI flow and FDI stock on OBS activities.

This paper uses both static and dynamic panel generalized methods of moments (GMM) estimation techniques to analyze the data of 70 GCC banks (45 conventional and 25 Islamic banks) over the period 1995–2017.

Empirical results indicate that FDI flow and FDI stock have a significant negative direct impact on OBS activities of GCC banks. The results lend support for the direct channel hypothesis for the effect of FDI on OBS activities and find no evidence in support of the indirect channel hypothesis. OBS activities from conventional banks appear to be more affected than those from Islamic banks.

The results of this study are expected to trigger appropriate policy response from the central banks of the respective GCC countries as well as their governments.

It is widely recognized that FDI inflows are of great importance to the economic development of emerging and developing countries. However, their impact on bank OBS activities has so far not been subject to accurate empirical assessment. This paper aims to fill this gap by providing an in-depth quantitative analysis of the impact of FDI flow and FDI stock separately, on bank OBS activities for both conventional and Islamic banks in GCC countries. It distinguishes between direct and indirect channels through which FDI flow and FDI stock may affect OBS activities for banks as a whole and both conventional and Islamic banks separately. It also uses both static and dynamic panel GMM estimation techniques to analyze the data.