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In robot programming by demonstration (PbD) of small parts assembly tasks, the accuracy of parts poses estimated by vision-based techniques in demonstration stage is far from enough to ensure a successful execution. This paper aims to develop an inference method to improve the accuracy of poses and assembly relations between parts by integrating visual observation with computer-aided design (CAD) model.

In this paper, the authors propose a spatial information inference method called probabilistic assembly graph with optional CAD model, shorted as PAGC*, to achieve this task. Then an assembly relation extraction method from CAD model is designed, where different assembly relation descriptions in CAD model are summarized into two fundamental relations that are colinear and coplanar. The relation similarity, distance similarity and rotation similarity are adopted as the similar part matching criterions between the CAD model and the observation. The knowledge of part in CAD is used to correct that of the corresponding part in observation. The likelihood maximization estimation is used to infer the accurate poses and assembly relations based on the probabilistic assembly graph.

In the experiments, both simulated data and real-world data are applied to evaluate the performance of the PAGC* model. The experimental results show the superiority of PAGC* in accuracy compared with assembly graph (AG) and probabilistic assembly graph without CAD model (PAG).

The paper provides a new approach to get the accurate pose of each part in demonstration stage of the robot PbD system. By integrating information from visual observation with prior knowledge from CAD model, PAGC* ensures the success in execution stage of the PbD system.

The purpose of this paper is to improve the precision of gangue detection. In the real production environment, some gangue features are not obvious, and it is difficult to distinguish between coal and gangue. The color of the conveyor belt is similar to the gangue, the background noise also brings challenge to gangue detection. To address the above problems, we propose a feature aggregation method based on optical flow (FAOF).

An FAOF is proposed. First, to enhance the feature representation of the current frame, FAOF applies the timing information of video stream, propagates the feature information of the past few frames to the current frame by optical flow. Second, the coordinate attention (CA) module is adopted to suppress the noise impact brought by the background of convey belt. Third, the Mish activation function is used to replace rectified linear unit to improve the generalization capability of our model.

The experimental results show that the gangue detection model proposed in this paper improve 4.3 average precision compared to baseline. This model can effectively improve the accuracy of gangue detection in real production environment.

The key contributions are as follows: this study proposes an FAOF; this study adds CA module and Mish to reduce noise from the background of the conveyor belt; and this study also constructs a large gangue data set.

The rapid development of 5G technology brings the expansion of the internet of things (IoT). A large number of devices in the IoT work independently, leading to difficulties in management. This study aims to optimize the member structure of the IoT so the members in it can work more efficiently.

In this paper, the authors consider from the perspective of crowd science, combining genetic algorithms and crowd intelligence together to optimize the total intelligence of the IoT. Computing, caching and communication capacity are used as the basis of the intelligence according to the related work, and the device correlation and distance factors are used to measure the improvement level of the intelligence. Finally, they use genetic algorithm to select a collaborative state for the IoT devices.

Experimental results demonstrate that the intelligence optimization method in this paper can improve the IoT intelligence level up to ten times than original level.

This paper is the first study that solves the problem of device collaboration in the IoT scenario based on the scientific background of crowd intelligence. The intelligence optimization method works well in the IoT scenario, and it also has potential in other scenarios of crowd network.

Explains why, following China‘s implementation of a market economy, public accounting firms were required to affiliate (hook‐up) with existing government or educational institutions until 1993 when partnerships and limited liability firms were also allowed. Describes the rules relating to independent accounting firms and changes which should foster their development but reports that, in fact, most firms are still affiliated. Discusses the reasons for this and the resulting problems, e.g. lack of competition and independence, low quality of service and increases in fraud, misrepresentation and under‐disclosure. Reveals that despite the 1995 exposure draft on eliminating the hooking‐up structure few de‐affiliations have taken place and identifies four problems which need solving if full de‐affiliation is to be achieved.

The purpose of this paper is to evaluate management accounting research in developing countries and formulate suggestions for its progression.

This is a desk based study of existing literature analysed through a framework of management control transformation in developing countries derived from the authors' research.

Research is growing, especially on accounting in state‐owned and privatised enterprises but more is needed on small and micro enterprises, agriculture, non‐governmental organisations, and transnational institutions.

This is the first review of this area and thus should help intending and existing scholars.

This paper provides, first, a historical perspective of accounting research relating to Asian/Pacific countries as seen from the vantage of the leading international journal in the United States and, second, a bibliographical data base and index of twenty‐six years of articles on this region of the world. It accomplishes the first objective by presenting a tabular profile of research in international accounting as it pertains to countries in the Asian/Pacific Rim region as shown in articles published in the International Journal of Accounting (formerly, the International Journal of Accounting, Education and Research) and related publications which appeared from 1965 to 1990. The articles are classified according to country, research methodology, subject, and five‐year time periods. The paper accomplishes the second objective by providing an annotated bibliography of 125 articles on Asian/Pacific Rim countries and indices by country and methodology, and subject.

This papers aims to provide a fixed cutter axis control (F-CAC) industrial robot (IR) milling for NURBS surfaces with large fluctuation, which can avoid over-cut and interference during IR milling in contrast to variable cutter axis control (V-CAC) IR milling.

After the design of a target surface, the IR reciprocating milling trajectory can be obtained using NURBS mapping projection method. A set of interpolation points of the reciprocating trajectory can be calculated using the equi-chord interpolation method. Combining with F-CAC method and curvature estimation, the IR reciprocating trajectory of the tool center point (TCP) without over-cut can be obtained. The programs corresponding to posture control using F-CAC can be generated by IR kinematics.

In contrast to the V-CAC milling method, the F-CAC method can machine successfully the NURBS surfaces with large fluctuation. The simulation and machining proves that F-CAC is feasible and effective to machine NURBS surface with large fluctuation without over-cut phenomenon. The F-CAC has wide application in carving and woodworking industry at present.

The F-CAC method is very practical and effective for IR milling of complex NURBS surfaces with large fluctuation without over-cut and interference phenomenon.

This paper aims to explore the future path of agricultural development in China toward 2060 under the dual carbon goals, so as to inform better policy choices for facilitating agricultural and rural transformation toward the goal of maintaining food security, sustainable income growth and low carbon emission.

This study employs a single-country, multi-sectoral computable general equilibrium model, CHINAGEM model and develops eight illustrative scenarios to simulate the impacts of attaining dual carbon goals on agricultural development in China. Additional two scenarios have also been designed to inform better policy making with the aim to offset the negative impact of the decarbonization schemes through facilitating agricultural technology progress.

Dual carbon goals are projected to impose substantial negative impact on agricultural productions and consumptions in China in the coming four decades. Under the assumption of business as usual, agricultural production will reduce by 0.49–8.94% along with the attainment of carbon neutrality goal by 2060, with the production of cereals and high-value being more severely damaged. To mitigate the adverse impact of the decarbonization schemes, it is believed that fastening technology progress in agriculture is one of the most efficient ways for maintaining domestic food security without harming the dual carbon goals. In particular, if agricultural productivity (particularly, for cereals and high-value products) can be increased by another 1% per year, the production losses caused by carbon emission mitigation will be fully offset. This implies that promoting technology progress is still the best way to facilitate agricultural development and rural transformation in future China.

The paper contributes to the literature in better informing the impact of dual carbon goals on China's agriculture and the effectiveness of technology progress in agriculture on buffering the adverse impact of the decarbonization schemes and promoting agricultural development.

The evolution of crowd intelligence is a mainly concerns issue in the field of crowd science. It is a kind of group behavior that is superior to the individual’s ability to complete tasks through the cooperation of many agents. In this study, the evolution of crowd intelligence is studied through the clustering method and the particle swarm optimization (PSO) algorithm.

This study proposes a crowd evolution method based on intelligence level clustering. Based on clustering, this method uses the agents’ intelligence level as the metric to cluster agents. Then, the agents evolve within the cluster on the basis of the PSO algorithm.

Two main simulation experiments are designed for the proposed method. First, agents are classified based on their intelligence level. Then, when evolving the agents, two different evolution centers are set. Besides, this paper uses different numbers of clusters to conduct experiments.

The experimental results show that the proposed method can effectively improve the crowd intelligence level and the cooperation ability between agents.

This paper proposes a crowd evolution method based on intelligence level clustering, which is based on the clustering method and the PSO algorithm to analyze the evolution.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.