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The purpose of this paper is to propose a multi-criteria decision-making model based on the case-based reasoning (CBR) method for interval-valued probabilistic linguistic term set (IVPLTS), which can cluster different categories of building suppliers for targeted management.

First, a new score function and distance measure for IVPLTS are proposed. Second, a green building supplier evaluation criterion system is constructed from five aspects: operation management, green management, cooperation potential, service level and product information. Finally, the IVPLTS-CBR model is used to evaluate the green building suppliers and groups them into three preset categories.

The feasibility and validity of the proposed method are verified by comparing with the advanced TOPSIS method and the IVPLTS-based VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. The compared results show that the proposed method is more consistent with the actual situation and has strong theoretical significance and practical value.

This paper presents a new method for clustering construction suppliers. Decision makers can use this method to classify construction suppliers into different categories, so that they can be targeted management. In this way, suppliers can be better guided and motivated to accelerate the green transformation and contribute their share to achieve the strategic goal of carbon neutral and carbon peak as soon as possible.

A new score function and distance measure for IVPLTS are proposed. Besides, a novel IVPLTS-CBR method is applied to rank and cluster building suppliers.

In the face of external paradoxical requirements, the cognitive framework of managers and employees use to perceive, interpret and reconstruct information is important to ease anxiety and improve job performance. The Yin-Yang balancing of eastern philosophical thought is particularly good at explaining and predicting changes and conflict environments. For this reason, this study aims to propose the eastern construction of the paradoxical cognitive framework based on the Yin-Yang balancing theory and its antecedent framework.

This paper contrasts the similarity and differences between Chinese and Western philosophy’s thoughts on paradoxes. On this basis, the eastern construction of the paradoxical cognitive framework is proposed. Then, the paper puts forward the antecedent framework of managers’ cognitive framework and employees’ paradoxical cognitive framework.

This paper proposes the eastern construction of the paradoxical cognitive framework includes the following three dimensions: the unity-in-diversity of paradoxical elements, the asymmetric balance of paradoxical elements and mutual transformation of paradoxical elements. In addition, this paper proposes an antecedent framework of the eastern construction of the paradoxical cognitive framework – the paradoxical requirement of organizational environment exerts a direct impact on managers’ and employees’ paradoxical cognitive framework; managers’ paradoxical cognitive framework has a positive impact on paradoxical leadership; paradoxical leadership exerts an indirect impact on employees’ paradoxical cognitive framework through the collective paradoxical cognitive framework; paradoxical leadership directly affects employees’ paradoxical cognitive framework.

This paper focuses on comparing the similarities and differences of the individual paradoxical cognitive framework in Chinese and Western cultures and proposes the eastern construction of the paradoxical cognitive framework and its antecedent framework. Future research needs to further verify the theoretical framework proposed in this paper.

This paper makes a detailed comparison of the paradox views in Chinese and Western philosophy. It is the first to propose the eastern construction of the paradoxical cognitive framework and its antecedent framework, laying a theoretical foundation for future empirical research.

This paper aims to examine how a firm’s capability affects its political networking in emerging economies and how the institutional environment influences the relationship between a firm’s capability and its political networking.

The authors test the theoretical model by analyzing a database from a World Bank survey in China.

The results show a nonlinear (U-shaped) relationship between a firm’s capability and its efforts in political networking. The relationship between a firm’s capability and political networking is contingent on the institutional environment, as reflected in institutional development and industry regulation.

This study elucidates political networking in emerging economies and contributes to research on corporate political strategy.

The purpose of this paper is to propose a fast, accurate and efficient algorithm for assessment of transient behavior of grounding grids buried in horizontal multilayered earth model considering soil ionization effect.

The purpose of this paper is to develop a numerical simulation method to calculate the lightning impulse response of the grounding grid buried in a horizontal multilayered earth model. The mathematical model about the hybrid method based on PI basic function belonging to time domain is proposed in the paper; the mode can precisely calculate the lightning current distribution and lightning impulse response to grounding grids buried in horizontal multilayered soil model considering soil ionization effect. To increase computing efficiency, quasi-static complex image method (QSCIM) and its time-domain Green’s function closed form are introduced in the model.

The hybrid model is rather stable, with the respect to the number of elements used and with excellent convergence rate. In addition, because this mathematical model belongs to the time domain algorithm, it is very powerful for the simulation of soil ionization caused by high amplitude lightning current.

To increase computing efficiency, QSCIM and its time domain Green's function closed form are introduced in the model.

The mathematical model about the hybrid method based on PI basic function can precisely calculate the lightning current distribution and lightning impulse response to grounding grids buried in horizontal multilayered soil model considering the soil ionization effect.

Considering the soil ionization effect, the simulation calculation of lightning impulse response of substation grounding grid buried in the actual horizontal multilayered earth can effectively support the scientific and efficient design of lightning protection performance of substation grounding grid.

The hybrid model in time domain is originally developed by the authors and used to precisely calculate the lightning current distribution and lightning impulse response to grounding grids buried in horizontal multilayered soil model considering soil ionization effect. It is simple and very efficient and can easily be extended to arbitrary grounding configurations.

The purpose of this paper is to provide a better understanding of the development of intelligent agriculture (IA) in China, which is an important tendency in advancing the agricultural productivity in the coming era.

Considering publications as featured evidence of an emerging phenomenon, the authors review publications of IA. Specifically, the use of term, definition and examples of IA, both English and Chinese literature, and government policies of China are all reviewed. Additionally, the authors use basic statistical and thematic analysis to help synthesizing the literature and drawing conclusions. Findings from various sources of publications supplement with each other.

IA in China has shown three main characteristics: unbalanced geographic distribution, an early stage of the trend and attention mainly focused on a limited range of technologies. Compared with the development of IA in other countries, such as Japan, India and the USA, featured with diversified properties, similarities and differences of IA development in China and in other countries are also discussed.

This general review contributes by uncovering the emergence of IA, identifying its general definition with a comprehensive set of practical examples and pointing out the present characteristics and problems of IA development in China. The general review provides a necessary summary for the policy makers and researchers to have a systematic understanding of IA and better promote its future development. At last, the paper calls for a process-based strategy with different goals at different stages, a sustainable mechanism coordinated by multiple participants, and a localized consideration for relevant policy making.

This paper aims to develop a climbing robot to help people inspect lamps of high-mast lighting.

The robot consists of driving mechanism, suspension mechanism and compression mechanism. The driving mechanism is realized by link chains and sprockets, which are arranged opposite to each other, to form a dual caterpillar mechanism. The compression mechanism squeezes the caterpillar, and rubber feet “grasps” the steel rope to generate enough adhesion forces. The suspension mechanism is used to compensate the contraction or extension of the chains. The robot is equipped with a DC motor with a rated power of 250 W and a wireless module to communicate with the operator’s console. The dynamic model of the robot and the control strategy is derived, and the stability of the controller is proofed.

The payload experiment shows the robot can afford up to 3.7 times payload versus its own weight. Even when the payload is 30 kg, the robot can maintain a speed of the 1 m/s. The experiments also show that the tracking error of the robot reaches zero.

The proposed moving mechanism has a high load/weight ratio, which is a verified solution for the cable inspection purpose.

A rope climbing robot for high mast lighting inspection is proposed. The developed mechanism can reach a speed of 1 m/s with the payload of 30 kg, while its own weight is only 15.6 kg. The payload/weight ratio of the robot is 2.24; this value is rather good in many climbing robots reported in other renowned journal.

Scattered parts are laid randomly during the manufacturing process and have difficulty to recognize and manipulate. This study aims to complete the grasp of the scattered parts by a manipulator with a camera and learning method.

In this paper, a cascaded convolutional neural network (CNN) method for robotic grasping based on monocular vision and small data set of scattered parts is proposed. This method can be divided into three steps: object detection, monocular depth estimation and keypoint estimation. In the first stage, an object detection network is improved to effectively locate the candidate parts. Then, it contains a neural network structure and corresponding training method to learn and reason high-resolution input images to obtain depth estimation. The keypoint estimation in the third step is expressed as a cumulative form of multi-scale prediction from a network to use an red green blue depth (RGBD) map that is acquired from the object detection and depth map estimation. Finally, a grasping strategy is studied to achieve successful and continuous grasping. In the experiments, different workpieces are used to validate the proposed method. The best grasping success rate is more than 80%.

By using the CNN-based method to extract the key points of the scattered parts and calculating the possibility of grasp, the successful rate is increased.

This method and robotic systems can be used in picking and placing of most industrial automatic manufacturing or assembly processes.

Unlike standard parts, scattered parts are randomly laid and have difficulty recognizing and grasping for the robot. This study uses a cascaded CNN network to extract the keypoints of the scattered parts, which are also labeled with the possibility of successful grasping. Experiments are conducted to demonstrate the grasping of those scattered parts.

The purpose of this paper is to design a unified operational design domain (ODD) monitoring framework for mitigating Safety of the Intended Functionality (SOTIF) risks triggered by vehicles exceeding ODD boundaries in complex traffic scenarios.

A unified model of ODD monitoring is constructed, which consists of three modules: weather condition monitoring for unusual weather conditions, such as rain, snow and fog; vehicle behavior monitoring for abnormal vehicle behavior, such as traffic rule violations; and road condition monitoring for abnormal road conditions, such as road defects, unexpected obstacles and slippery roads. Additionally, the applications of the proposed unified ODD monitoring framework are demonstrated. The practicability and effectiveness of the proposed unified ODD monitoring framework for mitigating SOTIF risk are verified in the applications.

First, the application of weather condition monitoring demonstrates that the autonomous vehicle can make a safe decision based on the performance degradation of Lidar on rainy days using the proposed monitoring framework. Second, the application of vehicle behavior monitoring demonstrates that the autonomous vehicle can properly adhere to traffic rules using the proposed monitoring framework. Third, the application of road condition monitoring demonstrates that the proposed unified ODD monitoring framework enables the ego vehicle to successfully monitor and avoid road defects.

The value of this paper is that the proposed unified ODD monitoring framework establishes a new foundation for monitoring and mitigating SOTIF risks in complex traffic environments.

Existing calibration methods mainly focus on the camera laser-plane calibration of a single laser-line length, which is not convenient and cannot guarantee the consistency of the results when several three-dimensional (3D) scanners are involved. Thus, this study aims to provide a unified step for different laser-line length calibration requirements for laser profile measurement (LPM) systems.

3D LPM is the process of converting physical objects into 3D digital models, wherein camera laser-plane calibration is critical for ensuring system precision. However, conventional calibration methods for 3D LPM typically use a calibration target to calibrate the system for a single laser-line length, which needs multiple calibration patterns and makes the procedure complicated. In this paper, a unified calibration method was proposed to automatically calibrate the camera laser-plane parameters for the LPM systems with different laser-line lengths. The authors designed an elaborate planar calibration target with different-sized rings that mounted on a motorized linear platform to calculate the laser-plane parameters of the LPM systems. Then, the camera coordinates of the control points are obtained using the intersection line between the laser line and the planar target. With a new proposed error correction model, the errors caused by hardware assembly can be corrected. To validate the proposed method, three LPM devices with different laser-line lengths are used to verify the proposed system. Experimental results show that the proposed method can calibrate the LPM systems with different laser-line lengths conveniently with standard steps.

The repeatability and accuracy of the proposed calibration prototypes were evaluated with high-precision workpieces. The experiments have shown that the proposed method is highly adaptive and can automatically calibrate the LPM system with different laser-line lengths with high accuracy.

In the repeatability experiments, there were errors in the measured heights of the test workpieces, and this is because the laser emitter had the best working distance and laser-line length.

By using this proposed method and device, the calibration of the 3D scanning laser device can be done in an automatic way.

The calibration efficiency of a laser camera device is increased.

The authors proposed a unified calibration method for LPM systems with different laser-line lengths that consist of a motorized linear joint and a calibration target with elaborately designed ring patterns; the authors realized the automatic parameter calibration.

China’s national carbon market will be officially launched in 2020, when it will become the world’s largest carbon market. However, China’s carbon market is faced with various major challenges. One of the most important challenges is its impact on the social and economic development of arid and semi-arid regions. By simulating the carbon price trends under different economic development and energy consumption levels, this study aims to help the government can plan ahead to formulate various countermeasures to promote the integration of arid and semi-arid regions into the national carbon market.

To achieve this goal, this paper builds a back propagation neural network model, takes the third phase of the European Union Emissions Trading System (EU ETS) as the research object and uses the mean impact value method to screen out the important driving variables of European Union Allowance (EUA) price, including economic development (Stoxx600, Stoxx50, FTSE, CAC40 and DAX), black energy (coal and Brent), clean energy (gas, PV Crystalox Solar and Nordex) and carbon price alternatives Certification Emission Reduction (CER). Finally, this paper sets up six scenarios by combining the above variables to simulate the impact of different economic development and energy consumption levels on carbon price trends.

Under the control of the unchanged CER price level, economic development, black energy and clean energy development will all have a certain impact on the EUA price trends. When economic development, black energy consumption and clean energy development are on the rise, the EUA price level will increase. When the three types of variables show a downward trend, except for the sluggish development of clean energy, which will cause the EUA price to rise sharply, the EUA price trend will also decline accordingly in the remaining scenarios.

On the one hand, this paper incorporates driving factors of carbon price into the construction of carbon price prediction system, which not only has higher prediction accuracy but also can simulate the long-term price trend. On the other hand, this paper uses scenario simulation to show the size, direction and duration of the impact of economic development, black energy consumption and clean energy development on carbon prices in a more intuitive way.