Search results

Feature extraction from 3D datasets is a current problem. Machine learning is an important tool for classification of complex 3D datasets. Machine learning classification techniques are widely used in various fields, such as text classification, pattern recognition, medical disease analysis, etc. The aim of this study is to apply the most popular classification and regression methods to determine the best classification and regression method based on the geodesics.

The feature vector is determined by the unit normal vector and the unit principal vector at each point of the 3D surface along with the point coordinates themselves. Moreover, different examples are compared according to the classification methods in terms of accuracy and the regression algorithms in terms of R-squared value.

Several surface examples are analyzed for the feature vector using classification (31 methods) and regression (23 methods) machine learning algorithms. In addition, two ensemble methods XGBoost and LightGBM are used for classification and regression. Also, the scores for each surface example are compared.

To the best of the author’s knowledge, this is the first study to analyze datasets based on geodesics using machine learning algorithms for classification and regression.

Cognitive maps are used in group decision processes to structure problems. The problem structuring methods helps decision makers to improve the comprehension of the problem, identifying alternative actions and conflicts. However, represents the individual perceptions in a representative group decision into a single structure can be a complex task. The paper aims to discuss these issues.

The objective of this paper is to improve the process of discussion, obtaining the interests and views of the participants and provide parameters to assist the analyst to guide the process. Furthermore, it is possible to analyze how participants are aligned or diverge from the group. The literature review presents some approaches for cognitive maps analysis, but there is a lack of structured methods to analyze them. This paper proposes a structure procedure for the aggregation of cognitive maps in three parts: workshop to generate individual maps, the aggregation of individual maps and the refinement of the global map.

An example illustrates the application of the proposed method and shows the construction of a global map that summarizes the concepts that participants consider important.

This paper presents a new procedure that allows reducing the bias of the analyst in the aggregation of individual cognitive maps maintaining the relevant information and allows decision makers know and approve the aggregation procedure.

To explore and explain differences in reform of activation policies, comparing the shifts in governance in France and The Netherlands from the 1990s onwards.

The paper is based on in‐depth case studies of the reform process in activation policies, using documentary sources and interviews with several stake‐holders. The theoretical scope is the debate on institutional change, path‐dependency and convergence.

Although both countries demonstrate converging tendencies in the transformation of their activation policies, there are remarkable differences in the new modes of governance. Moving away from a traditionally hierarchical organisation, France is gradually developing a network model with more emphasis on decentralisation. Alternatively, The Netherlands privatised their public employment services and explore principal – agent realtions in activation. The institutional context of both nation, in particular the concept of path‐dependency, seems crucial in the explanation of these differences. However, some new elements are path‐breaking in a national context but do not illustrate converging trends.

This comparative study is aimed at the fields of employment services, social benefits and social assistance in two countries. For a more complete approach of the changes is activation policies, further research is needed to include other fields of social policy and other nations whithin Europe.

The paper develops both empirical and theoretical conclusions on the path‐dependent and convergin elements in transforming labour market coordination throughout Europe.

The credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.

Using the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.

The results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.

Credit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

High-tech enterprises, as the national innovation powerhouses, have garnered considerable interest, particularly regarding their technological innovation capabilities. Nevertheless, prevalent research tends to spotlight the impact of individual factors on innovative behavior, with only a fraction adopting a comprehensive viewpoint, scrutinizing the causal amalgamations of precursor conditions influencing the overall innovation proficiency of high-tech enterprises.

This paper employs a hybrid approach integrating necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) to examine the combinatorial effects of antecedent factors on high-tech enterprises' innovation output. Our analysis draws upon data from 46 listed Chinese high-tech enterprises. To promote technological innovation within high-tech enterprises, we introduce a novel perspective that emphasizes technological innovation networks, grounded in a network agents-structure-environment framework. These antecedents are government subsidy, tax benefits, customer concentration, purchase concentration rate, market-oriented index and innovation environment.

The findings delineate four configurational pathways leading to high innovative output and three pathways resulting in low production.

This study thereby enriches the body of knowledge around technological innovation and provides actionable policy recommendations.

This study aims to empirically examine the conditions for latecomers to successfully pursue path-creating catch-up strategies. In particular, the company is divided into two conditions: the external environment, which refers to the gap in the market share between the leaders and latecomers, and the internal capacities of the company, such as the company’s absorptive capacity, re-combinative capabilities and technological innovation leadership.

Because firms supported by the government tend to be conservative in their decision-making and technology development strategies, governmental assistance is likely to negatively affect path-creating catch-up strategies. This study surveyed small to medium enterprises in the Korea IT industry and analyzed the latecomers’ catch-up strategies from internal and external environment perspectives.

After ensuring its innovation capacity by developing of internal capacity, it turned out to lead to path-creative catch-up strategy and market disparity and government dependence moderates this relation. While market disparity has a positive moderation effect, government dependence showed a negative moderation effect.

The authors proposed and tested hypotheses of how a firm’s path-creative catch-up strategy is adopted and succeeds. Regarding the internal conditions, the authors statistically proved that absorptive capabilities, re-combinative capabilities and technology innovation leadership are important factors for a firm’s technology innovation capacity.

Gas-insulated switchgear (GIS) stands as a pivotal component in power systems, susceptible to partial discharge occurrences. Nevertheless, manual inspection proves labor-intensive, exhibits a low defect detection rate. Conventional inspection robots face limitations, unable to perform live line measurements or adapt effectively to diverse environmental conditions. This paper aims to introduce a novel solution: the GIS ultrasonic partial discharge detection robot (GBOT), designed to assume the role of substation personnel in inspection tasks.

GBOT is a mobile manipulator system divided into three subsystems: autonomous location and navigation, vision-guided and force-controlled manipulator and data detection and analysis. These subsystems collaborate, incorporating simultaneous localization and mapping, path planning, target recognition and signal processing, admittance control. This paper also introduces a path planning method designed to adapt to the substation environment. In addition, a flexible end effector is designed for full contact between the probe and the device.

The robot fulfills the requirements for substation GIS inspections. It can conduct efficient and low-cost path planning with narrow passages in the constructed substation map, realizes a sufficiently stable detection contact and perform high defect detection rate.

The robot mitigates the labor intensity of grid maintenance personnel, enhances inspection efficiency and safety and advances the intelligence and digitization of power equipment maintenance and monitoring. This research also provides valuable insights for the broader application of mobile manipulators in diverse fields.

The robot is a mobile manipulator system used in GIS detection, offering a viable alternative to grid personnel for equipment inspections. Comparing with the previous robotic systems, this system can work in live electrical detection, demonstrating robust environmental adaptability and superior efficiency.

This chapter attempts an evaluation of Lenin's economic thought from a Marxian standpoint. This chapter argues that Lenin's reading of Marx's Capital in Development of Capitalism in Russia (1899) was biased toward Ricardian or logic-historical interpretation of value, disproportionality theory of crisis as well as economic determinism, characteristic of the Second International Marxism. While admitting that Lenin overcame economic determinism and reformist politics of the Second International Marxism in his Imperialism (1917), this chapter shows that some essential elements, such as thesis of progressiveness of capitalism, stagiest or typologist conceptions of capitalism, still persisted within and after Imperialism. Moreover, this chapter argues that Lenin's Imperialism cannot be considered as a successful concretization of three latter parts of Marx's plan of critique of political economy in Grundrisse (1857), that is, State (Part 4), Foreign Trade (Part 5), and World Market Crisis (Part 6). This chapter also argues that the ambivalence of Lenin's economic thoughts and incomplete break with the Second International Marxism unexpectedly led to Stalinist thesis of state monopoly capitalism, market socialist ideas, and reformist conception of “varieties of capitalisms.”

This study aims to identify the effects of innovation types on the service firm’s financial and nonfinancial performance as well as mediation and moderation effects of innovation and the firms’ performance linkages in the Indian service sector.

This study uses combined data from the World Bank innovation survey 2014 and World Bank enterprise survey (WBES) 2014 for India. It classified innovations into technological innovation (service and process) and nontechnological innovation (organizational and marketing) and used financial and nonfinancial performance measures. This study applies variance-based partial least square structural equation modeling (PLS-SEM) using Smart PLS 3 software.

The study results suggest that service innovation has the highest significant effect on a firm’s financial and nonfinancial performance, followed by process innovation. Marketing and organizational innovation have a long route to contribute to a firm’s financial performance via innovative and nonfinancial performance. The study results do not find any synergy effects of innovation types. Multi-group analysis (MGA) results suggest several significant distinctions in the path relationships between small and medium-sizes and large firms.

This study provides several crucial policy suggestions for the managers and policymakers concerning the effects of service and process innovation on service firms’ performance in India and the mediating factors of these relationships. The study suggests that managers should pay the highest importance to service innovation to swiftly and markedly surge service firms’ financial and nonfinancial performances. In contrast, a service firm’s innovative performance mainly results from its organizational and marketing innovations.

This study aims to propose the use of time series autoregressive integrated moving average (ARIMA) models to predict gas path performance in aero engines. The gas path is a critical component of an aero engine and its performance is essential for safe and efficient operation of the engine.

The study analyzes a data set of gas path performance parameters obtained from a fleet of aero engines. The data is preprocessed and then fitted to ARIMA models to predict the future values of the gas path performance parameters. The performance of the ARIMA models is evaluated using various statistical metrics such as mean absolute error, mean squared error and root mean squared error. The results show that the ARIMA models can accurately predict the gas path performance parameters in aero engines.

The proposed methodology can be used for real-time monitoring and controlling the gas path performance parameters in aero engines, which can improve the safety and efficiency of the engines. Both the Box-Ljung test and the residual analysis were used to demonstrate that the models for both time series were adequate.

To determine whether or not the two series were stationary, the Augmented Dickey–Fuller unit root test was used in this study. The first-order ARIMA models were selected based on the observed autocorrelation function and partial autocorrelation function.

Further, the authors find that the trend of predicted values and original values are similar and the error between them is small.