Cooperative Capabilities Research Articles

Multi-Objective Optimized GPSR Intelligent Routing Protocol for UAV Clusters

Unmanned aerial vehicle (UAV) clusters offer significant potential in civil, military, and commercial fields due to their flexibility and cooperative capabilities. However, characteristics such as dynamic topology and limited energy storage bring challenges to the design of routing protocols for UAV networks. This study leverages the Deep Double Q-Learning Network (DDQN) algorithm to optimize the traditional Greedy Perimeter Stateless Routing (GPSR) protocol, resulting in a multi-objective optimized GPSR routing protocol (DDQN-MTGPSR). By constructing a multi-objective routing optimization model through cross-layer data fusion, the proposed approach aims to enhance UAV network communication performance comprehensively. In addition, this study develops the above DDQN-MTGPSR intelligent routing algorithm based on the NS-3 platform and uses an artificial intelligence framework. In order to verify the effectiveness of the DDQN-MTGPSR algorithm, it is simulated and compared with the traditional ad hoc routing protocols, and the experimental results show that compared with the GPSR protocol, the DDQN-MTGPSR has achieved significant optimization in the key metrics such as the average end-to-end delay, packet delivery rate, node average residual energy variance and percentage of node average residual energy. In high dynamic scenarios, the above indicators were optimized by 20.05%, 12.72%, 0.47%, and 50.15%, respectively, while optimizing 36.31%, 26.26%, 8.709%, and 69.3% in large-scale scenarios, respectively.

Magnetic steering continuum robot for transluminal procedures with programmable shape and functionalities

Millimeter-scale soft continuum robots offer safety and adaptability in transluminal procedures due to their passive compliance, but this feature necessitates interactions with surrounding lumina, leading to potential medical risks and restricted mobility. Here, we introduce a millimeter-scale continuum robot, enabling apical extension while maintaining structural stability. Utilizing phase transition components, the robot executes cycles of tip-based elongation, steered accurately through programmable magnetic fields. Each motion cycle features a solid-like backbone for stability, and a liquid-like component for advancement, thereby enabling autonomous shaping without reliance on environmental interactions. Together with clinical imaging technologies, we demonstrate the capability of navigating through tortuous and fragile lumina to transport microsurgical tools. Once it reaches larger anatomical spaces such as stomach, it can morph into functional 3D structures that serve as surgical tools or sensing units, overcoming the constraints of initially narrow pathways. By leveraging this design paradigm, we anticipate enhanced safety, multi-functionality, and cooperative capabilities among millimeter-scale continuum robots, opening new avenues for transluminal robotic surgery.

SWOAM: Swarm optimized agents for energy management in grid-interactive connected buildings

With increasing complexity of smart city energy systems and rising energy demand, effective energy management solutions are crucial. Buildings now incorporate renewable energy sources and battery storage for efficient energy utilization, making optimal control strategies important. Compared to rule-based controllers and model-based methods, swarm and evolutionary algorithms have the advantages of providing cost-effective, stable, and scalable alternatives. However, their potential in data-rich environments and multi-building energy systems remains underexplored. This research bridges this gap by demonstrating the cooperative capabilities of population-based optimization agents for efficient energy management. Specifically, novel algorithm and framework, named Swarm Optimized Agents for Sequential Decision Making (SWOAM) is proposed. It combines an online k-means classifier and a swarm optimizer for optimal control of multi-building energy systems. By designing an online K-means learning strategy and an agent-based sequential episodic sampling approach, it is feasible to train a swarm of agents find an optimal energy management policy for buildings in a district. For training and evaluation, we use the standardized CityLearn building energy management environment. The agents are evaluated on three key metrics: electricity cost, carbon dioxide emissions and grid ramping. SWOAM delivers state-of-the-art performance and outperforms modern reinforcement learning and rule-based controllers.

The Impact of Graduate Education Scale on the Innovation Capability of the Tertiary Industry

With the rapid development of the global economy and the rise of the knowledge economy, innovation capability has become a key factor determining the competitiveness of a country or region. The tertiary industry, especially the service and high-tech industries, plays an increasingly important role in driving economic growth, promoting employment, and social progress. Graduate students, as the subjects of high-level talent cultivation, their quantity and quality are directly related to the construction of the national innovation system and the development potential of the tertiary industry. Graduate education, as an important way to cultivate high-level talents, plays an irreplaceable role in enhancing national innovation ability and promoting the development of the tertiary industry. Graduate education not only focuses on the impartation of knowledge but also emphasizes the cultivation of independent research ability, innovative thinking, and interdisciplinary cooperation capability, which are essential for driving the development of the service and high-tech industries. Therefore, by vigorously developing graduate education and cultivating more high-level talents with innovative spirit and practical ability, we can provide strong talent support and intellectual protection for the development of the service and high-tech industries. This will also promote the construction and improvement of the national innovation system, further enhancing the country's competitiveness and influence in the global economy.

Evaluation Model Construction of School-Enterprise Cooperation Innovation Ability Based on Big Data Analysis

Abstract This study analyzes SCIE papers published by 39 universities as a substantial big-data sample, employing latent class analysis to explore the characteristics of university-enterprise cooperation in Chinese institutions. It identifies five categorical attributes to construct a latent class model. This paper integrates hierarchical analysis with fuzzy mathematics to develop a comprehensive fuzzy evaluation model. By organizing and layering the factors, a rational set of indicators is established, and a hierarchical analysis structure is constructed. Utilizing a judgment matrix, the study calculates the importance rankings of all indicators, thereby highlighting the significant influence of the factors. Empirical results indicate that the model achieves optimal fit with five latent categories. Within the five primary indicators for evaluating the innovation capability of university-enterprise cooperation, the weight of innovation outcomes is the highest at 0.24, followed by industrial innovation at 0.22. The analysis reveals a regional imbalance in university-enterprise collaboration across the eastern coastal area, with Guangdong achieving the highest rating of 84.03, closely followed by Jiangsu. In assessing the innovation capability of university-enterprise cooperation in Guangdong's applied universities, the overall scores for universities categorized as B, C, and D are 3.641, 3.522, and 3.409, respectively. Notably, the scores for R&D investment intensity and Chinese patent applications are relatively low, suggesting these areas require enhancement to bolster support and development, thereby improving university-enterprise cooperation and innovation capabilities.

Driving Educational in Management Excellence: The Interconnected Roles of Cautious Thinking and Cooperation Capability for Successfully in Cognitive Presence

In the realm of education, the dynamics of learning have always been a subject of keen interest and in-depth investigation. This research explores the intricate relationship between cautious thinking, cooperation capability, and cognitive presence within the educational context. The results of data analysis indicate that these three variables have a strong and significant relationship. Notably, cautious thinking plays a pivotal role in enhancing students' critical thinking abilities, while cooperation capability exerts a positive influence on their cognitive presence. These findings provide a solid foundation for understanding the pivotal roles of cautious thinking and cooperation capability in elevating the quality of students' learning experiences. Furthermore, the implications of this research resonate profoundly in the field of management, offering the promise of enhancing educational practices and human resource development. With a hopeful outlook, the researchers anticipate that the outcomes of this study will serve as a stepping stone for further research and will contribute substantially to the ongoing enhancement of educational standards and management practices in the future.

THE SCIENTIFIC BASIS, SOME RESULTS, AND PERSPECTIVES OF MODELING EVOLUTIONARILY CONDITIONED NOOGENESIS OF ARTIFICIAL CREATURES IN VIRTUAL BIOCENOSES

This research aimed to gain a profound understanding of virtual biocenoses intricate digital ecosystems, with the goal of elucidating and replicating the emergence and evolution of intelligence in artificial creatures – referred to as noogenesis. A comprehensive analysis of existing studies within virtual biocenoses was undertaken to glean valuable insights into the complexities of modeling dynamic ecosystems where artificial agents engaged in intricate interactions. The pivotal role of neural networks in shaping the adaptive behaviors of artificial creatures within these environments was underscored. A meticulous investigation into neural networks' evolution methodologies revealed the evolution of their architecture complexity over time, culminating in the facilitation of flexible and intelligent behaviors. However, a lack of study existed in the domain of nurturing evolutionary-based communication and cooperation capabilities within virtual biocenoses. In response to this gap, a model was introduced and substantiated through simulation experiments. The simulation results vividly illustrated the model's remarkable capacity to engender adaptive creatures endowed with the capability to efficiently respond to dynamic environmental changes. These adaptive entities displayed efficient optimization of energy consumption and resource acquisition. Moreover, they manifested both intellectual and physical transformations attributed to the evolution and encoding principles inspired by the NeuroEvolution of Augmented Topologies. Significantly, it became apparent that the evolutionary processes intrinsic to the model were inextricably linked to the environment itself, thus harmonizing seamlessly with the overarching goal of this research. Future research directions in this field were outlined. These pathways provided a foundation for further exploration into the evolution of artificial creatures in virtual biocenoses and the emergence of advanced communication and cooperation capabilities. These advancements hold the potential to move artificial life and artificial intelligence to new levels of understanding and capability.

Intercultural Communication Dilemma and Countermeasures in International Trade

The aim of this paper is to explore the challenges and coping strategies of cross-cultural communication in international trade. Firstly, we introduce the importance and challenges of international trade, including business opportunities and risks. Then, we delve into several key aspects of cross-cultural communication challenges, including language barriers, cultural differences, and communication misunderstandings. In terms of coping strategies, we propose methods such as cross-cultural training, cultural sensitivity cultivation, and establishing effective communication mechanisms. These coping strategies aim to help businesses overcome challenges, build good cooperative relationships, and improve the effectiveness of international trade. Lastly, we emphasize the significance of this research and suggest future research directions, encouraging further exploration and improvement of international trade practices under cross-cultural communication challenges. Through the study presented in this paper, we can better understand and address the challenges of cross-cultural communication in international trade, enhancing the competitiveness and international cooperation capabilities of businesses.

Identification of ligand-receptor pairs that drive human astrocyte development.

Extrinsic signaling between diverse cell types is crucial for nervous system development. Ligand binding is a key driver of developmental processes. Nevertheless, it remains a significant challenge to disentangle which and how extrinsic signals act cooperatively to affect changes in recipient cells. In the developing human brain, cortical progenitors transition from neurogenesis to gliogenesis in a stereotyped sequence that is in part influenced by extrinsic ligands. Here we used published transcriptomic data to identify and functionally test five ligand-receptor pairs that synergistically drive human astrogenesis. We validate the synergistic contributions of TGFβ2, NLGN1, TSLP, DKK1 and BMP4 ligands on astrocyte development in both hCOs and primary fetal tissue. We confirm that the cooperative capabilities of these five ligands are greater than their individual capacities. Additionally, we discovered that their combinatorial effects converge in part on the mTORC1 signaling pathway, resulting in transcriptomic and morphological features of astrocyte development. Our data-driven framework can leverage single-cell and bulk genomic data to generate and test functional hypotheses surrounding cell-cell communication regulating neurodevelopmental processes.

How do firms capture value in a full-scene smart service? Effectiveness of value proposition and co-creation capabilities

Driven by data intelligence technologies and smart business logic, firms are increasingly advocating and implementing a novel full-scene smart service model. However, little is known about how value is co-created and captured in this model. Therefore, this study develops a research model based on the business model framework to examine how the value proposition of full-scene smart service influences the high-order capabilities of value co-creation (technological innovation capability and cooperation capability) and how these specific co-creation capabilities ultimately affect value outcomes. Our model is tested on a three-year panel (2018–2020) of 104 Chinese A-share listed firms providing full-scene smart service. Consistent with our theorizing, we find that value proposition acts as an important business model element to improve a firm's value co-creation capabilities and its economic value and that the value co-creation capabilities drive the firm's economic and social value. In further subsample analyses, we find that the results vary across firms with different levels of value proposition intensity and economic performance. The study contributes to theory and practice by shedding light on the value-creation mechanism of the full-scene smart service model.

The Impact of Capability on Cooperative Performance and Sustainability: A Case Study of West Java Coffee Farmers Cooperatives

The industrial revolution in the agricultural sector is faced with demographic challenges (ageing), so intelligent technology, artificial intelligence, big data, and augmented reality are strategic choices. The application of information technology has a direct or indirect impact on Indonesia's agricultural sector, so coffee agribusiness cooperatives' information and communication technology (ICT) is also increasingly needed to respond to market demand. Along with the development of automation, physical, cyber systems and IoT, coffee cooperatives need to be ready and adapt to the era of the industrial revolution 4.0 in capturing market demand opportunities, value chains, and the added value of coffee agribusiness. ICT's presence can improve the performance and institutional sustainability of coffee farmers in rural areas, including cooperatives. Performance is a description of the achievement of organizational tasks to realize the goals, objectives, mission and vision of the organization and its business. The performance of the cooperative describes the services provided to its members and the community/farmers as measured by using indicators to see the working mechanism of the organization and its business that has been carried out and to determine the achievement of the objectives obtained. Meanwhile, the ability to innovate is essential, especially the use of ICT, which is deemed necessary to support the performance and sustainability of coffee cooperatives, so that cooperatives can compete, be stable, or survive in the era of increasing free competition. . Quantitative descriptive method with Linear Regression analysis was used to identify the effect of cooperative capability on the performance and sustainability of cooperatives in several coffee cooperatives in West Java. The study's results found that the power of the cooperative did not significantly affect the performance of the Coffee Cooperative. Still, the capability of the cooperative had a positive and significant effect on the sustainability of the Coffee Cooperative. At the same time, the performance of the cooperative has a positive and significant impact on the sustainability of the coffee cooperative. The ability of cooperatives has a positive and significant effect on sustainability mediated by the performance of the Coffee Cooperative in the Industrial Revolution 4.0 era. This study recommends increasing the capabilities of cooperatives in membership, management, and business models to become sustainable cooperatives based on information technology to achieve added value from market-driven coffee products.

A Task Performance-Based sEMG-Driven Variable Stiffness Control Strategy for Upper Limb Bilateral Rehabilitation System

Bilateral rehabilitation robotics can allow hemiplegia patients to regain the cooperative capabilities of both arms by synchronized coordination movements. Furthermore, the variable stiffness actuators (VSA) integrated robotics can offer compliant advantages for human-robot interaction. Although various studies have proposed to improve training safety and comfortability by VSA, few studies have focused on inducing patient active participation by VSA-based variable stiffness control for bilateral rehabilitation. In this article, an surface electromyography (sEMG) driven variable stiffness control framework with a novel training task quantitative factor TPI was proposed to promote patient active participation in upper limb bilateral rehabilitation. The proposed control law integrates an sEMG-driven musculoskeletal model for providing real-time dynamic reference stiffness from the nonparetic limb as a task skill learning guide to the affected limb. Furthermore, the proposed TPI is designed in the high-level controller for rendering smooth and automatic transition among three patient-robot interaction modes for inducing active participants. In the low-level controller, a position-based bilateral impedance control and a cascaded backstepping position control were implemented for compliant task position planning and tracking. Preliminary experimental results show that the proposed method can promote patient active participation by providing minimal intervention assistance for facilitating efficient upper limb rehabilitation.

Peculiarities of using virtual whiteboards to form the professional competence of future lawyers in foreign language classes at university

Problem statement . The focuses of the current digital intercultural learning environment as training programs for professionals in the legal industry specify their developing of systemic foreign language communication skills, skills to analyze which can be based on information technologies and actualized in rapidly changing professional tasks. The study is aimed at substantiating the effectiveness of using virtual whiteboards to form the professional competence of future lawyers in foreign language classes at university. Methodology . The analysis of theory and methodology, generalization of crucial scientific papers on the studied problem, processing of results and creating interactive whiteboards are applied. The pedagogical experiment involved 97 students (girls - 48%, boys - 52%) of the Law Institute of Vyatka State University. Fisher's criterion (angular transformation) is used as a statistical processing method. Results . The didactic peculiarities of making use of virtual whiteboards when forming professional and legal competence of a professional in the legal industry during foreign language classes are stated: the capabilities of network intercultural cooperation when solving tasks in the legal industry; seeking legal assistance; foreign language communication; virtual discussion of criminal acts; independence of the interactive network environment for modeling legal processes; keeping the results in a cloud. At the control stage of the experiment, statistically significant differences between the levels of formed competences of the participants of the experimental and control groups were revealed. Conclusion . Making use of whiteboards will contribute to the formation of foreign language and professional legal competences of a specialist while providing a set of circumstances: active work with foreign regulatory acts in English, showing students new intercultural information collaboration and legal consultancy, combining different types of work, organizing foreign language feedback, solving real practical legal tasks.

The Effect of Performance on the Sustainability of Coffee Farmers’ Cooperatives in the Industrial Revolution 4.0 in West Java Indonesia

This research evaluates the effect the industrial revolution era 4.0 has had on the performance and sustainability of coffee farmer cooperatives, especially in the West Java region, considering that West Java is a coffee center area that is starting to be taken into account in Indonesia and the world in general, this is evidenced by the increasing number of farmer cooperatives coffee in the West Java region. One of the most monumental effects of the industrial revolution 1.0 was the birth of the British cooperative in Rochdale, the world’s first modern cooperative. The industry continues to develop, cooperatives continue to adapt and try to continue to develop in accordance with technological advances, especially now that the industrial revolution 4.0 has entered, which emphasizes information technology, especially the use of the internet. However, there has been no previous research examining the use of information technology in coffee farmer cooperatives, especially in the era of the industrial revolution 4.0, even though this information technology is very important in the development of cooperatives today. Quantitative descriptive method with SEM analysis was used to identify the effect of cooperative capability on the performance and sustainability of cooperatives in several coffee cooperatives in West Java. The study’s results found that the power of the cooperative did not significantly affect the performance of the Coffee Cooperative. Still, the capability of the cooperative had a positive and significant effect on the sustainability of the Coffee Cooperative. At the same time, the performance of the cooperative had a positive and significant impact on the sustainability of the coffee cooperative. The ability of cooperatives has a positive and significant effect on sustainability mediated by the performance of the Coffee Cooperative in the Industrial Revolution 4.0 era. This study recommends increasing the capabilities of cooperatives in membership, management, and business models to become sustainable cooperatives based on information technology to achieve added value from market-driven coffee products. The results of the study show that the respondents perceive that the cooperative’s performance has a positive effect on their sustainability. Improving the performance of cooperatives in terms of (1) productivity, (2) effectiveness, (3) quality, and (4) achievement can be regarded as having a direct impact on the Coffee Cooperative’s long-term viability. The industrial revolution in the agricultural sector is facing demographic challenges (ageing), so intelligent technology, artificial intelligence, big data, and augmented reality are strategic choices. The application of information technology has a direct or indirect positive impact on Indonesia’s agricultural sector. Cooperatives in coffee agribusiness is also increasingly needed to respond to market demand by applying Information and Communication Technology (ICT).

Framework for Connected and Automated Bus Rapid Transit with Sectionalized Speed Guidance based on deep reinforcement learning: Field test in Sejong City

Nowadays, Automated Vehicle (AV) technology is gaining attention as a candidate to improve the efficiency of Bus Rapid Transit (BRT) systems. However, there are still some challenges in AV technology including limited perception range and lack of cooperation capability in mixed traffic situations with drivers. The emerging Connected and Automated Vehicles (CAVs) and Cooperative Intelligent Transportation System (C-ITS) offer an unprecedented opportunity to solve such challenges. As a result, this study presents a framework for Connected and Automated BRT (CA-BRT), including a cloud-based architecture and a deep reinforcement learning system for Sectionalized Speed Guidance (SSG) system designed for CAVs. The proposed framework is field-tested in Sejong City in South Korea, where there are various road environments such as bus stops, overpasses, underground tunnels, intersections, and crosswalks. The driving performance of the proposed system is compared with different types of control scenarios, and the results from the field tests show that the proposed system improves the driving performance of the AVs in various aspects including driving safety, ride comfort, and energy efficiency with downstream information obtained from road infrastructures.

A Novel Model of Thyroid Nodule Segmentation for Ultrasound Images.

Ultrasonography is regarded as an effective technique for the detection, diagnosis and monitoring of thyroid nodules. Segmentation of thyroid nodules on ultrasound images is important in clinical practice. However, because in ultrasound images there is an unclear boundary between thyroid nodules and surrounding tissues, the accuracy of segmentation remains a challenge. Although the deep learning model provides an accurate and convenient method for thyroid nodule segmentation, it is unsatisfactory of the existing model in segmenting the margin of thyroid nodules. In this study, we developed boundary attention transformer net (BTNet), a novel segmentation network with a boundary attention mechanism combining the advantages of a convolutional neural network and transformer, which could fuse the features of both long and short ranges. Boundary attention is improved to focus on learning the boundary information, and this module enhances the segmentation ability of the network boundary. For features of different scales, we also incorporate a deep supervision mechanism to blend the outputs of different levels to enhance the segmentation effect. As the BTNet model incorporates the long range-short range connectivity effect and the boundary-regional cooperation capability, our model has excellent segmentation performance in thyroid nodule segmentation. The development of BTNet was based on the data set from Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital and the public data set. BTNet achieved good performance in the segmentation of thyroid nodules with an intersection-over-union of 0.810 and Dice coefficient of 0.892 Moreover, our work revealed great improvement in the boundary metrics; for example, the boundary distance was 7.308, the boundary overlap 0.201 and the boundary Dice 0.194, all with p values <0.05.

Gate‐Tunable Anisotropic Oxygen Ion Migration in SrCoOx: Toward Emerging Oxide‐Based Artificial Synapses

The construction of artificial synapse based on the electric field‐controlled ion migration has been developed to be a prospective approach to achieving intelligent devices with advantage of low‐energy consumption. However, it is still a very challenging task for artificial synapses to imitate the complex synapse diversity of biological system. Herein, the ionic liquid gating induced oxygen ion migration to realize the reversible phase transition between insulating SrCoO2.5 and metallic SrCoO3 with anisotropic dynamics due to the fast oxygen transport channel along [110] crystal orientation is used. The crystal orientation‐dependent oxygen ion migration and resultant metal–insulator transition offer an intriguing opportunity to build up a variety of artificial synapses with different performances, like excitatory or inhibitory characters, learning accuracy, and cooperation capability. Our findings not only give an insight into the anisotropic ion migration in oxides but also could be a fundamental step toward the development of diverse oxide‐based artificial neural networks.

Multi-UAV Cooperative Trajectory Planning Based on FDS-ADEA in Complex Environments

Multi-UAV cooperative trajectory planning (MUCTP) refers to the planning of multiple flyable trajectories based on the location of each UAV and mission point in a complex environment. In the planning process, the complex 3D space structure increases the difficulty of solving the trajectory points, and the mutual constraints of the UAV cooperative constraints can degrade the performance of the planning system. Therefore, to improve the efficiency of MUCTP, this study proposes MUCTP based on feasible domain space and adaptive differential evolution algorithm (FDS-ADEA). The method first constructs a three-dimensional feasible domain space to reduce the complexity of the search space structure; then, the constraints of heterogeneous UAVs are linearly weighted and transformed into a new objective function, and the information of the fitness value is shared in accordance with the adaptive method and the code correction method to improve the search efficiency of the algorithm; finally, the trajectories are smoothed to ensure the flyability of the UAVs performing the mission by combining the cubic B-spline curves. Experiments 1, 2, 3, and 4 validate the proposed algorithm. Simulation results verify that FDS-ADEA has fast convergence, high cooperative capability, and more reasonable planned trajectory sets when processing MUCTP.

Effectiveness of the ‘Food Safety and Health’ Workbook for High-school Students

The purpose of this study was implementing the high-school ‘Food Safety and Health’ curriculum using the workbook, and to evaluate the educational impact on, and satisfaction of student who participated in class. A total of 109 lessons were undertaken in home economics classes by referring to the ‘Food Safety and Health’ workbook for 1,154 students attending seven high schools located in seven cities and provinces across the Korea. In order to examine the effects of classes by referring to workbooks, pre- and post-evaluations were conducted by devising a questionnaire about dietary behavior associated with food safety, creative problemsolving abilities, community capacities, and social cooperation capacities. The results of the analysis of the collected data from 674 students who participated in the pre- and post-evaluations are as follows. First, according to the results of the paired &lt;i&gt;t&lt;/i&gt;-test conducted to examine the effects of using the workbook in classes on dietary behavior, significant positive changes were observed in the dietary behavior related to food safety, creative problem-solving skills, community consciousness, and social cooperation capabilities. Second, as a result of the students’ evaluation of classes by referring to the ‘Food Safety and Health’ workbook, both satisfaction and interest in the class using the workbook were high, and the difficulty level was deemed to be appropriate. Additionally, it was found that the students actively participated in learning activities. The reason for this appears to be that the aforementioned workbook consisted of various student activities such as experiments, practical exercises, and group activities aimed at strengthening the link between life and education, thus enabling increased student participation.

Cultural Study and Cultural Paradok on Entrepreneurship Behavior of The Minang Community

History records and the current reality has explained that the Minang people are an ethnic group known as the merchant tribe (entrepreneurs). His actions in trade from time to time have been recognized and his spread not only reaches his tribal areas but also extends to all parts of Indonesia and abroad. There are many amazing inspirational stories starting from the development of bilateral cooperation capabilities and the distribution of national ideologies through entrepreneurial activities. However, with all the potential and achievements achieved through entrepreneurship activities, it turns out that this profession is allegedly something that is not very coveted today by the Minang community. Entrepreneurship seems to be identified only for certain groups or qualifications of society and not for other communities. The entrepreneurial profession, which was originally something that was respected not only because of its ability to accumulate wealth but also its social effects, has become less "authoritative and elegant" in this day and age. It is necessary to study what phenomenon actually pervades the Minang community, where cultural wisdom upholds the entrepreneurship profession but the behavior of the people is indicated to be in the opposite direction.