With the advent of the 4th Industrial Revolution, changes in the market environment and employment environment are accelerating due to smart technological innovation, and securing professional manpower and developing human resources for domestic small and medium-sized enterprises is becoming very important. Recently, most of the domestic small and medium-sized enterprises are experiencing hiring difficulties, and the development and training of human resources to overcome this is still lacking in systemization, despite much support from the government. This reflects the reality that it is not easy to invest training costs and time to adapt new employees to small and medium-sized businesses. Based on these problems, the work-study parallel project was introduced to cultivate practical talent in small and medium-sized businesses. Work-study parallel training is carried out in the form of mentoring between corporate field teachers and learning workers in actual workplaces, and even if the training is the same, there are differences depending on the learner's attitude, learning motivation, and training achievement. Ego state is a theory that can identify personality types and has the advantage of being able to understand and acknowledge oneself and others and intentionally improve positive factors to induce optimized interpersonal relationships. Accordingly, the purpose of this study is to analyze the attitudes of learning workers, who are the actual subjects for improving the performance of work-study parallel projects and establishing a stable settlement within the company, based on their ego status. Through this study, we aim to understand the impact of the personality type of learning workers on training performance and to suggest ways to improve training performance through work-study parallelism.

Recently, ESG management has become a global trend, receiving increasing attention from stakeholders such as consumers, investors, and governments, as regulations related to ESG disclosure and supply chain due diligence have been strengthened since the United Nations Principles of Responsible Investment (UN PRI) was announced in 2006. ESG is an acronym for the environment (E), social (S), and governance (G) and is accepted as a key factor for the continuous survival and growth of a company. As a result, there are over 600 ESG management evaluation indicators operated domestically and internationally, and numerous global initiatives have emerged. Korea’s Ministry of Trade, Industry and Energy also announced “K-ESG Guidelines (December 2011)” and “K-ESG Guidelines for Supply Chain Response (December 22)” to help SMEs introduce ESG management and respond to supply chain due diligence. However, small-scale manufacturing companies with poor financial, human resources, and technological capabilities face significant challenges in introducing ESG management. Accordingly, this study aims to examine the current status of ESG management adoption in small-scale manufacturing companies with less than 150 people in Korea and propose activation plan ESG management based on the diagnostic requirements of the “Supply Chain Response K-ESG Guidelines.”

In the (3,3) close combat model based on the Lanchester Square Law, this study proposes a plan to optimally allocate residual combat power after the battle to other battlefields. As soon as the two camps of three units can grasp each other's information and predict the battle pattern immediately after the battle began, the Time Zero Allocation of Force (TZAF) scenario was used to initially allocate combat power to readjust the combat model. It reflects travel time, which is a "field friction" in which physical distance exists from battlefields that support combat power to battlefields that are supported. By developing existing studies that try to examine the effect of travel time on the battlefield through the combat model, this study forms a (3,3) combat model, which is a large number of minimum units. In order to achieve the combat purpose, the principle of optimal combat force operation is presented by examining the aspect that support combat power is allocated to the two battlefields and the consequent battle results. Through this, various scenarios were set in consideration of the travel time and the situation of the units, and differentiated results were obtained. Although the most traditional, it can be used as the basic logic of the training or the commander's decision-making system using the actual war game model.

To understand microorganism effects on wild mushroom fruiting bodies, we investigated the fungi in hyphosphere soil supporting wild mushroom species Cortinarius violaceus, Amanita hemibapha, Laccaria vinacelavellanea, and Amanita verna found in the Gotjawal area of Jeju Island. Fungal species identification based on morphological traits and molecular analysis of ITS, LSU rDNA, and -tubulin gene sequences resulted in isolation and identification of eleven fungal species previously unrecorded in Korea. These newly-recorded species are: Arthrinium kogelbergensis, Kalmusia longisporum, Keithomyces carneum, Neopyrenochaeta cercidis, Penicillium ranomafanaense, Phomatodes nebulosa, Pyrenochaeta nobilis, Tolypocladium album, Talaromyces kendrickii, Talaromyces qii, and Umbelopsis gibberispora, and their morphological characteristics and phylogenetic positions are described.

Mid-sized manufacturing companies, which account for 0.7%(5,480 companies), 13.8%(1.169 million persons) of total employment, and 15.7% of total sales, have recently experienced a lot of difficulties in management activities due to the impact of COVID-19, the U.S.-China trade war, and the collapse of global supply chains. To overcome this, revitalization of quality management activities to strengthen corporate competitiveness is emerging as an urgent task. In order for these quality management activities to achieve their intended purpose, the positive leadership of corporate managers is very important above all else. There have been many studies related to positive leadership, but most have focused on charismatic leadership and transformational leadership centered on large companies or small and medium-sized enterprises. Therefore, this study aims to present ways to strengthen the leadership of managers by empirically analyzing how the positive leadership of managers of mid-sized manufacturing companies, which was relatively under-researched, affects quality management activities and Business performance(Balanced Score Card; BSC).

The large process plant is currently implementing predictive maintenance technology to transition from the traditional Time-Based Maintenance (TBM) approach to the Condition-Based Maintenance (CBM) approach in order to improve equipment maintenance and productivity. The traditional techniques for predictive maintenance involved managing upper/lower thresholds (Set-Point) of equipment signals or identifying anomalies through control charts. Recently, with the development of techniques for big analysis, machine learning-based AAKR (Auto-Associative Kernel Regression) and deep learning-based VAE (Variation Auto-Encoder) techniques are being actively applied for predictive maintenance. However, this predictive maintenance techniques is only effective during steady-state operation of plant equipment, and it is difficult to apply them during start-up and shutdown periods when rises or falls. In addition, unlike processes such as nuclear and thermal power plants, which operate for hundreds of days after a single start-up, because the pumped power plant involves repeated start-ups and shutdowns 4-5 times a day, it is needed the prediction and alarm algorithm suitable for its characteristics. In this study, we aim to propose an approach to apply the optimal predictive alarm algorithm that is suitable for the characteristics of Pumped Storage Power Plant(PSPP) facilities to the system by analyzing the predictive maintenance techniques used in existing nuclear and coal power plants.

In the recent era of the fourth industrial revolution, many industries aim to maximize the efficiency of products and services by introducing cutting-edge technologies such as artificial intelligence and big data. In this situation, organizational culture is changing a lot due to the influx of the MZ generation with strong individualistic tendencies and the decreased face-to-face communication between members. However, active communication with colleagues is still essential to maximize performance, and the margins created by simplifying work processes and automating processes must be used for creating work performance. This requires cooperation and commitment through the job immersion of members who have an active attitude. This study analyzed how the organization's autonomous work environment and trust among members, which are creative work performance conditions, affect job immersion using raw data from the Occupational Safety and Health Research Institute. As a result, it was found that both the organization's autonomous working environment and trust among members significantly effected the members' job immersion. in order to achieve productivity and value improvement in companies, efforts are needed to increase workers' job immersion by building an autonomous working environment and trust among members. The results of this study are expected to contribute significantly to the search for ways to increase workers’ job commitment to improve organizational productivity.