• Journal of Information Technology Services
• /
• v.20 no.4
• /
• pp.69-80
• /
• 2021

Many studies have discussed the effectiveness of mentoring from a mentor or mentee perspective. However, it is is necessary to deeply understand the formal mentoring relationship from the perspective of both the mentor and the mentee because the mentoring relationship is the interaction between the mentor and the mentee. Therefore, in this study, the mentors' role through IPA was compared and analyzed from the perspective of mentors and mentees. A survey was conducted on 376 employees of the financial bank, and the managers in charge of the company's official workplace mentoring and employees who participated in the mentoring program were interviewed. As a result of the analysis, mentors are more satisfied with the rewarding experience, while mentees are satisfied with commitment, and organizational ascendency and impact. In addition, mentees judge that "Coach", "Provides support", "Provides vision & widens horizons", "Broaden experience", "Cooperation", "Motivates", "Networking ability", "Provide cross-functional information", "Role model", "Share credit", "Teacher", and "Transfer skills, leadership, & technology" are important as mentor's roles are important. Therefore, in order to foster mentors for effective workplace mentoring, it is necessary to educate the mentor in advance about the mentors' role that the mentee considers to be important.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.25 no.3
• /
• pp.93-102
• /
• 2021

The dynamic characterization of a three-story auxiliary building in a nuclear power plant (NPP) constructed with a monolithic reinforced concrete shear wall is investigated in this study. The shear wall is subjected to a joint-research, round-robin analysis organized by the Korea Atomic Energy Research Institute, South Korea, to predict seismic responses of that auxiliary building in NPP through a shake table test. Five different intensity measures of the base excitation are applied to the shaking table test to get the acceleration responses from the different building locations for one horizontal direction (front-back). Simultaneously to understand the global damage scenario of the structure, a frequency search test is conducted after each excitation. The primary motivation of this study is to develop a nonlinear numerical model considering the multi-layered shell element and compare it with the test result to validate through the modal parameter identification and floor responses. In addition, the acceleration amplification factor is evaluated to judge the dynamic behavior of the shear wall with the existing standard, thus providing theoretical support for engineering practice.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.4
• /
• pp.1193-1215
• /
• 2021

The measurement of the key product quality index plays an important role in improving the production efficiency and ensuring the safety of the enterprise. Since the actual working conditions and parameters will inevitably change to some extent with time, such as drift of working point, wear of equipment and temperature change, etc., these will lead to the degradation of the quality variable prediction model. To deal with this problem, the selective integrated moving windows based principal component regression (SIMV-PCR) is proposed in this study. In the algorithm of traditional moving window, only the latest local process information is used, and the global process information will not be enough. In order to make full use of the process information contained in the past windows, a set of local models with differences are selected through hypothesis testing theory. The significance levels of both T - test and χ² - test are used to judge whether there is identity between two local models. Then the models are integrated by Bayesian quality estimation to improve the accuracy of quality variable prediction. The effectiveness of the proposed adaptive soft measurement method is verified by a numerical example and a practical industrial process.

• Journal of the Semiconductor & Display Technology
• /
• v.21 no.1
• /
• pp.44-49
• /
• 2022

The number of single-person households is increasing worldwide, and among them, the proportion of elderly single-person households is increasing. In the case of elderly single-person households, a significant portion of their leisure time is devoted to watching TV. However, if they fall asleep while watching TV without turning it off, it may be difficult to sleep well due to lights and sounds of TV, which can cause health problems such as depression and reduced immunity. Therefore, in this paper, we propose a system that automatically turns off the TV when a person watching TV falls asleep. Images are collected using the camera installed in front of the TV. Since the posture of a person watching TV varies from a sitting posture to a lying posture, the system is designed to determine whether or not to fall asleep regardless of the posture. In addition, since it becomes difficult to judge eye movements as a person moves away from the TV, a method for extending the judgmentable distance is proposed. The system model was implemented and tested using a Raspberry Pi, a monitor, an infrared sensor, and a camera. Eye movements were judged regardless of sitting or lying position, and the distance between a user and a TV was extended by about 200 cm.

• Journal of Daesoon Thought and the Religions of East Asia
• /
• v.1 no.1
• /
• pp.17-37
• /
• 2021

Scholars of new religious movements have emphasized the role of "second founders," such as Judge J.F. Rutherford for the Jehovah's Witnesses, Brigham Young for the Mormons, or Deguchi Onisaburo for Oomoto. They systematize and structure movements often created by the "first founders" with a minimal organization only. The paper argues that the model for the sequence first founder/second founder described by these scholars is the relationship between Jesus and Paul of Tarsus at the origins of Christianity. It proposes a comparison between Jesus of Nazareth and Kang Jeungsan, who established the tradition leading to present-day Daesoon Jinrihoe. It then summarizes the biography of Jo Jeongsan, recognized by Daesoon Jinrihoe as its "second founder" within the same tradition, and discusses the analogies between his connection to the "first founder," Kang Jeungsan, and the connection Paul of Tarsus established with Jesus Christ. The paper considers recent scholarship about Paul, often described as the "New Perspective on Pauline Scholarship." Paul never personally met Jesus Christ, except after the latter's death through a spiritual revelation, just as Jo Jeongsan never met Kang Jeungsan, except after his death, when he manifested himself to him in spirit. Nonetheless, Paul was able to decisively shape the largest branch among the followers of Jesus Christ, just as Jo Jeongsan originated the lineage leading to Daesoon Jinrihoe, currently the largest religious order among those recognizing Kang Jeungsan as the incarnated Supreme God.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.2
• /
• pp.486-503
• /
• 2023

Logs play an important role in mastering the health of the system, experienced operation and maintenance engineer can judge which part of the system has a problem by checking the logs. In recent years, many system architectures have changed from single application to distributed application, which leads to a very huge number of logs in the system and manually check the logs to find system errors impractically. To solve the above problems, we propose a method based on Message Middleware and ATT-GRU (Attention Gate Recurrent Unit) to detect the logs anomaly of distributed systems. The works of this paper mainly include two aspects: (1) We design a high-performance distributed logs collection architecture to complete the logs collection of the distributed system. (2)We improve the existing GRU by introducing the attention mechanism to weight the key parts of the logs sequence, which can improve the training efficiency and recognition accuracy of the model to a certain extent. The results of experiments show that our method has better superiority and reliability.

• International conference on construction engineering and project management
• /
• 2013.01a
• /
• pp.596-601
• /
• 2013

In the current pavement construction practice, the state agencies traditionally determine the quality of the as-constructed pavement mix based on individual mixture material parameters (e.g., air voids, cement or asphalt content, aggregate gradation, etc.) and consider these parameters as key variables to influence payment schedule to the contractors and the present and future quality of the as-constructed mixture. A set of empirically pre-determined pay adjustment schedule for each parameter that was differently developed and being used by the individual agencies is then applied to a given project, in order to judge whether each parameter conforms to the designated specifications and consequently the contractor may either be rewarded or penalized in accordance with the payment schedule. With an improved quality assurance system, the Performance Related Specification, the individual parameters are not utilized as a direct judgment factor; rather, they become independent variables within a performance prediction function which is directly used to predict the performance. The quantified performance based on the prediction model is then applied to evaluate the pavement quality. This paper presents the brief history of the quality assurance in asphalt pavement construction including the Performance Related Specifications, statistical performance models in terms of fatigue and rutting distresses, as an example of the performance prediction models, and envisions the possibilities as to how this Performance Related Specification could be utilized in other infrastructures construction quality assurance.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.12
• /
• pp.485-496
• /
• 2018

So far, the deep learning, a field of artificial intelligence, has achieved remarkable results in solving problems from unstructured data. However, it is difficult to comprehensively judge situations like humans, and did not reach the level of intelligence that deduced their relations and predicted the next situation. Recently, deep neural networks show that artificial intelligence can possess powerful relational reasoning that is core intellectual ability of human being. In this paper, to analyze and observe the performance of Relation Networks (RN) among the neural networks for relational reasoning, two types of RN-based deep neural network models were constructed and compared with the baseline model. One is a visual question answering RN model using Sort-of-CLEVR and the other is a text-based question answering RN model using bAbI task. In order to maximize the performance of the RN-based model, various performance improvement experiments such as hyper parameters tuning have been proposed and performed. The effectiveness of the proposed performance improvement methods has been verified by applying to the visual QA RN model and the text-based QA RN model, and the new domain model using the dialogue-based LL dataset. As a result of the various experiments, it is found that the initial learning rate is a key factor in determining the performance of the model in both types of RN models. We have observed that the optimal initial learning rate setting found by the proposed random search method can improve the performance of the model up to 99.8%.

• Journal of Korea Port Economic Association
• /
• v.37 no.1
• /
• pp.71-85
• /
• 2021

A variety of methods have been proposed through a number of studies on sophisticated demand forecasting models that can reduce logistics costs. These studies mainly determine the applicable demand forecasting model based on the pattern of demand quantity and try to judge the accuracy of the model through statistical verification. Demand patterns can be broadly divided into regularity and irregularity. A regular pattern means that the order is regular and the order quantity is constant. In this case, predicting demand mainly through regression model or time series model was used. However, this demand is called "intermittent demand" when irregular and fluctuating amount of order quantity is large, and there is a high possibility of error in demand prediction with existing regression model or time series model. For items that show intermittent demand, predicting demand is mainly done using Croston or HOLTS. In this study, we analyze the demand patterns of various items of air cargo with intermittent patterns and apply the most appropriate model to predict and verify the demand. In this process, intermittent optimal demand forecasting model of air cargo is proposed by analyzing the fit of various models of air cargo by item and region.

• Journal of Wetlands Research
• /
• v.26 no.3
• /
• pp.279-284
• /
• 2024

Recently, the frequency and intensity of torential rains caused by climate change are increasing, and the damage to reservoir collapse in local governments continues to occur. Most local government reservoirs are aged reservoirs that have been built for more than 50 years, and there is a high risk of collapse due to recent heavy rainfall. In order to prevent reservoir collapse or overflow caused by heavy rainfall, a decision-making support system that can judge risks due to changes in storage capacity is needed. In this study, a reservoir discharge simulation model was constructed using a system dynamics technique that can dynamically represent causal relationships between various variables. Through discharge simulation, the change in storage capacity due to rainfall was analyzed, and the operation time and termination time of the discharge facility to prevent overflow of the reservoir were analyzed. Using the results of this study, it is possible to determine the timing of the overflow of the reservoir due to torrential rain, and also the capacity and operation timing of the discharge facility to prevent overflow can be known. hrough this, it is expected that local governments will be able to judge the risk of damage to reservoirs and establish a preliminary response plan to prevent damage.