• Geotechnical Engineering
• /
• v.10 no.3
• /
• pp.79-96
• /
• 1994

A tunnel design expert system entitled NESTED is developed using the artificial neural network. The expert system includes three neural network computer models designed for the stability assessment of underground openings and the estimation of correlation between the RMR and Q systems. The expert system consists of the three models and the computerized rock mass classification programs that could be driven under the same user interface. As the structure of the neural network, a multi -layer neural network which adopts an or ror back-propagation learning algorithm is used. To set up its knowledge base from the prior case histories, an engineering database which can control the incomplete and erroneous information by learning process is developed. A series of experiments comparing the results of the neural network with the actual field observations have demonstrated the inferring capabilities of the neural network to identify the possible failure modes and the support timing. The neural network expert system thus complements the incomplete geological data and provides suitable support recommendations for preliminary design of tunnels in rock masses.

• Structural Engineering and Mechanics
• /
• v.42 no.6
• /
• pp.831-847
• /
• 2012

Impact from water-borne debris during tsunami and flood events pose a potential threat to structures. Debris impact forces specified by current codes and standards are based on rigid body dynamics, leading to forces that are dependent on total debris mass. However, shipping containers and other debris are unlikely to be rigid compared to the walls, columns and other structures that they impact. The application of a simple one-dimensional model to obtain impact force magnitude and duration, based on acoustic wave propagation in a flexible projectile, is explored. The focus herein is on in-air impact. Based on small-scale experiments, the applicability of the model to predict actual impact forces is investigated. The tests show that the force and duration are reasonably well represented by the simple model, but they also show how actual impact differs from the ideal model. A more detailed three-dimensional finite element model is also developed to understand more clearly the physical phenomena involved in the experimental tests. The tests and the FE results reveal important characteristics of actual impact, knowledge of which can be used to guide larger scale experiments and detailed modeling. The one-dimensional model is extended to consider water-driven debris as well. When fluid is used to propel the 1-D model, an estimate of the 'added mass' effect is possible. In this extended model the debris impact force depends on the wave propagation in the two media, and the conditions under which the fluid increases the impact force are discussed.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2003.11a
• /
• pp.239-250
• /
• 2003

In this research, we propose a hybrid group decision support mechanism (H-GDSM) based on Fuzzy AHP (Analytic Hierarchy Process) and FCM (Fuzzy Cognitive Map). The AHP elicits a corresponding priority vector interpreting the preferred information among the decision makers. Corresponding vector was composed of the pairwise comparison values of a set of objects. Since pairwise comparison values are the judgments obtained from an appropriate semantic scale. However, AHP couldn't represent the causal relationship among information, which were used by decision makers. In contrast to AHP, FCM could represent the causal relationship among variables or information. Therefore, FCMs were successfully developed and used in several ill-structured domains, such as strategic decision-making, policy making, and simulations. Nonetheless, many researchers used subjective and voluntary inputs to simulate the FCM. As a result of subjective inputs, it couldn't avoid the rebukes of businessman. To overcome these limitations, we incorporated the Fuzzy membership functions, AHP and FCM into a H-GDSM. In contrast to current AHP methods and FCMs, the H-GDSM method developed herein could concurrently tackle the pairwise comparison involving causal relationships under a group decision-making environment. The strengths and contributions of our mechanism were 1) handling of qualitative knowledge and causal relationships, 2) extraction of objective input value to simulate the FCM, 3) multi-phase group decision support based on H-GDSM. To validate our proposed mechanism we developed a simple prototype system to support negotiation-based decisions in electronic commerce (EC).

• Human Ecology Research
• /
• v.56 no.1
• /
• pp.71-84
• /
• 2018

This study presents a case of a visual merchandising course adopting a problem-based learning (PBL) model, as a part of shop manager training program for high school students. Various vocational training classes are actively developed for vocational high schools, yet programs in the home economics area are relatively lacking. In particular, education programs for shop manager training are urgently required due to the high demand of this job in the fashion industry. The PBL model, which reflects constructionist learning theory, is considered for this visual merchandising course in order to help develop the ability of students to creatively apply their knowledge on real-world problems through self-driven learning. For the purpose of job analysis, two problem areas were identified through interviews conducted with shop managers who work for apparel shops in department stores. Based on the results of the interviews, professors and high school teachers developed two PBL instructional modules. The developed module courses were implemented with 2 classes of vocational high school students. The learning outcome was examined through the analysis of a student survey and reflection journals. It was apparent that the PBL courses effectively attracted the interests of learners in vocational training and improved their understanding of the contents as well as cooperation skills. The results of this study indicate that implementing the PBL model for the training of store managers can contribute to the vocational training programs for high school students.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.7
• /
• pp.1696-1701
• /
• 2009

In this paper we analyzed the management performance as the result of the korean government's support policy for the small and medium sized business (SMB). The governmental support policy was carried out for the companies classified in 3 criterion. The first is the upbringing of dynamic SMB group, which are driven by creativity and innovation. The second is the enforcement of technology-innovation and cooperation for SMB. The last is the establishment of the growth basis for SMB like funds, human resources and distribution channels. After categorization of above 3 classes, the affect of support policy on the management performance is analyzed, in terms of 3 aspects, management performance, technical performance and policy satisfaction. This study shows that the governmental support policy has the remarkable effects on the financial support sector of SMB. The 5 major sectors, 1) the upbinging of venture-innobiz innovation company, 2) rearing funds of knowledge-based service company, 3) R&D support, 4) support of management stability fund, 5) expansion of distribution channel to the public sector, are designed from 24 variables. The 3 sectors of these 5 are have the main influences from governmental support policy.

• Mycobiology
• /
• v.48 no.5
• /
• pp.410-417
• /
• 2020

Fungal ecological interactions play a key role in structuring community assemblages. These associations may involve both antagonistic and synergistic relationships, which are commonly influenced by abiotic factors such as nutrient conditions. However, information for extreme, oligotrophic systems remain poor. Herein, interactions among key members of the aquatic transient fungal community (Aspergillus niger, Cladosporium sp., and Coprinellus micaceus) of a low-nutrient freshwater system in the Cuatro Ci enegas Basin, Mexico were studied. Pairwise interaction bioassays were explored in vitro under different nutrient conditions, including carbohydrates-rich, carbohydrates and amino peptides-rich, and low nutrients. Our results indicated that antagonistic patterns prevail among the studied taxa. However, nutrient-dependent changes were observed in Cladosporium sp. shifting to synergy under carbohydrates-rich conditions, suggesting changes in the fungal community composition as a result of nutrient enrichment. Remarkably, our findings contrast with previous work demonstrating mainly synergistic interactions between our tested fungal isolates and co-occurring autochthonous bacteria (Aeromonas spp. and Vibrio sp.) under low-nutrient conditions. This observation may indicate that bacteria and fungi exhibit distinct community-level responses, driven by nutrient conditions. This contributes to the knowledge of fungal community dynamics and interspecific interactions in an oligotrophic ecosystem, highlighting the relevance of nutrient-based shifts and antagonistic interactions in ecosystem dynamics.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2012.05a
• /
• pp.350-355
• /
• 2012

Past few years have seen the growing importance of micro shock tubes in various engineering applications. A pharma ballistic technique is one such application which uses micro shock tube to accelerate drug particles and penetrate into skin, thus avoiding the usual injection drug delivery system. But for the efficient design of such instruments requires the detailed knowledge of shock characteristics and flow field inside a micro shock tube. Due to many factors such as boundary layer, low Reynolds number and high Knudsen number shock propagation inside micro shock tubes will be quite different from that of the well established macro shock tubes. In the present study, experimental studies were carried out on a micro shock tube of 3 mm diameter to investigate flow characteristics and shock propagation. Pressure values were measured at different locations inside the driven section. From the experimental values other parameters like shock velocity, shock strength were found and shock wave diagram was constructed.

• Safety and Health at Work
• /
• v.6 no.4
• /
• pp.295-304
• /
• 2015

Background: While attention has been paid to physical risks in the work environment and the promotion of individual employee health, mental health protection and promotion have received much less focus. Psychosocial risk management has not yet been fully incorporated in such efforts. This paper presents good practices in promoting mental health in the workplace in line with World Health Organization (WHO) guidance by identifying barriers, opportunities, and the way forward in this area. Methods: Semistructured interviews were conducted with 17 experts who were selected on the basis of their knowledge and expertise in relation to good practice identified tools. Interviewees were asked to evaluate the approaches on the basis of the WHO model for healthy workplaces. Results: The examples of good practice for Workplace Mental Health Promotion (WMHP) are in line with the principles and the five keys of the WHO model. They support the third objective of the WHO comprehensive mental health action plan 2013-2020 for multisectoral implementation of WMHP strategies. Examples of good practice include the engagement of all stakeholders and representatives, science-driven practice, dissemination of good practice, continual improvement, and evaluation. Actions to inform policies/legislation, promote education on psychosocial risks, and provide better evidence were suggested for higher WMHP success. Conclusion: The study identified commonalities in good practice approaches in different countries and stressed the importance of a strong policy and enforcement framework as well as organizational responsibility for WMHP. For progress to be achieved in this area, a holistic and multidisciplinary approach was unanimously suggested as a way to successful implementation.

• Journal of Korean Society for Quality Management
• /
• v.49 no.3
• /
• pp.421-431
• /
• 2021

Purpose: For improving outgoing quality, this study presents a novel sampling framework based on predictive analytics. Methods: The proposed framework is composed of three steps. The first step is the variable selection. The knowledge-based and data-driven approaches are employed to select important variables. The second step is the model learning. In this step, we consider the supervised classification methods, the anomaly detection methods, and the rule-based methods. The applying model is the third step. This step includes the all processes to be enabled on real-time prediction. Each prediction model classifies a product as a target sample or random sample. Thereafter intensive quality inspections are executed on the specified target samples. Results: The inspection data of three Samsung products (mobile, TV, refrigerator) are used to check functional defects in the product by utilizing the proposed method. The results demonstrate that using target sampling is more effective and efficient than random sampling. Conclusion: The results of this paper show that the proposed method can efficiently detect products that have the possibilities of user's defect in the lot. Additionally our study can guide practitioners on how to easily detect defective products using stratified sampling

• Journal of Information Processing Systems
• /
• v.15 no.4
• /
• pp.865-889
• /
• 2019

The need for cyber resilience is increasingly important in our technology-dependent society where computing devices and data have been, and will continue to be, the target of cyber-attackers, particularly advanced persistent threat (APT) and nation-state/sponsored actors. APT and nation-state/sponsored actors tend to be more sophisticated, having access to significantly more resources and time to facilitate their attacks, which in most cases are not financially driven (unlike typical cyber-criminals). For example, such threat actors often utilize a broad range of attack vectors, cyber and/or physical, and constantly evolve their attack tactics. Thus, having up-to-date and detailed information of APT's tactics, techniques, and procedures (TTPs) facilitates the design of effective defense strategies as the focus of this paper. Specifically, we posit the importance of taxonomies in categorizing cyber-attacks. Note, however, that existing information about APT attack campaigns is fragmented across practitioner, government (including intelligence/classified), and academic publications, and existing taxonomies generally have a narrow scope (e.g., to a limited number of APT campaigns). Therefore, in this paper, we leverage the Cyber Kill Chain (CKC) model to "decompose" any complex attack and identify the relevant characteristics of such attacks. We then comprehensively analyze more than 40 APT campaigns disclosed before 2018 to build our taxonomy. Such taxonomy can facilitate incident response and cyber threat hunting by aiding in understanding of the potential attacks to organizations as well as which attacks may surface. In addition, the taxonomy can allow national security and intelligence agencies and businesses to share their analysis of ongoing, sensitive APT campaigns without the need to disclose detailed information about the campaigns. It can also notify future security policies and mitigation strategy formulation.