• Journal of Korean Society of Archives and Records Management
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• v.21 no.3
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• pp.1-16
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• 2021

Record continuum is a theory providing the basis for archival science in the paradigm shift to the electronic record environment. However, critical analysis of it has been hardly performed so far, as it is still in development, and its core is a new perspective on records different from the life cycle model. Therefore, for further understanding of the significance and limitations of record continuum in the electronic record environment and performance of more in-depth theoretical development, an analysis of the meaning and nature of records contained in record continuum logic is essential. Given that record continuum does not define a record separately, the meaning and nature of records it contains in the recent electronic record environment are examined through the analysis of axis and dimension in a record continuum model.

• Steel and Composite Structures
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• v.48 no.2
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• pp.179-190
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• 2023

Many recent attempts have sought accurate prediction of pile pullout resistance (P_ul) using classical machine learning models. This study offers an improved methodology for this objective. Adaptive neuro-fuzzy inference system (ANFIS), as a popular predictor, is trained by a capable metaheuristic strategy, namely equilibrium optimizer (EO) to predict the P_ul. The used data is collected from laboratory investigations in previous literature. First, two optimal configurations of EO-ANFIS are selected after sensitivity analysis. They are next evaluated and compared with classical ANFIS and two neural-based models using well-accepted accuracy indicators. The results of all five models were in good agreement with laboratory P_uls (all correlations > 0.99). However, it was shown that both EO-ANFISs not only outperform neural benchmarks but also enjoy a higher accuracy compared to the classical version. Therefore, utilizing the EO is recommended for optimizing this predictive tool. Furthermore, a comparison between the selected EO-ANFISs, where one employs a larger population, revealed that the model with the population size of 75 is more efficient than 300. In this relation, root mean square error and the optimization time for the EO-ANFIS (75) were 19.6272 and 1715.8 seconds, respectively, while these values were 23.4038 and 9298.7 seconds for EO-ANFIS (300).

• Atmosphere
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• v.33 no.5
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• pp.519-530
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• 2023

Deep convection can make adverse effects on safe and efficient aviation operations by causing various weather hazards such as convectively-induced turbulence, icing, lightning, and downburst. To prevent such damage, it is necessary to accurately predict spatiotemporal distribution of deep convective area near the airport and airspace. This study developed a new index, the Aviation Convective Index (ACI), for deep convection, using the operational global Unified Model of the Korea Meteorological Administration. The ACI was computed from combination of three different variables: 3-hour maximum of Convective Available Potential Energy, averaged Outgoing Longwave Radiation, and accumulative precipitation using the fuzzy logic algorithm. In this algorithm, the individual membership function was newly developed following the cumulative distribution function for each variable in Korean Peninsula. This index was validated and optimized by using the 1-yr period of radar mosaic data. According to the Receiver Operating Characteristics curve (AUC) and True Skill Score (TSS), the yearly optimized ACI (ACI_YrOpt) based on the optimal weighting coefficients for 1-yr period shows a better skill than the no optimized one (ACI_NoOpt) with the uniform weights. In all forecast time from 6-hour to 48-hour, the AUC and TSS value of ACI_YrOpt were higher than those of ACI_NoOpt, showing the improvement of averaged value of AUC and TSS by 1.67% and 4.20%, respectively.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.60-75
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• 2024

The demand of users, who want to focus on the core functionality of their applications without having to manage complex virtual environments in the cloud environment, has created a new computing model called serverless computing. Within the serverless paradigm, resource provisioning and server administration tasks are delegated to cloud services, facilitating application development exclusively focused on program logic. Serverless computing has upgraded the utilization of cloud computing by reducing the burden on cloud service users, and it is expected to become the basic model of cloud computing in the future. A serverless platform is responsible for managing the cloud virtual environment on behalf of users, and it is also responsible for executing serverless functions that compose applications in the cloud environment. Considering the characteristics of serverless computing in which users are billed in proportion to the resources used, the efficiency of the serverless platform is a very important factor for both users and service providers. This paper aims to identify various factors that affect the performance of serverless computing and analyze the latest research trends related to it. Drawing upon the analysis, the future directions for serverless computing that address key challenges and opportunities in serverless computing are proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.801-825
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• 2024

For Internet of Things, it is more preferred to have immediate access to environment information from sensor nodes (SNs) rather than from gateway nodes (GWNs). To fulfill the goal, mutual authentication scheme between user and SNs with session key (SK) negotiation is more suitable. However, this is a challenging task due to the constrained power, computation, communication and storage resources of SNs. Though lots of authentication schemes with SK negotiation have been designed to deal with it, they are still insufficiently secure and/or efficient, and some even have serious vulnerabilities. Therefore, we design an efficient secure authentication scheme with session key negotiation (eSAS2KN) for wireless sensor networks (WSNs) utilizing fuzzy extractor technique, hash function and bitwise exclusive-or lightweight operations. In the eSAS2KN, user and SNs are mutually authenticated with anonymity, and an SK is negotiated for their direct and instant communications subsequently. To prove the security of eSAS2KN, we give detailed informal security analysis, carry out logical verification by applying BAN logic, present formal security proof by employing Real-Or-Random (ROR) model, and implement formal security verification by using AVISPA tool. Finally, computation and communication costs comparison show the eSAS2kN is more efficient and secure for practical application.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.177-198
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• 2018

Recently, as economic property it has become necessary to acquire and utilize the framework for water resource measurement and performance management as the property of water resources changes to hold "public property". To date, the evaluation of water technology has been carried out by feasibility study analysis or technology assessment based on net present value (NPV) or benefit-to-cost (B/C) effect, however it is not yet systemized in terms of valuation models to objectively assess an economic value of technology-based business to receive diffusion and feedback of research outcomes. Therefore, K-water (known as a government-supported public company in Korea) company feels the necessity to establish a technology valuation framework suitable for technical characteristics of water resources fields in charge and verify an exemplified case applied to the technology. The K-water evaluation technology applied to this study, as a public interest goods, can be used as a tool to measure the value and achievement contributed to society and to manage them. Therefore, by calculating the value in which the subject technology contributed to the entire society as a public resource, we make use of it as a basis information for the advertising medium of performance on the influence effect of the benefits or the necessity of cost input, and then secure the legitimacy for large-scale R&D cost input in terms of the characteristics of public technology. Hence, K-water company, one of the public corporation in Korea which deals with public goods of 'water resources', will be able to establish a commercialization strategy for business operation and prepare for a basis for the performance calculation of input R&D cost. In this study, K-water has developed a web-based technology valuation model for public interest type water resources based on the technology evaluation system that is suitable for the characteristics of a technology in water resources fields. In particular, by utilizing the evaluation methodology of the Institute of Advanced Industrial Science and Technology (AIST) in Japan to match the expense items to the expense accounts based on the related benefit items, we proposed the so-called 'K-water's proprietary model' which involves the 'cost-benefit' approach and the FCF (Free Cash Flow), and ultimately led to build a pipeline on the K-water research performance management system and then verify the practical case of a technology related to "desalination". We analyze the embedded design logic and evaluation process of web-based valuation system that reflects characteristics of water resources technology, reference information and database(D/B)-associated logic for each model to calculate public interest-based and profit-based technology values in technology integrated management system. We review the hybrid evaluation module that reflects the quantitative index of the qualitative evaluation indices reflecting the unique characteristics of water resources and the visualized user-interface (UI) of the actual web-based evaluation, which both are appended for calculating the business value based on financial data to the existing web-based technology valuation systems in other fields. K-water's technology valuation model is evaluated by distinguishing between public-interest type and profitable-type water technology. First, evaluation modules in profit-type technology valuation model are designed based on 'profitability of technology'. For example, the technology inventory K-water holds has a number of profit-oriented technologies such as water treatment membranes. On the other hand, the public interest-type technology valuation is designed to evaluate the public-interest oriented technology such as the dam, which reflects the characteristics of public benefits and costs. In order to examine the appropriateness of the cost-benefit based public utility valuation model (i.e. K-water specific technology valuation model) presented in this study, we applied to practical cases from calculation of benefit-to-cost analysis on water resource technology with 20 years of lifetime. In future we will additionally conduct verifying the K-water public utility-based valuation model by each business model which reflects various business environmental characteristics.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.239-251
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• 2010

In modern distributed enterprise applications that have multilayered architecture, business entities are a kind of crosscutting concerns running through service components that implements business logic in each layer. When business entities are modified, service components related to them should also be modified so that they can deal with those business entities with new types, even though their functionality remains the same. Our previous paper proposed what we call the DTT (Data Type-Tolerant) component model to efficiently process the variability of business entities, which are data externalized from service components. While the DTT component model, by removing direct coupling between service components and business entities, exempts the need to rewrite service components when business entities are modified, it incurs the burden of implementing data type converters that mediate between them. To solve this problem, this paper proposes a method to use ontology as the metadata of both SCDTs (Self-Contained Data Types) in service components and business entities, and a method to generate data type converter code using the ontology. This ontology-based DTT component model greatly enhances the reusability of service components and the efficiency in processing data variability by allowing the computer to automatically generate data type converters without error.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.12
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• pp.1185-1192
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• 2012

The typical operating temperature of an automotive fuel cell is lower than that of an internal combustion engine, which necessitates a refined strategy for thermal management. In particular, the performance of the cooling module has to be higher for a fuel cell system because the temperature difference between the fuel cell and the surrounding is lower than in the case of the internal combustion engine. Even though the cooling system of an automotive fuel cell determines the operating temperature and temperature distribution of the fuel cell, it has attracted little research attention. This study presents the mathematical model of a cooling system for an automotive fuel cell system using Matlab/$Simulink^{(R)}$. In particular, a radiator model is developed for design optimization from the development stage to the operating stage for an automotive fuel cell. The cooling system model comprises a fan, pump, and radiator. The pump and fan model have an empirical relation, and the dynamics of the pump and fan are only explained by motor dynamics. The basic design study was conducted, and the geometric setup of the radiator was investigated. When the control logic was applied, the pump senses the coolant inlet temperature and the fan senses the coolant out temperature. Additionally, the cooling module is integrated with the fuel cell system model so that the performance of the cooling module can be investigated under realistic operating conditions.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.212-218
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• 2003

State invariant is a property that holds in every reachable state. It can be used not only in understanding and analyzing complex software systems, but it can also be used for system verifications such as checking safety, liveness, and consistency. For these reasons, there are many vital researches for deriving state invariant from finite state machine models. In previous works every reachable state is to be considered to generate state invariant. Thus it is likely to be too complex for the user to understand. This paper seeks to answer the question `how to simplify state invariant\ulcorner`. Since the complexity of state invariant is strongly dependent upon the size of states to be considered, so the smaller the set of states to be considered is, the shorter the length of state invariant is. For doing so, we let the user focus on some interested scopes rather than a whole state space in a model. Computation Tree Logic(CTL) is used to specify scopes in which he/she is interested. Given a scope in CTL, mixed reachability analysis is used to find out a set of states inside it. Obviously, a set of states calculated in this way is a subset of every reachable state. Therefore, we give a weaker, but comprehensible, state invariant.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.15-32
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• 2006

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiple criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interactions may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.