• Journal of Smart Tourism
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• v.1 no.2
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• pp.13-18
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• 2021

Hotels have recently started to implement enterprise information systems to measure and report sustainability indicators in a smart manner. However, a complex ownership structure in a hotel chain prevents full smart systems adoption at the individual property level. This study explores how a smart sustainability performance measurement system (SPMS) for waste management adoption correlates with customer ratings, customer reviews, operational efficiency scores, and between franchised and corporate-managed properties. We derive insights from the secondary data constructed from multiple sources for a large multinational hotel chain hotel. The findings suggest that hotels that adopt SPMS have better operational efficiency scores and more customer reviews. Within the hotels that adopted SPMS, corporate-managed hotels have a lower level of ratings than franchised hotels, but they have higher operational efficiency scores and more reviews. We discuss research implications for the concept of smart tourism and hotel management literature and managerial implications.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.232-241
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• 2018

Operational Transformation (OT) algorithms for real-time collaborative editing systems are becoming increasingly important due to the increased demand for collaborative data processing. The operational transformation algorithm is a technique for real-time concurrency control and consistency maintenance with non-locking technique, and many studies have been conducted to overcome three issues of convergence, causality-prevention, and intention-prevention. However, previous work has the disadvantage of wasting memory by storing all operations that occurred during an edit operation in the history buffer to solve this problem. Therefore, we propose a memory-saving real-time collaborative editing system that maintains a constant memory space and concurrency control through a method of applying the valid-time to each user-generated operation in order to reduce memory waste. This system prevents long-term memory occupation of client-generated operations, thus it reduces the space and time complexity even with low-rate of collaboration work, so that the performance degradation avoids.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.264-270
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• 1998

This research broadens the prime concern of nuclear power plant operations from safe performance to both economic and safe performance. First emergency diesel generator is identified as one of main contributors for the lost plant availability through the review of plants forced outage records. The framework of an integrated architecture for performing modern on-line condition for operational availability improvement is configured in this work. For the development of the comprehensive sensor networks for complex target systems, an integrated methodology incorporating a structural hierarchy, a functional hierarchy, and a fault-system matrix is formulated. The second part of our research is development of intelligent diagnosis and maintenance advisory system, which employs Bayesian Belief networks (BBNs) as a high level reasoning tool incorporating inherent uncertainty use in probabilistic inference. Our prototype diagnosis algorithms are represented explicitly through topological symbols and links between them in a causal direction. As new evidence from sensor network development is entered into the model especially, our advisory of system provides operational advice concerning both availability and safety, so that the operator is able to determine the likely modes, diagnose the system state, locate root causes, and take the most advantageous action. Thereby, this advice improves operational availability

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.563-573
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• 2018

An Expert Seasonal Prediction System for operational Seasonal Outlook (ESPreSSO) is developed based on the APEC Climate Center (APCC) Multi-Model Ensemble (MME) dynamical prediction and expert-guided statistical downscaling techniques. Dynamical models have improved to provide meaningful seasonal prediction, and their prediction skills are further improved by various ensemble and downscaling techniques. However, experienced scientists and forecasters make subjective correction for the operational seasonal outlook due to limited prediction skills and biases of dynamical models. Here, a hybrid seasonal prediction system that grafts experts' knowledge and understanding onto dynamical MME prediction is developed to guide operational seasonal outlook in Korea. The basis dynamical prediction is based on the APCC MME, which are statistically mapped onto the station-based observations by experienced experts. Their subjective selection undergoes objective screening and quality control to generate final seasonal outlook products after physical ensemble averaging. The prediction system is constructed based on 23-year training period of 1983-2005, and its performance and stability are assessed for the independent 11-year prediction period of 2006-2016. The results show that the ESPreSSO has reliable and stable prediction skill suitable for operational use.

• Atmosphere
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• v.32 no.2
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• pp.87-101
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• 2022

In this paper, the performance improvement for the new KMA's Climate Prediction System (GloSea6), which has been built and tested in 2021, is presented by assessing the bias distribution of basic variables from 24 years of GloSea6 hindcasts. Along with the upgrade from GloSea5 to GloSea6, the performance of GloSea6 can be regarded as notable in many respects: improvements in (i) negative bias of geopotential height over the tropical and mid-latitude troposphere and over polar stratosphere in boreal summer; (ii) cold bias of tropospheric temperature; (iii) underestimation of mid-latitude jets; (iv) dry bias in the lower troposphere; (v) cold tongue bias in the equatorial SST and the warm bias of Southern Ocean, suggesting the potential of improvements to the major climate variability in GloSea6. The warm surface temperature in the northern hemisphere continent in summer is eliminated by using CDF-matched soil-moisture initials. However, the cold bias in high latitude snow-covered area in winter still needs to be improved in the future. The intensification of the westerly winds of the summer Asian monsoon and the weakening of the northwest Pacific high, which are considered to be major errors in the GloSea system, had not been significantly improved. However, both the use of increased number of ensembles and the initial conditions at the closest initial dates reveals possibility to improve these biases. It is also noted that the effect of ensemble expansion mainly contributes to the improvement of annual variability over high latitudes and polar regions.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.21-31
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• 2003

Determination of operational dimensions and tolerances is complex if there exist inconsistencies between operational and design specifications. Dimension and tolerance charts (D&T charts) have been used to establish the relationships among operational dimensions in complex machining. This chart proves that individual operations can be harmonized when they are interconnected. However, it is hard to generate the chart manually. Because operational dimensions and tolerances must meet the design specifications, the dimensions and tolerances of interconnected operations have to be verified serially for economical operations. In this paper, the chart is automatically generated from the interconnected operations. More importantly, all operational dimensions and tolerances displayed in the chart have been verified by using LP to meet the design specifications. Finally, the chart is converted to an operational routing sheet that contains a detailed process plan along with cutting speed, feed rate, and operational references based on material hardness, surface finish, and tool nose radius.

• KIEE International Transactions on Power Engineering
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• v.3A no.3
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• pp.161-167
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• 2003

This paper presents a study performed to investigate the steady-state operational strategies of UPFCs in the Jeollanam-Do system in Korea. The objective of the study was to determine the UPFC operating points under normal and contingency conditions. The study consists of developing load flow models to simulate different load levels with and without UPFCs in the system, assessing the effectiveness of UPFCs by contingency analysis, and introducing optimal corrective actions for removing voltage problems caused by contingencies. The paper describes analytical tools, models and approach. It also includes analysis and discussion of the study results. The paper contributes to the area of transmission operational studies with FACTS applications.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.123-134
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• 1997

In this paper we consider the CSP requirements determination problem of new equipment system. The CSP we deal with in the paper are restricted to the demand-based spare parts. For the newly procured equipment systems, mathematical analyses are made for the system which is constructed with the repairable items to derive the associated CSP requirement determination model in mathematical expression, respectively. Based on these analyses, a mathematical model is derived for making an optimal CSP requirement determination subject to the constraint of satisfying any given funds limitation. We assume that the failure of a part follows a Poisson process. Firstly, the operational availability concept in CSP is defined and the relation between the general system availability and the operational availability is established. Secondly, the problem is formulated as the operational availability maximization problem that should satisfy the funds limitation, and then, using the generalized Lagrange multipliers method, the optimal solution procedure is derived.

• Smart Structures and Systems
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• v.7 no.2
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• pp.153-167
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• 2011

The Subspace based System Identification Techniques (SSIT) have been very popular within the research circles in the last decade due to their proven superiority over the other existing system identification techniques. For operational (output only) modal analysis, the stochastic SSIT and for operational modal analysis in the presence of exogenous inputs, the combined deterministic stochastic SSIT have been used in the literature. This study compares the application of the two alternative techniques on a typical school building in Istanbul using 100 Monte Carlo simulations. The study clearly shows that the combined deterministic stochastic SSIT performs superior to the stochastic SSIT when the techniques are applied on noisy data from low to mid rise stiff structures.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1422-1431
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• 2015

The reliability of power system components can be affected by a numbers of factors such as the health level of components, external environment and operation environment of power systems. These factors also affect the electrical parameters of power system components for example the thermal capacity of a transmission element. The relationship of component reliability and power system is, therefore, a complex nonlinear function related to the above-mentioned factors. Traditional approaches for reliability assessment of power systems do not take the influence of these factors into account. The assessment results could not, therefore, reflect the short-term trend of the system reliability performance considering the influence of the key factors and provide the system dispatchers with enough information to make decent operational decisions. This paper discusses some of these important operational issues from the perspective of power system reliability. The discussions include operational reliability of power systems, reliability influence models for main performance parameters of components, time-varying reliability models of components, and a reliability assessment algorithm for power system operations considering the time-varying characteristic of various parameters. The significance of these discussions and applications of the proposed techniques are illustrated by case study results using the IEEE-RTS.