• The Korean Journal of Financial Management
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• v.24 no.3
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• pp.153-186
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• 2007

It is well known that the distributional properties of financial asset returns exhibit fatter-tails and skewer-mean than the assumption of normal distribution. The correct assumption of return distribution might improve the estimated performance of the Value-at-Risk(VaR) models in financial markets. In this paper, we estimate and compare the VaR performance using the RiskMetrics, GARCH and FIGARCH models based on the normal and skewed-Student-t distributions in two daily returns of the Korean Composite Stock Index(KOSPI) and Korean Won-US Dollar(KRW-USD) exchange rate. We also perform the expected shortfall to assess the size of expected loss in terms of the estimation of the empirical failure rate. From the results of empirical VaR analysis, it is found that the presence of long memory in the volatility of sample returns is not an important in estimating an accurate VaR performance. However, it is more important to consider a model with skewed-Student-t distribution innovation in determining better VaR. In short, the appropriate assumption of return distribution provides more accurate VaR models for the portfolio managers and investors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.2063-2076
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• 1996

In this thesis, in order to apply a punctured convolutional codes to the trellis coded modulation(TCM), an efficient punctured trellis coded modulation(PTCM) based on the decomposition of the metric into orthogonal components is presented. Also, a simulation is performed in an additive white Gaussian noise(AWGN) and a rician fading channel modeling the mobile satellite channel. The PTCM combines punctured convolutional coding with MPSK modulation to provide a large coding gain in a power-limited or bandwidth-limited channel. However, in general the use of the punctured convolutional code structure in the decoder results in a performance loss in comparison to trellis codes, due to difficulties in assigning metrics. But, the study shows no loss in performance for punctured trellis coded MPSK in comparison to TCM, and what is more, the punctured convolutional codes results in some savings in the complexity of Viterbi decoders, compared to TCM of the same rate. Also, the results shows that the punctured trellis coded .pi./8 shift 8PSK is an attractive scheme for power-limited and band-limited systems and especially, the Viterbi decoder with first and Lth phase difference metrics improves BER performance by the mobile satellite channel.

• Journal of Information Science Theory and Practice
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• v.8 no.2
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• pp.55-67
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• 2020

Webometric research in the Russian library sector is just beginning to gain momentum. This article examines the experience of webometric research in libraries from the perspective of the global practice. In particular, it highlights a number of foreign works, which may have a special practical value for Russian libraries, and emphasizes important webometrics areas for libraries. The purpose of this study is to research the practical application of key performance indicators (KPIs) abroad and conduct a webometric analysis of the websites of some leading Siberian and Far Eastern scientific libraries based on selected KPIs. The study data were collected with SimilarWeb and other analytical tools. The study revealed that key traffic metrics are the basis of webometric research, and identified available promising groundwork for the purpose of their further testing. The shortcomings in the current state of the websites of the Siberian and Far Eastern scientific libraries were noted. Based on the obtained webometric traffic indicators, the ranking of the Siberian and Far Eastern scientific libraries was made.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.199-206
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• 2012

Increment of mobile client's information request in wireless mobile networks requires a new method to manage and serve the streaming media object. This paper proposes a new object segment grouping method for enhancing the performance of streaming media services in wireless mobile networks. The proposed method performs the similarity metric for the partitioned object segments, and it process the disjunction, conjunction, and filtering for these metrics. This paper was to decided the partitioned group of object segments for these operation metrics, and it decided the performance of streaming media services. The simulation result showed that the proposed method has better performance in throughput, average startup latency, and cache hit ratio.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.23-32
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• 2024

Mobile Ad hoc Network is a network of multiple wireless nodes which communicate and exchange information together without any fixed and centralized infrastructure. The core objective for the development of MANET is to provide movability, portability and extensibility. Due to infrastructure less network topology of the network changes frequently this causes many challenges for designing routing algorithms. Many routing protocols for MANET have been suggested for last few years and research is still going on. In this paper we review three main routing protocols namely Proactive, Reactive and Hybrid, performance comparison of Proactive such as DSDV, Reactive as AODV, DSR, TORA and Hybrid as ZRP in different network scenarios including dynamic network size, changing number of nodes, changing movability of nodes, in high movability and denser network and low movability and low traffic. This paper analyzes these scenarios on the performance evaluation metrics e.g. Throughput, Packet Delivery Ratio (PDR), Normalized Routing Load(NRL) and End To-End delay(ETE).This paper also reviews various network layer security attacks challenge by routing protocols, detection mechanism proposes to detect these attacks and compare performance of these attacks on evaluation metrics such as Routing Overhead, Transmission Delay and packet drop rates.

• Architectural research
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• v.18 no.1
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• pp.21-29
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• 2016

Importance of FM has rapidly increased because of its growing business. However, due to lack of clarity and identity of FM in professional areas, standardization of FM became to be imperative in such a rapidly changing global business environment. Facility services are defined as the provision of support the primary activities of an organization, delivered by an internal or external provider. Majority of FM activities are services related to 'space and infrastructure' and 'people and organization' (CEN, 2011). The purpose of this study is to investigate definitions and characteristics of FM from both globally and domestic environment, by comparison with international or national standards, to identify quality management in FM and service characteristics of FM, to investigate the differences in service level elaboration in FM, and to suggest standard issues of quality management in FM service quality. This study examines contents of the European Standards in FM, Part 3 'Guidance on quality in Facility Management, especially for the process of QM standardized by CEN (2011) and explores undefined issues such as service level, measurement metrics according to service characteristics of FM. The European FM Standard guides the common process of QM in terms of requirements specification, service level elaboration, measurement metrics development although it does not specifically address various service levels, specific performance metrics and indicators.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.7 s.100
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• pp.821-828
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• 2005

In our life, we have used many digital appliances. They help us to improve the quality of life but sometimes give us unsatisfactory result. Because they produce specific noise. Especially vacuum cleaner produce much noise that is very annoying. So we need to study what sound metrics affect human sensibility. In this paper, we develop sound quality index for vacuum cleaner using the sound quality metrics defined in psychoacoustics. First, we carry out the subjective evaluation of vacuum cleaner sound to verify what vacuum sound feels good to human. And then artificial neural network estimated the complexity and the nonlinear characteristics of the relations between subjective evaluation and sound metrics. Finally the ANN is trained repeatedly to have a good performance for sound qualify index of the vacuum cleaner. As a result, the sound quality index of vacuum cleaner has a correlation of $93.5\%$ between the subjective evaluation and ANN. So, there exist three factors that Is loudness, sharpness, roughness which affect the sound quality of vacuum cleaner.

• Journal of the Korea Safety Management & Science
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• v.14 no.2
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• pp.147-158
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• 2012

This paper aims to develop a new chain metrics for obtaining lean Overall Equipment Effectiveness(OEE) and present implementation strategy which considers the properties for Total Productive Maintenance(TPM) to reduce machine losses, Performance Analysis and Control(PAC) to reduce labor losses, Lean Production System(LPS) to reduce floor wastes, and Theory of Constraints(TOC) to minimize the problem of Capacity Constrained Resource(CCR). The study reviews the related literatures and reformulates the structure of machine losses, labor losses and field wastes. The research also develops the integrated productivity metrics according to time, units, reliability and maintainability. It is found that the study develops the actual productivity measure in terms of efficiency, effectiveness and standard productivity. In addition to that, it outlines and develops by using the integrated LPS and TPM, lean OEE measures such as Time Based Productivity(TBP), Unit Based Productivity(UBP), and Reliability & Maintainability Based Availability(RMBA). Implication examples are proposed to make it easier and available for practioners to understand the implementation strategies about TPM OEE, lean OEE and TOC OEE. Futhermore related to other studies, the research contributes to create a new chain productivity measures to clear the interrelationship concepts of productivity, efficiency and effectiveness. Moreover the paper develops the enhanced OEE measures by integration of TPM, PAC, LPS and TOC with the perspective of schedule, throughput, reliability, maintainability and availability.

• The Korean Journal of Applied Statistics
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• v.37 no.3
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• pp.311-322
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• 2024

In this study, we conduct an exploratory analysis of the MovieLens data, which is frequently used in many recommender system researches, to examine the detailed characteristics of the data. Also, we seek alternatives to improve the well-known neural collaborative filtering (NCF) method. NCF improved matrix factorization method by using deep neural networks in recommender systems. We devise, generalized NCF (G-NCF), a variant of NCF and test the performances. The G-NCF we propose shows superior characteristics on average performance across key evaluation metrics, compared to the NCF, but it also has a slightly larger variance in the evaluation metrics. Evaluation metrics such as MAP and nDCG were considered for comparison.

• Computers and Concrete
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• v.33 no.1
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• pp.55-75
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• 2024

The present study introduces an optimum performance soft computing model for predicting the compressive strength of high-performance concrete (HPC) by comparing models based on conventional (kernel-based, covariance function-based, and tree-based), advanced machine (least square support vector machine-LSSVM and minimax probability machine regressor-MPMR), and deep (artificial neural network-ANN) learning approaches using a common database for the first time. A compressive strength database, having results of 1030 concrete samples, has been compiled from the literature and preprocessed. For the purpose of training, testing, and validation of soft computing models, 803, 101, and 101 data points have been selected arbitrarily from preprocessed data points, i.e., 1005. Thirteen performance metrics, including three new metrics, i.e., a20-index, index of agreement, and index of scatter, have been implemented for each model. The performance comparison reveals that the SVM (kernel-based), ET (tree-based), MPMR (advanced), and ANN (deep) models have achieved higher performance in predicting the compressive strength of HPC. From the overall analysis of performance, accuracy, Taylor plot, accuracy metric, regression error characteristics curve, Anderson-Darling, Wilcoxon, Uncertainty, and reliability, it has been observed that model CS4 based on the ensemble tree has been recognized as an optimum performance model with higher performance, i.e., a correlation coefficient of 0.9352, root mean square error of 5.76 MPa, and mean absolute error of 4.1069 MPa. The present study also reveals that multicollinearity affects the prediction accuracy of Gaussian process regression, decision tree, multilinear regression, and adaptive boosting regressor models, novel research in compressive strength prediction of HPC. The cosine sensitivity analysis reveals that the prediction of compressive strength of HPC is highly affected by cement content, fine aggregate, coarse aggregate, and water content.