• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.836-850
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• 2006

Nowadays, due to the rapidly increasing number of package software products, quality test has been emphasized for package software products. When testing software products, one of the most important factors is to select metrics which form the bases for tests. In this paper, the types of package software are represented as characteristic vectors having probabilistic relationships with metrics. The characteristic vectors could be regarded as indicators of software type. To assign the metrics for each software type, the past test metrics are collected and analyzed. Using Bayesian belief network, the dependency relationship network of the characteristic vectors and metrics is constructed. The dependency relationship network is then used to find the proper metrics for the test of new package software products.

• The KIPS Transactions:PartD
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• v.15D no.5
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• pp.629-646
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• 2008

Because most metricsin the literatures are described by a natural language, they can be interpreted in an ambigous manner. To cope with this problem, there are some researches to express based on Object Constraint Language(OCL). Because OCL has been proposed to describe structural constraintsfor Unified Modeling Language(UML) diagrams, it is difficult and awkward. In this paper, we propose Metric Description Language(MDL) which is a high level language to describe metrics. MDL supports a modular description of complex metrics, aggregation function, and automatic navigation between entities. Moreover, we develop MetriUs for describing metrics using MDL and supporting an automated computation for UML diagrams. In a case study, we have described a variety of existing metrics using MDL and found that MDL contributes to producing simpler expression of metrics than OCL.

• Korean Journal of Radiology
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• v.22 no.9
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• pp.1497-1513
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• 2021

The diagnostic and treatment methods of multiple myeloma (MM) have been rapidly evolving owing to advances in imaging techniques and new therapeutic agents. Imaging has begun to play an important role in the management of MM, and international guidelines are frequently updated. Since the publication of 2015 International Myeloma Working Group (IMWG) criteria for the diagnosis of MM, whole-body magnetic resonance imaging (MRI) or low-dose whole-body computed tomography (CT) and ¹⁸F-fluorodeoxyglucose positron emission tomography/CT have entered the mainstream as diagnostic and treatment response assessment tools. The 2019 IMWG guidelines also provide imaging recommendations for various clinical settings. Accordingly, radiologists have become a key component of MM management. In this review, we provide an overview of updates in the MM field with an emphasis on imaging modalities.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.994-1004
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• 2021

Objective: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management. Materials and Methods: All initial chest CTs of patients who tested positive for severe acute respiratory syndrome coronavirus 2 at our emergency department between March 25 and April 25, 2020, were identified (n = 120). Three patient management groups were defined: group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit [ICU]). Multiple pulmonary and cardiovascular metrics were extracted from the chest CT images using deep learning. Additionally, six laboratory findings indicating inflammation and cellular damage were considered. Differences in CT metrics, laboratory findings, and demographics between the patient management groups were assessed. The potential of these parameters to predict patients' needs for intensive care (yes/no) was analyzed using logistic regression and receiver operating characteristic curves. Internal and external validity were assessed using 109 independent chest CT scans. Results: While demographic parameters alone (sex and age) were not sufficient to predict ICU management status, both CT metrics alone (including both pulmonary and cardiovascular metrics; area under the curve [AUC] = 0.88; 95% confidence interval [CI] = 0.79-0.97) and laboratory findings alone (C-reactive protein, lactate dehydrogenase, white blood cell count, and albumin; AUC = 0.86; 95% CI = 0.77-0.94) were good classifiers. Excellent performance was achieved by a combination of demographic parameters, CT metrics, and laboratory findings (AUC = 0.91; 95% CI = 0.85-0.98). Application of a model that combined both pulmonary CT metrics and demographic parameters on a dataset from another hospital indicated its external validity (AUC = 0.77; 95% CI = 0.66-0.88). Conclusion: Chest CT of patients with COVID-19 contains valuable information that can be accessed using automated image analysis. These metrics are useful for the prediction of patient management.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.595-606
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• 2000

Software metrics evaluate the development process, measure the software development effort, and control the software quality effectively. Moreover in a current status to emphasize reusability, it is necessary to study of cohesion and coupling that plays an important role in evaluating reusability. Object oriented methodology to use the concept like encapsulation, inheritance, and polymorphism demands metrics that are different from existing procedural methodology, so a study for object oriented metrics is in progress at the present time. In this paper, we propose cohesion and coupling metrics for object oriented program, evaluate the proposed metrics by using the complexity properties proposed by Weyuker and Briand, and extract cohesion and coupling from C++ code.

• Journal of Information Technology Services
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• v.12 no.4
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• pp.349-367
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• 2013

In MANET, the AODV routing protocol with on-demand method has a problem in large control packet overhead. In order to improve this, we first need a comprehensive analysis of correlation between performance metrics and factors affecting the performance of AODV. Selected parameters based on this analysis make it enable to be a more accurate and fair performance analysis, as well as to reduce the time and effort when constructing a scenario for performance analysis. In this paper, various scenarios are configured to apply AODV by varying the values of factors affecting the performance with network simulator QualNet 5.0, and then the results are analysed using performance metrics proposed by IETF MANET working group. This paper also founds a correlation between performance metrics and factors affecting the performance for AODV routing protocol, choosing the values of factors that represent many of the most maximum and minimum values of each performance metrics, and proposes optimal simulation parameters for a more accurate performance evaluation of routing protocols with minimal scenario in experiments. Next, performance comparison of AODV, DSR and DYMO routing protocols based on the proposed simulation parameters is shown which provides a comparative analysis on the performance of on-demand routing protocols. Results of this paper could be very useful for the researcher or service provider who wants to find nice simulation environment or select a proper routing protocol.

• KIISE Transactions on Computing Practices
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• v.24 no.1
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• pp.46-52
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• 2018

Software metrics as a way to evaluate software play a significant role in reducing software development costs and improving quality. However, the emergence of various software metrics creates the problem that the user must select the correct metric. Various strategies have been studied to solve this problem. However, existing studies still have difficulties in selecting metrics by requiring high user interventions. Therefore, in this paper, we propose a method that helps to select the right metric and the metric tools by using their various characteristics as selection criteria, instead of using weighted expressions to minimize user intervention.

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.745-752
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• 2003

The component-based development methodology becomes famous as the reuse technology for independence and productivity of software development It is necessary component metrics for component-based systems, because It should be measurable to improve the quality of the software. Hence, in this paper, we propose component cohesion and coupling metrics which is reflected in characteristics of component. The operation use value is calculated by the information of classes interface commonly uses to offer the component's service. And, the operation similarity value is calculated by the operations use value. Component cohesion and coupling is calculated by the operation similarity and based of the information which is extracted in the analysis phase. And, we examine the necessity of component metrics in comparison with object-oriented metrics.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.271-282
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• 2019

There is a description that you cannot manage what you do not measure. The Korea Ministry of National Defense (MND) is conducting evaluations in various fields to obtain meaningful effects from IT investments, and views that the evaluation of the defense informatization sector is divided into defense informatization policy evaluation and defense informatization project evaluation. The defense informatization level evaluation can measure the informatization level of MND and the armed forces or organizations. Since the evaluation system being studied to measure the level of defense informatization is composed mainly of qualitative metrics, it is necessary to reconstruct it based on quantitative metrics that can guarantee objectivity. In addition, for managing the level of change by evaluation objects, the evaluation system should be designed with a focus on homeostasis of metrics so that it can be measured periodically. Moreover, metrics need to be promoted in terms of performance against targets. To this end, this study proposes to measure the level of defense informatization by dividing it into defense information network, computer systems, interoperability and standardization, information security, information environment, and information system use, and suggests their metrics.

• Phonetics and Speech Sciences
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• v.11 no.4
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• pp.81-87
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• 2019

The purpose of the current study is to investigate the realization of speech rhythm in English as spoken by Korean learners of English. The study particularly aims to examine the rhythm metrics of English read speech by learners who speak Busan or the South Kyungsang dialect of Korean. Twenty-four learners whose L1 is Busan Korean and eight native speakers of English read a passage wherein five sentences were segmented and labeled as vocalic and intervocalic intervals. Various rhythm metrics such as %V, Varcos, and Pairwise Variability Indexes (PVIs) were calculated. The results show that Korean learners read English sentences with significantly more vocalic and consonantal intervals at a slower speech rate than native English speakers. The analyses of rhythm metrics revealed that when the speech rate was not normalized, Korean learners' English showed more variability in the length of consonantal and vocalic intervals. However, speech-rate-normalized rhythm metrics for vocalic intervals indicated that Korean learners transferred their L1 rhythmic structures (a syllable-timed language) into their L2 speech (a stress-timed language). Overall, the results suggest that Korean learners' English reflects the rhythmic characteristics of their L1. The effect of the learners' L1 dialect on the realization of L2 speech rhythm is also speculated.