• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.4
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• pp.346-351
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• 2003

In spite of the size and complexity of software becomes large and complicated, the demand of rapid development, cost reduction, good productivity and good quality software is increasing in these days. Many methods were proposed for efficient software development such as various Case tools. Metrics, Process improvement model (CMM, SPICE, ISO9000) and etc. However, most of them we useful to manage the whole projects rather than an individual programming. In this paper, we introduced a system for quality assessment and complexity metrics for Java programs to assess the individual programmer's quality rather than team's quality. This system shows not only the metrics value for quality assessment but also the source code and the soucture of classes simultaneously.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.159-168
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• 2015

Aggregate Production Planning determines levels of production, human resources, inventory to maximize company's profits and fulfill customer's demands based on demand forecasts. Since performance of aggregate production planning heavily depends on accuracy of given forecasting demands, choosing an accurate forecasting method should be antecedent for achieving a good aggregate production planning. Generally, typical forecasting error metrics such as MSE (Mean Squared Error), MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and CFE (Cumulated Forecast Error) are utilized to choose a proper forecasting method for an aggregate production planning. However, these metrics are designed only to measure a difference between real and forecast demands and they are not able to consider any results such as increasing cost or decreasing profit caused by forecasting error. Consequently, the traditional metrics fail to give enough explanation to select a good forecasting method in aggregate production planning. To overcome this limitation of typical metrics for forecasting method this study suggests a new metric, WACFE (Weighted Absolute and Cumulative Forecast Error), to evaluate forecasting methods. Basically, the WACFE is designed to consider not only forecasting errors but also costs which the errors might cause in for Aggregate Production Planning. The WACFE is a product sum of cumulative forecasting error and weight factors for backorder and inventory costs. We demonstrate the effectiveness of the proposed metric by conducting intensive experiments with demand data sets from M3-competition. Finally, we showed that the WACFE provides a higher correlation with the total cost than other metrics and, consequently, is a better performance in selection of forecasting methods for aggregate production planning.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.165-172
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• 2008

There are many metrics when designing microprocessors. Especially, energy, power consumption and performance are the most fundamental metrics. Since these metrics are contradictory, microprocessor designers give more weight to some metrics than the other metrics. In this paper, we compare Intel Pentium 4 and Core2 Duo both qualitatively and quantitatively. Furthermore, we provide detailed comparison between Pentium 4 and Core2 Duo when running real benchmarks. Through performance counter of real processors, we calculate energy and power consumption. Performance metric is execution time. In experimental result, Core2 Duo consumes less energy and power. Moreover, performance of Core2 Duo is also better than that of Pentium 4. However, in case of bzip2 which is optimized in Pentium 4, Pentium 4 shows much better performance and lower energy and power consumption than Core2 Duo.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.197-206
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• 2015

Defect severity that is a measure of the impact caused by the defect plays an important role in software quality activities because not all software defects are equal. Earlier studies have concentrated on defining defect severity levels, but there have almost never been trials of measuring module severity. In this paper, first, we define a defect severity metric in the form of an exponential function using the characteristics that defect severity values increase much faster than severity levels. Then we define a new metrics set for software module severity using the number of defects in a module and their defect severity metric values. In order to show the applicability of the proposed metrics, we performed an analytical validation using Weyuker's properties and experimental validation using NASA open data sets. The results show that ms is very useful for measuring the module severity and msd can be used to compare different systems in terms of module severity.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.101-108
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• 2022

We propose an intrusion detection model that detects denial-of-service(DoS) and distributed reflection denial-of-service(DRDoS) attacks, based on the empirical data of each internet of things(IoT) device by training system and network metrics that can be commonly collected from various IoT devices. First, we collect 37 system and network metrics from each IoT device considering IoT attack scenarios; further, we train them using six types of machine learning models to identify the most effective machine learning models as well as important metrics in detecting and distinguishing IoT attacks. Our experimental results show that the Random Forest model has the best performance with accuracy of over 96%, followed by the K-Nearest Neighbor model and Decision Tree model. Of the 37 metrics, we identified five types of CPU, memory, and network metrics that best imply the characteristics of the attacks in all the experimental scenarios. Furthermore, we found out that packets with higher transmission speeds than larger size packets represent the characteristics of DoS and DRDoS attacks more clearly in IoT networks.

• Archives of Plastic Surgery
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• v.51 no.2
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• pp.169-181
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• 2024

Background With the advent of cranial orthoses as therapeutic medical devices for the treatment of severe positional head deformities in Japan, an increasing number of patients are being treated with them. However, assessing the effectiveness of a treatment is often difficult due to the use of different metrics. This study aimed to evaluate the effectiveness of cranial orthoses for deformational plagiocephaly using two- (2D) and three-dimensional (3D) evaluation metrics. Methods We conducted a retrospective study of infant patients with deformational plagiocephaly who underwent cranial orthosis treatment. We evaluated the severity of deformational plagiocephaly using cranial asymmetry (CA) and the cranial vault asymmetry index (CVAI) as 2D metrics, and anterior and posterior symmetry ratios as 3D metrics. The patients were divided into 24 subgroups based on the initial severity of each outcome and their age at the start of treatment. We analyzed the changes in outcomes and correlations within improvements across the age and severity categories. Results Overall, 1,038 infants were included in this study. The mean CA, CVAI, and anterior and posterior symmetry ratios improved significantly after cranial orthosis treatment. The improvement in each score was greater in patients with more severe initial deformities and in those who underwent treatment at a younger age. Conclusion Cranial orthosis treatment was effective in correcting deformational plagiocephaly in infants, as demonstrated by improvements in both 2D and 3D metrics. Patients with more severe initial deformities and those who underwent treatment at a younger age showed greater improvement.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.149-160
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• 2007

The IAEA launched the International Project on Innovative Nuclear Reactors and Fuel Cycles (INPRO) and developed the INPRO Methodology to provide guidelines and to assess the characteristics of a future innovative nuclear energy system in areas such as safety, economics, waste management, and proliferation resistance. The proliferation resistance area of the INPRO Methodology is reviewed here, and modifications for further improvements are proposed. The evaluation metrics including the evaluation parameters, evaluation scales and acceptance limits are developed for a practical application of the methodology to assess the proliferation resistance. The proliferation resistant characteristics of the DUPIC fuel cycle are assessed by applying the modified INPRO Methodology based on the developed evaluation metrics and acceptance criteria. The evaluation procedure and the metrics can be utilized as a reference for an evaluation of the proliferation resistance of a future innovative nuclear energy system.

• Proceedings of The Korean Society of Health Promotion Conference
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• 2007.11a
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• pp.66-67
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• 2007

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• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2548-2566
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• 2012

This paper derives two main end-to-end performance metrics, namely the spatial capacity density and the average end-to-end delay of the multi-hop wireless ad hoc networks with multi-antenna communications. Based on the closed-form expressions of these performance metrics, three hopping strategies, i.e., the closest neighbor, the furthest neighbor and the randomly selected neighbor hopping strategies have been investigated. This formulation provides insights into the relations among node density, diversity gains, number of hops and some other network design parameters which jointly determine network performances, and a method of choosing the best hopping strategy which can be formulated from a network design perspective.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.47-52
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• 2005

In this paper we describe SLA metrics and software architecture for newly upcoming IP TV service. Firstly we show the general description for IP TV. This consists of brief description of IP TV, the general figure of configuration and elements of IP TV network and communication protocol stack of IP TV data transmission for deriving communication quality parameter. And we propose SLA metrics depending on quality measurement point. According to the measurement point the measurable SLA metrics are different. The total view of the IP TV SLA measurement and management architecture is shown. When the quality measurement point is the routers that consist of internet node, the IP media NMS is the quality collection system. And when the quality measurement point is the IP TV STB(Set-Top Box), the IP media collector and Quality Collection Server are the quality collection system. And we show the software block diagram of IP TV SLA processing system and the other related network management systems.