• Archives of Plastic Surgery
• /
• 제51권2호
• /
• pp.169-181
• /
• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권5호
• /
• pp.2245-2266
• /
• 2016

The hop count routing metric is widely used in routing protocols of Wireless Sensor Networks (WSNs) due to its simplicity and effectiveness. With a lower hop count route, fewer transmissions are required to send a packet from the source to the destination. This can improve the throughput of a network because fewer transmissions results in less channel contention and interference. Despite this, the hop count routing metric may not be ideal for mobile scenarios where the topology of a network changes constantly and rapidly. In this paper, we propose to increase route stability in mobile WSNs by discovering paths that are more stable during route discoveries using routing metrics. Two routing metrics were proposed, the true beauty of these routing metrics lies in the fact that they can even be used even without specialized hardware such as GPS and other sensors. We implemented the proposed routing metrics in the AODV routing protocol and found that they are highly effective and outperform other stability-based routing metrics and the hop count routing metric.

• 한국비블리아학회지
• /
• 제14권1호
• /
• pp.79-90
• /
• 2003

• 한국전자거래학회지
• /
• 제6권2호
• /
• pp.73-85
• /
• 2001

Usability is defined by the effectiveness, efficiency and satisfaction with which specified users can achieve specified goal in particular environment. Today, many factors such as software acquisition, business re-engineering and the trend of software market have software industry considers usability as an important quality of software products. Therefore, the specification and measurement method for establishing the acceptable usability level of software is required during software development acquisition and evaluation. To evaluate whether software products is usable or not, we need evaluation method for software usability. This paper is not only to provide a framework for specifying the usability attributes of a product and establishing a comprehensive set of usability criteria, but also assessing usability metrics of the software. The usability metrics and checklist is developed based on the properties of the user interface using ISO standard and general usability principles with product-oriented view which means the Product has attributes contributing to determine the usability. This paper also suggested the way to weight the relative importance of the individual usability item depending on the software categories.

• 국제학술발표논문집
• /
• The 3th International Conference on Construction Engineering and Project Management
• /
• pp.302-309
• /
• 2009

The effectiveness of Building Information Modeling (BIM) tools and processes has been recognized by the industry and owners are beginning to adopt Triple Bottom Line accounting practices, to enhance economic performance and environmental and social performance. However, the widespread and practical application of Green BIM remains largely unrealized. The authors identify that lack of understanding of the applicability of sustainability metrics to BIM design process is a significant barrier to this adoption. Through literature review this paper outlines the various sustainability metrics available to construction and elaborates on the potential of BIM for sustainable design. The paper maps and correlates applicable concepts of sustainability evaluation systems to BIM and describes the constraints in current BIM tools.

• 한국정보과학회논문지:데이타베이스
• /
• 제34권5호
• /
• pp.437-447
• /
• 2007

다양한 유사도 측정 방법들이 웹 문서의 변경도 측정에 사용되어 왔다. 본 논문은 여섯 가지 웹 문서 변경 종류에 근거하여 변경도 측정 방법의 효과성 평가 척도를 정의하고, 새로운 유사도 측정 방법을 제안한다. 실제 웹 문서들과 인위적 문서들을 사용하여, 기존의 다섯 가지 측정 방법들(바이트 비교, TF IDF 코사인 거리, 단어 거리, 편집 거리, 슁글링)과 제안된 측정 방법을 비교 평가한다. 실험 결과 분석을 통해 제안된 측정 방법이 웹 문서의 변경 측정에 효과적임을 보인다. 본 연구는 웹 문서의 변화 정보를 필요로 하는 웹 응용 분야에서 웹 문서 변경도 측정 방법의 적합한 선택을 위한 지침이 될 수 있다.

• 한국군사과학기술학회지
• /
• 제15권5호
• /
• pp.643-650
• /
• 2012

This paper presents quantitative method of static combat effectiveness to classify fighter aircraft generations. We have analyzed performance metrics of United States(US), United Kingdom(UK), Russia, France, Sweden' fighters to determine jet-fighter generation. Both nominal and continuous variables were defined and used to present current trend of combat effectiveness.

• 산업경영시스템학회지
• /
• 제38권3호
• /
• pp.159-168
• /
• 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.

• International Journal of Computer Science & Network Security
• /
• 제23권11호
• /
• pp.21-31
• /
• 2023

In this paper, we focused on the problem of evaluating multi-class classification accuracy and simulation of multiple classifier performance metrics. Multi-class classifiers for sentiment analysis involved many challenges, whereas previous research narrowed to the binary classification model since it provides higher accuracy when dealing with text data. Thus, we take inspiration from the non-linear Support Vector Machine to modify the algorithm by embedding dynamic hyperplanes representing multiple class labels. Then we analyzed the performance of multi-class classifiers using macro-accuracy, micro-accuracy and several other metrics to justify the significance of our algorithm enhancement. Furthermore, we hybridized Enhanced Convolution Neural Network (ECNN) with Dynamic Support Vector Machine (DSVM) to demonstrate the effectiveness and efficiency of the classifier towards multi-class text data. We performed experiments on three hybrid classifiers, which are ECNN with Binary SVM (ECNN-BSVM), and ECNN with linear Multi-Class SVM (ECNN-MCSVM) and our proposed algorithm (ECNNDSVM). Comparative experiments of hybrid algorithms yielded 85.12 % for single metric accuracy; 86.95 % for multiple metrics on average. As for our modified algorithm of the ECNN-DSVM classifier, we reached 98.29 % micro-accuracy results with an f-score value of 98 % at most. For the future direction of this research, we are aiming for hyperplane optimization analysis.

• 한국컴퓨터정보학회논문지
• /
• 제21권8호
• /
• pp.65-75
• /
• 2016

In this paper, we present a novel approach to help MSR researchers obtain necessary data with a tool, termed General Purpose Extractor for Source code (GPES). GPES has a single function extracts high-quality data, e.g., the version history, abstract syntax tree (AST), changed code diff, and software quality metrics. Moreover, features such as an AST of other languages or new software metrics can be extended easily given that GPES has a flexible data model and a component-based design. We conducted several case studies to evaluate the usefulness and effectiveness of our tool. Case studies show that researchers can reduce the overall cost of data analysis by transforming the data into the required formats.