• Asian Pacific Journal of Cancer Prevention
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• v.17 no.7
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• pp.3123-3129
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• 2016

Background: Cancer is the fourth leading cause of death in Sabah Malaysia with a reported age-standardized incidence rate was 104.9 per 100,000 in 2007. The incidence rate depends on non-mandatory notification in the registry. Under-reporting will provide the false picture of cancer control program effectiveness. The present study was to evaluate the performance of the cancer registry system in terms of representativeness, data quality, simplicity, acceptability and timeliness and provision of recommendations for improvement. Materials and Methods: The evaluation was conducted among key informants in the National Cancer Registry (NCR) and reporting facilities from Feb-May 2012 and was based on US CDC guidelines. Representativeness was assessed by matching cancer case in the Health Information System (HIS) and state pathology records with those in NCR. Data quality was measured through case finding and re-abstracting of medical records by independent auditors. The re-abstracting portion comprised 15 data items. Self-administered questionnaires were used to assess simplicity and acceptability. Timeliness was measured from date of diagnosis to date of notification received and data dissemination. Results: Of 4613 cancer cases reported in HIS, 83.3% were matched with cancer registry. In the state pathology centre, 99.8% was notified to registry. Duplication of notification was 3%. Data completeness calculated for 104 samples was 63.4%. Registrars perceived simplicity in coding diagnosis as moderate. Notification process was moderately acceptable. Median duration of interval 1 was 5.7 months. Conclusions: The performances of registry's attributes are fairly positive in terms of simplicity, case reporting sensitivity, and predictive value positive. It is moderately acceptable, data completeness and inflexible. The usefulness of registry is the area of concern to achieve registry objectives. Timeliness of reporting is within international standard, whereas timeliness to data dissemination was longer up to 4 years. Integration between existing HIS and national registration department will improve data quality.

• Korean Journal of Radiology
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• v.23 no.5
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• pp.529-538
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• 2022

Objective: Since its introduction in 2011, the CT/MRI diagnostic Liver Imaging Reporting and Data System (LI-RADS) has been updated in 2014, 2017, and 2018. We evaluated the impact of CT/MRI diagnostic LI-RADS on liver MRI research methodology for the diagnosis of hepatocellular carcinoma (HCC). Materials and Methods: The MEDLINE, EMBASE, and Cochrane databases were searched for original articles reporting the diagnostic performance of liver MRI for HCC between 2011 and 2019. The MRI techniques, image analysis methods, and diagnostic criteria for HCC used in each study were investigated. The studies were classified into three groups according to the year of publication (2011-2013, 2014-2016, and 2017-2019). We compared the percentage of studies adopting MRI techniques recommended by LI-RADS, image analysis methods in accordance with the lexicon defined in LI-RADS, and diagnostic criteria endorsed by LI-RADS. We compared the pooled sensitivity and specificity between studies that used the LI-RADS and those that did not. Results: This systematic review included 179 studies. The percentages of studies using imaging techniques recommended by LI-RADS were 77.8% for 2011-2013, 85.7% for 2014-2016, and 84.2% for 2017-2019, with no significant difference (p = 0.951). After the introduction of LI-RADS, the percentages of studies following the LI-RADS lexicon were 0.0%, 18.4%, and 56.6% in the respective periods (p < 0.001), while the percentages of studies using the LI-RADS diagnostic imaging criteria were 0.0%, 22.9%, and 60.7%, respectively (p < 0.001). Studies that did not use the LI-RADS and those that used the LIRADS version 2018 showed no significant difference in sensitivity and specificity (86.3% vs. 77.7%, p = 0.102 and 91.4% vs. 89.9%, p = 0.770, respectively), with some difference in heterogeneity (I² = 94.3% vs. 86.7% in sensitivity and I² = 86.6% vs. 53.2% in specificity). Conclusion: LI-RADS imparted significant changes in the image analysis methods and diagnostic criteria used in liver MRI research for the diagnosis of HCC.

• Journal of Environmental Policy
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• v.13 no.1
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• pp.25-47
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• 2014

We examined the heterogeneity in the financial -environmental performance nexus, carrying out a meta-analysis of 48 outcomes from 26 empirical studies. Multiple correspondence analysis (MCA) was performed in this study to facilitate the analysis of the structural relationship among an array of study characteristics. As expected, the results of analyzing the multiple studies of the general corporate environmental performance and financial performance link suggested a significant positive relationship. Some of the results of the moderator analysis suggest that empirical studies using self-reporting measurement and structural equation method benefited from environmental performance as much as or more than the archival and regression method.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1121-1133
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• 2021

The paper examines the impacts of the various sustainability dimensions on the financial performance of commercial banks in three Arab countries. Three dimensions have been considered as constitutive of the term sustainable development (social, economic, and environmental). The relationship between the sustainability dimensions of companies and accounting indicators was analyzed. The main hypothesis posits that the dimensions of sustainability do not have a significant and positive effect on the financial performance of the commercial banks. The study population consisted of commercial banks operating in three Arab countries (Oman, United Arab Emirates, and Jordan); the period of the study is from 2007 to 2018. The data were collected from the financial reports and sustainability reports of each bank through the Internet. The overall results of the study showed a moderately positive relationship between all sustainability dimensions and the banks' financial performance. The main contribution of the research is to study the dimensions of sustainability reports as contained in the Global Reporting Initiative (GRI-G4) and their impacts on the financial performance of commercial banks. Thus, this research will contribute to increasing the interest of the banks in sustainable development in a context where this research in Arab countries is scarce.

• Korean Journal of Radiology
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• v.21 no.12
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• pp.1345-1354
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• 2020

Objective: To evaluate radiomics analysis in studies on mild cognitive impairment (MCI) and Alzheimer's disease (AD) using a radiomics quality score (RQS) system to establish a roadmap for further improvement in clinical use. Materials and Methods: PubMed MEDLINE and EMBASE were searched using the terms 'cognitive impairment' or 'Alzheimer' or 'dementia' and 'radiomic' or 'texture' or 'radiogenomic' for articles published until March 2020. From 258 articles, 26 relevant original research articles were selected. Two neuroradiologists assessed the quality of the methodology according to the RQS. Adherence rates for the following six key domains were evaluated: image protocol and reproducibility, feature reduction and validation, biologic/clinical utility, performance index, high level of evidence, and open science. Results: The hippocampus was the most frequently analyzed (46.2%) anatomical structure. Of the 26 studies, 16 (61.5%) used an open source database (14 from Alzheimer's Disease Neuroimaging Initiative and 2 from Open Access Series of Imaging Studies). The mean RQS was 3.6 out of 36 (9.9%), and the basic adherence rate was 27.6%. Only one study (3.8%) performed external validation. The adherence rate was relatively high for reporting the imaging protocol (96.2%), multiple segmentation (76.9%), discrimination statistics (69.2%), and open science and data (65.4%) but low for conducting test-retest analysis (7.7%) and biologic correlation (3.8%). None of the studies stated potential clinical utility, conducted a phantom study, performed cut-off analysis or calibration statistics, was a prospective study, or conducted cost-effectiveness analysis, resulting in a low level of evidence. Conclusion: The quality of radiomics reporting in MCI and AD studies is suboptimal. Validation is necessary using external dataset, and improvements need to be made to feature reproducibility, feature selection, clinical utility, model performance index, and pursuits of a higher level of evidence.

• Journal of Power System Engineering
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• v.16 no.1
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• pp.12-18
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• 2012

The fluid performance is one of the key design factors considered during the development of torque converters especially at conceptual design stages. Therefore the design environment that allows an easy access to legacy data of fluid performance could be critical to reduce the design life cycle as well as to increase the performance of the torque converter. In this paper we present a computer-based system that enables designers to utilize massive legacy data for their design of torque converters. For the implementation of the system we propose a standard format for the legacy data and build them into the database to be efficiently shared by designers in the company. Also we provide numerous analysis tools in the system that allow, for example, database management, data viewing and document generation for search, analysis and reporting. In the paper the implementation of the system is introduced in detail with its effective user interface.

• Smart Structures and Systems
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• v.26 no.5
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• pp.667-680
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• 2020

This study aims at reporting a systematic procedure for evaluating the static and dynamic structural performance of steel bridges based on a short-period structural health monitoring measurement. Sungsu bridge located in Korea is considered as a case study presenting the most recent tests carried out to examine the bridge condition. Short-period measurements of Structural Health Monitoring (SHM) system were used during the bridge testing phase. A novel symmetry index is introduced using statistical analyses of deflection and strain measurements. Frequency Domain Decomposition (FDD) is implemented to the strain measurements to estimate the bridge mode shapes and damping ratios. Furthermore, Markov Chain Monte Carlo (MCMC) is also implemented to examine the reliability of bridge performance while ambient design trucks are in static or moving at different speeds. Strain, displacement and acceleration were measured at selected locations on the bridge. The results show that the symmetry index can be an efficient and useful measure in assessing the steel bridge performance. The results from the used method reveal that the performance of the Sungsu bridge is safe under operational conditions.

• The Journal of Industrial Distribution & Business
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• v.13 no.8
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• pp.19-27
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• 2022

Purpose: CEOs develop policies through their effective decision-making while employees implement the policies so that a business realizes the expected returns. This research focuses on the importance of the CEO's sustainable leadership to distribute environmental education culture to improve employees' environmental performance. Research design, data and methodology: The PRISMA that is selected by the present research is an evidence-based minimum group of entities for reporting in systematic reviews and meta-analyses. The core focus of the concept is to note studies that evaluate the impacts of intervention and can also be utilized as a basis for writing systematic reviews rather than intervention evaluations. Results: The current investigation indicates that there are four kinds of suggestions (a. Increased organizational learning, b. Open communication, c. Participative decision making, d. Psychological empowerment) how the management should develop sustainable leadership for distributing green culture and improving employee green performance. Conclusions: Based on four solutions, the present research concludes that sustainable leadership for CEOs is not only of advantage in terms of protecting the environment and the people, but it fosters increased organizational learning. Increased organizational learning leads to better employee sustainable performance, which includes financial performance and the social and environmental initiatives the organization implements.

• Journal of Korean Society for Quality Management
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• v.31 no.4
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• pp.1-18
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• 2003

Quality is a critical competitive factor in today's environment because of the impact of quality on costs and delivery. Many companies regard quality as a key concept of company strategy in order to achieve the competitive edge. Measuring and reporting quality cost is the first step in quality management program. The supposition of quality cost model is that investment in prevention activities will bring rewards from reduced failure costs, and that further investment in prevention activities will show profits from reduced appraisal costs. In this study, the degree of quality cost deviation is conceptualized. This means a deviation between the ideal and present ranking in the amounts of quality cost categories. This study analysed that the effect of its deviation on quality management activity and performance variables. However, there are no difference in these variables. The major reason is that most of companies are endeavoring for quality management but operating quality cost system unsystematically. The review against a prevention and appraisal activity is necessary.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1244-1253
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• 2018

The color of traffic light is sensitive to various illumination conditions. Especially it loses the hue information when oversaturation happens on the lighting area. This paper proposes a traffic light recognition method robust to these illumination variations. The method consists of two steps of traffic light detection and recognition. It just uses the intensity and saturation in the first step of traffic light detection. It delays the use of hue information until it reaches to the second step of recognizing the signal of traffic light. We utilized a deep learning technique in the second step. We designed a deep convolutional neural network(DCNN) which is composed of three convolutional networks and two fully connected networks. 12 video clips were used to evaluate the performance of the proposed method. Experimental results show the performance of traffic light detection reporting the precision of 93.9%, the recall of 91.6%, and the recognition accuracy of 89.4%. Considering that the maximum distance between the camera and traffic lights is 70m, the results shows that the proposed method is effective.