• Journal of Wind Energy
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• v.9 no.4
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• pp.16-23
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• 2018

A damage detection method for the tripod support structure of offshore wind turbines is presented for structural health monitoring. A finite element model of a prototype tripod support structure is established and the modal properties are calculated. The degree and location of the damage are estimated based on the neural network technique using the changes of natural frequencies and mode shape due to the damage. The stress distribution occurring in the support structure is obtained by a dynamic analysis for the wind turbine system to select the output data of the neural network. The natural frequencies and mode shapes for 36 possible damage scenarios were used for the input data of the learned neural network for damage assessment. The estimated damages agreed reasonably well with the accurate ones. The presented method could be effectively applied for damage detection and structural health monitoring of various types of support structures of offshore wind turbines.

• Journal of Ocean Engineering and Technology
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• v.35 no.6
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• pp.426-433
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• 2021

In this study, three types of synthetic fiber materials were evaluated, namely, DM20, SK78, and T147, to replace steel chains in shipbuilding and offshore fields with fiber chains as there is increasing demand for chains with lighter weights and improved usabilities. The strength and quasi-static stiffness were analyzed to select suitable yarns for the fiber chains. The durability of the yarn was evaluated by performing a 3-T (time to rupture) test as a specific tension level. The results of the experiment revealed excellent dynamic stiffness in DM20 and highest values of the windward and leeward stiffness in T147. 3-T linear design characteristic curves for a specific tension level were derived for the three types of fiber materials. The findings of this study can provide insights for improving strength and durability in fiber chain design.

• Journal of Plant Biotechnology
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• v.2 no.2
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• pp.55-60
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• 2000

Experiments initiated 30 years ago to obtain selectable markers have led to a series of studies of Trp biosynthesis and anthranilate synthase (AS) the control enzyme using largely plant tissue cultures since they have experimental properties that can be readily exploited. Enzymological and compound feeding studies provided evidence that AS is the control point in the Trp biosynthesis branch and that altering the AS feedback control by the selection of mutants resistant to the Trp analog 5-methyl-tryptophan (5MT) can lead to the overproduction of this important amino acid. Plants regenerated from these Trp overproducing lines of most species also had high free Trp levels but Nicotiana tabaum (tobacco) plants expressed the feedback altered AS only in cultured cells and not in the regenerated plants. further tests by transient and stable expression of the cloned promoter for the naturally occurring tobacco feedback-insensitive AS, denoted ASA2, confirmed the tissue culture specific nature of the expression control. The 5MT caused by the expression of a feedback-insensitive AS from tobacco has been used to select protoplast fusion hybrids with several species since the resistance is expressed dominantly. Recently the ASA2 gene has been used successfully as a selectable marker to select transformed Astragalus sinicus and Glycine max hairy roots induced by Agrobactetium rhizogenes. These results show that the ASA2y-subunit can interact with the y-subunit of another species to form active feedback-insensitive enzyme that may be useful for selecting transformed cells. Plastid DNA transformation of tobacco has also effectively expressed ASA2 in the compartment in which Trp biosynthesis is localized in the cell.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.135-140
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• 2007

Feature selection is a preprocessing technique commonly used on high dimensional data. Feature selection studies how to select a subset or list of attributes that are used to construct models describing data. Feature selection methods attempt to explore data's intrinsic properties by employing statistics or information theory. The recent developments have involved approaches like correlation method, dimensionality reduction and mutual information technique. This feature selection have become the focus of much research in areas of applications with massive and complex data sets. In this paper, we provide a feature selection method considering data characteristics and generalization capability. It provides a computational approach for feature selection based on fuzzy cluster analysis of its attribute values and its performance measures. And we apply it to the system for classifying computer virus and compared with heuristic method using the contrast concept. Experimental result shows the proposed approach can give a feature ranking, select the features, and improve the system performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.560-568
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• 2012

Spectrum sensing and spectrum decision are the main functions that cognitive radios (CRs) have to perform in order to get the best available spectrum band for the establishment of a wireless communication. These problems are worsened in the presence of users with different demands and spectrum channels with different properties in a heterogeneous network. The primary objective in this work is to design and simulate a new spectrum decision algorithm for heterogeneous cognitive radio system. To this end, first, we consider all cognitive users are separated into different traffic classes according to their Quality of Service (QoS). The cognitive users within one traffic class perform spectrum sensing in centralized group-based cooperative spectrum sensing system and the users of different traffic classes share the sensing results. Second, we propose a novel use of the Analytic Hierarchy Process (AHP) to optimally select available bands according to user requirements and detected spectrum channel characteristics (SCC). In this paper, utility function is used as spectrum decision algorithm. Simulation results demonstrate that the proposed method shows can effectively select the best available spectrum channels with a low complexity.

• The Korean Journal of Food And Nutrition
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• v.31 no.2
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• pp.229-235
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• 2018

Ramie (Boehmeria nivea M.) has been used for fiber materials in Korea traditionally, but in recent years, the concern with ramie leaves for the food industry such as tteok (a kind of Korean rice cake) industry has been increasing, so a study for eatable ramie is required for the expansion of ramie consumption. Moreover, the ramie varieties for the food industry are not established, so the natural species are cultivated in general; therefore, it is very important to select the ramie varieties for the food industry such as rice cakes, tea, beverage and so on. This study was undertaken to compare the physiochemical properties among 9 ramie lines selected in the Yeonggwang-gun Agricultural Technology Center to select the eatable ramie varieties for the food industry. The contents of the protein among 9 ramie lines was 6.21~7.56% and had the highest content in the YG55. The folic acid (folate) and vitamin C content had varying differences among the 9 lines; the content of folate showed $771.52{\sim}1,978.84{\mu}g%$, that of vitamin C showed 149.42~275.34 mg%. The ACE inhibitory activity appeared to be the highest in YG88 (21.5%) among the 9 ramie varieties tested.

• Journal of Ocean Engineering and Technology
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• v.31 no.4
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• pp.308-314
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• 2017

The purpose of this study was to investigate the sea floor using a seismic profiler in the northern part of Chagwi-do of Jeju Island in order to select the optimal location for the 60-m-class berth of a sea test bed for wave energy converters and provide basic environmental data for designing a suction anchor. The echo types of the seismic profiles were classified based on the study of Kim et al. (2016a), and the location for installing the suction anchor was selected based on a sediment thickness of more than 10 m. The physical properties of the surface sediments were determined by analyzing the sediment samples obtained from 16 grab sample points. Based on the investigation and analysis, we proposed a survey area in the North-Eastern sea as an optimum location for the 60-m-class berth where the suction anchor could be installed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.754-758
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• 2005

Optimization of process variables such as arc current, welding voltage and welding speed in terms of the weld characteristics desired is the key step in achieving high quality and improving performance characteristics without increasing the cost. Consequently, incorrect settings of those process variables give rise to deviations in the welding characteristics from the desired bead geometry. Therefore, trainee welders are referred to the tabulated information relating different metal types and thickness as to recommend the desired values of process variables. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. However, it is difficult for the traditional identification methods to provide an accurate model because the optimized welding process is non-linear and time-dependent. In this paper, the possibilities of the Infra-red sensor in sensing and control of the bead geometry in the automated welding process are presented. Infra-red sensor is a well-known method to deal with the problems with a high degree of fuzziness so that the sensor is employed to build the relationship between process variables and the quality characteristic the proposed above respectively. Based on several neural networks, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. The developed system enables to select the optimal welding parameters and control the desired weld dimensions during arc welding process.

• Journal of Korean Academy of Nursing
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• v.45 no.6
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• pp.783-801
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• 2015

Purpose: The purpose of this study is to provide a comprehensive overview of the various measures available for assessment of oxaliplatin-induced peripheral neuropathy (OXLIPN) and to evaluate the measurement properties of each assessment tool. Methods: A systematic review was conducted to identify existing measures for OXLIPN found in the databases of PubMed, Cochrane Library, Embase, RISS and KoreaMed. The quality of the 24 identified tools was evaluated based on their properties of measurement including content validity, internal consistency, criterion validity, construct validity, reproducibility, responsiveness, floor-ceiling effects and interpretability. Results: Ten (41.7%) of the 24 tools were identified as specific measures for assessing OXLIPN and the most popular type of measures were clinical grading systems by clinicians (58.3%) and only 29.2% of measures were identified as patient reported outcomes. The most frequently used tool was National Cancer Institute-Common Toxicity Criteria (NCI-CTC), but the validity of NCI-CTC has not been reported appropriately. Overall, the Neuropathic Pain Symptom Inventory (NPSI) received the best psychometric scores, and the Chemotherapy-induced Peripheral Neuropathy Assessment Tool (CIPNAT) and Functional Assessment of Cancer Therapy/Gynaecologic Oncology Group-neurotoxicity-12 (FACT/GOG-Ntx-12) followed NPSI. Conclusion: To select appropriate measure, evidences should be accumulated through the clinical use of tools. Therefore, practitioner and researchers are urged to report relevant statistics required for the validation of the currently used measures for assessment of OXLIPN.

• Physical Therapy Korea
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• v.19 no.3
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• pp.124-131
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• 2012

Most conventional instruments measuring disability rely on total score by simply adding individual item responses, which is dependent on the items chosen to represent the underlying construct (test-dependent) and a test statistic, such as coefficient alpha for the estimate of reliability, varying from sample to sample (sample-dependent). By contrast, item response theory (IRT) method focuses on the psychometric properties of the test items instead of the instrument as a whole. By estimating probability that a respondent will select a particular rating for an item, item difficulty and person ability (or disability) can be placed on same linear continuum. These estimates are invariant regardless of the item used (test-free measurement) and the ability of sample applied (sample-free measurement). These advantages of IRT allow the creation of invariantly calibrated large item banks that precisely discriminate the disability levels of individuals. Computer adaptive testing (CAT) method often requiring a testing algorithm promise a means for administering items in a way that is both efficient and precise. This method permits selectively administering items that are closely matched to the ability level of individuals (measurement precision) and measuring the ability without the loss of precision provided by the full item bank (measurement efficiency). These measurement properties can reasonably be achieved using IRT and CAT method. This article aims to investigate comprehensive overview of the existing disability instrument for back pain and to inform physical therapists of an alternative innovative way overcoming the shortcomings of conventional disability instruments. An understanding of IRT and CAT method will equip physical therapist with skills in interpreting the measurement properties of disability instruments developed using the methods.