• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.9-16
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• 2013

Objective: The aim of this study is to investigate a trend of human error types observed in a series of verification and validation experiments for an Advanced Control Room(ACR) equipped with Lager Display Panel(LDP), Work Station Flat Panel Display(WS FPD), list type Alarm System(AS), Soft Control(SC) and Computerized Procedure System(CPS). Background: Operator behaviors in a fully computerized control room are quite different from those in a traditional hard-wired control room. Operators in an ACR all together monitor plant status and variables through their own interface system such as LDP and WS FPD, are notified of abnormal plant status through their own list type AS, control the plant through their own SC, and follow the structured procedure through their own CPS whereas operators in a traditional control room only separately do their duty directed by their supervisor. Especially the secondary task such as manipulating the user interface of ACR can be an extra burden to all the operators including the supervisor. Method: The Reason's human error classification method was applied to operators' behavioral data collected from a series of verification and validation experiments where operators showed their plant operational behaviors under a couple of harsh scenarios using the ACR simulator. Results: As operators accustomed to the new ACR system, knowledge or rule based mistakes appearing frequently in the early series of experiments decreased drastically in the latest stage of the series. Slip and lapse types of errors were observed throughout the series of experiments. Conclusion: Education and training can be one of the most important factors for the operators accustomed to the traditional control room to be adapted to the new system and to run the ACR successfully. Application: The results of this study implied that knowledge or rule based mistakes can be reduced by training and education but that lapse type errors might be reduced only through innovative improvement in human-system interface design or teamwork culture design including a new leadership style suitable for ACR.

• Journal of the Korean Society of Safety
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• v.24 no.4
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• pp.90-95
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• 2009

The purpose of this study is to investigate industrial safety and health experts' opinions on the examination system of WMSDs(work related musculoskeletal disorders) risk factors. For doing this, a questionnaire study and two FGIs(focused group interview) were conducted. A questionnaire with open questions about the examination system was developed, and sent to 42 experts consented bye-mail. Of the experts, 24 experts responded, whose data were used in the analysis. The FGIs were performed for the persons in charge of industrial safety and health in industries and ergonomists. The questionnaire study revealed that most experts(91.3%) agreed with legalization of employers' duty for preventing WMSDs, necessity of the 11 tasks designated by Ministry of Labor, the examination system and ergonomics program, and pertinency for the examination system classification of periodic and occasional one. However, more than half experts disagreed with timeliness and appropriateness of the legal system. This was validated by the low approval rates for appropriateness of the 11 tasks, methods of the examination, charge person in the examination and ergonomics program. FGIs showed that it was desirable for the examination system to be legalized, and that the system was generally properly performed. It was suggested that the system be partially revised with reflecting problems disclosed during its enforcement rather than whole revision. It is expected that when revising relevant legal system, the results of this study would be used as valuable data.

• Journal of the Korean Society for Library and Information Science
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• v.7
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• pp.3-67
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• 1980

Because of the changes made in the modes of cataloguing and classification in its long history, the present catalogue of the National Central Library has become complicated and provides an inadequate guide to its collection. There can be no doubt that this is a serious deficiency in a closed access library since materials housed in the library are virtually inaccessible to unskilled readers. The whole breakdown of the efficiency of the catalogue is emminent and will ultimately create the most serious problems for the library. The main purpose of this survey is: (a) to identify problem areas created by the frequent changes in the cataloguing and classifying principles in the library and (b) to grope a rational direction for the future development. Analysing the various classification schemes and cataloguing rules adopted in processing materials (mainly books) in the library, the following conclusions have been made. A. The library adopted five different clasification schemes in different periods, of which KDCP was used for the most part of its collection. KDCP is recommended to use for the future colletion. A classification development office is recommended to be established within the library, of which the main function is to revise the KDCP in collaboration with the appropriate committee of the Korean Library Association. B. The present practice in the library is to apply three different cataloguing rules and two different author notation tables to the Oriental, classical, and Western collections. Efforts should be made to find out an efficient system so that this variety is simplified. An alphabetical index should be added to the classified catalogue, and improvements are required in the Japanese collection. C. The technical services division is inadequately staffed. The staff should be sufficiently numerous and specially qualified. D. The present financial support for the technical services of the library is inadequate. Sufficient financial provision should be made to ensure the effective work. E. A feasibility study should be carried out to develop a computer processing system for providing machine-readable catalogue records on magnetic tape for use by the library community in Korea.

• Journal of Energy Engineering
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• v.20 no.3
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• pp.200-208
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• 2011

KHNP (Korea Hydro & Nuclear Power Co.) defines and manages equipment of Nuclear Power Plants systematically with functional importance determination of each equipment for efficient maintenance and optimal preventive maintenance. But the existing functional importance determinations have some different results between the plants, systems and engineers due to gap of understanding of classification criteria because they have been done in terms of equipment level rather than function level. so that caused the repeated work. To make up for this problem improve methodology of functional importance determination using MR (Maintenance Rule) and do classification of equipment for new nuclear power plants based on function level. In addition, methodical documentation for basis of importance determination is done to help that system engineers can easily understand and use.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2168-2187
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• 2021

The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.8-16
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• 2024

Communication with the deaf has always been crucial. Deaf and hard-of-hearing persons can now express their thoughts and opinions to teachers through sign language, which has become a universal language and a very effective tool. This helps to improve their education. This facilitates and simplifies the referral procedure between them and the teachers. There are various bodily movements used in sign language, including those of arms, legs, and face. Pure expressiveness, proximity, and shared interests are examples of nonverbal physical communication that is distinct from gestures that convey a particular message. The meanings of gestures vary depending on your social or cultural background and are quite unique. Sign language prediction recognition is a highly popular and Research is ongoing in this area, and the SVM has shown value. Research in a number of fields where SVMs struggle has encouraged the development of numerous applications, such as SVM for enormous data sets, SVM for multi-classification, and SVM for unbalanced data sets.Without a precise diagnosis of the signs, right control measures cannot be applied when they are needed. One of the methods that is frequently utilized for the identification and categorization of sign languages is image processing. African Buffalo Optimization using Support Vector Machine (ABO+SVM) classification technology is used in this work to help identify and categorize peoples' sign languages. Segmentation by K-means clustering is used to first identify the sign region, after which color and texture features are extracted. The accuracy, sensitivity, Precision, specificity, and F1-score of the proposed system African Buffalo Optimization using Support Vector Machine (ABOSVM) are validated against the existing classifiers SVM, CNN, and PSO+ANN.

• Journal of KIISE:Software and Applications
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• v.29 no.12
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• pp.966-978
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• 2002

There are two important problems in improving text classification systems based on machine learning approach. The first one, called "selection problem", is how to select a minimum number of informative documents from a given document collection. The second one, called "composition problem", is how to reorganize selected training documents so that they can fit an adopted learning method. The former problem is addressed in "active learning" algorithms, and the latter is discussed in "boosting" algorithms. This paper proposes a new learning method, called AdaBUS, which proactively solves the above problems in the context of Naive Bayes classification systems. The proposed method constructs more accurate classification hypothesis by increasing the valiance in "weak" hypotheses that determine the final classification hypothesis. Consequently, the proposed algorithm yields perturbation effect makes the boosting algorithm work properly. Through the empirical experiment using the Routers-21578 document collection, we show that the AdaBUS algorithm more significantly improves the Naive Bayes-based classification system than other conventional learning methodson system than other conventional learning methods

• KIEAE Journal
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• v.12 no.6
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• pp.77-84
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• 2012

The current architectural design of unit modular has been based on 2D of CAD program, so unit modular character which needs unit information management, as a dried-member system, has no effect on design process. The purpose of this study is We have developed a suitable BIM design process, according to various works of construction, then tried to contribute to supply and activation of the urban-life-housing based on unit modular. The BIM modeling process based on unit modular has been in order of unit combination with preparing manual classification, and, it has been constructed, at construction site, from housing foundation to roof finish by Bottom-up method. At a manufacturing factory, it has been produced in order of 1) grouping materials and parts, 2) fabricating unit boxes, and 3) interference examination of unit boxes, and each order has been classified as housing structure, architecture, plumbing process separately. At a construction site, the fabrication has been done in order of, like as a real housing construction scenario, 1) RC foundation work 2) unit module job-site-fabrication work, 3) roof truss work, 4) plumbing and HVAC work, and 5) housing interior finish work. After modeling process, the interference examination on each work of construction has finally completed modeling. The Unit modular utilizing BIM modeling can make easy housing maintenance through systematic control with preparing manual of unit module information, and securing accurate and speedy construction information. And it will promote design credibility and create maximum effect of unit modular construction method, such as construction period reduction and upgrade of construction quality, etc., through the computer simulation as real as construction environment in cyber space, and with the interfering examination.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.158-168
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• 2024

There is hardly any person in modern times who has not taken soft drinks instead of drinking water. The rate of people taking soft drinks being surprisingly high, researchers around the world have cautioned from time to time that these drinks lead to weight gain, raise the risk of non-communicable diseases and so on. Therefore, in this work an image-based tool is developed to monitor the nutritional information of soft drinks by using deep convolutional neural network with transfer learning. At first, visual saliency, mean shift segmentation, thresholding and noise reduction technique, collectively known as 'pre-processing' are adopted to extract the location of drinks region. After removing backgrounds and segment out only the desired area from image, we impose Discrete Wavelength Transform (DWT) based resolution enhancement technique is applied to improve the quality of image. After that, transfer learning model is employed for the classification of drinks. Finally, nutrition value of each drink is estimated using Bag-of-Feature (BoF) based classification and Euclidean distance-based ratio calculation technique. To achieve this, a dataset is built with ten most consumed soft drinks in Bangladesh. These images were collected from imageNet dataset as well as internet and proposed method confirms that it has the ability to detect and recognize different types of drinks with an accuracy of 98.51%.

• Research in Community and Public Health Nursing
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• v.11 no.1
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• pp.67-79
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• 2000

In recent years, the recipients of the services of the health centers in Korea have been shifted from individual sick persons to families as a unit. As a result, the home visiting care records which are all filled out manually, will be increased. Since there is virtually no increase in the number of community health nurses, the CHNs are required to work more efficiently. One of the ways to make the CHNs' work more efficient is to reduce recording time by using a computer. However, a computer system that can manage the families as a unit has not yet been developed. In response to this need, we developed a database system that can be utilized in home visiting care service. The family assessment data is collected. diagnosed. and evaluated according to the family diagnosis classification. The system for family diagnosis consists of seven areas. Those areas are family structure. maintenance of the family system, interaction and interchange. support. coping and adaptation, health management. and housing environment. The areas of the family diagnosis consists of 99 items in all. We expect the following from this system. First. the CHNs will be able to identify family problems more easily. Second. the community's health level can be confirmed by the statistics the system produces. Thirdly, the CHNs' nursing services will be cost effective via reduced recording time. Finally, the family problems of the sick individuals which have been neglected under the health system oriented on individual persons can be effectively managed.