• Journal of Korean Academy of Nursing
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• v.22 no.4
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• pp.620-635
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• 1992

This study identified correlations between perceived family support and hopelessness in patients admitted to Neuro - surgical Intensive Care Units. The purpose was to enhance theoretical understanding of the relationships of these two variables. The subjects of this study were 51 patients admitted to N-lCU, at three general hospitals in Seoul. Data were collected by researcher in structured interviews from Aug. 12 to Oct. 13, 1992. The research tools were parts of the Moos Family Environment Scale and the Beck Hopelessness Scale. The general characteristic data were analyzed for frequency and percentage ; the hypothesis was tested by the pearson product Moment Correlation Coefficient. After normality tests by using Kolmogorov - Sminorvtest, and T- test, ANOVA and Mann-Whitney U test, Kruskal -Wallis test were used on the Family Support and the Hopelessness about general charcteristics. The results of the above analysis were as follows 1) The average family support score for the group was 63.61 (tool average 51) and item average was 3.74 (tool item average 3) : the family support score of this sample was higher than average. The average family cohesion score of family support was 35.25 (tool average 27) and item average was 3.91 (tool item average 3). The average family expression score of family support was 28.35 (tool average 24) and item average was 3.57 (tool average 3). In this sample, perceived family expression was lower than family cohesion. 2) The average hopelessness score was 45.88 (tool average 60) and item average was 2.29 (tool item average 3) : the hopelessness score of this sample was low in comparison to the average. 3) The hypothesis in this study was supported. The main hypothesis that the higher the perceived family support level, the lower the level Of the hopelessness, was Supported (r＝-.3869 p＝.003). The sub-hypothesis that the higher the perceived family cohesion level, the lower the level of hopelessness, was supported(r＝-.3688 p＝.004). The sub-hypothesis that the higher the perceived family expression level, the lower the level of hopelessness, was supported (r＝-.3068 p＝.014). 4) General characteristics of the objects related to family support were ‘economic status’(p＝.025) and ‘helping person’(P＝.044) : the higher the economic status, the greater the family support. When the patient identified the helping person as a spouse, family support was rated more highly. The only general characteristic related to family cohesion was ‘helping person’(p＝.041). No general characteristics were related to family expression. 5) The one general characteristic related to hopelessness was ‘education’(p＝.002) : the higher their education, the lower their hopelessness. For these ICU patients, were related perceived family support and hopelessness, and family expression level was low in comparison to family cohesion level. The perceived family support of these seriously ill patients in situational crisis may have influenced the patient's emotional reaction of hopelessness. This study concluded that nurses in the ICU confirm the family support of the patient, and involve the family as the most intimate support systems in the care of the patient to help reduce the patient's hopelessness.

• Journal of Advanced Marine Engineering and Technology
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• v.19 no.4
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• pp.72-78
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• 1995

The diffusion of fuzzy logic techniques into real applications requires specific software supports which save development time and reduce the programming effort. But we has been lack of a tool devoted to support the design of fuzzy controllers. In this paper, on the basis of the general fuzzy set and .alpha.-cut set decomposition of fuzzy sets, a set of fuzzy reasoning tool(FRT) devoted to support the design of fuzzy dontroller for servo systems is developed. The major features of this tool are: 1) It supports users to analyze fuzzy ingerence status based on input deta and expected results by three-D graphic display. 2) It supports users to prepare input data and expected result. 3) It supports users to tuned scaling factor of membership functions, rules and fuzzy inference. The paper shows how the suggested design tools are suitable to give a consistent answer to the tuning of fuzzy control system. This FRT is expected to exert good performance and devoted to support which the design of fuzzy controller is illustrated in the servo systems.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.370-376
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• 2005

This paper is described the program algorithm which can easily estimate dynamics of test support system by using mathematica tool based on the finite element method. We can determine the geometry, dimensions of the test support system, through tool stated in this paper for a certain test conditions. As a result of computer simulation and manufactured test support system's experiment in oder to verify suggested program, the dynamics of the test support system was well correspondent each other.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.208-216
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• 2020

With the spread of smart manufacturing, one of the key topics of the 4th industrial revolution, manufacturing systems are moving beyond automation to smartization using artificial intelligence. In particular, in the existing automatic machining, a number of machining defects and non-processing occur due to tool damage or severe wear, resulting in a decrease in productivity and an increase in quality defect rates. Therefore, it is important to measure and predict tool life. In this paper, ν-ASVR (ν-Asymmetric Support Vector Regression), which considers the asymmetry of ⲉ-tube and the asymmetry of penalties for data out of ⲉ-tube, was proposed and applied to the tool wear prediction problem. In the case of tool wear, if the predicted value of the tool wear amount is smaller than the actual value (under-estimation), product failure may occur due to tool damage or wear. Therefore, it can be said that ν-ASVR is suitable because it is necessary to overestimate. It is shown that even when adjusting the asymmetry of ⲉ-tube and the asymmetry of penalties for data out of ⲉ-tube, the ratio of the number of data belonging to ⲉ-tube can be adjusted with ν. Experiments are performed to compare the accuracy of various kernel functions such as linear, polynomial. RBF (radialbasis function), sigmoid, The best result isthe use of the RBF kernel in all cases

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.117-124
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• 2021

The development of IOT technology and artificial intelligence technology is promoting the smartization of manufacturing system. In this study, data extracted from acceleration sensor and current sensor were obtained through experiments in the cutting process of SKD11, which is widely used as a material for special mold steel, and the amount of tool wear and product surface roughness were measured. SVR (Support Vector Regression) is applied to predict the roughness of the product surface in real time using the obtained data. SVR, a machine learning technique, is widely used for linear and non-linear prediction using the concept of kernel. In particular, by applying GSVQR (Generalized Support Vector Quantile Regression), overestimation, underestimation, and neutral estimation of product surface roughness are performed and compared. Furthermore, surface roughness is predicted using the linear kernel and the RBF kernel. In terms of accuracy, the results of the RBF kernel are better than those of the linear kernel. Since it is difficult to predict the amount of tool wear in real time, the product surface roughness is predicted with acceleration and current data excluding the amount of tool wear. In terms of accuracy, the results of excluding the amount of tool wear were not significantly different from those including the amount of tool wear.

• Journal of Korea Technology Innovation Society
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• v.20 no.1
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• pp.81-102
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• 2017

Financing, manpower support and tax are the most popular tools for policy for small and medium enterprises (SMEs). This paper, however, will introduce information analysis support for SMEs and will prove that can be a good tool. The information analysis support means the support of technology and market information for the technology development or commercialization of SMEs. Therefore, the support is a customized one. In the theory domain, we adopt and prove two theoretical grounds as an SMEs policy such as market and system failure. In the policy tool domain, we suggest four requirements to be an SMEs policy and prove the tool to satisfy these requirements. All the data and proofs are from a government research institute called K.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.90-96
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• 2021

As real-time data of factories can be collected using various sensors, the adaptation of intelligent unmanned processing systems is spreading via the establishment of smart factories. In intelligent unmanned processing systems, data are collected in real time using sensors. The equipment is controlled by predicting future situations using the collected data. Particularly, a technology for the prediction of tool wear and for determining the exact timing of tool replacement is needed to prevent defected or unprocessed products due to tool breakage or tool wear. Directly measuring the tool wear in real time is difficult during the cutting process in milling. Therefore, tool wear should be predicted indirectly by analyzing the cutting load of the main spindle, current, vibration, noise, etc. In this study, data from the current and acceleration sensors; displacement data along the X, Y, and Z axes; tool wear value, and shape change data observed using Newroview were collected from the high-speed, two-edge, flat-end mill machining process of SKD11 steel. The support vector machine technique (machine learning technique) was applied to predict the amount of tool wear using the aforementioned data. Additionally, the prediction accuracies of all kernels were compared.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.721-732
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• 1995

The IPSE(Integrated Project Support Environment) tool can be seen as a result of an attempt to synthesize the key aspects of language-centered, specific methodology-based and toolkit oriented environments, which are current CASE tools into an organic whole. The IPSE approach based on a process model is regarded as an effective way to implement integrated CASE. The PM-CASE(Process Model based CASE) tool is currently a prototype which draw diagrams describing processes by using a new modeling technique. Attributes related with a task of withen the process model should be defined an saved the database. These attributed are used to retrieve the information of products, and to call the tool related which the task. In this paper, TSEE(Process centered Software Engineering Environment) tools are compared and analyzed. By describing the basic concept, architecture and design of PM-CASE tool, a method of building an process model-based CASE tool is proposed be support an effect software development and management.

• Proceedings of the CALSEC Conference
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• 1999.07b
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• pp.607-614
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• 1999

In this paper, we demonstrate the implementation case using component based development tool under development process for application developments. The tool suggested provides the programming environment for the development of distributed manufacturing applications primarily. The development tool is classified into visual component, logic component, data component, knowledge component, neural net component, and service component which is a core component for the support component edit and execution. We applied the tool to the domain of the design and routing plan to retrieve existing similar design models in database, initiate a model, generate a process plan, and store the new model in the database automatically. Utilizing the tool, it integrates a geometric modeler, engineering/manufacturing database, and knowledge sources over the Internet.

• Journal of Construction Engineering and Project Management
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• v.8 no.1
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• pp.22-30
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• 2018

Achieving sustainability targets on construction projects has increasingly become one of the prime strategies for construction organizations. To provide more detailed guidance on sustainability implementation on projects, Construction Industry Institute (CII) Research Team (RT) 304 developed a catalog of the Construction Phase Sustainability Actions (CPSAs). The primary objective of this paper was the development of two support tools, the CPSA Screening Tool and the CPSA Implementation Index, that could be used to enable efficient application of CPSAs, support sustainability-related decisions, and measure CPSA implementation and performance. The authors developed the tools in four stages: conceptual, detailed planning, tool programming, and testing. The tools were then demonstrated on a capital project to confirm their efficacy and applicability. This paper presents the background, inputs and outputs, and the algorithms of each tool. The CPSA Screening Tool can prioritize the CPSAs most relevant to a project; the CPSA Implementation Index enables continuous monitoring of implementation levels.