• Journal of Korean Academy of Nursing
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• v.11 no.2
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• pp.55-68
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• 1981

The prime object of the study is to evaluate how much all the students of the Nursing Schools throughout the nation are in comprehension toward the application of nursing process to clinical experience as means of systematic solution of nursing problems. An effort has been made to find out the actual state whether they are in practice of clinical experience in accordance with application of nursing process, over the period of four weeks managing from December 1st to 28th, 1980 and centering on 36 nursing schools, and meanwhile and evaluation, employing the assessment tool used by Bertuccietal, has been made on the nursing process notes recorded by 200 senions out of 21 nursing schools where application of nursing process to clinical experience being in practice. The assessment tool is composed of 5 different criteria in view of patient nursing and authors made an attempt to find out the result of clinical experience on application students in accordance with 5 different scoring criteria and further evaluating all the findings thereof. The findings were disposed of accordance with practice duration and criteria of the specific sudents subject to this finding as to verify the scoring difference in significance and of which the results are as follows: 1) as of now, in 21 (58.2%) out of 36 nursing Schools nursing process in being appliced in clinical experience. 2) Schools that started the application of nursing process to clinical experience amount to - for more than 4 yrs -6 (28.6％) - for 2 to 3 yrs-11s(52.4％) - for 1 yr -4 (19.0％) 3) As for the response upon application of nursing process. To clinical etperience, the largest voice (61.9%) heard was that it is rather difficult beyond the lecturing thereof, to practically apply it outs patients and the second voice (19.1%) turned out to be that it is hard to put in practice owing to uninformed nurses of the process serving in the clinical field. 4) The response. Of the processors assigned to instruction as to the most difficult problem in criteria of nursing process, the largest voice (38.2%) centered on the problem assessment while the second voice (17.7%) on the indirect nursing activity and the objective data respectively and considered to be the easiest was the indirect nursing activity (11.7%). 5) In order for a satisfactory. application of nursing process to clinical experience hence-forth, it has been pointed out that sufficient number of nurses should be supplemented in clinical field (44.1%) and at the same time supplementory education (35.3%) centered around professors be necessary. 6) Of the criteria that record result of nursing process, a significant difference in comprehension of subjective and objective data has been revealed according to the degree of the practice duration of application to clinical experience. For instance, while although poor it may seen, only 74.9% in subjective data and 71.1% in objective data represent the student group in practice for more than 4 years and only 56.3% in subjective data and 66.8% in objective data represent the student group in practice for 2 to 3 years but they still surpass in comprehension over the student group in practice for 1 year attaning only 19.6% in subjective data and 16.8% in objective data (P < 0.005). 7) As for problem assessment, the student group who started application of nursing process for 4 years stand for 37,7% the group for 2 to 3 years started for 25.3% and the group for 1 year started for 5.4%, revealing no significant difference according to duration (P < 0.5) and as poor as to indicate only 22.8% on an overage is in comprehension. 8) On direct and indirect nursing activity, the student group of for more than 4 years in appling nursing process (representing 49.5% in direct nursing activity, 21.4% in indirect nursing activity). Know more about it than the student group of for 2 to 3 years (representing 36.3% in direct nursing activity, 20.8% in indirect nursing activity) but revealed no significant difference. (P ＜ 0.5) 9) The student group applying nursing process for more than 4 years subjective data (74.9%) comprehend were more than objective data (71.1%) but shown no significant difference (P < 0.5). 10) However, the student group applying nursing process for 2 to 3 years comprehend objective data (66.8%) well ever subjective data (55.5%) indicating that 40.9% in average is in comprehension, thereby revealing a significant difference (P < 0.005). 11) On the other hand, the student group applying nursing process to clinical experience for 1 year had revealed themselves as poorly as to comprehend only 11.7% are an average of it, revealing no significant difference (P < 0.5). In consequence of the fore going, I the conductor of the present study, hereby suggest the following points: 1) Application of nursing process to clinical experience be practiced in all the Nursing Schools all over the nation at the earliest possible date in order that scientific nursing be prevailed (as of now only 58.0%), 2) In teaching nursing process, it is desirable to teach specific method of applying to practical clinical situations. 3) In order to meet the end of satisfactory application of nursing process to clinical experience, sufgecient nursing man power be sysplemented in clinical field and at the save time supplementary education by professors is necessary. 4) Sinces the students whose application duration of nursing process to clinical experience is longer comprehend more about it, it is reguired that the schools not yet in practice of the application be promptlyurged to follow. 5) Of the criteria recording nursing process, since it is comparatively hard to comprehend“assessment”and“Direct and indirect nursing activity”, a concentrated instruction is desirable. 6) The students whose duration of application of nursing process to clinical experience falls short of 1 years be put in a concentrated guidance program on individual criterion.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.457-469
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• 2007

Process Capability Indexes(PCI) are used as the measure for evaluation of process capability analysis and is the statistical method for efficient process control. The fourth generation $PCI(C_{psk})$ is constructed from $C_{pmk}$ by introducing the factor $\mid\mu-T\mid$ in the numerator as an extra penalty for the departure of the process mean from the preassigned target value T And Process Incapability Indexes(PII) are presented by inversing PCI and include the information of PCI. This paper introduces the PII $C_{ss}^*$ provide manager with various information of process and include Gage R&R. PII $C_{ss}^*$ is presented by inversing PCI $C_{psk}$ and include the information of PCI $C_{psk}$.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.98-105
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• 1999

As the IC(Integrated Circuit) has been densified and complicated, it is required to thorough process control to improve yield. Experts, for this purpose, focused on the process analysis automation, which is came from the strict data management in semiconductor manufacturing. In this paper, we presents the process analysis system that can analyze causes, for a output after processes. Also, the plasma etching process that highly affects yield among semiconductor process is modeled to predict a output before the process. To approach this problem, we use adaptively trained neural networks that exhibit superior accuracy over statistical techniques. And in comparison with methods in other paper, a method that history of trend for input data is considered is shown to offer advantage in both learning and prediction capability. This research regards CD(Critical Dimension) that is considerable in high integrated circuit as output variable of the prediction model.

• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.177-182
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• 2017

As major ICT technologies such as IoT, cloud computing, and Big Data are being applied to manufacturing, smart factories are beginning to be built. The key of smart factory implementation is the ability to acquire and analyze data of the factory. Therefore, the need for a big data analysis platform is increasing. The purpose of this study is to construct a platform for big data analysis of manufacturing process and propose integrated method for analysis. The proposed platform is a RHadoop-based structure that integrates analysis tool R and Hadoop to distribute a large amount of datasets. It can store and analyze big data collected in the unit process and factory in the automation system directly in HBase, and it has overcome the limitations of RDB - based analysis. Such a platform should be developed in consideration of the unit process suitability for smart factories, and it is expected to be a guide to building IoT platforms for SMEs that intend to introduce smart factories into the manufacturing process.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.610-620
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• 2023

The interest in the aircraft interior market is gradually growing due to technological development based on the 4th industrial revolution and competition for airlines to attract customers, and as part of that, Cabin Display System (CDS) for FAA Part.25 civil aircraft is being developed in Korea. The CDS is a system that provides various multimedia services to passengers by utilizing Flexible and Transparent Organic Light Emitting Diodes (OLED) with Integrated Display Processing Module (IDPM). This paper presents a new method for efficient Data Load Process of large-sized files and deals with their implementation and performance. The results of this study are expected to be applied to Data Load Process development of avionics that require reliable large-capacity file transmission along with reducing the costs of development compared to existing ARINC-615A.

• Journal of information and communication convergence engineering
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• v.15 no.2
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• pp.79-84
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• 2017

In a cognitive radio network (CRN), cognitive radio users (CUs) should be powered by a small battery for their operations. The operations of the CU often include spectrum sensing and data transmission. The spectrum sensing process may help the CU avoid a collision with the primary user (PU) and may save the energy that is wasted in transmitting data when the PU is present. However, in a time-slotted manner, the sensing process consumes energy and reduces the time for transmitting data, which degrades the achieved throughput of the CRN. Subsequently, the sensing process does not always offer an advantage in regards to throughput to the CRN. In this paper, we propose a scheme to find an optimal policy (i.e., perform spectrum sensing before transmitting data or transmit data without the sensing process) for maximizing the achieved throughput of the CRN. In the proposed scheme, the data collection period is considered as the main factor effecting on the optimal policy. Simulation results show the advantages of the optimal policy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1935-1950
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• 2023

The arrival of the Internet of Things and 5G technology enables users to rely on edge computing platforms to process massive data. Data sharing based on edge computing refines the efficiency of data collection and analysis, saves the communication cost of data transmission back and forth, but also causes the privacy leakage of a lot of user data. Based on attribute-based encryption and blockchain technology, we design a fine-grained access control scheme for data in edge computing, which has the characteristics of verifiability, support for outsourcing decryption and user attribute revocation. User attributes are authorized by multi-attribute authorization, and the calculation of outsourcing decryption in attribute encryption is completed by edge server, which reduces the computing cost of end users. Meanwhile, We implemented the user's attribute revocation process through the dual encryption process of attribute authority and blockchain. Compared with other schemes, our scheme can manage users' attributes more flexibly. Blockchain technology also ensures the verifiability in the process of outsourcing decryption, which reduces the space occupied by ciphertext compared with other schemes. Meanwhile, the user attribute revocation scheme realizes the dynamic management of user attribute and protects the privacy of user attribute.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1113-1119
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• 2000

To operate a process plant safely and economically, process monitoring is very important. Process monitoring is the task to identify the state of the system from sensor data. Process monitoring includes data acquisition, regulatory control, data reconciliation, fault detection, etc. This research focuses on the data recon-ciliation using scale-space filtering and fault detection using functional-link associative neural networks. Scale-space filtering is a multi-resolution signal analysis method. Scale-space filtering can extract highest frequency factors(noise) effectively. But scale-space filtering has too large calculation costs and end effect problems. This research reduces the calculation cost of scale-space filtering by applying the minimum limit to the gaussian kernel. And the end-effect that occurs at the end of the signal of the scale-space filtering is overcome by using extrapolation related with the clustering change detection method. Nonlinear principal component analysis methods using neural network have been reviewed and the separately expanded functional-link associative neural network is proposed for chemical process monitoring. The separately expanded functional-link associative neural network has better learning capabilities, generalization abilities and short learning time than the exiting-neural networks. Separately expanded functional-link associative neural network can express a statistical model similar to real process by expanding the input data separately. Combining the proposed methods-modified scale-space filtering and fault detection method using the separately expanded functional-link associative neural network-a process monitoring system is proposed in this research. the usefulness of the proposed method is proven by its application a boiler water supply unit.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1289-1303
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• 2010

The need for statistical process control to check the performance of a process is becoming more important in chemical and pharmaceutical industries. This study illustrates the method to determine whether a process is in control and how to produce and interpret control charts. In the experiment, a stream of green dyed water and a stream of pure water were continuously mixed in the process. The concentration of the dye solution was measured before and after the mixer via a spectrophotometer. The in-line mixer provided benefits to the dye and water mixture but not for the stock dye solution. The control charts were analyzed, and the pre-mixer process was in control for both the stock and mixed solutions. The R and X-bar charts showed virtually all of the points within control limits, and there were no patterns in the X-bar charts to suggest nonrandom data. However, the post-mixer process was shown to be out of control. While the R charts showed variability within the control limits, the X-bar charts were out of control and showed a steady increase in values, suggesting that the data was nonrandom. This steady increase in dye concentration was due to discontinuous, non-steady state flow. To improve the experiment in the future, a mixer could be inserted into the stock dye tank. The mixer would ensure that the dye concentration of the stock solution is more uniform prior to entering the pre-mixer ow cell. Overall, this would create a better standard to judge the water and dye mixture data against as well.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.218-223
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• 2021

The five elements of big data are said to be Volume, Variety, Velocity, Veracity, and Value. Among them, data lacking the Veracity of the data or fake data not only makes an error in decision making, but also hinders the creation of value. This study analyzed YouTube's revenue structure to focus the effect of data integrity on data valuation among these five factors. YouTube is one of the OTT service platforms, and due to COVID-19 in 2020, YouTube creators have emerged as a new profession. Among the revenue-generating models provided by YouTube, the process of generating advertising revenue based on click-based playback was analyzed. And, analyzed the process of subtracting the profits generated from invalid activities that not the clicks due to viewers' pure interests, then paying the final revenue. The invalid activity in YouTube's revenue structure is Raw Data, not pure viewing activity of viewers, and it was confirmed a direct impact on revenue generation. Through the analysis of this process, the new Data Value Chain was proposed.