• Tuberculosis and Respiratory Diseases
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• v.87 no.2
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• pp.194-199
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• 2024

Background: In recent years, medical thoracoscopy has been well established to play an important role in undiagnosed pleural effusion; however, this procedure is underutilized due to limited availability of the instruments it requires. This study analysed the outcome of single port rigid thoracoscopy in patients with undiagnosed pleural effusions. Methods: This study retrospectively analysed the outcomes of all patients with undiagnosed pleural effusion presenting to our centre between 2016 to 2020 who underwent single port rigid medical thoracoscopy as a diagnostic procedure. Results: In total, 92 patients underwent single port rigid medical thoracoscopy. The most common presenting symptom was shortness of breath. A majority of the patients had lymphocytic exudative pleural effusion. The average biopsy sample size was 18 mm, and no major complication was reported in any of the patients. Conclusion: Single port rigid thoracoscopy is a safe and well-tolerated procedure that yields a biopsy of a larger size with high diagnostic yield. Moreover, the low cost of the instruments required by this procedure makes it particularly suited for use in developing countries.

• Smart Structures and Systems
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• v.33 no.4
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• pp.263-279
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• 2024

With the increasing diversity of internet media, available video data have become more convenient and abundant. Related video data-based research has advanced rapidly in recent years owing to advantages such as noncontact, low-cost data acquisition, high spatial resolution, and simultaneity. Additionally, structural nonlinearity extraction has attracted increasing attention as a tool for damage evaluation. This review paper aims to summarize the research experience with the recent developments and applications of video data-based technology for structural nonlinearity extraction and damage evaluation. The most regularly used object detection images and video databases are first summarized, followed by suggestions for obtaining video data on structural nonlinear damage events. Technologies for linear and nonlinear system identification based on video data are then discussed. In addition, common nonlinear damage types in disaster events and prevalent processing algorithms are reviewed in the section on structural damage evaluation using video data uploaded on online platform. Finally, a discussion regarding some potential research directions is proposed to address the weaknesses of the current nonlinear extraction technology based on video data, such as the use of uni-dimensional time-series data as leverage to further achieve nonlinear extraction and the difficulty of real-time detection, including the fields of nonlinear extraction for spatial data, real-time detection, and visualization.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.303-310
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• 2024

In this study, we conducted a work analysis at an active building construction site, utilizing three-axis acceleration sensors affixed to four plaster-board-pasting workers for five days. Although acceleration data is less accurate than visual or image recognition in identifying specific tasks, it can be easily captured using smartphones, even in challenging conditions such as poorly lit or obstructed construction sites. This accessibility facilitates continuous data collection over extended periods, enabling automated analysis without significant cost or time investment. In addition, this method can identify trends in worker behavior that elude conventional visual inspection. Our approach encompasses various evaluation indices, beginning with an analysis of average work time per plasterboard sheet and the differentiation of walking motions using acceleration data. Furthermore, we introduced a new evaluation index that quantifies the distribution of high- and low-intensity work based on acceleration readings. Through comparative analysis with evaluation indices from previous studies, we confirmed common trends and discussed the strengths and limitations of our proposed index. Our findings suggest a correlation between work experience and performance, as evidenced by smoother operational patterns among seasoned workers. In particular, proficient workers exhibited fewer instances of extremely intense or sporadic movements. This observation underscores the influence of experience on work dynamics.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.744-747
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• 2008

Quantity information focused on a design drawing plays a critical role in a decision making related to cost for project participants during project life cycles. Related participants absolutely depend on quantity take-off working which produces the quantity information by hand, and then a worker's mistake often causes many errors. The difference of quantity by the know-how of the person in charge of the estimation also occurs. In addition, the worker passes through the whole quantity take-off processes again in case of re-working for quantity take-off produced by a change order. The requirements about the automated estimation increase because of the needs for the accurate quantity take-off and dealing with the change order and recently, the studies about the automated estimation working process based on 34 cad model from 3d cad modeler are attempted in various viewpoints. However, the existing studies reach the limits such as common quantity data type framework for getting Quantity information. Focused on a certain 34 cad modeler and BIM based automation of estimation using it Therefore, the objective of this study is to develop the a series of system which can extract, analyze, and verify Quantity Data Type in modeler to automate quantity take-off originated from various 3d cad modelers as a foundation study for BIM based automation of estimation framework.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1010-1026
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• 2004

The goal of product line engineering is to support the systematic development of a set of similar software systems by understanding and controlling their common and distinguishing characteristics. The product line engineering is a process that develops reusable core assets and develops a set of software-intensive systems from a common set of core assets in a prescribed way. Currently, many software development technologies are accomplished in context of product line. However, much of the product line engineering research have focused on the reuse of work products relating to the software's architecture, detail design, and code. The product lines fulfill the promise of tailor-made systems built specifically for the needs of particular customers or customer groups. In particular, commonality and variability play central roles in the all product line development processes. These must be treated already during the requirement analysis phase. Requirements in product line engineering are basis of software development just like as traditional system development engineering, and basis of deciding other core assets' property - commonalities and variabilities. However, it is difficult to elicit, analyze and manage correct requirements. Therefore, it is necessary to develop systematic methods which can develop and manage requirement as core asset, which can be stable in anticipative change and can be well adapted to unpredictable change. In this paper, we suggest a method of managing requirements as core asset in product line. Through this method, the reuse of domain requirements can be enhanced. As a result, the cost and time of software development can be reduced and the productivity can be increased.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.17 no.1
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• pp.55-60
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• 1984

An experiment on the efficiency of soybean meal substituted for fish meal in the diet of common carp was carried out at the Fish Culture Experiment Station of the National Fisheries University of Pusan from June 27 to August 25, 1983. The carp used for the experiment were 50 fish each lot, each averaging 26 g in initial weight (total weight 1300 g). The experimental diets contained $10\%,\;20\%,\;30\%$, and $40\%$ soybean meal ($44\%$-protein) at iso-protein content basis in place of white fish meal in the control diet which contained $35\%$ protein. The growth rate in the control division was highest with progressive decrease in performance of the fish with increasing rates of soybean meal substituted in the test diets. Nevertheless, the $10\%\;and\;20\%$ soybean meal test diet groups showed acceptable conversions and growth rates, i. e. feed coefficients being 1.28 and l.30 and daily growth rates, $1.708\%\;and\;1.694\%$ compared to $1.22\%\;and\;1.758%$ for the control group, respectively. Therefore, soybean meal could be substituted for fish meal in carp diet by $20\%$ without significant differences of performance with some saving in feed cost.

• Korean Journal of Construction Engineering and Management
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• v.12 no.1
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• pp.3-12
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• 2011

Technology based civilization has made a sustained advancement, resulting in economic growth and material prosperity. The outcome was the beginning of environmental destruction. Especially, in regard to construction, it has been recognized as a key culprit for pollution. As such, the construction industry has recently shown interest in the environment, as it has been applying environment friendly method of construction and reducing wastes. As the number of old common housing increases in our country, reconstruction and remodeling are implemented as a means of improvement. However, it can be said that remodeling is the inevitable option because of cost and environmental problems associated with reconstruction. As part of its feature, remodeling work is preceded by removal work. And, removal work inevitably creates construction wastes. Treatment of wastes that takes into consideration environmental aspects is important and for this, removal work that is based on environment friendly remodeling to ensure selective separation must be implemented. Yet, a removal work based on environment friendly remodeling has a lower level of output compared to existing methods. Because remodeling work by its nature has a post construction work which proceeds after it, securing work efficiency is important as the removal work is a critical path activity. Thus, the present study improves the work process of a removal work that is based on environment friendly remodeling so that it becomes a work process that includes work efficiency. For this, as a case study, old common housing has been selected, and a TACT process has been developed which is based on data acquired from environment friendly removal work. And, this study develops an optimal TACT process which is based on environment friendly remodeling by conducting a simulation for a 15 floor apartment.

• Journal of the Korea Computer Graphics Society
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• v.18 no.2
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• pp.1-8
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• 2012

High dynamic range (HDR) images represent a far wider numerical range of exposures than common digital images. Thus it can accurately store intensity levels of light found in the specific scenes generated by light sources in the real world. Although a kind of professional HDR cameras which support fast accurate capturing has been developed, high costs prevent from employing those in general working environments. The common method to produce a HDR image with lower cost is to take a set of photos of the target scene with a range of exposures by general purpose cameras, and then to transform them into a HDR image by commercial softwares. However, the method needs complicate and accurate camera calibration processes. Furthermore, creating HDR environment maps which are used to produce high quality imaging contents includes delicate time-consuming manual processes. In this paper, we present an automatic HDR panorama environment map generating system which was constructed to make the complicated jobs of taking pictures easier. And we show that our system can be effectively applicable to photo-realistic compositing tasks which combine 3D graphic models with a 2D background scene using image-based lighting techniques.

• Journal of Yeungnam Medical Science
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• v.11 no.1
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• pp.127-134
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• 1994

The aim of this study was to identify the usefulness of pelviscopy in treatment besides its diagnostic value. The advantages of pelviscopic surgery are low cost, rapid recovery, good cosmetic effect, low incidence of complication and postoperative adhesion. So most of the pelvic exploration in gynecologic patients are replaced by the pelviscopic surgery these days. Pelviscopic surgery was performed on 136 patients at the Department of Obstetrics and Gynecology, College of Medicine, Yeungnam University from May 1991 to July 1993. The results obtained were as follows : The age distribution of the patients was from 19 to 55 with age of 31.2 years, and the mean parity was 0.96, the most common indication of pelviscopic surgery was tubal pregnancy(66.9%), the second most common indications was ovarian cyst(10.3%) and the other indications were endometriosis, corpus luteum cyst rupture, parovarian cyst, foreign body, tubal ligation, hydrosalpinx, uterine myoma and diagnostic procedure. The main types of surgery were salpingectomy in 58.8% and salpingoophorectomy in 16.3%. The mean duration of hospitalization was 2.1 days without specific complications. According to these results, it was postulated that the pelviscopic surgery was a useful operative tool in gynecologic treatment and its application could be extended to many other areas of gynecology with safety by the development of surgical techniques and instruments.