• Journal of Dental Rehabilitation and Applied Science
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• v.33 no.1
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• pp.47-54
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• 2017

The atrophy of edentulous ridge and pneumatization of the maxillary sinus often limit the volume of bone available for implant placement on maxillary posterior teeth. Most clinicians suffer difficulties from poor bone quality and quantity on maxillary posterior site. Thus, the success of maxillary posterior implant surgery depends on the increase of the available bone and obtaining a good initial stability of the implant after maxillary sinus reconstruction. The maxillary sinus augmentation methods include a crestal approach and a lateral approach. Less morbidity and complications after operation is major advantage to sinus augmentation using crestal approach than lateral approach. However, when the residual ridge height is ${\geq}6mm$, it is known that crestal approach is appropriate. Also delayed implantation after sinus augmentation is recommended in severely atrophic ridge. We present the three cases of implant placement simultaneously sinus augmentation using crestal approach in posterior maxilla site with ${\leq}3mm$ of residual alveolar bone.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of Sensor Science and Technology
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• v.32 no.3
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• pp.140-146
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• 2023

Water quality is crucial for human health and the environment. Accurate measurement of the quantity of organic carbon in water is essential for water quality evaluation, identification of water pollution sources, and appropriate implementation of water treatment measures. Total organic carbon (TOC) analysis is an important tool for this purpose. Although other methods, such as chemical oxygen demand (COD) and biochemical oxygen demand (BOD) are also used to measure organic carbon in water, they have limitations that make TOC analysis a more favorable option in certain situations. For example, COD requires the use of toxic chemicals, and BOD is time-consuming and can produce inconsistent and unreliable results. In contrast, TOC analysis is rapid and reliable, providing accurate measurements of organic carbon content in water. However, common methods for TOC analysis can be complex and energy-intensive because of the use of high-temperature heaters for liquid-to-gas phase transitions and the use of acid, which present safety risks. This study focuses on a TOC analysis method using TiO₂ photocatalysis, which has several advantages over conventional TOC analysis methods, including its low cost and easy maintenance. For TiO₂, rutile and anatase powders are mixed with an inorganic binder and spray-coated onto a glass fiber substrate. The TiO₂ powder and inorganic binder solutions are adjusted to optimize the photocatalytic reaction performance. The TiO₂ photocatalysis method is a simple and low-power approach to TOC analysis, making it a promising alternative to commonly used TOC analysis methods. This study aims to contribute to the development of more efficient and cost-effective approaches for water quality analysis and management by exploring the effectiveness and reliability of the developed equipment.

• Communications for Statistical Applications and Methods
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• v.17 no.1
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• pp.39-45
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• 2010

As the value of environment is increasing, the water quality has been a matter of interest to the nation and people. Research on water quality has been widely studied, but focused on geographical characteristic and river characteristics like inflow, outflow, quantity and speed of water. In this paper, two approaches to measure the similarity of sampling sites by using water quality data are discussed and compared with two-years empirical data of Yongdam-Dam. The existing method has calculated their similarities with principal component scores. The proposed approach in this paper use correlation matrix of water quality related variables and MDS for measuring the similarity, which is shown to be better in the sense of being clustering which is identical to geographical clustering since it can consider the time series pattern of water quality.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.5
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• pp.428-434
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• 2016

A lot of drawings for pipe construction and installation are needed to construct plant process system on the offshore plant structures. Depending on their scale or complexity, the required number of drawings related pipes sometimes amounts to several hundreds of thousands. Most major shipyards, therefore, have their own system which can automatically depict pipes’ geometric, manufacturing, and BOM(Bill of Material) information on the drawings. However, as the complexity and absolute quantity in the isometric region on the drawings is increased, the information extraction from the customized DB and positioning at the typical locations does not get to be enough to avoid the overlap between geometric contours, labels, and symbols. For this reason, the novel methods to arrange additional annotations without overlaps are presented in the paper. This approach is expected to increase the readability and legibility of the drawing and prevent the human error, and finally decrease the time-consuming and tedious jobs which are unnecessarily required to designers.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.1
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• pp.96-104
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• 2013

Study of human-robot Interaction gets more and more attention to expand the robot application for tasks difficult by robot alone. Developed countries are preparing for a new market by introducing the concept of 'Co-Robot' model of human-robot Interaction. Our research of direct teaching is a way to instruct robot's trajectory by human's handling of its end device. This method is more intuitive than other existing methods. The benefit of this approach includes easy and fast teaching even by non-professional workers. And it can enhance utilization of robots in small and medium-sized enterprises for small quantity batch production. In this study, we developed the algorithms for creating accurate trajectory from repeated inaccurate direct teaching and GUI for the direct teaching. We also propose the basic framework for direct teaching.

• Physical Therapy Rehabilitation Science
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• v.12 no.2
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• pp.177-184
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• 2023

Objective: Manual therapy is a commonly utilized approach in managing chronic pain, but its specific impact on pain catastrophizing remains uncertain. The objective of this systematic review and meta-analysis was to examine the effects of manual therapy on pain catastrophizing in individuals with chronic pain. Design: A systematic review and meta-analysis Methods: A comprehensive search was conducted in electronic databases to identify relevant studies published from 2014 onwards. Studies that evaluated the impact of manual therapy on pain catastrophizing in individuals with chronic pain were incorporated. The risk of bias in the selected studies was evaluated using the Cochrane tool for risk of bias in qualitative analysis. For the quantitative analysis, RevMan 5.4 software was utilized, employing a random-effects model as the analysis model. The effect measure used in the analysis was the standardized mean difference (SMD). Results: In total, 26 studies were collected, and following the screening process, three of them were incorporated into the final analysis. The included studies involved a total of 153 patients with chronic pain. The interventions comprised various manual therapy techniques targeting different areas of the body. Pain catastrophizing and pain intensity were the primary outcomes of interest. The meta-analysis revealed a significant reduction in pain catastrophizing scores following manual therapy intervention compared to control conditions (SMD = -0.91, 95% CI: -1.25 to -0.58). However, heterogeneity between the studies was observed. Conclusions: Despite the limited quantity and heterogeneity of studies, it has been demonstrated that manual therapy intervention is effective in reducing pain catastrophizing in individuals with chronic pain.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.444-453
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• 2003

Recently, a great interest of bio-technology(BT) is concentrated and the image analysis technique for electrophoresis gels is highly requested to analyze genetic information or to look for some new bio-activation materials. For this purpose, the location and quantity of each band in a lane should be measured. In most of existing techniques, the approach of peak searching in a profile of a lane is used. But this peak is improper as the representative of a band, because its location does not correspond to that of the brightest pixel or the center of gravity. Also, it is improper to measure band quantity in most of these approaches because various enhancement processes are commonly applied to original images to extract peaks easily. In this paper, we adopt an approach to measure accumulated brightness as a band quantity in each band region, which Is extracted by not using any process of changing relative brightness, and the gravity center of the region is calculated as a band location. Actually, we first extract lanes with an entropy-based threshold calculated on a gel-image histogram. And then, three other methods are proposed and applied to extract bands. In the MER method, peaks and valleys are searched on a vertical search line by which each lane is bisected. And the minimum enclosing rectangle of each band is set between successive two valleys. On the other hand, in the RG-1 method, each band is extracted by using region growing with a peak as a seed, separating overlapped neighbor bands. In the RG-2 method, peaks and valleys are searched on two vertical lines by which each lane is trisected, and the left and right peaks nay be paired up if they seem to belong to the same band, and then each band region is grown up with a peak or both peaks if exist. To compare above three methods, we have measured the location and amount of bands. As a result, the average errors in band location of MER, RG-1, and RG-2 were 6%, 3%, and 1%, respectively, when the lane length is normalized to a unit value. And the average errors in band amount were 8%, 5%, and 2%, respectively, when the sum of band amount is normalized to a unit value. In conclusion, RG-2 was shown to be more reliable in the accuracy of measuring the location and amount of bands.

• Journal of Soil and Groundwater Environment
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• v.14 no.3
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• pp.57-67
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• 2009

In soil and sediment environment, microorganisms play major roles in biochemical cycles of ecological significant elements. Because of its ecological significance, microbial diversity and community structure information are useful as indexes for assessing the quality of subsurface ecological environment and bioremediation. To achieve more accurate assessment, it is requested to gain sufficient yield and purity of DNA extracted from various soil and sediment samples. Although there have been a large number of basic researches regarding soil and sediment DNA extraction methods, little guideline information is given in literature when choosing optimal DNA extraction methods for various purposes such as environmental ecology impact assessment and bioremediation capability evaluation. In this study, we performed a thorough literature review to compare the characteristics of the current DNA extraction methods from soil and sediment samples, and discussed about considerations when selecting and applying DNA extraction methods for environmental impact assessment and bioremediation capability evaluation. This review suggested that one approach is not enough to gain the suitable quantity and yield of DNA for assessing microbial diversity, community structure and population dynamics, and that a careful attention has to be paid for selecting an optimal method for individual environmental purpose.

• The KIPS Transactions:PartA
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• v.15A no.1
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• pp.1-8
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• 2008

An occlusion culling method, one of visibility culling methods, excludes invisible objects or triangles which are covered by other objects. As it reduces computation quantity, occlusion culling is an effective method to handle complex scenes in real-time. But an existing common occlusion culling method, such as hardware occlusion query method, sends objects' data twice to GPU and this causes processing overheads once for occlusion culling test and the other is for rendering. And another existing hardware occlusion culling method, VCBP, can test objects' visibility quickly, but it neither test bounding volume nor return test result to application stage. In this paper, we propose a single pass occlusion culling method which uses temporal and spatial coherency, with effective occlusion culling hardware architecture. In our approach, the hardware performs occlusion culling test rapidly with cache on the rasterization stage where triangles are transformed into fragments. At the same time, hardware sends each primitive's visibility information to application stage. As a result, the application stage reduces data transmission quantity by excluding covered objects using the visibility information on previous frame and hierarchical spatial tree. Our proposed method improved maximum 44%, minimum 14% compared with S&W method based on hardware occlusion query. And the performance is increased 25% and 17% respectively, compared to maximum and minimum performance of CHC method which is based on occlusion culling method.