• Tribology and Lubricants
• /
• v.39 no.6
• /
• pp.256-261
• /
• 2023

This study is conducted to evaluate the durability of superhydrophobic surfaces, with a focus on two aspects: contact angle measurement and self-cleaning-performance analysis. Superhydrophobic copper and aluminum surfaces are fabricated using the immersion method and subjected to a rolling wear test, in which a 2 kg weight is placed on a rolling tester, under loaded conditions. To evaluate their durability, the contact angles of the specimens are measured for each cycle. In addition, the surface deformation of the specimens before and after the test is analyzed through SEM imaging and EDS mapping. The degradation of the self-cleaning performance is evaluated before and after the wear test. The results show that superhydrophobic aluminum is approximately 4.5 times more durable than superhydrophobic copper; the copper and aluminum specimens could endure 21,000 and 4,300 cycles of wear, respectively. The results of the self-cleaning test demonstrate that superhydrophobic aluminum is superior to superhydrophobic copper. After the wear test, the self-cleaning rates of the copper and aluminum specimens decrease to 72.7% and 83.4%, respectively. The relatively minor decrease in the self-cleaning rate of the aluminum specimen, despite the large number of wear cycles, confirms that the superhydrophobic aluminum specimen is more durable than its copper counterpart. This study is expected to aid in evaluating the durability of superhydrophobic surfaces in the future owing to the advantage of performing wear tests on superhydrophobic surfaces without damaging the surface coating.

• Safety and Health at Work
• /
• v.15 no.1
• /
• pp.24-32
• /
• 2024

Background: Learning from incidents for accident prevention is a two-stage process, involving the investigation of past accidents to identify the causal factors, followed by the identification and implementation of remedial measures to address the identified causal factors. The focus of past research has been on the identification of causal factors, with limited focus on the identification and implementation of remedial measures. This research begins to contribute to this gap. The motivation for the research is twofold. First, previous analyses show the recurring nature of accidents within the Ghanaian mining industry, and the causal factors also remain the same. This raises questions on the nature and effectiveness of remedial measures identified to address the causes of past accidents. Secondly, without identifying and implementing remedial measures, the full benefits of accident investigations will not be achieved. Hence, this study aims to assess the nature of remedial measures proposed to address investigation causal factors. Method: The study adopted SMARTER from business studies with the addition of HMW (H - Hierarchical, M - Mapping, and W - Weighting of causal factors) to analyse the recommendations from 500 individual investigation reports across seven different mines in Ghana. Results: The individual and the work environment (79%) were mostly the focused during the search for causes, with limited focus on organisational factors (21%). Forty eight percentage of the recommendations were administrative, focussing on fixing the problem in the immediate affected area or department of the victim(s). Most recommendations (70.4%) were support activities that only enhance the effectiveness of control but do not prevent/mitigate the failure directly. Across all the mines, there was no focus on evaluating the performance of remedial measures after their implementation. Conclusion: Identifying sharp-end causes leads to proposing weak recommendations which fail to address latent organisational conditions. The study proposed a guide for effective planning and implementation of remedial actions.

• Economic and Environmental Geology
• /
• v.46 no.4
• /
• pp.301-312
• /
• 2013

Landslides are caused by complex interaction among a large number of interrelated factors such as topography, geology, forest and soils. In this study, a comparative study was carried out using fuzzy relationship method and artificial neural network to evaluate landslide susceptibility. For landslide susceptibility mapping, maps of the landslide occurrence locations, slope angle, aspect, curvature, lithology, soil drainage, soil depth, soil texture, forest type, forest age, forest diameter and forest density were constructed from the spatial data sets. In fuzzy relation analysis, the membership values for each category of thematic layers have been determined using the cosine amplitude method. Then the integration of different thematic layers to produce landslide susceptibility map was performed by Cartesian product operation. In artificial neural network analysis, the relative weight values for causative factors were determined by back propagation algorithm. Landslide susceptibility maps prepared by two approaches were validated by ROC(Receiver Operating Characteristic) curve and AUC(Area Under the Curve). Based on the validation results, both approaches show excellent performance to predict the landslide susceptibility but the performance of the artificial neural network was superior in this study area.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.8 no.3
• /
• pp.96-106
• /
• 2005

The ability of remote sensing and GIS technique, which used to provide valuable informations in the time and space domain, has been known to be very useful in providing permanent records by mapping and monitoring flooded area. In 2000, floods were at the worst stage of devastation in Tonle Sap Lake, Mekong River Basin, for the second time in records during July and October. In this study, Landsat ETM+ and RADARSAT imagery were used to obtain the basic information on computation of the inundation area and volume using ISODATA classifier and segmentation technique. However, the extracted inundatton area showed only a small fraction than the actually inundated area because of clouds in the imagery and complex ground conditions. To overcome these limitations, the cost-distance method of GIS was used to estimate the inundated area at the peak level by integrating the inundated area from satellite imagery in corporation with digital elevation model (DEM). The estimated inundation area was simply converted with the inundation volume using GIS. The inundation volume was compared with the volume based on hydraulic modeling with MIKE 11. which is the most poppular among the dynamic river modeling system. The method is suitable for estimating inundation volume even when Landsat ETM+ has many clouds in the imagery.

• The KIPS Transactions:PartB
• /
• v.10B no.4
• /
• pp.373-380
• /
• 2003

Most of low cost digital cameras reveal relatively high lens distortion. The purpose of this research is to compensate the degradation of image quality due to the geometrical distortion of a lens system. The proposed method consists of two stages : calculation of a lens distortion coefficient by a simplified version of Tsai´s camera calibration and subsequent image warping of the original distorted image to remove geometrical distortion based on the calculated lens distortion coefficient. In the lens distortion coefficient calculation stage, a practical method for handling scale factor ratio and image center is proposed, after which its feasibility is shown by measuring the performance of distortion correction using a quantitative image quality measure. On the other hand, in order to apply image warping via inverse spatial mapping using the result of the lens distortion coefficient calculation stage, a cubic polynomial derived from an adopted radial distortion lens model must be solved. In this paper, for the purpose of real-time operation, which is essential for embedding into an information device, an approximated solution to the cubic polynomial is proposed in the form of a solution to a quadratic equation. In the experiment, potential for real-time implementation and equivalence in performance as compared with that from cubic polynomial solution are shown.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.29 no.2
• /
• pp.183-191
• /
• 2011

The objective of this study is 10 investigate the method to produce urban climate map so as to cope with climate change and efficiently control greenhouse gas in the city by using GIS. To produce urban climate map by using GIS, statistical data and spatial data of greenhouse gases related to climate change were collected and analyzed and the correlation between the type of urban climatop and urban climate change was analyzed by establishing GIS framework data construction method to prepare urban climate map and preparing and analyzing urban climate map related to the demonstration area. It was found that exact greenhouse gases emission quantity and absorption quantity can be calculated for each type of urban climatop by preparing urban climate map and the temperature is high in residential area, commercial area and industrial area and the emission quantity per unit area is high in the traffic area and industrial area. It seems that the influence of climate change can be presented for urban development by suggesting urban climate change for type of urban climatop and they can be utilized to save energy in urban area and to establish greenhouse gases reducing policy.

• Journal of the Korean Geophysical Society
• /
• v.1 no.1
• /
• pp.59-68
• /
• 1998

Ground penetrating radar (GPR) experiments were performed in a sand tank to study the ability of detection of buried pipes and to characterize the signal of the reflection wave. The ratios of diameter of buried pipes to the depth were set 4 up to 24 % and materials were metal, synthetic resin, and wood. In case of groundwater table below buried materials, strong reflection signals were observed irrespective of diameter and depth except for wood. While it is very difficult to detect the reflection signals in case that the groundwater table is set to higher than buried materials. The reflection signals from the bottom of the sand tank, however, were clearly observed even in case of higher groundwater table. This implies that the weak reflection signals from the buried materials are not all due to the wave attenuation. The vertical reflection profiling method is recommended in case that the object of the survey is to find horizontal position of buried material because this method has the advantage in cost and time of survey. However, the full or partial CMP gather method is recommended in case that the objects of the survey are to get the detailed subsurface information, i.e. the depth to buried material, interval velocity of geological layer, and mapping the groundwater table.

• Investigative Magnetic Resonance Imaging
• /
• v.6 no.2
• /
• pp.137-146
• /
• 2002

Purpose : This paper introduces an improved classification approach which adopts a deterministic relaxation method and an agglomerative clustering technique for the classification of MRI using neural network. The proposed approach can solve the problems of convergency to local optima and computational burden caused by a large number of input patterns when a neural network is used for image classification. Materials and methods : Application of Hopfield neural network has been solving various optimization problems. However, major problem of mapping an image classification problem into a neural network is that network is opt to converge to local optima and its convergency toward the global solution with a standard stochastic relaxation spends much time. Therefore, to avoid local solutions and to achieve fast convergency toward a global optimization, we adopt MFA to a Hopfield network during the classification. MFA replaces the stochastic nature of simulated annealing method with a set of deterministic update rules that act on the average value of the variable. By minimizing averages, it is possible to converge to an equilibrium state considerably faster than standard simulated annealing method. Moreover, the proposed agglomerative clustering algorithm which determines the underlying clusters of the image provides initial input values of Hopfield neural network. Results : The proposed approach which uses agglomerative clustering and deterministic relaxation approach resolves the problem of local optimization and achieves fast convergency toward a global optimization when a neural network is used for MRI classification. Conclusion : In this paper, we introduce a new paradigm to classify MRI using clustering analysis and deterministic relaxation for neural network to improve the classification results.

• Journal of KIISE:Software and Applications
• /
• v.26 no.10
• /
• pp.1219-1229
• /
• 1999

일반적으로 AND, OR, NOT과 같은 연산자를 사용하는 불리언 질의는 사용자의 검색의도를 정확하게 표현할 수 있기 때문에 검색 전문가들은 불리언 질의를 사용하여 높은 검색성능을 얻는다고 알려져 있지만, 일반 사용자는 자신이 원하는 정보를 불리언 형태로 표현하는데 익숙하지 않다. 본 논문에서는 검색성능의 향상과 사용자 편의성을 동시에 만족하기 위하여 사용자의 자연어 질의를 확장 불리언 질의로 자동 변환하는 방법론을 제안한다. 먼저 자연어 질의를 범주문법에 기반한 구문분석을 수행하여 구문트리를 생성하고 연산자 및 키워드 정보를 추출하여 구문트리를 간략화한다. 다음으로 간략화된 구문트리로부터 명사구를 합성하고 키워드들에 대한 가중치를 부여한 후 불리언 질의를 생성하여 검색을 수행한다. 또한 구문분석의 오류로 인한 검색성능 저하를 최소화하기 위하여 상위 N개 구문트리에 대해 각각 불리언 질의를 생성하여 검색하는 N-BEST average 방법을 제안하였다. 정보검색 실험용 데이타 모음인 KTSET2.0으로 실험한 결과 제안된 방법은 수동으로 추출한 불리언 질의보다 8% 더 우수한 성능을 보였고, 기존의 벡터공간 모델에 기반한 자연어질의 시스템에 비해 23% 성능향상을 보였다. Abstract There have been a considerable evidence that trained users can achieve a good search effectiveness through a boolean query because a structural boolean query containing operators such as AND, OR, and NOT can make a more accurate representation of user's information need. However, it is not easy for ordinary users to construct a boolean query using appropriate boolean operators. In this paper, we propose a boolean query formulation method that automatically transforms a user's natural language query into a extended boolean query for both effectiveness and user convenience. First, a user's natural language query is syntactically analyzed using KCCG(Korean Combinatory Categorial Grammar) parser and resulting syntactic trees are structurally simplified using a tree-simplifying mechanism in order to catch the logical relationships between keywords. Next, in a simplified tree, plausible noun phrases are identified and added into the same tree as new additional keywords. Finally, a simplified syntactic tree is automatically converted into a boolean query using some mapping rules and linguistic heuristics. We also propose an N-BEST average method that uses top N syntactic trees to compensate for bad effects of single incorrect top syntactic tree. In experiments using KTSET2.0, we showed that a proposed method outperformed a traditional vector space model by 23%, and surprisingly manually constructed boolean queries by 8%.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.57 no.5
• /
• pp.139-152
• /
• 2015

Along with climate change, it is reported that the scale and frequency of extreme climate events show unstable tendency of increase. Thus, to comprehend the change characteristics of precipitation data, it is needed to consider non-stationary. The main objectives of this study were to estimate future design floods for Wonpyeongcheon watershed based on RCP (Representative Concentration Pathways) scenario. Wonpyeongcheon located in the Keum River watershed was selected as the study area. Historical precipitation data of the past 35 years (1976~2010) were collected from the Jeonju meteorological station. Future precipitation data based on RCP4.5 were also obtained for the period of 2011~2100. Systematic bias between observed and simulated data were corrected using the quantile mapping (QM) method. The parameters for the bias-correction were estimated by non-parametric method. A non-stationary frequency analysis was conducted with moving average method which derives change characteristics of generalized extreme value (GEV) distribution parameters. Design floods for different durations and frequencies were estimated using rational formula. As the result, the GEV parameters (location and scale) showed an upward tendency indicating the increase of quantity and fluctuation of an extreme precipitation in the future. The probable rainfall and design flood based on non-stationarity showed higher values than those of stationarity assumption by 1.2%~54.9% and 3.6%~54.9%, respectively, thus empathizing the necessity of non-stationary frequency analysis. The study findings are expected to be used as a basis to analyze the impacts of climate change and to reconsider the future design criteria of Wonpyeongcheon watershed.