Jahangiri, Mehdi;Hoboubi, Naser;Rostamabadi, Akbar;Keshavarzi, Sareh;Hosseini, Ali Akbar
Safety and Health at Work
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v.7
no.1
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pp.6-11
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2016
Background: A permit to work (PTW) is a formal written system to control certain types of work which are identified as potentially hazardous. However, human error in PTW processes can lead to an accident. Methods: This cross-sectional, descriptive study was conducted to estimate the probability of human errors in PTWprocesses in a chemical plant in Iran. In the first stage, through interviewing the personnel and studying the procedure in the plant, the PTW process was analyzed using the hierarchical task analysis technique. In doing so, PTWwas considered as a goal and detailed tasks to achieve the goal were analyzed. In the next step, the standardized plant analysis risk-human (SPAR-H) reliability analysis method was applied for estimation of human error probability. Results: The mean probability of human error in the PTW system was estimated to be 0.11. The highest probability of human error in the PTW process was related to flammable gas testing (50.7%). Conclusion: The SPAR-H method applied in this study could analyze and quantify the potential human errors and extract the required measures for reducing the error probabilities in PTW system. Some suggestions to reduce the likelihood of errors, especially in the field of modifying the performance shaping factors and dependencies among tasks are provided.
In this paper, we propose a new automatic taxonomy generation algorithm for the audio genre classification. The proposed algorithm automatically generates hierarchical taxonomy based on the estimated classification accuracy at all possible nodes. The estimation of classification accuracy in the proposed algorithm is conducted by applying the training data to classifier using k-fold cross validation. Subsequent classification accuracy is then to be tested at every node which consists of two clusters by applying one-versus-one support vector machine. In order to assess the performance of the proposed algorithm, we extracted various features which represent characteristics such as timbre, rhythm, pitch and so on. Then, we investigated classification performance using the proposed algorithm and previous flat classifiers. The classification accuracy reaches to 89 percent with proposed scheme, which is 5 to 25 percent higher than the previous flat classification methods. Using low-dimensional feature vectors, in particular, it is 10 to 25 percent higher than previous algorithms for classification experiments.
Sports scene is characterized by large amount of global motion due to pan and zoom of camera motion, and includes many small objects moving independently. Some short period of sports games is thrilling to televiewers, and important to producers. At the same time that kinds of scenes exhibit exceptionally dynamic motions and it is very difficult to analyze the motions with conventional algorithms. In this thesis, several algorithms are proposed for global motion analysis on these dynamic scenes. It is shown that proposed algorithms worked well for motion compensation and panorama synthesis. When cascading the inter frame motions, accumulated errors are unavoidable. In order to minimize these errors, interpolation method of motion vectors is introduced. Affined transform or perspective projection transform is regarded as a square matrix, which can be factorized into small amount of motion vectors. To solve factorization problem, we preposed the adaptation of Newton Raphson method into vector and matrix form, which is also computationally efficient. Combining multi frame motion estimation and the corresponding interpolation in hierarchical manner enhancement algorithm of motion parameters is proposed, which is suitable for motion compensation and panorama synthesis. The proposed algorithms are suitable for special effect rendering for broadcast system, video indexing, tracking in complex scenes, and other fields requiring global motion estimation.
Journal of the Institute of Electronics Engineers of Korea SP
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v.42
no.2
s.302
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pp.101-112
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2005
As we perceive the world as 3-dimensional through our two eyes, we can extract 3-dimensional information from stereo images obtained from two or more cameras. Since stereo images have a large amount of data, with recent advances in digital video coding technology, efficient compression algorithms have been developed for stereo images. In order to compress stereo images and to obtain 3-D information such as depth, we find disparity vectors by using disparity estimation algorithm generally utilizing pixel differences between stereo pairs. However, it is not unusual to have stereo images having different intensity values for several reasons, such as incorrect control of the iris of each camera, disagreement of the foci of two cameras, orientation, position, and different characteristics of CCD (charge-coupled device) cameras, and so on. The intensity differences of stereo pairs often cause undesirable problems such as incorrect disparity vectors and consequent low coding efficiency. By compensating intensity differences between left and right images, we can obtain higher coding efficiency and hopefully reduce the perceptual burden of brain to combine different information incoming from two eyes. We propose several methods of intensity compensation such as local intensity compensation, global intensity compensation, and hierarchical intensity compensation as very simple and efficient preprocessing tool. Experimental results show that the proposed algerian provides significant improvement in coding efficiency.
This study extended Park et al.(2007c), which analyzed the efficiency of a hierarchical transit network, showed the result of a real data, and analyzed its applicability. Operating cost was estimated using a model which was established in this study, and minimum transit demand was derived from the operating cost. The minimum transit demand value is just a sample calculation, thus it varies by many inside and outside factors of the model. Looking at the inside of the model, operating cost and travel speed are major factors, and the possibility of introducing urban subway becomes high when the operating cost of the transit system is low and its travel speed is high. As far as the outside factors are concerned, according to the analysis on the network structure, transit demand, and transit mode share, the minimum transit demand value which was derived in this study will be the maximum value among the possible values. In the feasibility study, the benefit is likely to be overestimated and the cost is likely to be underestimated than those of this study. It could be concluded that the methodology of a feasibility study is appropriate in the field standard. This study analyzed the efficiency of introduction of urban subway using analytical approach, thus has many shortcomings and limitations. However the practical approach, like feasibility study, has some limitations as well. This study could be a basis on establishing an analysis framework that is more accurate and reasonable by comparing analytical approach and practical approach.
KSCE Journal of Civil and Environmental Engineering Research
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v.37
no.1
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pp.29-41
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2017
Design rainfalls are one of the most important hydrologic data for river management, hydraulic structure design and risk analysis. The design rainfalls are first estimated by a point frequency analysis and the IDF (intensity-duration-frequency) curve is then constructed by a nonlinear regression to either interpolate or extrapolate the design rainfalls for other durations which are not used in the frequency analysis. It has been widely recognised that the more reliable approaches are required to better account for uncertainties associated with the model parameters under circumstances where limited hydrologic data are available for the watershed of interest. For these reasons, this study developed a hierarchical Bayesian based GLM (generalized linear model) for a regional frequency analysis in conjunction with a scaling function of the parameters in probability distribution. The proposed model provided a reliable estimation of a set of parameters for each individual station, as well as offered a regional estimate of the parameters, which allow us to have a regional IDF curve. Overall, we expected the proposed model can be used for different aspects of water resources planning at various stages and in addition for the ungaged basin.
Kim, Hyun-Suk;Lee, Tae-Yoon;Hur, Dong-Seok;Rhee, Soo-Ahm;Kim, Tae-Jung
Korean Journal of Remote Sensing
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v.23
no.4
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pp.297-309
/
2007
The first Korean geostationary weather satellite, Communications, Oceanography and Meteorology Satellite (COMS) will be launched in 2008. The ground station for COMS needs to perform geometric correction to improve accuracy of satellite image data and to broadcast geometrically corrected images to users within 30 minutes after image acquisition. For such a requirement, we developed automated and fast geometric correction techniques. For this, we generated control points automatically by matching images against coastline data and by applying a robust estimation called RANSAC. We used GSHHS (Global Self-consistent Hierarchical High-resolution Shoreline) shoreline database to construct 211 landmark chips. We detected clouds within the images and applied matching to cloud-free sub images. When matching visible channels, we selected sub images located in day-time. We tested the algorithm with GOES-9 images. Control points were generated by matching channel 1 and channel 2 images of GOES against the 211 landmark chips. The RANSAC correctly removed outliers from being selected as control points. The accuracy of sensor models established using the automated control points were in the range of $1{\sim}2$ pixels. Geometric correction was performed and the performance was visually inspected by projecting coastline onto the geometrically corrected images. The total processing time for matching, RANSAC and geometric correction was around 4 minutes.
Kim, Junki;Choi, Seung-cheon;Kim, Jaehwi;Seo, Hong-Seok
The Korean Journal of Applied Statistics
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v.33
no.6
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pp.763-776
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2020
Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.
Kim, Ki-Dong;Lee, Tae-Jung;Jung, Won-Seok;Kim, Dong-Sool
Journal of Korean Society for Atmospheric Environment
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v.28
no.3
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pp.233-248
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2012
The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energy-use emissions, the emission from mobile source as one of key categories accounted for 19.4% and further the road transport emission occupied the most dominant portion in the category. The road transport emissions can be estimated on the basis of either the fuel consumed (Tier 1) or the distance travelled by the vehicle types and road types (higher Tiers). The latter approach must be suitable for simultaneously estimating $CO_2$, $CH_4$, and $N_2O$ emissions in local administrative districts. The objective of this study was to estimate 31 municipal GHG emissions from road transportation in Gyeonggi Province, Korea. In 2008, the municipalities were consisted of 2,014 towns expressed as Dong and Ri, the smallest administrative district unit. Since mobile sources are moving across other city and province borders, the emission estimated by fuel sold is in fact impossible to ensure consistency between neighbouring cities and provinces. On the other hand, the emission estimated by distance travelled is also impossible to acquire key activity data such as traffic volume, vehicle type and model, and road type in small towns. To solve the problem, we applied a hierarchical cluster analysis to separate town-by-town road patterns (clusters) based on a priori activity information including traffic volume, population, area, and branch road length obtained from small 151 towns. After identifying 10 road patterns, a rule building expert system was developed by visual basic application (VBA) to assort various unknown road patterns into one of 10 known patterns. The expert system was self-verified with original reference information and then objects in each homogeneous pattern were used to regress traffic volume based on the variables of population, area, and branch road length. The program was then applied to assign all the unknown towns into a known pattern and to automatically estimate traffic volumes by regression equations for each town. Further VKT (vehicle kilometer travelled) for each vehicle type in each town was calculated to be mapped by GIS (geological information system) and road transport emission on the corresponding road section was estimated by multiplying emission factors for each vehicle type. Finally all emissions from local branch roads in Gyeonggi Province could be estimated by summing up emissions from 1,902 towns where road information was registered. As a result of the study, the GHG average emission rate by the branch road transport was 6,101 kilotons of $CO_2$ equivalent per year (kt-$CO_2$ Eq/yr) and the total emissions from both main and branch roads was 24,152 kt-$CO_2$ Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.
To estimate level of genetic variation and genetic differentiation among populations of 3 populations in Abies koreana and 5 populations in Abies nephrolepis, 5 nSSR markers were analyzed. Except 1 locus where too many alleles were observed excessively, population genetic parameters were recalculated with 4 loci. Mean expected heterozygosities ($H_e$) were 0.292 in A. koreana and 0.220 in A. nephrolepis, respectively. In both species, positive fixation coefficient was estimated (F=0.065 for A. koreana and F=0.095 for A. nephrolepis), which suggests that there is an excess of homozygotes relative to Hardy-Weinberg expectations within populations. Relatively high degree of population differentiation was observed in A. koreana ($F_{ST}=0.063$). compared to that of A. nephrolepis ($F_{ST}=0.039$). From 3-level Hierarchical estimation of F-staticstics, only 4.9% of the genetic variation was allocated between species ($F_{PT}$), which suggested that most of genetic variation was shared between two species. On the basis of results from analysis of genetic relationships among populations, 2 populations of A. koreana (Mt. Halla and Mt. Deogyu) were genetically distinct from the populations of A. nephrolepis but a population of Mt. Jiri was allocated within a group of populations of A. nephrolepis. Populations of both species seemed to have undergone genetic drift due to gradual decrease in population size induced by global warming after the last glacier, which resulted in increase of homozygotes by inbreeding. It could be also postulated that these species might be diverged recently and It is likely that the two species have not fully speciated yet.
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