The application of non-parametric statistical techniques to an ALARA programme

For the cost-effective reduction of occupational radiation dose (ORD) at nuclear power plants, it is necessary to identify what are the processes of repetitive high ORD during maintenance and repair operations. To identify the processes, the point values such as mean and median are generally used, but they sometimes lead to misjudgment since they cannot show other important characteristics such as dose distributions and frequencies of radiation jobs. As an alternative, the non-parametric analysis method is proposed, which effectively identifies the processes of repetitive high ORD. As a case study, the method is applied to ORD data of maintenance and repair processes at Kori Units 3 and 4 that are pressurised water reactors with 950 MWe capacity and have been operating since 1986 and 1987 respectively, in Korea and the method is demonstrated to be an efficient way of analysing the data.     

Analysis of radiation workers' dose records in the Korean National Dose Registry

Data are presented on the externally received personal dose equivalent for radiation workers who used the Korea Radioisotope Association's personal monitoring and dose record keeping service since 1984, and provide initial statistics on Korean workers who have been exposed to ionising radiation in different occupations. The total number of workers registered during the period of 1984 to 1999 was 64,518. The number increased steadily and the accumulated dose also increased. The proportion of radiation workers by occupation was 38.4% for nuclear power plants, 20.3% for industrial organisations and 12.4% for non-destructive industry. The annual collective dose of radiation workers was 31.72 man.Sv in 1999. The mean annual dose by sex was 1.49 mSv for males and 0.56 mSv for females and the mean annual dose for a worker was 1.41 mSv with the highest mean dose being received by non-destructive industry (3.53 mSv). Very few workers (0.8%) received more than 20 mSv (2 rem) and only one more than 50 mSv, the legal limit for an annual dose increase. There has been a steady decline in the mean dose since 1984, showing a significant decrease in dose with time (p<0.001). The data showed that radiation protection in Korea was improving, though annual doses were still higher than other countries.     

A vehicle routing problem solved by using a hybrid genetic algorithm

The main purpose of this study is to find out the best solution of the vehicle routing problem simultaneously considering heterogeneous vehicles, double trips, and multiple depots by using a hybrid genetic algorithm. This study suggested a mathematical programming model with a new numerical formula which presents the amount of delivery and sub-tour elimination. This model gives an optimal solution by using OPL-STUDIO(ILOG CPLEX). This study also suggests a hybrid genetic algorithm (HGA) which considers the improvement of generation for an initial solution, three different heuristic processes, and a float mutation rate for escaping from the local solution in order to find the best solution. The suggested HGA is also compared with the results of a general genetic algorithm and existing problems suggested by Eilon and Fisher. We found better solutions rather than the existing genetic algorithms.     

Analysis and avoidance of singularities for local G 1 surface interpolation of Bézier curve network with 4-valent nodes

We propose a local method of constructing piecewise G ¹ Bézier patches to span a Bézier curve network with odd- and 4-valent node points. We analyze all possible singular cases of the G ¹ condition that is to be met by the curve network interpolation and propose a new G ¹ continuity condition using linear and quartic scalar weight functions. Using this condition, a curve network can be interpolated without modification at 4-valent nodes with two collinear tangent vectors, even in the presence of singularities. We demonstrate our approach by generating G ¹ surfaces over the curve network which includes singularities at its node vertices and edges.     

Neural network control for position tracking of a two-axis inverted pendulum system: experimental studies.

In this paper, experimental studies of a decentralized neural network control scheme of the reference compensation technique applied to control a 2-degrees-of-freedom (2-DOF) inverted pendulum on an x - y plane are presented. Each axis is controlled by two separate neural network controllers to have a decoupled control structure. Neural network controllers are applied not only to balance the angle of pendulum, but also to control the position tracking of the cart. The decoupled control structure can compensate for uncertainties and cancel coupling effects. Especially, a circular trajectory tracking task is tested for position tracking control of the cart while maintaining the angle of the pendulum. Experimental result shows that position control of the inverted pendulum and cart is successful.     

Energy-based control of a haptic device using brakes.

This paper proposes an energy-based control method of a haptic device with electric brakes. Unsmooth motion is frequently observed in a haptic system using brakes during a wall-following task. Since it is generally known that a haptic system using brakes is passive due to brake's characteristics, its energy behavior has seldom been investigated. However, force distribution at the end effector reveals that the unsmooth motion of a haptic system using brakes represents active behavior of the system in the specific direction. A force control scheme is proposed that computes the gain for smooth motion by considering the energy behavior of a system. Experiments show that smooth wall following is possible with a proposed force control scheme.     

Cancer classification using ensemble of neural networks with multiple significant gene subsets

Molecular level diagnostics based on microarray technologies can offer the methodology of precise, objective, and systematic cancer classification. Genome-wide expression patterns generally consist of thousands of genes. It is desirable to extract some significant genes for accurate diagnosis of cancer because not all genes are associated with a cancer. In this paper, we have used representative gene vectors that are highly discriminatory for cancer classes and extracted multiple significant gene subsets based on those representative vectors respectively. Also, an ensemble of neural networks learned from the multiple significant gene subsets is proposed to classify a sample into one of several cancer classes. The performance of the proposed method is systematically evaluated using three different cancer types: Leukemia, colon, and B-cell lymphoma.     

Efficient Monitoring Algorithm for Fast News Alerts

Recently, there has been a dramatic increase in the use of XML data to deliver information over the Web. Personal Weblogs, news Web sites, and discussion forums are now publishing RSS feeds for their subscribers to retrieve new postings. As the popularity of personal Weblogs and RSS feeds grows rapidly, RSS aggregation services and blog search engines have appeared, which try to provide a central access point for simpler access and discovery of new content from a large number of diverse RSS sources. In this paper, we study how the RSS aggregation services should monitor the data sources to retrieve new content quickly using minimal resources and to provide its subscribers with fast news alerts. We believe that the change characteristics of RSS sources and the general user access behavior pose distinct requirements that make this task significantly different from the traditional index refresh problem for Web search engines. Our studies on a collection of 10,000 RSS feeds reveal some general characteristics of the RSS feeds and show that, with proper resource allocation and scheduling, the RSS aggregator provides news alerts significantly faster than the best existing approach.     

Finite element analyses and verifying tests for a shock-absorbing effect of a pad in a spent fuel storage cask

A spent fuel storage cask is required to prove the safety of its canister under a hypothetical accidental drop condition which means that the canister is assumed to be free dropped on to a pad of the storage cask during the loading of the canister into a storage cask. In this paper, finite element analyses and verifying tests for a shock-absorbing effect of a pad in a spent fuel dry storage cask were carried out to improve the structural integrity of the canister under a hypothetical accidental drop condition. The pad of the storage cask was originally designed as cylindrical steel structure filled with concrete. The pad was modified by using the structure composed of steel and polyurethane-foam instead of the quarter of the upper concrete as an impact limiter. The effects of the shape and the thickness of the steel structure and the density of the polyurethane-foam which was used in between steel structures were studied. As the optimized pad of a spent fuel dry storage cask, the quarter of the upper concrete was replaced with 12 mm thick circular steel structure and polyurethane-foam whose density was 85 kg/m³. The drop tests of a 1/3 scale model for the canister on to the original pad and the optimized pad were conducted. The effect of the pad structure was evaluated from the drop tests. The optimized pad has a greater shock-absorbing effect than the original pad. In order to verify the analysis results, strains and accelerations in the time domain by the analytical methods were compared with those by a test. The numerical method of simulating the free drop test for a dry storage cask was verified and the numerical results were found to be reliable.