• Smart Structures and Systems
• /
• v.21 no.4
• /
• pp.407-420
• /
• 2018

In structural health monitoring, it is meaningful to comprehensively utilize accelerometers and strain gauges to obtain the modal information of a structure. In this paper, a modal estimation theory is proposed, in which the displacement modes of the locations without accelerometers can be estimated by the strain modes of selected strain gauge measurements. A two-stage sensor placement method, in which strain gauges are placed together with triaxial accelerometers to obtain more structural displacement mode information, is proposed. In stage one, the initial accelerometer locations are determined through the combined use of the modal assurance criterion and the redundancy information. Due to various practical factors, however, accelerometers cannot be placed at some of the initial accelerometer locations; the displacement mode information of these locations are still in need and the locations without accelerometers are defined as estimated locations. In stage two, the displacement modes of the estimated locations are estimated based on the strain modes of the strain gauge locations, and the quality of the estimation is seen as a criterion to guide the selection of the strain gauge locations. Instead of simply placing a strain gauge at the midpoint of each beam element, the influence of different candidate strain gauge positions on the estimation of displacement modes is also studied. Finally, the modal assurance criterion is utilized to evaluate the performance of the obtained multitype sensor placement. A bridge benchmark structure is used for a numerical investigation to demonstrate the effectiveness of the proposed multitype sensor placement method.

• Journal of the Korean Society of Safety
• /
• v.27 no.5
• /
• pp.148-157
• /
• 2012

Reliability-based design optimization (RBDO) problem is usually formulated as an optimization problem to minimize an objective function subjected to probabilistic constraint functions which may include deterministic design variables as well as random variables. The challenging task is that, because the probability models of the random variables are often assumed based on limited data, there exists a possibility of selecting inappropriate distribution models and/or model parameters for the random variables, which can often lead to disastrous consequences. In order to select the most appropriate distribution model from the limited observation data as well as model parameters, this study takes into account a set of possible candidate models for the random variables. The suitability of each model is then investigated by employing performance and risk functions. In this regard, this study enables structural design optimization and fitness assessment of the distribution models of the random variables at the same time. As the first paper of a two-part series, this paper describes a new design method considering probability model uncertainties. The robust performance of the proposed method is presented in Part 2. To demonstrate the effectiveness of the proposed method, an example of ten-bar truss structure is considered. The numerical results show that the proposed method can provide the optimal design variables while guaranteeing the most desirable distribution models for the random variables even in case the limited data are only available.

• Journal of Navigation and Port Research
• /
• v.36 no.1
• /
• pp.51-58
• /
• 2012

In spite of today's rapid growth of world cruise industry, little academic attention has yet been given to the decision making problems for cruise operations. This research deals with strategic cruise itinerary planning that any cruise company should face. Increasing demands for international itineraries and redeployments of cruise ships are adding complexity to the itinerary planning. A slight modification of the conventional PERT/CPM network is adopted. to cope with this complexity systematically. By this, the concept of candidate itinerary network is suggested for each cruise ship. To integrate these candidate itinerary networks for each ship in a single framework, an integer programming model has been developed to find the optimal itinerary planning for any fleet of cruise ships. A numerical example, based on real cruise itinerary practices, is tested to validate and interpret the model.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.5
• /
• pp.265-270
• /
• 2010

Reinforcement learning performs learning through interacting with trial-and-error in dynamic environment. Therefore, in dynamic environment, reinforcement learning method like TD-learning and TD(${\lambda}$)-learning are faster in learning than the conventional stochastic learning method. However, because many of the proposed reinforcement learning algorithms are given the reinforcement value only when the learning agent has reached its goal state, most of the reinforcement algorithms converge to the optimal solution too slowly. In this paper, we present GDRLS algorithm for finding the shortest path faster in a maze environment. GDRLS is select the candidate states that can guide the shortest path in maze environment, and learn only the candidate states to find the shortest path. Through experiments, we can see that GDRLS can search the shortest path faster than TD-learning and TD(${\lambda}$)-learning in maze environment.

• Smart Media Journal
• /
• v.4 no.4
• /
• pp.18-23
• /
• 2015

In this paper, we propose a method for detecting the number of clusters. This method can improve the performance of a gaussian mixture model function in conventional markov random field method by using the tensor voting. The key point of the proposed method is that extracts the number of the center through the continuity of saliency map of the input data of the tensor voting token. At first, we separate the foreground and background region candidate in a given natural images. After that, we extract the appropriate cluster number for each separate candidate regions by applying the tensor voting. We can make accurate modeling a gaussian mixture model by using a detected number of cluster. We can return the result of natural binary text image by calculating the unary term and the pairwise term of markov random field. After the experiment, we can confirm that the proposed method returns the optimal cluster number and text binarization results are improved.

• Korean Journal of Construction Engineering and Management
• /
• v.10 no.5
• /
• pp.148-157
• /
• 2009

When an emergency situation happens in buildings, the top priority is to ensure the occupant from danger as soon as possible. Achieving that goal is a multifaceted and difficult task. However, current evacuation systems have many deficiencies in dealing with the emergency in multi-level structures. The shortage of abilities to continuously update database, predict the future situation and provide the information to users with contextual information is the limit in current systems. Thus, it is very crucial to introduce Evacuation Information System (EIS), which is able to respond quickly to the emergency, and transfer the information to both the administrator and the occupant. The main purpose of this paper is to build EIS on the basis of the indoor Geographical Information System (GIS). When the emergency happens, EIS gives the instruction to Emergency Response Model (ERM) at once. ERM carries out the order and calculates the optimal evacuation routes, then sends the result to EIS. At last, EIS transmits evacuation messages to the occupant who implements evacuation plan. This paper highlights the benefits of EIS in two aspects. One is that EIS can update the data continuously to support evacuation strategy-making. The other is that it can transmit evacuation messages to both the administrator and the occupant.

• Journal of Intelligence and Information Systems
• /
• v.10 no.3
• /
• pp.1-10
• /
• 2004

In this paper, a new character segmentation algorithm of machine printed character recognition is proposed. The new approach of the proposed character segmentation algorithm overcomes the weak points of both feature-based approaches and recognition-based approaches in character segmentation. This paper defines side profiles of touching characters. The character segmentation algorithm gives a candidate single character in touching characters by side profiles, without any help of character recognizer. It segments touching characters and decides the candidate single character by side profiles. This paper also defines cutting cost, which makes the proposed character segmentation find an optimal segmenting path. The performance of the proposed character segmentation algorithm in this paper has been obtained using a real envelope reader system, which can recognize addresses in U.S. mail pieces and sort the mail pieces. 3359 mail pieces were tested. The improvement was from $68.92\%\;to\;80.08\%$ by the proposed character segmentation.

• Journal of KIISE:Information Networking
• /
• v.30 no.3
• /
• pp.424-436
• /
• 2003

In this paper, we propose the Centroid-based Backbone Core Tree(CBCT) generation algorithm for the shared tree-based IP multicasting. The proposed algorithm is based on the Core Based Tree(CBT) protocol. Despite the advantages over the source-based trees in terms of scalability, the CBT protocol still has the following limitations; first, the optimal core router selection is very difficult, and second, the multicast traffic is concentrated near a core router. The Backbone Core Tree(BCT) protocol, as an extension of the CBT protocol has been proposed to overcome these limitations of the CBT Instead of selecting a specific core router for each multicast group, the BCT protocol forms a backbone network of candidate core routers which cooperate with one another to make multicast trees. However, the BCT protocol has not mentioned the way of selecting candidate core routers and how to connect them. The proposed CBCT generation algorithm employs the concepts of the minimum spanning tree and the centroid. For the performance evaluation of the proposed algorithm, we showed the performance comparison results for both of the CBT and CBCT protocols.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.3
• /
• pp.360-366
• /
• 2008

The initial fuzzy partitions in fuzzy rule-based classification systems are determined by considering the domain region of each attribute with the given data, and the optimal classification boundaries within the fuzzy partitions can be discovered by tuning their parameters using various learning processes such as neural network, genetic algorithm, and so on. In this paper, we propose a selection method for fuzzy partition based on statistical information to maximize the performance of pattern classification without learning processes where statistical information is used to extract the uncertainty regions (i.e., the regions which the classification boundaries in pattern classification problems are determined) in each input attribute from the numerical data. Moreover the methods for extracting the candidate rules which are associated with the partition intervals generated by statistical information and for minimizing the coupling problem between the candidate rules are additionally discussed. In order to show the effectiveness of the proposed method, we compared the classification accuracy of the proposed with those of conventional methods on the IRIS and New Thyroid Cancer data. From experimental results, we can confirm the fact that the proposed method only considering statistical information of the numerical patterns provides equal to or better classification accuracy than that of the conventional methods.

• Journal of the Korea Convergence Society
• /
• v.10 no.11
• /
• pp.71-77
• /
• 2019

This paper defines a multi-selection knapsack problem and presents an algorithm for seeking its optimal solution. Multi-selection means that all members of the particular group be selected or excluded. Our branch-and-bound algorithm introduces a simplex containing the feasible region of the original problem to exploit the fact that the most tightly underestimating function on the simplex is linear. In bounding operation, the subproblem defined over the candidate simplex is minimized. During the branching process the candidate simplex is splitted into two one-less dimensional subsimplices by being projected onto two hyperplanes. The approach of this paper can be applied to solving the global minimization problems under various types of the knapsack constraints.