• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.243-250
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• 2012

This paper proposes a 3D map-building algorithm using one LRF (Laser Range Finder) while a mobile robot is navigating on the slanted surface. There are several researches on 3D map buildings using the LRF. However most of them are performing the map building only on the flat surface. While a mobile robot is moving on the slanted surface, the view angle of LRF is dynamically changing, which makes it very difficult to build the 3D map using encoder data. To cope with this dynamic change of the view angle in build 3D map, IMU and balance filters are fused to correct the unstable encoder data in this research. Through the real navigation experiments, it is verified that the fusion of multiple sensors are properly performed to correct the slope angle of the slanted surface. The effectiveness of the balance filter are also checked through the hill climbing navigations.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2780-2785
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• 1997

Although KBANN(knowledge-based artificial neural network) has been shown to be more effective than other machine learning algorithms, KBANN doesn't have the theory refinement capability because the topology of the network can't be altered dynamically. Although TopGen algorithm was proposed to extend the ability of KABNN in this respect, it also had some defects due to the connection of hidden nodes from all input nodes and the use of beam search. An algorithm, which could solve this TopGen's defects by adding the hidden nodes connected from only related input nodes and using hill-climbing search with backtracking, is proposed.

• ETRI Journal
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• v.43 no.2
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• pp.260-271
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• 2021

This paper addresses Very large-scale integration (VLSI) placement optimization, which is important because of the rapid development of VLSI design technologies. The goal of this study is to develop a hybrid algorithm for VLSI placement. The proposed algorithm includes a sequential combination of a genetic algorithm and an evolutionary algorithm. It is commonly known that local search algorithms, such as random forest, hill climbing, and variable neighborhoods, can be effectively applied to NP-hard problem-solving. They provide improved solutions, which are obtained after a global search. The scientific novelty of this research is based on the development of systems, principles, and methods for creating a hybrid (combined) placement algorithm. The principal difference in the proposed algorithm is that it obtains a set of alternative solutions in parallel and then selects the best one. Nonstandard genetic operators, based on problem knowledge, are used in the proposed algorithm. An investigational study shows an objective-function improvement of 13%. The time complexity of the hybrid placement algorithm is O(N2).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11C
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• pp.1119-1126
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• 2007

In this paper, we examine the scheme that the CR (Cognitive Radio) user can coexist with primary user with obeying the concept of interference temperature proposed by FCC. Regarding to the capability of classifying the signals of primary user after the spectrum sensing, the interference temperature model can be discriminated by the ideal and generalized ones. And then, about each model, it can optimize the bandwidth and transmit power with satisfying predetermined capacity of CR user. Especially, it has been considered to allocate to CR user not to interfere to primary users for proper coexistence in conventional interference temperature multiple access technique, proposed by T. Clancy, but this paper proposes the scheme that considering QoS of not only primary users, but also CR user. The hill-climbing algorithm is employed to produce the bandwidth and transmit power subject to satisfying the required capacity.

• Journal of The Korean Digital Architecture Interior Association
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• v.11 no.3
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• pp.53-59
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• 2011

In creative design, it is necessary to understand the characteristic of architectural design. In the world of design problem, a distinction can be made between those that are well-defined and those that are ill-defined. Well-defined problems are those for which the ends or goal, are already prescribed and apparent, their solution requires the provision of appropriate means. For ill-defined problems, on the other hand, both the ends and the means of solution are unknown at the outset of the problem solving exercise, at least in their entirety. Most of design problems is ill-defined, which is unknown at the beginning of the problem solving exercise. In order to solve the design problem, Designers take advantage of the search methods of problem space, such as global-search-methods(depth-first-methods, breath-first-methods), local-search-methods(generate and test, heuristics, hill-climbing, reasoning) and visual thinking, which is represented through sketching. Sketching is a real part of design reasoning and it does so through a special kind of visual imagery. Also in the design problem solving it have been an important means of problem exploration and solution generation. By sketching, they represent images held in the mind as well as makes graphic images which help generate mental images of entity that is being designed. The search methods of problem space and a visual thinking have been crucially considered in the architectural design. The purpose of this paper is to explore the property of design by means of the pre-existed-experiment data and literature research. The findings will help design the architectural design for more creative results.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.42-47
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• 2010

Many contests by micro mouse was celebrated of which maze search algorithms performance are compared. That is used in various forms based on left(right) weight method, euclidean algorithm method, hill climbing method. However we feel uncomfortable to test algorithms performance through direct development of programs or hardwares as no software platform to test in maze search algorithms. In this research we develop of a platform for maze search algorithms that is easily to produce various forms of maze that are hard to be realized by hardware, to apply algorithms, and evaluate the seek time, operation count, steps and performance. The platform is consist of main layer, interface layer, user layer which has merit to apply and replace easily algorithms. We verified that the maze search algorithm can be applied even in the development and experiment of algorithm by evaluating and analyzing its performance through the experiment of platform.

• Journal of Korean Foot and Ankle Society
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• v.1 no.2
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• pp.89-94
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• 1997

The functional disabilities post arthrodesis of the ankle include difficulty in climbing inclined surface, such as hill, ramps, or stair even through without pain. There will be periankle joints arthrosis as time passes. Total ankle replacement permits remobilization, no need for prolonged immobilization. There will be no increas in the mechanical stress of the neiboring joint. Total ankle replacement has been proposed as an alternative to arthrodesis in the management of painful arthrosis of the tibiotalar joint recently. We performed 7 cases of replacement from 1990. 4. 1 to 1996. 7. 1 with 2-3 years follow up. A retrospective review was undertaken for 7 patients with the arthrosis of tibiotatar joint. The results were as following. 1. The clinical results according to the point system for ankle study evaluation were excellent in 2 cases, good in 4 cases, and fair 1 case. 2. The improvement was especially obvious in terms of pain and functional recovery. 3. Total ankle replacement especially unconstrained type seems quite good alternative to arthrodesis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.1
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• pp.37-44
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• 2014

For testing a two-wheeled vehicle's per-charge range, this study conducted road and chassis dynamometer driving tests. Three typical road routes within Daejeon Metropolitan City were selected for the road-driving test. In the case of CVS-40 mode driving tests using a chassis dynamometer, various road-loading conditions were set. In this study, two-wheeled electric vehicles' per charge range on the road was confirmed through testing, and the range and energy consumption efficiency depending on various chassis dynamometer road load settings were measured. Then, the results of the actual road driving tests were compared with those of the chassis dynamometer driving tests, and road load settings that yielded per-charge range testing results similar to those under actual road driving conditions in the chassis dynamometer experiments were studied.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.92-98
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• 2017

Data clustering determines a group of patterns using similarity measure in a dataset and is one of the most important and difficult technique in data mining. Clustering can be formally considered as a particular kind of NP-hard grouping problem. K-means algorithm which is popular and efficient, is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. This method is also not computationally feasible in practice, especially for large datasets and large number of clusters. Therefore, we need a robust and efficient clustering algorithm to find the global optimum (not local optimum) especially when much data is collected from many IoT (Internet of Things) devices in these days. The objective of this paper is to propose new Hybrid Simulated Annealing (HSA) which is combined simulated annealing with K-means for non-hierarchical clustering of big data. Simulated annealing (SA) is useful for diversified search in large search space and K-means is useful for converged search in predetermined search space. Our proposed method can balance the intensification and diversification to find the global optimal solution in big data clustering. The performance of HSA is validated using Iris, Wine, Glass, and Vowel UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KSAK (K-means+SA+K-means) and SAK (SA+K-means) are better than KSA(K-means+SA), SA, and K-means in our simulations. Our method has significantly improved accuracy and efficiency to find the global optimal data clustering solution for complex, real time, and costly data mining process.

• Journal of KIISE
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• v.43 no.4
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• pp.480-488
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• 2016

Search-Based Software Testing (SBST) is an effective technique for test data generation on large domain size. Although the performance of SBST seems to be affected by the structural characteristics of Software Under Test (SUT), studies for the comparison of SBST techniques considering structural characteristics are rare. In addition to the comparison study for SBST, we analyzed the best algorithm with different structural characteristics of SUT. For the generalization of experimental results, we automatically generated 19,800 SUTs by combining four metrics, which are expected to affect the performance of SBST. According to the experiment results, Genetic algorithm showed the best performance for SUTs with high complexity and test data evaluation with count ${\leq}20,000$. On the other hand, the genetic simulated annealing and the simulated annealing showed relatively better performance for SUTs with high complexity and test data evaluation with count ${\geq}50,000$. Genetic simulated annealing, simulated annealing and hill climbing showed better performance for SUTs with low complexity.