• MALSORI
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• no.64
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• pp.137-153
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• 2007

The pronunciation lexicon of a continuous speech recognition system should contain enough pronunciation variations to be used for building a search space large enough to contain a correct path, whereas the size of the pronunciation lexicon needs to be constrained for effective decoding and lower perplexities. This paper describes a procedure for selecting pronunciation variations to be included in the lexicon based on the frequencies of the corresponding phonetic rules observed in the training corpus. Likelihood of a phonetic rule's application is estimated using the observation frequency of the rule and is used to control the construction of a pronunciation lexicon. Experiments with various pronunciation lexica show that the proposed method is helpful to improve the speech recognition performance.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.232-241
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• 2014

This paper proposes an underwater localization algorithm using probabilistic object recognition. It is organized as follows; 1) recognizing artificial objects using imaging sonar, and 2) localizing the recognized objects and the vehicle using EKF(Extended Kalman Filter) based SLAM. For this purpose, we develop artificial landmarks to be recognized even under the unstable sonar images induced by noise. Moreover, a probabilistic recognition framework is proposed. In this way, the distance and bearing of the recognized artificial landmarks are acquired to perform the localization of the underwater vehicle. Using the recognized objects, EKF-based SLAM is carried out and results in a path of the underwater vehicle and the location of landmarks. The proposed localization algorithm is verified by experiments in a basin.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.6
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• pp.17-24
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• 1994

This paper is a study on Korean word recognition and suggest the method that stabilizes the state-transition in the HMM by applying the `inertia' to the feature vector sequences. In order to reduce the quantized distortion considering probability distribution of input vectors, we used SOFM, an unsupervised learning method, as a vector quantizer, By applying inertia to the feature vector sequences, the overlapping of probability distributions for the response path of each word on the self organizing feature map can be reduced and the state-transition in the Hmm can be Stabilized. In order to evaluate the performance of the method, we carried out experiments for 50 DDD area names. The results showed that applying inertia to the feature vector sequence improved the recognition rate by 7.4% and can make more HMMs available without reducing the recognition rate for the SOFM having the fixed number of neuron.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.19-24
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• 2011

This paper presents a method about amorphous obstacles avoidance for local path planning in the two-dimensional sensor environment. In particular, the proposed method is extended from some of the recent studies about a point obstacle avoidance. In the paper, repulsive forces of two types are proposed in order that the robot avoids from the amorphous obstacle with various size and form. A judgment of curvatures in the proposed method simplifies the recognition of obstacles to make the path-planning efficient. In addition, the line of sight(LOS) and the range of recognition are considered in the environment. By simulation results, the proposed method for amorphous obstacle avoidance shows better performance than the related existing method and we confirmed advantages of proposed method.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.89-97
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• 2023

In this paper, we propose factors that make log analysis difficult and design technique for detecting various objects embedded in the logs which helps in the subsequent analysis. In today's IT systems, logs have become a critical source data for many advanced AI analysis techniques. Although logs contain wealth of useful information, it is difficult to directly apply techniques since logs are semi-structured by nature. The factors that interfere with log analysis are various objects such as file path, identifiers, JSON documents, etc. We have designed a BERT-based object pattern recognition algorithm for these objects and performed object identification. Object pattern recognition algorithms are based on object definition, GROK pattern, and regular expression. We find that simple pattern matchings based on known patterns and regular expressions are ineffective. The results show significantly better accuracy than using only the patterns and regular expressions. In addition, in the case of the BERT model, the accuracy of classifying objects reached as high as 99%.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1232-1239
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• 2009

This paper proposes an exploration strategy to efficiently find a specific place in large unknown environments with wall-following based path planning. Many exploration methods proposed so far showed good performance but they focused only on efficient planning for modeling unknown environments. Therefore, to successfully accomplish the room finding task, two additional requirements should be considered. First, suitable path-planning is needed to recognize the room number. Most conventional exploration schemes used the gradient method to extract the optimal path. In these schemes, the paths are extracted in the middle of the free space which is usually far from the wall. If the robot follows such a path, it is not likely to recognize the room number written on the wall because room numbers are usually too small to be recognized by camera image from a distance. Second, the behavior which re-explores the explored area is needed. Even though the robot completes exploration, it is possible that some rooms are not registered in the constructed map for some reasons such as poor recognition performance, occlusion by a human and so on. With this scheme, the robot does not have to visit and model the whole environment. This proposed method is very simple but it guarantees that the robot can find a specific room in most cases. The proposed exploration strategy was verified by various experiments.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.5
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• pp.295-301
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• 2017

Recently, autonomous navigation technology, obstacle recognition, and obstacle collision avoidance technology are actively being developed for an unmanned surface vehicle (USV). The path to move from the current location to the destination should be planned, in order for an USV to autonomously operate safely to its destination. The dynamic window approach (DWA) is a well-known navigation scheme as a local path planning. The DWA algorithm derives the linear velocity and angular velocity by evaluating the destination direction, velocity, and distance from the obstacle. However, because DWA algorithm does not consider tracking the path, when using only the DWA algorithm, the ship may navigate away from the path line after avoiding obstacles. In this paper, we propose an improved DWA algorithm that can follow path line. And we implemented the simulation and compared the existing DWA algorithm with the improved DWA algorithm proposed in this paper. As a result, it is confirmed that the proposed DWA algorithm follows the path line better.

• Journal of agricultural medicine and community health
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• v.41 no.2
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• pp.63-74
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• 2016

Objectives: We surveyed the awareness and current status of using fumigant carbon disulfide for exterminate Curculio sikkimensis among chestnut farmers in Chungnam Province to suggest directions for health education and public relations. Methods: We designed questionnaires to evaluate recognition of fumigant carbon disulfide. We conducted a questionnaire survey to assess recognition and recognition level of fumigant carbon disulfide by the study variables. Results: The recognition status for fumigant carbon disulfide was 74.5%, but the recognition level was low (know well 27.5%). The path of recognition was 45.1% and 15.7% for neighbor and rural technology center, respectively. The recognition status for warning label of fumigant carbon disulfide was 52.9%. Recognition for warning label of fumigant carbon disulfide was tended to increase with high educational attainment, bigger owning land area. Recognition on the content of warning label were 29.4%, 27.5%, 21.6%, and 21.6% for inflammability, toxicity, hazard, and explosiveness, respectively. Using personal protection equipment was tended to increase with the high status of awareness on fumigant carbon disulfide. Conclusions: Health education programs for using fumigant carbon disulfide are needed for chestnut farmers. In addition, publicity information activities about prevention and protection of carbon disulfide poisoning are needed for high risk farmers.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.85-92
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• 2005

This paper describes the recognition method of small-obstacles using a camera for a mobile robot in indoor environment. The technique of image processing using a camera has been widely used for an automaton of industrial system, an inspection of inferior goods, a lookout of an invader, and a vision sensor of intelligent robot. Mobile robot could meet small-obstacles such as a small plastic bottle of about 0.5 l in quantity, a small box of $7{\times}7{\times}7cm^3$ in volume, and so on in its designated path, and could be disturbed by them in the locomotion of a mobile robot. So, it is necessary to research on the recognition of small-obstacles using a camera and program. In this paper, 2-D image processing algorism and method fur recognition of small-obstacles using a camera for a mobile robot in indoor environment was developed. The characteristic test of the developed program to confirm the recognition of small-obstacles was performed. It is shown that the developed program could judge the size and the position of small-obstacles accurately.

• Journal of the Korean Home Economics Association
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• v.31 no.3
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• pp.29-46
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• 1993

The purpose of this study were to investigate the relation between home management ability and family life satisfaction of home makers, and to find out variables which influence them. The data were collected though the questionnaire whose respondent were 408 home makers in Kwang Ju and Kang Reung. The data were analyzed by various statistical method such as Cronbach's coefficient, factor analysis, frequency, percentage, mean, F-test, t-test, Duncan's multiple range test, regression analysis and path analysis. The results were as follow. 1. Home management ability score showed 68.5. Influential variables on home management ability were the level of education (husband and wife), occupation of husband and income as sociodemographic variables, and degree of resourcefulness recognition and of communication as psychological variables. 2. Family life satisfaction score showed 74.6. Influential variables on home management ability were the level of education (husband), occupation of husband and income as sociodemographic variables, and degree of resourcefulness recognition, of communication and of stress recognition as psychological variables. 3. The degree of communication was the highest influential variable to have influence on family life satisfaction. And the degree of resourcefulness recognition, of stress recognition, occupation of husband and wife, level of education(husband), number of children were variables to have directly and/or indirectly influence on family life satisfaction.