• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.1-10
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• 2005

This paper presents a technique for localization of a mobile robot using a single ultrasonic sensor. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, corners and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD (Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a physically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.410-427
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• 2009

This study aims to rethink the meaning of graphicacy, discuss the possible criteria to evaluate the level of graphicacy, and show how the graphicacy differs through different grades. First, it finds that as school grades advance, implicit information processing abilities, and conceptual information processing abilities were more required comparing to explicit information processing abilities, when interpreting graphic data. Secondly, the percentage of items which examinee showed a proficient level, decreased as school grades advanced. Thirdly, the graphicacy level of sixth graders was the status of being able to derive explicit information from pictorial maps and read implicit information in simple contour map or line graphs. Ninth graders were able to infer causal relationship between geographic phenomenons by utilizing graphic materials. Tenth graders could read graphic materials by utilizing simple knowledge and experience.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.116-127
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• 2002

A new approach to improve the speaker adaptation algorithm by means of the variable number of observation density functions for CDHMM speech recognizer has been proposed. The proposed method uses the observation density function with more than one mixture in each state to represent speech characteristics in detail. The number of mixtures in each state is determined by the number of frames and the determinant of the variance, respectively. The each MAP Parameter is extracted in every mixture determined by these two methods. In addition, the state segmentation method requiring speaker adaptation can segment the adapting speech more Precisely by using speaker-independent model trained from sufficient database as a priori knowledge. And the state duration distribution is used lot adapting the speech duration information owing to speaker's utterance habit and speed. The recognition rate of the proposed methods are significantly higher than that of the conventional method using one mixture in each state.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.1-12
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• 2003

In this paper, we Introduce the Unreal Tournament (UT) game and the Gamebots system. The former it a well-known 3D first-person action game and the latter is an intelligent agent research testbed based on UT And then we explain the design and implementation of KGBot, which is an intelligent non-player character deploying effectively within the 3D virtual environment provided by UT and the Gamebots system. KGBot is a bot client within the Gamebots System. KGBot accomplishes its own task to find out and dominate several domination points pro-located on the complex surface map of 3D virtual environment KGBot adopts UM-PRS as its control engine, which is a general BDI agent architecture. KGBot contains a hierarchical knowledge base representing its complex behaviors in multiple layers. In this paper, we explain details of KGBot's Intelligent behaviors, tuck af locating the hidden domination points by exploring the unknown world effectively. constructing a path map by collecting the waypoints and paths distributed over the world, and finding an optimal path to certain destination based on this path graph. Finally we analyze the performance of KGBot exploring strategy and control engine through some experiments on different 3D maps.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4766-4786
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• 2016

Looking for missing companions who are out of touch in public places might suffer a long and painful process. With the help of mobile crowdsourcing, the missing person's location may be reported in a short time. In this paper, we propose MissingFound, an assistant system that applies mobile crowdsourcing for finding missing companions. Discovering valuable users who have chances to see the missing person is the most important task of MissingFound but also a big challenge with the requirements of saving battery and protecting users' location privacy. A customized metric is designed to measure the probability of seeing, according to users' movement traces represented by WiFi RSSI fingerprints. Since WiFi RSSI fingerprints provide no knowledge of users' physical locations, the computation of probability is too complex for practical use. By parallelizing the original sequential algorithms under MapReduce framework, the selecting process can be accomplished within a few minutes for 10 thousand users with records of several days. Experimental evaluation with 23 volunteers shows that MissingFound can select out the potential witnesses in reality and achieves a high accuracy (76.75% on average). We believe that MissingFound can help not only find missing companions, but other public services (e.g., controlling communicable diseases).

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.12
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• pp.391-398
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• 2015

This paper devises a performance improvement and evaluation process of circuit minimization algorithms for mentorship education of distinguished informatics gifted secondary students. In the process, students learn that there are several alternative equivalent circuits for a target function and recognize the necessity for formalized circuit minimization methods. Firstly, they come at the concept of circuit minimization principle from Karnaugh Map which is a manual methodology. Secondly, they explore Quine-McCluskey algorithm which is a computational methodology. Quine-McCluskey algorithm's time complexity is high because it uses set operations. To improve the performance of Quine-McCluskey algorithm, we encourage them to adopt a bit-wise data structure instead of integer array for sets. They will eventually see that the performance achievement is about 36%. The ultimate goal of the process is to enlarge gifted students' interest and integrated knowledge about computer science encompassing electronic switches, logic gates, logic circuits, programming languages, data structures and algorithms.

• Journal of the Korean Solar Energy Society
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• v.36 no.1
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• pp.11-18
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• 2016

The local wind systems in the Pohang region were categorized into wind sectors. Still, thorough knowledge of wind resource assessment, wind environment analysis, and atmospheric environmental impact assessment was required since the region has outstanding wind resources, it is located on the path of typhoon, and it has large-scale atmospheric pollution sources. To overcome the resolution limitation of meteorological dataset and problems of categorization criteria of the preceding studies, the high-resolution wind resource map of the Korea Institute of Energy Research was used as time-series meteorological data; the 2-step method of determining the clustering coefficient through hierarchical clustering analysis and subsequently categorizing the wind sectors through non-hierarchical K-means clustering analysis was adopted. The similarity of normalized time-series wind vector was proposed as the Euclidean distance. The meteor-statistical characteristics of the mean vector wind distribution and meteorological variables of each wind sector were compared. The comparison confirmed significant differences among wind sectors according to the terrain elevation, mean wind speed, Weibull shape parameter, etc.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.351-359
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• 2022

In this paper, this app is an online learning tool web application that helps learners learn efficiently. It discusses how learners can improve their learning efficiency in these three aspects: retrieval practice, systematization, metacognition. Through this web service, learners can proceed with learning with a flash card-based retrieval practice. In this case, a method of managing a flash card in a form similar to a directory-file system using a composite pattern is described. Learners can systematically organize their knowledge by converting flash cards into a mind map. The color of the mind map varies according to the learner's learning progress, and learners can easily recognize what they know and what they do not know through color. In this case, it is proposed to build a deep learning model to improve the accuracy of an algorithm for determining and predicting learning progress.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.162-162
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• 2022

Stormwater management is an essential component of land-use planning and development. Due to the additional challenges posed by climate change and urbanization, various stormwater management schemes have been developed to limit flood damages and ease water quality concerns. Nature-based solutions (NBS) are increasingly used as cost-effective measures to manage stormwater runoff from various land uses. Specifically, constructed wetlands were already considered as socially acceptable green stormwater infrastructures that are widely used in different countries. There is a large collection of published literature regarding the effectiveness or efficiency of constructed wetlands in treating stormwater runoff; however, metadata analyses using bibliographic information are very limited or seldomly explored. This study was conducted to determine the trends of publication regarding stormwater treatment wetlands using a bibliometric analysis approach. Moreover, the research productivity of various countries, authors, and institutions were also identified in the study. The Web of Science (WoS) database was utilized to retrieve bibliographic information. The keywords ("constructed wetland*" OR "treatment wetland*" OR "engineered wetland*" OR "artificial wetland*") AND ("stormwater*" or "storm water*") were used to retrieve pertinent information on stormwater treatment wetlands-related publication from 1990 up to 2021. The network map of keyword co-occurrence map was generated through the VOSviewer software and the contingency matrices were obtained using the Cortext platform (www.cortext.net). The results obtained from this inquiry revealed the areas of research that have been adequately explored by past studies. Furthermore, the extensive collection of published scientific literature enabled the identification of existing knowledge gaps in the field of stormwater treatment wetlands.