• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.399-404
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• 2010

In this paper, we propose a method for precision improvement based on core clusters and term proximity. The method is composed by three steps. The initial retrieval documents are clustered based on query term combination, which occurred in the document. Core clusters are selected by using proximity between query terms. Then, the documents in core clusters are reranked based on context information of query. On TREC AP test collection, experimental results in precision at the top documents(P@100) show that the proposed method improved 11.2% over the language model.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.37-42
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• 2012

The pseudo relevance feedback suggests that frequent words at the top documents are related to initial query. However, the main drawback associated with the term frequency method is the fact that it relies on feature independence, and disregards any dependencies that may exist between words in the text. In this paper, we propose query expansion based on word graph using term proximity. It supplements term frequency method. On TREC WT10g test collection, experimental results in MAP(Mean Average Precision) show that the proposed method achieved 6.4% improvement over language model.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.189-194
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• 2012

In this paper, we propose a query expansion method based on word graphs using pseudo-relevant and pseudo non-relevant documents to achieve performance improvement in information retrieval. The initially retrieved documents are classified into a core cluster when a document includes core query terms extracted by query term combinations and the degree of query term proximity. Otherwise, documents are classified into a non-core cluster. The documents that belong to a core query cluster can be seen as pseudo-relevant documents, and the documents that belong to a non-core cluster can be seen as pseudo non-relevant documents. Each cluster is represented as a graph which has nodes and edges. Each node represents a term and each edge represents proximity between the term and a query term. The term weight is calculated by subtracting the term weight in the non-core cluster graph from the term weight in the core cluster graph. It means that a term with a high weight in a non-core cluster graph should not be considered as an expanded term. Expansion terms are selected according to the term weights. Experimental results on TREC WT10g test collection show that the proposed method achieves 9.4% improvement over the language model in mean average precision.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.31-36
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• 2014

Social network services(SNS) including Twitter and Facebook are good resources to extract various issues like public interest, trend and topic. This paper proposes a method to extract query-related issues by calculating relatedness between terms in Twitter. As a term that frequently appears near query terms should be semantically related to a query, we calculate term relatedness in retrieved documents by summing proximity that is proportional to term frequency and inversely proportional to distance between words. Then terms, relatedness of which is bigger than threshold, are extracted as query-related issues, and our system shows those issues with a connected network. By analyzing single transitions in a connected network, compound words are easily obtained.

• Journal of Korean Elementary Science Education
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• v.23 no.3
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• pp.199-207
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• 2004

Elementary science curriculum is designed to be closely-related magnetism with electricity in a physics domain and this paper explored whether elementary school students have recognized of relationships between them and whether there are any trends in the degree of recognition by grades. The elementary students of 3rd to 6th grade (total 154 persons) in a school in a local city participated in the experiment. Two forms of questionnaire were administrated to each grades. In the first questionnaire about magnetism, students were asked to rank the physics terms as the degree of proximity into magnetism and to write briefly the reason. In the second questionnaire about electricity, students were asked to do the same routine. The closer to the central term in the diagram, the lower score were given and the terms were classified as closely related to magnetism, electricity and the rest. Calculated the response frequency and averaged by the ranked terms, it was examined that the scores of proximity in how students closely rated conception to magnetism and electricity. The result said that the upper grades students showed the degree of proximity with magnetism and electricity as closely. Therefore, the sequence of comprehension of magnetism and electricity concept, which was found in the elementary school curriculum, seems to be found in the elementary students＇ recognitions by grades.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.80-81
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• 2007

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.2071-2078
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• 2009

In this paper, we proposed a non-contact respiration measurement system with ultrasonic proximity sensor. Ultrasonic proximity sensor approach of respiration measurement which respiration signatures and rates can be derived in real-time for long-term monitoring is presented. 240 kHz ultrasonic sensor has been applied for the proposed measurement system. The time of flight of sound wave between the transmitted signal and received signal have been used for a respiration measurement from abdominal area. Respiration rates measured with the ultrasonic proximity sensor were compared with those measured with standard techniques on 5 human subjects. Accurate measurement of respiration rate is shown from the 50 cm measurement distance. The data from the method comparison study is used to confirm the performance of the proposed measurement system. The current version of respiratory rate detection system using ultrasonic can successfully measure respiration rate. The proposed measurement method could be used for monitoring unconscious persons from a relatively close range, avoiding the need to apply electrodes or other sensors in the correct position and to wire the subject to the monitor. Monitoring respiration using ultrasonic sensor offers a promising possibility of non-contact measurement of respiration rates. Especially, this technology offers a potentially inexpensive implementation that could extend applications to consumer home-healthcare and mobile-healthcare products. Further advances in the sensor design, system design and signal processing can increase the range of the measurement and quality of the rate-finding for broadening the potential application areas of this technology.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.883-886
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• 2016

본 논문에서는 장기투약자의 복약 관리 시스템 개발의 기초 연구로 Textile proximity pressure sensor를 개발하였고, 약통의 무게 감지를 통하여 약의 복용 여부를 판별하는 연구를 수행하였다. 실험은 총 2가지로, 약의 개수에 따른 baseline검출 실험과 약 한알의 무게 도출 실험을 수행하였다. 잡음을 제거하기 위해 5 point의 이동평균필터(MAF: Moving average filter)를 적용하였다. 본 논문을 통해 얻은 결과는 차후 장기 투약이 필요한 환자로 하여금 규칙적으로 약을 복용하도록 하여 만성질환의 완치율을 높이는 데 기여할 수 있을 것으로 판단된다.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.451-462
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• 2019

Document-term frequency matrix is a type of data used in text mining. This matrix is often based on various documents provided by the objects to be analyzed. When analyzing objects using this matrix, researchers generally select only terms that are common in documents belonging to one object as keywords. Keywords are used to analyze the object. However, this method misses the unique information of the individual document as well as causes a problem of removing potential keywords that occur frequently in a specific document. In this study, we define data that can overcome this problem as proximity data. We introduce twelve methods that generate proximity data and cluster the objects through two clustering methods of multidimensional scaling and k-means cluster analysis. Finally, we choose the best method to be optimized for clustering the object.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.3-10
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• 2014

Millimeter wave (mmWave) has attracted great interest recently and the necessity of Millimeter Mobile Broadband (MMB) system has appeared based on the 4 Generation Long Term Evolution-Advanced (LTE-A) Specification. Currently, there are many studies about the mmWave communication channel. And it is subject of interest to analyze the performance in MMB channel environments. In this paper, we design the MMB system for 5th Generation mobile communication and propose channel models through the analysis of the mmWave propagation characteristics. Also, we have analyzed the performance of the MMB system of 28 GHz band in MMB channel environments.