• The Journal of Korean Association of Computer Education
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• v.16 no.2
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• pp.61-68
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• 2013

SNS is a social networking service that helps people to have a two-way communication, manage their personal relationships and share information. The domestic and international SNS markets have attained a steady growth, and their growth is being more accelerated recently. Under these circumstances, immature students are more likely to show negative cyber behavior. This study attempted to analyze the relationship between the use of SNS, motives of SNS use, the use of active SNS functions, SNS-dependency and views in SNS and negative SNS behaviors among elementary and middle school students. For this, negative cycber behaviors are classified into four stages depending on the severity, for each of which distribution of factors is investigated and the combination of factors to determine each stage is obtained through association rule analysis. As a result, it is found that 85% of the students rarely show negative cyber behaviors, stealing personal information and contacting with strangers are the most frequent negative behaviors, and students with a great dependency on SNS are highly probable to show negative behaviors.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.939-948
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• 2012

The most widely used data mining technique is to explore association rules. This technique has been used to find the relationship between items in a massive database based on the interestingness measures such as support, confidence, lift, etc. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control.In general, association rule technique generates the rule, 'If A, then B.', whereas negative association rule technique generates the rule, 'If A, then not B.', or 'If not A, then B.'. We can determine whether we promote other products in addition to promote its products only if we add negative association rules to existing association rules. In this paper, we proposed the negatively attributable and pure confidence to overcome the problems faced by negative association rule technique, and then we checked three conditions for interestingness measure. The comparative studies with negative confidence, negatively pure confidence, and negatively attributable and pure confidence are shown by numerical examples. The results show that the negatively attributable and pure confidence is better than negative confidence and negatively pure confidence.

• Management & Information Systems Review
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• v.35 no.1
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• pp.235-251
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• 2016

The main purposes of this study is to examine the effect of treatment setting on patient participation, and the moderating effect of negative emotion between treatment setting and patient participation. For the purposes of this study's goals, the 320 samples for this empirical study were collected from the general hospital and medical clinic outpatients in C and carried out hierarchial regression by SPSS 19.0. The results of this study are as follows. There is positive effect of cleanness of the treatment setting on behavior factor in patient participation. The higher aging of patient have influences on emotional factor in patient participation. There are positive effects of the third person in treatment settings on emotional and informational factors in patient participation. There is negative effect of negative emotion on emotional and informational factors in patient participation. There are negative effects of time pressure in treatment settings on emotional and informational factors in Patient Participation. On interaction effect, there are positive effects of cleanness in treatment setting and negative emotion on emotional and informational factors in patient participation. Implications for theoretical and practical patient participation are discussed.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.25-34
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• 2022

With the development of online services, the ripple effect of negative comments is increasing, and the damage of cyber violence is rising. Various methods such as filtering based on forbidden words and reporting systems prevent this, but it is challenging to eradicate negative comments. Therefore, this study aimed to increase the accuracy of the classification of negative comments using deep learning and blur the parts corresponding to profanity. Two different conditional training helped decide the number of deep learning layers and filters. The accuracy of 88% confirmed with 90% of the dataset for training and 10% for tests. In addition, Grad-CAM enabled us to find and blur the location of swear words in negative comments. Although the accuracy of classifying comments based on simple forbidden words was 56%, it was found that blurring negative comments through the deep learning model was more effective.

• Annual Conference of KIPS
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• 2006.05a
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• pp.469-472
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• 2006

본 논문은 비음수 행렬 인수분해(NMF, non-negative matrix factorization)를 이용하여 문장을 추출하여 문서를 요약하는 새로운 방법을 제안하였다. 제안된 방법은 문장추출에 사용되는 의미 특징(semantic feature)이 비 음수 값을 갖기 때문에 잠재의미분석에 비해 문서의 내용을 정확하게 요약한다. 또한, 적은 계산비용을 통하여 쉽게 요약 문장을 추출할 수 있는 장점을 갖는다.

• Korean Journal of English Language and Linguistics
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• v.1 no.3
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• pp.369-386
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• 2001

This paper will show that traditional approaches to the derivation of different negative words have been of an essentially hypothetical nature, based on either linguists' intuitions or rather scant evidence, and that native-speaker dictionary entries show meaning potentials (rather than meanings) which are in fact linguistic and cognitive prototypes. The purpose of this paper is to demonstrate that using a large corpus of natural language can provide better answers to questions about word-formation (i.e., with particular reference to negative prefixation) than any other source of information.

• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.107-110
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• 2004

IEEE 802.15.3 is wireless Medium Access Control(MAC) and Physical Layer(PHY) specification for high rate WPAN (Wireless Personal Area Network). IEEE 802.15.3 MAC Layer provides Qos with three kinds of acknowledgements; No acknowledgement, Immediate acknowledgement, and Delayed acknowledgement. This paper presents how to improve QoS with new acknowledgement method called Delayed Negative acknowledgement. This paper describes the method of using Delayed Negative acknowledgement and presents the calculation of QoS improvement by using Delayed Negative acknowledgement.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.7
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• pp.397-401
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• 2004

In an edge-weighted(positive, negative, or zero weights are possible) tree, we want to solve the problem of finding a longest path such that the sum of the weights of the edges in the path is non-negative. We present an algorithm to find a longest non-negative path of a degree 3 tree in Ο(n log n) time, where n is the number of nodes in the tree.

• Journal of the Korean Institute of Telematics and Electronics
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• v.10 no.2
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• pp.7-15
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• 1973

The operation behaviors of negative-resistance multivibrators. are described. The oscillation phenomena in monostable and bistable mode negative-resistance circuits are analyzed by using a analog computer. It is presented that voltage-controlled negative -resistance switching circuits may be in oscillation state for a time or parmanently by adding the bias voltage or trigger pulse. The results show that the care must be taken for this fact in the constructions of negative resistance switching circuits.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.12
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• pp.880-884
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• 2006

In an edge-weighted(positive, negative, or zero weights are possible) tree, we want to solve the problem of finding a longest path such that the sum of the weights of the edges in tile path is non-negative. To find a longest non-negative path of a tree we present a sequential algorithm with O(n logn) time and a CREW PRAM parallel algorithm with $O(log^2n)$ time and O(n) processors. where n is the number of nodes in the tree.