• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.181-187
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• 2005

This paper proposes and implements a service model to transfer messages safely for PDA on CDMA wireless network and a secure massage transfer protocol which considers characteristics of PDA. Proposed service uses SMS(Short Message Service) connect to a off-line client device with the wired network for data communication. After receiving SMS message, client device processes the SMS message and creates a data channel through RAS(Remote Access Service), then the data of the server can be pushed to clients. The implemented security protocol can provide safe data transmission on each communication line through two way channels(SMS and data). Also, by using security nonce table, this protocol can reduce a number of transmissions for exchanging a safe session key, so intensity of encryption can be increased.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.83-89
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• 2017

In this paper, we propose an extended method of one-hot Long Short-Term Memory (LSTM) and evaluate the performance on spam filtering task. Most of traditional methods proposed for spam filtering task use word occurrences to represent spam or non-spam messages and all syntactic and semantic information are ignored. Major issue appears when both spam and non-spam messages share many common words and noise words. Therefore, it becomes challenging to the system to filter correct labels between spam and non-spam. Unlike previous studies on information filtering task, instead of using only word occurrence and word context as in probabilistic models, we apply a neural network-based approach to train the system filter for a better performance. In addition to one-hot representation, using term weight with attention mechanism allows classifier to focus on potential words which most likely appear in spam and non-spam collection. As a result, we obtained some improvement over the performances of the previous methods. We find out using region embedding and pooling features on the top of LSTM along with attention mechanism allows system to explore a better document representation for filtering task in general.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5607-5609
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• 2014

Introduction: Although continuing education is necessary for practicing nurses, it is very difficult to organize traditional classes because of large numbers of nurses and working shifts. Considering the increasing development of mobile electronic learning, we carried out a study to compare effects of the traditional face to face method with mobile learning delivered as text messages by cell phone. Materials and Methods: Sixty female nurses working in our hospital were randomly divided into class and short message service (SMS) groups. Lessons concerning breast cancer screening were prepared as 54 messages and sent in 17 days for the SMS group, while the class group participated in a class held by a university lecturer of breast and cancer surgery. Pre- and post-tests were undertaken for both groups at the same time; a retention test also was performed one month later. For statistical analysis, the paired T test and the independent sample T test were used with SPSS software version 16; p<0.05 was considered significant. Results: Mean age and mean work experience of participants in class and SMS groups was $35.8{\pm}7.2$, $9.8{\pm}6.7$, $35.4{\pm}7.3$, and $11.5{\pm}8.5$, respectively. There was a significant increase in mean score post-tests (compared with pretests) in both groups (p<0.05). Although a better improvement in scores of retention tests was demonstrated in the SMS group, the mean subtraction value of the post- and pretests as well as retention- and pretests showed no significant difference between the 2 groups (p=0.3 and p =0.2, respectively). Conclusions: Our study shows that teaching via SMS may probably replace traditional face to face teaching for continuing education in working nurses. Larger studies are suggested to confirm this.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.13-19
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• 2018

Although it's been nearly decade since the electronic notarization system enforced, the utilization is not high because of the troublesomeness of the client or his agent to visit the notarial office directly. Recently, the ministry of justice introduced e-notary based on audio-visual conference through amendament of the notarial law, and hence it will vitalize the usage of e-notary. In addition, due to the spread of smartphones, many people use SMS messages to express simple statements or promises. However, in case of legal disputes, the judgment of the court is different according to the case. The electronic notarization system can be used to prove of evidence of SMS messages, however, there is a hassle to convert SMS messages to electronic documents. To solve this problem, this paper proposes an SMS notarization system using smartphones. The proposed system uses reliable notarization server and it is divided into notarization system for message senders and notarization system for message receivers according to notary requestor.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2595-2602
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• 2010

This paper introduces a mobile spam filtering system that considers the style of short text messages sent to mobile phones for detecting spam. The proposed system not only relies on the occurrence of content words as previously suggested but additionally leverages the style information to reduce critical cases in which legitimate messages containing spam words are mis-classified as spam. Moreover, the accuracy of spam classification is improved by normalizing the messages through the correction of word spacing and spelling errors. Experiment results using real world Korean text messages show that the proposed system is effective for Korean mobile spam filtering.

• The Research Journal of the Costume Culture
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• v.24 no.1
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• pp.13-26
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• 2016

The purpose of the present study is to investigate the effect of time remaining to use mileage in the notification message from retailers on consumer responses. A total of 577 consumers participated in experiments involving different notification messages of the time remaining to use mileage. Results showed: 1) a significant difference in mileage benefit perception, positive emotion, negative emotion, attitude toward retailers, and repurchase intention according to the remaining time to use mileages, 2) benefit perception positively affected positive emotion and negatively affected negative emotion; positive emotion positively affected and negative emotion negatively affected attitude toward retailers; and attitude positively affected repurchase intention on retailers, and 3) the remaining time to use mileages moderates the relationship between attitude and repurchase intention. Findings highlighted the importance of timing of the message to notify the consumer as to remaining time to use mileage. In the case of a message indicating long remaining time to use mileage, consumers showed more positive responses toward retailers than did consumers who had a message indicating short remaining time to use mileage. These results can be used as guidelines to select the optimal time to send notification messages of remaining time to use mileage in order to generate positive consumer responses.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.7
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• pp.271-276
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• 2014

Short message service(SMS) in a mobile communication environment is a very convenient method. However, it caused a serious side effect of generating spam messages for advertisement. Those who send spam messages distort or deform SMS sentences to avoid the messages being filtered by automatic filtering system. In order to increase the performance of spam filtering system, we need to recover the distorted sentences into normal sentences. This paper proposes a method of normalizing the various types of distorted sentence and extracting keywords through automatic word spacing and compound noun decomposition.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.295-300
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• 2011

Twitter is a popular microblogging service that enables the users to send and read short text messages. These messages are becoming source to analyze topic trends and identify relations among temporal topics. In this paper, we propose a method to classify the temporal topics on Twitter as a problem of grouping the similar patterns. To provide a starting point for a classification under the same topics, we identify the content word weighting scheme based on Latent Dirichlet Allocation (LDA). And we formulate how the temporal topics in the time window can be classified like peaky topics, constant topics, and periodic topics. We provide different real case studies which show the validity of the proposed method. Evaluations show that the proposed method is useful as a classifying model in the analysis of the temporal topics.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.95-108
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• 1999

The CDMA mobile system consists of several subsystems and each subsystem has many processing elements that handle voice messages and control messages for performing CDMA call processing functions through CDMA Interconnection Network(CIN). For assuring a high throughput and a short delay in the CIN, an efficient medium access control protocol should be provided. In this paper, we propose a new access control protocol of CIN for providing real time communications in CDMA mobile system. Also, we evaluate the delay performance of the proposed access control protocol and compare it with that of the existing access control protocol. Through a set of numerical examples, we show that our proposed protocol provides a better delay performance than the existing protocol.

• Journal of Korea Multimedia Society
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• v.20 no.7
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• pp.1065-1072
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• 2017

As smart devices and social network services (SNSs) become increasingly pervasive, individuals produce large amounts of data in real time. Accordingly, studies on unstructured data analysis are actively being conducted to solve the resultant problem of information overload and to facilitate effective data processing. Many such studies are conducted for filtering inappropriate information. In this paper, a feature-weighting method considering SNS-message features is proposed for the classification of short text messages generated on SNSs, using Markov logic networks for category inference. The performance of the proposed method is verified through a comparison with an existing frequency-based classification methods.