• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.1
• /
• pp.11-18
• /
• 2020

This study aims to complement the poor performance of existing context-aware authentication techniques in the mobile environment. The data used are GPS, Call Detail Record(CDR) and app usage. locational classification according to GPS density was implemented in order to distinguish other people in populated areas in the processing of GPS. It also handles missing values that may occur in data collection. The authentication model consists of two long-short term memory(LSTM) and one Artificial Neural Network(ANN) that aggregates the results, which produces authentication scores. In this paper, we compare the accuracy of this technique with that of other studies. Then compare the number of authentication attempts required to detect someone else's authentication. As a result, we achieved an average 11.6% improvement in accuracy and faster detection of approximately 60% of the experimental data.

• Journal of Digital Convergence
• /
• v.10 no.4
• /
• pp.341-346
• /
• 2012

Social network service is service that enables the human network to be built up on web. It is important to record users' information simply and establish the network with people based on the information to provide with the social network service effectively. But it is very troublesome work for the user to input his or her own information on the mobile environment. In this paper we suggested a system which classifies users' behavior using context and creates blogging sentences automatically after inferring the destination. For this, users' behavior is classified and the destination is inferred with the sequence matching method using Naive Bayes classification. Then sentences which are suitable for situation is created by arranging the processed context using the structure of 5W1H. The system was evaluated satisfaction degree by comparing the created sentences based on actually collected data with users' intension and got accuracy rate of 88.73%.

• Journal of Digital Convergence
• /
• v.11 no.3
• /
• pp.389-395
• /
• 2013

More sales of food and beverage coupons have been made using SNS on social commerce recently. If one buys coupons on social commerce, he/she can enjoy products at a lower price; however, there are drawbacks that one must consider such as location, service hours, and discount rate. Thus, this paper suggests a system that recommends food and beverage coupons on social commerce for users that considers a user's personal context of location, time, and purchase history. In order to reflect a user's context awareness and continuous preference, this paper suggests a method based on the Bayesian network. In order to reflect personalized weighting on the standard of coupon selection to match a user's preference, a measurement and classification of weighting preferences is performed on the basis of AHP. 20 experiments in one month involving 12 students were carried out to verify the effectiveness of the system, resulting in an 80% satisfaction level.

• The KIPS Transactions:PartC
• /
• v.13C no.7 s.110
• /
• pp.859-864
• /
• 2006

The openness of the Web allows any user to access almost any type of information easily at any time and anywhere. However, with function of easy access for useful information, internet has dysfunctions of providing users with harmful contents indiscriminately. Some information, such as adult content, is not appropriate for all users, notably children. Additionally for adults, some contents included in abnormal porn sites can do ordinary people's mental health harm. In the meantime, since Internet is a worldwide open network it has a limit to regulate users providing harmful contents through each countrie's national laws or systems. Additionally it is not a desirable way of developing a certain system-specific classification technology for harmful contents, because internet users can contact with them in diverse way, for example, porn sites, harmful spams, or peer-to-peer networks, etc. Therefore, it is being emphasized to research and develop context-based core technologies for classifying harmful contents. In this paper, we propose an efficient text filter for blocking harmful texts of web documents using context-based technologies.

• The Journal of the Korea Contents Association
• /
• v.11 no.12
• /
• pp.497-503
• /
• 2011

In this paper, we proposed the MCE as a GMM training method to improve the performance of environmental sounds recognition. We model the environmental sounds data with newly defined misclassification function using the log likelihood of the corresponding class and the log likelihood of the rest classes for discriminative training. The model parameters are estimated with the loss function using GPD(generalized probabilistic descent). For recognition performance comparison, we extracted the 12 degrees features using preprocessing and MFCC(mel-frequency cepstral coefficients) of the 9 kinds of environmental sounds and carry out GMM classification experiments. According to the experimental results, MCE training method showed the best performance by an average of 87.06% with 19 mixtures. This result confirmed us that MCE training method could be effectively used as a GMM training method in environmental sounds recognition.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.11
• /
• pp.6676-6684
• /
• 2014

This paper analyzed an existing literature review of street environment, density, accessibility, and diversity in terms of not the street level, but also the urban context level. In addition, this paper examined Jane Jacobs' theory (1961) regarding the relevance between the diversity of facilities and increasing volume of pedestrians. To find the explanation ability and significance among variables, this paper employed Enter's method of Regression Analysis in the industrial classification of restaurant business and liquor business. This empirical analysis of both theories of Jacobs (1961) and MacCormac (1983) had a different signification from existing research. Jacobs (1961) suggested the relevance among various facilities for increasing the volume of pedestrians, and MacCormac (1983) explained the different impact by industrial classification. In future research, the subdividing of industrial classification is necessary for a more precise and specific analysis.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.7
• /
• pp.259-266
• /
• 2018

In this paper, we propose a method to classify a document using a Recurrent Neural Network by extracting features considering word sense and contexts. Word2vec method is adopted to include the order and meaning of the words expressing the word in the document as a vector. Doc2vec is applied for considering the context to extract the feature of the document. RNN classifier, which includes the output of the previous node as the input of the next node, is used as the document classification method. RNN classifier presents good performance for document classification because it is suitable for sequence data among neural network classifiers. We applied GRU (Gated Recurrent Unit) model which solves the vanishing gradient problem of RNN. It also reduces computation speed. We used one Hangul document set and two English document sets for the experiments and GRU based document classifier improves performance by about 3.5% compared to CNN based document classifier.

• Journal of Korea Trade
• /
• v.23 no.8
• /
• pp.110-131
• /
• 2019

Purpose - This paper investigates the implications for facilitating trade in the products of Industry 4.0. To identify the issues caused by the conflicts of policy objectives such as applying the tariff concession under the ITA and imposing the export control, by exploring the case of classification of drones. Design/methodology - We adopted a single case study method to gain a deeper understanding of the complex and multifaceted issues of Customs classification in the context of facilitating trade in the products of Industry 4.0. This study employs the case of drones to explore how these issues of Customs classification affect trade facilitation. We ensured the internal validity of the study by confirming the pattern of the results with the existing theories. Findings - Our main findings can be summarised as follows: the intrinsic nature of the products that converge several technologies causes issues in the classification. The inconsistency in product classification delays customs clearance by hindering the Customs risk-management system that pinpoints products subject to controls. To address the issues, therefore, we proposed fundamental reforms of Customs to empower themselves with management roles. Facilitating trade in the products of Industry 4.0 requires more enhanced Customs capability. Therefore, the reforms should include comprehensive capacity-building activities, such as changes in staff-trainings, promotion system, organisation and culture. Customs also need roles in robust designing of cooperative systems to compensate for the lacks of controls and to ensure concrete risk management for expedited Customs procedures. As well, by equipping the Single Window of Customs with crucial control functions of other ministries, Customs need to support the cooperation. The role of harmonising various preaudits of other ministries with its own is another essential role that ensures predictability of clearance procedure. Originality/value - There are scanty studies in the field of knowledge about what obstacles exist and what solution is available in the course of transforming to 'Industry 4.0'. In filling out the gap of knowledge, this paper is of academic significance in that it applies the research theory on trade facilitation for the specific cases of classification of the product of Industry 4.0 to verify its effectiveness and to extend the subject of the studies to the scope of Industry 4.0. It also has practical significance in that the results have provided implications for reforms of Customs procedures to facilitate trade in the products of Industry 4.0.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.1
• /
• pp.76-87
• /
• 2005

In this paper, we propose a new profile, ROHC(RObust Header Compression) profile 7, for SCTP with ROHC for applying robust header compression SCTP, which is a transport layer protocol. The proposed new profile 7 adds a new field of 1 or 2 byte size on the existing SCTP packet header, which can make the SCTP stream to be diveded into acknowledgement stream and data stream. In addition, the classification of the stream can be used for recovering fault context. Consequently, in the case of using proposed ROHC-SCTP, it is possible to reduce the SCTP header overhead rate and also can be saved bandwidth.

• Journal of Fisheries and Marine Sciences Education
• /
• v.28 no.3
• /
• pp.645-652
• /
• 2016

At the initial stage of propulsion shaft design, in line with shaft alignment, an intensified consideration of lateral vibration is needed to verify its operational safety. Recently the alignment problem affecting the lateral vibration has been becoming issues. However, the theoretical method of forced lateral vibration analysis is not cleary established so far and it is about to simply limited among the classification societies and international standards to avoid the blade natural frequency resonance cpm outside of ${\pm}20%$ of engine rpm at MCR. On the other hand, longer center distance between each support bearing shows an affirmative result normally in shaft alignment analysis whereas the blade order resonance speed may cause lowering near the limitation in the aspect of lateral vibration. Therefore, it is required careful attention to engineers as described above. As a method to solve the problem, it is mainly considered that remove forward stern tube bearing. In this paper, based on a medium size container ship case, theoretical study was carried out in the context of the forward stern tube bearing. The various effects and functions of forward stern tube bearing are reviewed and evaluated. Then an guidance note to lead the conclusion is proposed.