• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.3
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• pp.71-82
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• 2004

Recently, network model inspired by social insect behavior attracts the public attention. The AntNet is an adaptive and distributed routing algorithm using mobile agents, called ants, that mimic the activities of social insect. In this paper. we present a new hardware architecture to realize an AntNet-based routing in practical system on a chip application. The modified AntNet algorithm for hardware implementation is compared with the original algorithm on the various traffic patterns and topologies. Implementation results show that the proposed architecture is suitable and efficient to realize adaptive routing based on the AntNet.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1388-1397
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• 2015

Recently, an application business model was proposed to implement an M-coupon system using the NFC-based mobile devices. In this paper, the security requirements were surveyed for a secure M-coupon system and to analyze the threats on the existing NFC-based M-coupon protocols. After considering the implementation efficiency and security, this paper presents a novel M-coupon protocol based on the Diffie-Hellman key agreement scheme. This protocol can be an alternative to solve the security problems related to the PKI (Public Key Infrastructure) and secret key distribution. Furthermore, this M-coupon protocol is designed to provide user authentication and counteract the relay attack.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.121-136
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• 2006

Software architecture and protocols to be maintained between components for the reconfigurable SDR system is analyzed and suggest system design idea for the implementation of software. To do this, related surveys are reviews and set up the system model with the structure of embedded system. SDR system architecture is suggested with five layered structure, consisted with hardware, operating system, middle-ware, service objects and application layer. SDR system is designed to be work on the basis of Linux operating system, and aimed to be scalable and reconfigurable. It is introduced the design result of software protocol and state transition diagram for the implementations of software download function which is the most important feature in SDR.

• Special Issue of the Society of Naval Architects of Korea
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• 2015.09a
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• pp.74-78
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• 2015

When floating platform or drilling unit is located at operating station during its design life, it has to have the sufficient stability considering external environment. To evaluate whether offshore structure is complied with the required design criteria for intact stability, the factors which decrease the righting moment have to be considered. Wind heeling moment is one of main factors because the direction is opposite to the righting moment. According to 2009 MODU CODE (Code for the construction and equipment of Mobile Offshore Drilling Units, 2009), wind heeling moment derived from wind tunnel test on scale model of offshore structure enables to apply as alternative given formula and method in 2009 MODU CODE. However, there is no the specific method for applying data derived from wind tunnel test. Based on the following reasons, this paper presents that the calculation method of wind heeling moment utilizing non-dimensional coefficient relative to wind loads (wind forces and moments) and the comparison with each method applying an example.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.317-323
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• 2021

Social media is increasingly becoming a part of our daily life for communicating each other. There are various tools and applications for communication and therefore, identity theft is a common issue among users of such application. A new style of identity theft occurs when cybercriminals break into WhatsApp account, pretend as real friends and demand money or blackmail emotionally. In order to prevent from such issues, data mining can be used for text classification (TC) in analysis authorship attribution (AA) to recognize original sender of the message. Arabic is one of the most spoken languages around the world with different variants. In this research, we built a machine learning model for mining and analyzing the Arabic messages to identify the author of the messages in Saudi dialect. Many points would be addressed regarding authorship attribution mining and analysis: collect Arabic messages in the Saudi dialect, filtration of the messages' tokens. The classification would use a cross-validation technique and different machine-learning algorithms (Naïve Baye, Support Vector Machine). Results of average accuracy for Naïve Baye and Support Vector Machine have been presented and suggestions for future work have been presented.

• ETRI Journal
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• v.43 no.1
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• pp.95-108
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• 2021

Application (app) ratings are feedback provided voluntarily by users and serve as important evaluation criteria for apps. However, these ratings can often be biased owing to insufficient or missing votes. Additionally, significant differences have been observed between numeric ratings and user reviews. This study aims to predict the numeric ratings of Google apps using machine learning classifiers. It exploits numeric app ratings provided by users as training data and returns authentic mobile app ratings by analyzing user reviews. An ensemble learning model is proposed for this purpose that considers term frequency/inverse document frequency (TF/IDF) features. Three TF/IDF features, including unigrams, bigrams, and trigrams, were used. The dataset was scraped from the Google Play store, extracting data from 14 different app categories. Biased and unbiased user ratings were discriminated using TextBlob analysis to formulate the ground truth, from which the classifier prediction accuracy was then evaluated. The results demonstrate the high potential for machine learning-based classifiers to predict authentic numeric ratings based on actual user reviews.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2188-2203
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• 2021

With the rapid development of mobile Internet, smart phones have been widely popularized, among which Android platform dominates. Due to it is open source, malware on the Android platform is rampant. In order to improve the efficiency of malware detection, this paper proposes deep learning Android malicious detection system based on behavior features. First of all, the detection system adopts the static analysis method to extract different types of behavior features from Android applications, and extract sensitive behavior features through Term frequency-inverse Document Frequency algorithm for each extracted behavior feature to construct detection features through unified abstract expression. Secondly, Long Short-Term Memory neural network model is established to select and learn from the extracted attributes and the learned attributes are used to detect Android malicious applications, Analysis and further optimization of the application behavior parameters, so as to build a deep learning Android malicious detection method based on feature analysis. We use different types of features to evaluate our method and compare it with various machine learning-based methods. Study shows that it outperforms most existing machine learning based approaches and detects 95.31% of the malware.

• The Journal of Korean Institute of Information Technology
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• v.17 no.1
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• pp.149-156
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• 2019

Mixed reality technology (MR) has become one of the fourth industrial revolution element technologies. MR technology has been widely applied not only as a digital contents industry but also in the fields of architecture, tourism, medical field, and education. In this paper, we propose a collaborative service platform for architectural applications that inter-operate with heterogeneous devices such as MR device, PC and mobile, and develop prototype system and verify it. As a result, the 3D model using the skp extension, which is mainly used in architecture design office, was created by using developed prototype system and generate the MR contents for the hololens, which is the MR device, and the conversion time and normal operation were confirmed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.591-593
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• 2022

This paper proposes a partial offloading system for minimizing application service processing latency in an FEC (Fog/Edge Computing) environment, and it analyzes the offloading effect of the proposed system against local-only and edge-server-only processing based on network load. A partial offloading algorithm based on reconstruction linearization of multi-branch structures is included in the proposed system, as is an optimal collaboration algorithm between mobile devices and edge servers [1,2]. The experiment was conducted by applying layer scheduling to a logical CNN model with a DAG topology. When compared to local or edge-only executions, experimental results show that the proposed system always provides efficient task processing strategies and processing latency.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.586-596
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• 2011

In the IT industry, processing units of IT applications are getting smaller and high efficient. Furthermore, the realization of various smart functions is highly feasible now due to advances in sensing technology. The service infrastructures on high efficient and compact mobile devices are applied to various areas. These also could be possessed by users and is built into the devices. Currently, studies on the UX(User Experience) field to attempt an analysis and prediction of user's information are continuing with reference to the UI(User Interface). However, research on the common framework of classification and storing the user-information, and standardization of form has not been attempted yet. In this study, we proposed the AUX(Associative user Experience) model and process structure to store various empirical data by users. The AUX model expressed a diversity of user's empirical data using extended E-TCPN model. And also, we expressed the data structure using XML with reference to the application of AUX model. This expressed model and separation of process structure guarantee its specialty, productivity and flexibility through the humanistic characteristics of users and the independence of technical process structure. The AUX model maps out the AUX information process architecture and expressed the process with the improved MPP algorithm, to analyze of its performance. The simulation of movements applying to MPP traffic allocation of VOD is used to analyze of its performance. The playback deviation of MPP Graphic Allocation Algorism where the AUX model was applied was improved by 10.41% more than the one where it was not applied. As a result of that, playback performance has improved due to the conversion of AUX with accessing media, content of users and dynamic traffic allocation such as MPI and CPI.