• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.954-961
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• 2010

Stream cipher was worse than block cipher in terms of security, but faster in execution speed as an advantage. However, since so far there have been many algorithm researches about the execution speed of block cipher, these days, there is almost no difference between them in the execution speed of AES. Therefore an secure and fast stream cipher development is urgently needed. In this paper, we propose a 32bit output fast stream cipher, AA32, which is composed of ASR(Arithmetic Shifter Register) and simple logical operation. Proposed algorithm is a cipher algorithm which has been designed to be implemented by software easily. AA32 supports 128bit key and executes operations by word and byte unit. As Linear Feedback Sequencer, ASR 151bit is applied to AA32 and the reduction function is a very simple structure stream cipher, which consists of two major parts, using simple logical operations, instead of S-Box for a non-linear operation. The proposed stream cipher AA32 shows the result that it is faster than SSC2 and Salsa20 and satisfied with the security required for these days. Proposed cipher algorithm is a fast stream cipher algorithm which can be used in the field which requires wireless internet environment such as mobile phone system and real-time processing such as DRM(Digital Right Management) and limited computational environments such as WSN(Wireless Sensor Network).

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.148-154
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• 2008

In a ubiquitous computing environment, a ubiquitous smart space is required to help devices provide intelligent services. The smart space embedded with mobile devices should have the capabilities of collecting data and refining the data to contact. Unfortunately, the context information in a ubiquitous smart space has many ambiguous characteristics. Therefore, it is necessary to adapt a standard taxonomy for contact information in the smart space and to implement an inference technique of the context information based on taxonomy. Rule-based inference engine, such as CLIPS, Jess, was employed for providing situation-aware services. However, it is difficult for these engines to be used in resource limited mobile devices. In this paper, we propose a light-weight inference engine providing autonomous situation aware services in mobile environment. It can be utilized for personal mobile devices tuck as mobile phone, PMP and navigation. It can also support both generalized rules and specialized rules as using hierarchical taxonomy information.

• Science of Emotion and Sensibility
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• v.17 no.3
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• pp.65-74
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• 2014

Due to recent interest in user experience and its significance, much research surrounding this theme is now being conducted. In this research, I investigated user experience during usage of a product and the satisfaction acquired by it, as well as the relationship between satisfaction of having used a product and whether the user would be more likely to purchase another product from the same company. The same experiment was conducted in South Korea and the United States of America in order to get more generalized experimental results. I found that amongst the six representative user emotions expressed while using a product, two of them correlated the most. First, 'Satisfaction in Usability' (the emotions aroused by satisfaction with usage or the practicality of the product); and second, 'Discomfort or Displeasure' (uncomfortable or unpleasant emotions expressed while using a product. The above two factors were found to be of the most influence concerning satisfaction of the product. Also 'Satisfaction in Usability' was found to be of the most influence in their preferability towards purchasing an item from the same company in the future. The significance of this finding is that aside from focussing on the attractiveness of the product's exteriors and design, one should be concerned on the ease of usage and effectiveness as well as usability of the product, all of which contribute to how efficiently a consumer will utilize the product. Furthermore, in agreement with previous research concerning the correlation between satisfaction of a product and positive perspective on consecutive purchases, the result of this study shows that the more satisfaction consumers feel after using a product, the more likely they are to purchase additional merchandises from the same company which manufactured the original product.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.443-452
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• 2004

The paper presents an intelligent space management system for ubiquitous computing. The system is basically a home/office automation system that could control light, electronic key, and home appliances such as TV and audio. On top of these basic capabilities, there are four elegant features in the system. First, we can access the system using either a cellular Phone or using a browser on the PC connected to the Internet, so that we control the system at any time and any place. Second, to provide more human-oriented interface, we integrate voice recognition functionalities into the system. Third, the system supports not only reactive services but also proactive services, based on the regularities of user behavior. Finally, by exploiting embedded technologies, the system could be run on the hardware that has less-processing power and storage. We have implemented the system on the embedded board consisting of StrongARM CPU with 205MHz, 32MB SDRAM, 16MB NOR-type flash memory, and Relay box. Under these hardware platforms, software components such as embedded Linux, HTK voice recognition tools, GoAhead Web Server, and GPIO driver are cooperated to support user-friendly intelligent space.

• Journal of Communication Design
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• v.57
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• pp.44-53
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• 2016

Expected consumer's consumption propensity affected by advertisement using media facade and how this advertisement can affect consumer response and advertising effectiveness will be examined practically. This research showed TV advertisement and media facade advertisement to each participants of research in order to evaluate consumer response and effectiveness of media facade advertisement and took a survey. Research result, positive response was observed that consumer who were exposed of media facade advertisement showed more positive cognition/emotional response than TV advertisement. And effectiveness of media facade is more than standard. However, product attitude was not statistically positive. Therefore, it can be said that media facade advertisement does not affect positively on product attitude, but it is effective on purchase intention. Next, consumer who is exposed of media facade advertisement showed little low correlation on cognition response and product attitude, but showed positive correlation on cognition response, purchase intention, emotional response and product attitude. Accordingly, more positive consumer's cognition and emotional response is, the higher advertisement effect can be observed. Last, positive result were not presented in consumer's consumption propensity in regards to rational/emotional response. This means that it is invalid to state that consumer response differs for consumer propensity. Through result of experiment, a statement that media facade is a new media that has various possibility as advertisement mediator had been proved. Especially, as it shows that positive effect exists regardless of consumer's consumption propensity, use of media facade as marketing means is reasonable for firm in order to increase satisfaction of consumer and brand value.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.115-121
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• 2021

This paper used big data and artificial intelligence technology to predict the rapidly increasing internet traffic. There have been various studies on traffic prediction in the past, but they have not been able to reflect the increasing factors that induce huge Internet traffic such as smartphones and streaming in recent years. In addition, event-like factors such as the release of large-capacity popular games or the provision of new contents by OTT (Over the Top) operators are more difficult to predict in advance. Due to these characteristics, it was impossible for an ISP (Internet Service Provider) to reflect real-time service quality management or traffic forecasts in the network business environment with the existing method. Therefore, in this study, in order to solve this problem, an Internet traffic collection system was constructed that searches, discriminates and collects traffic data in real time, separate from the existing NMS. Through this, the flexibility and elasticity to automatically register the data of the collection target are secured, and real-time network quality monitoring is possible. In addition, a large amount of traffic data collected from the system was analyzed by machine learning (AI) to predict future traffic of OTT operators. Through this, more scientific and systematic prediction was possible, and in addition, it was possible to optimize the interworking between ISP operators and to secure the quality of large-scale OTT services.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.531-534
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• 2014

DLNA is an established industry standard which supports contents sharing among smart devices in home wired- and wireless-network environment and is well known in Korea as Allshare or Smartshare. The DLNA standard is implemented as built-in services in most of Android smart phones and tablets. In addition to the handheld devices, DLNA service can also be employed in speakers, printers, and so on. However, users have reported many interoperability issues between DLNA devices. Developers typically identify causes by analyzing the packet exchange information between devices. However, this approach costs them to put additional effort to filter relevant packets, to reconstruct packet exchange history and the protocol flow. Consequently, it ends up with increased development time. In this paper, we demonstrate a technique to automatically analyze and visualize the packet exchange history. We modified a router firmware to capture and store packets exchanged between DLNA devices, and then analyze and visualize the stored packet exchange history for developers. We believe that visualized packet exchange history can help developers to test the interoperability between DLNA devices with less effort, and ultimately to improve the productivity of developers.

• Smart Media Journal
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• v.10 no.2
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• pp.76-83
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• 2021

With the development and use of smart devices such as smartphones and tablets increases, the mobile application market based on mobile devices is growing rapidly. Mobile application users write reviews to share their experience in using the application, which can identify consumers' various needs and application developers can receive useful feedback on improving the application through reviews written by consumers. However, there is a need to come up with measures to minimize the amount of time and expense that consumers have to pay to manually analyze the large amount of reviews they leave. In this work, we propose to collect delivery application user reviews from Google PlayStore and then use machine learning and deep learning techniques to classify them into four categories like application feature advantages, disadvantages, feature improvement requests and bug report. In the case of the performance of the Hugging Face's pretrained BERT-based Transformer model, the f1 score values for the above four categories were 0.93, 0.51, 0.76, and 0.83, respectively, showing superior performance than LSTM and GRU.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.115-122
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• 2022

Recently, the importance of CPR training for the layperson has been emphasized to improve the survival rate of out-of-hospital cardiac arrest patients. An accurate and realistic training strategy is required for the CPR training effect for laypersons. In this study, we develop an extended reality (XR) based CPR training system and evaluate its usability. The XR based CPR training system consisted of three applications. First, a 3D heart anatomy image registered to the manikin is transmitted to the smart glasses to guide the chest compression point. The second application provides visual and auditory information about the CPR process through smart glasses. At the same time, the smartwatch sends a vibration notification to guide the compression rate. The 'Add-on-kit' is a device that detects the depth and speed of chest compression via sensors installed on the manikin and sends immediate feedback to the smartphone. One hundred laypersons who participated in this study agreed that the XR based CPR training system has realism and effectiveness. XR based registration technology will contribute to improving the efficiency of CPR training by enhancing realism, immersion, and self-directed learning.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.620-626
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• 2020

This research propose and simulate a solar power generation system monitoring system based on Modbus TCP communication using RaspberryPi, an IOT equipment, as a master and an inverter as a slave. In this model, various sensors are added to the RaspberryPi to add necessary information for monitoring solar power plants, and power generation prediction and monitoring information are transmitted to the smart phone through real-time power generation prediction. In addition, information that is continuously generated by the solar power plant is built on the server as big data, and a deep learning model for predicting power generation is trained and updated. As a result of the study, stable communication was possible based on Modbus TCP with the Raspberry Pi in the inverter, and real-time prediction was possible with the deep learning model learned in the Raspberry Pi. The server was able to train various deep learning models with big data, and it was confirmed that LSTM showed the best error with a learning error of 0.0069, a test error of 0.0075, and an RMSE of 0.0866. This model suggested that it is possible to implement a real-time monitoring system that is simpler, more convenient, and can predict the amount of power generation for inverters of various manufacturers.