• Journal of the Ergonomics Society of Korea
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• v.31 no.1
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• pp.101-107
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• 2012

Objective: The aim of this study is to investigate service design cases by online service companies and suggests framework to understand service design of them. Background: Recently, exploratory service design cases by online service companies such as Google, Apple, and NHN has been developed. Service design and online service experience design has been booming among user experience professionals but these two areas are not clearly defined. It is interesting to study the definition and key factors of service design and online service experience design. Moreover, investigating service design cases by online service companies is needed. Method: Due to diversification of service design cases by online service companies, this study has reviewed online resources and literatures about top 5 online service companies in USA and Korea. Furthermore, this study used expert interview who worked for service design at NHN. To understand the attributes of service design cases, this study developed 3 types of service design classifications scheme such as service design as extension of online service, space design and event service design. Finally, this study suggested a new framework for service design cases. Results: This study investigated service design cases by online service companies and suggests key issues and frameworks to uncover service design for online service. Conclusion: Service design cases for online service was analyzed by $2^*2$ matrix(extension, $enrichment^*product$, service) to explain characteristics and attributes. NHN's Knowledge-iN bookshelf at NHN library1 is a unique form of service design as a tool of enrichment of online experience. Application: The results of this study might help to understand service design cases and plan new service design for online service companies with structured framework.

• Imaging Science in Dentistry
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• v.50 no.2
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• pp.169-174
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• 2020

Purpose: Periodontal disease causes tooth loss and is associated with cardiovascular diseases, diabetes, and rheumatoid arthritis. The present study proposes using a deep learning-based object detection method to identify periodontally compromised teeth on digital panoramic radiographs. A faster regional convolutional neural network (faster R-CNN) which is a state-of-the-art deep detection network, was adapted from the natural image domain using a small annotated clinical data- set. Materials and Methods: In total, 100 digital panoramic radiographs of periodontally compromised patients were retrospectively collected from our hospital's information system and augmented. The periodontally compromised teeth found in each image were annotated by experts in periodontology to obtain the ground truth. The Keras library, which is written in Python, was used to train and test the model on a single NVidia 1080Ti GPU. The faster R-CNN model used a pretrained ResNet architecture. Results: The average precision rate of 0.81 demonstrated that there was a significant region of overlap between the predicted regions and the ground truth. The average recall rate of 0.80 showed that the periodontally compromised teeth regions generated by the detection method excluded healthiest teeth areas. In addition, the model achieved a sensitivity of 0.84, a specificity of 0.88 and an F-measure of 0.81. Conclusion: The faster R-CNN trained on a limited amount of labeled imaging data performed satisfactorily in detecting periodontally compromised teeth. The application of a faster R-CNN to assist in the detection of periodontally compromised teeth may reduce diagnostic effort by saving assessment time and allowing automated screening documentation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.8 s.338
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• pp.11-16
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• 2005

This paper proposes a bit manipulation accelerator (BMA) having application specific instructions, which efficiently supports scrambling, convolutional encoding, puncturing, and interleaving. Conventional DSPs cannot effectively perform bit manipulation functions since かey have multiply accumulate (MAC) oriented data paths and word-based functions. However, the proposed accelerator can efficiently process bit manipulation functions using parallel shift and Exclusive-OR (XOR) operations and bit jnsertion/extraction operations on multiple data. The proposed BMA has been modeled by VHDL and synthesized using the SEC $0.18\mu m$ standard cell library and the gate count of the BMA is only about 1,700 gates. Performance comparisons show that the number of clock cycles can be reduced about $40\%\sim80\%$ for scrambling, convolutional encoding and interleaving compared with existing DSPs.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.1
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• pp.76-84
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• 2009

This paper proposes a SOC platform which is eligible for education and application SOC design. The platform, fully synthesizable and reconfigurable, includes the OpenRISC embedded processor, some basic peripherals such as GPIO, UART, debug interlace, VGA controller and WISHBONE interconnect. The platform uses a set of development environment such as compiler, assembler, debugger and RTOS that is built for HW/SW system debugging and software development. Designed SOC, IPs and Testbenches are described in the Verilog HDL and verified using commercial logic simulator, GNU SW development tool kits and the FPGA. Finally, a multimedia SOC derived from the SOC platform is implemented to ASIC using the Magnachip cell library based on 0.18um 1-poly 6-metal technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1183-1188
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• 2016

Kinect sensor version 2 is a kind of camera released by Microsoft as a computer vision and a natural user interface for game consoles like Xbox one. It allows acquiring color images, depth images, audio input and skeletal data with a high frame rate. In this paper, using depth image, we present a surveillance system of a certain area within Kinect's field of view. With computer vision library(Emgu CV), if an object is detected in the target area, it is tracked and kinect camera takes RGB image to send it in database server. Therefore, a mobile application on android platform was developed in order to notify the user that Kinect has sensed strange motion in the target region and display the RGB image of the scene. User gets the notification in real-time to react in the best way in the case of valuable things in monitored area or other cases related to a reserved zone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3230-3253
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• 2017

Android malware steals users' private information, and embedded unsafe advertisement (ad) libraries, which execute unsafe code causing damage to users. The majority of such traffic is HTTP and is mixed with other normal traffic, which makes the detection of malware and unsafe ad libraries a challenging problem. To address this problem, this work describes a novel HTTP traffic flow mining approach to detect and categorize Android malware and unsafe ad library. This work designed AndroCollector, which can automatically execute the Android application (app) and collect the network traffic traces. From these traces, this work extracts HTTP traffic features along three important dimensions: quantitative, timing, and semantic and use these features for characterizing malware and unsafe ad libraries. Based on these HTTP traffic features, this work describes a supervised classification scheme for detecting malware and unsafe ad libraries. In addition, to help network operators, this work describes a fine-grained categorization method by generating fingerprints from HTTP request methods for each malware family and unsafe ad libraries. This work evaluated the scheme using HTTP traffic traces collected from 10778 Android apps. The experimental results show that the scheme can detect malware with 97% accuracy and unsafe ad libraries with 95% accuracy when tested on the popular third-party Android markets.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3910-3922
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• 2000

Current power systems are distributed geographically and operated in the form of Energy Management System(EMS)/ Supervision Control and Data Acquisition(SCADA) with the aid of computers and communications. Recently a variety of utilities have had interests in using inforrration technology to bring the efficiency and low operational costs. There is also a trend to integrdte the production, transmission, distribution and management/control of power into one and unified distributed system. To this end, Electric Power Hesearch Institute(EPRI) announced a new standard communication protocol called Inter-Control Center Protocol(ICCP).ICCP specifies the use of Manufacturing Message Specification(MMS) for services required by rccr in application layer and supports the communications between heterogeneous control centers. This paper presents the characteristics of MMS,ICCP and their relationship. Futherrnore, we implement the basic functional blocks of ICCP using MMS services under TCI/IP environments. Finally, we model a simple power system and apply the rccp protocol to this system in a window-based scheme, and finally show the operation and validation of this protocol.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.440-445
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• 2017

Due to the advance of e-commerce systems, the number of people using online shopping and products has significantly increased. Therefore, the need for an accurate recommendation system is becoming increasingly more important. Recurrent neural network is a deep-learning algorithm that utilizes sequential information in training. In this paper, an evaluation is performed on the application of recurrent neural networks to recommendation systems. We evaluated three recurrent algorithms (RNN, LSTM and GRU) and three optimal algorithms(Adagrad, RMSProp and Adam) which are commonly used. In the experiments, we used the TensorFlow open source library produced by Google and e-commerce session data from RecSys Challenge 2015. The results using the optimal hyperparameters found in this study are compared with those of RecSys Challenge 2015 participants.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.102-111
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• 2005

In this paper, we propose an advanced hardware architecture for the fast inter prediction engine of the video coding standard MPEG-4 AVC. We describe the algorithm and derive the hardware architecture emphasizing and real time operation of the quarter_pel based motion estimation. The fast inter prediction engine is composed of block segmentation, motion estimation, motion compensation, and the fast quarter_pel calculator. The proposed architecture has been verified by ARM-interfaced emulation board using Excalibur & Virtex2 FPGA, and also by synthesis on Samsung 0.18 um CMOS technology. The synthesis result shows that the proposed hardware can operate at 62.5MHz. In this case, it can process about 88 QCIF video frames per second. The hardware is being used as a core module when implementing a complete MPEG-4 AVC video encoder chip for real-time multimedia application.

• The KIPS Transactions:PartC
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• v.11C no.2
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• pp.163-170
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• 2004

The additional mechanism Is required to set up a secure connection among the communication subjects in the internet environment. Each entity should transfer and receive the encrypted and hashed data to guarantee the data integrity. Also, the mutual authentication procedure should be processed using a secure communication protocol. The SSL/TLS is a protocol which creates the secure communication channel among the communication subjects and sends/receives a data. Although the OpenSSL which implements the TLS is using by many developers and its stability and performance are proved, it has a difficulty in using because of its large size. So, this Paper designs and implements the secure communication which the users can use easily by modification works of OpenSSL library API. We proved the real application results using the DRM client/server case which supports a secure communication using the implemented API.