• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.8
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• pp.674-682
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• 2013

Along with increasing of its subscribers and traffic for high-speed LTE service, it is widely expected to bring about the 2nd data explosion and results in any inconvenience of users. This paper proposes a smart traffic management scheme and its system design based on user's participating with the mobile application, in order to provide a fast and stable service for end users as well as to resolve the network overhead with increasing traffic. By making use of a time shift by users who want to reduce data usage amount and communication cost, the proposed scheme tries to reduce the peak traffic by shifting the delay-tolerant services, such as file sharing and software download, into the other time line. It also reduces the high volumed video traffics by transforming them into a user customized one. In addition, we suggest a mechanism to select video size and service time, then proposes an overall system design and its user service scenarios.

• Journal of KIISE
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• v.42 no.12
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• pp.1623-1628
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• 2015

As the performance of mobile devices has increased, high-end multicore CPUs have become the norm in smartphones. However, such high performance devices are exposed to the problem of battery depletion due to the energy consumption caused by software performance, and despite increases in battery capacity. The required resources are dynamic and varied, and further user interaction is highly random; thus, Linux-based power management such as DVFS is needed to fulfill requirements. In order to reduce power consumption, we propose a method to restrict the CPU frequency of data download while maintaining user reactivity. This can supplement the weakness of existing Linux-based power management techniques like DVFS in relation to webpage loading. Through the implementation of our method at the application level, we confirm that energy consumption from webpage loading is reduced.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.281-284
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• 2008

This paper describes ASIC design of multimedia SoC Platform. The implemented Platform consists of 32-bit OpenRISC1200 Microprocessor, WISHBONE on-chip bus, VGA Controller, Debug Interface, SRAM Interface and UART. The 32-bit OpenRISC1200 processor has 5 stage pipeline and Harvard architecture with separated instruction/data bus. The VGA Controller can display RCB data on a CRT or LCD monitor. The Debug Interface supports a debugging function for the Platform. The SRAM Interface supports 18-bit address bus and 32-bit data bus. The UART provides RS232 protocol, which supports serial communication function. The Platform is design and verified on a Xilinx VERTEX-4 XC4VLX80 FPGA board. Test code is generated by a cross compiler' and JTAG utility software and gdb are used to download the test code to the FPGA board through parallel cable. Finally, the Platform is implemented into a single ASIC chip using Chatered 0.18um process and it can operate at 100MHz clock frequency.

• Journal of Digital Convergence
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• v.13 no.5
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• pp.205-211
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• 2015

Recently, a mobile communication network and the wireless terminal is suddenly develop, mobile office service is more and more the sportlight. However, the user may receive an attack from a malicious third party if the up/download the data in the remote to perform the work in a mobile office environment. In this paper, we propose scheme to manage the information lost due to theft smartphone that contain spill prevention personal information and company information from the mobile office environment (call history, incoming messages, phonebook, calendar, location information, banking information, documents, etc.). The proposed scheme using the number of triangular fuzzy information about the state of the personal information and business intelligence to implement a pair-wise comparison matrix. In particular, the proposed scheme is to prevent the value obtained by constructing a pair-wise comparison matrix for personal information and business intelligence and pair your smartphone is lost when a third party not allow access to personal information and corporate information is leaked to the outside.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.455-464
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• 2015

As the number of overseas travelers with smartphones increases, there is a growing interest in smartphone applications, which can assist traveling. Typically, travelers need applications to obtain basic information, such as weather, map, currency, etc. However, existing smartphone applications are not suitable to do so because they require network connection that is expensive and unstable in overseas. For example, one of the most frequently used smartphone map application requires a network connection, and much battery to download images. Since travelers spend most of their time outside, there is no chance to charge the battery. In this paper, we propose a study on implementation of a smartphone application for overseas travelers, called Travel Manager, which aims to reduce usages of network connection and battery. Travel Manager first checks whether smartphone is connected to the network, and then synchronizes the travel information. It also automatically calculates traveling expenses by considering currency rate. That is, the proposed smartphone application can be used regardless of the network connection and minimizes the battery usage.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.106-112
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• 2019

The Korea Copyright Commission has pursued copyright technology R&D projects to prevent illegal copying of comics and Webtoons. We developed a feature-based scanned comic filtering technology in order to apply technical measures to specific types of online service providers. We also developed technologies in order to monitor and identify illegally distributed comics on webhard sites and to monitor and identify illegally distributed webtoons. Even though all comic books posted on webhard sites are illegal, it is no trouble to download and access popular comics by accessing websites in foreign countries. Even under these circumstances, the comic and webtoon copyright protection technologies developed over the past six years have been used at all. In this paper, we examine what the problems are and find solutions to propose a copyright protection method for webtoons.

• Journal of International Academy of Physical Therapy Research
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• v.12 no.1
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• pp.2261-2266
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• 2021

Background: Deep learning related research works on website medical images have been actively conducted in the field of health care, however, articles related to the musculoskeletal system have been introduced insufficiently, deep learning-based studies on classifying orthopedic manual therapy images would also just be entered. Objectives: To create a deep learning model that categorizes cervical mobilization images and establish a web application to find out its clinical utility. Design: Research and development. Methods: Three types of cervical mobilization images (central posteroanterior (CPA) mobilization, unilateral posteroanterior (UPA) mobilization, and anteroposterior (AP) mobilization) were obtained using functions of 'Download All Images' and a web crawler. Unnecessary images were filtered from 'Auslogics Duplicate File Finder' to obtain the final 144 data (CPA=62, UPA=46, AP=36). Training classified into 3 classes was conducted in Teachable Machine. The next procedures, the trained model source was uploaded to the web application cloud integrated development environment (https://ide.goorm.io/) and the frame was built. The trained model was tested in three environments: Teachable Machine File Upload (TMFU), Teachable Machine Webcam (TMW), and Web Service webcam (WSW). Results: In three environments (TMFU, TMW, WSW), the accuracy of CPA mobilization images was 81-96%. The accuracy of the UPA mobilization image was 43~94%, and the accuracy deviation was greater than that of CPA. The accuracy of the AP mobilization image was 65-75%, and the deviation was not large compared to the other groups. In the three environments, the average accuracy of CPA was 92%, and the accuracy of UPA and AP was similar up to 70%. Conclusion: This study suggests that training of images of orthopedic manual therapy using machine learning open software is possible, and that web applications made using this training model can be used clinically.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.1-14
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• 2019

Because of the characteristics of game software, it is important to quickly identify and reflect users' needs into game software after its launch. However, most sites such as the Google Play Store, where users can download games and post reviews, provide only very limited and ambiguous classification categories for game reviews. Therefore, in this paper, we develop an automatic classification system for game reviews that categorizes reviews into categories that are clearer and more useful for game providers. The developed system converts words in reviews into vectors using word2vec, which is a representative word embedding model, and classifies reviews into the most relevant categories by measuring the similarity between those vectors and each category. Especially, in order to choose the best similarity measure that directly affects the classification performance of the system, we have compared the performance of three representative similarity measures, the Euclidean similarity, cosine similarity, and the extended Jaccard similarity, in a real environment. Furthermore, to allow a review to be classified into multiple categories, we use a threshold-based multi-category classification method. Through experiments on real reviews collected from Google Play Store, we have confirmed that the system achieved up to 95% accuracy.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.5
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• pp.811-821
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• 2019

Image making for a person is a way to improve various factors that can express oneself, such as appearance, impression, and confidence. In general, people use mirror or camera as a traditional method to make their own image or perform presentation exercises. Recently, as smart mirrors are widely used in various fields, attempts to use smart mirrors as image making tools instead of mirrors have been frequently made. Smart Mirror is considered as a suitable tool to provide image making service because it can attach various devices such as a camera and a microphone in addition to the main advantage of a mirror that it is easily accessible. In this paper, we present BuddyMirror - a smart mirror software that provides image-making service to users, and a dedicated mobile app for flexibly running the mirror software. BuddyMirror provides functions for presentation, mock interview, and styling service at the request of users, interworking with the dedicated mobile app. We also describe the techniques developed for implementing and activating each of the new services as a module of MagicMirror, a widely used smart mirror development platform. The developed mobile app enables users to deliver presentations to BuddyMirror or to download the recorded video for image-making services.

• Smart Media Journal
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• v.13 no.6
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• pp.9-15
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• 2024

In recent trends, there has been an increase in 'Qshing' attacks, a hybrid form of phishing that exploits fake QR (Quick Response) codes impersonating government agencies to steal personal and financial information. Particularly, this attack method is characterized by its stealthiness, as victims can be redirected to phishing pages or led to download malicious software simply by scanning a QR code, making it difficult for them to realize they have been targeted. In this paper, we have developed a classification technique utilizing machine learning algorithms to identify the maliciousness of URLs embedded in QR codes, and we have explored ways to integrate this with existing QR code readers. To this end, we constructed a dataset from 128,587 malicious URLs and 428,102 benign URLs, extracting 35 different features such as protocol and parameters, and used AutoML to identify the optimal algorithm and hyperparameters, achieving an accuracy of approximately 87.37%. Following this, we designed the integration of the trained classification model with existing QR code readers to implement a service capable of countering Qshing attacks. In conclusion, our findings confirm that deriving an optimized algorithm for classifying malicious URLs in QR codes and integrating it with existing QR code readers presents a viable solution to combat Qshing attacks.