• 한국정보통신학회논문지
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• 제12권12호
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• pp.2323-2329
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• 2008

저가형 이미지 센서 기술의 발전과 무선 센서 네트워크 기술의 발전으로 인해 WMSN(Wireless Multimedia Sensor Networks) 기술이 활발히 연구되고 있다. WMSN은 기존의 무선 센서 네트워크 기술에 멀티미디어 컨텐츠를 센싱하고 전송 및 처리하는 기반기술을 포함한다. 멀티미디어 컨텐츠는 많은 데이터량을 가지므로 이를 처리하기 위해서는 많은 컴퓨팅 자원과 높은 네트워크 대역폭을 필요로 한다. 저사양의 센서 노드에서 멀티미디어 컨텐츠를 수용하기 위해서는 컴퓨팅 자원을 고려한 압축 기법 및 효율적인 전송에 대한 연구가 필요하다. 본 논문에서는 무선 센서 네트워크에서 이미지를 효율적으로 압축하고 전송하기 위한 압축기법인 YWCE기법을 제안한다. YWCE는 웨이블릿의 Resolution Scalability 특성을 이용한 4가지 움직임 보상/예측 기법을 도입한다. 실험을 통하여 4가지 각 압축 기법들의 조합에 따라 매우 높은 성능을 나타냄을 보였다.

• Journal of Information Technology Applications and Management
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• 제30권1호
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• pp.21-32
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• 2023

This study presents a way to design picture books that allow children to experience indirectly through realistic media at home and educational institutions for children whose direct experiences and activities are reduced offline in the post-COVID-19 era. The development and popularization of realistic media such as AR continues to be grafted and developed in the picture book field, and the advantage of this picture book is that children at the stage before learning letters can feel the story and character situation of the book through the experience of AR and QR animation in the picture book. In this process, you can get access to imaginary areas that can not be experienced in flat-panel illustrations with spatial animation to help improve the scalability and literacy of the story contained on the page. Children's education through realistic animation can increase the learning effect and needs to continue after COVID-19. Therefore, by presenting the process of viewing and experiencing picture books using AR and QR, the result of the study suggests that the design process of realistic picture books is not just a combination of technology, but a process of expanding children's perception and imagination. This study aims to find out how visual perception is designed differently by analyzing the differences and characteristics of each animation design, focusing on the AR and QR picture book "Where am I?" published by the researcher, and to contribute to the active introduction and development of realistic animation in the field of children's picture books and education.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.276-279
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• 2005

As the Ubiquitous generation approaches, the importance of the sensor data processing is growing. The data approximation scheme, one of the data processing methods, can be the key of sensor data processing, for it is related not only to the lifetime of sensors but also to the size of the storage. In this paper, we propose the Harmonic Wavelet transform which can minimize the relative error for given sensor data. Harmonic Wavelets use the harmonic mean as a representative which is the minimum point of the maximum relative error between two data values. In addition, Harmonic Wavelets retain the relative errors as wavelet coefficients so we can select proper wavelet coefficients that reduce the relative error more easily. We also adapt the greedy algorithm for local optimization to reduce the time complexity. Experimental results show the performance and the scalability of Harmonic Wavelets for sensor data.

• Journal of information and communication convergence engineering
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• 제16권2호
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• pp.99-105
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• 2018

k-Nearest neighbor join (k-NN Join) is a computationally intensive algorithm that is designed to find k-nearest neighbors from a dataset S for every object in another dataset R. Most related studies on k-NN Join are based on single-computer operations. As the data dimensions and data volume increase, running the k-NN Join algorithm on a single computer cannot generate results quickly. To solve this scalability problem, we introduce the locality-sensitive hashing (LSH) k-NN Join algorithm implemented in Spark, an approach for high-dimensional big data. LSH is used to map similar data onto the same bucket, which can reduce the data search scope. In order to achieve parallel implementation of the algorithm on multiple computers, the Spark framework is used to accelerate the computation of distances between objects in a cluster. Results show that our proposed approach is fast and accurate for high-dimensional and big data.

• Journal of Information Technology Applications and Management
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• 제26권5호
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• pp.57-65
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• 2019

Recommendation Systems are information technologies that E-commerce merchants have adopted so that online shoppers can receive suggestions on items that might be interesting or complementing to their purchased items. These systems stipulate valuable assistance to the user's purchasing decisions, and provide quality of push service. Traditionally, Recommendation Systems have been designed using a centralized system, but information service is growing vast with a rapid and strong scalability. The next generation of information technology such as Cloud Computing and Big Data Environment has handled massive data and is able to support enormous processing power. Nevertheless, analytic technologies are lacking the different capabilities when processing big data. Accordingly, we are trying to design a conceptual service model with a proposed new algorithm and user adaptation on dynamic recommendation service for big data environment.

• 한국전자거래학회지
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• 제7권3호
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• pp.93-103
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• 2002

The combination of data warehousing and Internet technology produces a new concept - web warehousing. Due to the availability of web technologies and the need to make prompt decisions with timely information, web warehousing is emerging as a key strategic business weapon. Yet despite the many promising benefits of web warehousing, researchers have also identified several challenges, including scalability and availability. With the rise of the Internet and data centric computing applications, the use of new Storage Area Network (SAN) technology has been spotlighted for the possibility of a new data repository for web warehousing. In this article, the two new concepts of web warehousing and storage area networks are introduced. In particular, a SAN is discussed in detail as an alternative data repository to overcome the current limitations of web warehousing.

• 천문학회보
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• 제42권2호
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• pp.88.3-89
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• 2017

We present our experiences with open-source NoSQL database systems in analyzing spatial and temporal astronomical data. We conduct experiments of using Redis in-memory NoSQL database system by modifying and exploiting its support of geohash for astronmical spatial data. Our experiment focuses on performance, cost, difficulty, and scalability of the database system. We also test OpenTSDB as a possible NoSQL database system to process astronomical time-series data. Our experiments include ingesting, indexing, and querying millions or billions of astronomical time-series measurements. We choose our KMTNet data and the public VVV (VISTA Variables in the Via Lactea) catalogs as test data. We discuss issues in using these NoSQL database systems in astronomy.

• 대한임베디드공학회논문지
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• 제6권6호
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• pp.377-382
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• 2011

This paper describes the method of data synchronization among devices for personal cloud services. Existing data synchronization for mobile devices is based on a central server to mobile devices or a PC to a mobile device. However, the purpose of this paper is to share user data in heterogeneous environments, without depending on central server. This technology can be applied to synchronize personal data between a device and a personal cloud storage for personal cloud services. The ad hoc synchronization needs a sync agent service discovery module, a user authentication module, a network adapter, and an application data synchronization module. The method described in this paper is better than existing synchronization technology based on client-server in availability, performance, scalability quality attributes.

• International Journal of Computer Science & Network Security
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• 제21권12spc호
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• pp.451-458
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• 2021

Providing a secure and effective way to protect confidential and private data is an urgent process, and accordingly, we will present in this research paper a new method, which is called multiple rounds variable block method (MRVB) which depends on the use of a colored image that is kept secret to generate needed work and round keys. This method can be used to encrypt-decrypt data using various lengths private key and data blocks with various sizes. The number of rounds also will be variable starting from one round. MRVB will be implemented and compared with the encryption-decryption standards DES and AES to show the improvements provided by the proposed method in increasing the security level and in increasing the throughput of the process of data cryptography. The generated private key contents will depend on the used image_key and on the selected number of rounds and the selected number of bytes in each block of data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권4호
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• pp.1146-1165
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• 2022

A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology. Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making. Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details. In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment. Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.