• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 춘계학술발표대회
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• pp.79-81
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• 2019

Collecting data in wireless sensor networks in minimum time is a traditional problem which is known NP-hard. Previous studies built the schedule using the node-based or link-based metrics to prioritize the transmissions. In this work, we combine the effect of both metrics to obtain a smaller aggregation time. We compare our work with state of the art schemes and report the improvement.

• 디지털산업정보학회논문지
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• 제9권2호
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• pp.81-87
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• 2013

In this paper, we present an implementation of Long Term Evolution (LTE) Uplink (UL) system on a Software Defined Radio (SDR) platform using a conventional Personal Computer (PC), which adopts Graphic Processing Units (GPU) and Universal Software Radio Peripheral2 (USRP2) with URSP Hardware Driver (UHD) for SDR software modem and Radio Frequency (RF) transceiver, respectively. We have adopted UHD because UHD provides flexibility in the design of transceiver chain. Also, Cognitive Radio (CR) engine have been implemented by using libraries from UHD. Meanwhile, we have implemented the software modem in our system on GPU which is suitable for parallel computing due to its powerful Arithmetic and Logic Units (ALUs). From our experiment tests, we have measured the total processing time for a single frame of both transmit and receive LTE UL data to find that it takes about 5.00ms and 6.78ms for transmit and receive, respectively. It particularly means that the implemented system is capable of real-time processing of all the baseband signal processing algorithms required for LTE UL system.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1986년도 춘계학술발표회 논문집
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• pp.113-118
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• 1986

Nowdays switching software designs are based on the concept of maximizing efficiency. This idea is to put through the most call, in the fastest time, using the fewest possible resources. So the memory usages are embossed one of the most important part to be considered in the switching software. This paper discusses the general concepts of switching software at first, then describes the switching data base from the view point of the access time, memory efficiency, and call processing environment.

• 산업경영시스템학회지
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• 제15권25호
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• pp.53-62
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• 1992

Computer software users develop and utilize their application software by themselves since Processing methods are different by quantity and qualify of the information The developed model needs input data and error numbers generated during the testing phases. However. total error numbers of the existing model and each error time was needed as data for developing the new model. But, maximum likelihood estimation must be used to exponential model of binomial-type and estimating of parameters by using the searched data. Parameter estimation can be done with trial and error or simulation.

• Journal of Information Processing Systems
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• 제8권4호
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.544-547
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• 2007

Because data processing systems in recent years are more complicated, main function of the data processing is divided as several sub-functions which are implemented and verified in each subsystem of the data processing system. For the verification of data processing system, many interface tests among subsystems are required and also a lot of simulation systems are demanded. This paper proposes CTHS (Common Test Harness System) for satellite ground segment development which has all of functions for interface test of the data processing system in one PC. Main functions of the CTHS software are data interface, system log generation, and system information display. For the interface test of the data processing system, all of actions of the CTHS are executed by a pre-defined operation scenario which is written by purpose of the data processing system test.

• 한국정보처리학회논문지
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• 제3권5호
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• pp.1112-1120
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• 1996

소프트웨어 개발시에 소프트웨어 개발팀의 생산성을 향상시키기 위한 방법 중의 하나가 한번 사용한 소프트웨어 컴포넌트를 재사용하는 것이다. 이러한 재사용할 수 있는 소프트웨어는 종종 소프트웨어 라이브러리로써 구성된다. 라이브러리로부터 선택 된 소프트웨어 모듈을 효과적으로 재사용하기 위해서 사용자가 쉽게 찾을 수 있는 충분한 정보를 필요로 한다. 본 논문에서는 소프트웨어 컴포넌트 재사용을 위해 클래스간의 릴레이션쉽 정보를 제공하고 사용자가 원하는 컴포넌트가 라이브러리에 없는 경우 클래스에서 원하는 데이터와 함수만을 가져와 합성만을 가져와 합성할 수 있을 설계 및 구현하였다.

• 한국통신학회논문지
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• 제42권2호
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• pp.460-470
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• 2017

본 논문은 intelligent SSD (iSSD)를 통해 빅 데이터 마이닝을 효과적으로 처리하기 위한 방안에 대해서 소개한다. iSSD는 데이터 전송 비용을 줄이고 데이터가 저장된 장소와 가장 가까운 곳에서 데이터를 처리하기 위해, SSD 내부에 데이터 처리 능력을 부여한 장치이다. 본 논문에서는 먼저, iSSD의 등장 배경 및 효율적인 데이터 처리를 위한 iSSD 구조에 대해 소개한다. 더 나아가, iSSD를 이용하여 데이터 마이닝 알고리즘들을 빠르게 수행하는 방안을 소개한다. 끝으로, iSSD 뿐만 아니라 호스트 CPU, GPU 등 이질 (heterogeneous) 컴퓨팅 자원을 함께 활용하여 데이터 마이닝 알고리즘의 성능을 크게 향상시키는 협업 방안을 소개한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 춘계학술발표대회
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• pp.677-679
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• 2017

Data convergecast is an indispensable task for any WSN applications. Typically, scheduling in the WSN consists of two phases: tree construction and scheduling. The optimal tree structure and scheduling for the network is proven NP-hard. This paper focuses on the delay optimality while constructing the data convergecast tree. The algorithm can take any tree as the input, and by performing the switches (i.e. a node changes its parent), the expected aggregation delay is potentially reduced. Note that while constructing the tree, only the in-tree collisions between the child nodes sending data to their common parent is considered.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.658-673
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• 2021

Data deduplication technology improves data storage efficiency while storing and managing large amounts of data. It reduces storage requirements by determining whether replicated data is being added to storage and omitting these uploads. Data deduplication technologies require data confidentiality and integrity when applied to cloud storage environments, and they require a variety of security measures, such as encryption. However, because the source data cannot be transformed, common encryption techniques generally cannot be applied at the same time as data deduplication. Various studies have been conducted to solve this problem. This white paper describes the basic environment for data deduplication technology. It also analyzes and compares multiple proposed technologies to address security threats.