• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제3권8호
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• pp.321-328
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• 2014

본 논문에서는 모바일 기기 사용자들의 다음 방문 장소를 효율적으로 예측할 수 있는 맵리듀스 기반의 이동 패턴 마이닝 시스템을 소개한다. 이 시스템은 대용량의 사용자 이동 궤적 데이터 집합으로부터 은닉 마코프 모델로 표현되는 각 사용자의 이동 패턴을 학습해내고, 이 모델을 현재 이동 궤적에 적용함으로써 다음 방문 장소를 예측한다. 본 시스템은 사용자별 이동 패턴 모델을 학습하는 후단부와 실시간으로 다음 방문 장소를 예측하는 전단부 등 크게 두 부분으로 구성된다. 이 중에서 후단부는 주요 장소 추출, 이동 궤적 변환, 이동 패턴 모델 학습 등 총 3개의 맵리듀스 작업 모듈들로 구성된다. 이에 반해, 본 시스템의 전단부는 이동 경로 후보군 생성, 다음 장소 예측 등 총 2개의 작업 모듈들로 구성된다. 그리고 본 시스템을 구성하는 각 작업 모듈의 맵과 리듀스 함수들은 하둡 인프라를 효과적으로 활용하여 병렬 처리를 극대화할 수 있도록 설계하였다. 대용량의 공개 벤치마크 데이터 집합인 GeoLife를 이용하여 본 논문에서 소개한 시스템의 성능을 분석하기 위한 실험들을 수행하였고, 실험 결과를 통해 본 시스템의 높은 성능을 확인할 수 있었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(1)
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• pp.285-288
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• 2001

In this paper, we propose strategies that eliminating packet loss and minimize delay time during handoff under wireless LAN environments. As a mobile host moves between cells, a handoff takes place. A few handoff protocol have been proposed to eliminate the packet loss, but they have a heavy overhead. So, We proposed handoff protocol using the next-cell prediction scheme that send not to current BS but to mobile host and next BS, therefore next BS buffered packet send mobile host after handoff. We also present simulation results for our simulation using the Network Simulator (ns2). The simulations show that our handoff scheme is no packet loss.

• Journal of Communications and Networks
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• 제11권4호
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• pp.337-349
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• 2009

In this paper, we introduce a novel mobility model for mobile sinks in which the sinks move towards randomly distributed destinations, where each destination is associated with a mission. The novel mobility model is termed the random mobility with destinations. There have been many studies on mobile sinks; however, they merely support two extreme cases of sink mobility. The first case features the most common and general mobility, with the sinks moving randomly, unpredictably, and inartificially. The other case takes into account mobility only along predefined or determined paths such that the sinks can gather data from sensor nodes with minimum overhead. Unfortunately, these studies for the common mobility and predefined path mobility might not suit for supporting the random mobility with destinations. In order to support random mobility with destination, we propose a new protocol, in which the source nodes send their data to the next movement path of a mobile sink. To implement the proposed protocol, we first present a mechanism for predicting the next movement path of a mobile sink based on its previous movement path. With the information about predicted movement path included in a query packet, we further present a mechanism that source nodes send energy-efficiently their data along the next movement path before arriving of the mobile sink. Last, we present mechanisms for compensating the difference between the predicted movement path and the real movement path and for relaying the delayed data after arriving of the mobile sink on the next movement path, respectively. Simulation results show that the proposed protocol achieves better performance than the existing protocols.

• 정보처리학회논문지C
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• 제12C권5호
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• pp.701-708
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• 2005

무선 통신망에서 다양한 요구의 QoS(Quality of Service)를 보장하고 한정된 대역폭을 효과적으로 사용하기 위한 기법에는 이동성 예측 기법과 채널 할당 기법이 있다. 이러한 이동성 예측 기법들 중에서는 가장 최근에 제안되었으며, 셀 내부의 이동 경로를 저장하는 방법을 사용하는 Detailed-ZMHB 알고리즘이 가장 우수한 성능을 보인다. 또한, 여러 채널 할당 기법 중에서 핸드오프 호(Handoff Call)의 접속 실패율을 줄이기 위하여, 핸드오프 호에 우선순위를 두어 다소의 신규 호 블록킹율을 감수하고, 핸드오프 호의 접속 실패율(Dropping Probability)을 낮추는 방법들이 제안되었다. 특히, CDMA(Code Division Multiple Access) 시스템에서의 소프트 핸드오프의 경우, 신호의 세기에 따라 인접한 셀 중 두 개를 선택하여 채널을 예약하는 방법을 사용한다. 본 논문에서는 핸드오프 호의 접속 실패율을 줄이기 위하여, 예측 알고리즘에서 사용하는 이동 경로 저장 방법을 이용하는 새로운 채널 예약 기법을 제안한다. 그 결과로, 본 논문에서 제안한 채널 예약 기법이 기존의 기법보다 핸드오프 호의 접속 실패율이 약 67-71$\%$정도 낮다.

• 한국소음진동공학회논문집
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• 제12권5호
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• pp.365-373
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• 2002

This paper concerns the design and application of an electro-rheological (ER) fluid damper to semiactive vibration control of rotor systems. In particular, the system under present study is constructed structurally flexible in order to explore multiple critical speeds within operation range. To this end, the dynamic models of the proposed ER damper and its associated amplifier are derived in the first place. Subsequently entire rotor system model is assembled along with the dynamics of the end effector based on a finite element method enabling prediction as to its free and forced vibration characteristics. Next, an artificial intelligent (AI) feedback controller is synthesized taking into account the peculiarity of Coulomb damping effect in rotor applications. Finally, computational and experimental results are presented including model validation and control performances. In practice, such an AI control proved effective whether the spin speed was either before or after critical speeds.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 춘계학술발표대회
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• pp.777-780
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• 2014

본 논문에서는 휴대용 기기 사용자들의 이동 궤적을 기록한 대용량의 GPS 위치 데이터 집합으로부터 각 사용자의 이동 패턴 모델을 학습해내고, 이 모델을 적용하여 각 사용자의 다음 방문 장소를 효율적으로 예측할 수 있는 맵리듀스 기반의 분산 데이터 마이닝 시스템을 소개한다. 본 시스템은 크게 사용자별 이동 패턴 모델을 학습하는 후단부와 실시간으로 다음 방문 장소를 예측하는 전단부로 구성된다. 이 중에서 후단부는 주요 장소 추출, 이동 궤적 변환, 이동 패턴 모델 학습 등 총 3개의 맵리듀스 작업 모듈들로 구성된다. 이에 반해, 본 시스템의 전단부는 이동 경로 후보군 생성, 다음 장소 예측 등 총 2개의 맵리듀스 작업 모듈들로 구성된다. 그리고 본 시스템을 구성하는 각각의 작어마다 분산처리를 극대화할 수 있도록 맵과 리듀스 함수를 설계하였다. 끝으로, 대용량의 GeoLife 벤치마크 데이터 집합을 이용하여 본 논문에서 소개한 시스템의 예측 성능을 분석하기 위한 실험을 수행하였고, 이를 통해 본 시스템의 높은 성능을 확인할 수 있었다.

• 경영과학
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• 제22권1호
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• pp.179-197
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• 2005

This study examines market acceptance for DMB service, one of the touted new business models in Korea's next-generation mobile communications service market, using adoption end diffusion of innovation as the theoretical framework. Market acceptance for DMB service was assessed by predicting the demand for the service using the Bass model, and the demand variability over time was then analyzed by integrating the innovation adoption model proposed by Rogers (2003). In our estimation of the Bass model, we derived the coefficient of innovation and coefficient of imitation, using actual diffusion data from the mobile telephone service market. The maximum number of subscribers was estimated based on the result of a survey on satellite DMB service. Furthermore, to test the difference in diffusion pattern between mobile phone service and satellite DMB service, we reorganized the demand data along the diffusion timeline according to Rogers' innovation adoption model, using the responses by survey subjects concerning their respective projected time of adoption. The comparison of the two demand prediction models revealed that diffusion for both took place forming a classical S-curve. Concerning variability in demand for DMB service, our findings, much in agreement with Rogers' view, indicated that demand was highly variable over time and depending on the adopter group. In distinguishing adopters into different groups by time of adoption of innovation, we found that income and lifestyle (opinion leadership, novelty seeking tendency and independent decision-making) were variables with measurable impact. Among the managerial variables, price of reception device, contents type, subscription fees were the variables resulting in statistically significant differences. This study, as an attempt to measure the market acceptance for satellite DMB service, a leading next-generation mobile communications service product, stands out from related studies in that it estimates the nature and level of acceptance for specific customer categories, using theories of innovation adoption and diffusion and based on the result of a survey conducted through one-to-one interviews. The authors of this paper believe that the theoretical framework elaborated in this study and its findings can be fruitfully reused in future attempts to predict demand for new mobile communications service products.

• Asian Pacific Journal of Cancer Prevention
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• 제15권6호
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• pp.2785-2791
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• 2014

Aims: To analyze time-dependent changes in female breast cancer (BC) mortality in China, forecast the trend in the ensuing 5 years, and provide recommendations for prevention and management. Materials and Methods: Mortality data of breast cancer in China from 1991 to 2011 was used to describe characteristics and distribution, such as the changes of the standardized mortality rate, urban-rural differences and age differences. Trend-surface analysis was used to study the geographical distribution of mortality. In addition, curve estimation, time series modeling, Gray modeling (GM) and joinpoint regression were performed to estimate and predict future trends. Results: In China, the mortality rate of breast cancer has increased yearly since 1991. In addition, our data predicted that the trend will continue to increase in the ensuing 5 years. Rates in urban areas are higher than those in rural areas. Over the past decade, all peak ages for death by breast cancer have been delayed, with the first death peak occurring at 55 to 65 years of age in urban and rural areas. Geographical analysis indicated that mortality rates increased from Southwest to Northeast and from West to East. Conclusions: The standardized mortality rate of breast cancer in China is rising and the upward trend is predicted to continue for the next 5 years. Since this can cause an enormous health impact in China, much better prevention and management of breast cancer is needed. Consequently, disease control centers in China should place more focus on the northeastern, eastern and southeastern parts of China for breast cancer prevention and management, and the key population should be among women between ages 55 to 65, especially those in urban communities.

• 한국안전학회지
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• 제35권3호
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• pp.96-104
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• 2020

The numerical simulations were conducted to investigate the thermal-fluid phenomena occurred inside the experimental apparatus during a PCCS, used to remove heat released in accidents from a containment of light water nuclear power plant, operation. Numerical simulations of the flow and heat transfer caused by wall condensation inside the containment simulation vessel (CSV), which equipped with 18 vertical heat exchanger tubes, were conducted using the commercial computational fluid dynamics (CFD) software ANSYS-CFX. Shear stress transport (SST) and the wall condensation model were used for turbulence closure and wall condensation, respectively. The simulation using the actual size of the apparatus. However, rather than simulating the whole experimental apparatus in consideration of the experimental cases, calculation resources, and calculation time, the simulation model was prepared only in CSV. Selective simulation was conducted to verify the effects of non-condensable gas(NC gas) concentration, CSV internal pressure, and wall sub-cooling conditions. First, as a result of the internal flow of CSV, it was observed that downward flow due to condensation occurred surface of the vertical tube and upward flow occurred in the distant place. Natural convection occurred actively around the heat exchanger tube. Due to this rising and falling internal flow, natural circulation occurred actively around the heat exchanger tubes. Next, in order to check the performance of built-in condensation model using according to the non-condensable gas concentration, CSV internal flow and wall sub-cooling, the heat flux values were compared with the experimental results. On average, the results were underestimated with and error of about 25%. In addition, the influence of CSV internal pressure and wall sub-cooling was small, but when the condensate was highly generated due to the low non-condensable gas concentration, the error was large compared to the experimental values. This is considered to be due to the nature of the condensation model of the CFX code. However, in spite of the limitations of CFD, it is valid to use the built-in condensation model of CFD for PCCS performance prediction from a conservative perspective.

• 로봇학회논문지
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• 제16권4호
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• pp.336-344
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• 2021

This paper presents a robust deep learning-based human tracking framework in crowded environments. For practical human tracking applications, a target must be robustly tracked even in undetected or overcrowded situations. The proposed framework consists of two parts: robust deep learning-based human detection and tracking while recognizing the aforementioned situations. In the former part, target candidates are detected using Detectron2, which is one of the powerful deep learning tools, and their weights are computed and assigned. Subsequently, a candidate with the highest weight is extracted and is utilized to track the target human using a Kalman filter. If the bounding boxes of the extracted candidate and another candidate are overlapped, it is regarded as a crowded situation. In this situation, the center information of the extracted candidate is compensated using the state estimated prior to the crowded situation. When candidates are not detected from Detectron2, it means that the target is completely occluded and the next state of the target is estimated using the Kalman prediction step only. In two experiments, people wearing the same color clothes and having a similar height roam around the given place by overlapping one another. The average error of the proposed framework was measured and compared with one of the conventional approaches. In the error result, the proposed framework showed its robustness in the crowded environments.