• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.8
• /
• pp.321-328
• /
• 2014

In this paper, we present a MapReduce-based mobility pattern mining system which can predict efficiently the next place of mobile users. It learns the mobility pattern model of each user, represented by Hidden Markov Models(HMM), from a large-scale trajectory dataset, and then predicts the next place for the user to visit by applying the learned models to the current trajectory. Our system consists of two parts: the back-end part, in which the mobility pattern models are learned for individual users, and the front-end part, where the next place for a certain user to visit is predicted based on the mobility pattern models. While the back-end part comprises of three distinct MapReduce modules for POI extraction, trajectory transformation, and mobility pattern model learning, the front-end part has two different modules for candidate route generation and next place prediction. Map and reduce functions of each module in our system were designed to utilize the underlying Hadoop infrastructure enough to maximize the parallel processing. We performed experiments to evaluate the performance of the proposed system by using a large-scale open benchmark dataset, GeoLife, and then could make sure of high performance of our system as results of the experiments.

• Proceedings of the IEEK Conference
• /
• 2001.06a
• /
• pp.285-288
• /
• 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
• /
• v.11 no.4
• /
• pp.337-349
• /
• 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.

• The KIPS Transactions:PartC
• /
• v.12C no.5 s.101
• /
• pp.701-708
• /
• 2005

The mobility prediction algorithm and the channel reservation scheme have been reported as an effective means to provide QoS guarantees and the efficient resource reservation in wireless networks. Among these prediction algorithms, the recently proposed Detailed-ZMHB algorithm makes use of the history of the user's positions within the current cell to predict the next cell, which provides the better prediction accuracy than the others. The handoff prioritizing schemes are proposed to provide improved performance at the expense of an increase in the blocking probability of new calls. In the soft handoff of the CDMA systems, a mobile can communicate via two adjacent cells simultaneously for a while before the actual handoff takes place. In this paper, we propose a new channel reservation scheme making use of the user mobility pattern information in order to reduce the call dropping probability. Our results show that the proposed scheme gives about 67.5-71.1$\%$ lower call dropping probability, compared to the existing scheme.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.12 no.5
• /
• pp.365-373
• /
• 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.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2014.04a
• /
• pp.777-780
• /
• 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.

• Korean Management Science Review
• /
• v.22 no.1
• /
• pp.179-197
• /
• 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
• /
• v.15 no.6
• /
• pp.2785-2791
• /
• 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.

• Journal of the Korean Society of Safety
• /
• v.35 no.3
• /
• pp.96-104
• /
• 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.

• The Journal of Korea Robotics Society
• /
• v.16 no.4
• /
• pp.336-344
• /
• 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.