• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.393-406
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• 2015

We examine how to model mortality risk using the adaptation of the mean-reverting processes for the two factor model proposed by Cairns et al. (2006b). Mortality improvements have been recently observed in some countries such as United Kingdom; therefore, we assume long-run mortality converges towards a trend at some unknown time and the mean-reverting processes could therefore be an appropriate stochastic model. We estimate the parameters of the two-factor model incorporated with mean-reverting processes by a Metropolis-Hastings algorithm to fit United Kingdom mortality data from 1991 to 2015. We forecast the evolution of the mortality from 2014 to 2040 based on the estimation results in order to evaluate the issue price of a longevity bond of 25 years maturity. As an application, we propose a method to quantify the speed of mortality improvement by the average mean reverting times of the processes.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.75-96
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• 2016

This paper investigates the usefulness of drones in an urban delivery system. We define the vehicle and drone routing problem with time window (VDRPTW) and present a model that can describe a dual mode delivery system consisting of drones and vehicles in the metropolitan area. Drones are relatively free from traffic congestion but have limited flight range and capacity. Vehicles are not free from traffic congestion, and the complexity of urban road network reduces the efficiency of vehicles. Using drones and vehicles together can reduce inefficiency of the urban delivery system because of their complementary cooperation. In this paper, we assume that drones operate in a point-to-point manner between the depot and customers, and that customers in the need of fast delivery are willing to pay additional charges. For the experiment datasets, we use instances of Solomon (1987), which are well known in the Vehicle Routing Problem society. Moreover, to mirror the urban logistics demand trend, customers who want fast delivery are added to the Solomon's instances. We propose a hybrid evolutionary algorithm for solving VDRPTW. The experiment results provide different useful insights according to the geographical distributions of customers. In the instances where customers are randomly located and in instances where some customers are randomly located while others form some clusters, the dual mode delivery system displays lower total cost and higher customer satisfaction. In instances with clustered customers, the dual mode delivery system exhibits narrow competition for the total cost with the delivery system that uses only vehicles. In this case, using drones and vehicles together can reduce the level of dissatisfaction of customers who take their cargo over the time-window. From the view point of strategic flexibility, the dual mode delivery system appears to be more interesting. In meeting the objective of maximizing customer satisfaction, the use of drones and vehicles incurs less cost and requires fewer resources.

• Journal of KIISE:Information Networking
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• v.34 no.3
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• pp.186-192
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• 2007

The virus throttling technique[5,6] is the one of well-known worm early technique. Virus throttling reduce the worm propagration by delaying connection packets artificially. However the worm detection time is not sufficiently fast as expected when the worm generated worm packets at a low rate. This is because the virus throttling technique use only delay queue length. In this paper we use the trend of weighted average delay queue length (TW AQL). By using TW AQL, the worm detection time is not only shorten at a low rate Internet worm, but also the false alarm does not largely increase. By experiment, we also proved our proposed algorithm had better performance.

• Journal of KIISE:Information Networking
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• v.37 no.1
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• pp.1-7
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• 2010

Network Centric Warfare(NCW) is becoming a prominent concept in the current trend of warfare. To support high quality communication between strategic/tactical units in the concept of NCW, Tactical Airborne Networks are likely to be constructed in the near future to take part in the NCW. In these Tactical Airborne Networks with dynamic topology variations due to very high mobility of participants nodes, more efficient and reliable neighbor discovery protocols are needed. This paper presents the adaptive HELLO message scheduling algorithm for Tactical Airborne Network using directional antennas. The purposed algorithm can reduce the overhead of periodic HELLO message transfer, while guaranteeing successful data transmission. We concluded a mathematical analysis and simulation studies using Qualnet 4.5 for evaluation the performance and efficiency of the proposed scheme.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.785-794
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• 2002

Automatic stock trading systems should be able to solve various kinds of optimization problems such as market trend prediction, stock selection, and trading strategies, in a unified framework. But most of the previous trading systems based on supervised learning have a limit in the ultimate performance, because they are not mainly concerned in the integration of those subproblems. This paper proposes a stock trading system, called R-Trader, based on reinforcement teaming, regarding the process of stock price changes as Markov decision process (MDP). Reinforcement learning is suitable for Joint optimization of predictions and trading strategies. R-Trader adopts two popular reinforcement learning algorithms, temporal-difference (TD) and Q, for selecting stocks and optimizing other trading parameters respectively. Technical analysis is also adopted to devise the input features of the system and value functions are approximated by feedforward neural networks. Experimental results on the Korea stock market show that the proposed system outperforms the market average and also a simple trading system trained by supervised learning both in profit and risk management.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.289-294
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• 2014

In the recent enterprises and are utilizing the CRM using data mining techniques and new marketing plan. However, data mining techniques are necessary expertise, general public access is difficult, it will be subject to constraints of time and space. in this paper, in order to solve this problem, we have proposed a Mobile CRM applying the data mining method. Thus, to analyze the structure of an existing CRM system, and defines the data flow and format. Also, define the process of the system, was designed sales trend analysis algorithm and customer sales recommendation algorithm using data mining techniques. Evaluation of the proposed system, through the test scenario to ensure proper operation, it was carried out the comparison and verification with the existing system. Results of the test, the value of existing programs and data matches to verify the reliability and use queries the proposed statistical tables to reduce the analysis time of data, it was verified rapidity.

• Korean Journal of Oriental Medicine
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• v.12 no.2 s.17
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• pp.93-101
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• 2006

Pulse feeling is one of the most important diagnosis method in Oriental medicine. But it is not easy to make an objective and standardized diagnosis. In this study, we found how to quantify diagnosis. Specially dally the high practicality in clinic, we search some parameters especially well-related to floating and sinking pulse by statistic analysis. By extension, we find the pulse patterns of the floating and sinking pulse. We choose 15 subjects diagnosed as floating pulse and 15 subjects diagnosed as sinking pulse by oriental doctors. And their pulse signals were acquired by Pulse analyzer which has piezoresistive pressure sensor. For the quantification of the floating and sinking pulse, at first, we examined the parameters which were highly correlated with oriental doctor's diagnosis. And then we derived pulse patterns of the floating-sinking pulse from preprocessed signal and its ensemble average. We also looked trend variation (PH-Curve) between contact and pulse pressure. As a result, statistically there is the biggest difference between contact pressure, the maximum pulse pressure, diastolic area (Ad) and floating and sinking data. Through the PH-Curve, which represented the relationship between contact and pulse pressure, we could divide the floating and sinking pulse clearly. As a basic research of pulse diagnosis algorithm, we can contribute to select essential parameters in diagnosis algorithm And using these diagnosis method, we expect to find typical pulse patterns and some useful parameters about other pulses like slow/rapid, large/fine pulse and so on. We hope that this study will contribute pulse objectification.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.5
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• pp.1-12
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• 2013

Road's accidents caused by Ice, snow, Wet of roads surface conditions and weather conditions situations that are constantly occurring. That is, driver's negligence and safe driving ability of individuals due to lack of awareness, and Road management main agent(the government and the public, etc.) due to road conditions, if there is insufficient information. So Related research needs is a trend that is required. In this study, gather Camera(Stereo camera)'s image data, and analysis polarization coefficients and wavelet transform. And unlike traditional single-dimensional classification algorithms as multi-dimensional analysis by using SVM classification techniques, develop an algorithm to determine road conditions. Four on the road conditions (dry, wet, snow, ice) recognition success rate for the detection and analysis of experiments.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.103-108
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• 2016

With the growing trend of pervasive computing, (the idea that technology is moving beyond personal computers to everyday devices) there is a growing demand for lightweight ciphers to safeguard data in a network that is always available. For all block cipher applications, the AES is the preferred choice. However, devices used in pervasive computing have extremely constraint environment and as such the AES will not be suitable. In this paper we design and implement a new lightweight compact block cipher that takes advantage of both S-P network and the Feistel structure. The cipher uses the S-box of PRESENT algorithm and a key dependent one stage omega permutation network is used as the cipher's P-box. The cipher is implemented on iNEXT-V6 board equipped with virtex-6 FPGA. The design synthesized to 196 slices at 337 MHz maximum clock frequency.

• Science of Emotion and Sensibility
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• v.17 no.2
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• pp.111-122
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• 2014

This study has analyzed the scanning path algorithm shown at the process of exploring spatial information through an observation experiment with the object of lobby in subway station. In the estimation of observation time by section, the frequency of scanning type was found to increase as the observation time got longer, which makes it possible that the longer the observation lasts the more the observation interruptions occur. In addition, the observation slipped out of the range of imaging when any fatigue was caused from the observation or the more active exploration took place. Furthermore, when the trend line was employed for the examination of the changes to the scanning type by time section, "concentration" "diagonal or vertical" showed a sharp and a gentle increases along with the increase of time section respectively, while "circulation. combination, horizontal" showed a reduction. The observation data of the subjects observing a space include various visual information. The analysis of the scanning type found at "attention concentration" enabled to draw this significant conclusion. The features of increase and decrease of scanning types can be a fundamental data for understanding the scanning tendency by time.