• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.4 s.175
• /
• pp.1007-1015
• /
• 2000

This paper proposes an adaptive trajectory generation strategy of using on-line ZMP information and an impedance control method for biped robots. Since robots experience various disturbances during their locomotion, their walking mechanism should have the robustness against those disturbances, which requires an on-line adaptation capability. In this context, an on-line trajectory planner is proposed to compensate the required moment for recovering stability. The ZMP equation and sensed ZMP information are used in this trajectory generation strategy. In order to control a biped robot to be able to walk stably, its controller should guarantee stable footing at the moment of feet contacts with the ground as well as maintaining good trajectory tracking performance. Otherwise, the stability of robot will be significantly compromised. To reduce the magnitude of an impact and guarantee a stable footing when a foot contacts with the ground, this paper. proposes to increase the damping of the leg drastically and to modify the reference trajectory of the leg. In the proposed control scheme, the constrained leg is controlled by impedance control using the impedance model with respect to the base link. Computer simulations performed with a 3-dof environment model that consists of combination of a nonlinear and linear compliant contact model show that the proposed controller performs well and that it has robustness against unknown uneven surface. Moreover, the biped robot with the proposed trajectory generator can walk even when it is pushed with a certain amount of external force.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.21 no.5
• /
• pp.1-9
• /
• 2007

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the coner and iron losses. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the hybrid artificial intelligent controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.6
• /
• pp.2099-2105
• /
• 2017

In a power system that has a high wind penetration, the output power fluctuation of a large-scale wind turbine generator (WTG) caused by the varying wind speed increases the maximum frequency deviation, which is an important metric to assess the quality of electricity, because of the reduced system inertia. This paper proposes a stable power-smoothing scheme of a doubly-fed induction generator (DFIG) that can suppress the maximum frequency deviation, particularly for a power system with a high wind penetration. To do this, the proposed scheme employs an additional control loop relying on the system frequency deviation that operates in combination with the maximum power point tracking control loop. To improve the power-smoothing capability while guaranteeing the stable operation of a DFIG, the gain of the additional loop is modified with the rotor speed and frequency deviation. The gain is set to be high if the rotor speed and/or frequency deviation is large. The simulation results based on the IEEE 14-bus system demonstrate that the proposed scheme significantly lessens the output power fluctuation of a WTG under various scenarios by modifying the gain with the rotor speed and frequency deviation, and thereby it can regulate the frequency deviation within a narrow range.

• The KIPS Transactions:PartD
• /
• v.10D no.4
• /
• pp.577-590
• /
• 2003

The shape-based retrieval is defined as the operation that searches for the (sub) sequences whose shapes are similar to that of a query sequence regardless of their actual element values. In this paper, we propose a similarity model suitable for shape-based retrieval and present an indexing method for supporting the similarity model. The proposed similarity model enables to retrieve similar shapes accurately by providing the combination of various shape-preserving transformations such as normalization, moving average, and time warping. Our indexing method stores every distinct subsequence concisely into the disk-based suffix tree for efficient and adaptive query processing. We allow the user to dynamically choose a similarity model suitable for a given application. More specifically, we allow the user to determine the parameter p of the distance function $L_p$ when submitting a query. The result of extensive experiments revealed that our approach not only successfully finds the subsequences whose shapes are similar to a query shape but also significantly outperforms the sequence search.

• Journal of KIISE:Software and Applications
• /
• v.37 no.9
• /
• pp.694-705
• /
• 2010

The mutation operation is the main operation in the evolutionary programming which has been widely used for the optimization of real valued function. In general, the mutation operation utilizes both a probability distribution and its parameter to change values of variables, and the parameter itself is subject to its own mutation operation which requires other parameters. However, since the optimal values of the parameters entirely depend on a given problem, it is rather hard to find an optimal combination of values of parameters when there are many parameters in a problem. To solve this shortcoming at least partly, if not entirely, in this paper, we propose a new mutation operation in which the parameter for the variable mutation is theoretically estimated from the self-adaptive perspective. Since the proposed algorithm estimates the scale parameter of the Cauchy probability distribution for the mutation operation, it has an advantage in that it does not require another mutation operation for the scale parameter. The proposed algorithm was tested against the benchmarking problems. It turned out that, although the relative superiority of the proposed algorithm from the optimal value perspective depended on benchmarking problems, the proposed algorithm outperformed for all benchmarking problems from the perspective of the computational time.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.1
• /
• pp.185-190
• /
• 2014

Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high-lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness-associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

• Journal of Digital Convergence
• /
• v.11 no.4
• /
• pp.153-164
• /
• 2013

Business model innovation creates differentiated value to customers by transforming various elements of doing business. Rather than focusing singularly on either the external or internal environment, the business model innovation aims to identify the optimal combination of internal resources, competence, and the external factors, such as customer's needs and new opportunity. However, due to lack of clear definition of business model innovation, and inability to generate company's core business model, business model innovation has been difficult for companies to lead next growth. This paper reviews existing definitions of business model innovation and explore existing types of business model innovation and timing of business model innovation through two case studies. Concept of business model innovation which we identify, is composed of value proposition, value creation through value chains and networks, and profit model innovation. Finally, we demonstrates that already successful businesses can also create new values through business model innovation and adaptive advantage, even in a rapidly changing market environment.

• Journal of the Korea Concrete Institute
• /
• v.14 no.6
• /
• pp.1022-1031
• /
• 2002

This paper presents efficient models for bridge structures using CART-ANFIS (classification and regression tree-adaptive neuro fuzzy inference system). A fuzzy decision tree partitions the input space of a data set into mutually exclusive regions, each region is assigned a label, a value, or an action to characterize its data points. Fuzzy decision trees used for classification problems are often called fuzzy classification trees, and each terminal node contains a label that indicates the predicted class of a given feature vector. In the same vein, decision trees used for regression problems are often called fuzzy regression trees, and the terminal node labels may be constants or equations that specify the predicted output value of a given input vector. Note that CART can select relevant inputs and do tree partitioning of the input space, while ANFIS refines the regression and makes it continuous and smooth everywhere. Thus it can be seen that CART and ANFIS are complementary and their combination constitutes a solid approach to fuzzy modeling.

• The KIPS Transactions:PartC
• /
• v.9C no.3
• /
• pp.375-384
• /
• 2002

In the current Internet, the QoS of interactive applications is hardly guaranteed because of variable bandwidth, packet loss and delay. Moreover, VoIP which is becoming an important part of the information infra-structure in these days, is susceptible to network packet loss and end-to-end delay. Therefore, it needs error control mechanisms in network level or application level. The FEC-based error control mechanisms are used for interactive audio application such as VoIP. The FEC sends a main information along with redundant information to recover the lost packets and adjusts redundant information depending on network conditions to reduce the bandwidth overhead. However, because most of the error control mechanisms do not consider end-to-end delay but packet loss rate, their performances are poor. In this paper, we propose a new error control algorithm, SCCRP, considering packet loss rate as well as end-to-end delay. Through experiments, we confirm that the SCCRP has a lower packet loss rate and a lower end-to-end delay after reconstruction.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.1
• /
• pp.89-99
• /
• 2011

In this paper, we propose an routing algorithm for ultra low power and high reliable transmission in WBAN environment. This algorithm is to minimize energy consumption and to maximize the life and reliability for medical devices. Also, this algorithm is not only medical devices but also non-medical devices is to minimize energy consumption and to maximize the life of device. The combination of the distance from the previous node and residual energy calculates weight. The calculated weight is used to calculate the weight of full path by cumulative weights. The full path to the smallest of the weights are set to the path. Also this algorithm is able to select another path to avoid the error path by determining the link status between nodes, when occurs link error and congestion. In this paper, we show that WSN routing algorithm based on shortest hop count routing algorithm and EAR routing algorithm compared to ensure high reliability and low power characteristic of WBAN to be verified through simulations.