• Physical Therapy Korea
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• v.3 no.2
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• pp.95-105
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• 1996

Type I, II, III are regarded as "true" joint receptors, type IV is considered a class of pain receptor. Type I, II and III mechanoreceptors, via static and dynamic input, signal joint position, intraarticular pressure changes, and the direction, amplitude, and velocity of joint movements. Type I mechanoreceptor subserve both static and dynamic physiologic functions. Type I are found primarily in the stratum fibrosum of the joint capsule and ligaments. Type I receptors have a low threshold for activation and are allow to adapt to changes altering their firing frequency. Type II receptors have a low threshold for activation. These dynamic receptors respond to joint movement. Type II receptors are thus termed rapidly adapting. Type II joint receptors are located at the junction of the synovial membrane and fibrosum of the joint capsule and intraarticular and extraarticular fat pads. Type III receptors have been found in collateral ligaments of the joints of the extremities. Morphologically similar to Golgi tendon organ. These dynamic receptors have a high threshold to stimulation and are slowly adating. Type IV receptors possess free nerve ending that have been found in joint capsule and fat pads. They are not normally active, but respond to extreme mechanical deformation of the joint as well as to direct chemical or mechanical irritation. Small amplitude oscillatory and distraction movements(joint mobilization) techniques are used to stimulate the mechanoreceptors that may inhibit the transmission of nociceptors stimuli at the spinal cord or brain stem levels.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.2 no.1
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• pp.9-19
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• 1996

Type I, II, III are regarded as "true" joint receptors, type IV is considered a class of pain receptor. Type I, II and III mechanoreceptors, via static and dynamic input, signal joint position, intraarticular pressure changes, and the direction, amplitude, and velocity of joint movements. Type I mechanoreceptor subserve both static and dynamic physiologic functions. Type I are found primarily in the stratum fibrosum of the joint capsule and ligaments. Type I receptors have a low threshold for activation and are allow to adapt to changes altering their firing frequency. Type II receptors have a low threshold for activation. These dynamic receptors respond to joint movement. Type II receptors are thus termed rapidly adapting. Type II joint receptors are located at the junction of the synovial membrane and fibrosum of the joint capsule and intraarticular and extraarticular fat pads. Type III receptors have been found in collateral ligaments of the joints of the extremities. Morphologically similar to Golgi tendon organ. These dynamic receptors have a high threshold to stimulation and are slowly adating. Type IV receptors possess free nerve ending that have been found in joint capsule and fat pads. They are not normally active, but respond to extreme mechanical deformation of the joint as well as to direct chemical or mechanical irritation. Small amplitude oscillatory and distraction movements(joint mobilization) techniques are used to stimulate the mechanoreceptors that may inhibit the transmission of nociceptors stimuli at the spinal cord or brain stem levels.

• The Journal of Korean Association of Computer Education
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• v.18 no.2
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• pp.83-90
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• 2015

In an virtualization environment, several virtual machines use physical resources together. If a specific virtual machine uses to much of the computing resources, other machines may not be working properly. There are various method to solve this problem. Most representative study is to migrate a specified virtual machines to a different server, a target server. In this study, server load can be transferred to a target server by the remigrate of the load imposed on virtual machine. It is still problematic that virtual machine has to remigrate to a different server. This thesis has proposed the algorithm determining the remigration targets by applying dynamic thresholds to solve those problems. The migration algorithm applies dynamic thresholds according to the following criteria. Firstly, the usage of CPU, network and memory; secondly, decide the set of artificial machine and the target server based on the resources surpassed thresholds; thirdly, determine artificial machines based on the resource usage in the target server.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.83-87
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• 2007

This research studies real time interaction and dynamic data shared through 3D scenes in virtual network environments. In a distributed virtual environment of client-server structure, consistency is maintained by the static information exchange; as jerks occur by packet delay when updating messages of dynamic data exchanges are broadcasted disorderly, the network bottleneck is reduced by predicting the movement path by using the Dead-reckoning algorithm. In Dead-reckoning path prediction, the error between the estimated and the actual static values which is over the threshold based on the shared object location requires interpolation and multicasting of the previous location by the ESPDU of DIS. The shared dynamic data of the 3D virtual environment is implementation using the VRML.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.97-100
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• 2001

A common network such as internet does not provide a guaranteed network bandwidth to accommodate multimedia service in a reliable fashion. In this paper, we propose a new rate control mechanism for multimedia service on the internet which is adaptive to the dynamic QoS in real-time. Also we adapt an QoS monitoring module and real-time transmission control module to adapt dynamic network bandwidth. To do this, we used layer attribution of media data and also considered loss rate and buffer threshold in receiver side for measurement of dynamic QoS.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.923-934
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• 2000

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.489-496
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• 2002

This study proposes a new polling algorithm allowing dynamic change in polling period based on line utilization prediction. Polling is the most important function in network monitoring, but excessive polling data causes rather serious congestion conditions of network when network is In congestion. Therefore, existing multiple polling algorithms decided network congestion or load of agent with previously performed polling Round Trip Time or line utilization, chanced polling period, and controlled polling traffic. But, this algorithm is to change the polling period based on the previous polling and does not reflect network conditions in the current time to be polled. A algorithm proposed in this study is to predict whether polling traffic exceeds threshold of line utilization on polling path based on the past data and to change the polling period with the prediction. In this study, utilization of each line configuring network was predicted with AR model and violation of threshold was presented in probability. In addition, suitability was evaluated by applying the proposed dynamic polling algorithm based on line utilization prediction to the actual network, reasonable level of threshold for line utilization and the violation probability of threshold were decided by experiment. Performance of this algorithm was maximized with these processes.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.8
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• pp.116-121
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• 2001

The paper presents the dynamic characteristics of a rotor-bearing system supported by an actively controlled hydrodynamic journal bearing. The proportional. derivative and integral controls are adopted for the control algorithm to control the hydrodynamic journal bearing with an axial groove. Also, the cavitation algorithm implementing the Jakobsson-Floberg-Olsson boundary condition is adopted to predict cavitation regions in the fluid film more accurately than conventional analysis, which uses the Reynolds condition. The speed at onset of instability of a rotor-bearing system is increased by both proportional and derivative control of the bearing. The proportional control increases the stability threshold without affecting the whirl ratio. However, for the derivative control of the bearing, increase of stability threshold speed is accompanied by a parallel reduction of the whirl ratio. The integral control has no effect on stability characteristics of hydrodynamic journal bearing. The PD-control is more effective than proportional or derivative control. Results 7how the active control of bearing can be adopted for the stability improvement of a rotor-bearing system.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.11-16
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• 2005

Recently, there are a lot of endeavor to implement a fuzzy theory to artificial neural network. Goh proposed the fuzzy single layer perceptron algorithm and advanced fuzzy perceptron based on the generalized delta rule to solve the XOR Problem and the classical Problem. However, it causes an increased amount of computation and some difficulties in application of the complicated image recognition. In this paper, we propose an enhanced fuzzy single layer Perceptron using the dynamic adjustment of threshold. This method is applied to the XOR problem, which used as the benchmark in the field of pattern recognition. The method is also applied to the recognition of digital image for image application. In a result of experiment, it does not always guarantee the convergence. However, the network show improved the learning time and has the high convergence rate.

• Genomics & Informatics
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• v.1 no.1
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• pp.25-31
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• 2003

Local alignment is an important task in molecular biology to see if two sequences contain regions that are similar. The most popular approach to local alignment is the use of dynamic programming due to Smith and Waterman, but the alignment reported by the Smith-Waterman algorithm has some undesirable properties. The recent approach to fix these problems is to use the notion of normalized scores for local alignments by Arslan, Egecioglu and Pevzner. In this paper we consider the problem of finding all local alignments whose normalized scores are above a given threshold, and present a fast heuristic algorithm. Our algorithm is 180-330 times faster than Arslan et al.'s for sequences of length about 120 kbp and about 40-50 times faster for sequences of length about 30 kbp.