• The Journal of the Acoustical Society of Korea
• /
• v.19 no.8
• /
• pp.3-11
• /
• 2000

This paper considers the performance of a dynamic priority control function (DPCF) of a threshold-based Bernoulli priority jump (TBPJ) scheme. Loss-sensitive and delay-sensitive traffics are applied to a system with a TBPJ scheme that is a general state-dependent Bernoulli scheduling scheme. Loss-sensitive and delay-sensitive traffics represent sound and data, respectively. Under the TBPJ scheme, the first packet of the loss-sensitive traffic buffer goes into the delay-sensitive traffic buffer with Bernoulli probability p according to system states which represent the buffer thresholds and the number of packets waiting for scheduling. Performance analysis shows that TBPJ scheme obtains large performance build-up for the delay-sensitive traffic without performance degradation for the loss-sensitive traffic. TBPJ scheme shows also better performance than that of HOL scheme.

• Smart Media Journal
• /
• v.13 no.4
• /
• pp.48-56
• /
• 2024

In the livestock industry, detecting environmental outliers and predicting data are crucial tasks. Outliers in livestock environment data, typically gathered through time-series methods, can signal rapid changes in the environment and potential unexpected epidemics. Prompt detection and response to these outliers are essential to minimize stress in livestock and reduce economic losses for farmers by early detection of epidemic conditions. This study employs two methods to experiment and compare performances in setting thresholds that define outliers in livestock environment data outlier detection. The first method is an outlier detection using Mean Squared Error (MSE), and the second is an outlier detection using a Dynamic Threshold, which analyzes variability against the average value of previous data to identify outliers. The MSE-based method demonstrated a 94.98% accuracy rate, while the Dynamic Threshold method, which uses standard deviation, showed superior performance with 99.66% accuracy.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.9
• /
• pp.133-141
• /
• 1994

Conventional competitive learning algorithms compute the Euclidien distance to determine the winner neuron out of all predetermined output neurons. In such cases, there is a drawback that the performence of the learning algorithm depends on the initial reference(=weight) vectors. In this paper, we propose a new competitive learning algorithm that dynamically generates output neurons. The proposed method generates output neurons by dynamically changing the class thresholds for all output neurons. We compute the similarity between the input vector and the reference vector of each output neuron generated. If the two are similar, the reference vector is adjusted to make it still more like the input vector. Otherwise, the input vector is designated as the reference vector of a new outputneuron. Since the reference vectors of output neurons are dynamically assigned according to input pattern distribution, the proposed method gets around the phenomenon that learning is early determined due to redundant output neurons. Experiments using speech data have shown the proposed method to be superior to existint methods.

• Proceedings of the Optical Society of Korea Conference
• /
• 2003.02a
• /
• pp.38-39
• /
• 2003

The GaAs semiconductor whispering gallery modes, produced in the peripheral Rayleigh band region of W／sub Rayleigh／ ＝ (${\Phi}$／2)( 1-n／sub eff／n), exhibit novel properties of ultralow thresholds open to nano-ampere regime associated with photonic quantum ring (PQR) production (Fig 1 (a)). The PQR phenomena are associated with a photonic field-driven phase transition of quantum well(QW)-to-quantum wire (QWR) and hence the photonic (non-de Broglie) quantum corral effects, on the Rayleigh cavity confined carriers in dynamic steady state, occur as schematically shown in Fig 1. (omitted)

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.27 no.7C
• /
• pp.664-669
• /
• 2002

In this paper, we propose the fuzzy control algorithm for effective buffer control to connected traffic in ATM networks. The proposed Fuzzy control algorithm has two priorities and uses Fuzzy sets to search for dynamic thresholds. In this words, the difuzzification value controls the threshold in the buffer to according to traffic priority (low or high) using fuzzy set theory for traffic connected after reasoning. Performance analysis result: it was confirmed that with the proposed scheme, performance improves at cell loss rate, when compared with the existing PBS scheme.

• Journal of Life Science
• /
• v.20 no.4
• /
• pp.496-502
• /
• 2010

The acidic saline animal model of pain has been suggested to mimic fibromyalgia (FM). Oligomeric proanthocyanidin complexes (OPC) from grape seeds are known to act as an antioxidant. We studied the effects of OPC on the pain threshold in the acidic saline animal model of pain. The left gastrocnemius muscle was injected with $100\;{\mu}l$ of saline at pH 4.0 under brief isoflurane anesthesia on days 0 and 5. Control rats (n=5) received identical injections of physiological saline (pH 7.2) on the same schedule. Rats (n=10) with acidic saline injection were separated into two study subgroups. After measurement of pre-drug pain thresholds, rats were injected intraperitoneally with either saline or OPC 300 mg/kg. Paw withdrawal thresholds to pressure were again measured 60 min after intraperitoneal injection. Nociceptive thresholds were measured with a Dynamic Plantar Aesthesiometer by applying an increasing pressure to right or left hind paw until the rat withdrew the paw. Compared to baseline (day 0), acid injections produced mechanical hyper-responsiveness on day 7 (pre-drug) in these rats [p<0.05]. A potent antihyperalgesic effect was observed when rats were injected intraperitoneally with OPC 300 mg/kg [injected paw, p=0.001; contralateral paw, p=0.002]. OPC treatment decreased the expression of acid sensing ion channel 3 in the brain motor cortex area on immunohistochemical staining when OPC 300 mg/kg was administered intraperitoneally in the animal model of FM pain [p<0.05]. Further research is required to determine the efficacy of OPC treatments in FM pain in humans.

• KIPS Transactions on Computer and Communication Systems
• /
• v.4 no.11
• /
• pp.369-382
• /
• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• Smart Media Journal
• /
• v.9 no.4
• /
• pp.102-108
• /
• 2020

In this paper, we propose a real-time method of detecting hand motions and extracting the signal frame induced by EF(Electric Field) sensors. The signal induced by hand motion includes not only noises caused by various environmental sources as well as sensor's physical placement, but also different initial off-set conditions. Thus, it has been considered as a challenging problem to detect the motion signal and extract the motion frame automatically in real-time. In this study, we remove the PLN(Power Line Noise) using LPF with 10Hz cut-off and successively apply MA(Moving Average) filter to obtain clean and smooth input motion signals. To sense a hand motion, we use two thresholds(positive and negative thresholds) with offset value to detect a starting as well as an ending moment of the motion. Using this approach, we can achieve the correct motion detection rate over 98%. Once the final motion frame is determined, the motion signals are normalized to be used in next process of classification or recognition stage such as LSTN deep neural networks. Our experiment and analysis show that our proposed methods produce better than 98% performance in correct motion detection rate as well as in frame-matching rate.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.13 no.4
• /
• pp.395-404
• /
• 2000

A damage detection and assessment algorithm is developed by measuring accelerations at limited locations of a structure under forced vibrations. The developed algorithm applies a time-domain system identification (SI) method that identifies a structure by solving a linearly constrained nonlinear optimization problem for optimal structural parameters. An equation error of the dynamic equilibrium of motion is minimized to estimate optimal parameters. An adaptive parameter grouping scheme is applied to localize damaged members with sparse measured accelerations. Damage is assessed in a statistical manner by applying a time-windowing technique to the measured time history of acceleration. Displacements and velocities at the measured degrees of freedom (DOF) are computed by integrating the measured accelerations. The displacements at the unmeasured DOF are estimated as additional unknowns to the unknown structural parameters, and the corresponding velocities and accelerations we computed by a numerical differentiation. A numerical simulation study with a truss structure is carried out to examine the efficiency of the algorithm. A data perturbation scheme is applied to determine the thresholds lot damage indices and to compute the damage possibility of each member.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.11S
• /
• pp.3684-3693
• /
• 2000

In this paper, performance of a nonblocking high speed packet switch with switching capacity m which adopts a dynamic priority control function (DPCF) of a threshold- based Bernoulli priority jump (TBPJ) scheme is considered. Each input queue has two separate buffers with different sizes for two classes of traffics, delay-sensitive and loss-sensitive traffics, and adopts a TBPJ scheme that is a general state-dependent Bernoulli scheduling scheme. Under the TBP] scheme, a head packet of the delay-sensitive traffic buffer goes into the loss -sensitive traffic buffer with Hernoulli probability p according to systems states that represent the buffer thresholds and the number of packets waiting for scheduling. Performance analysis shows that TBPJ scheme obtains large performance build-up for the delay-sensitive traffic without performance degradation for the loss-sensitive traffic. In addition to, TBP] scheme shows better performance than that of HOL scheme.