• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12B
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• pp.1083-1096
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• 2008

This paper proposes an energy-aware path management scheme, so-called the TBP(Threshold based Back-Pressure) algorithm, which is designed for lifetime extension of the energy-constrained wireless sensor networks. With the goal of fair energy consumptions, we extensively utilize the available paths between the source and the sink nodes. The traffic distribution feature of the TBP algorithm operates in two scales; the local and the whole routing area. The threshold and the back-pressure signal are introduced for implementing those operations. It is noticeable that the TBP algorithm maintains the scalability by defining both the threshold and the back-pressure signal to have their meanings locally confined to one hop only. Throughout several experiments, we observe that the TBP algorithm enhances the network-wide energy distribution. which implies the extension of the network lifetime. Additionally, both the delay and the throughput outcomes show remarkable improvements. This shows that the energy-aware path control scheme holds the effects of the congestion control.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.1
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• pp.7-11
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• 2002

By focusing on the resonant vibration mode of soil-underground structure system, this paper obtained dynamic soil stiffness and easy sliding conditions at the interface between soil and underground structure. Multi-step method is employed to isolate two primary causes of soil-structure interaction. Mohr-Coulomb criterion is used to determine the threshold level of the sliding. To find out the conditions the interface slides easily, parametric studies are performed about the factors governing sliding, which are the size and location of underground structures, ground condition, the configuration of surface deposit and interface friction coefficients.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2464-2479
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• 2014

Multi-view video coding is an international encoding standard that attains good performance by fully utilizing temporal and inter-view correlations. However, it suffers from high computational complexity. This paper presents a fast encoder design to reduce the level of complexity. First, when the temporal correlation of a group of pictures is sufficiently strong, macroblock-based inter-view prediction is not employed for the non-anchor pictures of B-views. Second, when the disparity between two adjacent views is above some threshold, frame-based inter-view prediction is disabled. Third, inter-view prediction is not performed on boundary macroblocks in the auxiliary views, because the references for these blocks may not exist in neighboring views. Fourth, finer partitions of inter-view prediction are cancelled for macroblocks in static image areas. Finally, when estimating the disparity of a macroblock, the search range is adjusted according to the mode size distribution of the neighboring view. Compared with reference software, these techniques produce an average time reduction of 83.65%, while the bit-rate increase and peak signal-to-noise ratio loss are less than 0.54% and 0.05dB, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.7-16
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• 2011

This study discussed the applicability of satellite SAR (Synthetic Aperture Radar) imagery with regard to reservoir monitoring, and tried the extraction of reservoir storage from multi-temporal C-band RADARSAT-1 SAR backscattering images of Yedang and Goongpyeong agricultural reservoirs, acquired from May to October 2005. SAR technology has been advanced as a complementary and alternative approach to optical remote sensing and in-situ measurement. Water bodies in SAR imagery represent low brightness induced by low backscattering, and reservoir storage can be derived from the backscatter contrast with the level-area-volume relationship of each reservoir. The threshold segmentation over the routine preprocessing of SAR images such as speckle reduction and low-pass filtering concluded a significant correlation between the SAR-derived reservoir storage and the observation record in spite of the considerable disagreement. The result showed up critical limitations for adopting SAR data to reservoir monitoring as follows: the inappropriate specifications of SAR data, the unreliable rating curve of reservoir, the lack of climatic information such as wind and precipitation, the interruption of inside and neighboring land cover, and so on. Furthermore, better accuracy of SAR-based reservoir monitoring could be expected through different alternatives such as multi-sensor image fusion, water level measurement with altimeters or interferometry, etc.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.10
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• pp.52-62
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• 2003

This paper discusses ternary logic gate, ternary D flip-flop, and ternary four-digit parallel input/output register. The ternary logic gates consist of n-channel pass transistors and neuron MOS(νMOS) threshold inverters on voltage mode. They are designed with a transmission function using threshold inverter that are in turn, designed using Down Literal Circuit(DLC) that has various threshold voltages. The νMOS pass transistor is very suitable gate to the multiple-valued logic(MVL) and has the input signal of the multi-level νMOS threshold inverter. The ternary D flip-flop uses the storage element of the ternary data. The ternary four-digit parallel input/output register consists of four ternary D flip-flops which can temporarily store four-digit ternary data. In this paper, these circuits use 3.3V low power supply voltage and 0.35m process parameter, and also represent HSPICE simulation result.

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

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.55-62
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• 2009

The power consumption of a high-end microprocessor increases very rapidly. High power consumption will lead to a rapid increase in the chip temperature as well. If the temperature reaches beyond a certain level, chip operation becomes either slow or unreliable. Therefore various approaches for Dynamic Thermal Management (DTM) have been proposed. In this paper, we propose a learning based temperature prediction scheme for a multi-core system. In this approach, from repeatedly executing an application, we learn the thermal patterns of the chip, and we control the temperature in advance through DTM. When the predicted temperature may go beyond a threshold value, we reduce the temperature by decreasing the operation frequencies of the corresponding core. We implement our temperature prediction on an Intel's Quad-Core system which has integrated digital thermal sensors. A Dynamic Frequency System (DFS) technique is implemented to have four frequency steps on a Linux kernel. We carried out experiments using Phoronix Test Suite benchmarks for Linux. The peak temperature has been reduced by on average $5^{\circ}C{\sim}7^{\circ}C$. The overall average temperature reduced from $72^{\circ}C$ to $65^{\circ}C$.

• Geomechanics and Engineering
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• v.20 no.2
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• pp.113-120
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• 2020

Rock damage is the main cause of accidents in underground engineering. It is difficult to predict rock damage accurately by using only one parameter. In this study, a rock failure prediction model was established by using stress, energy, and damage. The prediction level was divided into three levels according to the ratio of the damage threshold stress to the peak stress. A classification predicting model was established, including the stress, energy, damage and AE impact rate using Bayesian method. Results show that the model is good practicability and effectiveness in predicting the degree of rock failure. On the basis of this, a multi-parameter classification predicting deterioration model of rock failure was established. The results provide a new idea for classifying and predicting rockburst.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.16-25
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• 2020

Vegetation segmentation in a field color image is a process of distinguishing vegetation objects of interests like crops and weeds from a background of soil and/or other residues. The performance of the process is crucial in automatic precision agriculture which includes weed control and crop status monitoring. To facilitate the segmentation, color indices have predominantly been used to transform the color image into its gray-scale image. A thresholding technique like the Otsu method is then applied to distinguish vegetation parts from the background. An obvious demerit of the thresholding based segmentation will be that classification of each pixel into vegetation or background is carried out solely by using the color feature of the pixel itself without taking into account color features of its neighboring pixels. This paper presents a new pixel-based segmentation method which employs a multi-layer perceptron neural network to classify the gray-scale image into vegetation and nonvegetation pixels. The input data of the neural network for each pixel are 2-dimensional gray-level values surrounding the pixel. To generate a gray-scale image from a raw RGB color image, a well-known color index called Excess Green minus Excess Red Index was used. Experimental results using 80 field images of 4 vegetation species demonstrate the superiority of the neural network to existing threshold-based segmentation methods in terms of accuracy, precision, recall, and harmonic mean.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.372-384
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• 2014

DTV field tests have been performed to measure field strength and to check reception ratio on indoor and outdoor sites. They use an antenna of 9m to measure DTV signal in case of outdoor measurement on the road. Modern skyscrapers require the analysis of vertical-directional wave propagation by measuring vertical-directional DTV signal. Even if the field strength is above the reception threshold of $43dB{\mu}V/m$, the reception is impossible in case of strong multi-path or high impulse noise. So, vertical-directional field measurement is essential in environment of tall buildings. In this paper, we developed an octo type multi-copter to measure vertical-directional DTV signal level. A compact and portable DTV signal level meter, an antenna, a microwave transmitter for data transmission, and a recording equipment are equipped in the multi-copter. Three different sites are selected to test the measurement system. Developed measurement system using the multi-copter is very useful in measuring vertical-directional DTV signal, especially in apartments, non-accessible area by vehicles, and forbidden areas.