• Journal of Broadcast Engineering
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• v.26 no.7
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• pp.868-876
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• 2021

Deploying deep neural network model training performs remarkable performance in the fields of Object detection and Instance segmentation. To train these models, features are first extracted from the input image using a backbone network. The extracted features can be reused by various tasks. Research has been actively conducted to serve various tasks by using these learned features. In this process, standardization discussions about encoding, decoding, and transmission methods are proceeding actively. In this scenario, it is necessary to analyze the response characteristics of features against various distortions that may occur in the data transmission or data compression process. In this paper, experiment was conducted to inject various distortions into the feature in the object recognition task. And analyze the mAP (mean Average Precision) metric between the predicted value output from the neural network and the target value as the intensity of various distortions was increased. Experiments have shown that features are more robust to distortion than images. And this points out that using the feature as transmission means can prevent the loss of information against the various distortions during data transmission and compression process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2450-2460
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• 2015

Recently, as interest in IoT (Internet of Things) increase, research and standardization of a new protocol which reflects the characteristics of IoT has progressed. Among them, RPL(IPv6 for Low-Power Lossy Network) is a standardized routing protocol for IoT. RPL utilizes DIO (DODAG Information Object) messages which is flooded from the sink node to the whole network for path establish and maintenance. However, in large scale networks, not only a long time is required to propagate the DIO message to the whole networks but also a bottleneck effect around the sink node is occurred. Multi-sink based approaches which take advantage of reducing routing overhead and bottleneck effect are widely used to solve these problems. In this paper, we define 'unnecessary path update problems' that may arise when applying the RPL protocol to the multi sink based IoT networks and propose two methods namely Routing Metric based Path Update Decision method and Immediate Successor based Path Update Decision method for selective routing update.

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.1-8
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• 2010

Recently lots of attention has been paid to gene set analysis for identifying differentially expressed gene-sets between two sample groups. Unlike earlier approaches, the gene set analysis enables us to find significant gene-sets along with their functional characteristics. For this reason, various novel approaches have been suggested lately for gene set analysis. As one of such, PAGE is a parametric approach that employs average difference (AD) as an expression metric to quantify expression differences between two sample groups and assumes that the distribution of gene scores is normal. This approach is preferred to non-parametric approach because of more effective performance. However, the metric AD does not reflect either gene expression intensities or variances over samples in calculating gene scores. Thus, in this paper, we investigate the usefulness of several other expression metrics for parametric gene-set analysis, which consider actual expression intensities of genes or their expression variances over samples. For this purpose, we examined three expression metrics, WAD (weighted average difference), FC (Fisher's criterion), and Abs_SNR (Absolute value of signal-to-noise ratio) for parametric gene set analysis and evaluated their experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.1-6
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• 2017

Recent researches on radio frequency energy harvesting networks(RF-EHNs) with limited energy resource like battery have been focusing on the development of a new scheme that can effectively extend the whole lifetime of a network to semipermanent. In order for considerable increase both in the amount of energy obtained from radio frequency energy harvesting and its charging effectiveness, it is very important to design a network that supports energy harvesting and data transfer simultaneously with the full consideration of various characteristics affecting the performance of a RF-EHN. In this paper, we proposes an interference-based charging aware routing protocol(ICARP) that utilizes interference information and charging time to maximize the amount of energy harvesting and to minimize the end-to-end delay from a source to the given destination node. To accomplish the research objectives, this paper gives a design of ICARP adopting new network metrics such as interference information and charging time to minimize end-to-end delay in energy harvesting wireless networks. The proposed method enables a RF-EHN to reduce the number of packet losses and retransmissions significantly for better energy consumption. Finally, simulation results show that the network performance in the aspects of packet transmission rate and end-to-end delay has enhanced with the comparison of existing routing protocols.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.44-51
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• 2009

This paper addresses a face verification method using the nonlinear composite filter. This face verification process can be simple and speedy because it does not require any reprocessing such as face detection, alignment or cropping. The optimum nonlinear composite filter is derived by minimizing the output energy due to additive noise and an input scene while maintaining the outputs of training images constant. The filter is equipped with the discrimination capability and the robustness to additive noise by minimizing the outputs of the input scene and the noise, respectively. We build the nonlinear composite filter with two training images and compare the filter with the conventional synthetic discriminant function (SDF) filter. The receiver operating characteristics (ROC) curves are presented as a metric for the performance evaluation. According to the experimental results the optimum nonlinear composite filter is shown to be a robust scheme for face verification in low resolution and noise environments.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.764-771
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• 2010

The stability analysis method of an unsaturated slope considering the suction stress was performed on the infinite sand slope. During drying and wetting processes, the Soil-Water Characteristics Curve (SWCC) of the sand with the relative density of 75% was measured using the automated SWCC apparatus. Also, the Suction Stress Characteristics Curve (SSCC) was estimated. Based on these results, the stability analysis of an unsaturated infinite slope was carried out considering the slope angle, the weathering zone and the relative change in friction angle as a soil depth. According to the result of slope stability analysis, the safety factors of slope were less than 1 when the slope angles were more than $50^{\circ}$. The safety factors of slope tend to increase with increasing the depth from the ground surface. Especially, the safety factors have a tendency to increase and decrease above near the ground water level due to the suction stress. The maximum safety factor of slope in this analysis was occurred at the Air Entry Value (AEV) of drying process. The influence range of suction stress above the ground water level can be found out and can be defined as the funicular zone which means the metric suction range from the air entry point to the point of residual volumetric water content.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.5
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• pp.13-26
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• 1999

This paper presents a metric that can guide to optimal circuit models for interconnects among various models, given interconnect parameters and operating environment. To get this goal, we categorize interconnects into RC~c1ass and RLC-c1ass model domains based on the quantitative modeling error analysis using total resistance, inductance and capacitance of interconnects as well as operating frequency. RC~c1ass circuit models, which include most on~chip interconnects, can be efficiently analyzed by using the model~order reduction techniques. RLC-c1ass circuit models are constructed using one of three candidates, ILC(Iterative Ladder Circuit) macromodels, MC(Method of Characteristics) macromodels, and state-based convolution method, the selection process of which is based upon the allowable modeling error and electrical parameters of interconnects. We propose the model domain diagram leading to optimal circuit models and the division of model domains has been achieved considering the simulation cost of macromodels under the environmental assumption of the general purpose circuit simulator such as SPICE. The macromodeling method presented in this paper keeps the passivity of the original interconnects and accordingly guarantees the unconditional stability of circuit models.

• Journal of the Korea Safety Management & Science
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• v.16 no.1
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• pp.169-176
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• 2014

This research discusses the characteristics and the implementation strategies for two types of quality metrics to analyze innovation effects in six sigma projects: fixed specification type and moving specification type. $Z_{st}$, $P_{pk}$ are quality metrics of fixed specification type that are influenced by predetermined specification. In contrast, the quality metrics of moving specification type such as Strictly Standardized Mean Difference(SSMD), Z-Score, F-Statistic and t-Statistic are independent from predetermined specification. $Z_{st}$ sigma level obtains defective rates of Parts Per Million(PPM) and Defects Per Million Opportunities(DPMO). However, the defective rates between different industrial sectors are incomparable due to their own technological inherence. In order to explore relative method to compare defective rates between different industrial sectors, the ratio of specification and natural tolerance called, $P_{pk}$, is used. The drawback of this $P_{pk}$ metric is that it is highly dependent on the specification. The metrics of F-Statistic and t-Statistic identify innovation effect by comparing before-and-after of accuracy and precision. These statistics are not affected by specification, but affected by type of statistical distribution models and sample size. Hence, statistical significance determined by above two statistics cannot give a same conclusion as practical significance. In conclusion, SSMD and Z-Score are the best quality metrics that are uninfluenced by fixed specification, theoretical distribution model and arbitrary sample size. Those metrics also identify the innovation effects for before-and-after of accuracy and precision. It is beneficial to use SSMD and Z-Score methods along with popular methods of $Z_{st}$ sigma level and $P_{pk}$ that are commonly employed in six sigma projects. The case studies from national six sigma contest from 2011 to 2012 are proposed and analyzed to provide the guidelines for the usage of quality metrics for quality practitioners.

• Journal of Surface Science and Engineering
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• v.34 no.5
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• pp.403-408
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• 2001

In this work, the cyclic perfluorinated ether (c-C$_4$F$_{8}$O) with very high destructive removal efficiency (DRE) than other alternative gases, such as $C_3$F$_{8}$, c-C$_4$F$_{8}$ and NF$_3$ was used as an alternative process chemical. The plasma cleaning of silicon nitride using gas mixtures of c-C$_4$F$_{8}$O/O$_2$ and c-C$_4$F$_{8}$O/O$_2$+ $N_2$ was investigated in order to evaluate the effects of adding $N_2$ to c-C$_4$F$_{8}$O/O$_2$ on the global warming effects. Under optimum condition, the emitted net perfluorocompounds (PFCs) during cleaning of silicon nitride were quantified and then the effects of additive $N_2$ by obtaining the destructive removal efficiency (DRE) and the million metric tons of carbon equivalent (MMT-CE) were calculated. DRE and MMTCE were obtained by evaluating the volumetric emission using. Fourier transform-infrared spectroscopy (FT-IR). During the cleaning using c-C$_4$F$_{8}$O/O$_2$+$N_2$, DRE values as high as (equation omitted) 98% were obtained and MMTCE values were reduced by as high as 70% compared to the case of $C_2$F$_{6}$O$_2$. Recombination characteristics were indirectly investigated by combining the measurements of species in the chamber using optical emission spectroscopy (OES), before and after the cleaning, in order to understand any correlation between plasma and emission characteristics as well as cleaning rate of silicon nitride.silicon nitride.

• Smart Structures and Systems
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• v.32 no.1
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• pp.1-7
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• 2023

In modal analysis, the mode shape reflects the vibration characteristics of the structure, and thus it is widely performed for finite element model updating and structural health monitoring. Generally, the acceleration-based mode shape is suitable to express the characteristics of structures for the translational vibration; however, it is difficult to represent the rotational mode at boundary conditions. A tilt sensor and gyroscope capable of measuring rotational mode are used to analyze the overall behavior of the structure, but extracting its mode shape is the major challenge under the small vibration always. Herein, we conducted a feasibility study on a multi-mode shape estimating approach utilizing a single physical quantity signal. The basic concept of the proposed method is to receive multi-metric dynamic responses from two sensors and obtain mode shapes through bridge loading test with relatively large deformation. In addition, the linear transformation matrix for estimating two mode shapes is derived, and the mode shape based on the gyro sensor data is obtained by acceleration response using ambient vibration. Because the structure's behavior with respect to translational and rotational mode can be confirmed, the proposed method can obtain the total response of the structure considering boundary conditions. To verify the feasibility of the proposed method, we pre-measured dynamic data acquired from five accelerometers and five gyro sensors in a lab-scale test considering bridge structures, and obtained a linear transformation matrix for estimating the multi-mode shapes. In addition, the mode shapes for two physical quantities could be extracted by using only the acceleration data. Finally, the mode shapes estimated by the proposed method were compared with the mode shapes obtained from the two sensors. This study confirmed the applicability of the multi-mode shape estimation approach for accurate damage assessment using multi-dimensional mode shapes of bridge structures, and can be used to evaluate the behavior of structures under ambient vibration.