• Journal of Communications and Networks
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• 제12권4호
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• pp.334-345
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• 2010

In this paper, we study optimal tradeoffs of achievable throughput versus consumed power in wireless ad-hoc networks formed by a collection of multiple antenna nodes. Relying on adaptive modulation and/or dynamic channel coding rate allocation techniques for multiple antenna systems, we examine the maximization of throughput under power constraints as well as the minimization of transmission power under throughput constraints. In our examination, we also consider the impacts of enforcing quality of service requirements expressed in the form of channel coding block loss constraints. In order to properly model temporally correlated loss observed in fading wireless channels, we propose the use of finite-state Markov chains. Details of fading statistics of signal-to-interference-noise ratio, an important indicator of transmission quality, are presented. Further, we objectively inspect complexity versus accuracy tradeoff of solving our proposed optimization problems at a global as oppose to a local topology level. Our numerical simulations profile and compare the performance of a variety of scenarios for a number of sample network topologies.

• 제어로봇시스템학회논문지
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• 제5권8호
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• pp.961-968
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• 1999

In this paper we handle a system that transform sensor data to sensor information. Sensor informations from redundant accelerometers are manipulated to represent the configuration of objects carrying sensors. Basic sensor unit of the proposed systme is composed of 3 accelerometers that are aligned along x-y-z coordination axes of motion. To refine the sensor information, at first the sensor data are fused by geometrical optimization to reduce the variance of sensor information. To overcome the error caused from inexact alignment of each sensor to the coordination system, we propose a calibration technique that identifies the transformation between the coordinate axes and real sensor axes. The calibration technique make the sensor information approach real value. Also, we propose a technique that decomposes the accelerometer data into motion acceleration component and gravity acceleration component so that we can get more exact configuration of objects than in the case of raw sensor data. A set of experimental results are given to show the usefulness of the proposed method as well as the experiments in which the proposed techniques are applied to human body motion capture.

• 대한임베디드공학회논문지
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• 제15권3호
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• pp.119-127
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• 2020

The detection and recognition of abnormal driving becomes crucial for achieving safety in Intelligent Transportation Systems (ITS). This paper presents a feature extraction method based on spectral data to train a neural network model for driving behavior recognition. The proposed method uses a two stage signal processing approach to derive time-saving and efficient feature vectors. For the first stage, the feature vector set is obtained by calculating variances from each frequency bin containing the power spectrum data. The feature set is further reduced in the second stage where an intersection method is used to select more significant features that are finally applied for training a neural network model. A stream of live signals are fed to the trained model which recognizes the abnormal driving behaviors. The driving behaviors considered in this study are weaving, sudden braking and normal driving. The effectiveness of the proposed method is demonstrated by comparing with existing methods, which are Particle Swarm Optimization (PSO) and Convolution Neural Network (CNN). The experiments show that the proposed approach achieves satisfactory results with less computational complexity.

• KSBB Journal
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• 제9권1호
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• pp.8-15
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• 1994

재조합 효모를 이용한 hirudin 발효생산조건의 최적화 연구를 수행하였다. Hirudin 유전자는 GAL10 promoter와 MFal 분비신호, GAL7 terminator와 결합되어 있다. 재조합 효모의 성장속도와 hirudin 최종 농도를 증가시키기 위하여 최적의 배지조성과 배양조건을 결정하였다. 최적의 배지조성과 배양조건은 yeast extract 40g/$\ell$, casamino acid 5g/$\ell$, 포도당 20g/$\ell$, galactose 30g/$\ell$, DO 50%, 온도 $30^{\circ}C$였다. 이 조건으로 2.5$\ell$ 발효조에서 회분식배양을 수행한 결과 비성장속도는 $0.13hr^{-1}$, 최종 건조균체농도는 30g cell/$\ell$, 최종 hirudin 농도는 64mg/$\ell$로 나타났다.

• ETRI Journal
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• 제38권3호
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• pp.560-567
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• 2016

To solve the problem of parameter optimization in image sensor-based visible light positioning systems, theoretical limits for both the location and the azimuth angle of the image sensor receiver (ISR) are calculated. In the case of a typical indoor scenario, maximum likelihood estimations for both the location and the azimuth angle of the ISR are first deduced. The Cramer-Rao Lower Bound (CRLB) is then derived, under the condition that the observation values of the image points are affected by white Gaussian noise. For typical parameters of LEDs and image sensors, simulation results show that accurate estimates for both the location and azimuth angle can be achieved, with positioning errors usually on the order of centimeters and azimuth angle errors being less than $1^{\circ}$. The estimation accuracy depends on the focal length of the lens and on the pixel size and frame rate of the ISR, as well as on the number of transmitters used.

• Smart Structures and Systems
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• 제22권2호
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• pp.175-183
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• 2018

Time-series data often contain one of the most valuable pieces of information in many fields including manufacturing. Because time-series data are relatively cheap to acquire, they (e.g., vibration signals) have become a crucial part of big data even in manufacturing shop floors. Recently, deep-learning models have shown state-of-art performance for analyzing big data because of their sophisticated structures and considerable computational power. Traditional models for a machinery-monitoring system have highly relied on features selected by human experts. In addition, the representational power of such models fails as the data distribution becomes complicated. On the other hand, deep-learning models automatically select highly abstracted features during the optimization process, and their representational power is better than that of traditional neural network models. However, the applicability of deep-learning models to the field of prognostics and health management (PHM) has not been well investigated yet. This study integrates the "residual fitting" mechanism inherently embedded in the wavelet transform into the convolutional neural network deep-learning structure. As a result, the architecture combines a signal smoother and classification procedures into a single model. Validation results from rotor vibration data demonstrate that our model outperforms all other off-the-shelf feature-based models.

• 전자공학회논문지
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• 제50권6호
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• pp.9-21
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• 2013

트래킹(Tracking)은 셀의 관점에서 트래킹 영역내의 UE(User Equipment)를 탐색하는 과정이다. 이 논문에서는, 매크로셀-마이크로셀 계층적 LTE 네트워크에 관한 PMMT(Pure Macro-Micro Tracking)과 IMMT(Integrated Macro-Micro Tracking)로 불리는 두가지 트래킹 기법의 성능을 평가한다. 이런 네트워크에서 UE들은 매크로셀과 겹쳐 있는 마이크로셀 모두에서 신호를 받을 수 있다. PMMT 기법에서 UE는 매크로셀-계층 또는 겹쳐있는 마이크로셀-계층에서 각각 호출될 수 있다. IMMT 기법에서 UE는 매크로셀-계층과 겹쳐있는 마이크로셀-계층의 조합으로 호출된다. 매크로셀-계층과 마이크로셀-계층 사이에 최적의 로드밸런스가 평가되었고, 분석 모델은 두 기법을 평가하기 위해 개발되었다.

• 센서학회지
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• 제17권1호
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• pp.15-22
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• 2008

When designing image sensors including a CMOS vision chip for edge detection, resolution is a significant factor to evaluate the performance. It is hard to improve the resolution of a bio-inspired CMOS vision using a resistive network because the vision chip contains many circuits such as a resistive network and several signal processing circuits as well as photocircuits of general image sensors such as CMOS image sensor (CIS). Low resolution restricts the use of the application systems. In this paper, we improve the resolution through layout and circuit optimization. Furthermore, we have designed a printed circuit board using FPGA which controls the vision chip. The vision chip for edge detection has been designed and fabricated by using $0.35{\mu}m$ double-poly four-metal CMOS technology, and its output characteristics have been investigated.

• 센서학회지
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• 제27권4호
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• pp.269-274
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• 2018

High-sensitivity signal-to-noise ratio (SNR) microphones are essentially required for a broad range of automatic speech recognition applications. Piezoelectric microphones have several advantages compared to conventional capacitor microphones including high stiffness and high SNR. In this study, we designed a new piezoelectric membrane structure by using the finite elements method (FEM) and an optimization technique to improve the sensitivity of the transducer, which has a high-quality AlN piezoelectric thin film. The simulation demonstrated that the sensitivity critically depends on the inner radius of the top electrode, the outer radius of the membrane, and the thickness of the piezoelectric film in the microphone. The optimized piezoelectric transducer structure showed a much higher sensitivity than that of the conventional piezoelectric transducer structure. This study provides a visible path to realize micro-scale high-sensitivity piezoelectric microphones that have a simple manufacturing process, wide range of frequency and low DC bias voltage.

• 한국정밀공학회지
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• 제30권11호
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• pp.1187-1192
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• 2013

In the case of 4 wheel drive (4-WD) type car, power switching occurs to 4-WD by operating lever or switch that operates power switching device attached in transfer case which can operate motor by electric signal. So if the RPM of motor is high, power switching will not exactly occur and can cause damage to gear in transfer case according to circumstances. So in this study, we applied 2 level of planet gear type motor spindle of motor drive part of a power train. And conducted decelerating to increase torque to switch power safe and accurately. Also, we researched efficiency of gear by designing reduction gear ratio and gear type and by calculating contact stress and bending strength. Based on researched content, we made drive head of power switching device and a reduction module which uses type that uses motor spindle as sun gear and ring gear as cover.