• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.56-63
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• 2016

This paper presents a novel method for detecting a ghost key at the membrane type keyboard, which has additional resistive coating to the membrane film. Also, the optimal ratio of resistances for detecting a ghost key was designed based on the characteristics of the membrane film. The optimal ratio of resistances was considered to be able to detect the worst case (i.e., difference voltage between normal key and ghost key is minimum). The ability of the proposed methods are evaluated by simulation studies in this paper. In order to verify the proposed method, the experiment was carried out with a designed circuit and A/D (analog to digital) in MCU (micro controller unit). The proposed method is implemented into the membrane type keyboard and is verified by experimental results.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.1
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• pp.129-140
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• 2017

In this paper, a $4{\times}32$-channel neural recording system capable of acquiring neural signals is introduced. Four 32-channel neural recording ICs, complex programmable logic devices (CPLDs), a micro controller unit (MCU) with USB interface, and a PC are used. Each neural recording IC, implemented in $0.18{\mu}m$ CMOS technology, includes 32 channels of analog front-ends (AFEs), a 32-to-1 analog multiplexer, and an analog-to-digital converter (ADC). The mid-band gain of the AFE is adjustable in four steps, and have a tunable bandwidth. The AFE has a mid-band gain of 54.5 dB to 65.7 dB and a bandwidth of 35.3 Hz to 5.8 kHz. The high-pass cutoff frequency of the AFE varies from 18.6 Hz to 154.7 Hz. The input-referred noise (IRN) of the AFE is $10.2{\mu}V_{rms}$. A high-resolution, low-power ADC with a high conversion speed achieves a signal-to-noise and distortion ratio (SNDR) of 50.63 dB and a spurious-free dynamic range (SFDR) of 63.88 dB, at a sampling-rate of 2.5 MS/s. The effectiveness of our neural recording system is validated in in-vivo recording of the primary somatosensory cortex of a rat.

• Journal of the Semiconductor & Display Technology
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• v.12 no.2
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• pp.13-17
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• 2013

In lighting system where several large-area organic light-emitting diode (OLED) lighting panels are involved, panel aging may appear differently from each other, resulting in a falling-off in lighting quality. To achieve uniform light output across large-area OLED lighting panels, we have employed an optical feedback circuit. Light output from each OLED panel is monitored by the optical feedback circuit that consists of a photodiode, I-V converter, 10-bit analogdigital converter (ADC), and comparator. A photodiode generates current by detecting OLED light from one side of the glass substrate (i.e., edge emission). Namely, the target luminance from the emission area (bottom emission) of OLED panels is monitored by current generated from the photodiode mounted on a glass edge. To this end, we need to establish a mapping table between the ADC value and the luminance of bottom emission. The reference ADC value corresponds to the target luminance of OLED panels. If the ADC value is lower or higher than the reference one (i.e., when the luminance of OLED panel is lower or higher than its target luminance), a micro controller unit (MCU) adjusts the pulse width modulation (PWM) used for the control of the power supplied to OLED panels in such a way that the ADC value obtained from optical feedback is the same as the reference one. As such, the target luminance of each individual OLED panel is unchanged. With the optical feedback circuit included in the lighting system, we have observed only 2% difference in relative intensity of neighboring OLED panels.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.6 s.360
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• pp.1-8
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• 2007

In wireless sensor network which uses limited battery, power consumption is very important factor for the survivality of the system. By using low-power communication to reduce power consumption, error rate is increased in typical conditions. This paper analyzes power consumption of specific error control coding (ECC) implementations. With identical link quality, ECC provides coding gain which save the power for transmission at the cost of computing power. In sensor node, transmit power is higher than computing power of Micro Controller Unit (MCU). In this paper, Viterbi algerian is applied to the low-transmit-power sensor networks in terms of network power consumption. Practically, Viterbi algorithm presents 20% of reduction of re-transmission in compared with Auto Repeat Request (ARQ) system. Furthermore, it is observed that network power consumption is decreased by almost 18%.

• Journal of Bio-Environment Control
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• v.23 no.1
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• pp.26-30
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• 2014

Purpose of this study was a development of a sprayer arm auto control system that could be operated according to distance from pear trees for automation of pest control. Auto control system included two parts, hardware and software. First, controller was made with an MCU and relay switches. Two types of ultra-sonic sensors were installed to measure distance from pear trees: one on/off type that detect up to 3 m, and the other continuous type providing 0~5 V output corresponding to distance of 0~3 m. Second, an auto control algorithm was developed to control. Each spraying arm was controlled according to the sensor-based distance from the pear trees. And it could dodge obstacles to protect itself. Max and min signal values were eliminated, when five sensor signals was collected, and then signals were averaged to reduce sensor's noises. According to results of field experiment, auto control test result was better than non auto control test result. Spraying rates were 69.25% (left line) and 98.09% (right line) under non auto control mode, because pear trees were not planted uniformly. But, auto control test's results were 92.66% (left line) and 94.64% (right line). Spraying rate was increased by maintaining distance from tree.