• Journal of Power Electronics
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• v.17 no.5
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• pp.1308-1316
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• 2017

The distributed maximum power point tracking (DMPPT) concept is widely adopted in photovoltaic systems to avoid mismatch loss. However, the high cost and complexity of DMPPT hinder its further promotion in practice. Based on the concept of DMPPT, this paper presents an integrated submodule level half-bridge stack structure along with an optimal current point tracking (OCPT) control algorithm. In this full power processing integrated solution, the number of power switches and passive components is greatly reduced. On the other hand, only one current sensor and its related AD unit are needed to perform the ideal maximum power generation for all of the PV submodules in any irradiance case. The proposal can totally eliminate different small-scaled mismatch effects in real-word condition and the true maximum power point of each PV submodule can be achieved. As a result, the ideal maximum power output of the whole PV system can be achieved. Compared with current solutions, the proposal further develops the integration level of submodule DMPPT solutions with a lower cost and a smaller size. Moreover, the individual MPPT tracking for all of the submodules are guaranteed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1307-1315
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• 2017

While the PSK mode of the DTLS is the most efficient in terms of the performance, it is not easy to pre-distribute and manage the symmetric key pairs as the number of sensor devices increases. On the other hand, both the RPK and certificate modes offer a convenient key management tool, but they do not guarantee a good computational performance. In this paper, the end-to-end security protocol suitable for the constrained devices is proposed, based on both the ECQV certificate and the PSK mode. Namely, the initial DTLS handshake is performed using the ECQV certificate, and the subsequent DTLS handshakes with the other CoAP servers in the same group are performed using the PSK mode for the purpose of reducing the overall computational load. Furthermore, a fine-grained access control for the CoAP client can be enforced to allow access to the limited number of CoAP servers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• The KIPS Transactions:PartA
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• v.17A no.2
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• pp.81-92
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• 2010

There has been some research in the equipment defect detection based on vibration information. Most research of them is based on vibration monitoring to determine the equipment defect or not. In this paper, we introduce more accurate system for engine defect detection based on vibration information and we focus on detection of engine defect for boat and system control. First, it uses the duplicated-checking method for vibration information to determine the engine defect or not. If there is a defect happened, we use the method using error part of vibration information basis with error range to determine which kind of error is happened. On the other hand, we use the engine trend analysis and standard of safety engine to implement the vibration information database. Our simulation results show that the probability of engine defect determination is 100% and the probability of engine defect classification and detection is 96%.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.237.1-237.1
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• 2014

Etching is one of the most important steps in semiconductor manufacturing. In etch process control a critical task is to stop the etch process when the layer to be etched has been removed. If the etch process is allowed to continue beyond this time, the material gets over-etched and the lower layer is partially removed. On the other hand if the etch process is stopped too early, part of the layer to be etched still remains, called under-etched. Endpoint detection (EPD) is used to detect the most accurate time to stop the etch process in order to avoid over or under etch. The goal of this research is to develop a hardware and software system for EPD. The hardware consists of an Optical Plasma Monitor (OPM) sensor which is used to continuously monitor the plasma optical emission intensity during the etch process. The OPM software was developed to acquire and analyze the data to perform EPD. Our EPD algorithm is based on the following theory. As the etch process starts the plasma generated in the vacuum is added with the by-products from the etch reactions on the layer being etched. As the endpoint reaches and the layer gets completely removed the plasma constituents change gradually changing the optical intensity of the plasma. Although the change in optical intensity is not apparent, the difference in the plasma constituents when the endpoint has reached leaves a unique signature in the data gathered. Though not detectable in time domain, this signature could be obscured in the frequency spectrum of the data. By filtering and analysis of the changes in the frequency spectrum before and after the endpoint we could extract this signature. In order to do that, first, the EPD algorithm converts the time series signal into frequency domain. Next the noise in the frequency spectrum is removed to look for the useful frequency constituents of the data. Once these useful frequencies have been selected, they are monitored continuously in time and using a sub-algorithm the endpoint is detected when significant changes are observed in those signals. The experiment consisted of three kinds of etch processes; ashing, SiO2 on Si etch and metal on Si etch to develop and evaluate the EPD system.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.6
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• pp.904-911
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• 2015

The objective of this study was to investigate the quality characteristics of traditional wine using an radio-frequency identification (RFID) system annexed to a fermenter. In this study, we proposed an RFID-based data transmission scheme for monitoring fermentation of traditional alcoholic beverages. The pH, total acidity, total sugar, soluble sugar, free sugar, alcohol content, and organic acids of were investigated and subjected to fermentation of traditional alcoholic beverages three times. The pH ranged from 7.98, 7.95, and 7.68 at day 0, decreased drastically to 3.31~2.96 at day 2, and then slowly increased to the end point, finally reaching 3.34 at day 20. Acidity tended to increase quickly with time, especially for all samples after day 2. The fermentation environment induced a sudden increase acidity in reactants and indicated a low pH. The total sugars during fermentation quickly decreased to the range of 20.3, 22.43, and 19.2% at day 2, and the slope of reduction steadily decreased to 5.1, 6.1, and 4.8% at day 10. On the other hand, the alcohol content showed the reverse trend as total sugars. The alcohol content also showed the same pattern as total acids, showing the highest alcohol content of 17.3% (v/v) on day 20. In this study on traditional wine fermentation using an RFID system, we showed that pH, soluble sugar, and alcohol content can be adopted as key indicators for quality control and standardization of traditional wine manufacturing.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.3
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• pp.464-477
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• 2013

There is a great need to develop a training program proven to change behavior and improve knowledge. The purpose of this study was to evaluate employee hygiene knowledge, hygiene practice, and cleanliness, before and after HACCP system implementation at one small-size restaurant. The efficiency of the system was analyzed using time-temperature control after implementation of u-HACCP$^{(R)}$. The employee hygiene knowledge and practices showed a significant improvement (p<0.05) after HACCP system implementation. In non-heating processes, such as seasoned lettuce, controlling the sanitation of the cooking facility and the chlorination of raw ingredients were identified as the significant CCP. Sanitizing was an important CCP because total bacteria were reduced 2~4 log CFU/g after implementation of HACCP. In bean sprouts, microbial levels decreased from 4.20 logCFU/g to 3.26 logCFU/g. There were significant correlations between hygiene knowledge, practice, and microbiological contamination. First, personnel hygiene had a significant correlation with 'total food hygiene knowledge' scores (p<0.05). Second, total food hygiene practice scores had a significant correlation (p<0.05) with improved microbiological qualities of lettuce salad. Third, concerning the assessment of microbiological quality after 1 month, there were significant (p<0.05) improvements in times of heating, and the washing and division process. On the other hand, after 2 months, microbiological was maintained, although only two categories (division process and kitchen floor) were improved. This study also investigated time-temperature control by using ubiquitous sensor networks (USN) consisting of an ubi reader (CCP thermometer), an ubi manager (tablet PC), and application software (HACCP monitoring system). The result of the temperature control before and after USN showed better thermal management (accuracy, efficiency, consistency of time control). Based on the results, strict time-temperature control could be an effective method to prevent foodborne illness.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.17 no.1
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• pp.28-37
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• 2006

Purpose: Evaluation of vocal cord vibration is very important in cases of voice disorders. There are several equipments for examining the vocal fold vibration such as laryngeal stroboscope, ultra high-speed digital imaging system, and videokymograph. Among these, laryngeal stroboscope is the most popular equipment because of easy to examine the laryngeal pathology. However, current laryngo-stroboscopes are too bulky to move and relatively expensive. The purpose of this research is to develope a portable laryngeal stroboscope of equivalent performance with the current equipments. Methods and Materials: Recently developed high luminescent white LEDs(light emitting diodes) are placed at the head of the endoscope as light sources for the CCD image sensor which is also placed at the head with imaging lens. This arrangement eliminates the bulky light source like expensive halogen or xenon lamps as well as the optical light guiding cables. The LEDs are controlled to flash in phase with the voice frequency of the examinee. The CCD captures these strobo images and converts them into video signals for examinations. Results: There was no functional differences between preexisting stroboscope and the newly developed stroboscope of this study. LED light sources and microprocessor based control circuits of the stroboscope enabled the development of flicker-less, hand-held, portable and battery-operating stroboscope. Conclusion: The developed stroboscope is cost-effective, small-sized, easy to use and very easy desirable to bring and to use in any place.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.141-148
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• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• Journal of Bio-Environment Control
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• v.13 no.4
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• pp.217-225
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• 2004

This study was performed to provide the basic knowledge about the mushroom cultivation facilities. Classified current status of cultivation facilities in Gyeongnam province was investigated by questionnaire. The structure of Pleurotus eryngii cultivation facilities can be classified into the simple and permanent frame type. The simple frame structures were mostly single-span type, on the other hand, the permanent frame structures were more multi-span than simple structures. And the scale of cultivation facilities was very different regardless of structural type. But as a whole, the length, width and ridge height were prevailing approximately 20.0 m, $6.6\~7.0m$ and $4.6\~5.0m$ range, respectively. The floor area was about $132\~160\;m^2$, and floor was built with concrete to protect mushrooms from various harmful infection. The roof slope of the simple and permanent type showed about $41.5^{\circ}\;and\;18.6\~28.6^{\circ}$, respectively. The width and layer number of growing bed for mushroom cultivation were around $1.2\~1.6m$, 4 layers in common, respectively. Most of year round cultivation facilities were equipped with cooler, heater, humidifier, and ventilating fan. Hot water boiler was the most commonly used heating system, the next was electric heater and then steam boiler. The industrial air conditioner has been widely used for cooling. And humidity was controlled mostly by ultra-wave or centrifuging humidifier. But some farmers has been using nozzle system for auxiliary purpose. More then $90\%$ of the mushroom house had the independent environment control system. The inside temperature was usually controlled by sensor, but humidity and $CO_2$ concentration was controlled by timer for each growing stage. The capacity of medium bottle was generally 850 cc and 1100cc, some farms used 800 cc, 950 co and 1,250 cc. Most of mushroom producted has been usually shipped to both circulating company and joint market.