• Smart Structures and Systems
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• v.17 no.5
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• pp.819-835
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• 2016

In this paper, the activities carried out within the EU funded Clean Sky Joint Technology Initiative (JTI GRA) Project and aimed at developing a morphing flap, are illustrated. The reference device is a regional aircraft single slotted flap, enhanced with deforming capabilities to obtain improved hyper-lift performance. The design started with the identification of the internal architecture, intended to allow camber variations. A concentrated-hinge architecture was selected, for its ability to fit different curvatures and for the possibility of easily realizing an "armadillo-like" configuration, then avoiding the use of a complicate deformable skin. The flap layout is made of segmented ribs, elastically hinged each other and span-wise connected by conventional spars. Relative rotations of the rib elements are forced by SMA structural actuators, i.e., cooperating in the external loads absorption. Super-elastic SMA are used to make up recovery elastic elements, necessary to regain the original shape after activation. These further elements in turn contribute to the overall flap rigidity. After assessing the hinge number and the size of the SMA active and passive elements, the advanced design phase was dealt with. It was aimed at solving manufacturing issues and producing the executive drawings. The realized demonstrator was finally tested in lab conditions to prove its functionality in terms of whether target shape actuation or attained shape preservation under loads. On the basis of the numerical results and the experimental outcomes, precious hints were obtained for further developments of the concept.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.128-134
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• 2016

IoT devices including smart devices are connected with internet, thus they have security threats everytime. Particularly, IoT devices are composed of low performance MCU and small-capacity memory because they are miniaturized, so they are likely to be exposed to various security threats like DoS attacks. In addition, in case of IoT devices installed for a remote place, it's not easy for users to control continuously them and to install immediately security patch for them. For most of IoT devices connected directly with internet under user's intention, devices exposed to outside by setting IoT gateway, and devices exposed to outside by the DMZ function or Port Forwarding function of router, specific protocol for IoT services was used and the devices show a response when services about related protocol are required from outside. From internet search engine for IoT devices, IP addresses are inspected on the basis of protocol mainly used for IoT devices and then IP addresses showing a response are maintained as database, so that users can utilize related information. Specially, IoT devices using HTTP and HTTPS protocol, which are used at usual web server, are easily searched at usual search engines like Google as well as search engine for the sole IoT devices. Ill-intentioned attackers get the IP addresses of vulnerable devices from search engine and try to attack the devices. The purpose of this study is to find the problems arisen when HTTP, HTTPS, CoAP, SOAP, and RestFUL protocols used for IoT devices are detected by search engine and are maintained as database, and to seek the solution for the problems. In particular, when the user ID and password of IoT devices set by manufacturing factory are still same or the already known vulnerabilities of IoT devices are not patched, the dangerousness of the IoT devices and its related solution were found in this study.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.502-502
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• 2007

Current thin film process using memory device fabrication process use expensive processes such as manufacturing of photo mask, coating of photo resist, exposure, development, and etching. However, direct printing technology has the merits about simple and cost effective processes because inks are directly injective without mask. And also, this technology has the advantage about fabrication of fine pattern line on various substrates such as PCB, FCPB, glass, polymer and so on. In this work, we have fabricated the fine and thick metal pattern line for the electronic circuit board using metal ink contains Ag nano-particles. Metal lines are fabricated by two types of printing methods. One is a conventional printing method which is able to quick fabrication of fine pattern line, but has various difficulties about thick and high resolution DPI(Dot per Inch) pattern lines because of bulge and piling up phenomenon. Another(Second) methods is sequential printing method which has a various merits of fabrication for fine, thick and high resolution pattern lines without bulge. In this work, conductivities of metal pattern line are investigated with respect to printing methods and pattern thickness. As a result, conductivity of thick pattern is about several un.

• Journal of IKEEE
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• v.25 no.3
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• pp.473-478
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• 2021

Although CNTFETs have attracted great attention due to their ability to increase semiconductor device performance by about 13 times, the commercialization of CNTFETs has been challenging because of the immature deposition process of CNTs. To overcome these difficulties, circuit design method considering the known limitations of the CNTFET manufacturing process is receiving increasing attention. SRAM is a major element constituting microprocessor and is regularly and repeatedly positioned in the cache memory; so, it has the advantage that CNTs can be more easily and densely deposited in SRAM than other circuit blocks. In order to take these advantages, this paper presents a circuit design method for SRAM cells considering CNT density and then evaluates its performance improvement using HSPICE simulation. As a result of simulation, it is found that when CNTFET is applied to SRAM, the gate width can be reduced by about 1.7 times and the read speed also can be improved by about 2 times when the CNT density was increased in the same gate width.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Korean Chemical Engineering Research
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• v.47 no.6
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• pp.715-719
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• 2009

The phase change electrode board for the bio-information detection through electrical property response of phase change material was developed in this study. We manufactured the electrode board using Aluminum first that is widely used in conventional semiconductor device process. Without further treatment, these aluminum electrodes tend to contain voids in PETEOS(plasma enhanced tetraethyoxysilane) material that are easily detected by cross-sectional SEM(Scanning Electron Microscope). The voids can be easily attacked and transformed into holes in between PETEOS and electrodes after etch back and washing process. In order to resolve this issue of Al electrode board, we developed a electrode board manufacturing method using low resistivity TiN, which has advantages in terms of the step-coverage of phase change($Ge_2Sb_2Te_5$, GST) thin film as well as thermodynamic stability, without etch back and washing process. This TiN material serves as the top and bottom electrode in PRAM(Phase-change Random Access Memory). The good connection between the TiN electrode and GST thin film was confirmed by observing the cross-section of TiN electrode board using SEM. The resistances of amorphous and crystalline GST thin film on TiN electrodes were also measured, and 1000 times difference between the amorphous and crystalline resistance of GST thin film was obtained, which is well enough for the signal detection.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.18-26
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• 2016

The semiconductor industry is one of the key industries of Korea, which has continued growing at a steady annual growth rate. Important technology for the semiconductor industry is high integration of devices. This is to increase the memory capacity for unit area, of which key is photolithography. The photolithography refers to a technique for printing the shadow of light lit on the mask surface on to wafer, which is the most important process in a semiconductor manufacturing process. In this study, the width and step-height of wafers patterned through this process were measured to ensure uniformity. The widths and inter-plate heights of the specimens patterned using photolithography were measured using transmissive digital holography. A transmissive digital holographic interferometer was configured, and nine arbitrary points were set on the specimens as measured points. The measurement of each point was compared with the measurements performed using a commercial device called scanning electron microscope (SEM) and Alpha Step. Transmission digital holography requires a short measurement time, which is an advantage compared to other techniques. Furthermore, it uses magnification lenses, allowing the flexibility of changing between high and low magnifications. The test results confirmed that transmissive digital holography is a useful technique for measuring patterns printed using photolithography.