• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.181-184
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• 2001

Chemical Mechanical Polishing(CMP) of Shallow Trench Isolation(STI) structure in 0.18 m semiconductor device fabrication is studied. CMP process is applied for the STI structure with and without reverse moat pattern and End Point Detection (EPD) method is tested. To optimize the transistor properties related metal 1 parameters, we studied the correlation between CMP thickness of STI using high selectivity slurry, DOE of gate etch recipe, and 1st metal DC values. Remaining thickness of STI CMP is proportional to the thickness of gate-etch process and this can affect to gate profile. As CMP thickness increased, the N-poly foot is deteriorated, and the P-Poly Noth is getting better. If CD (Critical Dimension) value is fixed at some point, all IDSN/P values are in inverse proportional to CMP thickness by reason of so called Profile Effect. Weve found out this phenomenon in all around DOE conditions of Gate etch process and we also could understand that it would not have any correlation effects between VT and CMP thickness in the range of POE 120 sec conditions. As CMP thickness increased by 100 ${\AA}$, 3.2 u${\AA}$ of IDSN is getting better in base 1 condition. In POE 50% condition, 1.7 u${\AA}$ is improved, and 0.7 u${\AA}$ is improved in step 2 condition. Wed like to set the control target of CD (critical dimension) in gate etch process which can affect Idsat, VT property versus STI topology decided by CMP thickness. We also would like to decide optimized thickness target of STI CMP throughout property comparison between conventional STI CMP with reverse moat process and newly introduced STI CMP using high selectivity slurry. And we studied the process conditions to reduce Gate Profile Skew of which source known as STI topology by evaluation of gate etch recipe versus STI CMP thickness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.285-293
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• 2017

Jump rope has two motions. It starts as hand motion and ends as jump motion. Therefore, two motions should be considered together to detect rotations accurately. But previous researches only consider one of the two motions as in push-up, sit-up, lift dumbbells etc, which results in inaccurate detection of rotations. In this paper, detection of rotation in jump rope using two motions through 6-axis accelerometer gyro sensor is proposed. Jump motion is detected using accelerometer sensor and hand motion is detected using gyro sensor. Also start point and end point of jump rope is detected using magnitude and standard deviation of accelerometer and gyro sensor values. The count of rotation is detected using y-axis of gyro sensor value. Y-axis of gyro sensor value indicate hand motion of jump rope motion. The usefulness of the proposed method is confirmed through experimental results.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.96-98
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• 2005

In this paper, an algorithm to compensate the distorted signals due to Current Transformer(CT) saturation is suggested, First, DWT which can be easily realized by filter banks in real-time applications is used to detect a start point and an end point of the saturation. Secondly, For enough Datas those need to use the least-square curve fitting method, the distorted current signal is compensated by the AR(autoregressive) model using the data during the previous healthy section until pick point of Saturation. Thirdly, the least-square curve fitting method is used to restore the distorted section of the secondary current. Finaly, this algorithm had a Hadware test using DSP board(TMS320C32) with Doble test device. DWT has superior detection accuracy and the proposed compensation algorithm which shows very stable features under various levels of remanent flux in the CT core is also satisfactory. And this algorithm is more correct than a previous algorithm which is only using the LSQ fitting method. Also it can be used as a MU involving the compensation function that acquires the second data from CT and PT.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.523-523
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• 2012

As the wafer geometric requirements continuously complicated and minutes in tens of nanometers, the expectation of real-time add-on sensors for in-situ plasma process monitoring is rapidly increasing. Various industry applications, utilizing plasma impedance monitor (PIM) and optical emission spectroscopy (OES), on etch end point detection, etch chemistry investigation, health monitoring, fault detection and classification, and advanced process control are good examples. However, process monitoring in semiconductor manufacturing industry requires non-invasiveness. The hypothesis behind the optical monitoring of plasma induced ion current is for the monitoring of plasma induced charging damage in non-invasive optical way. In plasma dielectric via etching, the bombardment of reactive ions on exposed conductor patterns may induce electrical current. Induced electrical charge can further flow down to device level, and accumulated charges in the consecutive plasma processes during back-end metallization can create plasma induced charging damage to shift the threshold voltage of device. As a preliminary research for the hypothesis, we performed two phases experiment to measure the plasma induced current in etch environmental condition. We fabricated electrical test circuits to convert induced current to flickering frequency of LED output, and the flickering frequency was measured by high speed optical plasma monitoring system (OPMS) in 10 kHz. Current-frequency calibration was done in offline by applying stepwise current increase while LED flickering was measured. Once the performance of the test circuits was evaluated, a metal pad for collecting ion bombardment during plasma etch condition was placed inside etch chamber, and the LED output frequency was measured in real-time. It was successful to acquire high speed optical emission data acquisition in 10 kHz. Offline measurement with the test circuitry was satisfactory, and we are continuously investigating the potential of real-time in-situ plasma induce current measurement via OPMS.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.205-212
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• 2015

SSH provides a secure, encrypted communication channel between two end point systems using public key encryption. But SSH brute force attack is one of the most significant attacks. This kind of attack aims to login to the SSH server by continually guessing a large number of user account and password combinations. In this paper, we analyze logs of SSH brute force attacks in 2014 and propose a failed-log based detection mechanism in high performance computing service environment.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.369-379
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• 2022

In weighted k-nearest neighbor (WkNN)-based Fingerprinting positioning step, a process of comparing the requested positioning signal with signal information for each reference point stored in the fingerprint DB is performed. At this time, the higher the number of matched base station identifiers, the higher the possibility that the terminal exists in the corresponding location, and in fact, an additional weight is added to the location in proportion to the number of matching base stations. On the other hand, if the matching number of base stations is small, the selected candidate reference point has high dependence on the similarity value of the signal. But one problem arises here. The positioning signal can be compared with the repeater signal in the signal information stored on the DB, and the corresponding reference point can be selected as a candidate location. The selected reference point is likely to be an outlier, and if a certain weight is applied to the corresponding location, the error of the estimated location information increases. In order to solve this problem, this paper proposes a WkNN technique including an outlier removal function. To this end, it is first determined whether the repeater signal is included in the DB information of the matched base station. If the reference point for the repeater signal is selected as the candidate position, the reference position corresponding to the outlier is removed based on the clustering technique. The performance of the proposed technique is verified through data acquired in Seocho 1 and 2 dongs in Seoul.

• Journal of Platform Technology
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• v.6 no.4
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• pp.69-77
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• 2018

In the case of personal information files containing personal information, there is insufficient awareness of personal information protection in end-point areas such as personal computers, smart terminals, and personal storage devices. In this study, we use Diffie-Hellman method to securely retrieve personal information files generated by web crawler. We designed SEED and ARIA using hybrid slicing to protect against attack on personal information file. The encryption performance of the personal information file collected by the Web crawling method is compared with the encryption decryption rate according to the key generation and the encryption decryption sharing according to the user key level. The simulation was performed on the personal information file delivered to the external agency transmission process. As a result, we compared the performance of existing methods and found that the detection rate is improved by 4.64 times and the information protection rate is improved by 18.3%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5555-5567
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• 2018

State-of-art instance segmentation networks are successful at generating 2D segmentation mask for region proposals with highest classification score, yet 3D object segmentation task is limited to geocentric embedding or detector of Sliding Shapes. To this end, we propose an amodal 3D instance segmentation network called A3IS-CNN, which extends the detector of Deep Sliding Shapes to amodal 3D instance segmentation by adding a new branch of 3D ConvNet called A3IS-branch. The A3IS-branch which takes 3D amodal ROI as input and 3D semantic instances as output is a fully convolution network(FCN) sharing convolutional layers with existing 3d RPN which takes 3D scene as input and 3D amodal proposals as output. For two branches share computation with each other, our 3D instance segmentation network adds only a small overhead of 0.25 fps to Deep Sliding Shapes, trading off accurate detection and point-to-point segmentation of instances. Experiments show that our 3D instance segmentation network achieves at least 10% to 50% improvement over the state-of-art network in running time, and outperforms the state-of-art 3D detectors by at least 16.1 AP.

• The Journal of the Acoustical Society of Korea
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• v.34 no.4
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• pp.321-327
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• 2015

In this paper, we propose an algorithm for achieving robust Visual Voice Activity Detection (VVAD) for enhanced speech recognition. In conventional VVAD algorithms, the motion of lip region is found by applying an optical flow or Chaos inspired measures for detecting visual speech frames. The optical flow-based VVAD is difficult to be adopted to driving scenarios due to its computational complexity. While invariant to illumination changes, Chaos theory based VVAD method is sensitive to motion translations caused by driver's head movements. The proposed Local Variance Histogram (LVH) is robust to the pixel intensity changes from both illumination change and translation change. Hence, for improved performance in environmental changes, we adopt the novel threshold estimation using total variance change. In the experimental results, the proposed VVAD algorithm achieves robustness in various driving situations.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.4
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• pp.403-410
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• 2000

In this paper, the development of a stock information retrieval system using speech recognition and its features are described. The system is based on DHMM (discrete hidden Markov model) and PLUs (phonelike units) are used as the basic unit for recognition. End-point detection and echo cancellation are included to facilitate speech input. Continuous speech recognizer is implemented to allow multi-word speech. Data collected over several months are analyzed.