• Proceedings of the IEEK Conference
• /
• 1999.11a
• /
• pp.240-243
• /
• 1999

This paper presents a data-dependent precharge suppression(DPS) D-flip-flop(DFF) with precharge suppression scheme according to data-transition probability The main feature of the DPS DFF is that precharge is suppressed when there is no data transition. The proposed DPS DFF consumes less power than the conventional Yuan-Svensson's true single phase clocking(TSPC) DFF when the data-transition probability is low. The simulation result shows that the power consumption is reduced by 42.2 % when the data-transition probability is 30%.

• Korean Journal of Computational Design and Engineering
• /
• v.12 no.4
• /
• pp.245-254
• /
• 2007

This research proposed feature extraction algorithms as an input of STEP Ap214 data, and feature parameterization process to simplify further design change and maintenance. The procedure starts with suppression of blend faces of an input solid model to generate its simplified model, where both constant and variable-radius blends are considered. Most existing cell decomposition algorithms utilize concave edges, and they usually require complex procedures and computing time in recomposing the cells. The proposed algorithm using reference features, however, was found to be more efficient through testing with a few sample cases. In addition, the algorithm is able to recognize depression features, which is another strong point compared to the existing cell decomposition approaches. The proposed algorithm was implemented on a commercial CAD system and tested with selected industrial product models, along with parameterization of recognized features for further design change.

• Korean Journal of Computational Design and Engineering
• /
• v.15 no.3
• /
• pp.243-252
• /
• 2010

This paper describes a new practical simplification method for feature-based solid models. In this approach, a solid model created using feature modeling operations is first simplified by the suppression of detailed features, and then, if necessary, the model is converted to a surface model to facilitate its modification. Finally, the simplified surface model is delivered to analysis packages. The algorithm was implemented based on CATIA V.5 and applied to mid-surface generation of plastic parts for structural analysis to prove the validity and usefulness.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.1795-1811
• /
• 2019

In order to achieve rapid and accurate detection of vehicle objects in complex traffic conditions, we propose a novel vehicle detection method. Firstly, more contextual and small-object vehicle information can be obtained by our Joint Feature Network (JFN). Secondly, our Evolved Region Proposal Network (EPRN) generates initial anchor boxes by adding an improved version of the region proposal network in this network, and at the same time filters out a large number of false vehicle boxes by soft-Non Maximum Suppression (NMS). Then, our Mask Network (MaskN) generates an example that includes the vehicle occlusion, the generator and discriminator can learn from each other in order to further improve the vehicle object detection capability. Finally, these candidate vehicle detection boxes are optimized to obtain the final vehicle detection boxes by the Fine-Tuning Network(FTN). Through the evaluation experiment on the DETRAC benchmark dataset, we find that in terms of mAP, our method exceeds Faster-RCNN by 11.15%, YOLO by 11.88%, and EB by 1.64%. Besides, our algorithm also has achieved top2 comaring with MS-CNN, YOLO-v3, RefineNet, RetinaNet, Faster-rcnn, DSSD and YOLO-v2 of vehicle category in KITTI dataset.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.382-383
• /
• 2016

Canny edge detection of the image is composed of four kinds of Gaussian filter, gradient calculation, Non-maximum suppression, and Hypothesis Thresholding. Feature is the ratio between the vehicle body, the windows, and the wheels obtained from the edge image. Features that make the proportion of these vehicles are different for each respective model. We have identified by application of this algorithm where only a small vehicle.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.10a
• /
• pp.77-80
• /
• 2013

SURF algorithm is an algorithm to extract feature points and to generate descriptors from input images. It is robust to change of environment such as scale, rotation, illumination and view points. Because of these features, it is used for many image processing applications such as object recognition, constructing panorama pictures and 3D image restoration. But there is disadvantage for real time operation because many recognition algorithms such as SURF algorithm requires a lot of calculations. In this paper, we propose a design of feature extractor and descriptor generator based on SURF for high memory efficiency. The proposed design reduced a memory access and memory usage to operate in real time.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.680-683
• /
• 1987

The speech signal processing in the auditory system can be analysized based on two representations : Average discharge rate and Temporal discharge pattern. But the average discharge rate representation is restricted by the narrow dynamic range because of the rate saturation and the two tone suppression phenomena, and the temporal discharge pattern representation needs a sophisticate frequency analysis and synchrony measure. In this paper, a simple representation is proposed : using a model considering the interaction of Cochlear fluid-BM movement and a haircell model, the feature of speech signals (formant frequency and pitch of vowels) is easily estimated in the Average Synchronized Rate.

• East Asian mathematical journal
• /
• v.37 no.5
• /
• pp.599-612
• /
• 2021

In China, Weibo is one of the social platforms with more users. It has the characteristics of fast information transmission and wide coverage. People can comment on a certain event on Weibo to express their emotions and attitudes. Judging the emotional tendency of users' comments is not only beneficial to the monitoring of the management department, but also has very high application value for rumor suppression, public opinion guidance, and marketing. This paper proposes a two-input Adaboost model based on TextCNN and BiLSTM. Use the TextCNN model that can perform local feature extraction and the BiLSTM model that can perform global feature extraction to process comment data in parallel. Finally, the classification results of the two models are fused through the improved Adaboost algorithm to improve the accuracy of text classification.

• The Korean Journal of Physiology and Pharmacology
• /
• v.14 no.6
• /
• pp.385-390
• /
• 2010

Excessive extracellular matrix (ECM) accumulation is the main feature of chronic renal disease including diabetic nephropathy. Plasminogen activator inhibitor (PAI)-1 is known to play an important role in renal ECM accumulation in part through suppression of plasmin generation and matrix metalloproteinase (MMP) activation. The present study examined the effect of PAI-1 antisense oligodeoxynucleotide (ODN) on fibronectin upregulation and plasmin/MMP suppression in primary mesangial cells cultured under high glucose (HG) or transforming growth factor (TGF)-${\beta}1$, major mediators of diabetic renal ECM accumulation. Growth arrested and synchronized rat primary mesangial cells were transfected with $1\;{\mu}M$ phosphorothioate-modified antisense or control mis-match ODN for 24 hours with cationic liposome and then stimulated with 30 mM D-glucose or 2 ng/ml TGF-${\beta}1$. PAl-1 or fibronectin protein was measured by Western blot analysis. Plasmin activity was determined using a synthetic fluorometric plasmin substrate and MMP-2 activity analyzed using zymography. HG and TGF-${\beta}1$ significantly increased PAI-1 and fibronectin protein expression as well as decreased plasmin and MMP-2 activity. Transient transfection of mesangial cells with PAI-1 antisense ODN, but not mis-match ODN, effectively reversed basal as well as HG- and TGF-${\beta}1$-induced suppression of plasmin and MMP-2 activity. Both basal and upregulated fibronectin secretion were also inhibited by PAI-1 antisense ODN. These data confirm that PAI-1 plays an important role in ECM accumulation in diabetic mesangium through suppression of protease activity and suggest that PAI-1 antisense ODN would be an effective therapeutic strategy for prevention of renal fibrosis including diabetic nephropathy.

• The Journal of the Acoustical Society of Korea
• /
• v.35 no.2
• /
• pp.102-109
• /
• 2016

This paper proposes a noise suppression method through SNR (Singal-to Noise Ratio) estimation in the two microphone array environment of close spacing. The conventional method uses a noise suppression method for a gain function obtained through the SNR estimation based on coherence function from full band. However, this method cause performance decreased by the noise damage that affects all the feature vector component. So, we propose a noise suppression method that allocates a frequency domain signal into N constant multi frequency band and each frequency band gets a gain function through SNR estimation based on coherence function. Performance evaluation of the proposed method is shown by comparison with PESQ (Perceptual Evaluation of Speech Quality) value which is an objective quality evaluation method provided by the ITU-T (International Telecommunications Union Telecommunication).