• Asia pacific journal of information systems
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• v.15 no.4
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• pp.89-107
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• 2005

As new information technology(IT) adoption continues to produce many investment opportunities, imperfectly informed IT managers keep trying to acquire credible external signals to update their knowledge on new technologies. Such learning processes usually help them to reach better IT adoption decisions. In some cases, however, the opposite of the goal is achieved. Most IT managers quickly converge to the same adoption decision independent of their private information. Interestingly, such information cascade is the outcome of each individual decision maker's rational choice. A technology acceptance model(TAM) is adopted that has been widely used to predict the end-user's acceptance of a new technology. A model with individual charact-eristics and information cascade variables is constructed to explain user's intention in adopting blogging. The model is empirically tested with surveyed data. The results show that individual characteristics and information cascades have significant impacts in the case of blogging.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.3
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• pp.421-426
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• 2002

Hybrid cascade multilevel PWM inverter has advantages of hybrid structure which enhances the better utilization of power semiconductor switches, that is, both hi호 power-low frequency switch, GTO and low power-high frequency switch, IGBT can be used in the same circuit. In this paper, a static var compensator using hybrid cascade 5-level PWM inverter is presented for high voltage/high power applications. The proposed system is modelled by circuit DQ transformation, and thus an equivalent circuit is obtained which reveals the important characteristics of the system and lead to the related equations. Finally, circuit structure and characteristics is presented and the validity of the characteristics analysis is shown through PSIM simulation.

• Annual Conference of KIPS
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• 2015.04a
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• pp.1022-1024
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• 2015

휴먼-컴퓨터 인터렉션과 같은 응용분야에서 손동작 인식을 위한 많은 연구가 이루어지고 있다. 손동작 인식을 이용한 인터렉션의 성능 향상을 위해서는 정확한 손 영역 검출이 필요하다. 본 논문에서는 색상 정보를 이용하여 Cascade 방식에 기반한 손 영역 검출 방법을 제안한다. Cascade 방식으로 손 영역을 검출할 경우보다 강인한 인식률을 얻기 위해서 색상정보를 이용하였으며, Haar-like 특징점으로 학습된 분류기를 통해 손 영역 검출 방법을 제안한다.

• Review of KIISC
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• v.5 no.2
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• pp.90-96
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• 1995

Gollmann이 제안한 Cascade 생성기는 비선형성, 발생되는 수열의 난수특성, 주기성등 암호 알고리즘으로서 필요한 제반 특성을 보장하기 때문에 그동안 스트림 암호의 핵심 논리로 널리 사용되어 왔다. 그러나 최근 생성기 내부의 각 단계별로 시각 제어 수열과 출력 수열 사이에 암호 알고리즘으로는 부적당한 상관관계 특성이 존재함이 입증되었다. 본 고에서는 이러한 상관관계 특성을 이용하여,. 단순 순환 쉬프트 래지스터로 구성된 Cascade 생성기에 대한 기지 평문 공격 방식을 제안한다. 기존의 Lock-in effect 공격방식에 대하여 $10^{21}$ 정도의 안전성을 보장하는 8단계 11-cycle Cascade 생성기에 본 방식을 적용한 결과 불과 88,000 출력 비트만을 사용하여 공격이 성공함을 실험적으로 입증하였다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.12
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• pp.37-43
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• 2009

This paper describes a monolithic Darlington-cascade amplifier (DCA) operating at X-band, realized with a 0.35-micron SiGe bipolar process, which provides 45 GHz $f_T$. A conventional cascade amplifier was also designed on the same process and tested to establish a reference. Compared to the reference cascade amplifier, the proposed monolithic amplifier circuit exhibits an improved gain of 2.5 dB and improved output power 1-dB compression point of 5.2 dB with 72% wider bandwidth. Measurement results show 19.5 dB gain, 11.2 dBm 1-dB compression power, and 3.1 GHz bandwidth. These results demonstrate that the Darlington-cascade cell is an advantageous substitute to the conventional cascade amplifier.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.873-891
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• 2018

This paper suggests an automatic approach to extracting Java method implementation patterns associated with method identifiers using Cascade K-Medoids. Java method implementation patterns indicate recurring implementations for achieving the purpose described in the method identifier with the given parameters and return type. If the implementation is different from the purpose, readers of the code tend to take more time to comprehend the method, which eventually affects to the increment of software maintenance cost. In order to automatically identify implementation patterns and its representative sample code, we first propose three groups of feature vectors for characterizing the Java method signature, method body and their relation. Then, we apply Cascade K-Medoids by enhancing the K-Medoids algorithm with the Calinski and Harrabasez algorithm. As the evaluation of our approach, we identified 16,768 implementation patterns of 7,169 method identifiers from 50 open source projects. The implementation patterns have been validated by the 30 industrial practitioners with from 1 to 6 years industrial experience, resulting in 86% of the precision.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.3
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• pp.481-486
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• 2002

In this paper, we propose CELM(Cascade ELM) to improve stability. We could realize as cascade connected each other key value with N degree equation which has a initial value. And we could know to be improved in stability with the nature of Chaos in simulation result. In efficiency, this CELM algorithm identified sire of encrypted code with size of source code and we could know more efficient than existing RSA and ECC. In speed, CELM took average 0.18㎳ degree to encrypt a file. Although it was slower than DES, it was faster than ECC of RSA.

• Annual Conference of KIPS
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• 2016.04a
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• pp.700-703
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• 2016

OpenCV(Open Computer Vision)에서 제공하는 얼굴 검출 알고리즘은 Haar-like feature와 Cascade 방식을 이용하여 얼굴의 패턴을 찾아내 얼굴을 검출한다. 그러나 우연히 얼굴이 아닌 곳이 얼굴과 유사한 패턴일 경우, 얼굴로 인식하는 오류를 범하게 된다. 따라서 본 논문은 MCT(Modified Census Transform)와 신경망을 이용하여 잘못된 얼굴 검출 영역을 감소시키는 알고리즘을 제안한다. MCT는 다양한 조명 조건에서도 강인한 얼굴 영상의 지역적 구조 특징을 추출하기 위하여 사용되고, 신경망 알고리즘은 Haar-Cascade 알고리즘의 얼굴 검출 방법으로 검출된 영역이 실제로 얼굴인지 아닌지를 판단하기 위하여 사용된다. 실험에서 사용된 6개의 데이터들은 인터넷에서 수집한 것으로서, Haar-Cascade 알고리즘의 얼굴 검출 방법으로 얼굴을 검출하였을 때 오검출된 영역이 1개 이상 존재한다. 본 논문에서 제안한 알고리즘으로 실험한 결과, Haar-Cascade 알고리즘의 얼굴 검출 방법에 비하여 오검출된 영역이 감소된 것을 확인할 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.318-321
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• 2002

A static var compensator using hybrid cascade 5-level PWM inverter is presented for high voltage/high power applications. The proposed system is modelled by circuit DQ transformation, and thus an equivalent circuit is obtained which reveals the important characteristics of the system and lead to the related equations. The proposed system has advantages of hybrid structure which enhances the better utilization of power semiconductor switches, that is, both high power-low frequency switch, GTO and low power-high frequency switch, IGBT can be used in the same circuit. In this paper, circuit structure and characteristics is presented and the validity of the characteristics analysis is shown through PSIM simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2882-2903
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• 2022

Image super-resolution (SR) processing is of great value in the fields of digital image processing, intelligent security, film and television production and so on. This paper proposed a densely connected deep learning network based on cascade architecture, which can be used to solve the problem of super-resolution in the field of image quality enhancement. We proposed a more efficient residual scaling dense block (RSDB) and the multi-channel cascade architecture to realize more efficient feature reuse. Also we proposed a hybrid loss function based on L₁ error and L_∞ error to achieve better L_∞ error performance. The experimental results show that the overall performance of the network is effectively improved on cascade architecture and residual scaling. Compared with the residual dense net (RDN), the PSNR / SSIM of the new method is improved by 2.24% / 1.44% respectively, and the L_∞ performance is improved by 3.64%. It shows that the cascade connection and residual scaling method can effectively realize feature reuse, improving the residual convergence speed and learning efficiency of our network. The L_∞ performance is improved by 11.09% with only a minimal loses of 1.14% / 0.60% on PSNR / SSIM performance after adopting the new loss function. That is to say, the L_∞ performance can be improved greatly on the new loss function with a minor loss of PSNR / SSIM performance, which is of great value in L_∞ error sensitive tasks.