• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.529-531
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• 2005

A block-based fast motion estimation algorithm is proposed in this paper to perform motion estimation based on the efficiently reduced search ranges in MPEG-4(ERS). This algorithm divides the search areas into several small search areas and the candidate small search area that has the lowest average of sum norm difference between current macroblock and candidate macroblock is chosen to perform block motion estimation using the Nobel Successive Elimination Algorithm (NSEA). Experimental results of the proposed algorithm show that the averaging PSNR improvement is better maximum 0.125 dB than other tested algorithms and bit saving effect is maximum 20kbps for some tested sequences in low-bit rate circumstance.

• ETRI Journal
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• 제35권5호
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• pp.757-766
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• 2013

This paper deals with the estimation of the time of arrival (TOA) of ultra-wideband signals under IEEE 802.15.4a channel models. The proposed approach is based on a randomness test and consists of determining whether an autoregressive (AR) process modeling an energy frame is random or not by using a distance to measure the randomness. The proposed method uses a threshold that is derived analytically according to a preset false alarm probability. To highlight the effectiveness of the developed approach, simulation setups as well as real data experiments are conducted to assess the performance of the new TOA estimation algorithm. Thereby, the proposed method is compared with the cell averaging constant false alarm rate technique, the threshold comparison algorithm, and the technique based on maximum energy selection with search back. The obtained results are promising, considering both simulations and collected real-life data.

• Asian Pacific Journal of Cancer Prevention
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• 제17권8호
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• pp.4043-4048
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• 2016

Background: Head and neck cancer (HNC) is the ninth most common cancer worldwide, and has a poor 5-year survival rate averaging 50%, which has not changed for decades. A high prevalence of HNC has been reported in the southwestern region of Saudi Arabia, as compared to other areas of the country. However, data in regards to HNC are scattered and not well documented. Thus, the aim of this systematic review was to gather all available and updated important information regarding HNC in Saudi Arabia, and highlight the gaps of knowledge in our country with regard to this disease. In addition, suggestions of solutions to overcome the current status and improve our future standard of care to fight HNC are also highlighted. Materials and Methods: The electronic databases PubMed and Google Scholar using English-language literature were used for this systematic review, using specific inclusion and exclusion criteria and keywords. The search was performed in April 2016 and updated in June 2016. Results: Our search revealed twenty-one studies that fulfilled our inclusion and exclusion criteria and that were conducted in Saudi Arabia. These studies investigated different aspects of HNC, including prevalence, risk factors, biomarkers, and assessed knowledge and awareness of both public and practitioners with regard to HNC. Conclusions: This review uncovered a big gap in our epidemiological data in cancer information in general, and head and neck cancer in particular. In addition, a lack of knowledge and awareness of both the public and health care practitioners hinders the early diagnosis of disease and negatively impact the prognosis, treatment and outcome. The Ministry of Health in Saudi Arabia should develop a more systematic way and adapt policies to gather cancer information in general, and head and neck cancer in particular, from all governmental and private sectors from all over the kingdom, and develop educational programs to raise the knowledge and awareness of HNC in the country.

• 한국정보통신학회논문지
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• 제19권6호
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• pp.1477-1484
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• 2015

본 논문에서는 칼만 필터 알고리즘과 공분산 행렬을 결합한 강인한 이동 물체 추적 방법을 제안한다. 연속적으로 변화하는 영상 내에서 추적하고자 하는 물체의 특징으로서 공분산 행렬은 특징들의 상관관계뿐만 아니라 공간적인 속성과 통계적 속성을 다루므로 목표물의 형태와 모양의 변화에도 추적의 지속성을 보장한다. 그러나 이동 물체의 움직이는 속도가 연산 속도보다 고속의 경우 실시간 추적이 어려우며 탐색 윈도우가 목표물을 놓치므로 이를 해결하기 위해 칼만 필터를 사용하여 이동 물체의 영역을 추정하며, 칼만 탐색 윈도우 내 이동 물체 영역의 공분산 행렬을 특징 벡터로 구성하고, 후보 영역의 공분산 행렬과 비교하면서 추적하는 방법을 실험하여 96.3%의 추적률을 달성하였다.