• ETRI Journal
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• 제26권6호
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• pp.555-559
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• 2004

We propose an efficient digital IF down converter architecture for dual-mode WCDMA/cdma2000 based on the concept of software defined radio. Multi-rate digital filters and fractional frequency conversion techniques are adopted to implement the front end of a dual-mode receiver for WCDMA and cdma2000. A sub-sampled digital IF stage was proposed to support both WCDMA and cdma2000 while lowering the sampling frequency. Use of a CIC filter and ISOP filter combined with proper arrangement of multi-rate filters and common filter blocks resulted in optimized hardware implementation of the front end block in 292k logic gates.

• International Journal of Contents
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• 제12권1호
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• pp.65-69
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• 2016

Wireless communication chipsets have fixed transmission rate and communication distance. Although there are many kinds of chipsets with throughput and distance purpose, they cannot support various types of wireless applications. This paper provides theoretic research results in order to support various wireless applications requiring different throughput, delayed quality-of-service (QoS), and different communication distances by using a wireless communication chipset with fixed rate and transmission power. As a performance metric, the probability for a data frame that successfully receives at a desired receiver is adopted. Based on this probability, the average number of transmission in order to make a successful frame transmission is derived. Equations are utilized to analyze the performance of a single-hop with channel coding and a dual-hop without error correction matter transmission system. Our results revealed that single-hop transmission assisted by channel coding could extend its communication distance. However, communication range extending effect of the single-hop system was limited. Accordingly, dual-hop transmission is needed to overcome the communication distance limit of a chipset.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권12호
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• pp.4356-4371
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• 2014

When the load in a multi-cell orthogonal frequency division multiple access (OFDMA) system is allowed to excessively increase in face of frequent handover, the cell area becomes smaller than the designed size, and thus continuity of quality of service (QoS) for handover requests cannot be guaranteed. To efficiently support the mobility of a mobile terminal (MT), we should adaptively cope with the resource demand of handover calls. This paper proposes a twofold resource-reservation scheme for OFDMA systems to guarantee continuity of QoS for various mobile multimedia services during MT handover from lightly to heavily loaded cells. Our twofold scheme attempts to guarantee service continuity for handover and to maximize resource allocation efficiency. We performed a simulation to evaluate our scheme in terms of outage probability, handover failure rate, total throughput, and blocking rate.

• Asian Pacific Journal of Cancer Prevention
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• 제17권sup3호
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• pp.213-218
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• 2016

Cancer is a major health problem in the Arab region including Iraq. An adequate database is essential for effective cancer control strategies. Such a database may be provided through cancer registration but supportive household surveys may be useful. This article reports selected results on the feasibility of household surveys to support and validate cancer registration in Basrah governorate - southern Iraq. A large scale multi-stage cluster sample household survey was carried out in Basrah during 2013. It covered 6,999 households and involved gathering data on demographic characteristics and both incident cancer cases and cancer-related deaths among members of these households during a three-year recall period (2010-2012). The data obtained yielded an average annual incidence rate of 91 per 100,000 population (age-standardized incidence rate of 148.8 /100,000) and cancer specific mortality rate of 68 per 100,000 population (age-standardized mortality rate of 126.3/100,000). The results showed an overall pattern of cancer similar to that reported according to cancer registration but the household survey results were consistently higher than those of the cancer registration by a margin of approximately 20- 30% with respect to incident cancer and about 70 % with respect to cancer-specific mortality. Household surveys on cancer, while costly and time consuming, are a very useful additional source of information on cancer at the population level. They can be performed for specific purposes with effective resource mobilization.

• 디지털융복합연구
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• 제11권1호
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• pp.225-236
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• 2013

음성인식 기술은 단순한 단어 인식을 넘어 자연스럽게 발성한 연속 음성도 인식할 수 있는 수준으로 발전해 왔다. 아이폰에 탑재된 자연어 음성인식 처리 소프트웨어인 시리(Siri)가 2010년에 발표되면서, 음성인식에 대한 연구가 관심을 받고 있다. 한국어 음성 인식 소프트웨어들은 대부분 단어 위주의 인식 서비스로 구성 되어 있으며, 잡음처리 및 음성 에너지 조절 기능들이 부족해 만족할 만한 인식률을 보이지 못하고 있다. 또한 요구된 발성 규칙을 따르지 못한 음성 질의들은 아예 처리하지 못하고 있는 실정이다. 본 논문에서는 이러한 현실적 어려움을 개선할 수 있도록 다목적 전처리 프로세서를 제안하였다. 이 처리기는 음성인식 엔진에 독립적이며, 잡음 제거 기능, 규칙에 따르지 않은 음성 질의도 처리 할 수 있는 핵심어 추출 기능, 그 핵심어를 수식하는 전술부 및 그 해당 음성 질의로부터 수행하기를 원하는 후술부 까지도 추출할 수 있는 기능을 갖추도록 하였다. 실험을 통해, 잡음 제거 효과 평가, 핵심어 인식 성공률, 연속음 인식 성공률을 측정하여 제안한 방법의 타당성을 확인하였다.

• 한국지능시스템학회논문지
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• 제23권3호
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• pp.262-267
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• 2013

The recognition of human emotional state is one of the most important components for efficient human-human and human- computer interaction. In this paper, four emotions such as fear, disgust, joy, and neutral was a main problem of classifying emotion recognition and an approach of visual-stimuli for eliciting emotion based on physiological signals of skin conductance (SC), skin temperature (SKT), and blood volume pulse (BVP) was used to design the experiment. In order to reach the goal of solving this problem, half-against-half (HAH) multi-class support vector machine (SVM) with Gaussian radial basis function (RBF) kernel was proposed showing the effective techniques to improve the accuracy rate of emotion classification. The experimental results proved that the proposed was an efficient method for solving the emotion recognition problems with the accuracy rate of 90% of neutral, 86.67% of joy, 85% of disgust, and 80% of fear.

• 한국건축시공학회지
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• 제11권3호
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• pp.238-246
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• 2011

Choosing the best-performance materials is a crucial task for the successful completion of a project in the construction field. In general, the process of material selection is performed through the use of information by a highly experienced expert and the purchasing agent, without the assistance of logical decision-making techniques. For this reason, the construction field has considered various artificial intelligence (AI) techniques to support decision systems as their own selection method. This study proposes the application of a systematic and efficient support vector machine (SVM) model to select optimal exterior materials. The dataset of the study is 120 completed construction projects in South Korea. A total of 8 input determinants were identified and verified from the literature review and interviews with experts. Using data classification and normalization, these 120 sets were divided into 3 groups, and then 5 binary classification models were constructed in a one-against-all (OAA) multi classification method. The SVM model, based on the kernel radical basis function, yielded a prediction accuracy rate of 87.5%. This study indicates that the SVM model appears to be feasible as a decision support system for selecting an optimal construction method.

• 한국통신학회논문지
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• 제36권1A호
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• pp.8-18
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• 2011

발광 다이오드와 같은 광원을 이용하여 조명과 통신의 두가지 기능을 동시에 이용할 수 있는 가시광 무선 통신은 최근 초고속 개인용 무선 네트워크에서 각광을 받고 있다. 광원의 제한된 대역폭으로 인하여 무선 광채널에서 전송률을 향상시키는 것이 이슈로 대두되는 가운데, 본 논문에서는 전송률을 향상시키는 기법으로써 다중 입출력 무선 광채널에서 두 개의 데이터 스트림을 지원하기 위해 고유값 분해를 이용한 공간 다중화 시스템을 설계한다. 채널의 변화에 따라 적응적 변조 기법을 적용하여 주파수 효율을 높이기 위해 펄스 진폭 변조 기법을 이용한다. 본 논문에서는 세기 변조를 이용한 변조 기법의 세 가지 제한 조건인 비음수성, 총 광출력값, 비트 오류율에 대하여 주파수 효율성을 향상시키기 위해 광출력값, 오프셋값, 변조 크기를 적응적으로 할당하기 위한 기법을 이론적으로 제안한다. 모의 실험 결과를 통해 본 논문의 제안 기법이 각 데이터 스트림에 광출력값을 동일하게 할당하는 기법에 비해 성능 향상을 이룰 수 있다는 것을 보인다.

• 정보보호학회논문지
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• 제28권3호
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• pp.617-623
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• 2018

본 연구는 안드로이드 정적분석을 기반으로 추출된 AndroidManifest 권한 특징을 통해 악성코드를 탐지하고자 한다. 특징들은 AndroidManifest의 권한을 기반으로 분석에 대한 자원과 시간을 줄였다. 악성코드 탐지 모델은 1500개의 정상어플리케이션과 500개의 악성코드들을 학습한 SVM(support vector machine), NB(Naive Bayes), GBC(Gradient Boosting Classifier), Logistic Regression 모델로 구성하여 98%의 탐지율을 기록했다. 또한, 악성앱 패밀리 식별은 알고리즘 SVM과 GPC (Gaussian Process Classifier), GBC를 이용하여 multi-classifiers모델을 구현하였다. 학습된 패밀리 식별 머신러닝 모델은 악성코드패밀리를 92% 분류했다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권5호
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• pp.2484-2498
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• 2017

Various types of social media make the people share their personal experience in different ways. In some social networking sites. Some users post their reviews, some users can support these reviews with comments, and some users just rate the reviews as kind of support or not. Unfortunately, there is rare explicit negative comments towards other reviews. This means if there is a link between two users, it must be positive link. Apparently, the negative link is invisible in these social network. Or in other word, the negative links are redundant to positive links. In this work, we first discuss the feature extraction from social media data and propose new method to compute the distance between each pair of comments or reviews on social media. Then we investigate whether we can predict negative links via regression analysis when only positive links are manifested from social media data. In particular, we provide a principled way to mathematically incorporate multi-facet data in a novel framework, Constructing Negative Links, CsNL to predict negative links for discovering the hidden information. Additionally, we investigate the ways of solution to general negative link predication problems with CsNL and its extension. Experiments are performed on real-world data and results show that negative links is predictable with multi-facet of social media data by the proposed framework CsNL. Essentially, high prediction accuracy suggests that negative links are redundant to positive links. Further experiments are performed to evaluate coefficients on different kernels. The results show that user generated content dominates the prediction performance of CsNL.