• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권4호
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• pp.613-631
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• 2013

Cognitive radio (CR) is proposed as a key solution to improve spectral efficiency and overcome the spectrum scarcity. Spectrum sensing is an important task in each CR system with the aim of identifying the spectrum holes and using them for secondary user's (SU) communications. Several conventional methods for spectrum sensing have been proposed such as energy detection, matched filter detection, etc. However, the main limitation of these classical methods is that the CR network is not able to communicate with its own base station during the spectrum sensing period and thus a fraction of the available primary frame cannot be exploited for data transmission. The other limitation in conventional methods is that the SU data frames should be synchronized with the primary network data frames. To overcome the above limitations, here, we propose a spectrum sensing technique based on blind source separation (BSS) that does not need time synchronization between the primary network and the CR. Moreover, by using the proposed technique, the SU can maintain its transmission with the base station even during spectrum sensing and thus higher rates are achieved by the CR network. Simulation results indicate that the proposed method outperforms the accuracy of conventional BSS-based spectrum sensing techniques.

• 대한의용생체공학회:의공학회지
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• 제35권3호
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• pp.68-74
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• 2014

Recent research on mild cognitive impairment (MCI) has shown that cognitive and memory decline in this disease is accompanied by disruptive changes in the brain functional network. However, there have been no graph-theoretical studies using $^{11}C$-PIB PET data of the Alzheimer's Disease or mild cognitive impairment. In this study, we acquired $^{18}F$-FDG PET and $^{11}C$-PIB PET images of twenty-four normal aging control participants and thirty individuals with MCI from ADNI (Alzheimer's Disease Neuroimaging Initiative) database. Brain networks were constructed by thresholding binary correlation matrices using graph theoretical approaches. Both normal control and MCI group showed small-world property in $^{11}C$-PIB PET images as well as $^{18}F$-FDG PET images. $^{11}C$-PIB PET images showed significant difference between NC (normal control) and MCI over large range of sparsity values. This result will enable us to further analyze the brain using established graph-theoretical approaches for $^{11}C$-PIB PET images.

• ETRI Journal
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• 제38권6호
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• pp.1153-1162
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• 2016

This paper addresses the resource allocation (RA) problem in multi-cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered-such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP-hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub-gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권7호
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• pp.1533-1546
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• 2013

Wireless multicast is considered as an effective transmission mode for the future mobile social contact services supported by Long Time Evolution (LTE). Though wireless multicast has an excellent resource efficiency, its performance suffers deterioration from the channel condition and wireless resource availability. Cognitive Radio (CR) and Device to Device (D2D) are two solutions to provide potential resource. However, resource allocation for cognitive wireless multicast based on D2D is still a great challenge for LTE social networks. In this paper, a joint sub-carriers and power allocation model based on D2D for general cognitive radio multicast (CR-D2D-MC) is proposed for Orthogonal Frequency-Division Multiplexing (OFDM) LTE systems. By opportunistically accessing the licensed spectrum, the maximized capacity for multiple cognitive multicast groups is achieved with the condition of the general scenario of imperfect spectrum sensing, the constrains of interference to primary users (PUs) and an upper-bound power of secondary users (SUs) acting as multicast source nodes. Furthermore, the fairness for multicast groups or unicast terminals is guaranteed by setting a lower-bound number of the subcarriers allocated to cognitive multicast groups. Lagrange duality algorithm is adopted to obtain the optimal solution to the proposed CR-D2D-MC model. The simulation results show that the proposed algorithm improves the performance of cognitive multicast groups and achieves a good balance between capacity and fairness.

• 대한인간공학회지
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• 제31권2호
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• pp.371-377
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• 2012

Objective: The aim of this study is to investigate effect of driver's cognitive distraction on driver's physiological state and driving performance, and then to determine parameters appropriate for detecting the cognitive distraction. Background: Driver distraction is a major cause of traffic accidents and poses a serious threat to traffic safety due to ever increasing use of in-vehicle information systems and mobile phones during driving. Cognitive distraction, among four different types of distractions, prevents a driver from processing traffic information correctly and adapting to change in surround vehicle behavior in time. However, the cognitive distraction is more difficult to detect because it normally does not involve significant change in driver behavior. Method: A full-scale driving simulator was used to create virtual driving environment and situations. Participants in the experiment drove the driving simulator in three different conditions: attentive driving with no secondary task, driving and conducting secondary task of adding numbers, and driving and conducting secondary task of conversing with an experimenter. Parameters related with driver's physiological state and driving performance were measured and analyzed for their change. Results: The experiment results show that driver's cognitive distraction, induced by secondary task of addition and conversation during driving, increased driver's cognitive workload, and indeed brought change in driver's physiological state and degraded driving performance. Conclusion: The galvanic skin response, pupil size, steering reversal rate, and driver reaction time are shown to be statistically significant for detecting cognitive distraction. The appropriate combination of these parameters will be used to detect the cognitive distraction and estimate risk of traffic accidents in real-time for a driver distraction warning system.

• 한국화재소방학회논문지
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• 제32권2호
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• pp.92-101
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• 2018

본 연구는 외상사건에 반복적으로 노출되는 소방공무원들의 외상 후 스트레스가 자살에 미치는 영향을 살펴보고, 외상 후 스트레스와 자살생각과의 관계에서 인지적 정서조절의 조절효과를 검증하고자 하였다. 이를 위해 외상 후 스트레스, 한국판 자살생각, 인지적 정서조절을 측정하였다. 연구결과는 다음과 같다. 첫째, 외상 후 스트레스, 적응적 인지적 정서조절, 부적응적 인지적 정서조절은 상관관계가 있음이 확인되었다. 둘째, 외상 후 스트레스와 자살생각과의 관계에서 인지적 정서조절의 조절효과를 알아보기 위해 위계적 회귀분석을 실시한 결과, 적응적 인지적 정서조절은 낮은 외상 후 스트레스 집단에서 조절효과를 가졌고, 부적응적 인지적 정서조절은 높은 외상 후 스트레스 집단에서 조절효과를 갖는 것으로 확인되었다. 이러한 결과를 바탕으로 본 연구에서는 학문적, 임상적 시사점과 함께 후속 연구의 필요성에 대해 논의하였다.

• 한국의학물리학회지:의학물리
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• 제21권1호
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• pp.42-51
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• 2010

뇌 기능 연구 분야에서는 MRI, PET, MEG 영상 시스템 등을 이용한 인지기능에 대한 정량적 평가 연구가 계속적으로 이루어 지고 있다. 최근에는 컴퓨터 기술을 응용하여 인지 기능의 정량적 분석을 효과적으로 하고자 시도되고 있다. 본 연구에서는 터치 스크린을 이용하여 인지 기능의 정량적 평가를 할 수 있는 소프트웨어 패키지를 구현하였다. 여기서 구현된 내용은 집중력, 숫자 기억력, 조합 기억력, 위상 기억력, 시각 및 근육 반응, 청각 반응 등으로 되어 있다. 우리는 구현된 소프트웨어에 대하여 실험적 검증과정을 거치고자 20~59세까지의 연령 및 성별에 따른 80명을 대상으로 실험을 수행하였다. 남녀 모두 40세 이후의 연령에서 인지기능의 감쇄가 일어나는 결과를 정량적 획득하였다. 본 연구에서는 고가 장비인 영상 시스템뿐만 아니라 상대적으로 간소화된 소프트웨어를 이용하여서도 인지기능의 정량적 평가가 가능함을 보여주고 있다. 이러한 방법을 적용하여 다양한 그룹의 인지 기능의 정량적 평가 및 비교를 수행하는 데 비용과 시간을 줄일 수 있을 것으로 보인다.

• 한국전자파학회지:전자파기술
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• 제17권3호
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• pp.17-25
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• 2006

석유, 철강 등과 함께 주파수 자원은 정보화 사회에서 소중한 자산으로 사용이 한정되어 있는 유한자원이다. 새로운 서비스를 위해 새로 할당할 대역이 더 이상 남아 있지 않는 지금, 주파수 부족 현상은 광대역 멀티미디어 통신 서비스를 제공해야 하는 차세대 무선 통신 서비스를 실현함에 있어서 큰 걸림돌이 될 것으로 예상된다. 하지만 FCC의 보고에 따르면 할당된 주파수 대역이 효율적으로 사용되고 있지 않음을 확인할 수 있다 이러한 관찰은 주파수 부족 현상이 주파수 자원이 가지고 있는 유한성의 문제보다는 비효율적으로 운영되고 있는 주파수 관리 방식에 원인이 있다는 것을 말해준다. Cognitive Radio 기술은 이렇게 비효율적으로 사용되고 있는 지금의 상황을 해결해줄 수 있는 기술로 주목받고 있다. Cognitive Radio에 대한 많은 연구가 지금까지 진행되어 왔지만 아직까지 단일화된 정의나 구체적인 시나리오가 제시되지 않은 상태이다. 이에 따라 본 고에서는 Cognitive Radio 기술이 적용될 수 있는 구체적 시나리오를 파악하고자 주요 관점 별로 구체적인 시나리오를 제시하고 각 시나리오에 따라서 Cognitive Radio 기술이 어떠한 방식으로 주파수 사용 효율을 높일 수 있는 지와 이때 요구되는 핵심 기술들에 대해 논의한다.

• IEIE Transactions on Smart Processing and Computing
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• 제3권4호
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• pp.173-180
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• 2014

Random access protocols feature inherent sensing functionality and distributed coordination, making them suitable for cognitive radio communication environments, where secondary users must detect the white space of the primary spectrum and utilize the idle primary spectrum efficiently without centralized control. These characteristics have led to the adoption of carrier-sensing-multiple-access/collision-avoidance (CSMA/CA) in cognitive radio. This paper proposes a new analytical framework for evaluating the performance of a CSMA/CA protocol that considers the characteristics of idle periods based on the primary traffic behavior in cognitive radio systems. In particular, the CSMA/CA-based secondary network was analyzed in the terms of idle period utilization, which is the average effective data transmission time portion in an idle period. The use of the idle period was maximized by taking its statistical features into consideration.

• International journal of advanced smart convergence
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• 제12권2호
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• pp.17-24
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• 2023

Given the surge in the elderly population, and increasing in dementia cases, there is a growing interest in digital therapies that facilitate steady remote treatment. However, in the cognitive assessment of digital therapies through clinical trials, the absence of log data as an essential evaluation factor is a significant issue. To address this, we propose a solution of utilizing weighted derived variables based on high-importance variables' accuracy in log data utilization as an indirect cognitive assessment factor for digital therapies. We have validated the effectiveness of this approach using machine learning techniques such as XGBoost, LGBM, and CatBoost. Thus, we suggest the use of log data as a rapid and indirect cognitive evaluation factor for digital therapy users.