• Title/Summary/Keyword: Cognitive complexity

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Adaptive Algorithms for Bayesian Spectrum Sensing Based on Markov Model

  • Peng, Shengliang;Gao, Renyang;Zheng, Weibin;Lei, Kejun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3095-3111
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    • 2018
  • Spectrum sensing (SS) is one of the fundamental tasks for cognitive radio. In SS, decisions can be made via comparing the test statistics with a threshold. Conventional adaptive algorithms for SS usually adjust their thresholds according to the radio environment. This paper concentrates on the issue of adaptive SS whose threshold is adjusted based on the Markovian behavior of primary user (PU). Moreover, Bayesian cost is adopted as the performance metric to achieve a trade-off between false alarm and missed detection probabilities. Two novel adaptive algorithms, including Markov Bayesian energy detection (MBED) algorithm and IMBED (improved MBED) algorithm, are proposed. Both algorithms model the behavior of PU as a two-state Markov process, with which their thresholds are adaptively adjusted according to the detection results at previous slots. Compared with the existing Bayesian energy detection (BED) algorithm, MBED algorithm can achieve lower Bayesian cost, especially in high signal-to-noise ratio (SNR) regime. Furthermore, it has the advantage of low computational complexity. IMBED algorithm is proposed to alleviate the side effects of detection errors at previous slots. It can reduce Bayesian cost more significantly and in a wider SNR region. Simulation results are provided to illustrate the effectiveness and efficiencies of both algorithms.

Visual Landscape Plan for Shinan Province with Ecological Landscape Resources (생태경관자원 활용을 고려한 신안군 경관기본계획)

  • Joo, Shin-Ha;Yun, Hui-Jae
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.12 no.1
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    • pp.32-43
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    • 2009
  • The purpose of this study is to suggest the visual landscape plan for Shinan province with ecological landscape resources, which is comprised of more than 1,000 islands. The plan was done by the order of image plan, landscape structure plan and detained landscape plan. The image of Shinan province was elicited as 'nature', 'complexity' and 'connectivity', by the aspects of planning, cognitive and strategic sides. The landscape zones are planned, such as leisure zone, rural & marine ecological zone and marine tourism zone, and the landscape axes are also set, such as marine axis, ecological axis and circular axis. Especially to conserve the ecological resources, some conservation zones are proposed and design guidelines for each landscape type are also provided, which are not commonly included in the urban landscape plan. Consequently, the landscape plan and ecological environmental plan were complementary to each other. In the detailed landscape plan, more specific plans and design guidelines are suggested for coastal scenery, village and forest scenery, historical and cultural landscape management and promotion. To improve the visual landscape in terms of planning and administrative aspects, the visual landscape plan has become increasingly important for the local governments. The establishment of visual landscape plan may hopefully help to make Shinan province more beautiful and attractive. The landscape plan and ecological environment plan should be integrated, and the further discussion and research are necessary.

Development of Driver's Safety/Danger Status Cognitive Assistance System Based on Deep Learning (딥러닝 기반의 운전자의 안전/위험 상태 인지 시스템 개발)

  • Miao, Xu;Lee, Hyun-Soon;Kang, Bo-Yeong
    • The Journal of Korea Robotics Society
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    • v.13 no.1
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    • pp.38-44
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    • 2018
  • In this paper, we propose Intelligent Driver Assistance System (I-DAS) for driver safety. The proposed system recognizes safety and danger status by analyzing blind spots that the driver cannot see because of a large angle of head movement from the front. Most studies use image pre-processing such as face detection for collecting information about the driver's head movement. This not only increases the computational complexity of the system, but also decreases the accuracy of the recognition because the image processing system dose not use the entire image of the driver's upper body while seated on the driver's seat and when the head moves at a large angle from the front. The proposed system uses a convolutional neural network to replace the face detection system and uses the entire image of the driver's upper body. Therefore, high accuracy can be maintained even when the driver performs head movement at a large angle from the frontal gaze position without image pre-processing. Experimental result shows that the proposed system can accurately recognize the dangerous conditions in the blind zone during operation and performs with 95% accuracy of recognition for five drivers.

Two-Dimensional POMDP-Based Opportunistic Spectrum Access in Time-Varying Environment with Fading Channels

  • Wang, Yumeng;Xu, Yuhua;Shen, Liang;Xu, Chenglong;Cheng, Yunpeng
    • Journal of Communications and Networks
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    • v.16 no.2
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    • pp.217-226
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    • 2014
  • In this research, we study the problem of opportunistic spectrum access (OSA) in a time-varying environment with fading channels, where the channel state is characterized by both channel quality and the occupancy of primary users (PUs). First, a finite-state Markov channel model is introduced to represent a fading channel. Second, by probing channel quality and exploring the activities of PUs jointly, a two-dimensional partially observable Markov decision process framework is proposed for OSA. In addition, a greedy strategy is designed, where a secondary user selects a channel that has the best-expected data transmission rate to maximize the instantaneous reward in the current slot. Compared with the optimal strategy that considers future reward, the greedy strategy brings low complexity and relatively ideal performance. Meanwhile, the spectrum sensing error that causes the collision between a PU and a secondary user (SU) is also discussed. Furthermore, we analyze the multiuser situation in which the proposed single-user strategy is adopted by every SU compared with the previous one. By observing the simulation results, the proposed strategy attains a larger throughput than the previous works under various parameter configurations.

A study on the deconstruction shown in the 21st century fashion decentering phenomenon - Focused on visual beauty and wearable comfort of the clothing - (21세기 패션의 탈중심화 현상에 나타난 해체성에 관한 연구 - 의복의 외형미와 착용미를 중심으로 -)

  • Chung, Sehui;Kim, Yonson
    • The Research Journal of the Costume Culture
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    • v.23 no.1
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    • pp.145-160
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    • 2015
  • The purpose of this study is to review the concept and thinking structure of deconstruction theoretically and thereupon, analyze the visual beauty and wearable comfort of the clothing and further, discuss the aesthetic characteristics and values of the decentering phenomenon in the 21st century fashion. Deconstruction provides for an cognitive framework whereby we could comprehensively review the difficult-to-understand and imprudent creativity unravelling in the name of the post-modernism as well as the ambiguous visual beauty and wearable comfort of our contemporary fashion. In particular, deconstruction refuses such concepts involving the relationship between the conventional clothing and its components as order, symmetry, balance, harmony, perfection and simplicity and instead, attaches some sense of value to such relatively inferior concepts as disorder, asymmetry, unbalance, disharmony, imperfection and complexity, and thus, reflects them in the modes of aesthetic representations to create new aesthetics and expand the expressive potential.

Linear/Non-Linear Tools and Their Applications to Sleep EEG : Spectral, Detrended Fluctuation, and Synchrony Analyses (컴퓨터를 이용한 수면 뇌파 분석 : 스펙트럼, 비경향 변동, 동기화 분석 예시)

  • Kim, Jong-Won
    • Sleep Medicine and Psychophysiology
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    • v.15 no.1
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    • pp.5-11
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    • 2008
  • Sleep is an essential process maintaining the life cycle of the human. In parallel with physiological, cognitive, subjective, and behavioral changes that take place during the sleep, there are remarkable changes in the electroencephalogram (EEG) that reflect the underlying electro-physiological activity of the brain. However, analyzing EEG and relating the results to clinical observations is often very hard due to the complexity and a huge data amount. In this article, I introduce several linear and non-linear tools, developed to analyze a huge time series data in many scientific researches, and apply them to EEG to characterize various sleep states. In particular, the spectral analysis, detrended fluctuation analysis (DFA), and synchrony analysis are administered to EEG recorded during nocturnal polysomnography (NPSG) processes and daytime multiple sleep latency tests (MSLT). I report that 1) sleep stages could be differentiated by the spectral analysis and the DFA ; 2) the gradual transition from Wake to Sleep during the sleep onset could be illustrated by the spectral analysis and the DFA ; 3) electrophysiological properties of narcolepsy could be characterized by the DFA ; 4) hypnic jerks (sleep starts) could be quantified by the synchrony analysis.

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Robust Image Watermarking via Perceptual Structural Regularity-based JND Model

  • Wang, Chunxing;Xu, Meiling;Wan, Wenbo;Wang, Jian;Meng, Lili;Li, Jing;Sun, Jiande
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.1080-1099
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    • 2019
  • A better tradeoff between robustness and invisibility will be realized by using the just noticeable (JND) model into the quantization-based watermarking scheme. The JND model is usually used to describe the perception characteristics of human visual systems (HVS). According to the research of cognitive science, HVS can adaptively extract the structure features of an image. However, the existing JND models in the watermarking scheme do not consider the structure features. Therefore, a novel JND model is proposed, which includes three aspects: contrast sensitivity function, luminance adaptation, and contrast masking (CM). In this model, the CM effect is modeled by analyzing the direction features and texture complexity, which meets the human visual perception characteristics and matches well with the spread transform dither modulation (STDM) watermarking framework by employing a new method to measure edge intensity. Compared with the other existing JND models, the proposed JND model based on structural regularity is more efficient and applicable in the STDM watermarking scheme. In terms of the experimental results, the proposed scheme performs better than the other watermarking scheme based on the existing JND models.

Structural Equation Modeling on Clinical Decision Making Ability of Nurses (간호사의 임상의사결정능력 구조모형)

  • Park, Min Kyoung;Kim, Soukyoung
    • Journal of Korean Academy of Nursing
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    • v.49 no.5
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    • pp.601-612
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    • 2019
  • Purpose: The purpose of this study was to construct and test a hypothetical model of clinical decision-making ability of nurses based on the Decision Making Process model and the Cognitive Continuum theory. Methods: The data were collected from nurses working at 11 hospitals in Busan, Daejeon, and South Gyeongsang Province from June 30 to August 1, 2017. Finally, the data from 323 nurses were analyzed. Results: The goodness-of-fit of the final model was at a good level ($x^2/df=2.46$, GFI=.87, AGFI=.84, IFI=.90, CFI=.90, SRMR=.07, RMSEA=.07) and 6 out of 10 paths of the model were supported. The clinical decision-making ability was both directly and indirectly affected by task complexity and indirectly affected by experiences, autonomy, and work environment. Specifically, it was strongly directly affected by analytical competency but was insignificantly affected by intuitive competency. These variables accounted for 66.0% of clinical decision-making ability. Conclusion: The nurses' clinical decision-making ability can be improved by improving their analytical competency. Therefore, it is necessary to organize nursing work, create a supportive work environment, and develop and implement various education programs.

Development of Mathematical Task Analytic Framework: Proactive and Reactive Features

  • Sheunghyun, Yeo;Jung, Colen;Na Young, Kwon;Hoyun, Cho;Jinho, Kim;Woong, Lim
    • Research in Mathematical Education
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    • v.25 no.4
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    • pp.285-309
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    • 2022
  • A large body of previous studies investigated mathematical tasks by analyzing the design process prior to lessons or textbooks. While researchers have revealed the significant roles of mathematical tasks within written curricular, there has been a call for studies about how mathematical tasks are implemented or what is experienced and learned by students as enacted curriculum. This article proposes a mathematical task analytic framework based on a holistic definition of tasks encompassing both written tasks and the process of task enactment. We synthesized the features of the mathematical tasks and developed a task analytic framework with multiple dimensions: breadth, depth, bridging, openness, and interaction. We also applied the scoring rubric to analyze three multiplication tasks to illustrate the framework by its five dimensions. We illustrate how a series of tasks are analyzed through the framework when students are engaged in multiplicative thinking. The framework can provide important information about the qualities of planned tasks for mathematics instruction (proactive) and the qualities of implemented tasks during instruction (reactive). This framework will be beneficial for curriculum designers to design rich tasks with more careful consideration of how each feature of the tasks would be attained and for teachers to transform mathematical tasks with the provision of meaningful learning activities into implementation.

Current Status, Development Trends and Implications of Digital Therapeutics (DTx) (디지털 치료기기의 현황 및 개발 동향과 시사점)

  • S.H. Lee;M.H. Bae
    • Electronics and Telecommunications Trends
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    • v.39 no.4
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    • pp.73-81
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    • 2024
  • As the demand for a healthy life increases and the use of information technology expands, interest in digital healthcare has increased. Among the digital healthcare technologies, digital therapeutics (DTx), which are capable of disease prevention, management, and treatment rather than simple healthcare, are expected to play a key role in future healthcare services. As interest in untact remote treatment that can minimize the risk of viral infection has rapidly increased since the spread of COVID-19, the application of DTx has received much attention because it can partially replace face-to-face treatment for mental illnesses, chronic diseases, and other diseases, reducing concerns about infection. In addition, because of the nature of software, DTx have lower toxicity and fewer side effects than existing treatments and do not require manufacturing, transportation, and storage like general medicines. Hence, they can be supplied in large quantities at low cost and have the advantage of lowering medical costs. However, despite these advantages, it has been pointed out that there are difficulties in investment and universal use because of the complexity of pricing and malpractice compensation. In other words, if it is difficult to prove and measure the improvements in disease management and treatment using DTx and it takes a considerable amount of time and money to do so, it will be difficult to attract investment from stakeholders such as medical providers and pharmaceutical companies. In this paper, we examine the domestic and global application status and development trends of DTx and determine the relevant implications.