• International Journal of Naval Architecture and Ocean Engineering
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• 제11권2호
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• pp.782-795
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• 2019

Safety is always acritical focus of exploration of ocean resources, and it is well recognized that human factor is one of the major causes of accidents and breakdowns. Our research developed a dynamic human reliability assessment approach, Predicted Mean Vote-Cognitive Reliability and Error Analysis Method (PMV-CREAM), that is applicable to monitoring the cognitive reliability of oceanauts during deep-sea missions. Taking into account the difficult and variable operating environment of manned submersibles, this paper analyzed the cognitive actions of oceanauts during the various procedures required by deep-sea missions, and calculated the PMV index using human factors and dynamic environmental data. The Cognitive Failure Probabilities (CFP) were calculated using the extended CREAM approach. Finally, the CFP were corrected using the PMV index. This PMV-CREAM hybrid model can be utilized to avoid human error in deep-sea research, thereby preventing injury and loss of life during undersea work. This paper verified the method with "Jiaolong" manned submersible 7,000 m dive test. The"Jiaolong" oceanauts CR(Corrected CFP) is dynamic from 3.0615E-3 to 4.2948E-3, the CR caused by the environment is 1.2333E-3. The result shown the PMV-CREAM method could describe the dynamic human reliability of manned submersible caused by thermal environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2037-2051
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• 2012

Cognitive radio (CR) is envisioned as a promising paradigm of exploiting intelligence for enhancing efficiency of underutilized spectrum bands. In CR, the main concern is to reliably sense the presence of primary users (PUs) to attain protection against harmful interference caused by potential spectrum access of secondary users (SUs). In this paper, evolutionary algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA) are proposed to minimize the total sensing decision error at the common soft data fusion (SDF) centre of a structurally-centralized cognitive radio network (CRN). Using these techniques, evolutionary operations are invoked to optimize the weighting coefficients applied on the sensing measurement components received from multiple cooperative SUs. The proposed methods are compared with each other as well as with other conventional deterministic algorithms such as maximal ratio combining (MRC) and equal gain combining (EGC). Computer simulations confirm the superiority of the PSO-based scheme over the GA-based and other conventional MRC and EGC schemes in terms of detection performance. In addition, the PSO-based scheme also shows promising convergence performance as compared to the GA-based scheme. This makes PSO an adequate solution to meet real-time requirements.

• ETRI Journal
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• 제45권1호
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• pp.28-44
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• 2023

We propose short packet communication in an underlay cognitive radio network assisted by an intelligent reflecting surface (IRS) composed of multiple reconfigurable reflectors. This scheme, called the IRS protocol, operates in only one time slot (TS) using the IRS. The IRS adjusts its phases to give zero received cumulative phase at the secondary destination, thereby enhancing the end-to-end signal-to-noise ratio. The transmitting power of the secondary source is optimized to simultaneously satisfy the multi-interference constraints, hardware limitations, and performance improvement. Simulation and analysis results of the average block error rates (BLERs) show that the performance can be enhanced by installing more reconfigurable reflectors, increasing the blocklength, lowering the number of required primary receivers, or sending fewer information bits. Moreover, the proposed IRS protocol always outperforms underlay relaying protocols using two TSs for data transmission, and achieves the best average BLER at identical transmission distances between the secondary source and secondary destination. The theoretical analyses are confirmed by Monte Carlo simulations.

• Journal of Information Processing Systems
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• 제12권2호
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• pp.295-309
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• 2016

Spectrum sensing is an essential function that enables cognitive radio technology to explore spectral holes and resourcefully access them without any harmful interference to the licenses user. Spectrum sensing done by a single node is highly affected by fading and shadowing. Thus, to overcome this, cooperative spectrum sensing was introduced. Currently, the advancements in multiple antennas have given a new dimension to cognitive radio research. In this paper, we propose a multiple energy detector for cooperative spectrum sensing schemes based on the evidence theory. Also, we propose a reporting mechanism for multiple energy detectors. With our proposed system, we show that a multiple energy detector using a cooperative spectrum sensing scheme based on evidence theory increases the reliability of the system, which ultimately increases the spectrum sensing and reduces the reporting time. Also in simulation results, we show the probability of error for the proposed system. Our simulation results show that our proposed system outperforms the conventional energy detector system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.5015-5027
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• 2015

Transceiver optimization in multiple input multiple output (MIMO) cognitive systems is studied in this paper. The joint transceiver beamformer design is introduced to minimize the transmit power at secondary base station (SBS) while simultaneously controlling the interference to primary users (PUs) and satisfying the secondary users (SUs) signal-to-interference-plus-noise ratio (SINR) based on the convex optimization method. Due to the limited cooperation between SBS and PUs, the channel state information (CSI) usually cannot be obtained perfectly at the SBS in cognitive system. In this study, both perfect and imperfect CSI scenarios are considered in the beamformer design, and the proposed method is robust to CSI error. Numerical results validate the effectiveness of the proposed algorithm.

• 방송과미디어
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• 제11권1호
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• pp.78-85
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• 2006

Cognitive radio is a paradigm for wireless communication in which either network of wireless node itself changes particular transmission or reception parameters to execute its tasks efficiently without interfering with the licensed users. This paper represents a performance of the cognitive radio technology on dual polarized MIMO system using six-port receiver. Six-port technology is well known direct conversion receiver. In this paper, a six-port phase discriminator based polarization signal separation is shown. That is, the SER(Symbol Error Rate) performance is improved using polarization separator and simple receiver architecture is proposed applying six-port receiver. The six-port technology has priority to adapt changeable frequency system and variable environments for cognitive radio. In general, dual polarized MIMO system has good capacity and quality using polarization separator [1].

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권6호
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• pp.1379-1397
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• 2013

We consider a system where a licensed radio spectrum is shared by multiple primary users(PUs) and secondary users(SUs). As the spectrum of interest is licensed to primary network, power and channel allocation must be carried out within the cognitive radio network so that no excessive interference is caused to PUs. For this system, we study the joint beamforming and power allocation problem via game theory in this paper. The problem is formulated as a non-cooperative beamforming and power allocation game, subject to the interference constraints of PUs as well as the peak transmission power constraints of SUs. We design a joint beamforming and power allocation algorithm for maximizing the total throughput of SUs, which is implemented by alternating iteration of minimum mean square error based decision feedback beamforming and a best response based iterative power allocation algorithm. Simulation results show that the algorithm has better performance than an existing algorithm and can converge to a locally optimal sum utility.

• Journal of electromagnetic engineering and science
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• 제11권4호
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• pp.250-256
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• 2011

This paper applies a compressed algorithm to improve the spectrum sensing performance of cognitive radio technology. At the fusion center, the recovery error in the analog to information converter (AIC) when reconstructing the transmit signal from the received time-discrete signal causes degradation of the detection performance. Therefore, we propose a subspace pursuit (SP) algorithm to reduce the recovery error and thereby enhance the detection performance. In this study, we employ a wide-band, low SNR, distributed compressed sensing regime to analyze and evaluate the proposed approach. Simulations are provided to demonstrate the performance of the proposed algorithm.

• 대한안전경영과학회지
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• 제9권2호
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• pp.9-17
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• 2007

There is no universally agreed classification of human error, nor is there one in prospect. Thus, a taxonomy is usually made for a specific purpose. To seek the types of human errors in the environment of man-machine interface under the railway industry, we develop a cognitive information processing model incorporating the human's mental states. Using the model, this study investigates the types of human errors about the railway workers. Thus, a survey is conducted for railway safety personnel-locomotive engineers, station employees, and train commanders- in Korean railway company. Through the survey that is designed to investigate four types of human errors from the Questionnaires composed of thirty Questions, we analyze the types of human errors related to railway safety according to affiliated offices, operation shifts, age, and working years. Finally, from the insights of the results some guidelines for the railway safety management are presented.

• Journal of Preventive Medicine and Public Health
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• 제52권5호
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• pp.333-343
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• 2019

Objectives: This study aimed to evaluate the association between dental implants and cognitive function in community-dwelling older adults. Methods: Data were collected from the baseline survey (2016-2017) of the Korean Frailty and Aging Cohort Study. The study sample comprised 1115 community-dwelling people aged 70 years to 84 years who had 0-19 natural teeth. Dental implants and natural teeth were identified by panoramic radiography, while the cognitive function was assessed by the Korean version of the Mini-Mental State Examination (MMSE-KC). The association between dental implants and cognitive function was analyzed by multiple linear regression. Sensitivity analysis was performed to test for potential bias. Results: The mean number of natural teeth in the study population was 9.50 (standard deviation [SD], 6.42), and the mean MMSE-KC score was 24.93 (SD, 3.55). In the simple univariate analysis, tooth replacement, age, sex, smoking status, alcohol consumption, body mass index, osteoporosis, number of natural teeth, periodontitis, chewing discomfort, tooth-brushing frequency, education level, monthly household income, participation in economic activity, living alone, and marital status had a significant impact on the association. After adjusting for confounders, the association between dental implants and cognitive function remained significant (B, 0.85; standard error, 0.40; p<0.05). Age, body mass index, periodontitis, tooth-brushing frequency, and education level were also significantly associated with cognitive function. The results of the sensitivity analyses were consistent with those of the primary analysis. Conclusions: Dental implants were associated with cognitive function in older adults living in the community. Dental implants as tooth replacements may play a role in preserving cognitive function.