• Safety and Health at Work
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• v.12 no.3
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• pp.359-364
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• 2021

Aim: We aimed to examine the cross-sectional and longitudinal associations between sleep and work-related impaired cognitive and emotional functioning in police employees. Methods: This study included 410 participants (52% men) employed in a police district in Norway at baseline, of which 50% also participated in the study at 6 months later follow-up. The questionnaires included items measuring work schedule, sleep length, insomnia, as well as impaired cognitive and emotional functioning at work. Results: The results showed that insomnia was related to impaired work-related emotional functioning measured at baseline, and to impaired cognitive functioning measured at both baseline and follow-up. Sleep length and rotating shift work were not associated with future decline in cognitive or emotional functioning. Conclusion: Our study indicates that the relationship between insomnia and emotional functioning at work may be transient, whereas insomnia can be related to both immediate and future impaired cognitive functioning. Replication of the findings in larger samples is advised. The findings call for an emphasis on the prevention and treatment of sleep problems among police employees as a mean of maintaining and improving cognitive and emotional functioning at work, and thereby reducing the risk for impaired performance and negative health and safety outcomes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2128-2147
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• 2021

Cognitive radio systems are being implemented recently to tackle spectrum underutilization problems and aid efficient data traffic. Spectrum sensing is the crucial step in cognitive applications in which cognitive user detects the presence of primary user (PU) in a particular channel thereby switching to another channel for continuous transmission. In cognitive radio systems, the capacity to precisely identify the primary user's signal is essential to secondary user so as to use idle licensed spectrum. Based on the inherent capability, a new spectrum sensing technique is proposed in this paper to identify all types of primary user signals in a cognitive radio condition. Hence, a spectrum sensing algorithm using improved convolutional neural network and long short-term memory (CNN-LSTM) is presented. The principle used in our approach is simulated annealing that discovers reasonable number of neurons for each layer of a completely associated deep neural network to tackle the streamlining issue. The probability of detection is considered as the determining parameter to find the efficiency of the proposed algorithm. Experiments are carried under different signal to noise ratio to indicate better performance of the proposed algorithm. The PU signal will have an associated modulation format and hence identifying the presence of a modulation format itself establishes the presence of PU signal.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.353-360
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• 2014

In cognitive radio networks (CRNs), SU (secondary user)'s transmissions are frequently disrupted by PU (primary user)'s transmission. Therefore SU expereiences consecutive retransmission timeout and its exponential backoff, and subsequently, the TCP of SU does not proceed with the transmission even after the disruption is over or the SU succeeds to hold an idle channel. In order to solve this problem, we propose a cross-layer approach called TCP-Freeze-CR. Moreover we consider a practical scenario where either secondary transmitter (ST) or secondary receiver (SR) detects PU's transmission, which results in the need of spectrum synchronization mechanism. All of our proposals are implemented and verified with a real CRN testbed consisting of 6 software radios called USRP. The experimental results illustrate that standard TCP suffers from significant performance degradation and show that TCP-Freeze-CR greatly mitigates the degradation.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.251-255
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• 2011

In this paper, we investigate an adaptive cognitive radio (CR) scheme where a sensing duration and a detection threshold for spectrum sensing are adaptively determined according to the channel condition in a fading channel. We optimize the sensing duration and detection threshold of a secondary user to maximize the performance of the secondary user guaranteeing a primary user's secure communication. In addition, we analyze the effect of channel fading on the optimization of the sensing duration and detection threshold. Our numerical results show that the performance of the adaptive CR scheme can be drastically improved if a secondary user can take the advantage of channel information between primary and secondary users.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.117-134
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• 2004

This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.

• ETRI Journal
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• v.31 no.3
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• pp.263-270
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• 2009

This paper investigates linear soft combination schemes for cooperative spectrum sensing in cognitive radio networks. We propose two weight-setting strategies under different basic optimality criteria to improve the overall sensing performance in the network. The corresponding optimal weights are derived, which are determined by the noise power levels and the received primary user signal energies of multiple cooperative secondary users in the network. However, to obtain the instantaneous measurement of these noise power levels and primary user signal energies with high accuracy is extremely challenging. It can even be infeasible in practical implementations under a low signal-to-noise ratio regime. We therefore propose reference data matrices to scavenge the indispensable information of primary user signal energies and noise power levels for setting the proposed combining weights adaptively by keeping records of the most recent spectrum observations. Analyses and simulation results demonstrate that the proposed linear soft combination schemes outperform the conventional maximal ratio combination and equal gain combination schemes and yield significant performance improvements in spectrum sensing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1319-1335
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• 2017

This paper proposes an opportunistic reporting-based sensing-reporting-throughput optimization scheme that maximizes the spectral efficiency of secondary users (SUs) in cooperative cognitive radio networks with a soft combining rule. The performance of cooperative spectrum sensing depends on the sensing time, the reporting time of transmitting sensing results, and the fusion scheme. While longer sensing time and reporting time improve the sensing performance, this shortens the allowable data transmission time, which in turn degrades the spectral efficiency of SUs. The proposed scheme adopts an opportunistic reporting scheme to restrain the reporting overhead and it jointly controls the sensing-reporting overhead in order to increase the spectral efficiency of SUs. We show that there is a trade-off between the spectral efficiency of SUs and the overheads of cooperative spectrum sensing. The numerical results demonstrate that the proposed scheme significantly outperforms the conventional sensing-throughput optimization schemes when there are many SUs. Moreover, the numerical results show that the sensing-reporting time should be jointly optimized in order to maximize the spectral efficiency of SUs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1751-1768
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• 2011

Falls are one of the most concerned accidents for elderly people and often result in serious physical and psychological consequences. Many researchers have studied fall detection techniques in various domain, however none released to a commercial product satisfying user requirements. We present a systematic modeling and evaluating procedure for best classification performance and then do experiments for comparing the performance of six procedures to get a statistical classifier based wrist-type fall detector to prevent dangerous consequences from falls. Even though the wrist may be the most difficult measurement location on the body to discern a fall event, the proposed feature deduction process and fall classification procedures shows positive results by using data sets of fall and general activity as two classes.

• Speech Sciences
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• v.8 no.4
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• pp.119-129
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• 2001

Language is one aspect of cognition, along with attention and concentration, learning and memory, visuospatial abilities, and executive function. The purpose of this study was to determine the effect of language intervention by cognitive approach on language expressive performance in a patient with conduction aphasia. This study used several tasks such as Attention and concentration task, visual memory tasks, memory tasks, categorization, divergent thinking, self-monitoring and evaluate thinking. The effects of treatment were evaluated by periodic probing of both trained and untrained familiar words in three tasks; picture naming, answering to questions and telling stories. The results showed improvements both in trained and untrained words. Therefore, we concluded that expressive language performance of this aphasic patient is amenable to this intervention, and that cognitive therapy approach can be useful.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.1
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• pp.41-44
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• 2015

In cognitive radios, exponentially distributed idle period(EIP) is considered in this paper. In the EIP case, durations of idle periods are be limited and varied by primary traffic arrivals. Accordingly, we first analyze the idle period utilization which can be achieved by the slotted ALOHA in cognitive radio communications. The idle period utilization is a newly defined performance metric to measure the transmission performance of the secondary network as effective time durations utilized for successful secondary transmissions in an idle period. Then, the idle period utilization is maximized through controlling the data transmission time. All technical processes are mathematically analyzed and expressed as closed form solutions.