• Korean Journal of Adult Nursing
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• v.29 no.3
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• pp.266-277
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• 2017

Purpose: The purpose of this study was to design a mobile-application of a cognitive training program for people who have chemo-related cognitive complaints. Methods: The program was developed based on the network-based instructional system design proposed by Jung. The program consisted of several tasks centered on four cognitive domains: learning, memory, working memory, and attention. For memory learning, a target-image and all its elements (color, position, and number) were presented on the screen that had to be recognized among a number of distractor-figures. In working memory training, the previous learned target-figure according to the level of difficulty had to be remembered among many different figures. In attention training named "Find the same figure," two identical symbols in a grid-pattern filled with different images were presented on the screen, and these had to be simultaneously touched. In attention training named "Find the different figure," a different symbol in a grid pattern filled with same figures had to be selected. This program was developed to train for a minimum of 20 min/day, four days/week for six weeks. Results: This cognitive training revealed statistically significant improvement in subjective cognitive impairments (t=3.88, p=.006) at six weeks in eight cancer survivors. Conclusion: This cognitive training program is expected to offer individualized training opportunities for improving cognitive function and further research is needed to test the effect in various settings.

• Korean Journal of Cognitive Science
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• v.18 no.2
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• pp.179-191
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• 2007

In a goal-oriented dialogue, spoken' intentions can be represented by domain actions that consist of pairs of a speech art and a concept sequence. The domain action prediction of user's utterance is useful to correct some errors that occur in a speech recognition process, and the domain action prediction of system's utterance is useful to generate flexible responses. In this paper, we propose a model to predict a domain action of the next utterance using a neural network. The proposed model predicts the next domain action by using a dialogue history vector and a current domain action as inputs of the neural network. In the experiment, the proposed model showed the precision of 80.02% in speech act prediction and the precision of 82.09% in concept sequence prediction.

• Journal of information and communication convergence engineering
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• v.7 no.1
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• pp.7-12
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• 2009

The advanced computer network and Internet technology enables connectivity of computers through an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, making it vulnerable to previously unidentified attack patterns and variations in attack and increasing false negatives. Intrusion detection and prevention technologies are thus required. We proposed a network based hybrid Probe Intrusion Detection model using Fuzzy cognitive maps (PIDuF) that detects intrusion by DoS (DDoS and PDoS) attack detection using packet analysis. A DoS attack typically appears as a probe and SYN flooding attack. SYN flooding using FCM model captures and analyzes packet information to detect SYN flooding attacks. Using the result of decision module analysis, which used FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance evaluation, the "IDS Evaluation Data Set" created by MIT was used. From the simulation we obtained the max-average true positive rate of 97.064% and the max-average false negative rate of 2.936%. The true positive error rate of the PIDuF is similar to that of Bernhard's true positive error rate.

• The Journal of Information Systems
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• v.24 no.1
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• pp.147-168
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• 2015

Why people reduce or stop using social network services(SNS), which are regarded as a mean of relationship and communication, unlike the early trend? To explain the phenomenon, this study tries to predict psychological decision making process of users from perspectives of cognitive dissonance theory. From this perspective, this study attempted an integrative approach that reflected 'User's literacy' indicating the ability of individuals to use SNS, and 'negative mass media influence' such as media reports on side effects or the bad experiences of acquaintances, along with the 3 factors used in the SNS Prior research. This study conducted an empirical analysis by surveying 256 facebook users, and the major findings are as follows:- First, Social-overload, complexity, uncertainty and negative media influence are significantly affect dissonance on the use of SNS. Second, Dissonance on the use of SNS significantly affects the behavior that possibly reduces and limits the use of SNS. In other words, the users who have experienced psychological dissonance respond passively by avoiding the use of SNS to resolve the dissonance. Third, the moderating effect of User's literacy wasn't a significant. This study presents a clue to understand psychological decision making process of use of SNS and a guideline for establishing practical strategies. In addition, it is important to note that this study contributes to expansion of theoretical discussion about usage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3887-3907
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• 2015

This paper introduces a full duplex single secondary user multiple-input multiple-output (FD-SSU-MIMO) cognitive radio network, where secondary user (SU) opportunistically accesses the authorized spectrum unoccupied by primary user (PU) and transmits data based on FD-MIMO mode. Then we study the network achievable average sum-rate maximization problem under sum transmit power budget constraint at SU communication nodes. In order to solve the trade-off problem between SU's sensing time and data transmission time based on opportunistic spectrum access (OSA) and the power allocation problem based on FD-MIMO transmit mode, we propose a simple trisection algorithm to obtain the optimal sensing time and apply an alternating optimization (AO) algorithm to tackle the FD-MIMO based network achievable sum-rate maximization problem. Simulation results show that our proposed sensing time optimization and AO-based optimal power allocation strategies obtain a higher achievable average sum-rate than sequential convex approximations for matrix-variable programming (SCAMP)-based power allocation for the FD transmission mode, as well as equal power allocation for the half duplex (HD) transmission mode.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4664-4681
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• 2020

Modulation recognition (MR) plays a key role in cognitive radar, cognitive radio, and some other civilian and military fields. While existing methods can identify the signal modulation type by extracting the signal characteristics, the quality of feature extraction has a serious impact on the recognition results. In this paper, an end-to-end MR method based on long short-term memory (LSTM) and the gated recurrent unit (GRU) is put forward, which can directly predict the modulation type from a sampled signal. Additionally, the sliding window method is applied to fast-changing mixed-modulation signals for which the signal modulation type changes over time. The recognition accuracy on training datasets in different SNR ranges and the proportion of each modulation method in misclassified samples are analyzed, and it is found to be reasonable to select the evenly-distributed and full range of SNR data as the training data. With the improvement of the SNR, the recognition accuracy increases rapidly. When the length of the training dataset increases, the neural network recognition effect is better. The loss function value of the neural network decreases with the increase of the training dataset length, and then tends to be stable. Moreover, when the fast-changing period is less than 20ms, the error rate is as high as 50%. As the fast-changing period is increased to 30ms, the error rates of the GRU and LSTM neural networks are less than 5%.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.67-80
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• 2014

Spectrum sensing is vital for secondary unlicensed nodes to coexist and avoid interference with the primary licensed users in cognitive wireless networks. In this paper, we develop models for bounding interference levels from secondary network to the primary nodes within a spectrum sensing framework. Instead of classical stochastic approaches where Poisson point processes are used to model transmitters, we consider a more practical model which takes into account the medium access control regulations and where the secondary Poisson process is judiciously thinned in two phases to avoid interference with the secondary as well as the primary nodes. The resulting process will be a modified version of the Mat$\acute{e}$rn point process. For this model, we obtain bounds for the complementary cumulative distribution function of interference and present simulation results which show the developed analytical bounds are quite tight. Moreover, we use these bounds to find the operation regions of the secondary network such that the interference constraint is satisfied on receiving primary nodes. We then obtain theoretical results on the primary and secondary throughputs and find the throughput limits under the interference constraint.

• Korean Journal of Biological Psychiatry
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• v.25 no.1
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• pp.1-8
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• 2018

Insomnia is a common sleep-related symptom which occurs in many populations, however, the neural mechanism underlying insomnia is not yet known. The hyperarousal model explains the neural mechanism of insomnia to some extent, and the frontal cortex dysfunction has been known to be related to primary insomnia. In this review, we discuss studies that applied resting state and/or task-related functional magnetic resonance imaging to demonstrate the deficits/dysfunctions of functional activation and network in primary insomnia. Empirical evidence of the hyperarousal model and proposed relation between the frontal cortex and other brain regions in primary insomnia are examined. Reviewing these studies could provide critical insights regarding the pathophysiology, brain network and cerebral activation in insomnia and the development of novel methodologies for the diagnosis and treatment of insomnia.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1074-1086
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• 2015

We Relay-assisted cellular network architecture has been developed to cover cell-edge users and to improve capacity. However, the deployment of relay stations (RSs) in cellular networks may increase the total energy consumption. Though energy efficiency has become a major concern in cellular networks, little work has studied the energy efficiency of relay-assisted cellular networks by sleep scheduling. In this paper, a distributed base stations (BSs) sleep scheduling scheme in relay-assisted cellular networks is proposed. The goal is to maximize the energy efficiency under the spectral efficiency constraint. Firstly, whether the BSs should be sleeping or active is determined by the traffic profile. Then, the transmission powers of the active BSs are optimized within the game-theoretic framework, by using an interior-point method, so as to maximize the energy efficiency. Simulation results demonstrate that the effectiveness of the proposed scheme is superior to that turning on all the BSs without sleep scheduling.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.37-44
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• 2016

It is important that using of efficient radio resource because of deficiency spectrum problem, so that related to this problem many researches are have proceeded. To solve this problem, Cognitive Radio(CR) was suggested. The channels are allocated to the secondary users when the primary users don't use the channels, and unfairness of secondary users can be serious problem and channel quality of multichannel can be different due to the different traffic pattern of primary users. In this paper, we propose MAC prtocol both of the user's fairness and channel quality in CR networks. Simulation results show the comparison with CR MAC protocols.