• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.316-322
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• 2014

A movie recommendation system is proposed to learn a preference model of a viewer by using multimodal features of a video content and their evoked implicit responses of the viewer in synchronized manner. In this system, facial expression, body posture, and physiological signals are measured to estimate the affective states of the viewer, in accordance with the stimuli consisting of low-level and affective features from video, audio, and text streams. Experimental results show that it is possible to predict arousal response, which is measured by electrodermal activity, of a viewer from auditory and text features in a video stimuli, for estimating interestingness on the video.

• Korean Journal of Cognitive Science
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• v.14 no.1
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• pp.41-50
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• 2003

We tested the capability of the pleasure and arousal dimension-based facial expression synthesis system and proposed the most effective interface for it. First, we tried to confirm the adequateness of the dimensional model as a basic structure of the internal states for the system. Fer it, subjects compared the 17 facial expressions on the two axes. The results validated the fundamental hypothesis of the system. Second, we chose 21 representative expressions from the system to test its performance and had subjects rate their similarities. We analyzed these data using multidimensional scaling methods and these results verified the system's reliability. Third, we compared the efficiencies of two interfaces -coordinate values and slide bars- to find the most suitable interface for the system. Subjects synthesise 25 facial expressions with each interface of it. The results showed that the visualization of two dimensional values into Cartesian coordinate is more stable as an input display of facial expression synthesis system based on dimensions.

• Korean Journal of Cognitive Science
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• v.21 no.4
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• pp.459-480
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• 2010

A dialogue system includes various morphological analyses for recognizing a user's intention from the user's utterances. However, a user can represent various intentions via emotional states in addition to morphological expressions. Thus, a user's emotion recognition can analyze a user's intention in various manners. This paper presents a new method to automatically recognize a user's emotion for a dialogue system. For general emotions, we define nine categories using a psychological approach. For an optimal feature set, we organize a combination of sentential, a priori, and context features. Then, we employ a support vector machine (SVM) that has been widely used in various learning tasks to automatically classify a user's emotions. The experiment results show that our method has a 62.8% F-measure, 15% higher than the reference system.

• Journal of the Korean association of regional geographers
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• v.11 no.5
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• pp.474-487
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• 2005

This paper aims to provide empirical evidence required to describe the level of achievement by analyzing students' item response in NAEP implemented in the United States in 2001. The geography assessment in the NAEP is aimed to test students of 4th, 8th, and 12th grades, and consists of content dimension and cognitive dimension, The former includes 'space and place' 'environment and society' and 'spatial dynamics and connections,' and the latter includes 'knowing' 'understanding' and 'applying,' The level of achievement is defined as three levels for each grade: Basic, Proficient, and Advanced. In this paper, descriptions of achievement is derived inductively from an analysis of student's responses to the items which were selected by using item-mapping method. As a result, there is a great difference between the level of achievement derived empirically from students' response and the level of achievement designed principally suggested by the expert committee. The former could have a contribution to the improvement in geography curriculum.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.641-646
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• 2011

In this paper, we investigate a power control problem which is very critical in underlay-based spectrum sharing systems. Although an underlay-based spectrum sharing system is more efficient compared to an overlay-based spectrum sharing system in terms of spectral utilization, some practical problems obstruct its commercialization. One of them is a real-time-based power adaptation of secondary transmitters. In the underlay-based spectrum sharing system, it is essential to adapt secondary user's transmit power to interference channel states to secure primary users' communication. Thus, we propose a practical power control scheme for secondary transmitters. The feedback overhead of our proposed scheme is insignificant because it requires one-bit signaling, while the optimal power control scheme requires the perfect information of channel states. In addition, the proposed scheme is robust to feedback delay. We compare the performance of the optimal and proposed schemes in terms of primary user's outage probability and secondary user's throughput. Our simulation results show that the proposed scheme is almost optimal in terms of both primary user's outage probability and secondary user's throughput when the secondary user's transmit power is low. As the secondary user's transmit power increases, the primary user's outage probability of the proposed scheme is degraded compared with the optimal scheme while the secondary user's throughput still approaches that of the optimal scheme. If the feedback delay is considered, however, the proposed scheme approaches the optimal scheme in terms of both the primary user's outage probability and secondary user's throughput regardless of the secondary user's transmit power.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.11
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• pp.59-68
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• 2010

In this paper, we present a new method to complete Dynamic Spectrum Access by modifying the reward function. Partially Observable Markov Decision Process (POMDP) is an eligible algorithm to predict the upcoming spectrum opportunity. In POMDP, Reward function is the last portion and very important for prediction. However, the Reward function has only two states (Busy and Idle). When collision happens in the channel, reward function indicates busy state which is responsible for the throughput decreasing of secondary user. In this paper, we focus the difference between busy and collision state. We have proposed a new algorithm for reward function that indicates an additional state of collision which brings better communication opportunity for secondary users. Secondary users properly utilize opportunities to access Primary User channels for efficient data transmission with the help of the new reward function. We have derived mathematical belief vector of the new algorithm as well. Simulation results have corroborated the superior performance of improved reward function. The new algorithm has increased the throughput for secondary user in cognitive radio network.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.188-204
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• 2018

This study examined how early maternal language use was associated with school readiness at kindergarten entry among children of Asian or Hispanic immigrant mothers in the United States. Using a nationally representative sample from the Early Childhood Longitudinal Study-Birth Cohort (ECLS-B; $N{\approx}1,500$), this study estimates multivariate regression models to address each research question. This study finds generally advantages of maternal use of English and bilingualism for children's expressive language in both Asian and Hispanic groups and for children's pro-social behavior in the Asian group. It also finds that longer residency in the U.S. is associated with higher levels of approaches to learning for children of bilingual Asian mothers and lower levels of behavior problems for children of bilingual Hispanic mothers. Based on the findings, social work implications for the healthy development of young children of immigrants were discussed.

• Korean journal of communication and information
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• v.47
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• pp.96-119
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• 2009

Although there ate many studies on cross-cultural comparison of advertising appeals, very little is known about how receivers from different cultures process visual images in global advertising. The purpose of this study is to examine how cultural differences between East Asians and Westerners influence the cognitive process of visual images from standardized global advertising by employing the Nisbett's framework of holistic/analytic thought. Nisbett contends that East Asian tend to attend to the context and the relations between objects and contexts as holistic thinkers while Americans tend to see the worlds analytically. The results of a experimental study conducted using 80 subjects from Korea and the United States suggest that Korean participants are more likely to mention relatively peripheral, nonsalient, or background information than are American participants. Thus, this study support the Nisbett's notion that East Asians are more sensitive to contextual information than are Westerners and challenge the belief that standardized visual images are part of a "universal language".

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.276-284
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• 2020

This paper proposes a new convolutional neural network (CNN) based spectrum sensing technique for cognitive radio communications. The proposed technique determines the existence of the primary user (PU) by using energy detection without any prior knowledge of the PU's signal. In the proposed method, the received signal is high-rate sampled to sense the entire spectrum bands of interest. After that, fast Fourier transform (FFT) of the signal converts the time domain signal to frequency domain spectrum and by stacking those consecutive spectrums, a 2 dimensional signal is made. The 2 dimensional signal is cut by the sensing channel bandwidth and inputted to the CNN. The CNN determines the existence of the primary user. Since there are only two states (existence or non-existence), binary classification CNN is used. The performance of the proposed method is examined through computer simulation and indoor experiment. According to the results, the proposed method outperforms the conventional threshold-based method by over 2 dB.

• Education of Primary School Mathematics
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• v.27 no.3
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• pp.227-246
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• 2024

The purposes of this study were to analyze the levels of cognitive demand and questioning types in tasks of 'Data and Chance' presented in elementary mathematics textbooks in Korea, the United States, and Australia. The levels of cognitive demand of textbook tasks were analyzed according to the knowledge and process and thinking types required in the tasks. The tasks were also analyzed for questioning types, answer types, and response types. As a result, in terms of knowledge and process and thinking types in tasks, all three countries had something in common: the percentage of tasks requiring 'representation' and process was the highest, and the percentage of tasks requiring 'basic application of skill/concept' was also the highest. From a thinking types perspective, differences were found between textbook tasks in the three countries in graph and chance learning. The results of analyzing questioning types showed that in all three textbooks, the percentage of observational reasoning questions was highest, followed by the percentage of factual questions. The proportions and characteristics of the constructing questions included in the U.S. and Australian textbooks differed from those in the Korean textbooks. Based on these results, this study presents implications for constructing elementary mathematics textbook tasks in 'Data and Chance.'