• Korean Journal of Cognitive Science
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• v.11 no.3_4
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• pp.13-22
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• 2000

The present study examined the role of spatial attention in implicit memory for words when the word identity processing was not required. Spatial attention to the identity-irrelevant perceptual features of the words was manipulated by using a visual search task (Experiment 1) or a focused attention task (Experiment 2). In two e experiments. a significant priming effect was not found for the target words as well as for the distractor words. Implicit memory for words was not affected by spatial attention on the perceptual properties of the words. indicating that the word identity processing is required to produce priming.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• Clinical Psychopharmacology and Neuroscience
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• v.16 no.4
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• pp.481-488
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• 2018

Preliminary studies have claimed that short term fasting would negatively affect school performance and cognition. In contrast some other studies have reported not important decline in cognition and executive function as a result of fasting. Also limited attention was generally devoted to dietetic regimens, nutritional status and body weight. Yet neuroscience and neuro-cognitive aspects of acute hunger on the electroencephalogram and differences between obese and non-obese cases is not well understood. Hence, we decided to design and perform a case study in a more controlled situation similar to reality. Therefore, we performed several examinations including subjective tests (for eating status) and objective tests (cognitive tests such as Stroop effect and Sternberg search and electroencephalogram measures such as steady-state visual evoked potential and auditory steady-state responses) for an obese and a non-obese academic case before and after a simple breakfast. The results showed that the breakfast effects on the neuro-cognitive functions depend on either obesity status, nutritional status of the case or the type of cognitive task (visual or auditory). This paper would open a new insight to answer some important questions about the neuro-cognitive implications of fasting and feeding in obese and non-obese human cases.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.1295-1298
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• 2006

Influences of anti-reflection surface treatment, radius of curvature and ambient illuminance on legibility of reflective-type displays were studied. The results showed that legibility mainly depended on the surface treatment. Better surface treatment also produced less visual fatigue after the letter-search task

• Korean Journal of Computational Design and Engineering
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• v.18 no.3
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• pp.155-166
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• 2013

We present recent human-vehicle interaction (HVI) research conducted in the area of defense and military application. Research topics discussed in this paper include: training simulation for overland navigation tasks; expertise effects in overland navigation performance and scan patterns; pilot's perception and confidence on an overland navigation task; effects of UAV (Unmanned Aerial Vehicle) supervisory control on F-18 formation flight performance in a simulator environment; autonomy balancing in a manned-unmanned teaming (MUT) swarm attack, enabling visual detection of IED (Improvised Explosive Device) indicators through Perceptual Learning Assessment and Training; usability test on DaViTo (Data Visualization Tool); and modeling peripheral vision for moving target search and detection. Diverse and leading HVI study in the defense domain suggests future research direction in other HVI emerging areas such as automotive industry and aviation domain.

• Journal of the Ergonomics Society of Korea
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• v.27 no.4
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• pp.15-26
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• 2008

Recently, Internet Protocol TV technology has a latent power for searching information by using internet-connected interactive TV media. It is hard to browse and search web site conveniently since the visual and input devices are not sufficient for navigating through the websites. Zoomable user interface is a possible solution that may reduce users' task load and improve their performance. In this paper, we made three types of web browsers as scroll, physical zooming and semantic zooming type. Fifteen participants asked to do searching tasks and their task time, accuracy and subjective responses are recorded. In the result, though scroll type is evaluated more efficient than other types in task time and accuracy since participants are familiar with scroll type interface, semantic zooming type is highly rated in subjective responses such as perceived searching efficiency, satisfaction and joyfulness. This result implied semantic zooming is a possible solution which is improving user experience of searching websites using Internet Protocol TV.

• The Korean Journal of Nuclear Medicine
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• v.35 no.3
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• pp.142-151
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• 2001

Purpose: This study was performed to search the relatively specific brain regions related to the semantic processing of Korean and English words on the one hand and the regions common to both on the other. Materials and Methods: Regional cerebral blood flow associated with different semantic tasks was examined using $[^{15}O]H_2O$ positron omission tomography in 13 healthy volunteers. The tasks consisted of semantic tasks for Korean words, semantic tasks for English words and control tasks using simple pictures. The regions specific and common to each language were identified by the relevant subtraction analysis using statistical parametric mapping. Results: Common to the semantic processing of both words, the activation site was observed in the fusiform gyrus, particularly the left side. In addition, activation of the left inferior temporal gyrus was found only in the semantic processing of English words. The regions specific to Korean words were observed in multiple areas, including the right primary auditory cortex; whereas the regions specific to English words were limited to the right posterior visual area. Conclusion: Internal phonological process is engaged in performing the visual semantic task for Korean words of the high proficiency, whereas visual scanning plays an important role in performing the task for English words of the low proficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.173-182
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• 2005

In this paper, we propose a landmark recognition method which is irrelevant to the camera viewpoint on the navigation for localization. Features in previous research is variable to camera viewpoint, therefore due to the wealth of information, extraction of visual landmarks for positioning is not an easy task. The proposed method in this paper, has the three following stages; first, extraction of features, second, learning and recognition, third, matching. In the feature extraction stage, we set the interest areas of the image. where we extract the corner points. And then, we extract features more accurate and resistant to noise through statistical analysis of a small eigenvalue. In learning and recognition stage, we form robust feature models by testing whether the feature model consisted of five corner points is an invariant feature irrelevant to viewpoint. In the matching stage, we reduce time complexity and find correspondence accurately by matching method using similarity evaluation function and Graham search method. In the experiments, we compare and analyse the proposed method with existing methods by using various indoor images to demonstrate the superiority of the proposed methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1247-1254
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• 2009

The purpose of the present study was to compare and analyze the differential effects of in-vehicle electronic device usage types(searching for targeted destinations in navigational purpose, watching TV in entertain purpose, and dialing a cellular-phone in phone-usage purpose) on driver's front-to-rear-end collision avoidance behavior, and to find effective collision warning format for this behavior. The result indicated that (1) the drivers showed more impaired collision avoidance performances when they were asked to search the name of targeted destination than the other task requirements, and (2) auditory warning appeared to be most effective among the other types of warning. In particular, it was suggested that the "Visual-Only" collision warning could induce most undesirable result when the drivers were engaged in both visual and auditory information processing.