• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.16-22
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• 2001

There is no doubt that agents play an increasingly predominant role in e-commerce, whether these are business-to-consumer or business-to-business applications. However most of the current e-commerce agents only support a single bid for a product at a fixed price. Although price is an important factor, it is not the only concern of both business and consumer. There is doubt as to whether such agents satisfv both parties. Negotiation on a variety of issues is needed in order to reach an agreement. In this paper, a computational agent negotiation(CAN) model is proposed to facilitate multiple-issue negotiation via an agent. The main contribution of the CAN model is it enables agent to participate actively in the negotiation with various feedback instead of simply an agreement or rejection.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.150-158
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• 2021

Intracranial hemorrhage (ICH) refers to acute bleeding inside the intracranial vault. Not only does this devastating disease record a very high mortality rate, but it can also cause serious chronic impairment of sensory, motor, and cognitive functions. Therefore, a prompt and professional diagnosis of the disease is highly critical. Noninvasive brain imaging data are essential for clinicians to efficiently diagnose the locus of brain lesion, volume of bleeding, and subsequent cortical damage, and to take clinical interventions. In particular, computed tomography (CT) images are used most often for the diagnosis of ICH. In order to diagnose ICH through CT images, not only medical specialists with a sufficient number of diagnosis experiences are required, but even when this condition is met, there are many cases where bleeding cannot be successfully detected due to factors such as low signal ratio and artifacts of the image itself. In addition, discrepancies between interpretations or even misinterpretations might exist causing critical clinical consequences. To resolve these clinical problems, we developed a diagnostic model predicting intracranial bleeding and its subtypes (intraparenchymal, intraventricular, subarachnoid, subdural, and epidural) by applying deep learning algorithms to CT images. We also constructed a visualization tool highlighting important regions in a CT image for predicting ICH. Specifically, 1) 27,758 CT brain images from RSNA were pre-processed to minimize the computational load. 2) Three different CNN-based models (ResNet, EfficientNet-B2, and EfficientNet-B7) were trained based on a training image data set. 3) Diagnosis performance of each of the three models was evaluated based on an independent test image data set: As a result of the model comparison, EfficientNet-B7's performance (classification accuracy = 91%) was a way greater than the other models. 4) Finally, based on the result of EfficientNet-B7, we visualized the lesions of internal bleeding using the Grad-CAM. Our research suggests that artificial intelligence-based diagnostic systems can help diagnose and treat brain diseases resolving various problems in clinical situations.

• Journal of Computational Design and Engineering
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• v.3 no.3
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• pp.250-265
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• 2016

Owing to our rapidly aging society, accessibility evaluation to enhance the ease and safety of access to indoor and outdoor environments for the elderly and disabled is increasing in importance. Accessibility must be assessed not only from the general standard aspect but also in terms of physical and cognitive friendliness for users of different ages, genders, and abilities. Meanwhile, human behavior simulation has been progressing in the areas of crowd behavior analysis and emergency evacuation planning. However, in human behavior simulation, environment models represent only "as-planned" situations. In addition, a pedestrian model cannot generate the detailed articulated movements of various people of different ages and genders in the simulation. Therefore, the final goal of this research was to develop a virtual accessibility evaluation by combining realistic human behavior simulation using a digital human model (DHM) with "as-is" environment models. To achieve this goal, we developed an algorithm for generating human-like DHM walking motions, adapting its strides, turning angles, and footprints to laser-scanned 3D as-is environments including slopes and stairs. The DHM motion was generated based only on a motion-capture (MoCap) data for flat walking. Our implementation constructed as-is 3D environment models from laser-scanned point clouds of real environments and enabled a DHM to walk autonomously in various environment models. The difference in joint angles between the DHM and MoCap data was evaluated. Demonstrations of our environment modeling and walking simulation in indoor and outdoor environments including corridors, slopes, and stairs are illustrated in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3095-3111
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• 2018

Spectrum sensing (SS) is one of the fundamental tasks for cognitive radio. In SS, decisions can be made via comparing the test statistics with a threshold. Conventional adaptive algorithms for SS usually adjust their thresholds according to the radio environment. This paper concentrates on the issue of adaptive SS whose threshold is adjusted based on the Markovian behavior of primary user (PU). Moreover, Bayesian cost is adopted as the performance metric to achieve a trade-off between false alarm and missed detection probabilities. Two novel adaptive algorithms, including Markov Bayesian energy detection (MBED) algorithm and IMBED (improved MBED) algorithm, are proposed. Both algorithms model the behavior of PU as a two-state Markov process, with which their thresholds are adaptively adjusted according to the detection results at previous slots. Compared with the existing Bayesian energy detection (BED) algorithm, MBED algorithm can achieve lower Bayesian cost, especially in high signal-to-noise ratio (SNR) regime. Furthermore, it has the advantage of low computational complexity. IMBED algorithm is proposed to alleviate the side effects of detection errors at previous slots. It can reduce Bayesian cost more significantly and in a wider SNR region. Simulation results are provided to illustrate the effectiveness and efficiencies of both algorithms.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.55-68
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• 2023

In recent years, the Television White Space (TVWS) has attracted the interest of many researchers due to its propagation characteristics obtainable between 470MHz and 790MHz spectrum bands. The plenty of unused channels in the TV spectrum allows the secondary users (SUs) to use the channels for broadband services especially in rural areas. However, when the number of SUs increases in the TVWS wireless network the aggregate interference also increases. Aggregate interferences are the combined harmful interferences that can include both co-channel and adjacent interferences. The aggregate interference on the side of Primary Users (PUs) has been extensively scrutinized. Therefore, resource allocation (power and spectrum) is crucial when designing the TVWS network to avoid interferences from Secondary Users (SUs) to PUs and among SUs themselves. This paper proposes a model to improve the resource allocation for reducing the aggregate interface among SUs for broadband services in rural areas. The proposed model uses joint power and spectrum hybrid Firefly algorithm (FA), Genetic algorithm (GA), and Particle Swarm Optimization algorithm (PSO) which is considered the Co-channel interference (CCI) and Adjacent Channel Interference (ACI). The algorithm is integrated with the admission control algorithm so that; there is a possibility to remove some of the SUs in the TVWS network whenever the SINR threshold for SUs and PU are not met. We considered the infeasible system whereby all SUs and PU may not be supported simultaneously. Therefore, we proposed a joint spectrum and power allocation with an admission control algorithm whose better complexity and performance than the ones which have been proposed in the existing algorithms in the literature. The performance of the proposed algorithm is compared using the metrics such as sum throughput, PU SINR, algorithm running time and SU SINR less than threshold and the results show that the PSOFAGA with ELGR admission control algorithm has best performance compared to GA, PSO, FA, and FAGAPSO algorithms.

• Korean Journal of Cognitive Science
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• v.15 no.4
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• pp.1-14
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• 2004

When two objects are tying in the same visual direction there occurs abrupt depth change between two objects, which is against the assumption of the computational model for stereopsis on the surfaces in a natural scene. For this reason, this stimulus configuration is popularly used in the studies for the effectiveness of the constraints employed in the computational model. Contrary to the results from two nails (or objects) tying in the same visual direction, the two different surfaces from random-dot stereogram (RDS) in the same situation can be seen simultaneously in the different depth. The seemingly contradictory results between two situations my reflect the different strategies imposed by binocular mechanism for each situation during binocular matching process. Otherwise, the surfaces tying in the same visual direction is not equivalent situation to two objects tying in the same visual direction with regards to matching process. In order to examine above possibilities, the stereoscopic depth of the surface was measured after manipulating the visual direction of the surface elements. The visual direction of each dot pair from different surfaces in RDS (in Experiment 1) or the visual direction of line (hawing rectangle with regard to that of the vertical line (in Experiment 2) was manipulated. The stereoscopic depth of the surface was found to be varied depending on visual direction of the surface elements in both RDS and line hawing stimulus. Similar to the results from two nails situation depth of the surface was greatly reduced when each surface element was tying in the same visual direction as that of the other surface element or the other object. These results suggest that binocular mechanism imposes no different strategy in resolving correspondence problem in both two objects and two surfaces situation. And the results were discussed in the context of usefulness of the constraints employed in the computational model for stereopsis.

• Korean Journal of Cognitive Science
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• v.28 no.2
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• pp.111-131
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• 2017

The connectionist model is one approach to studying language processing from a computational perspective. And building a representation in the connectionist model study is just as important as making the structure of the model in that it determines the level of learning and performance of the model. The connectionist model has been constructed in two different ways: localist representation and distributed representation. However, the localist representation used in the previous studies had limitations in that the unit of the output layer having a rare target activation value is inactivated, and the past distributed representation has the limitation of difficulty in confirming the result by the opacity of the displayed information. This has been a limitation of the overall connection model study. In this paper, we present a new method to induce distributed representation with local representation using abstraction of information, which is a feature of restricted Boltzmann machine, with respect to the limitation of such representation of the past. As a result, our proposed method effectively solves the problem of conventional representation by using the method of information compression and inverse transformation of distributed representation into local representation.

• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.1-10
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• 2020

According to the Fourth Industrial Revolution, SW education is emphasized around the world to educate student with new abilities. Following to these global trends, SW education has become mandatory in Korea's 2015 revised curriculum. However, Korean elementary SW education is focused on the use of block-based programming languages. In addition, the point of view of selecting goals and organizing content of SW Education, the affective domain is ignored and focused only on the cognitive and psychomotor domains. So, this study explored method of SW education using the concept of Team-Shared Mental Model for develop of community capacity and Python, which is textual programming language gaining popularity recently. As a result of performing the post test t-test on two groups with similar Team-Shared Mental Model formation, we found that it was effective in forming a Team-Shared Mental Model of the group applying the SW teaching method suggested in the study.

• Korean Journal of Cognitive Science
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• v.22 no.3
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• pp.299-326
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• 2011

The text such as stories, blogs, chat, message and reviews have the overall emotional flow. It can be classified to the text having similar emotional flow if we compare the similarity between texts, and it can be used such as recommendations and opinion collection. In this paper, we extract emotion terms from the text sequentially and analysis emotion terms in the pleasantness-unpleasantness and activation dimension in order to identify the emotional flow of the text. To analyze the 'dominant emotion' which is the overall emotional flow in the text, we add the time dimension as sequential flow of the text, and analyze the emotional flow in three dimensional space: pleasantness-unpleasantness, activation and time. Also, we suggested that a classification method to compute similarity of the emotional flow in the text using the Euclidean distance in three dimensional space. With the proposed method, we analyze the dominant emotion in korean modern short stories and classify them to similar dominant emotion.

• Journal of Educational Research in Mathematics
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• v.8 no.2
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• pp.651-662
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• 1998

Mathematics is means for making sense of one's experiential world and products of human activities. A usefulness of mathematics is derived from this features of mathematics. Keeping the meaning of situations during the mathematizing of situations. However, theories about the development of mathematical concepts have turned mainly to an understanding of invariants. The purpose of this study is to show the possibility of computer in representing situation and phenomena. First, we consider situated cognition theory for looking for the relation between various representation and situation in problem. The mathematical concepts or model involves situations, invariants, representations. Thus, we should involve the meaning of situations and translations among various representations in the process of mathematization. Second, we show how the process of computational mathematization can serve as window on relating situations and representations, among various representations. When using computer software such as ALGEBRA ANIMATION in mathematics classrooms, we identified two benifits First, computer software can reduce the cognitive burden for understanding the translation among various mathematical representations. Further, computer softwares is able to connect mathematical representations and concepts to directly situations or phenomena. We propose the case study for the effect of computer software on practical mathematics classrooms.