• Journal of the Korean Society for information Management
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• v.28 no.2
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• pp.159-175
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• 2011

The purposes of this study are to evaluate the navigability of three web-based mapping applications and to suggest how to improve the navigability of all web-based mapping applications. With these purposes, this study conducted a web-based survey congruent with a think aloud and systematic observation for individual participants, followed up by a focus group with all participants. Based on the findings, recommendations are proposed for web-based mapping applications that include a standard click and drag panning function in mapping applications, a scaled zooming option, increased text for icons and buttons, and other potential changes to computer hardware for increased navigability in these applications. By improving the navigability of web-based mapping applications, the learning time may be reduced for each application and the speed at which users' geographic information needs are met will be quicker.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.429-436
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• 2004

This paper proposes an independent component analyses(ICAs) of the fixed-point (FP) algorithm based on Newton and secant method by adding the kurtosis, respectively. The kurtosis is applied to cluster the analyzed components, and the FP algorithm is applied to get the fast analysis and superior performance irrelevant to learning parameters. The proposed ICAs have been applied to the problems for separating the 6-mixed signals of 500 samples and 10-mixed images of $512\times512$ pixels, respectively. The experimental results show that the proposed ICAs have always a fixed analysis sequence. The results can be solved the limit of conventional ICA without a kurtosis which has a variable sequence depending on the running of algorithm. Especially. the proposed ICA can be used for classifying and identifying the signals or the images. The results also show that the secant method has better the separation speed and performance than Newton method. And, the secant method gives relatively larger improvement degree as the problem size increases.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.468-475
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• 2014

The recommend system is getting more difficult real time recommend by lager preference data set, computing power and recommend algorithm. For this reason, recommend system is proceeding actively one's studies toward distribute processing method of large preference data set. This paper studied distribute processing method of large preference data set using hadoop distribute processing platform and mahout machine learning library. The recommend algorithm is used Co-occurrence Matrix similar to item Collaborative Filtering. The Co-occurrence Matrix can do distribute processing by many node of hadoop cluster, and it needs many computation scale but can reduce computation scale by distribute processing. This paper has simplified distribute processing of co-occurrence matrix by changes over from four stage to three stage. As a result, this paper can reduce mapreduce job and can generate recommend file. And it has a fast processing speed, and reduce map output data.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.408-416
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• 2017

This paper proposes a real-time side-rear vehicle detection algorithm that detects vehicles quickly and accurately in blind spot areas when driving. The proposed algorithm uses a cascade classifier created by AdaBoost Learning using the MCT (modified census transformation) feature vector. Using this classifier, the smaller the detection window, the faster the processing speed of the MCT classifier, and the larger the detection window, the greater the accuracy of the MCT classifier. By considering these characteristics, the proposed algorithm uses two classifiers with different detection window sizes. The first classifier quickly generates candidates with a small detection window. The second classifier accurately verifies the generated candidates with a large detection window. Furthermore, the vehicle classifier and the wheel classifier are simultaneously used to effectively detect a vehicle entering the blind spot area, along with an adjacent vehicle in the blind spot area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2750-2757
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• 2010

Recently, there have been a number of voices from industry that automotive education at the college is too theoretical and so college graduates are lack of practical ability to apply the automotive idea to actual systems. In order to educate engineering students design qualities in creative problem solving, this paper reports the results of employing engineering design projects in a Motor sports course of at A College. This paper presents design creterion and manufacture process of $CO_2$ model dragster, measures $CO_2$ model dragster speed and aerodynamic drag. In order to investigate the impact of engineering design on student's learning, a survey was conducted in 2008 spring semester. According to the results of survey analyses, student's key competencies and satisfaction reports high values on engineering design projects.

• Journal of Korea Multimedia Society
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• v.4 no.4
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• pp.297-305
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• 2001

Recently advances in high-speed networks and multimedia computer technologies allow new types of multimedia applications to manipulate large volumes of multimedia data. However, in the real time and/or the heterogeneous data transmissions, there are many difficulties such as network transmission delay, the implementation difficulties, and so on. To solve these problems, in this paper, we extend the method of the multimedia service design which is proposed by OMG. To do this, we suggest an efficient real time audio/video stream framework, called Smart Explorer, based un CORBA and JMF Java Media API. And we separate the transmission path of control data from that of media data and use RTP/RTCP protocol for efficient real time audio/video transmission. Also we show the appropriate implementation of the audio/video stream system based on our suggested framework Smart Explorer. In the future, we expect our audio/video stream system to be applied to the real time communication software such as broadcasting, distance learning, and video conferencing.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.216-224
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• 2010

A RAM-based Neural Network(RNN) has the advantages of processing speed and hardware implementation. In spite of these advantages, it has a saturation problem, weakness of repeated learning and extract of a generalized pattern. To resolve these problems of RNN, the 3DNS model using cumulative multi discriminator was proposed. But that model does not solve the saturation problem yet. In this paper, we proposed a adaptive weight cumulative neural net(AWCNN) using the adaptive weight neuron (AWN) for solving the saturation problem. The proposed nets improved a recognition rate and the saturation problem of 3DNS. We experimented with the MNIST database of NIST without preprocessing. As a result of experimentations, the AWCNN was 1.5% higher than 3DNS in a recognition rate when all input patterns were used. The recognition rate using generalized patterns was similar to that using all input patterns.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.617-624
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• 2017

Speech recognition is now one of the most widely used technologies in HCI. Many applications where speech recognition may be used (such as home automation, automatic speech translation, and car navigation) are now under active development. In addition, the demand for speech recognition systems in mobile environments is rapidly increasing. This paper is intended to present a method for instant recognition of the Korean vowel 'ㅡ', as a part of a Korean speech recognition system. The proposed method uses bulk indicators (which are calculated in the time domain) instead of the frequency domain and consequently, the computational cost for the recognition can be reduced. The bulk indicators representing predominant sequence patterns of the vowel 'ㅡ' are learned by neural networks and final recognition decisions are made by those trained neural networks. The results of the experiment show that the proposed method can achieve 88.7% recognition accuracy, and recognition speed of 0.74 msec per syllable.

• Convergence Security Journal
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• v.19 no.4
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• pp.115-121
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• 2019

Recently, as the use of smart devices is becoming more common, various and convenient services are being developed. Among these services, the Social Network Service(SNS) is easily accessible anywhere, anytime. In particular, as well as sharing information, it forms a social relationship in cyberspace to expand new connections, and the SNS account is used as an authentication means of other services to provide users with speed and convenience at all times. However, despite the many advantages of SNS, due to security vulnerabilities occurring in the interworking process with various services, accidents of personal information are constantly occurring, and it is urgent to prepare countermeasures against potential risk factors. It is a necessary situation. Therefore, in this paper, the use of SNS is expected to increase rapidly in the future, and it is expected that it will be used as the basic data for developing the countermeasures by learning the countermeasures according to the security threats of the SNS.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.186-191
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• 2003

Skills in tracing of the MR divide into following, approaching, avoiding and warning and so on. It is difficult to have all these skills learned as neural network. To make this up for, skills consisted of each module, and Mobile Robot was controlled by the output of module adequate for the situation. A mobile Robot was equipped multi-ultrasonic sensor and a USB Camera, which can be in place of human sense, and the measured environment information data is learned through Modular Neural Network. MNN consisted of optimal combination of activation function in the Expert Network and its structure seemed to improve learning time and errors. The Gating Network(GN) used to control output values of the MNN by switching for angle and speed of the robot. In the paper, EN of Modular Neural network was designed optimal combination. Traveling with a real MR was performed repeatedly to verity the usefulness of the MNN which was proposed in this paper. The robot was properly controlled and driven by the result value and the experimental is rewarded with good fruits.