• Journal of the Korea Computer Graphics Society
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• v.23 no.5
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• pp.39-49
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• 2017

In this study, we propose the core factors and application of asymmetric virtual reality(VR) content in which head-mounted display(HMD) user and Non-HMD users can work together in a co-located space that can lead to various experiences and high presence. The core of the proposed asymmetric VR content is that all users are immersed in VR and participate in new experiences by reflecting widely a range of users' participation and environments, regardless of whether or not users wear the HMD. For this purpose, this study defines the role relationships between HMD user and Non-HMD users, the viewpoints provided to users, and the speech communication structure available among users. Based on this, we verified the core factors through the process of producing assistive asymmetric VR content and cooperative asymmetric VR content directly. Finally, we conducted a survey to examine the users' presence and their experience of the proposed asymmetric VR content and to analyze the application method. As a result, it was confirmed that if the purpose of asymmetric VR content and core factors between the two types of users are clearly distinguished and defined, the independent experience presented by the VR content together with perceived presence can provide a satisfactory experience to all users.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.17-25
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• 2011

At the computer games, we can experience a variety of environments using a virtual object. It is similar to that be trained in War-game simulator of the defense. Actual soldiers and a computer-generated virtual group(Computer Generated Force: CGF) in 3-D virtual battlefield environment are training. However, path finding algorithm, one of the techniques of simulation models, to the current level only considers the shortest time path. So, this current level at the special situation of the army in the battlefield for selecting the optimal path is limited. The focus of this paper is to select the least-cost path using the deadline with several different mission conditions(METT+TC). For the only shortest time path algorithm and the least-cost path algorithm using dealine,($d_t$, one of METT+TC elements), Its usefulness is verifying the change of the move spent time(t) for all possible paths and the fighting power of the combat troops(Troops ability, a) through a comparison of the total cost of moves(c(t)). According to the results, when considering the deadline, the proposed algorithm saves about 62.5% of the maximum cost.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.10
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• pp.31-38
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• 2008

This paper describes sensor network system implementation for the IEEE 1451.2 standard which guarantees compatibilities between various wired sensors. The proposed system consists of the Network Capable Application Processor(NCAP) in the IEEE 1451.0, the Transducer Independent Interface(TII) in the IEEE 1451.2, the Transducer Electronic Data Sheet(TEDS) and sensors. The research goal of this study is to minimize and optimize system complexity for IC design. The NCAP is implemented using C language in personal computer environment. TII is used in the parallel port between PC and an FPGA application board. Transducer is implemented using Verilog on the FPGA application board. We verified the proposed system architecture based on the standards.

• Journal of the Korea Computer Graphics Society
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• v.22 no.5
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• pp.17-26
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• 2016

This paper presents an adaptive slicing method based on merging vertical layer polylines. Firstly, we slice the input 3D polygon model uniformly with the minimum printable thickness, which results in bounding polylines of the cross section at each layer. Next, we group a set of layer polylines according to vertical connectivity. We then remove polylines in overdense area of each group. The number of layers to merge is determined by the layer thickness computed using the cusp height of the layer. A set of layer polylines are merged into a single polyline by removing the polylines within the layer thickness. The proposed method maintains the shape features as well as reduces the printing time. For evaluation, we sliced ten 3D polygon models using our method and a global adaptive slicing method and measured the total length of polylines which determines the printing time. The result showed that the total length from our method was shorter than the other method for all ten models, which meant that our method achieved less printing time.

• Journal of Korea Game Society
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• v.9 no.3
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• pp.15-22
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• 2009

Our society is the information-oriented knowledge society which demands the ability how to use computers to all members of the society and is the aging society which the old people 60 or older exist plentifully. But in our society, there are rarely the computers for the old people which are considered their body limit. In this research, we proposed a grip type Hangul(Korean alphabet)interface which are designed under the consideration for the body limit of the old people. The comparison analysis of the proposed Hangul interface is accomplished with the keyboard(ME TOO SV01) for old persons and the key buttons of the old person cellular phone(LG KV-3900) as existing products. The comparison analysis consists of quantitative evaluation as measurements and qualitative evaluation as a survey of the satisfaction levels of 10 older persons. The results of the quantitative evaluation show that the proposed Hangul interface is the best one in the human-technology-design, the number of input buttons which requires moving of user's fingers, the maximum range of moving of user's fingers, and the number of the fingers to use text inputs. The survey results of the satisfaction levels show that interface shape, and input button's positions have best levels and they show that input button's gaps and ease of use have the second levels but their points are almost same with the best points of the keyboard.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.13-21
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• 2010

One of the most distinguished features of the DHP association rules mining algorithm is that it counts the support of hash key combinations composed of k items at phase k-1, and uses the counted support for pruning candidate large itemsets to improve performance. At this time, it is desirable for each hash key combination to have a separate count variable, where it is impossible to allocate the variables owing to memory shortage. So, the algorithm uses a direct hashing mechanism in which several hash key combinations conflict and are counted in a same hash bucket. But the direct hashing mechanism is not efficient because the distribution of hash key combinations is unvalanced by the characteristics sourced from the mining process. This paper proposes a mapped perfect hashing function which maps the region of hash key combinations into a continuous integer space for phase 3 and maximizes the efficiency of direct hashing mechanism. The results of a performance test experimented on 42 test data sets shows that the average performance improvement of the proposed hashing mechanism is 7.3% compared to the existing method, and the highest performance improvement is 16.9%. Also, it shows that the proposed method is more efficient in case the length of transactions or large itemsets are long or the number of total items is large.

• Journal of the Korea Society of Computer and Information
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• v.18 no.6
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• pp.21-28
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• 2013

This paper proposes an effective fire detection approach that includes the following multiple heterogeneous algorithms: moving region detection using grey level histograms, color segmentation using fuzzy c-means clustering (FCM), feature extraction using a grey level co-occurrence matrix (GLCM), and fire classification using support vector machine (SVM). The proposed approach determines the optimal threshold values based on grey level histograms in order to detect moving regions, and then performs color segmentation in the CIE LAB color space by applying the FCM. These steps help to specify candidate regions of fire. We then extract features of fire using the GLCM and these features are used as inputs of SVM to classify fire or non-fire. We evaluate the proposed approach by comparing it with two state-of-the-art fire detection algorithms in terms of the fire detection rate (or percentages of true positive, PTP) and the false fire detection rate (or percentages of true negative, PTN). Experimental results indicated that the proposed approach outperformed conventional fire detection algorithms by yielding 97.94% for PTP and 4.63% for PTN, respectively.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.109-114
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• 2012

Honeycombs are dense structures that small cysts, which generally have about 2~10 mm in diameter, are surrounded by the wall of fibrosis. When honeycomb is found in the patients, the incidence of acute exacerbation is generally very high. Thus, the observation and quantitative measurement of honeycomb are considered as a significant marker for clinical diagnosis. In this point of view, we propose an automatic segmentation method using morphological image processing and assessment of the degree of clustering techniques. Firstly, image noises were removed by the Gaussian filtering and then a morphological dilation method was applied to segment lung regions. Secondly, honeycomb cyst candidates were detected through the 8-neighborhood pixel exploration, and then non-cyst regions were removed using the region growing method and wall pattern testing. Lastly, final honeycomb regions were segmented through the extraction of dense regions which are consisted of two or more cysts using cluster analysis. The proposed method applied to 80 High resolution computed tomography (HRCT) images and achieved a sensitivity of 89.4% and PPV (Positive Predictive Value) of 72.2%.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.41-49
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• 2021

All application programs, including malware, call the Application Programming Interface (API) upon execution. Recently, using those characteristics, attempts to detect and classify malware based on API Call information have been actively studied. However, datasets containing API Call information require a large amount of computational cost and processing time. In addition, information that does not significantly affect the classification of malware may affect the classification accuracy of the learning model. Therefore, in this paper, we propose a method of extracting a essential feature set after reducing the dimensionality of API Call information by applying various feature selection methods. We used CICAndMal2020, a recently announced Android malware dataset, for the experiment. After extracting the essential feature set through various feature selection methods, Android malware classification was conducted using CNN (Convolutional Neural Network) and the results were analyzed. The results showed that the selected feature set or weight priority varies according to the feature selection methods. And, in the case of binary classification, malware was classified with 97% accuracy even if the feature set was reduced to 15% of the total size. In the case of multiclass classification, an average accuracy of 83% was achieved while reducing the feature set to 8% of the total size.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.63-70
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• 2022

Although 2D Object detection has been largely improved in the past years with the advance of deep learning methods and the use of large labeled image datasets, 3D object detection from 2D imagery is a challenging problem in a variety of applications such as robotics, due to the lack of data and diversity of appearances and shapes of objects within a category. Google has just announced the launch of Objectron that has a novel data pipeline using mobile augmented reality session data. However, it also is corresponding to 2D-driven 3D object detection technique. This study explores more mature 2D object detection method, and applies its 2D projection to Objectron 3D lifting system. Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a stochastic representation of object regions using Gaussian distributions. We also present a similarity measure for the Gaussian distributions based on the Hellinger Distance, which can be viewed as a stochastic Intersection-over-Union. Our experimental results show that the proposed Gaussian representations are closer to annotated segmentation masks in available datasets. Thus, less accuracy problem that is one of several limitations of Objectron can be relaxed.