• Proceedings of the CALSEC Conference
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• 2005.11a
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• pp.78-84
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• 2005

As the research activities related to 'Ubiquitous Computing' whose concept was introduced by Mark Weiser are growing, RFID(Radio Frequency Identification) technology has recently gained attention as a technology to advance the ubiquitous computing and a lot of related researches are also in progress. Research works done so far are mainly linked to the situation that the research outputs apply to meet the requirements for asset tracking and data sharing with partners over supply chain by using fixed RFID readers. However, it is essential that users have access to real-time information about the tagged objects and services whenever and wherever they want in the era of ubiquitous computing, so mobile devices-including PDA, smart phone, cellular phone, etc - which are equipped with an RFID reader can be regarded as an essential terminal for users living in ubiquitous computing environment. As far as the application with mobile devices are concerned, there are many considerations due to their limited capabilities of data processing, battery consumption and so on. In this paper, we review the generic RFID network model and introduce the revised RFID network model in consideration of incorporation with mobile devices equipped with an RFID reader. Also, we derive the requirements for software embedded within an RFID- enabled mobile terminal and then discuss essential components for implementation. Moreover, we develop the applications for asset management at museum by using mobile RFID network model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.689-692
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• 2021

This paper is a prior study to improve the efficiency of offloading based on mobile agents to optimize allocation of computing resources and reduce latency that support user proximity of application services in a Fog/Edge Computing (FEC) environment. We propose an algorithm that effectively reduces the execution time and the amount of memory required when extracting optimal moving patterns from the vast set of spatio-temporal movement history data of moving objects. The proposed algorithm can be useful for the distribution and deployment of computing resources for computation offloading in future FEC environments through frequency-based optimal path extraction.

• Journal of KIISE:Databases
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• v.37 no.4
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• pp.185-196
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• 2010

Existing methods to compute reverse skyline queries are not correct to process the queries in dataset with region objects which have conditions like a price is 5~7 dollars and a distance to beach is 1km~2km, since they consider datasets with only point objects. To solve the problem, we propose a novel method to process reverse skyline queries for region objects in this paper. It has advantages. First, it is expected to get a good performance, because it is extended from efficient reverse skyline (ERSL) algorithm which is a best algorithm to computing reverse skyline queries in datasets with point objects. Second, it can give a right of choice unlike the others to a person requesting the query. That is because results of reverse skyline have a difference preference according to proposed pruning methods and overlap relations. This algorithm is a first for supporting region objects. Therefore there are not any other algorithms to compare their performance. For that reason, our experiment to prove the efficiency of proposed algorithm is focused what conditions give an effect to its performance and result and how much time it needs to process the query.

• Journal of The Korean Association of Information Education
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• v.22 no.3
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• pp.297-305
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• 2018

Physical computing is the concept of expanding computing to humans, environments, and objects. It draws attention as a programming learning medium based on physical outputs in integration of hardware and software. This study developed a programming learning model based on interactive prototyping using the characteristics of physical computing with a high degree of technical freedom and analyzed its learning effect in an experiment. To examine the effect of the experimental treatment, this researcher divided fifty nine 5th-grade elementary students into an experimental group and into a control group. the interactive prototyping programming learning model was applied to the experimental group, and a linear sequential programming learning model was applied to the control group. Information Science Creative Personality Test was conducted before and after the experimental treatment. Analysis of Covariance was conducted with the pre-test scores of the two groups. As a result, it was proved that there was the effect of learning at the significance level of .05. It indicates that the physical computing based interactive prototyping programming learning model is applicable to the programming learning for 5th-grade elementary students.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.53-63
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• 2024

Alzheimer's disease is a brain disorder that worsens over time and affects millions of people around the world. It leads to a gradual deterioration in memory, thinking ability, and behavioral and social skills until the person loses his ability to adapt to society. Technological progress in medical imaging and the use of artificial intelligence, has provided the possibility of detecting Alzheimer's disease through medical images such as magnetic resonance imaging (MRI). However, Deep learning algorithms, especially convolutional neural networks (CNNs), have shown great success in analyzing medical images for disease diagnosis and classification. Where CNNs can recognize patterns and objects from images, which makes them ideally suited for this study. In this paper, we proposed to compare the performances of Alzheimer's disease detection by using two deep learning methods: You Only Look Once (YOLO), a CNN-enabled object recognition algorithm, and Visual Geometry Group (VGG16) which is a type of deep convolutional neural network primarily used for image classification. We will compare our results using these modern models Instead of using CNN only like the previous research. In addition, the results showed different levels of accuracy for the various versions of YOLO and the VGG16 model. YOLO v5 reached 56.4% accuracy at 50 epochs and 61.5% accuracy at 100 epochs. YOLO v8, which is for classification, reached 84% accuracy overall at 100 epochs. YOLO v9, which is for object detection overall accuracy of 84.6%. The VGG16 model reached 99% accuracy for training after 25 epochs but only 78% accuracy for testing. Hence, the best model overall is YOLO v9, with the highest overall accuracy of 86.1%.

• Korean Journal of Computational Design and Engineering
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• v.15 no.2
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• pp.106-114
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• 2010

The swept volume, the region of a moving object, is applied in many fields such as valid paths for motions of tools, visualization in robot paths and interference tests for parts assembling or disjointing. The shape of a swept volume depends on an generators computed with normal vectors of an object and velocity vectors of a motion. Although free-from surfaces are widely used to represent geometric models in CAD, computing the generators for a free-form object is a formidable task. Previous approaches exploit the closed form expressions of generators but limited to planer or quadric faces. In this paper, we propose the algorithm to compute swept volumes generated by free-form objects in screw motions. For the algorithm a tracing method is applied to the computation of generators. It considers curvatures of surfaces of an object to increase the computational accuracy. We implemented our algorithm in the CATIA V.5 environment to test the validity of our algorithm and to generate examples.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.951-958
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• 2007

Radio Frequency Identification (RFID) is a technology for automated identification of objects and people. RFID may be viewed as a means of explicitly labeling objects to facilitate their "perception" by computing devices. RFlD systems have been gaining more popularity in areas especially in supply chain management and automated identification systems. However, there are many existing and potential problems in the RFlD systems which could threat the technology s future. To successfully adopt RFID technology in various applications. we need to develop the solutions to protect the RFID system s data information. This study investigates important issues related to privacy and security of RF1D based on the recent literature and suggests solutions to cope with the problem.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.130-141
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• 2017

Feature selection is one of the most challenging problems of pattern recognition and data mining. In this paper, a feature selection algorithm based on an improved version of binary differential evolution is proposed. The method simultaneously optimizes two feature selection criteria, namely, set approximation accuracy of rough set theory and relational algebra based derived score, in order to select the most relevant feature subset from an entire feature set. Superiority of the proposed method over other state-of-the-art methods is confirmed by experimental results, which is conducted over seven publicly available benchmark datasets of different characteristics such as a low number of objects with a high number of features, and a high number of objects with a low number of features.

• Journal of Advanced Navigation Technology
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• v.12 no.1
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• pp.8-14
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• 2008

In this paper, I have presented a new approach which can track moving objects in unknown environments. This scheme is important in providing a computationally feasible alternative to complete enumeration of JPDA which is intractable. I have proved that given an artificial measurement and track's configuration, proposed scheme converges to a proper plot in a finite number of iterations. In this light, even if the performance is enhanced by using the relaxation, I also note that the difficulty in tuning the parameters of the relaxation scheme is critical aspect of this suggestion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.829-832
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• 2003

This paper presents a technique that allows objects written with local semantics to be made remote. It works by creating interfaces that have roughly the same method signatures as the local interfaces but are remote. These generated interfaces form a layer between the application server interfaces and the RMI runtime. This technique results in the coding of tediously repeated try/catch blocks for the RMI remote interface.