• The Journal of the Convergence on Culture Technology
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• v.2 no.1
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• pp.93-98
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• 2016

As information technologies are rapidly developed recently, social networking services through a variety of mobile devices and smart screen is becoming popular. SNS is a social networking based services which is online forms from existed offline. SNS can also be used differently which is confused with the online community. A modelling algorithm is a variety of techniques, which are assocoation, clustering, neural networks, and decision trees, etc. By utilizing this technique, it is necessary to study to effectively using the large number of materials. In this paper, we evaluate in particular the performance of the algorithm based on the results of the clustering using Facebook Insights data for the EM algorithm to be evaluated as a good performance in clustering. Through this analysis it was based on the results of the application of the experimental data of the change and the South Australian state library according to the performance of the EM algorithm.

• Journal of the HCI Society of Korea
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• v.12 no.3
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• pp.13-23
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• 2017

In this paper, we propose a new in-hand 3D modeling system that improves user convenience. Since traditional modeling systems are inconvenient to use, an in-hand modeling system has been studied, where an object is handled by hand. However, there is also a problem that it requires additional equipment or specific constraints to remove hands for good modeling. In this paper, we propose a contact state change detection algorithm for automatic hand removal and improved ICP algorithm that enables outlier handling and additionally uses color for accurate registration. The proposed algorithm enables accurate modeling without additional equipment or any constraints. Through experiments using real data, we show that it is possible to accomplish accurate modeling under the general conditions without any constraint by using the proposed system.

• Journal of Power Electronics
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• v.15 no.3
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• pp.670-684
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• 2015

The hybrid cascaded multilevel inverter (HCMLI) is a popular converter topology that is being increasingly used in high power medium voltage drives. The intricacy of the control technique for a HCMLI increases with the number of levels and due to fluctuating dc voltages. This paper presents a novel offline quadrant search based space vector modulation technique to synthesize a sinusoidal output from a dispersed pattern of voltage vectors due to different voltages in the auxiliary unit. Such an investigation has never been reported in the literature and it is being attempted for the first time. The method suggested distributes the voltage vectors for a reduced total harmonic distortion at minimal computation. In addition, the proposed algorithm determines the maximum modulation index in the linear modulation range in order to synthesize a sinusoidal output for both normal and abnormal vector patterns. It is better suited for a wide range of practical applications. It is particularly well suited for renewable source fed inverters which utilize large capacitor banks to maintain the dc link, which are prone to such slow fluctuations. The proposed quadrant search space vector modulation technique is simulated using MATLAB/SIMULINK and implemented using a Nexys-2 Spartan-3E FPGA for a developed prototype.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2922-2945
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• 2018

Achieving efficient authentication is a crucial issue for stream data commonly seen in content delivery, peer-to-peer, and multicast/broadcast networks. Stream authentication mechanisms need to be operated efficiently at both sender-side and receiver-side at the same time because of the properties of stream data such as real-time and delay-sensitivity. Until now, many stream authentication mechanisms have been proposed, but they are not efficient enough to be used in stream applications where the efficiency for sender and receiver sides are required simultaneously since most of them could achieve one of either sender-side and receiver-side efficiency. In this paper, we propose an efficient stream authentication mechanism, so called TIM, by integrating Trapdoor Hash Function and Merkle Hash Tree. Our construction can support efficient streaming data processing at both sender-side and receiver-side at the same time differently from previously proposed other schemes. Through theoretical and experimental analysis, we show that TIM can provide enhanced performance at both sender and receiver sides compared with existing mechanisms. Furthermore, TIM provides an important feature for streaming authentication, the resilience against transmission loss, since each data block can be verified with authentication information contained in itself.

• Journal of Power Electronics
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• v.15 no.5
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• pp.1274-1285
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• 2015

This paper deals with model reference adaptive system (MRAS) speed estimators based on a secondary flux for linear induction motors (LIMs). The operation of these estimators significantly depends on an adaptation mechanism. Fixed-gain PI controller is the most common adaptation mechanism that may fail to estimate the speed correctly in different conditions, such as variation in machine parameters and noisy environment. Two adaptation mechanisms are proposed to improve LIM drive system performance, particularly at very low speed. The first adaptation mechanism is based on fuzzy theory, and the second is obtained from an LIM mechanical model. Compared with a conventional PI controller, the proposed adaptation mechanisms have low sensitivity to both variations of machine parameters and noise. The optimum parameters of adaptation mechanisms are tuned using an offline method through chaotic optimization algorithm (COA) because no design criterion is given to provide these values. The efficiency of MRAS speed estimator is validated by both numerical simulation and real-time hardware-in-the-loop (HIL) implementations. Results indicate that the proposed adaptation mechanisms improve performance of MRAS speed estimator.

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1586-1593
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• 2015

Calligraphy contents(shortly called, CalliContents) depict the feature of communication media with artistic sentences or drawings before being processed into digital contents to become printed advertisement, visual design and entertainment products. As a fast growing business model, they can be applied to every single scope of all fields these days and each application case presented excellent effects to grab consumers' attention immediately. In this paper, we designed and produced an emotional bi-directional recommendation DIY calligraphy contents platform to consume created cultural contents and boost personalized contents industry that meets consumer's needs through both wired and wireless-based software with convergence of artistic and emotional calligraphy contents and ICT. For this works, we established for DIY calligraphy consumers a foundation of a virtuous circle of the CalliContents where various CalliContents are provided in on and offline environment and a third party target is opened at the CalliContents platform

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1133-1151
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• 2010

Energy balanced consumption routing is based on assumption that the nodes consume energy both in transmitting and receiving. Lopsided energy consumption is an intrinsic problem in low-cost sensor networks characterized by multihop routing and in many traffic overhead pattern networks, and this irregular energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed low-cost sensor networks. We formulate the energy consumption balancing problem as an optimal balancing data transmitting problem by combining the ideas of corona cluster based network division and optimized transmitting state routing strategy together with data transmission. We propose a localized cluster based routing scheme that guarantees balanced energy consumption among clusters within each corona. We develop a new energy cluster based routing protocol called "OECR". We design an offline centralized algorithm with time complexity O (log n) (n is the number of clusters) to solve the transmitting data distribution problem aimed at energy balancing consumption among nodes in different cluster. An approach for computing the optimal number of clusters to maximize the network lifetime is also presented. Based on the mathematical model, an optimized energy cluster routing (OECR) is designed and the solution for extending OEDR to low-cost sensor networks is also presented. Simulation results demonstrate that the proposed routing scheme significantly outperforms conventional energy routing schemes in terms of network lifetime.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3657-3682
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• 2018

This paper presents a Bluetooth and pedestrian dead reckoning (PDR)-based indoor fusion localization approach (BtPDR) using smartphones. A Bluetooth and PDR-based indoor fusion localization approach can localize the initial position of a smartphone with the received signal strength (RSS) of Bluetooth. While a smartphone is moving, BtPDR can track its position by fusing the localization results of PDR and Bluetooth RSS. In addition, BtPDR can adaptively modify the parameters of PDR. The contributions of BtPDR include: a Bluetooth RSS-based Probabilistic Voting (BRPV) localization mechanism, a probabilistic voting-based Bluetooth RSS and PDR fusion method, and a heuristic search approach for reducing the complexity of BRPV. The experiment results in a real scene show that the average positioning error is < 2m, which is considered adequate for indoor location-based service applications. Moreover, compared to the traditional PDR method, BtPDR improves the location accuracy by 42.6%, on average. Compared to state-of-the-art Wireless Local Area Network (WLAN) fingerprint + PDR-based fusion indoor localization approaches, BtPDR has better positioning accuracy and does not need the same offline workload as a fingerprint algorithm.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1729-1738
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• 2014

The offline verification of state of charge estimation, power estimation, fault diagnosis and emergency control of battery management system (BMS) is one of the key technologies in the field of electric vehicle battery system. It is difficult to test and verify the battery management system software in the early stage, especially for algorithms such as system state estimation, emergency control and so on. This article carried out the virtual environment modeling for verification of battery management system. According to the input/output parameters of battery management system, virtual environment is determined to run the battery management system. With the integration of the developed BMS model and the external model, the virtual environment model has been established for battery management system in the vehicle's working environment. Through the virtual environment model, the effectiveness of software algorithm of BMS was verified, such as battery state parameters estimation, power estimation, fault diagnosis, charge and discharge management, etc.

• Journal of Platform Technology
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• v.10 no.3
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• pp.51-59
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• 2022

Machine learning, which has recently innovatively developed, has become an important technology that can solve various optimization problems. In this paper, we introduce the latest research papers that solve the problem of channel sharing in heterogeneous networks using machine learning, analyze the characteristics of mainstream approaches, and present a guide to future research directions. Existing studies have generally adopted Q-learning since it supports fast learning both on online and offline environment. On the contrary, conventional studies have either not considered various coexistence scenarios or lacked consideration for the location of machine learning controllers that can have a significant impact on network performance. One of the powerful ways to overcome these disadvantages is to selectively use a machine learning algorithm according to changes in network environment based on the logical network architecture for machine learning proposed by ITU.