• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.8
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• pp.19-27
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• 2016

Nowadays the adaptive buffering techniques for burst stream packet configuration and its operation algorithm to save energy in IP core network have been studied. This paper explains the selection method of packet buffering interval for energy saving when configuring burst stream packet at the ingress router in IP core network. Especially the adaptive buffering interval and its implementation scheme are required to improve the energy saving efficiency at the input part of the ingress router. In this paper, we propose the best adaptive buffering scheme that a current buffering interval is adaptively buffering scheme based on the input traffic of the past buffering interval, and analyze its characteristics of energy saving and end-to-end delay by computer simulation. We show the improvement of energy saving effect and reduction of mean delay variation when using an appropriate inverse-function selecting the buffering interval for the configuration of burst stream packet in this paper. We confirm this method have superior properties compared to other method. The proposed method shows that it is less sensitive to the various input traffic type of ingress router and a practical method.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.47-53
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• 2004

We propose a new speech enhancement algorithm based on left-right Hidden Markov Model (HMM) with state decision using Log-likelihood Ratio Test (LRT). Since the conventional HMM-based speech enhancement methods try to improve speech quality for all states, they introduce huge computational loads inappropriate to real-time implementation. In the left-right HMM, only the current and the next state are considered for a possible state transition so to reduce the computational complexity. In this paper, we propose a method to decide the current state by using the LRT on the previous state. Experimental results show that the proposed method improves the speed up to 60% with 0.2∼0.4 dB degradation of speech quality compared to the conventional method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.125-135
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• 2012

This paper proposes the new object detection system with two laser-scanners and a camera for classifying the objects and predicting the location of objects on road street. This detection system could be applied the new C-ITS service such as ADAS(Advanced Driver Assist System) or (semi-)automatic vehicle guidance services using object's types and precise position. This study describes the some examples in other countries and feasibility of object detection system based on a camera and two laser-scanners. This study has developed the heterogenous sensor's fusion method and shows the results of implementation at road environments. As a results, object detection system at roadside infrastructure is a useful method that aims at reliable classification and positioning of road objects, such as a vehicle, a pedestrian, and obstacles in a street. The algorithm of this paper is performed at ideal condition, so it need to implement at various condition such as light brightness and weather condition. This paper should help better object detection and development of new methods at improved C-ITS environment.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.154-161
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• 2018

As the number of smartphone users increases, research on indoor location recognition service is necessary. Access to indoor locations is predominantly WiFi, Bluetooth, etc., but in most quarters, WiFi is equipped with WiFi functionality, which uses WiFi features to provide WiFi functionality. The study uses the random forest algorithm, which employs the fingerprint index of the acquired WiFi and the use of the multI-value classification method, which employs the receiver signal strength of the acquired WiFi. As the data of the fingerprint, a total of 4 radio maps using the Mac address together with the received signal strength were used. The experiment was conducted in a limited indoor space and compared to an indoor location recognition system using an existing random forest, similar to the method proposed in this study for experimental analysis. Experiments have shown that the system's positioning accuracy as suggested by this study is approximately 5.8 % higher than that of a conventional indoor location recognition system using a random forest, and that its location recognition speed is consistent and faster than that of a study.

• 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.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.427-434
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• 2016

This paper focuses on a real-time hardware processing by implementing the ARM Cortex-M4 based embedded system, using a conversion algorithm from a muscular sense to both visual and auditory elements, which recognizes rotations of a human body, directional changes and motion amounts out of human senses. As an input method of muscular sense, AHRS(Attitude Heading Reference System) was used to acquire roll, pitch and yaw values in real time. These three input values were converted into three elements of HSI color model such as intensity, hue and saturation, respectively. Final color signals were acquired by converting HSI into RGB color model. In addition, Three input values of muscular sense were converted into three elements of sound such as octave, scale and velocity, which were synthesized to give an output sound using MIDI(Musical Instrument Digital Interface). The analysis results of both output color and sound signals revealed that input signals of muscular sense were correctly converted into both color and sound in real time by the proposed conversion method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1269-1276
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• 2016

Recently, natural disasters including earthquakes, tsunamis, floods, and snowstorms, in addition to disasters of human origin such as arson, and acts of terror, have caused numerous injuries and fatalities around the world. During such disasters, victims need to obtain information such as the exact location of the disaster and appropriate evacuation routes in order to relocate to safe areas. In this study, We propose the algorithm for Emergency Rescue Evacuation Support System(ERESS). In case a emergency disaster occurs, ERESS is possible to detect it quickly using through the movement of people. The mobile terminal analyzes behavior and location of indoor pedestrian. And it sends the result to the server. The server determines whether an emergency situation occurred or not based on the received transmission information. When an emergency situation occurs, the server will notify it to the mobile terminal. Then, indoor pedestrian conduct emergency evacuation using mobile terminal.

• Journal of Power Electronics
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• v.17 no.2
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• pp.533-541
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• 2017

This paper presents a novel Parameter-Independent Fictive-Axis (PIFA) approach for the Voltage-Oriented Control (VOC) algorithm used in grid-tied single-phase inverters. VOC is based on the transformation of the single-phase grid current into the synchronous reference frame. As a result, an orthogonal current signal is needed. Traditionally, this signal has been obtained from fixed time delays, digital filters or a Hilbert transformation. Nevertheless, these solutions present stability and transient drawbacks. Recently, the Fictive Axis Emulation (FAE) VOC has emerged as an alternative for the generation of the quadrature current signal. FAE requires detailed information of the grid current filter along with its transfer function for signal creation. When the transfer function is not accurate, the direct and quadrature current components present steady-state oscillations as the fictive two-phase system becomes unbalanced. Moreover, the digital implementation of the transfer function imposes an additional computing burden on the VOC. The PIFA VOC presented in this paper, takes advantage of the reference current to create the required orthogonal current, which effectively eliminates the need for the filter transfer function. Moreover, the fictive signal amplitude and phase do not change with a frequency drift, which results in an increased reliability. This yields a fast, linear and stable system that can be installed without fine tuning. To demonstrate the good performance of the PIFA VOC, simulation and experimental results are presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1490-1501
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• 2016

In this paper, we propose an image-based indoor localization system using parallel distributed computing. In order to reduce computation time for indoor localization, an scale invariant feature transform (SIFT) algorithm is performed in parallel by using Apache Spark. Toward this goal, we propose a novel image processing interface of Apache Spark. The experimental results show that the speed of the proposed system is about 3.6 times better than that of the conventional system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.414-418
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• 2016

In this paper, a hardware architecture of low area gradient magnitude calculator is proposed. For the hardware complexity reduction, the characteristic of orthogonal projection vector and hardware resource sharing technique are applied. The proposed hardware architecture can be implemented without degradation of the gradient magnitude data quality since the proposed hardware is implemented with original algorithm. The FPGA implementation result shows the 15% of logic elements and 38% embedded multiplier savings compared with previous work using Altera Cyclone VI (EP4CE115F29C7N) FPGA and Quartus II v15.0 environment.