• The Journal of the Acoustical Society of Korea
• /
• v.33 no.3
• /
• pp.216-224
• /
• 2014

In this paper, we propose a new method to drastically reduce computational complexity in Gaussian Mixture Model (GMM)-based Speaker Identification (SI). Generally, GMM-based SI systems have very high computational complexity proportional to the length of the test utterance, the number of enrolled speakers, and the GMM size. These make the SI systems difficult to be used in various real applications in spite of their broad applicability. Thus, a trade-off between computational complexity and identification accuracy is considered as a primary issue for practical applications. In order to reduce computational complexity sharply with a little loss of accuracy, we introduce a method based on the Universal Background Model (UBM) clustering approach and then we show that it can be used successfully in real-time applications. In experiments with the proposed algorithm, we obtained a speed-up factor of 6 with a negligible loss of accuracy.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.7
• /
• pp.87-93
• /
• 2014

TIn analysis as the first step of S/W development, security requirements of identification and authentication, ID and password management, authentication process, authentication method, ete. should be defined. Identification is to uniquely identify certain users and applications running on a certain system. Authentication means the function to determine true or false users and applications in some cases. This paper is to suggest the security requirements for identification and authentication in analysis step. Firstly, individual ID should be uniquely identified. The second element is to apply the length limitations, combination and periodic changes of passwords. The third should require the more reinforced authentication methods besides ID and passwords and satisfy the defined security elements on authentication process. In this paper, the security requirements for the step of identification and authentication have been explained through several practical implementation methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.6
• /
• pp.2160-2179
• /
• 2015

In many Radio Frequency Identification (RFID) applications, the reader recognizes the tags within its scope repeatedly. For these applications, some algorithms such as the adaptive query splitting algorithm (AQS) and the novel semi-blocking AQS (SBA) were proposed. In these algorithms, a staying tag retransmits its ID to the reader to be identified, even though the ID of the tag is stored in the reader's memory. When the length of tag ID is long, the reader consumes a long time to identify the staying tags. To overcome this deficiency, we propose a slot allocated blocking anti-collision algorithm (SABA). In SABA, the reader assigns a unique slot to each tag in its range by using a slot allocation mechanism. Based on the allocated slot, each staying tag only replies a short data to the reader in the identification process. As a result, the amount of data transmitted by the staying tags is reduced greatly and the identification rate of the reader is improved effectively. The identification rate and the data amount transmitted by tags of SABA are analyzed theoretically and verified by various simulations. The simulation and analysis results show that the performance of SABA is superior to the existing algorithms significantly.

• Smart Structures and Systems
• /
• v.15 no.3
• /
• pp.683-698
• /
• 2015

Railroad bridges form an integral part of railway infrastructure throughout the world. To accommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence of changing structural conditions, the load carrying capacity and serviceability of existing bridges must be assessed. One way is through system identification of in-service railroad bridges. To dates, numerous researchers have reported system identification studies with a large portion of their applications being highway bridges. Moreover, most of those models are calibrated at global level, while only a few studies applications have used globally and locally calibrated model. To reach the global and local calibration, both ambient vibration tests and controlled tests need to be performed. Thus, an approach for system identification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smart sensors are employed and provided a portable way to collect data that is then used to determine bridge frequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides global and local information of the bridge. The ability of the model to simulate local responses is validated by comparing predicted and measured strain in one of the diagonal members of the truss. This research demonstrates the potential of using measured field data to perform model calibration in a simple and practical manner that will lead to better understanding the state of railroad bridges.

• Journal of KIISE:Information Networking
• /
• v.37 no.6
• /
• pp.477-482
• /
• 2010

Recently, advanced Internet applications such as Internet telephone, multimedia streaming, and file sharing have appeared. Especially, P2P or web-based file sharing applications have been notorious for their illegal usage of contents and massive traffic consumption by a few users. This paper presents a novel method to identify the P2P or web-based file names with traffic monitoring. For this purpose, we have utilized the Korean decoding method on the IP packet payload. From experiments, we have shown that the file names requested by BitTorrent, Clubbox, and Tple applications could be correctly identified.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.644-646
• /
• 2004

The closed loop identification(CLID) is a very useful method for on-line applications since it can identify the plant in the closed-loop system composed of the plant and the controller. There are some literatures on CLID, but they and mainly focused on SISO(Single-Input/Single-Output) problem. In this paper, a CLID method is proposed for MIMO(Multi-Input/Multi-Output) systems. The CLID method is applied to a MIMO benchmark plant, TRMS(Twin-Rotor MIMO System). To illustrate the performance of the closed-loop system identification., unit step responses in the TRMS are represented and compared with the open-loop identification via some simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.10a
• /
• pp.115-120
• /
• 1997

System identification is the task of inferring a mathematical description of a dynamic system from a series of measurements of the system. There are several motives for establishing mathematical descriptions of dynamic systems. Typical applications encompass simulation, prediction, fault diagnostics, and control system design. The paper demonstrates that neural networks can be used effective for the identification of nonlinear dynamical systems. The content of this paper concerns dynamic neural network models, where not all inputs to and outputs from the networks are measurable. Only one model type is treated, the well-known Innovation State Space model(Kalman Predictor). The identification is based only on input/output measurements, so in fact a non-linear Extended Kalman Filter problem is solved. Even for linear models this is a non-linear problem without any assurance of convergence, and in spite of this fact an attempt is made to apply the principles from linear models, an extend them to non-linear models. Computer simulation results reveal that the identification scheme suggested are practically feasible.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.1
• /
• pp.118-124
• /
• 2004

In this paper, we present a indirect adaptive control method using a wavelet neural network (WNN) for the control of chaotic nonlinear systems without precise mathematical models. The proposed indirect adaptive control method includes the off-line identification and on-line control procedure for chaotic nonlinear systems. In the off-line identification procedure, the WNN based identification model identifies the chaotic nonlinear system by using the serial-parallel identification structure and is trained by the gradient-descent method. And, in the on-line control procedure, a WNN controller is designed by using the off-line identification model and is trained by the error back-propagation algorithm. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with applications to the chaotic nonlinear systems.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.3
• /
• pp.193-197
• /
• 2012

This paper focuses on identifying which appliance is currently operating by analyzing electrical load signature for home energy monitoring system. The identification framework is comprised of three steps. Firstly, specific appliance features, or signatures, were chosen, which are DC (Duty Cycle), SO (Slope of On-state), VO (Variance of On-state), and ZC (Zero Crossing) by reviewing observations of appliances from 13 houses for 3 days. Five appliances of electrical rice cooker, kimchi-refrigerator, PC, refrigerator, and TV were chosen for the identification with high penetration rate and total operation-time in Korea. Secondly, K-NN and Naive Bayesian classifiers, which are commonly used in many applications, are employed to estimate from which appliance the signatures are obtained. Lastly, one of candidates is selected as final identification result by majority voting. The proposed identification frame showed identification success rate of 94.23%.

• Smart Structures and Systems
• /
• v.29 no.5
• /
• pp.715-728
• /
• 2022

Recently, numbers of long span pedestrian suspension bridges have been constructed worldwide. While recent tragedies regarding pedestrian suspension bridges have shown how these bridges can wreak havoc on the society, there are no specific guidelines for construction standards nor safety inspections yet. Therefore, a structural health monitoring system that could help ensure the safety of pedestrian suspension bridges are needed. System identification is one of the popular applications for structural health monitoring method, which estimates the dynamic system. Most of the system identification methods for bridges are currently adapting output-only system identification method, which assumes the dynamic load to be a white noise due to the difficulty of measuring the dynamic load. In the case of pedestrian suspension bridges, the pedestrian load is within specific frequency range, resulting in large errors when using the output-only system identification method. Therefore, this study aims to develop a system identification method for pedestrian suspension bridges considering both input and output of the dynamic system. This study estimates the location and the magnitude of the pedestrian load, as well as the dynamic response of the pedestrian bridges by utilizing artificial intelligence and computer vision techniques. A simulation-based validation test was conducted to verify the performance of the proposed system. The proposed method is expected to improve the accuracy and the efficiency of the current inspection and monitoring systems for pedestrian suspension bridges.