• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3599-3619
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• 2019

In human activity recognition system both static and motion information play crucial role for efficient and competitive results. Most of the existing methods are insufficient to extract video features and unable to investigate the level of contribution of both (Static and Motion) components. Our work highlights this problem and proposes Static-Motion fused features descriptor (SMFD), which intelligently leverages both static and motion features in the form of descriptor. First, static features are learned by two-stream 3D convolutional neural network. Second, trajectories are extracted by tracking key points and only those trajectories have been selected which are located in central region of the original video frame in order to to reduce irrelevant background trajectories as well computational complexity. Then, shape and motion descriptors are obtained along with key points by using SIFT flow. Next, cholesky transformation is introduced to fuse static and motion feature vectors to guarantee the equal contribution of all descriptors. Finally, Long Short-Term Memory (LSTM) network is utilized to discover long-term temporal dependencies and final prediction. To confirm the effectiveness of the proposed approach, extensive experiments have been conducted on three well-known datasets i.e. UCF101, HMDB51 and YouTube. Findings shows that the resulting recognition system is on par with state-of-the-art methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.706-711
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• 2008

This paper is presented an accurate localization scheme for mobile robots based on the fusion of ultrasonic satellite (U-SAT) with inertial navigation system (INS), i.e., sensor fusion. Our aim is to achieve enough accuracy less than 100 mm. The INS consist of a yaw gyro, two wheel-encoders. And the U-SAT consist of four transmitters, a receiver. Besides the localization method in this paper fuse these in an extended Kalman filter. The performance of the localization is verified by simulation and two actual data(straight, curve) gathered from about 0.5 m/s of driving actual driving data. localization methods used are general sensor fusion and sensor fusion through Kalman filter using data from INS. Through the simulation and actual data studies, the experiment show the effectiveness of the proposed method for autonomous mobile robots.

• Smart Structures and Systems
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• v.16 no.2
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.1
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• pp.109-130
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• 2013

This study is to offer the raw data for conservation and restoration of national park by surveying and analysing the vascular plants in the Gayasan national park. The flora were summarized as 102 families, 328 genera, 469 species, 4 subspecies, 59 varieties and 9 forms. The endangered plants designated by Ministry of Environment were 2 taxa; Pedicularis hallaisanensis Hurus. and Gymnadenia conopsea for. albiflora Y.N.Lee. The rare plants designated by Korea Forest Service were 13 taxa; Crypsinus hastatus (Thunb.) Copel., Ligusticum tachiroei (Franch. & Sav.) M. Hiroe & Constance, Primula modesta var. fauriae (Franch.) Takeda, Lilium distichum Nakai ex Kamibay and so forth. The korean endemic plants were 15 taxa; Betula ermanii Cham., Carpinus laxiflora (Siebold & Zucc.) Blume, Stewartia pseudocamellia Maxim., Galium koreanum (Nakai) Nakai, Heloniopsis koreana Fuse, N.S. Lee & M.N. Tamura and so forth. The specific plants by floristic region were 66 taxa; Betula chinensis Maxim., Spiraea fritschiana Schneid., Vaccinium hirtum var. koreanum (Nakai) Kitam., Cimicifuga heracleifolia Kom., Adoxa moschatellina L. and so forth. The plants with approval for delivering oversea were 22 taxa; Salix hallaisanensis H.L$\acute{e}$v., Sanguisorba argutidens Nakai, Viola albida Palib., Weigela subsessilis (Nakai) L.H.Bailey and so forth. The naturalized plants were 30 taxa; Chenopodium album L., Lepidium apetalum Willd., Trifolium pratense L., Bidens frondosa L., Helianthus tuberosus L. and so forth.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.72-77
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• 2008

Identification of humans from multiple view points is an important task for surveillance and security purposes. For optimal performance the system should use the maximum information available from sensors. Multimodal biometric systems are capable of utilizing more than one physiological or behavioral characteristic for enrollment, verification, or identification. Since gait alone is not yet established as a very distinctive feature, this paper presents an approach to fuse face and gait for identification. In this paper we will use the single camera case i.e both the face and gait recognition is done using the same set of images captured by a single camera. The aim of this paper is to improve the performance of the system by utilizing the maximum amount of information available in the images. Fusion in considered at decision level. The proposed algorithm is tested on the NLPR database.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.1-22
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• 2014

Recent technological advances provide the opportunity to use large amounts of multimedia data from a multitude of sensors with different modalities (e.g., video, text) for the detection and characterization of criminal activity. Their integration can compensate for sensor and modality deficiencies by using data from other available sensors and modalities. However, building such an integrated system at the scale of neighborhood and cities is challenging due to the large amount of data to be considered and the need to ensure a short response time to potential criminal activity. In this paper, we present a system that enables multi-modal data collection at scale and automates the detection of events of interest for the surveillance and reconnaissance of criminal activity. The proposed system showcases novel analytical tools that fuse multimedia data streams to automatically detect and identify specific criminal events and activities. More specifically, the system detects and analyzes series of incidents (an incident is an occurrence or artifact relevant to a criminal activity extracted from a single media stream) in the spatiotemporal domain to extract events (actual instances of criminal events) while cross-referencing multimodal media streams and incidents in time and space to provide a comprehensive view to a human operator while avoiding information overload. We present several case studies that demonstrate how the proposed system can provide law enforcement personnel with forensic and real time tools to identify and track potential criminal activity.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.1
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• pp.5-7
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• 2022

KEPCO's plan is undergoing a trial operation to replace the open-loop section with ring main units configuration where underground distribution lines are installed, by linking the multi-way circuit breakers auto (MCA) on the power side of each pad-mounted transformer. However, ring main units application mentioned above may cause the ripple effects, when implementing the configuration without a study of protection coordination. Because ring main units with classical pre-set protection devices contribution in fault condition didn't consider yet. For the reliable ring main units operation, it is necessary to resolve several protection issues such as the protection coordination with substation side, prevention of the transformer inrush current. These issues can radically deteriorate the distribution system reliability Hence, it is essential to design proper protection coordination to reduce these types of problems. This paper presents a scheme of ring main units' configuration and MCA's settings of time-current curves to preserve the performance of protection coordination among the switchgears considering constraints, e.g. prevention of the ripple effects (on the branch section when a transformer failure occurs and the mainline when a branch line failure occurs). It was confirmed that the propagation of the failure for each interrupter segment could be minimized by applying the proposed TCC and the interrupter settings for the MCAs (branch, transformer). Further, it was verified that the undetected area of the distribution automation system (DAS) could be supplemented by having the MCA configurated ring main units operate first, instead of the internal protection equipment in the transformer such as the fuse, STP when a transformer failure occurs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.93-102
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• 2020

The design of large complex mechanical systems, such as automobile, aircraft, and ship, is a kind of Multidisciplinary Design Optimization (MDO) because it requires both experience and expertise in many areas. With the rapid development of technology and the demand to improve human convenience, the complexity of these systems is increasing further. The design of such a complex system requires an integrated system design, i.e., MDO, which can fuse not only domain-specific knowledge but also knowledge, experience, and perspectives in various fields. In the past, the MDO relied heavily on the designer's intuition and experience, making it less efficient in terms of accuracy and time efficiency. Process integration and the design optimization framework mainly support MDO owing to the evolution of IT technology. This paper examined the procedure and methods to implement an efficient MDO with reasonable effort and time using RCE, an open-source PIDO framework. As a benchmarking example, the authors applied the proposed MDO methodology to a bulk carrier's conceptual design synthesis model. The validity of this proposed MDO methodology was determined by visual analysis of the Pareto optimal solutions.