• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.643-647
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• 2021

The use of data analysis on large volumes of data constitutes a challenge for deducting knowledge and new information. Data can be heterogeneous and complex: Semi-structured data (Example: XML), Data from social networks (Example: Tweets) and Factual data (Example: Spreading of Covid-19). In this paper, we propose a generic multidimensional model in order to analyze complex data, according to several dimensions.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.291-300
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• 1998

This paper demonstrates how ambient vibration measurements at a limited number of locations can be effectively utilized to estimate parameters of a finite element model of a large-scale structural system involving a large number of elements. System identification using ambient vibration measurements presents a challenge requiring the use of special identification techniques, which ran deal with very small magnitudes of ambient vibration contaminated by noise without the knowledge of input farces. In the present study, the modal parameters such as natural frequencies, damping ratios, and mode shapes of the structural system were estimated by means of appropriate system identification techniques including the random decrement method. Moreover, estimation of parameters such as the stiffness matrix of the finite element model from the system response measured by a limited number of sensors is another challenge. In this study, the system stiffness matrix was estimated by using the quadratic optimization involving the computed and measured modal strain energy of the system, with the aid of a sensitivity relationship between each element stiffness and the modal parameters established by the second order inverse modal perturbation theory. The finite element models thus identified represent the actual structural system very well, as their calculated dynamic characteristics satisfactorily matched the observed ones from the ambient vibration test performed on a large-scale structural system subjected primarily to ambient wind excitations. The dynamic models identified by this study will be used for design of an active mass damper system to be installed on this structure fer suppressing its wind vibration.

• Parasites, Hosts and Diseases
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• v.51 no.1
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• pp.69-74
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• 2013

Leishmania tropica is one of the causative agents of leishmaniasis in humans. Routes of infection have been reported to be an important variable for some species of Leishmania parasites. The role of this variable is not clear for L. tropica infection. The aim of this study was to explore the effects of route of L. tropica infection on the disease outcome and immunologic parameters in BALB/c mice. Two routes were used; subcutaneous in the footpad and intradermal in the ear. Mice were challenged by Leishmani major, after establishment of the L. tropica infection, to evaluate the level of protective immunity. Immune responses were assayed at week 1 and week 4 after challenge. The subcutaneous route in the footpad in comparison to the intradermal route in the ear induced significantly more protective immunity against L. major challenge, including higher delayed-type hypersensitivity responses, more rapid lesion resolution, lower parasite loads, and lower levels of IL-10. Our data showed that the route of infection in BALB/c model of L. tropica infection is an important variable and should be considered in developing an appropriate experimental model for L. tropica infections.

• Food Science and Industry
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• v.51 no.1
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• pp.8-15
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• 2018

Functional food research has been struggling to demonstrate their beneficial effects in human, however, the physiological changes in humans who are in the target for functional food are very subtle and long term. In addition, it is difficult to obtain significant beneficial effect because of the necessity of using relatively healthy subjects. Relatively healthy subjects are homeostatic, and most of the biomarkers maintain a certain level under the "normal" or "resting" state. Moreover, due to wide inter-individual variation, it is difficult to detect significant changes. To address this problem, research has been actively conducted to identify the efficacy of natural products using 'omics' and 'bioinformatics' technology. In this review, we would like to introduce the human intervention studies applied homeostatic challenge model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.614-616
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• 2021

The world faces difficulties in terms of eye care, including treatment, quality of prevention, vision rehabilitation services, and scarcity of trained eye care experts. However, it is difficult to develop a method for classifying various ocular diseases because the existing dataset for retinal image disclosure does not consist of various diseases found in clinical practice. We propose a method for classifying ocular diseases using the Retinal Fundus Multi-disease Image Dataset (RFMiD), a dataset published in the ISBI-2021 challenge. Our goal is to develop a robust and generalizable model for screening retinal images into normal and abnormal categories. The performance of the proposed model shows a value of 0.9782 for the test dataset as an area under the curve (AUC) score.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.106-116
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• 2024

Ensuring robust 3D object detection is a core challenge for autonomous driving systems operating in urban environments. To tackle this issue, various 3D representation, including point cloud, voxels, and pillars, have been widely adopted, making use of LiDAR, Camera, and Radar sensors. These representations improved 3D object detection performance, but real-world urban scenarios with unexpected situations can still lead to numerous false positives, posing a challenge for robust 3D models. This paper presents a post-processing algorithm that dynamically adjusts object detection thresholds based on the distance from the ego-vehicle. While conventional perception algorithms typically employ a single threshold in post-processing, 3D models perform well in detecting nearby objects but may exhibit suboptimal performance for distant ones. The proposed algorithm tackles this issue by employing adaptive thresholds based on the distance from the ego-vehicle, minimizing false negatives and reducing false positives in the 3D model. The results show performance enhancements in the 3D model across a range of scenarios, encompassing not only typical urban road conditions but also scenarios involving adverse weather conditions.

• Journal of Arbitration Studies
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• v.23 no.3
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• pp.81-99
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• 2013

One of the most defining characteristics of arbitration is that an arbitral tribunal's jurisdiction is established by parties' mutual agreement. If a party to the arbitral proceedings believes that a tribunal constituted lacks jurisdiction to conduct the arbitral proceedings, it may challenge the jurisdiction of the tribunal in different ways. Although the concept of kompetenz-kompetenz and the grounds to challenge the Tribunal's jurisdiction are readily accepted in the arbitration community, what parties often fail to observe is the time limit imposed by the relevant laws in bringing such objections. This article aims to examine several main ways of challenging the tribunal's jurisdiction and the applicable time limits in each scenario. The article will then focus on the consequences of a party's failure to adhere to the strict time limits and its effect at the post-award stage. These issues will be considered in the light of case law from different Model law jurisdictions with particular illustrations from the arbitration law of Singapore.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.5
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• pp.548-552
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• 2015

In this paper, we describe the quadruped walking-control algorithm of the complete full-size humanoid DARPA Robotics Challenge-HUBO (DRC-HUBO) robot. Although DRC-HUBO is a biped robot, we require a quadruped walking function using two legs and two arms to overcome uneven terrains in the DRC. We design a wave-type quadruped walking pattern as a feedforward control using several walking parameters, and we design zero moment point (ZMP) controllers to maintain stable walking using an inverted pendulum model and an observed-state feedback control scheme. In particular, we propose a switching algorithm for ZMP controllers using supporting value and weighting factors in order to maintain the ZMP control performance during foot switching. Finally, we verify the proposed algorithm by performing quadruped walking experiments using DRC-HUBO.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.187-190
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• 2006

TETRA system provides the radio authentication service which permits only authorized radio to access network. Radio authentication is the process which checks the sameness of authentication-key(K) by challenge-response protocol between radio and authentication center. This paper analyzes authentication-key generation/delivery/injection model in TETRA authentication system and analyzes the threat of clone radio caused by authentication-key exposure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5287-5303
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• 2018

Handling vast amount of data found in large transactional datasets is an obvious challenge for the conventional data mining algorithms. Addressing this challenge, our paper proposes a parallel approach for proper decomposition of mining problem into sub-problems in order to find frequent patterns from these datasets. The proposed, Pattern Mining for Large Distributed Dataset (PMLDD) approach, ensures minimum dependencies as well as minimum communications among sub-problems. It establishes a linear aggregation of the intermediate results so that it can be adapted to large-scale programming models like MapReduce. In this context, an algorithmic structure for MapReduce programming model is presented. PMLDD guarantees an efficient load balancing among the sub-problems by a specific selection criterion. Further, it optimizes the number of required iterations over the dataset for mining frequent patterns as compared to the existing approaches. Finally, we believe that our approach is scalable enough to handle larger datasets in terms of performance evaluation, and the result analysis justifies all these mentioned concerns.