• Structural Engineering and Mechanics
• /
• v.33 no.3
• /
• pp.325-337
• /
• 2009

Structural damage detection, damage localization and severity estimation of jacket platforms, based on calculating modal strain energy is presented in this paper. In the structure, damage often causes a loss of stiffness in some elements, so modal parameters; mode shapes and natural frequencies, in the damaged structure are different from the undamaged state. Geometrical location of damage is detected by computing modal strain energy change ratio (MSECR) for each structural element, which elements with higher MSECR are suspected to be damaged. For each suspected damaged element, by computing cross-modal strain energy (CMSE), damage severity as the stiffness reduction factor -that represented the ratios between the element stiffness changes to the undamaged element stiffness- is estimated. Numerical studies are demonstrated for a three dimensional, single bay, four stories frame of the existing jacket platform, based on the synthetic data that generated from finite element model. It is observed that this method can be used for damage detection of this kind of structures.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.5
• /
• pp.2610-2628
• /
• 2019

Advanced persistent threats (APTs) are constant attacks of specific targets by hackers using intelligent methods. All current internal infrastructures are constantly subject to APT attacks created by external and unknown malware. Therefore, information security officers require a framework that can assess whether information security systems are capable of detecting and blocking APT attacks. Furthermore, an on-line evaluation of information security systems is required to cope with various malicious code attacks. A regular evaluation of the information security system is thus essential. In this paper, we propose a dynamic updated evaluation framework to improve the detection rate of internal information systems for malware that is unknown to most (over 60 %) existing static information security system evaluation methodologies using non-updated unknown malware.

• Journal of Korea Multimedia Society
• /
• v.21 no.2
• /
• pp.261-270
• /
• 2018

Hearing-impaired people are increasing rapidly due to the global aging trend. Early detection of hearing loss requires an easy-to-use audiometry device for the public. Existing audiometry systems were developed as PC-based, PDA-based, or smartphone apps. These devices were often dependent on specific software platforms and hardware platforms. In this paper, we tried to improve software platform compatibility by using cross platform, and tried to implement IoT-based pure tone audiometry device which does not require sound pressure level correction due to hardware differences. Pure tone audiometry is available in a variety of ways depending on the type of hearing loss and age. Using the IoT-based audiometry device implemented in this paper, it will be possible for an app developer who lacks hardware knowledge to easily develop an app with various scenarios for hearing screening. The results of this study will contribute to overcoming the software and hardware dependency in the development of IoT-based healthcare device.

• The Journal of Korea Robotics Society
• /
• v.15 no.2
• /
• pp.197-204
• /
• 2020

In this paper, we present a learning platform for robotic grasping in real world, in which actor-critic deep reinforcement learning is employed to directly learn the grasping skill from raw image pixels and rarely observed rewards. This is a challenging task because existing algorithms based on deep reinforcement learning require an extensive number of training data or massive computational cost so that they cannot be affordable in real world settings. To address this problems, the proposed learning platform basically consists of two training phases; a learning phase in simulator and subsequent learning in real world. Here, main processing blocks in the platform are extraction of latent vector based on state representation learning and disentanglement of a raw image, generation of adapted synthetic image using generative adversarial networks, and object detection and arm segmentation for the disentanglement. We demonstrate the effectiveness of this approach in a real environment.

• International Journal of Contents
• /
• v.16 no.1
• /
• pp.75-86
• /
• 2020

As the elderly population is becoming an aging society, the elderly are experiencing many problems. Social security costs for the elderly are increasing and the un-linked social phenomenon is emerging. Thus, the social infrastructure and welfare system established in the past economic growth period are in danger of not functioning properly. People socially isolated or with chronic diseases among the elderly are exposed to various accidents. Thus, an active healthcare management service is imperative. Additionally, in the event of a dangerous situation, the system must have ways to notify guardians (family or medical personnel) regarding appropriate action. Thus, in this paper, we propose the smartphone-based healthcare and emergency response service platform. The proposed service platform aggregates movement of relevant data in real-time using a smartphone. Based on aggregated data, it will always recognize the user's movements and current state using the human motion recognition mechanism. Thus, the proposed service platform provides real-time status monitoring, activity reports, a health calendar, location-based hospital information, emergency situation detection, and cloud messaging server-based efficient notification to several subscribers such as family, guardians, and medical personnel. Through this service, users or guardians can augment the level of care for the elderly through the reports. Also, if an emergency situation is detected, the system immediately informs guardians so as to minimize the risk through immediate response.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.1
• /
• pp.237-242
• /
• 2017

This paper presents development of the transponder system which provides an accurate train position, especially for supporting 400km/h high speed train. Here, we analyzed an operating frequency band of the transponder system which can be interoperable with the Eurobalise system already installed in Korea railroad as to be used for the automatic train protection (ATP). By investigating the power frequency band and its data frequency band of the transponder system, we presents the adoptable frequency band for the developed transponder system. Additionally, through the real testbed using HEMU-430X, we evaluate its performance requirement and shows interoperable operation with the Eurobalise system.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.23 no.3
• /
• pp.479-490
• /
• 2013

Recently, the number of attacks by malicious application has significantly increased, targeting Android-platform mobile terminal such as Samsung Galaxy Note and Galaxy Tab 10.1. The malicious application can be distributed to currently used mobile devices through open market masquerading as an normal application. An attacker inserts malicious code into an application, which might threaten privacy by rooting attack. Once the rooting attack is successful, malicious code can collect and steal private data stored in mobile terminal, for example, SMS messages, contacts list, and public key certificate for banking. To protect the private information from the malicious attack, malicious code detection, rooting attack detection and countermeasure method are required. To meet this end, this paper investigates rooting attack mechanism for Android-platform mobile terminal. Based on that, this paper proposes countermeasure system that enables to extract and collect events related to attacks occurring from mobile terminal, which contributes to active protection from malicious attacks.

• Animal Bioscience
• /
• v.36 no.6
• /
• pp.973-979
• /
• 2023

Objective: The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system, which is the most efficient and reliable tool for precisely targeted modification of the genome of living cells, has generated considerable excitement for industrial applications as well as scientific research. In this study, we developed a gene-editing and detection system for chick embryo sexing during the embryonic stage. Methods: By combining the CRISPR/Cas9 technical platform and germ cell-mediated germline transmission, we not only generated Z chromosome-targeted knockin chickens but also developed a detection system for fluorescence-positive male chicks in the embryonic stage. Results: We targeted a green fluorescent protein (GFP) transgene into a specific locus on the Z chromosome of chicken primordial germ cells (PGCs), resulting in the production of Z^GFP-knockin chickens. By mating Z^GFP-knockin females (Z^GFP/W) with wild males (Z/Z) and using a GFP detection system, we could identify chick sex, as the GFP transgene was expressed on the Z chromosome only in male offspring (Z^GFP/Z) even before hatching. Conclusion: Our results demonstrate that the CRISPR/Cas9 technical platform with chicken PGCs facilitates the production of specific genome-edited chickens for basic research as well as practical applications.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.2
• /
• pp.610-630
• /
• 2020

A large number of people suffered from traffic accidents each year, so people pay more attention to traffic safety. However, the traditional methods use laser sensors to calculate the vehicle distance at a very high cost. In this paper, we propose a method based on deep learning to calculate the vehicle distance with a monocular camera. Our method is inexpensive and quite convenient to deploy on the mobile platforms. This paper makes two contributions. First, based on Light-Head RCNN, we propose a new vehicle detection framework called Light-Car Detection which can be used on the mobile platforms. Second, the planar homography of projective geometry is used to calculate the distance between the camera and the vehicles ahead. The results show that our detection system achieves 13FPS detection speed and 60.0% mAP on the Adreno 530 GPU of Samsung Galaxy S7, while only requires 7.1MB of storage space. Compared with the methods existed, the proposed method achieves a better performance.

• Journal of Information Processing Systems
• /
• v.14 no.1
• /
• pp.239-251
• /
• 2018

In existing cloud services, information security and privacy concerns have been worried, and have become one of the major factors that hinder the popularization and promotion of cloud computing. As the cloud computing infrastructure, the security of virtual machine systems is very important. This paper presents an immune-inspired intrusion detection model in virtual machines of cloud computing environment, denoted I-VMIDS, to ensure the safety of user-level applications in client virtual machines. The model extracts system call sequences of programs, abstracts them into antigens, fuses environmental information of client virtual machines into danger signals, and implements intrusion detection by immune mechanisms. The model is capable of detecting attacks on processes which are statically tampered, and is able to detect attacks on processes which are dynamically running. Therefore, the model supports high real time. During the detection process, the model introduces information monitoring mechanism to supervise intrusion detection program, which ensures the authenticity of the test data. Experimental results show that the model does not bring much spending to the virtual machine system, and achieves good detection performance. It is feasible to apply I-VMIDS to the cloud computing platform.