• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.06a
• /
• pp.491-494
• /
• 2007

Recently, in the flow of the digital convergence and u-IT technology development, USN is expected to play a leading role. Currently, it is considered as a previous stage of an activation phase in the life cycle. However, the remarkable growth is predicted in the future. Therefore the political concern and the support are desperately needed for USN to be the core growth engine of the future IT industry. Thus, in this research, we present the condition of the national USN industry by the actual conditions of industry in 2006. And the political suggestion for the new industry monitoring element and essential element of strategy is drawn to contribute to the early activation of the national USN industry.

• Smart Structures and Systems
• /
• v.17 no.6
• /
• pp.957-980
• /
• 2016

Structural damage detection (SDD) is a challenging task in the field of structural health monitoring (SHM). As an exploring attempt to the SDD problem, a hybrid self-adaptive Firefly-Nelder-Mead (SA-FNM) algorithm is proposed for the SDD problem in this study. First of all, the basic principle of firefly algorithm (FA) is introduced. The Nelder-Mead (NM) algorithm is incorporated into FA for improving the local searching ability. A new strategy for exchanging the information in the firefly group is introduced into the SA-FNM for reducing the computation cost. A random walk strategy for the best firefly and a self-adaptive control strategy of three key parameters, such as light absorption, randomization parameter and critical distance, are proposed for preferably balancing the exploitation and exploration ability of the SA-FNM. The computing performance of the SA-FNM is evaluated and compared with the basic FA by three benchmark functions. Secondly, the SDD problem is mathematically converted into a constrained optimization problem, which is then hopefully solved by the SA-FNM algorithm. A multi-step method is proposed for finding the minimum fitness with a big probability. In order to assess the accuracy and the feasibility of the proposed method, a two-storey rigid frame structure without considering the finite element model (FEM) error and a steel beam with considering the model error are taken examples for numerical simulations. Finally, a series of experimental studies on damage detection of a steel beam with four damage patterns are performed in laboratory. The illustrated results show that the proposed method can accurately identify the structural damage. Some valuable conclusions are made and related issues are discussed as well.

• Smart Structures and Systems
• /
• v.26 no.3
• /
• pp.345-360
• /
• 2020

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

• Korean Security Journal
• /
• no.16
• /
• pp.137-159
• /
• 2008

In the 21st century, the Information Revolution caused unpredictable kinds of complications. Human society conducts a tactical network war like Swarming. Network war simultaneously consists of merits such as global monitoring and anti-dictatorship campaign, and violent demerits like terrorism. It has been becoming a generalization of terrorism of the present time to build a brotherhood and ideology to commit terrorism. This is considered as new terrorism, a form of network war. Theses days, terror organizations including Al Qaeda establish a brotherly network to commit terrorism when and where they want. New terrorism is a novel form that harms unspecified individuals. In fact, many countries have been experiencing damage from new terrorism. It is becoming an urgent issue to every country to prepare a suitable plan that cope with new terrorism. This dissertation provides defense strategy in macro and micro aspect as a responding scheme to new terrorism.

• Smart Structures and Systems
• /
• v.24 no.5
• /
• pp.669-681
• /
• 2019

Bridge collapses may deliver a huge impact on our society in a very negative way. Out of many reasons why bridges collapse, poor maintenance is becoming a main contributing factor to many recent collapses. Furthermore, the aging of bridges is able to make the situation much worse. In order to prevent this unwanted event, it is indispensable to conduct continuous bridge monitoring and timely maintenance. Visual inspection is the most widely used method, but it is heavily dependent on the experience of the inspectors. It is also time-consuming, labor-intensive, costly, disruptive, and even unsafe for the inspectors. In order to address its limitations, in recent years increasing interests have been paid to the use of unmanned aerial vehicles (UAVs), which is expected to make the inspection process safer, faster and more cost-effective. In addition, it can cover the area where it is too hard to reach by inspectors. However, this strategy is still in a primitive stage because there are many things to be addressed for real implementation. In this paper, a typical procedure of bridge inspection using UAVs consisting of three phases (i.e., pre-inspection, inspection, and post-inspection phases) and the detailed tasks by phase are described. Also, three major challenges, which are related to a UAV's flight, image data acquisition, and damage identification, respectively, are identified from a practical perspective (e.g., localization of a UAV under the bridge, high-quality image capture, etc.) and their possible solutions are discussed by examining recently developed or currently developing techniques such as the graph-based localization algorithm, and the image quality assessment and enhancement strategy. In particular, deep learning based algorithms such as R-CNN and Mask R-CNN for classifying, localizing and quantifying several damage types (e.g., cracks, corrosion, spalling, efflorescence, etc.) in an automatic manner are discussed. This strategy is based on a huge amount of image data obtained from unmanned inspection equipment consisting of the UAV and imaging devices (vision and IR cameras).

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.9
• /
• pp.57-68
• /
• 2011

Self-healing is an approach to evaluating constraints defined in target system and to applying an appropriate strategy when violating the constrains. Today, the computing environment is very complex, so researches that endow a system with the self-healing's ability that recognizes problem arising in a target system are being an important issues. However, most of the existing researches are that self-healing developers need much effort and time to analyze and model constraints. Thus, in order to improve these problems, this paper proposes the method that automatically generates monitoring module by using UML models for self-healing. The approach proposes: 1) defining system knowledge required for self-healing from UML model, 2) process for generating monitor, by using monitor generated, and process for monitoring the problems. Through these, we can reduce the efforts of self-healing developers to analyze target system, and secure monitoring scope based on information of system knowledge. Also we can minimize the efforts to develop the monitoring environment automatically. to evaluate the proposed approach, we apply proposed approach to ATM prototype system for qualitative result, and perform quantitative evaluation through video conference system in our existing research.

• Journal of Korean Society of Forest Science
• /
• v.102 no.2
• /
• pp.189-197
• /
• 2013

The Cancun Agreements under the United Nations Framework Convention on Climate Change require developing countries aiming to undertake REDD+ activities to develop a national strategy or action plan, addressing the drivers of deforestation and forest degradation, a measurement, reporting and verifying (MRV) system including forest monitoring system, and safeguards to ensure equity and co-benefits for local communities and indigenous peoples, and biodiversity. The Government of Indonesia and the Government of Norway established REDD+ cooperation through signing a 'Letter of Intent' in May, 2010. Indonesia agreed on 'a two year suspension on all new concessions for conversion of peat and natural forest'. In turn, Norway agreed to support Indonesia's REDD+ implementation efforts up to one billion United States dollars. Indonesia's REDD+ national strategy (June, 2012) accepted most of the requests included in the 'Letter of Intent'. The REDD+ national strategy, however, does not reflect requests of the Cancun Agreements which noted identification of the drivers of deforestation and forest degradation and guarantee of real greenhouse gas emissions reductions. Indonesia lays emphasis on Norwegian requests which includes expected financial support rather than the Cancun Agreements which have a weak legally-binding requirements.

• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.151-171
• /
• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Pediatric Gastroenterology, Hepatology & Nutrition
• /
• v.15 no.2
• /
• pp.63-73
• /
• 2012

Development of antiviral resistance to lamivudine is the most important factor for the treatment failure. It is necessary to establish proper guidelines to overcome drug resistance for children with chronic hepatitis B. Primary treatment with lamivudine should be considered if patients are in immune-clearance phase and have persistently elevated ALT levels more than twice the upper limit of normal value. Before initiating the therapy, careful consideration of the patient's status is required to exclude abnormal liver function tests due to other causes. The treatment option should be carefully decided to suppress the viral replication effectively. To obtain good compliance, clinicians should educate patients and their parents. Appropriate monitoring for virologic breakthrough and genotypic resistance is important in deciding to change the treatment plan. Sequential monotherapy should be avoided and a combination of drugs in other categories is recommended. New antiviral agents, such as entecavir and tenofovir, which have high potency and high genetic barrier, are soon expected to be available for use with children.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.287-290
• /
• 1996

Fault diagnosis problem is currently the subject of extensive research and numerous survey paper can be found. Although several works are studied on the fault detection and isolation observers and the residual generators, those are concerned with only the detection of actuator failures or sensor failures. So, the perfect detection and isolation is strongly required for practical applications. In this paper, a, strategy of fault diagnosis using multiple proportional integral (PI) observers including the magnitude of actuator failures is provided. It is shown that actuator failures are detected and isolated perfectly by monitoring the integrated error between actual output and estimated output by a PI observer. Also in presence of complex actuator and sensor failures, these failures are detected and isolated by multiple PI observers.