• IEIE Transactions on Smart Processing and Computing
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• v.5 no.4
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• pp.256-266
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• 2016

Concurrently detected and annotated abnormal events can have a significant impact on surveillance systems. By considering the specific domain of pedestrian trajectories, this paper presents two main contributions. First, as introduced in much of the work on trajectory-based anomaly detection in the literature, only information about pedestrian paths, such as direction and speed, is considered. Differing from previous work, this paper proposes a framework that deals with additional types of trajectory-based anomalies. These abnormal events take places when a person enters prohibited areas. Those restricted regions are constructed by an online learning algorithm that uses surrounding information, including detected pedestrians and background scenes. Second, a simple data-boosting technique is introduced to overcome a lack of training data; such a problem particularly challenges all previous work, owing to the significantly low frequency of abnormal events. This technique only requires normal trajectories and fundamental information about scenes to increase the amount of training data for both normal and abnormal trajectories. With the increased amount of training data, the conventional abnormal trajectory classifier is able to achieve better prediction accuracy without falling into the over-fitting problem caused by complex learning models. Finally, the proposed framework (which annotates tracks that enter prohibited areas) and a conventional abnormal trajectory detector (using the data-boosting technique) are integrated to form a united detector. Such a detector deals with different types of anomalous trajectories in a hierarchical order. The experimental results show that all proposed detectors can effectively detect anomalous trajectories in the test phase.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.765-768
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• 2012

Recently, the supply ratio of smart devices application has become increasable, utilization of device increases constantly. At the same time, used application is more gentrified. However, using time of devices is decreased. To solve these problems, many research is studying about the hardware/software. One of them is profiling power consumption by process units. The process can be managed, based on measured energy consumption data. These means that it can efficiently use the residual energy. Application at the stage of program design can analyze and used-energy using the trace by considering the low-power can design. In this paper, we studied software-based power-metering framework for android platform. We survey each process-level power consumption measurement techniques, compare advantages and disadvantages of the technique and propose improved measures.

• Smart Structures and Systems
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• v.26 no.4
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• pp.495-506
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• 2020

Monitoring of complex processes faces several challenges mainly due to the lack of relevant sensory information or insufficient elaborated decision-making strategies. These challenges motivate researchers to adopt complex data processing and analysis in order to improve the process representation. This paper presents the development and implementation of quality monitoring framework based on a model-driven approach using embedded artificial intelligence strategies. In this work, the strategies are applied to the supervision of a microfabrication process aiming at showing the great performance of the framework in a very complex system in the manufacturing sector. The procedure involves two methods for modelling a representative quality variable, such as surface roughness. Firstly, the hybrid incremental modelling strategy is applied. Secondly, a generalized fuzzy clustering c-means method is developed. Finally, a comparative study of the behavior of the two models for predicting a quality indicator, represented by surface roughness of manufactured components, is presented for specific manufacturing process. The manufactured part used in this study is a critical structural aerospace component. In addition, the validation and testing are performed at laboratory and industrial levels, demonstrating proper real-time operation for non-linear processes with relatively fast dynamics. The results of this study are very promising in terms of computational efficiency and transfer of knowledge to manufacturing industry.

• Journal of Digital Convergence
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• v.13 no.3
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• pp.201-208
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• 2015

Recently computer, smart phone, medical devices, etc has become used in a variety of environments as the application fields of IT products have become diversification. Attack case of abuse of software security vulnerabilities is on the increase as the application fields of software have become diversification. Accordingly, secure coding program is of a varied but history management, updating, API module to be vulnerable to attack. Thus, this paper proposed a materialization of CMS linked system to enable check the vulnerability of the source code to content unit for secure software development, configuration management system that interwork on the transmission module. Implemented an efficient coding system secure way that departmentalized by the function of the program and by analyzing and applying secure coding standards.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.7
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• pp.587-594
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• 2013

With the development of web 2.0 and the rapid diffusion of smart devices, current web service, which only provides very limited information and service, has been transformed into user-friendly and comprehensive web service called mash-up service. Mash-up service is defined as comprehensive service that is created by combining variety of web services. When composing a mesh-up service, Open API is used as web service interface. Current mash-up service, however, has fundamental problem in that it could not satisfy the various needs of users who want I-centric personalized service because it is developed and provided by service developers. To overcome these obstacles, a lot of studies on mesh-up framework are being performed for improving mash-up proess though, it is still in beginning stage. In this paper, we introduce an API selection and compostion method as the key technology for mesh-up framework that support the automatic creation of mesh-up service.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.103-111
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• 2013

This paper provide a framework for an IGILMS(internet-based global integrated logistics management system) which can access and mediate cargo transportations among small- and medium-sized domestic/international logistics corporations as regards cargo, registration and search for space, public tender and negotiation, contract, payment and safety-guarantee, transportation through the internet, wireless communication means, or smart phone etc. In addition, we describe a model to provide customized services in the B2B e-market for IGILMS and the structure and the control of its fulfillment process, and provide technical architecture of the IGILMS for an internet-based global logistics management system. To validate an efficiency of the proposed system, we develop a simulation model and analyze the performance of the proposed system.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.109-119
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• 2015

The interaction between wireless sensors such as Internet of Things (IoT) and Cloud is a new paradigm of communication virtualization to overcome resource and efficiency restriction. Cloud computing provides unlimited platform, resources, services and also covers almost every area of computing. On the other hand, Wireless Sensor Networks (WSN) has gained attention for their potential supports and attractive solutions such as IoT, environment monitoring, healthcare, military, critical infrastructure monitoring, home and industrial automation, transportation, business, etc. Besides, our virtual groups and social networks are in main role of information sharing. However, this sensor network lacks resource, storage capacity and computational power along with extensibility, fault-tolerance, reliability and openness. These data are not available to community groups or cloud environment for general purpose research or utilization yet. If we reduce the gap between real and virtual world by adding this WSN driven data to cloud environment and virtual communities, then it can gain a remarkable attention from all over, along with giving us the benefit in various sectors. We have proposed a Pub/Sub-based sensor virtualization framework Cloud environment. This integration provides resource, service, and storage with sensor driven data to the community. We have virtualized physical sensors as virtual sensors on cloud computing, while this middleware and virtual sensors are provisioned automatically to end users whenever they required. Our architecture provides service to end users without being concerned about its implementation details. Furthermore, we have proposed an efficient content-based event matching algorithm to analyze subscriptions and to publish proper contents in a cost-effective manner. We have evaluated our algorithm which shows better performance while comparing to that of previously proposed algorithms.

• Smart Structures and Systems
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• v.17 no.1
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• pp.149-165
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• 2016

Floods have been known to be one of the main causes of bridge collapse. Contrary to earthquakes, flood events tend to occur repeatedly and more frequently in rainfall areas; flood-induced damage and collapse account for a significant portion of disasters in many countries. Nevertheless, in contrast to extensive research on the seismic fragility analysis for civil infrastructure, relatively little attention has been devoted to the flood-related fragility. The present study proposes a novel methodology for deriving flood fragility curves for bridges. Fragility curves are generally derived by means of structural reliability analysis, and structural failure modes are defined as excessive demands of the displacement ductility of a bridge under increased water pressure resulting from debris accumulation and structural deterioration, which are known to be the primary causes of bridge failures during flood events. Since these bridge failure modes need to be analyzed through sophisticated structural analysis, flood fragility curve derivation that would require repeated finite element analyses may take a long time. To calculate the probability of flood-induced failure of bridges efficiently, in the proposed framework, the first order reliability method (FORM) is employed for reducing the required number of finite element analyses. In addition, two software packages specialized for reliability analysis and finite element analysis, FERUM (Finite Element Reliability Using MATLAB) and ABAQUS, are coupled so that they can exchange their inputs and outputs during structural reliability analysis, and a Python-based interface for FERUM and ABAQUS is newly developed to effectively coordinate the fragility analysis. The proposed framework of flood fragility analysis is applied to an actual reinforced concrete bridge in South Korea to demonstrate the detailed procedure of the approach.

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.467-478
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• 2002

With the rapid development of wired or wireless Internet, various kinds of resource constrained mobile devices, such as cellular phone, PDA, homepad, smart phone, handhold PC, and so on, have been emerging into personal or commercial usages. Most software to be embedded into those devices has been forced to have the characteristic of flexibility rather than the fixedness which was an inherent property of embedded system. It means that recent technologies require the flexible embedding into the variety of resource constrained mobile devices. A document processor for XML which has been positioned as a standard mark-up language for information representation on the Web, is one of the essential software to be embedded into those devices for browsing the information. In this paper, a framework for configurable XML processor called EmXJ is designed and implemented for flexible embedding into various types of resource constrained mobile devices, and its advantages are compared to conventional XML processors.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.233-240
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• 2019

In order to predict and respond to cyber attacks, a number of security companies quickly identify the methods, types and characteristics of attack techniques and are publishing Security Intelligence Reports(SIRs) on them. However, the SIRs distributed by each company are huge and unstructured. In this paper, we propose a framework that uses five analytic techniques to formulate a report and extract key information in order to reduce the time required to extract information on large unstructured SIRs efficiently. Since the SIRs data do not have the correct answer label, we propose four analysis techniques, Keyword Extraction, Topic Modeling, Summarization, and Document Similarity, through Unsupervised Learning. Finally, has built the data to extract threat information from SIRs, analysis applies to the Named Entity Recognition (NER) technology to recognize the words belonging to the IP, Domain/URL, Hash, Malware and determine if the word belongs to which type We propose a framework that applies a total of five analysis techniques, including technology.