• ETRI Journal
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• v.41 no.4
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• pp.494-505
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• 2019

In this paper, we propose a new framework for detecting the unauthorized dumping of garbage in real-world surveillance camera. Although several action/behavior recognition methods have been investigated, these studies are hardly applicable to real-world scenarios because they are mainly focused on well-refined datasets. Because the dumping actions in the real-world take a variety of forms, building a new method to disclose the actions instead of exploiting previous approaches is a better strategy. We detected the dumping action by the change in relation between a person and the object being held by them. To find the person-held object of indefinite form, we used a background subtraction algorithm and human joint estimation. The person-held object was then tracked and the relation model between the joints and objects was built. Finally, the dumping action was detected through the voting-based decision module. In the experiments, we show the effectiveness of the proposed method by testing on real-world videos containing various dumping actions. In addition, the proposed framework is implemented in a real-time monitoring system through a fast online algorithm.

• Journal of Information Science Theory and Practice
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• v.7 no.1
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• pp.52-71
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• 2019

An insider threat is a threat that comes from people within the organization being attacked. It can be described as a function of the motivation, opportunity, and capability of the insider. Compared to managing the dimensions of opportunity and capability, assessing one's motivation in committing malicious acts poses more challenges to organizations because it usually involves a more obtrusive process of psychological examination. The existing body of research in psycholinguistics suggests that automated text analysis of electronic communications can be an alternative for predicting and detecting insider threat through unobtrusive behavior monitoring. However, a major challenge in employing this approach is that it is difficult to minimize the risk of missing any potential threat while maintaining an acceptable false alarm rate. To deal with the trade-off between the risk of missed catches and the false alarm rate, we propose a unified psycholinguistic framework that consolidates multiple text analyzers to carry out sentiment analysis, emotion analysis, and topic modeling on electronic communications for unobtrusive psychological assessment. The user scenarios presented in this paper demonstrated how the trade-off issue can be attenuated with different text analyzers working collaboratively to provide more comprehensive summaries of users' psychological states.

• Smart Structures and Systems
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• v.30 no.1
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• pp.17-34
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• 2022

For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.

• ETRI Journal
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• v.44 no.2
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• pp.183-193
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• 2022

Smart cities are expected to provide residents with convenience via various agents such as CCTV, delivery robots, security robots, and unmanned shuttles. Environmental data collected by various agents can be used for various purposes, including advertising and security monitoring. This study suggests a surveillance map data framework for efficient and integrated multimodal data representation from multi-agents. The suggested surveillance map is a multilayered global information grid, which is integrated from the multimodal data of each agent. To confirm this, we collected surveillance map data for 4 months, and the behavior patterns of humans and vehicles, distribution changes of elevation, and temperature were analyzed. Moreover, we represent an anomaly detection algorithm based on a surveillance map for security service. A two-stage anomaly detection algorithm for unusual situations was developed. With this, abnormal situations such as unusual crowds and pedestrians, vehicle movement, unusual objects, and temperature change were detected. Because the surveillance map enables efficient and integrated processing of large multimodal data from a multi-agent, the suggested data framework can be used for various applications in the smart city.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.295-311
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• 2023

Cloud computing has evolved significantly, intending to provide users with fast, dependable, and low-cost services. With its development, malicious users have become increasingly capable of attacking both its internal and external security. To ensure the security of cloud services, encryption, authorization, firewalls, and intrusion detection systems have been employed. However, these single monitoring agents, are complex, time-consuming, and they do not detect ransomware and zero-day vulnerabilities on their own. An innovative Record and Replay-based hybrid Honeynet (R2NET) system has been developed to address this issue. Combining honeynet with Record and Replay (RR) technology, the system allows fine-grained analysis by delaying time-consuming analysis to the replay step. In addition, a machine learning algorithm is utilized to cluster the logs of attackers and store them in a database. So, the accessing time for analyzing the attack may be reduced which in turn increases the efficiency of the proposed framework. The R2NET framework is compared with existing methods such as EEHH net, HoneyDoc, Honeynet system, and AHDS. The proposed system achieves 7.60%, 9.78%%, 18.47%, and 31.52% more accuracy than EEHH net, HoneyDoc, Honeynet system, and AHDS methods.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.348-366
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• 2007

Capacity of modem storage devices is becoming larger than yesterday and integration of disk is increasing. It refers that physical errors can damage a lot of digital information on storage devices. So we propose file system test framework in this paper to test integrity and robustness of file systems. We develop the tool for generating bad sectors on disks and the tool which creates all physical errors defined in storage devices. We also develop the tool for immediately monitoring the condition of read and write execution on storage devices. So, by integrating those tools, we develop FORT, test framework for confirming robustness of file system. We analyze robustness of ext3 file systems by FORT. Lastly, we present draft of intelligent system merging file system and device driver's layer architecture.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.45-55
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• 2012

Electronic data management is getting important to reduce overall cost and run-time of clinical data management with the enhancement of data quality. It also critically needs to meet regulated guidelines for the overall quality and safety of electronic clinical trials. The purpose of this paper is to develop the performance evaluation framework in electronic clinical data management. Four key metrics in the area of infrastructure, intellectual preparation, study implementation and study completion covering major aspects of clinical trial processes are proposed. The performance measures evaluate the extent of regulation compliance, data quality, cost and efficiency of electronic data management process. They also provide measurement indicators for each evaluation items. Based on the key metrics, the performance evaluation framework is developed in three major areas involved in clinical data management - clinical site, monitoring and data coordinating center. As of the initial attempt how to evaluate the extent of electronic data management in clinical trials by Delphi survey, further empirical studies are planned and recommended.

• Environmental Engineering Research
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• v.15 no.2
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• pp.105-109
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• 2010

The European Union (EU) Water Framework Directive (WFD) (2000/60/EC) was transposed into Irish law by Statutory Instrument Nos. 722 of 2003, 413 of 2005 and 218 of 2009, which set out a new strategy and process to protect and enhance Ireland's water resources and water-dependent ecosystems. The Directive requires a novel, holistic, integrated, and iterative process to address Ireland's natural waters based on a series of six-year planning cycles. Key success factors in implementing the Directive include an in-depth and balanced treatment of the ecological, economic, institutional and cultural aspects of river basin management planning. Introducing this visionary discipline for the management of sustainable water resources requires a solemn commitment to a new mindset and an overarching monitoring and management regime which hitherto has never been attempted in Ireland. The WFD must be implemented in conjunction with a myriad of complimentary directives and associated legislation, addressing such key related topics as flood/drought management, biodiversity protection, land use planning, and water/wastewater and diffuse pollution engineering and regulation. The critical steps identified for river basin management planning under the WFD include: 1) characterization and classification of water bodies (i.e., how healthy are Irish waters?), 2) definition of significant water pressures (e.g., agriculture, forestry, septic tanks), 3) enhancement of measures for designated protected areas, 4) establishment of objectives for all surface and ground waters, and 5) integrating these critical steps into a comprehensive and coherent river basin management plan and associated programme of measures. A parallel WFD implementation programme critically depends on an effective environmental management system (EMS) approach with a plan-do-check-act cycle applied to each of the evolving six-year plans. The proactive involvement of stakeholders and the general public is a key element of this EMS approach.

• Korean Journal of Construction Engineering and Management
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• v.12 no.1
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• pp.85-96
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• 2011

The access monitoring and control system of vehicles involved in construction logistics has been evolved from paper-based through bar code-based and to RFID-based management with pursuing automatic data collection and management. However, existing management methods have a limit that they still need manpower allocation for access control of vehicles. Therefore this research has proposed an framework that includes devices and an information system for effective and efficient data collection for access control of vehicles for construction logistics. And the proposed framework has been verified through a laboratory test using a prototype system developed in this research. It is expected that the installation methods of RFID antenna and tag for the framework could be applied to not only the access control of construction site but also various RFID applications at construction sites.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.3
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• pp.380-393
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• 2015

This study presents how we can evaluate stereo camera systems for the structural deformation monitoring. A stereo camera system, consisting of a set of stereo cameras and reflective markers attached on the structure, is introduced for the measurement and the stereo pattern recognition (SPR) method is utilized for the full-field structural deformation estimation. Performance of this measurement system depends on many parameters including types and specifications of the cameras, locations and orientations of them, and sizes and positions of markers; it is difficult to experimentally identify the effects of each parameter on the measurement performance. In this study, a simulation framework for evaluating performance of the stereo camera systems with various parameters has been developed. The maximum normalized root-mean-square (RMS) error is defined as a representative index of stereo camera system performance. A plate structure is chosen for an introductory example. Its several modal harmonic vibrations are generated and estimated in the simulation framework. Two cases of simulations are conducted to see the effects of camera locations and the resolutions of the cameras. An experimental validation is carried out for a few selected cases from the simulations. Using the simultaneous laser displacement sensor (LDS) measurements as the reference, the measurement errors are obtained and compared with the simulations.