• Journal of Sensor Science and Technology
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• v.25 no.4
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• pp.297-301
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• 2016

ISO/IEC JTC1/SC29WG11 MPEG has been standardizing UD(user description) to give a user personalized recommendation services. Besides, CD(context description), service description(SD), and recommendation description(RD) are recently being standardized by UD Adhoc Group in MPEG with an advanced UD to cope with needs of current and upcoming services such as augmented reality and social network. The descriptions was reflected to MPEG-UD WD(Working Draft) at MPEG $107^{th}$ meeting and the document was finally approved as international standard by national bodies with standard number(ISO/IEC IS 21000-22 UD) at $114^{th}$ MPEG meeting. In addition, reference software WD to validate conformance of UD standard was approved at $113^{th}$ MPEG meeting. In this paper, we developed a demo program for visual communication according to guideline defined in reference software WD to validate the reference software as well as UD standard.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.119-124
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• 2024

Effective fire sensing is important to protect lives and property from the disaster. In this paper, we present an intelligent visual sensing method for detecting fires based on machine learning techniques. The proposed method involves a two-step process. In the first step, fire and non-fire images are used to train a convolutional neural network (CNN), and in the next step, feature vectors consisting of 256 values obtained from the CNN are used for the learning of a support vector machine (SVM). Linear and nonlinear SVMs with different parameters are intensively tested. We found that the proposed hybrid method using an SVM with a linear kernel effectively increased the recall rate of fire image detection without compromising detection accuracy when an imbalanced dataset was used for learning. This is a major contribution of this study because recall is important, particularly in the sensing of disaster situations such as fires. In our experiments, the proposed system exhibited an accuracy of 96.9% and a recall rate of 92.9% for test image data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.296-302
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• 2021

This paper proposes an approach to the classification of respiratory states of humans based on visual information. An ultra-wide-band radar sensor acquired respiration signals, and the respiratory states were classified based on two-dimensional (2D) images instead of one-dimensional (1D) vectors. The 1D vector-based classification of respiratory states has limitations in cases of various types of normal respiration. The deep neural network model was employed for the classification, and the model learned the 2D images of respiration signals. Conventional classification methods use the value of the quantified respiration values or a variation of them based on regression or deep learning techniques. This paper used 2D images of the respiration signals, and the accuracy of the classification showed a 10% improvement compared to the method based on a 1D vector representation of the respiration signals. In the classification experiment, the respiration states were categorized into three classes, normal-1, normal-2, and abnormal respiration.

• Korean journal of communication and information
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• v.54
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• pp.98-117
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• 2011

This paper is a theoretical inquiry of the changing roles of digital technologies in the representation of risk. Critically examining existing perspectives on risk society and risk communication, this paper argues that digital technologies and images in risk communication have been relatively understudied. Having said that, this paper suggests that Actor-network Theory provide useful theoretical tools for current studies on how digital technologies affect contemporary risk communication practices. Furthermore, this paper examines varied recent studies investigating how digital technologies of visualization are at play in risk communication practices. In doing so, this paper demonstrates how digital images and technologies interrupt the processes that scientific evidence is presented and facts are constructed in varied contemporary scientific reasoning. It will focus on the emerging mode of seeing and visual regime made possible by the increased usage of digital image and technologies, which are characterized by networked connection, sensor, computerized algorithm, and increased storage space. Finally this paper will discuss on the implications on future studies on the roles of digital images and technologies in risk communication practices in Korean context.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.1-18
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• 2012

This paper identifies technology trends of national research and development (national R&D) by exploiting Korean national R&D patents, ranging from 2007 to 2010. In this paper, co-word analysis (CWA), which is a method to identify the relationship among technology terms by using their co-occurrences, is incorporated into network analysis to visualize the relationships among technology keywords of national R&D patents and calculate network indexes concerning inter-relationship diversity and strength of technology keywords. As a result, this research found that inter-relationship among technology keywords in national R&D are getting increasingly strengthening in an overall sense. In addition, the keyword inter-relationship diversity-strength map proposed in this paper revealed some significant technological keywords of national R&D : core technology keywords including "sensor", "film" and "fuel" and emerging keywords including "biosensor" and "thermoelectric". Because the proposed approach helps identify interdisciplinary trends of technology keywords from a massive volume of national R&D patents in a visual and quantitative way, we expect that the approach can be incorporated as a preliminary into the R&D planning process to assist R&D policy makers to understand technology convergence of national R&D and develop relevant R&D policies.

• Journal of the Korean Society of Visualization
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• v.22 no.2
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• pp.27-34
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• 2024

In this study, we propose a novel approach for rapid and accurate pathogen detection by integrating Polydiacetylene (PDA) hydrogel sensors with advanced deep learning algorithms and visualization techniques. PDA hydrogel sensors exhibit a color transition in the presence of pathogens, enabling straightforward and quick pathogen detection. We developed a reliable pathogen detection system that combines deep neural network algorithms with color quantification technology for image-based analysis. This image-based system retains the ease of pathogen detection offered by PDA sensors while deriving quantified color standards to overcome the limitations of human visual assessment, enhancing reliability. This advancement contributes to public health and the development and application of pathogen detection technology.

• Smart Structures and Systems
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• v.19 no.2
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• pp.225-236
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• 2017

Railroad bridges in North America are an integral but aging part of the railroad network and are typically only monitored using visual inspections. When quantitative information is required for assessment, railroads often monitor bridges using accelerometers. However without a sensor to directly measure displacements, it is difficult to interpret these results as they relate to bridge performance. Digital Image Correlation (DIC) is a non-contact sensor technology capable of directly measuring the displacement of any visible bridge component. In this research, a railroad bridge was monitored under load using DIC and accelerometers. DIC measurements are directly compared to serviceability limits and it is observed that the bridge is compliant. The accelerometer data is also used to calculate displacements which are compared to the DIC measurements to assess the accuracy of the accelerometer measurements. These measurements compared well for zero-mean lateral data, providing measurement redundancy and validation. The lateral displacements from both the accelerometers and DIC at the supports were then used to determine the source of lateral displacements within the support system.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.5
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• pp.259-266
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• 2022

In this study, we developed a deep learning and vision sensor-based assembly performance evaluation method isfor prefabricated steel structures. The assembly parts were segmented using a modified version of the receptive field block convolution module inspired by the eccentric function of the human visual system. The quality of the assembly was evaluated by detecting the bolt holes in the segmented assembly part and calculating the bolt hole positions. To validate the performance of the evaluation, models of standard and defective assembly parts were produced using a 3D printer. The assembly part segmentation network was trained based on the 3D model images captured from a vision sensor. The sbolt hole positions in the segmented assembly image were calculated using image processing techniques, and the assembly performance evaluation using the k-nearest neighbor algorithm was verified. The experimental results show that the assembly parts were segmented with high precision, and the assembly performance based on the positions of the bolt holes in the detected assembly part was evaluated with a classification error of less than 5%.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1196-1204
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• 2001

In this paper, a new architecture of operating software associated with the component-based method is proposed. The proposed architecture comprises 문 execution module and a decision-making module. In order to make effective development and maintenance, the execution module is divided into three components. The components are referred to as Symbol, Gateway, and Control, respectively: The symbol component is for the GUI environments and the standard interfaces; the gateway component is for the network communication and the structure of asynchronous processes; the control component is for the asynchronous processing and machine setting or operations. In order to verify the proposed architecture, and off-line version of operating software is made, and its steps are as follows; I) Make virtual execution modules for the manufacturing devices such as dual-arm robot, handling robot, CNC, and sensor; ii) Make decision-making module; iii) Integrate the modules and GUI using a well-known development tools such as Microsofts Visual Basic; iv) Execute the overall operating software to validate the proposed architecture. The proposed software architecture in this paper has the advantages such as independent development of each module, easy development of network communication, and distributed processing of resources, and so on.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.6
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• pp.600-618
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• 2014

The metadata for urban meteorological observation is standardized through comparison with those established at the World Meteorological Organization and the Korea Meteorological Administration to understand the surrounding environment around the sites exactly and maintain the networks and sites efficiently. It categorizes into metadata for an observational network and observational sites. The latter is again divided into the metadata for station general information, local scale information, micro scale information, and visual information in order to explain urban environment in detail. The metadata also contains the static information such as urban structure, surface cover, metabolism, communication, building density, roof type, moisture/heat sources, and traffic as well as the update information on the environment change, maintenance, replacement, and/or calibration of sensors. The standardized metadata for urban meteorological observation is applied to the Weather Information Service Engine (WISE) integrated meteorological sensor network and sites installed at Incheon area. It will be very useful for site manager as well as researchers in fields of urban meteorology, radiation, surface energy balance, anthropogenic heat, turbulence, heat storage, and boundary layer processes.