• Journal of Environmental Health Sciences
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• v.50 no.4
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• pp.291-301
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• 2024

Background: Based on rapid industrial development, environmental pollution has emerged as a social problem and exposure to environmental diseases is increasing. The number of patients suffering environmental diseases in Daejeon Metropolitan City is also steadily increasing, and the prevalence of atopic dermatitis there is the highest in the country. Objectives: In order to minimize exposure to harmful factors for the prevention and management of environmental diseases, an environmental disease management system suitable for the environmental characteristics of each region is needed. Basic preliminary research should be conducted to identify environmental hazards in Daejeon Metropolitan City and establish a management system. Methods: Among the households (about 50 people) participating in the 2022 Indoor Environment Remote Measurement (IoT) program, households (children aged 5 or older and adults) with insufficient results for indoor air quality measurement and symptoms related to environmental diseases were selected. The subjects were tested for living conditions, blood tests, biomarker analysis (immunoglobulin E, Eosinophil count, histamine) and multiple allergy antigen tests (MAST, 93 types). Results: Participants were 53.7% female and 46.3% male, and the average age showed an even age distribution. IgE and eosinophil count were positively correlated, and significant results were found for atopic dermatitis and IgE (p<0.05). Typical risk factors observed in the survey was the amount of indoor ventilation, chemical exposure, heredity, house dust mites, fungi, and food. Conclusions: The purpose of this study was to help establish a regional management system for environmental diseases, research and diagnosis of environmental diseases. This study is meaningful in that it is a study with customized consulting suitable for the environment of Daejeon Metropolitan City. If the limitations are addressed and continuous research is conducted, it will be helpful for the management, diagnosis, and research of environmental diseases.

• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.4
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• pp.189-198
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• 2015

Most IoT-related approaches have tried to establish the relation by connecting the network between things. The proposed research will present how the pervasive interaction of eco-system formed by touching the objects between humans and things can be recognized on purpose. By collecting and sharing the detected patterns among all kinds of things, we can construct the environment which enables individualized interactions of different objects. To perform the aforementioned, we are going to utilize technical procedures such as event-driven signal processing, pattern matching for signal recognition, and hardware in the loop simulation. We will also aim to implement the prototype of sensor processor based on Arduino MCU, which can be integrated with system using Arduino-Matlab/Simulink hybrid-interoperation environment. In the experiment, we use piezo transducer to detect the vibration or vibrates the surface using acoustic wave, which has specific frequency spectrum and individualized signal shape in terms of time axis. The signal distortion in time and frequency domain is recorded into memory tracer within sensor processor to extract the meaningful pattern by comparing the stored with lookup table(LUT). In this paper, we will contribute the initial prototypes for the acoustic touch processor by using off-the-shelf MCU and the integrated framework based on Matlab/Simulink model to provide the individualization of the touch-sensing for the user on purpose.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.11-17
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• 2020

This paper proposed the design of a new window signage system architecture, which utilized a window of a building, with attached LED for visible light communication. In this paper, the proposed method using the LED strip to transmit light data and receive the data through a HMD with a smart device camera. The LED strip attached to the existing building window, as a part of semi-transparent signage. Semi-transparent signage based on a controllable LED strip-modules and attached to the window used to provide entertainment contents and the information service to people through optical camera communication (OCC) as well. Also, this work suggests using the camera supplied Head Mounted Device (HMD) as an OCC receiver. The LED attached window signage system structure described in this paper can be utilized in various buildings infrastructure like house, shopping areas, industrial building, etc.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2167-2175
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• 2017

In recent years, an IoT is dramatically developing according to the enhancement of AI, the increase of connected devices, and the high-performance cloud systems. Huge data produced by many devices and sensors is expanding the scope of services, such as an intelligent diagnostics, a recommendation service, as well as a smart monitoring service. The studies of edge computing are limited as a role of small server system with high quality HW resources. However, there are specialized requirements in a smart factory domain needed edge computing. The edges are needed to pre-process containing tiny filtering, pre-formatting, as well as merging of group contexts and manage the regional rules. So, in this paper, we extract the features and requirements in a scope of efficiency and robustness. Our edge offers to decrease a network resource consumption and update rules and learning models. Moreover, we propose architecture of edge computing based on learning factors sharing with a cloud system in a smart factory.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.539-554
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• 2018

Effective interaction between user and device is considered an important ability of IoT devices. For some applications, it is necessary to recognize human facial expressions in real time and make accurate judgments in order to respond to situations correctly. Therefore, many researches on facial image analysis have been preceded in order to construct a more accurate and faster recognition system. In this study, we constructed an automatic recognition system for facial expressions through two steps - a facial recognition step and a classification step. We compared various models with different sets of data with pixel information, landmark coordinates, Euclidean distances among landmark points, and arctangent angles. We found a fast and efficient prediction model with only 30 principal components of face landmark information. We applied several prediction models, that included linear discriminant analysis (LDA), random forests, support vector machine (SVM), and bagging; consequently, an SVM model gives the best result. The LDA model gives the second best prediction accuracy but it can fit and predict data faster than SVM and other methods. Finally, we compared our method to Microsoft Azure Emotion API and Convolution Neural Network (CNN). Our method gives a very competitive result.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.203-210
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• 2019

Recently, a number of researchers have produced research and reports in order to forecast more exactly air quality such as particulate matter and odor. However, such research mainly focuses on the atmospheric diffusion models that have been used for the air quality prediction in environmental engineering area. Even though it has various merits, it has some limitation in that it uses very limited spatial attributes such as geographical attributes. Thus, we propose the new approach to forecast an air quality using a deep learning based ensemble model combining temporal and spatial predictor. The temporal predictor employs the RNN LSTM and the spatial predictor is based on the geographically weighted regression model. The ensemble model also uses the RNN LSTM that combines two models with stacking structure. The ensemble model is capable of inferring the air quality of the areas without air quality monitoring station, and even forecasting future air quality. We installed the IoT sensors measuring PM2.5, PM10, H2S, NH3, VOC at the 8 stations in Jeonju in order to gather air quality data. The numerical results showed that our new model has very exact prediction capability with comparison to the real measured data. It implies that the spatial attributes should be considered to more exact air quality prediction.

• Journal of Digital Convergence
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• v.16 no.4
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• pp.307-312
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• 2018

This paper deals with the role and direction of design in the era of 4th industrial revolution. In addition to understanding the whole of science and technology such as Artificial Intelligence, Internet of Things, Cyber Physical System, 3D printer and Bio which are leading technology of the $4^{th}$ industrial revolution, this thesis is seeking direction of design that makes human life and society comfortable and convenient. The design in the 4th Industrial Revolution must be at the center of society and human being. Therefore, the design using ICT technology is also applied to the emotional design that stimulates human emotion warmly through in-depth study on society and human culture and environment. Through the above research, the design that has continued to evolve along with the development of technology continues to play a role as a design in which human emotion is alive.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.6
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• pp.745-753
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• 2016

This paper presents a fully synthesizable low power interconnect bus for millimeter-scale wireless sensor nodes. A segmented ring bus topology minimizes the required chip real estate with low input/output pad count for ultra-small form factors. By avoiding the conventional open drain-based solution, the bus can be fully synthesizable. Low power is achieved by obviating a need for local oscillators in member nodes. Also, aggressive power gating allows low-power standby mode with only 53 gates powered on. An integrated wakeup scheme is compatible with a power management unit that has nW standby mode. A 3-module system including the bus is fabricated in a 180 nm process. The entire system consumes 8 nW in standby mode, and the bus achieves 17.5 pJ/bit/chip.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.7
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• pp.659-664
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• 2016

In this paper, we suggest operational trans-conductance amplifier(OTA) for current-mode FIR filter that can be used in a digital circuit system requiring high operating frequency and low power consumption. The current-mode signal processing is one of the very innovative design method for a low power consumption system with high operating frequency because it shows a constant power regardless of frequency. From the simulation result using 0.35um CMOS process, when Vdd is 2V, it is confirmed that the proposed circuit showed the dynamic range of the about 1V, about 50% of supply voltage and output current swing of about 0~200uA. Also, the power consumption was evaluated with about 21uW and the active size for an integration was measured with $71um{\times}166um$.