• Journal of the Korean Society of Safety
• /
• v.33 no.6
• /
• pp.85-92
• /
• 2018

This study aimed to reduce of traps incident of metro train door by suggesting preventive actions throughout analyzing why railway drivers and passengers commit unsafe behaviors which are human factors making occurrence of the incidents. The incident cases were analyzed and Incident Tree was structured by brainstorming with safety experts. In addition, the questionnaire survey was conducted for comparison with the analysis results. As the result, this study suggested driver's factors, passenger's factors, and public relation plan for safe use of metro in order to reduce the frequency of the incidents. For driver's factors, implementing job-rotation systems between railway and non-railway drivers, installing Object Detection Sensors between the metro doors and PSD, and flexible operation of dwell time were suggested. For passenger's factors, placing a platform safety person, installing a safety fence in front of the stairs and the elevators, and country wide public relations through mass media were suggested.

• Microbiology and Biotechnology Letters
• /
• v.48 no.4
• /
• pp.574-581
• /
• 2020

Next generation sequencing is commonly used to characterize the microbiome structure. MiSeq is commonly used to analyze the microbiome due to its relatively long read length. However, recently, Illumina introduced the 250x2 chip for HiSeq 2500. The purpose of this study was to compare the performance of MiSeq and HiSeq in the context of oral microbiome samples. The MiSeq Reagent Kit V3 and the HiSeq Rapid SBS Kit V2 were used for MiSeq and HiSeq 2500 analyses, respectively. Total read count, read quality score, relative bacterial abundance, community diversity, and relative abundance correlation were analyzed. HiSeq produced significantly more read sequences and assigned taxa compared to MiSeq. Conversely, community diversity was similar in the context of MiSeq and HiSeq. However, depending on the relative abundance, the correlation between the two platforms differed. The correlation between HiSeq and MiSeq sequencing data for highly abundant taxa (> 2%), low abundant taxa (2-0.2%), and rare taxa (0.2% >) was 0.994, 0.860, and 0.416, respectively. Therefore, HiSeq 2500 may also be compatible for microbiome studies. Importantly, the HiSeq platform may allow a high-resolution massive parallel sequencing for the detection of rare taxa.

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.1-10
• /
• 2021

Cyberbullying has become a severe issue and brought a powerful impact on the cyber world. Due to the low cost and fast spreading of news, social media has become a tool that helps spread insult, offensive, and hate messages or opinions in a community. Detecting cyberbullying from social media is an intriguing research topic because it is vital for law enforcement agencies to witness how social media broadcast hate messages. Twitter is one of the famous social media and a platform for users to tell stories, give views, express feelings, and even spread news, whether true or false. Hence, it becomes an excellent resource for sentiment analysis. This paper aims to detect cyberbully threats based on Naïve Bayes, support vector machine (SVM), and k-nearest neighbour (k-NN) classifier model. Sentiment analysis will be applied based on people's opinions on social media and distribute polarity to them as positive, neutral, or negative. The accuracy for each classifier will be evaluated.

• Current Optics and Photonics
• /
• v.6 no.4
• /
• pp.381-391
• /
• 2022

Two-photon-polymerization additive-manufacturing systems feature high resolution and precision. However, there are few reports on specific methods and possible problems concerning the use of small lasers to independently build such platforms. In this paper, a femtosecond-laser two-photon-polymerization additive-manufacturing system containing an optical unit, control unit, monitoring unit, and testing unit is built using a miniature femtosecond laser, with a detailed building process and corresponding control software that is developed independently. This system has integrated functions of light-spot detection, interface searching, micro-/nanomanufacturing, and performance testing. In addition, possible problems in the processes of platform establishment, resin preparation, and actual polymerization for two-photon-polymerization additive manufacturing are explained specifically, and the causes of these problems analyzed. Moreover, the impacts of different power levels and scanning speeds on the degree of polymerization are compared, and the influence of the magnification of the object lens on the linewidth is analyzed in detail. A qualitative analysis model is established, and the concepts of the threshold broadening and focus narrowing effects are proposed, with their influences and cooperative relation discussed. Besides, a linear structure with micrometer accuracy is manufactured at the millimeter scale.

• Journal of Positioning, Navigation, and Timing
• /
• v.10 no.4
• /
• pp.235-242
• /
• 2021

Unmanned Aerial Vehicles (UAVs), which were used for military purposes, are gradually expanding their application fields under the influence of electrification and digitalization. Starting from the field of aerial imaging and Intelligence Surveillance and Reconnaissance (ISR) mission, nowadays the possibility of Urban Air Mobility (UAM), which transports passengers and cargo with drones, is widely under discussion. In order to occupy the rapidly growing global unmanned aerial vehicle market in advance, it is necessary to secure core technologies and develop key UAVs components based on the new technologies. In the navigation field, it is necessary to secure a precise position with guaranteed reliability and continuity, unrelated to the operating environments. The reliability and continuity should be secured in the algorithm level and in the H/W component levels also. In order to achieve this technical goal, the Ministry of Science and ICT has launched the 'Unmanned Vehicle Core Technology Research and Development Program' in 2019 to support the R&D on the unmanned vehicle technologies. In this paper, authors introduce the unmanned vehicle core technology research and development program to the related researchers. The authors summarize the backgrounds of the program and show the technological tasks and objectives on the sub-programs in the unmanned vehicle navigation program. We present the program schedules especially focused on the test and evaluation of the developed technologies and components.

• Journal of the Korean Society of Industry Convergence
• /
• v.25 no.6_1
• /
• pp.927-939
• /
• 2022

This study was conducted to develop a Web-GIS based monitoring module of smart city that can effectively respond, manage and improve situation in all stages of illegal dumping management on a city scale. First, five technologies were set for the core technical elements of the module configuration. Five core technical elements are as follows; video screening technology based on motion vector analysis, human behavior detection based on intelligent video analytics technology, mobile app for receiving civil complaints about illegal dumping, illegal dumping risk model and street cleanliness map, Web-GIS based situation monitoring technology. The development contents and results for each set of core technical elements were evaluated. Finally, a Web-GIS based 'illegal dumping monitoring module' was proposed. It is possible to collect and analyze city data at the local government level through operating the proposed module. Based on this, it is able to effectively detect illegal dumpers at relatively low cost and identify the tendency of illegal dumping by systematically managing habitual occurrence areas. In the future, it is expected to be developed in the form of an add-on module of the smart city integration platform operated by local governments to ensure interoperability and scalability.

• International journal of advanced smart convergence
• /
• v.11 no.2
• /
• pp.211-218
• /
• 2022

Pandemic situations such as COVID-19 can occur supply chain crisis. Under the supply chain crisis, delivering farm products from the farm to the city is also very challenging. Therefore it is essential to prepare food sufficiency people who live in a city. We firmly insist on food self-production/consumption systems in each home. However, since it is impossible to grow high-quality crops without expertise knowledge. Therefore expert system is essential to grow high-quality crops in home. To address this problem, we propose a smart kitchen farm as a data-based monitoring system and platform with ICT convergence technology. Our proposed approach 1) collects data and makes judgments based on expert knowledge for home users, 2) increases product quality of the smart kitchen farms by predicting abnormal/normal crops, and 3) controls each personal home cultivation environment through data-based monitoring within the smart central server. We expect people can cultivate high-quality crops in thir kitchens through this system without expert knowledge about cultivation.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.17 no.5
• /
• pp.273-280
• /
• 2022

Along with the advancement of deep learning technology, securing high-quality dataset for verification of developed technology is emerging as an important issue, and developing robust deep learning models to the domestic road environment is focused by many research groups. Especially, unlike expressways and automobile-only roads, in the complex city driving environment, various dynamic objects such as motorbikes, electric kickboards, large buses/truck, freight cars, pedestrians, and traffic lights are mixed in city road. In this paper, we built our dataset through multi camera-based processing (collection, refinement, and annotation) including the various objects in the city road and estimated quality and validity of our dataset by using YOLO-based model in object detection. Then, quantitative evaluation of our dataset is performed by comparing with the public dataset and qualitative evaluation of it is performed by comparing with experiment results using open platform. We generated our 2D dataset based on annotation rules of KITTI/COCO dataset, and compared the performance with the public dataset using the evaluation rules of KITTI/COCO dataset. As a result of comparison with public dataset, our dataset shows about 3 to 53% higher performance and thus the effectiveness of our dataset was validated.

• Korean Journal of Materials Research
• /
• v.33 no.5
• /
• pp.195-204
• /
• 2023

Micro-electronic gas sensor devices were developed for the detection of carbon monoxide (CO), nitrogen oxides (NO_x), ammonia (NH₃), and formaldehyde (HCHO), as well as binary mixed-gas systems. Four gas sensing materials for different target gases, Pd-SnO₂ for CO, In₂O₃ for NO_x, Ru-WO₃ for NH₃, and SnO₂-ZnO for HCHO, were synthesized using a sol-gel method, and sensor devices were then fabricated using a micro sensor platform. The gas sensing behavior and sensor response to the gas mixture were examined for six mixed gas systems using the experimental data in MEMS gas sensor arrays in sole gases and their mixtures. The gas sensing behavior with the mixed gas system suggests that specific adsorption and selective activation of the adsorption sites might occur in gas mixtures, and allow selectivity for the adsorption of a particular gas. The careful pattern recognition of sensing data obtained by the sensor array made it possible to distinguish a gas species from a gas mixture and to measure its concentration.

• Tuberculosis and Respiratory Diseases
• /
• v.86 no.2
• /
• pp.94-101
• /
• 2023

A recent understanding of the dynamic continuous spectrum of Mycobacterium tuberculosis infection has led to the recognition of incipient tuberculosis, which refers to the latent infection state that has begun to progress to active tuberculosis. The importance of early detection of these individuals with a high-risk of progression to active tuberculosis is emphasized to efficiently implement targeted tuberculosis preventive therapy. However, the tuberculin skin test or interferon-γ release assay, which is currently used for the diagnosis of latent tuberculosis infection, does not aid in the prediction of the risk of progression to active tuberculosis. Thus, a novel test is urgently needed. Recently, simultaneous and systematic analysis of differentially expressed genes using a high-throughput platform has enabled the discovery of key genes that may serve potential biomarkers for the diagnosis or prognosis of diseases. This host transcriptional investigation has been extended to the field of tuberculosis, providing promising results. The present review focuses on recent progress and challenges in the field of blood transcriptional signatures to predict progression to active tuberculosis.