• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.3
• /
• pp.166-172
• /
• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.18 no.1
• /
• pp.101-112
• /
• 2016

Monitoring and control of the greenhouse environment play a decisive role in greenhouse crop production processes. The network system for greenhouse control was developed by using recent technologies of networking and wireless communications. In this paper, a remote monitoring and control system for greenhouse using a smartphone and a computer with internet has been developed. The system provides real-time remote greenhouse integrated management service which collects greenhouse environment information and controls greenhouse facilities based on sensors and equipments network. Graphical user interface for an integrated management system was designed with bases on the HMI and the experimental results showed that a sensor data and device status were collected by integrated management in real-time. Because the sensor data and device status can be displayed on a web page, transmitted using the server program to remote computer and mobile smartphone at the same time. The monitored-data can be downloaded, analyzed and saved from server program in real-time via mobile phone or internet at a remote place. Performance test results of the greenhouse control system has confirmed that all work successfully in accordance with the operating conditions. And data collections and display conditions, event actions, crops and equipments monitoring showed reliable results.

• Journal of the Institute of Convergence Signal Processing
• /
• v.24 no.2
• /
• pp.119-125
• /
• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Korean Geotechnical Society
• /
• v.40 no.3
• /
• pp.77-84
• /
• 2024

Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.6
• /
• pp.121-130
• /
• 2024

In this paper, we propose and design an NCS-based job matching system for individuals with disabilities. This system allows users with disabilities to access it, input basic information (personal and disability-related details), and take a simple test related to job performance. The system then provides NCS job-related information appropriate to their type and degree of disability. To effectively link various NCS-based jobs, it is essential to consider the degree of disability for each type of disability. However, most evaluation tools target specific types of disabilities or assess the vocational abilities of individuals with disabilities in a limited manner, focusing only on cognitive levels or certain physical functions. This makes it challenging to apply these tools to an NCS-based job matching system for individuals with disabilities. Therefore, in this paper, we utilize the ICF coresets for VR to assess the cognitive levels or physical functions required for performing specific jobs. Additionally, we use the NCS vocational competency evaluation tools to determine the levels of vocational competencies required for performing specific jobs. By doing so, we match NCS-based jobs according to the type and degree of disability. The proposed NCS-based job matching system relies on the user's interaction with the system, which may pose challenges for visually impaired individuals or those with intellectual and autism spectrum disabilities who have low literacy levels. Enhancing the accessibility of this system could enable individuals with disabilities to receive recommendations for NCS-based jobs that suit their vocational abilities.

• The Journal of the Acoustical Society of Korea
• /
• v.26 no.6
• /
• pp.250-258
• /
• 2007

Current speech recognition technology s achieved high performance with the development of hardware devices, however it is insufficient for some applications where high reliability is required, such as voice control of powered wheelchairs for disabled persons. For the system which aims to operate powered wheelchairs safely by voice in real environment, we need to consider that non-voice commands such as user s coughing, breathing, and spark-like mechanical noise should be rejected and the wheelchair system need to recognize the speech commands affected by disability, which contains specific pronunciation speed and frequency. In this paper, we propose non-voice rejection method to perform voice/non-voice classification using both YIN based fundamental frequency(F0) extraction and reliability in preprocessing. We adopted a multi-template dictionary and acoustic modeling based speaker adaptation to cope with the pronunciation variation of inarticulately uttered speech. From the recognition tests conducted with the data collected in real environment, proposed YIN based fundamental extraction showed recall-precision rate of 95.1% better than that of 62% by cepstrum based method. Recognition test by a new system applied with multi-template dictionary and MAP adaptation also showed much higher accuracy of 99.5% than that of 78.6% by baseline system.

• Journal of Family Resource Management and Policy Review
• /
• v.28 no.1
• /
• pp.27-38
• /
• 2024

Given the concern about the reduction in birth rate in Korea today, the objective of this study was to examine the association between Work·Family Compatibility policy and parenting stress, focusing on sex and occupational groups. Data from the 13th year Panel Study on Korean Children were analyzed by descriptive statistics, a one-way analysis of variance, and Duncan's post hoc test. The results of this study were as follows: First, the most commonly used aspect of the Work·Family Compatibility policy among both males and females was flextime, irrespective of occupational types. Also, flextime was the most used policy among professional workers. Second, regarding the use of related systems and parenting stress, it was found that all respondents perceived above average parenting stress. Specifically, the parenting stress scores of male users of flextime were higher than those of family care leave users. The parenting stress of military personnel were the lowest among males' occupational groups. Among females, the parenting stress scores of maternity leave users were higher than those of shorter workweek user. Diverse discussions and implications were suggested about promoting the usage of Work·Family Compatibility policy.

• Nuclear Engineering and Technology
• /
• v.55 no.11
• /
• pp.4274-4281
• /
• 2023

Blanket is of vital importance for engineering application of the fusion reactor. Nuclear heat deposition in materials is the main heat source in blanket structure. In this paper, the three-dimensional method for thermal-hydraulics/neutronics coupling analysis is developed and applied for the full-scale module of the helium-cooled ceramic breeder tritium breeding blanket (HCCB TBB) designed for China Fusion Engineering Test Reactor (CFETR). The explicit coupling scheme is used to support data transfer for coupling analysis based on cell-to-cell mapping method. The coupling algorithm is realized by the user-defined function compiled in Fluent. The three-dimensional model is established, and then the coupling analysis is performed using the paralleled Coupling Analysis of Thermal-hydraulics and Neutronics Interface Code (CATNIC). The results reveal the relatively small influence of the coupling analysis compared to the traditional method using the radial fitting function of internal heat source. However, the coupling analysis method is quite important considering the nonuniform distribution of the neutron wall loading (NWL) along the poloidal direction. Finally, the structure optimization of the blanket is carried out using the coupling method to satisfy the thermal requirement of all materials. The nonlinear effect between thermal-hydraulics and neutronics is found during the blanket structure optimization, and the tritium production performance is slightly reduced after optimization. Such an adverse effect should be thoroughly evaluated in the future work.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.4
• /
• pp.400-405
• /
• 2024

When cavitation noise occurs in ship propellers, the level of underwater radiated noise abruptly increases, which can be a critical threat factor as it increases the probability of detection, particularly in the case of naval vessels. Therefore, accurately and promptly assessing cavitation signals is crucial for improving the survivability of submarines. Traditionally, techniques for determining cavitation occurrence have mainly relied on assessing acoustic/vibration levels measured by sensors above a certain threshold, or using the Detection of Envelop Modulation On Noise (DEMON) method. However, technologies related to this rely on a physical understanding of cavitation phenomena and subjective criteria based on user experience, involving multiple procedures, thus necessitating the development of techniques for early automatic recognition of cavitation signals. In this paper, we propose an algorithm that automatically detects cavitation occurrence based on simple statistical features reflecting cavitation characteristics extracted from acoustic signals measured by sensors attached to the hull. The performance of the proposed technique is evaluated depending on the number of sensors and model test conditions. It was confirmed that by sufficiently training the characteristics of cavitation reflected in signals measured by a single sensor, the occurrence of cavitation signals can be determined.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.19 no.2
• /
• pp.55-62
• /
• 2015

Purpose Various methods for reducing radiation exposure have been continuously being developed. The aim of this study is to evaluate effectiveness of dose reduction, image quality and PET SUV changes by applying combination of automatic exposure dose(AEC), automated dose-optimized selection of X-ray tube voltage(CAREkV) and sinogram affirmed iterative reconstruction(SAFIRE) which can be controled by user. Materials and Methods Torso, AAPM CT performance and IEC body phantom images were acquired using biograph mCT64, (Siemens, Germany) PET/CT scanner. Standard CT condition was 120 kV, 40 mAs. Radiation exposure and noise were evaluated by applying AEC, CAREkV(120 kV, 40 mAs) and SAFIRE(120 kV, 25 mAs) with torso phantom compare to standard CT condition. And torso, AAPM and IEC phantom images were acquired with combination of 3 methods in condition of 120 kV, 25 mAs to evaluate radiation exposure, noise, spatial resolution and SUV changes. Results When applying AEC, CTDIvol and DLP were decreased by 50.52% and 50.62% compare to images which is not applying AEC. mAs was increased by 61.5% to compensate image quality according to decreasing 20 kV when applying CAREkV. However, CTDIvol and DLP were decreased by 6.2% and 5.5%. When reference mAs was the lower and strength was the higher, reduction of radiation exposure rate was the bigger. Mean SD and DLP were decreased by 2.2% and 38% when applying SAFIRE even though mAs was decreased by 37.5%(from 40 mAs to 25 mAs). Combination of 3 methods test, SD decreased by 5.17% and there was no significant differences in spatial resolution. And mean SD and DLP were decreased by 6.7% and 36.9% compare to 120 kV, 40 mAs with AEC. For SUV test, there was no statistical differences(P>0.05). Conclusion Combination of 3 methods shows dose reduction effect without degrading image quality and SUV changes. To reduce radiation exposure in PET/CT study, continuous effort is needed by optimizing various dose reduction methods.