• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.161-170
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• 2019

Multi-product mass production small and medium enterprise factories have a wide variety of products and a large number of products, wasting manpower and expenses for inventory management. In addition, there is no way to check the status of inventory in real time, and it is suffering economic damage due to excess inventory and shortage of stock. There are many ways to build a real-time data collection environment, but most of them are difficult to afford for small and medium-sized companies. Therefore, smart factories of small and medium enterprises are faced with difficult reality and it is hard to find appropriate countermeasures. In this paper, we implemented the contents of extension of existing inventory management method through character extraction on label with barcode and QR code, which are widely adopted as current product management technology, and evaluated the effect. Technically, through preprocessing using OpenCV for automatic recognition and classification of stock labels and barcodes, which is a method for managing input and output of existing products through computer image processing, and OCR (Optical Character Recognition) function of Google vision API. And it is designed to recognize the barcode through Zbar. We propose a method to manage inventory by real-time image recognition through Raspberry Pi without using expensive equipment.

• Korean Chemical Engineering Research
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• v.59 no.4
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• pp.565-573
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• 2021

Isotherms, kinetics and thermodynamic properties for adsorption of Brilliant Green(BG), Quinoline Yellow(QY) dyes by activated carbon were carried out using variables such as dose of adsorbent, pH, initial concentration, contact time, temperature and competitive. BG showed the highest adsorption rate of 92.4% at pH 11, and QY was adsorbed at 90.9% at pH 3. BG was in good agreement with the Freundlich isothermal model, and QY was well matched with Langmuir model. The separation coefficients of isotherm model indicated that these dyes could be effectively treated by activated carbon. Estimated adsorption energy by Temkin isotherm model indicated that the adsorption of BG and QY by activated carbon is a physical adsorption. The kinetic experimental results showed that the pseudo second order model had a better fit than the pseudo first order model with a smaller in the equilibrium adsorption amount. It was confirmed that surface diffusion was a rate controlling step by the intraparticle diffusion model. The activation energy and enthalpy change of the adsorption process indicated that the adsorption process was a relatively easy endothermic reaction. The entropy change indicated that the disorder of the adsorption system increased as the adsorption of BG and QY dyes to activated carbon proceeded. Gibbs free energy was found that the adsorption reaction became more spontaneous with increasing temperature. As a result of competitive adsorption of the mixed solution, it was found that QY was disturbed by BG and the adsorption reduced.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.949-955
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• 2020

In this Study, Social Network Analysis of IoT related patents in South Korea, China, and Japan was conducted from the viewpoint of patent informatics. To this end, 2,526 patents filed by PCT until December 2019 were investigated up to the subclass level of the IPC code. As a result, in the case of South Korea, representative IPC codes are in the order of G06Q, H04L, G06F, H04W, and the highest frequency of interconnection is H04L→H04W, H04W→H04L, H04W→H04B. In China, the representative IPC codes are in the order of H04L, H04W, G05B, G06Q. South Korea has strong technological convergence centered on the G06Q, while China has strong convergence centered around H04L and H04W. Moreover, in China, H04L and H04W have more diverse combinations than in South Korea in Section A, B, G, and H. In the future, it is necessary to study the diversity of technology convergence of H04L and H04W in China.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.5
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• pp.17-30
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• 2001

In this paper, we implemented a scalar multiplier needed at an elliptic curve cryptosystem over standard basis in $GF(2^{163})$. The scalar multiplier consists of a radix-16 finite field serial multiplier and a finite field inverter with some control logics. The main contribution is to develop a new fast finite field inverter, which made it possible to avoid time consuming iterations of finite field multiplication. We used an algorithmic transformation technique to obtain a data-independent computational structure of the Extended Euclid GCD algorithm. The finite field multiplier and inverter shown in this paper have regular structure so that they can be easily extended to larger word size. Moreover they can achieve 100% throughput using the pipelining. Our new scalar multiplier is synthesized using Hyundai Electronics 0.6$\mu\textrm{m}$ CMOS library, and maximum operating frequency is estimated about 140MHz. The resulting data processing performance is 64Kbps, that is it takes 2.53ms to process a 163-bit data frame. We assure that this performance is enough to be used for digital signature, encryption & decryption and key exchange in real time embedded-processor environments.

• Journal of IKEEE
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• v.26 no.3
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• pp.510-514
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• 2022

In this paper, we propose the development of high-sensitivity low-end radiation measuring sensor module. The proposed measurement sensor module is a scintillator + photomultiplier(SiPM) sensor optimization structure design, amplification and filter and control circuit design for sensor driver, control circuit design including short-distance communication, sensor mechanism design and manufacturing, and GUI development applied to prototypes consists of, etc. The scintillator + photomultiplier(SiPM) sensor optimization structure design is designed by checking the characteristics of the scintillator and the photomultiplier (SiPM) for the sensor structure design. Amplification, filter and control circuit design for sensor driver is designed to process fine scintillation signal generated by radiation with a scintillator using SiPM. Control circuit design including short-distance communication is designed to enable data transmission through MCU design to support short-range wireless communication function and wired communication support. The sensor mechanism design and manufacture is designed so that the glare generated by wrapping a reflective paper (mirroring) on the outside of the plastic scintillator is reflected to increase the efficiency in order to transmit the fine scintillation signal generated from the plastic scintillator to the photomultiplier(SiPM). The GUI development applied to the prototype expresses the date and time at the top according to each screen and allows the measurement unit and time, seconds, alarm level, communication status, battery capacity, etc. to be expressed. In order to evaluate the performance of the proposed system, the results of experiments conducted by an authorized testing institute showed that the radiation dose measurement range was 30 𝜇Sv/h ~ 10 mSv/h, so the results are the same as the highest level among products sold commercially at domestic and foreign. In addition, it was confirmed that the measurement uncertainty of ±7.4% was measured, and normal operation was performed under the international standard ±15%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.281-290
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• 2022

In Korea, the number of national facilities for which a safety inspection is mandatory is increasing, and a safer safety inspection method is needed. This study aimed to increase the efficiency of the bridge safety inspection by enabling rapid exterior inspection while securing the safety of inspectors by using drones to perform the safety inspections of bridges, which had mainly relied on visual inspections. For the research, the Youngjong Grand Bridge in Incheon was selected as a test bed and was divided into four parts: the warren truss, suspension bridge main cable, main tower, and pier. It was possible to establish a five-step standard procedure for drone safety inspections. The step-by-step contents of the standard procedure obtained as a result of this research are: Step 1, facility information collection and analysis, Step 2, analysis of vulnerable parts and drone flight planning, Step 3, drone photography and data processing, Step 4, condition evaluation by external inspection, Step 5, building of external inspection diagram and database. Therefore, if the safety inspections of civil engineering facilities including bridges are performed according to this standard procedure, it is expected that these inspection can be carried out more systematically and efficiently.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.849-858
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• 2023

Investigating disaster sites such as earthquakes and landslides involves significant risks due to potential secondary disasters like facility collapse. In situations where direct access is challenging, there is a need to develop methods for safely acquiring high-precision 3D disaster information using light detection and ranging (LiDAR) equipped drone survey systems. In this study, the feasibility of using drone LiDAR in disaster scenarios was examined, focusing on the collapse accident at Jeongja Bridge in Bundang-gu, Seongnam City, in April 2023. High-density point clouds for the accident bridge were collected, and the bridge's 3D terrain information was reconstructed and compared to the measurement performance of 10 ground control points. The results showed horizontal and vertical root mean square error values of 0.032 m and 0.055 m, respectively. Additionally, when compared to a point cloud generated using ground LiDAR for the same target area, a vertical difference of approximately 0.08 m was observed, but overall shapes showed minimal discrepancies. Moreover, in terms of overall data acquisition and processing time, drone LiDAR was found to be more efficient than ground LiDAR. Therefore, the use of drone LiDAR in disaster sites with significant risks allows for safe and rapid onsite investigations.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.73-80
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• 2023

The recent steep increase in the minimum hourly wage has increased the burden of labor costs, and the share of unmanned stores is increasing in the aftermath of COVID-19. As a result, theft crimes targeting unmanned stores are also increasing, and the "Just Walk Out" system is introduced to prevent such thefts, and LiDAR sensors, weight sensors, etc. are used or manually checked through continuous CCTV monitoring. However, the more expensive sensors are used, the higher the initial cost of operating the store and the higher the cost in many ways, and CCTV verification is difficult for managers to monitor around the clock and is limited in use. In this paper, we would like to propose an AI image processing fusion algorithm that can solve these sensors or human-dependent parts and detect customers who perform abnormal behaviors such as theft at low costs that can be used in unmanned stores and provide cloud-based notifications. In addition, this paper verifies the accuracy of each algorithm based on behavior pattern data collected from unmanned stores through motion capture using mediapipe, object detection using YOLO, and fusion algorithm and proves the performance of the convergence algorithm through various scenario designs.

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

• Tunnel and Underground Space
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• v.34 no.3
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• pp.208-217
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• 2024

There is so much research effort for developing and implementing deep learning-based surveillance systems to manage health and safety issues in construction sites. Especially, the development of deep learning-based object detection in various environmental changes has been progressing because those affect decreasing searching performance of the model. Among the various environmental variables, the accuracy of the object detection model is significantly dropped under low illuminance, and consistent object detection accuracy cannot be secured even the model is trained using low-light images. Accordingly, there is a need of low-light enhancement to keep the performance under low illuminance. Therefore, this paper conducts a comparative study of various deep learning-based low-light image enhancement models (GLADNet, KinD, LLFlow, Zero-DCE) using the acquired construction site image data. The low-light enhanced image was visually verified, and it was quantitatively analyzed by adopting image quality evaluation metrics such as PSNR, SSIM, Delta-E. As a result of the experiment, the low-light image enhancement performance of GLADNet showed excellent results in quantitative and qualitative evaluation, and it was analyzed to be suitable as a low-light image enhancement model. If the low-light image enhancement technique is applied as an image preprocessing to the deep learning-based object detection model in the future, it is expected to secure consistent object detection performance in a low-light environment.