• Korean Journal of Optics and Photonics
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• v.33 no.6
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• pp.317-323
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• 2022

In this investigation, we describe a chromatic confocal sensor based on a geometric phase lens for measuring the thicknesses of transparent plates. In order to design a compact sensor, a geometric phase lens, which has diffractive and polarizing characteristics, is used as a device to generate chromatic aberration, and a fiber optic module is adopted. The systematic error of the sensor is reduced with wavelength peak detection by Gaussian curve fitting and the common error compensation obtained by the repeatedly consecutive experimental results. An approach to calculate the plate thickness is derived and verified with sapphire and BK7 plates. Because of the simple and compact design of the proposed sensor with rapid measurement capability, it is expected to be widely used in thickness measurements of transparent plates as an alternative to traditional approaches.

• Journal of Microbiology and Biotechnology
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• v.32 no.3
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• pp.365-377
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• 2022

Mammalian target of rapamycin (mTOR) is a serine-threonine kinase member of the cellular phosphatidylinositol 3-kinase (PI3K) pathway, which is involved in multiple biological functions by transcriptional and translational control. mTOR is a downstream mediator in the PI3K/Akt signaling pathway and plays a critical role in cell survival. In cancer, this pathway can be activated by membrane receptors, including the HER (or ErbB) family of growth factor receptors, the insulin-like growth factor receptor, and the estrogen receptor. In the present work, we congregated an electronic network of mTORC1 built on an assembly of data using natural language processing, consisting of 470 edges (activations/interactions and/or inhibitions) and 206 nodes representing genes/proteins, using the Cytoscape 3.6.0 editor and its plugins for analysis. The experimental design included the extraction of gene expression data related to five distinct types of cancers, namely, pancreatic ductal adenocarcinoma, hepatic cirrhosis, cervical cancer, glioblastoma, and anaplastic thyroid cancer from Gene Expression Omnibus (NCBI GEO) followed by pre-processing and normalization of the data using R & Bioconductor. ExprEssence plugin was used for network condensation to identify differentially expressed genes across the gene expression samples. Gene Ontology (GO) analysis was performed to find out the over-represented GO terms in the network. In addition, pathway enrichment and functional module analysis of the protein-protein interaction (PPI) network were also conducted. Our results indicated NOTCH1, NOTCH3, FLCN, SOD1, SOD2, NF1, and TLR4 as upregulated proteins in different cancer types highlighting their role in cancer progression. The MCODE analysis identified gene clusters for each cancer type with MYC, PCNA, PARP1, IDH1, FGF10, PTEN, and CCND1 as hub genes with high connectivity. MYC for cervical cancer, IDH1 for hepatic cirrhosis, MGMT for glioblastoma and CCND1 for anaplastic thyroid cancer were identified as genes with prognostic importance using survival analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1716-1722
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• 2021

Recently, the capacity of video content delivery services has been increasing significantly. Therefore, the importance of user recommendation is increasing. In addition, these contents contain a variety of characteristics, making it difficult to express the characteristics of the content properly only with a few keywords(Elements used in the search, such as titles, tags, topics, words, etc.) specified by the user. Consequently, existing recommendation systems that use user-defined keywords have limitations that do not properly reflect the characteristics of objects. In this paper, we compare the efficiency of between a method using voice data-based subtitles and an image comparison method using keyframes of images in recommendation module of educational video service systems. Furthermore, we propose the types and environments of video content in which each analysis technique can be efficiently utilized through experimental results.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.101-106
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• 2022

In this paper, WBG semiconductor such as SiC and GaN were applied as power switches for LCL circuit that can be applied to satellite power systems and the test results of the LCL circuit are reported. P-channel MOSFET and N-channel MOSFET, which were generally used in the conventional LCL circuit, were applied together to expand the utility of the test results. The design and stability evaluation were performed using a Micro Cap circuit simulation program. For the test circuit, a module using each switch was manufactured, and a total of 5 modules were manufactured and the steady state and transient state characteristics were compared. From the experimental results, the LCL circuit for power supply of the satellite power system constructed in this paper satisfied the constant current and constant voltage conditions under various operating conditions. The P-channel MOSFET showed the lowest efficiency characteristics, and the three N-channel switches of Si, SiC and GaN showed relatively high efficiency characteristics of up to 99.05% or more. In conclusion, it was verified that the on-resistor of the switch had a direct effect on the efficiency and loss characteristics.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.78-84
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• 2022

An air circuit breaker (ACB) is an electrical protection device that interrupts abnormal fault currents that result from overloads or short circuits in a low-voltage power distribution line. The ACB consists of a main circuit part for current flow, mechanism part for the opening and closing operation of movable conductors, and arc-extinguishing part for arc extinction during the breaking operation. The driving mechanism of the ACB is a spring energy charging type. The faster the contact opening speed of the movable conductors during the opening process, the better the breaking performance. However, there is a disadvantage that the durability of mechanism decreases in inverse proportion to the use of a spring capable of accumulating high energy to configure the breaking speed faster. Therefore, to simultaneously satisfy the breaking performance and mechanical endurance of the ACB, its driving mechanism must be optimized. In this study, a dynamic model of the ACB was developed using the MDO(Mechanism Dynamics Option) module of CREO, which is widely used in multibody dynamics analysis. To improve the opening velocity, the Taguchi design method was applied to optimize the design parameters of an ACB with many linkages. In addition, to evaluate the improvement in the operating characteristics, the simulation and experimental results were compared with the MDO model and improved prototype sample, respectively.

• 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%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4065-4083
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• 2021

Super-resolution can improve the clarity of low-resolution (LR) images, which can increase the accuracy of high-level compute vision tasks. Portable devices have low computing power and storage performance. Large-scale neural network super-resolution methods are not suitable for portable devices. In order to save the computational cost and the number of parameters, Lightweight image processing method can improve the processing speed of portable devices. Therefore, we propose the Enhanced Information Multiple Distillation Network (EIMDN) to adapt lower delay and cost. The EIMDN takes feedback mechanism as the framework and obtains low level features through high level features. Further, we replace the feature extraction convolution operation in Information Multiple Distillation Block (IMDB), with Ghost module, and propose the Enhanced Information Multiple Distillation Block (EIMDB) to reduce the amount of calculation and the number of parameters. Finally, coordinate attention (CA) is used at the end of IMDB and EIMDB to enhance the important information extraction from Spaces and channels. Experimental results show that our proposed can achieve convergence faster with fewer parameters and computation, compared with other lightweight super-resolution methods. Under the condition of higher peak signal-to-noise ratio (PSNR) and higher structural similarity (SSIM), the performance of network reconstruction image texture and target contour is significantly improved.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.315-333
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• 2021

Due to the Global Navigation Satellite System (GNSS) modernization, recently launched GNSS satellites transmit signals at various frequency bands such as L1, L2 and L5. Considering the Korean Positioning System (KPS) signal and other GNSS augmentation signals in the future, there is a high probability of applying more complex communication techniques to the new GNSS signals. For the reason, GNSS receivers based on flexible Software Defined Radio (SDR) concept needs to be developed to evaluate various experimental communication techniques by accessing each signal processing module in detail. This paper proposes a novel SDR-based A-GNSS receiver capable of processing multi-GNSS/RNSS signals at multi-frequency bands. Due to the modular structure, the proposed receiver has high flexibility and expandability. For real-time implementation, A-GNSS server software is designed to provide immediate delivery of satellite ephemeris data on demand. Due to the sampling bandwidth limitation of RF front-ends, multiple SDRs are considered to process the multi-GNSS/RNSS multi-frequency signals simultaneously. To avoid the overflow problem of sampled RF data, an efficient memory buffer management strategy was considered. To collect and process the multi-GNSS/RNSS multi-frequency signals in real-time, the proposed SDR A-GNSS receiver utilizes multiple threads implemented on a CPU and multiple NVIDIA CUDA GPGPUs for parallel processing. To evaluate the performance of the proposed SDR A-GNSS receiver, several experiments were performed with field collected data. By the experiments, it was shown that A-GNSS requirements can be satisfied sufficiently utilizing only milliseconds samples. The continuous signal tracking performance was also confirmed with the hundreds of milliseconds data for multi-GNSS/RNSS multi-frequency signals and with the ten-seconds data for multi-GNSS/RNSS single-frequency signals.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.897-905
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• 2022

Research for video key frame detection has been actively conducted in the fields of computer vision. Recently with the advances on deep learning techniques, performance of key frame detection has been improved, but the various type of video content and complicated background are still a problem for efficient learning. In this paper, we propose a novel method for key frame detection, witch utilizes contrastive learning and memory bank module. The proposed method trains the feature extracting network based on the difference between neighboring frames and frames from separate videos. Founded on the contrastive learning, the method saves and updates key frames in the memory bank, witch efficiently reduce redundancy from the video. Experimental results on video dataset show the effectiveness of the proposed method for key frame detection.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1199-1206
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• 2022

In this paper, unlike door locks that are controlled only by the existing keypad because electronic devices can be easily operated through apps on smartphones in modern society, an app was created using app inventory so that door locks can be controlled using smartphones. Through the Bluetooth module experiment, the communication distance with the smartphone was controlled up to 10m when there were no obstacles, and through the voice recognition experiment, the recognition rate was 85% and 90% at 500~1000Hz and 1000~1500Hz, respectively, and 70% and 80% at 80dB noise. Through the results of the experimental evaluation, it was confirmed that convenience and security could be improved.