• Current Photovoltaic Research
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• 제8권4호
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• pp.114-119
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• 2020

In this study, Mitigation of Potential-induced degradation (PID) for PERC solar cells using SiO2 Structure of ARC layer. The conventional PID test was conducted with a cell-level test based on the IEC-62804 test standard, but a copper PID test device was manufactured to increase the PID detection rate. The accelerated aging test was conducted by maintaining 96 hours with a potential difference of 1000 V at a temperature of 60℃. As a result, the PERC solar cell of SiO2-Free ARC structure decreased 22.11% compared to the initial efficiency, and the PERC solar cell of the Upper-SiO2 ARC structure decreased 30.78% of the initial efficiency and the PID reliability was not good. However, the PERC solar cell with the lower-SiO2 ARC structure reduced only 2.44%, effectively mitigating the degradation of PID. Na+ ions in the cover glass generate PID on the surface of the PERC solar cell. In order to prevent PID, the structure of SiNx and SiO2 thin films of the ARC layer is important. SiO2 thin film must be deposited on bottom of ARC layer and the surface of the PERC solar cell N-type emitter to prevent surface recombination and stacking fault defects of the PERC solar cell and mitigated PID degradation.

• 대한의용생체공학회:의공학회지
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• 제42권4호
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• pp.167-174
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• 2021

The purpose of this study is to classify TIFF images, PNG images, and JPEG images using deep learning, and to compare the accuracy by verifying the classification performance. The TIFF, PNG, and JPEG images converted from chest X-ray DICOM images were applied to five deep neural network models performed in image recognition and classification to compare classification performance. The data consisted of a total of 4,000 X-ray images, which were converted from DICOM images into 16-bit TIFF images and 8-bit PNG and JPEG images. The learning models are CNN models - VGG16, ResNet50, InceptionV3, DenseNet121, and EfficientNetB0. The accuracy of the five convolutional neural network models of TIFF images is 99.86%, 99.86%, 99.99%, 100%, and 99.89%. The accuracy of PNG images is 99.88%, 100%, 99.97%, 99.87%, and 100%. The accuracy of JPEG images is 100%, 100%, 99.96%, 99.89%, and 100%. Validation of classification performance using test data showed 100% in accuracy, precision, recall and F1 score. Our classification results show that when DICOM images are converted to TIFF, PNG, and JPEG images and learned through preprocessing, the learning works well in all formats. In medical imaging research using deep learning, the classification performance is not affected by converting DICOM images into any format.

• 한국지하수토양환경학회지:지하수토양환경
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• 제27권1호
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• pp.17-24
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• 2022

This work examined the effect of mixing transition metal-based additives [FeCl₃, Fe-containing paper mill sludge (PMS), CoCl₂·H₂O, ZrO₂, and α-Fe₂O₃] on the thermochemical conversion of coffee waste (CW) in carbon dioxide-assisted pyrolysis process. Compared to the generation amounts of syngas (0.7 mole% H₂ & 3.0 mole% CO) at 700℃ from single pyrolysis of CW, co-pyrolysis in the presence of Fe- or Zr-based additives resulted in the enhanced production of syngas, with the measured concentrations of H₂ and CO ranging 1.1-3.4 mole% and 4.6-13.2 mole% at the same temperature, respectively. In addition, α-Fe₂O₃ biochar possessed the adsorption capacity of As(V) (19.3 mg g^-1) comparable to that of ZrO₂-biochar (21.2 mg g^-1). In conclusion, solid-type Fe-based additive can be highly considered as an efficient catalyst to simultaneously produce syngas (H₂ & CO) as fuel energy resource and metal-biochar as sorbent.

• 한국전기전자재료학회논문지
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• 제35권3호
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• pp.303-307
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• 2022

Magnetoelectric (ME) properties of 3-0 type particulate composites have been investigated with respect to application features for reliable magnetic sensitivity and magnetically-induced output voltage. In order to figure out the magnetoelectric characteristics in the ME composites, frequency dependent ME responses were studied from [0.948 Na_0.5K_0.5NbO₃-0.052 LiSbO₃]-[Co_1-xZn_xFe₂O₄] (NKNLS)/Co_1-xZn_xFe₂O₄ (CZFO, x=0, 0.1, and 0.2). As a result, the maximal α_ME of 23.15 mV/cm·Oe was achieved from the NKNLS-CZFO (x_Zn = 0.1) composites at resonance frequency of 315 kHz and H_dc = 0 Oe. From the frequency dependent ME responses, it is clearly described that the self-biased ME composites can be used for applications as both magnetic sensors and energy harvesters, respectively.

• Tribology and Lubricants
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• 제38권3호
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• pp.93-100
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• 2022

Micro-light emitting diode (micro-LED) displays offer numerous advantages such as high brightness, fast response, and low power consumption. Hence, they are spotlighted as the next-generation display. However, defective LEDs may be created due to non-uniform contact loads or LED alignment errors. Therefore, a repair process involving the replacement of defective LEDs with favorable ones is necessitated. The general repair process involves the removal of defective micro-LEDs, interconnection material transfer, as well as new micro-LED transfer and bonding. However, micro-LEDs are difficult to repair since their size decreases to a few tens of micron in width and less than 10 ㎛ in thickness. The conventional nozzle-type dispenser for fluxes and the conventional vacuum chuck for LEDs are not applicable to the micro-LED repair process. In this study, transfer conditions are determined using a micro stamp for repairing micro-LEDs. Results show that the aging time should be set to within 60 min, based on measuring the aging time of the flux. Additionally, the micro-LEDs are subjected to a compression test, and the result shows that they should be transferred under 18.4 MPa. Finally, the I-V curves of micro-LEDs processed by the laser and hot plate reflows are measured to compare the electrical properties of the micro-LEDs based on the reflow methods. It was confirmed that the micro-LEDs processed by the laser reflow show similar electrical performance with that processed by the hot plate reflow. The results can provide guidance for the repair of micro-LEDs using micro stamps.

• Genomics & Informatics
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• 제19권4호
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• pp.44.1-44.9
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• 2021

Autism is a complex neurodevelopmental disorder, the prevalence of which has increased drastically in India in recent years. Neuroligin is a type I transmembrane protein that plays a crucial role in synaptogenesis. Alterations in synaptic genes are most commonly implicated in autism and other cognitive disorders. The present study investigated the neuroligin 3 gene in the Indian autistic population by sequencing and in silico pathogenicity prediction of molecular changes. In total, 108 clinically described individuals with autism were included from the North Karnataka region of India, along with 150 age-, sex-, and ethnicity-matched healthy controls. Genomic DNA was extracted from peripheral blood, and exonic regions were sequenced. The functional and structural effects of variants of the neuroligin 3 protein were predicted. One coding sequence variant (a missense variant) and four non-coding variants (two 5'-untranslated region [UTR] variants and two 3'-UTR variants) were recorded. The novel missense variant was found in 25% of the autistic population. The C/C genotype of c.551T>C was significantly more common in autistic children than in controls (p = 0.001), and a significantly increased risk of autism (24.7-fold) was associated with this genotype (p = 0.001). The missense variant showed pathogenic effects and high evolutionary conservation over the functions of the neuroligin 3 protein. In the present study, we reported a novel missense variant, V184A, which causes abnormal neuroligin 3 and was found with high frequency in the Indian autistic population. Therefore, neuroligin is a candidate gene for future molecular investigations and functional analysis in the Indian autistic population.

• Genomics & Informatics
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• 제20권3호
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• pp.30.1-30.9
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• 2022

Hereditary spastic paraplegia is a not common inherited neurological disorder with heterogeneous clinical expressions. ALDH18A1 (located on 10q24.1) gene-related spastic paraplegias (SPG9A and SPG9B) are rare metabolic disorders caused by dominant and recessive mutations that have been found recently. Autosomal recessive hereditary spastic paraplegia is a common and clinical type of familial spastic paraplegia linked to the SPG11 locus (locates on 15q21.1). There are different symptoms of spastic paraplegia, such as muscle atrophy, moderate mental retardation, short stature, balance problem, and lower limb weakness. Our first proband involves a 45 years old man and our second proband involves a 20 years old woman both are affected by spastic paraplegia disease. Genomic DNA was extracted from the peripheral blood of the patients, their parents, and their siblings using a filter-based methodology and quantified and used for molecular analysis and sequencing. Sequencing libraries were generated using Agilent SureSelect Human All ExonV7 kit, and the qualified libraries are fed into NovaSeq 6000 Illumina sequencers. Sanger sequencing was performed by an ABI prism 3730 sequencer. Here, for the first time, we report two cases, the first one which contains likely pathogenic NM_002860: c.475C>T: p.R159X mutation of the ALDH18A1 and the second one has likely pathogenic NM_001160227.2: c.5454dupA: p.Glu1819Argfs Ter11 mutation of the SPG11 gene and also was identified by the whole-exome sequencing and confirmed by Sanger sequencing. Our aim with this study was to confirm that these two novel variants are direct causes of spastic paraplegia.

• Clinics in Shoulder and Elbow
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• 제25권3호
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• pp.224-229
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• 2022

Background: Most acromioclavicular joint (ACJ) injuries are caused by direct trauma to the shoulders, and various methods and techniques are used to treat them; however, none of the options can be considered the gold standard. This study examines the horizontal stability of the ACJ after a complete dislocation was repaired using one of two Ethibond suture techniques, the loop technique and the two holes in the clavicle technique. Methods: In this single-blind, randomized clinical trial, 104 patients diagnosed with complete ACJ dislocation type V were treated using Ethibond sutures with either the loop technique or the two holes in the clavicle technique. Horizontal changes in the ACJ were radiographically assessed in the lateral axial view, and shoulder function was evaluated by the Constant (CS) and Taft (TS) scores at intervals of 3, 6, and 12 months after surgery. Results: The horizontal stability of the ACJ was better with the two-hole technique than the loop technique at all measurement times. CS and TS changes showed a significant upward trend over time with both techniques. The mean CS and TS at the final visit were 95.2 and 11.6 with the loop technique and 94.0 and 11.9 with the two-hole technique, respectively. The incidence of superficial infections caused by the subcutaneous pins was the same in the two groups. Conclusions: Due to the improved ACJ stability with the two-hole technique, it appears to be a more suitable option than the loop technique for AC joint reduction.

• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2334-2340
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• 2021

Radioactive particle tracking (RPT) is a minimally invasive nuclear technique that tracks a radioactive particle inside a volume of interest by means of a mathematical location algorithm. During the past decades, many algorithms have been developed including ones based on artificial intelligence techniques. In this study, RPT technique is applied in a simulated test section that employs a simplified mixer filled with concrete, six scintillator detectors and a¹³⁷Cs radioactive particle emitting gamma rays of 662 keV. The test section was developed using MCNPX code, which is a mathematical code based on Monte Carlo simulation, and 3516 different radioactive particle positions (x,y,z) were simulated. Novelty of this paper is the use of a location algorithm based on a deep learning model, more specifically a 6-layers deep rectifier neural network (DRNN), in which hyperparameters were defined using a Bayesian optimization method. DRNN is a type of deep feedforward neural network that substitutes the usual sigmoid based activation functions, traditionally used in vanilla Multilayer Perceptron Networks, for rectified activation functions. Results show the great accuracy of the DRNN in a RPT tracking system. Root mean squared error for x, y and coordinates of the radioactive particle is, respectively, 0.03064, 0.02523 and 0.07653.

• 분석과학
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• 제35권2호
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• pp.69-81
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• 2022

The method of measuring and classifying the energy category of neutrons directly using raw data acquired through a CZT detector is not satisfactory, in terms of accuracy and efficiency, because of its poor energy resolution and low measurement efficiency. Moreover, this method of measuring and analyzing the characteristics of low-energy or low-activity gamma-ray sources might be not accurate and efficient in the case of neutrons because of various factors, such as the noise of the CZT detector itself and the influence of environmental radiation. We have therefore developed an efficient method of analyzing radiation characteristics using a neutron and gamma-ray analysis algorithm for the rapid and clear identification of the type, energy, and radioactivity of gamma-ray sources as well as the detection and classification of the energy category (fast or thermal neutrons) of neutron sources, employing raw data acquired through a CZT detector. The neutron analysis algorithm is based on the fact that in the energy-spectrum channel of 558.6 keV emitted in the nuclear reaction ¹¹³Cd + ¹n → ¹¹⁴Cd + in the CZT detector, there is a notable difference in detection information between a CZT detector without a PE modulator and a CZT detector with a PE modulator, but there is no significant difference between the two detectors in other energy-spectrum channels. In addition, the gamma-ray analysis algorithm uses the difference in the detection information of the CZT detector between the unique characteristic energy-spectrum channel of a gamma-ray source and other channels. This efficient method of analyzing radiation characteristics is expected to be useful for the rapid radiation detection and accurate information collection on radiation sources, which are required to minimize radiation damage and manage accidents in national disaster situations, such as large-scale radioactivity leak accidents at nuclear power plants or nuclear material handling facilities.