• Journal of the Semiconductor & Display Technology
• /
• v.20 no.4
• /
• pp.171-176
• /
• 2021

Die-to-wafer (D2W) hybrid bonding in the multilayer semiconductor manufacturing process is one of wafer direct bonding, and various studies are being conducted around the world. A noteworthy point in the current die-to-wafer process is that a lot of voids occur on the bonding surface of the die during bonding. In this study, as a suggested method for removing voids generated during the D2W hybrid bonding process, a flexible mechanism for implementing convex for die bonding to be applied to the bond head is proposed. In addition, modeling of flexible mechanisms, analysis/design/control/evaluation of static/dynamics properties are performed. The proposed system was controlled by capacitive sensor (lion precision, CPL 290), piezo actuator (P-888,91), and dSpace. This flexure mechanism implemented a working range of 200 ㎛, resolution(3σ) of 7.276nm, Inposition(3σ) of 3.503nm, settling time(2%) of 500.133ms by applying a reverse bridge type mechanism and leaf spring guide, and at the same time realized a maximum step difference of 6 ㎛ between die edge and center. The results of this study are applied to the D2W hybrid bonding process and are expected to bring about an effect of increasing semiconductor yield through void removal. In addition, it is expected that it can be utilized as a system that meets the convex variable amount required for each device by adjusting the elongation amount of the piezo actuator coupled to the flexible mechanism in a precise unit.

• PNF and Movement
• /
• v.20 no.3
• /
• pp.431-441
• /
• 2022

Purpose: The purpose of this study was to compare the changes in the contact area, maximum pressure, maximum mean pressure, and maximum force of functional insoles and general insoles when walking. Methods: Foot pressure was measured by the ignition of functional insoles and general insoles on Company N shoes. The foot pressure was measured using a precision pressure distribution meter (Pedar - X mobile system, Novel, Germany). Each insole sensor contained 99 independent cells and was inserted between the foot and the shoe. A wireless Bluetooth-type program was used to measure the pressure detected by the measuring insoles. In order to eliminate adaptation and fatigue caused by wearing the guide during the experiment, sufficient rest was taken between each experiment, and the wearing order was randomly selected. Results: Functional insole significantly increased the forefoot and midfoot (medial, lateral) (p<0.05), while total foot, forefoot, and rearfoot peak pressure significantly decreased (p < 0.05) compared to the general insole. Conclusion: In the functional insole, a high contact area was measured inside, even in the middle of the foot, leading to a proper change in foot pressure. It was confirmed that the contact area was reduced and dispersion occurred well. In addition, it was found that the maximum pressure in the front and back of the entire foot was reduced, so the weight pressure dispersion in the functional insole was evenly distributed, and the maximum average pressure change was similar.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.6
• /
• pp.435-439
• /
• 2022

ROK has a lot to benchmark from how Ukraine is fighting Russia back with its tactical wins. They have taken a targeted strategy to strike Russia's top generals with high precision. To carry out this strategy, Ukraine is operating a Special Operations Force, which utilizes US/NATO forces, civilian and own resources for maximum impact. Of note, they utilize Starlink for seamless connection from detection, decision-making to strike to maximize operational efficiency. As ROK faces security threat of weapons of mass destruction, Ukraine's military intelligence organization set-up, weapons system and operations can provide some guidance on how to leverage its various SOF as well.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.11
• /
• pp.107-114
• /
• 2022

In this paper, proposes a delivery robot that can be autonomous driving learning. The proposed robot is designed to be used in park-type apartments without ground parking facilities. Compared to the existing apartments with complex ground and underground routes, park-type apartments have a standardized movement path, allowing the robot to run stably, making it suitable for students' initial education environment. The delivery robot is configured to enable delivery of parcels through machine learning technology for route learning and autonomous driving using cameras and LiDAR sensors. In addition, the control MCU was designed by separating it into three parts to enable learning by level, and it was confirmed that it can be used as a delivery robot for learning through operation tests such as autonomous driving and obstacle recognition. In the future, we plan to develop it into an educational delivery robot for various delivery services by linking with the precision indoor location information recognition technology and the public technology platform of the apartment.

• Journal of Biomedical Engineering Research
• /
• v.44 no.2
• /
• pp.109-117
• /
• 2023

In this study, the effect of the shape of the specimen and the feedrate of the dental ultrasonic surgical instrument on the cutting force and surface roughness of the specimen is analyzed. Experimental specimens were made of SAWBONES artificial bone materials in square and spherical specimens. In addition, the cutting feedrate of the surgical instrument was controlled through the developed moving system. The cutting force generated when cutting the specimen was measured through a force sensor. After the experiment, the cutting surface of the specimen was observed through a three-dimensional optical microscope and the surface roughness was measured. Through one-way ANOVA, the effect of each specimen shape and feed rate on surface roughness was analyzed. As a result of the experiment, the cutting force increased proportionally in the initial feed rate increase stage, but the increase in cutting force decreased as the feed rate continued to increase. Also, the cutting force showed a difference according to the shape of the specimen. The spherical specimen with a relatively small cutting surface area had less cutting force than the square specimen. However, as a result of one-way ANOVA, it was found that the specimen shape and feed rate did not affect the surface roughness. In future studies, it is expected to be used for comparative analysis of ultrasonic surgical instruments and correlation analysis between cutting factors.

• Journal of Korean Critical Care Nursing
• /
• v.16 no.1
• /
• pp.1-14
• /
• 2023

Purpose : This study aimed to compare peripheral pulse oxygen saturation (SpO₂) values, measured at different monitoring sites, and arterial oxygen saturation (SaO₂) of neurocritical patients. Methods : The study included 110 patients admitted to the neurosurgical intensive care unit of a university hospital. The patients' SpO₂ values were measured in their index fingers, both second toes, both earlobes, and foreheads, using the patient monitoring system. These values were compared with the standard value of SaO₂ measured using a blood gas analyzer. Data were analyzed using descriptive values, Pearson's correlation coefficients, Lin's concordance correlation coefficients (CCC), and Bland-Altman plots. Result : Regardless of the measuring site, SpO₂ was correlated with the paired measurements of SaO₂ (r=.40~.60, p<.001, CCC range=.40~.58). No significant bias in paired measurements of SpO₂ and SaO₂ was observed at all sites (-0.06~0.19%, p>.05). SpO₂ values at the left finger and right earlobe had the narrowest range, with a 95% limits of agreement (LOA) (left finger -3.04~2.93% and right earlobe -3.18~2.79%). SpO₂ at the index finger, on the side without an arterial catheter, had a narrower range of 95% LOA than that of the opposing finger (-3.00~2.97% vs. -3.73~3.26%). Conclusion : SpO₂ at the finger without an arterial catheter had the highest level of precision. This study suggests using the index finger, on the side without an arterial catheter, for pulse oximetry in neurocritical patients.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2022.10a
• /
• pp.88-88
• /
• 2022

Detection of stress responses in crops is important to diagnose crop growth and evaluate yield. Also, the multi-spectral sensor is effectively known to evaluate stress caused by nutrient and moisture in crops or biological agents such as weeds or diseases. Therefore, in this experiment, multispectral images were taken by an unmanned aerial vehicle(UAV) under field condition. The experiment was conducted in the long-term fertilizer field in the National Institute of Crop Science, and experiment area was divided into different status of NPK(Control, N-deficiency, P-deficiency, K-deficiency, Non-fertilizer). Total 11 vegetation indices were created with RGB and NIR reflectance values using python. Variations in nutrient content in plants affect the amount of light reflected or absorbed for each wavelength band. Therefore, the objective of this experiment was to evaluate vegetation indices derived from multispectral reflectance data as input into machine learning algorithm for the classification of nutritional deficiency in rice. RandomForest model was used as a representative ensemble model, and parameters were adjusted through hyperparameter tuning such as RandomSearchCV. As a result, training accuracy was 0.95 and test accuracy was 0.80, and IPCA, NDRE, and EVI were included in the top three indices for feature importance. Also, precision, recall, and f1-score, which are indicators for evaluating the performance of the classification model, showed a distribution of 0.7-0.9 for each class.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.1
• /
• pp.46-63
• /
• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• Journal of Mushroom
• /
• v.16 no.3
• /
• pp.155-161
• /
• 2018

In this study, we analyze the growth environment using smart farm technology in order to develop the optimal growth model for the precision cultivation of the bottle-grown oyster mushroom 'Suhan'. Experimental farmers used $88m^2$ of bed area, 2 rows and 5 columns of shelf shape, 5 hp refrigerator, 100T of sandwich panel for insulation, 2 ultrasonic humidifiers, 12 kW of heating, and 5,000 bottles for cultivation. Data on parameters such as temperature, humidity, carbon dioxide concentration, and illumination, which directly affect mushroom growth, were collected from the environmental sensor part installed at the oyster mushroom cultivator and analyzed. It was found that the initial temperature at the time of granulation was $22^{\circ}C$ after the scraping, and the mushroom was produced and maintained at about $25^{\circ}C$ until the bottle was flipped. On fruiting body formation, mushrooms were harvested while maintaining the temperature between $13^{\circ}C$ and $15^{\circ}C$. Humidity was approximately 100% throughout the growth stage. Carbon dioxide concentration gradually increased until 3 days after the beginning of cultivation, and then increased rapidly to approximately 2,600 ppm. From the 6th day, $CO_2$ concentration was gradually decreased through ventilation and maintained at 1,000 ppm during the harvest. Light was not provided at the initial stage of oyster mushroom cultivation. On the $3^{rd}$ and $4^{th}$ day, mushrooms were irradiated by 17 lux light. Subsequently, the light intensity was increased to 115-120 lux as the growth progressed. Fruiting body characteristics of 'Suhan' cultivated in a farmhouse were as follows: Pileus diameter was 30.9 mm and thickness was 4.5 mm; stipe thickness was 11.0 mm and length was 76.0 mm; stipe and pileus hardness was 0.8 g/mm and 2.8 g/mm, respectively; L values of the stipe and pileus were 79.9 and 52.3, respectively. The fruiting body yield was 160.2 g/850 ml, and the individual weight was 12.8 g/10 unit.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.19 no.2
• /
• pp.60-67
• /
• 2015

The finite element (FE) model updating is a commonly used approach in civil engineering, enabling damage detection, design verification, and load capacity identification. In the FE model updating, acceleration responses are generally employed to determine modal properties of a structure, which are subsequently used to update the initial FE model. While the acceleration-based model updating has been successful in finding better approximations of the physical systems including material and sectional properties, the boundary conditions have been considered yet to be difficult to accurately estimate as the acceleration responses only correspond to translational degree-of-freedoms (DOF). Recent advancement in the sensor technology has enabled low-cost, high-precision gyroscopes that can be adopted in the FE model updating to provide angular information of a structure. This study proposes a FE model updating strategy based on data fusion of acceleration and angular velocity. The usage of both acceleration and angular velocity gives richer information than the sole use of acceleration, allowing the enhanced performance particularly in determining the boundary conditions. A numerical simulation on a simply supported beam is presented to demonstrate the proposed FE model updating approach.