• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.6_2
• /
• pp.1051-1058
• /
• 2020

The chemical mechanical planarization (CMP) is a process of physically and chemically polishing the semiconductor substrate. The planarization quality of a substrate can be evaluated by the within wafer non-uniformity (WIWNU). In order to improve WIWNU, it is important to manage the pad profile. In this study, a device capable of non-contact measurement of the pad thickness profile was developed. From the measured pad profile, the profile of the pad surface and the groove was extracted using the envelope function, and the pad thickness profile was derived using the difference between each profile. Thickness profiles of various CMP pads were measured using the developed PMS and envelope function. In the case of IC series pads, regardless of the pad wear amount, the envelopes closely follow the pad surface and grooves, making it easy to calculate the pad thickness profile. In the case of the H80 series pad, the pad thickness profile was easy to derive because the pad with a small wear amount did not reveal deep pores on the pad surface. However, the pad with a large wear amount make errors in the lower envelope profile, because there are pores deeper than the grooves. By removing these deep pores through filtering, the pad flatness could be clearly confirmed. Through the developed PMS and the pad thickness profile calculation method using the envelope function, the pad life, the amount of wear and the pad flatness can be easily derived and used for various pad analysis.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.6_2
• /
• pp.971-977
• /
• 2020

In this paper, We propose a portable electrostatic meter which can measure high voltage static electricity caused by friction to prevent fire or explosion accidents in grinding, crushing, power injection, transport, filling, dust removal, painting, and foreign matter removal processes. The proposed device not only shows static electricity strength in 4 steps with respect to distance and voltage but also gives warning with a buzzer, on process facilities that are likely to generate high voltage static electricity due to friction. The device is implemented by filtering the signal detected by the wireless antenna, amplifying the signal by 6 times, and passing the signal through the integrator circuit. Tests are carried out with an electrostatic discharge simulator. And the results show that 4 LEDs are turned on at the distance of 10cm, 3 LEDs at 12cm, 2 LEDs at 13cm, and 1 LED at 15cm, when a fixed voltage of 500V is given. And also, the tests show that the static electricity can be detected at 5cm on 100V, 10cm on 200V, 15cm on 500V, 20cm on 1000V, and 25cm on 1500V. We expect to reduce accidents caused by static electricity by allowing safety managers on fields where fire or explosion accidents can happen to monitor static electricity.

• Journal of Broadcast Engineering
• /
• v.25 no.6
• /
• pp.965-972
• /
• 2020

Depth maps have distance information of objects. They play an important role in organizing 3D information. Color and depth images are often simultaneously obtained. However, depth images have lower resolution than color images due to limitation in hardware technology. Therefore, it is useful to upsample depth maps to have the same resolution as color images. In this paper, we propose a novel method to upsample depth map by shifting the pixel position instead of compensating pixel value. This approach moves the position of the pixel around the edge to the center of the edge, and this process is carried out in several steps to restore blurred depth map. The experimental results show that the proposed method improves both quantitative and visual quality compared to the existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.6
• /
• pp.722-728
• /
• 2020

Digital image processing has been applied in a wide range of fields due to the development of IoT technology and plays an important role in data processing. Various techniques have been proposed to remove such noise, but the conventional impulse noise canceling methods are insufficient to remove noise of edge components of an image, and have a disadvantage of being greatly affected by random impulse noise. Therefore, in this paper, we propose an algorithm that effectively removes edge component noise in random impulse noise environment. The proposed algorithm calculates the threshold value by determining the noise level and switches the filtering process by comparing the reference value with the input pixel value. The proposed algorithm shows good performance in the existing method, and the simulation results show that the noise is effectively removed from the edge of the image.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.2
• /
• pp.214-220
• /
• 2021

In modern society, various digital communication equipments are being used due to the influence of the 4th industrial revolution, and accordingly, interest in removing noise generated in the data transmission process is increasing. In this paper, we propose a filtering algorithm to remove AWGN generated during digital image transmission. The proposed algorithm removes noise based on mask matching to preserve information such as the boundary of an image, and uses pixel values with similar patterns according to the pattern of the input pixel value and the surrounding pixels for output calculation. To evaluate the proposed algorithm, we simulated with existing AWGN removal algorithms, and analyzed using enlarged image and PSNR comparison. The proposed algorithm has superior AWGN removal performance compared to the existing method, and is particularly effective in images with strong noise intensity of AWGN.

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.1
• /
• pp.44-49
• /
• 2022

Abstract Recently, with the development of IoT technology and communication media, various video equipment is being used in industrial fields. Image data acquired from cameras and sensors are easily affected by noise during transmission and reception, and noise removal is essential as it greatly affects system reliability. In this paper, we propose a weight filter algorithm based on the pixel value distribution pattern to preserve details in the process of restoring images damaged in AWGN. The proposed algorithm calculates weights according to the pixel value distribution pattern of the image and restores the image by applying a filtering mask. In order to analyze the noise removal performance of the proposed algorithm, it was simulated using enlarged image and PSNR compared to the existing method. The proposed algorithm preserves important characteristics of the image and shows the performance of efficiently removing noise compared to the existing method.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.4
• /
• pp.157-162
• /
• 2022

Today, most data is stored in a database (DB). In the DB environment, the users requests the DB to find the data they wants. Similarity Query has predicate that explained by a similarity. However, in the process of processing the similarity query, it is difficult to use an index that can reduce the range of processed records, so the cost of calculating the similarity for all records in the table is high each time. To solve this problem, this paper defines a lightweight similarity function. The lightweight similarity function has lower data filtering accuracy than the similarity function, but consumes less cost than the similarity function. We present a method for reducing similarity query processing cost by using the lightweight similarity function features. Then, Chebyshev distance is presented as a lightweight similarity function to the Euclidean distance function, and the processing cost of a query using the existing similarity function and a query using the lightweight similarity function is compared. And through experiments, it is confirmed that the similarity query processing cost is reduced when Chebyshev distance is applied as a lightweight similarity function for Euclidean similarity.

• Journal of Broadcast Engineering
• /
• v.26 no.6
• /
• pp.725-737
• /
• 2021

Although the performance of cameras is gradually improving now, there are noise in the acquired digital images from the camera, which acts as an obstacle to obtaining high-resolution images. Traditionally, a filtering method has been used for denoising, and a convolutional neural network (CNN), one of the deep learning techniques, has been showing better performance than traditional methods in the field of image denoising, but the details in images could be lost during the learning process. In this paper, we present a CNN for image denoising, which improves image details by learning the details of the image based on wavelet transform. The proposed network uses two subnetworks for detail enhancement and noise extraction. The experiment was conducted through Gaussian noise and real-world noise, we confirmed that our proposed method was able to solve the detail loss problem more effectively than conventional algorithms, and we verified that both objective quality evaluation and subjective quality comparison showed excellent results.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.4
• /
• pp.815-821
• /
• 2021

The advantage of big data is to collect a large amount of data on the Internet and refine and use valuable data. That is, the unstructured data is processed so that the user can analyze and utilize it from a necessary point of view. This paper is a relatively small project and is based on unstructured data that can be closely applied to real life and used for marketing. The subjects of the experiment were modeled on lodging companies in the Seoul metropolitan area an hour away from Seoul, and analyzed for the increase in lodging rates before and after marketing using big data. As an experiment that shows the effects of increasing sales, reducing costs, and increasing returns by users, we propose a system to determine and filter whether data input in the process of analyzing big data such as social networks can be used as accommodation-related information.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.1242-1242
• /
• 2022

Annually, several construction workers fall ill, are injured, or die due to heat-related exposure. The prevalence of work-related heat illness may rise and become an issue for workers operating in temperate climates, given the increase in frequency and intensity of heatwaves in the US. An increase in temperature negatively impacts physical exertion levels and mental state, thereby increasing the potential of accidents on the job site. To reduce the impact of heat stress on workers, it is critical to develop and implement measures for monitoring physical exertion levels and mental state in hot conditions. For this, limited studies have evaluated the utility of wearable biosensors in measuring physical exertion and mental workload in hot conditions. In addition, most studies focus solely on male participants, with little to no reference to female workers who may be exposed to greater heat stress risk. Therefore, this study aims to develop a process for objective and continuous assessment of worker physical exertion and mental workload using wearable biosensors. Physiological data were collected from eight (four male and four female) participants performing a simulated drilling task at 92oF and about 50% humidity level. After removing signal artifacts from the data using multiple filtering processes, the data was compared to a perceived muscle exertion scale and mental workload scale. Results indicate that biosensors' features can effectively detect the change in worker physical and mental state in hot conditions. Therefore, wearable biosensors provide a feasible and effective opportunity to continuously assess worker physical exertion and mental workload.