• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.649-652
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• 2005

The camera cellular phone has a large portion of cellular phone market in recent year. The variety of a customer demand makes a fast model change and the spatial resolution is changed from VGA to multi-mega pixel. The 1.3 mega pixel (MP) camera cellular phone was first released into the Korean market in October 2003. The major cellular phone companies released a 2MP camera cellular phone that supports zoom function and a 2MP camera cellular phone is settled down with the Korea cellular phone market. It makes a keen competition in price and demands automation for phone camera module. There is an increasing requirement for the automatic assembly to correspond to a fast model change. The hard automation techniques that rely on dedicated manufacturing system are too inflexible to meet this requirement. Therefore in this study, this system is designed with the flexibility concept in order to cope with phone camera module change. The system has a same platform that has X-Y-Z motion or X-Z motion with ${\mu}m$order accuracy. It has a special gripper according to the type of a component to be put together. If the camera model changes, the gripper may be updated to fit for the camera module. The controller of this system acquires the data sets that have the information about the assembly part by the tray. This information is obtained ahead of an inspection step. The controller excludes an inferior part to be assembled by using this information to diminish the inferior goods. The assembly jig used in this system has a function of self adjustment that reduces the tact time and also diminish the inferior goods. Finally, the intelligent assembly system for phone camera module will be designed to get a flexibility to meet model change and a high productivity with a high reliability.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.1
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• pp.1-7
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• 2007

As fiber reinforced composite materials are widely used in aircraft, space structures and robot arms, the study on non-destructive testing methods has become an important research area for improving their reliability and safety. AE (acoustic emission) can evaluate the defects by detecting the emitting strain energy when elastic waves are generated by the initiation and growth of crack, plastic deformation, fiber breakage, matrix cleavage, or delamination. In the paper, AE signals generated under uniaxial tension were measured and analyzed using the $8{\times}8$ matrix piezo electric sensor. The electronic circuit to control the transmitting distance of AE signals was designed and constructed. The optical data storage system was also designed to store the AE signal of 64channels using LED (light emitting diode) elements. From the tests, it was shown that the source location and propagation path of AE signals in composite materials could be detected effectively by the $8{\times}8$ matrix piezo electric sensor.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.61-64
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• 2008

Seasonal distribution of the oceanic water intrusion was investigated using satellite SST (sea surface temperature) and chl-a (chlorophyll-a) images taken by the MODIS Aqua sensor. The warm water mass emanating periodically from the meandering Kuroshio Current brings the oceanic water intrusion, known as the 'Kyucho' phenomenon, into Kagoshima bay during the winter. Satellite SST images and buoy robot data show that this warm water intrusion has the characteristics of a semigeostrophic gravity current influenced by the Coriolis effect. However, it is difficult to find the oceanic water intrusion during the summer season considering that it is accompanied by thermal stratification, and SST shows almost the same temperature between the inner side of the bay and the ocean. In this research, the satellite chl-a images taken by MODIS Aqua were employed instead of SST images to reveal the oceanic water intrusion in each season. The enclosed bay has the tendency to undergo eutrophication caused by organic materials from land and differences in chl-a concentration of the bay water and the oceanic water. As a result, distribution of low concentration chl-a with oceanic water intrusion in summer season shows almost the same pattern in winter season. On the other hand, in spring season, both SST and chl-a images are available to differentiate the oceanic water intrusion. Therefore, applying the suitable satellite sensor images for each season is effective in the monitoring of oceanic water intrusion. Moreover, in this area, SST and chl-a distribution reveal not only the oceanic water intrusion into Kagoshima bay but also the intrusion at Fukiage seashore facing East China Sea.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.42-47
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• 2018

Recently, as the demand for limited resources continues to rise and problems of resource depletion rise worldwide, the importance of renewable energy is gradually increasing. In order to solve these problems, various methods such as energy conservation and alternative energy development have been suggested, and biogas, which can utilize the gas produced from biomass as fuel, is also receiving attention as the next generation of innovative renewable energy. New and renewable energy using biogas is an energy production method that is expected to be possible in large scale because it can supply energy with high efficiency in compliance with energy supply method of recycling conventional resources. In order to more efficiently produce and manage these biogas, a biogas plant has emerged. In recent years, a large number of biogas plants have been installed and operated in various locations. Organic wastes corresponding to biogas production resources in a biogas plant exist in a wide variety of types, and each of the incoming raw materials is processed in different processes. Because such a process is required, the case where the biogas plant process is inefficiently operated is continuously occurring, and the economic cost consumed for the operation of the biogas production relative to the generated biogas production is further increased. In order to solve such problems, various attempts such as process analysis and feedback based on the feedstock have been continued but it is a passive method and very limited to operate a medium/large scale biogas plant. In this paper, we propose "CNN-based production yield prediction algorithm for increasing process efficiency of biogas plant" for efficient operation of biogas plant process. Based on CNN-based production yield forecasting, which is one of the deep-leaning technologies, it enables mechanical analysis of the process operation process and provides a solution for optimal process operation due to process-related accumulated data analyzed by the automated process.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.192-197
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• 2017

In this paper, image filter optimization method based on common sub-expression elimination is proposed for low-power image feature extraction hardware design. Low power and high performance object recognition hardware is essential for industrial robot which is used for factory automation. However, low area Gaussian gradient filter hardware design is required for object recognition hardware. For the hardware complexity reduction, we adopt the symmetric characteristic of the filter coefficients using the transposed form FIR filter hardware architecture. The proposed hardware architecture can be implemented without degradation of the edge detection data quality since the proposed hardware is implemented with original Gaussian gradient filtering algorithm. The expremental result shows the 50% of multiplier savings compared with previous work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1176-1182
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• 2021

Recently, with the development of artificial intelligence and IoT technology, automation, and unmanned work are progressing in various fields, and the importance of image processing, which is the basis of AI object recognition, is increasing. In particular, in systems that require detailed data processing, noise removal is used as a preprocessing step, but the existing algorithm does not consider the noise level of the image, so it has the disadvantage of blurring in the filtering process. Therefore, in this paper, we propose a modified Gaussian filter that determines the weight by determining the noise level of the image. The proposed algorithm obtains the noise estimate for the AWGN of the image using quadtree segmentation, determines the Gaussian weight and the pixel weight, and obtains the final output by convolution with the local mask. To evaluate the proposed algorithm, it was simulated compared to the existing method, and superior performance was confirmed compared to the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.645-651
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• 2021

With the advent of the Fourth Industrial Revolution, modern society uses a diverse pool of devices. In this context, there is increasing interest in removing various kinds of noise arising in data transmission. However, it is difficult to restore image that damaged by mixed noise, and a digital filter that effectively restores an image according to the characteristics of the noise is required. In this paper, we propose a digital switching filter algorithm to remove mixed noise generated during digital image transmission. The proposed algorithm switches the filtering process through noise judgment and reconstructs the image using fuzzy weights and combined weights based on the pixel values inside the mask. To evaluate the proposed algorithm, we compared it with existing filter algorithms through simulation. Filtering results were expanded and compared for visual evaluation, and PSNR comparison was used for quantitative evaluation.

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

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.705-710
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• 2021

Nowadays, cutting-edge information communication technology is the genuine core technology of the fourth Industrial Revolution and is still making great progress rapidly among various technology fields. The biggest issue in ICT fields is the machine learning based Artificial Intelligence applications using big data in cloud computing environment on the basis of wireless network, and also the technology fields of autonomous control applications such as Autonomous Car or Mobile Robot. Since value of the high-tech ICT technology depends on the surrounded environmental factors and is very flexible, the precise technology valuation method is urgently needed in order to get successful technology transfer, transaction and commercialization. In this research, we analyze the characteristics of the high-tech ICT technology and the main factors in technology transfer or commercialization process, and propose the precise technology valuation method that reflects the characteristics of the ICT technology through phased analysis of the existing technology valuationmodel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.910-916
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• 2021

In modern society, various digital communication equipment is being used due to the influence of the 4th industrial revolution. Accordingly, interest in removing noise generated in a data transmission process is increasing, and research is being conducted to efficiently reconstruct an image. In this paper, we propose a filtering algorithm to remove the AWGN generated in the digital image transmission process. The proposed algorithm classifies pixels with high similarity by selecting regions with similar patterns around the input pixels according to block matching to remove the AWGN that appears strongly in the image. The selected pixel determines the estimated value by applying the weight obtained by the local steering kernel, and obtains the final output by adding or subtracting the input pixel value according to the standard deviation of the center mask. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and comparative analysis was performed using enlarged images and PSNR.