• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.76-83
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• 2022

With the recent development of IT technology, research and interest in various biosignal measuring devices is increasing. As an aging society is in full swing, research on the elderly population using IT-related technologies is continuously developing. This study is about the development of life pattern detection and fall detection algorithm, which is one of the medical service areas for the elderly, who are rapidly developing as they enter a super-aged society. This study consisted of a system using a 3-axis accelerometer and an electrocardiogram sensor, collected data, and then analyzed the data. It was confirmed that behavioral patterns could be classified from the actual research results. In order to evaluate the usefulness of the human activity monitoring system implemented in this study, experiments were performed under various conditions, such as changes in posture and walking speed, and signal magnitude range and signal vector magnitude parameters reflecting the acceleration of gravity of the human body and the degree of human activity. was extracted. And the possibility of discrimination according to the condition of the subject was examined by these parameter values.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.1
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• pp.1-22
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• 2023

This study proposes an integrated use of region and industry as a way to classify firms' innovation activities by type. Existing studies have used the method of determining innovative activities according to the components of the technological regimes and aggregating them by industry classification, but this method cannot fully reflect the heterogeneity within industries in an increasingly sophisticated innovation environment. Therefore, this study divides firms by region and industry and conducts a cluster analysis on the proportion of innovative activities by the components of the technological regimes to derive a total of four innovation types. Using the 2016 Korean Innovation Survey to classify innovation types in the manufacturing industry, we found that innovation activities are concentrated in Seoul, Busan, Incheon, and Chungnam/ Sejong/ Daejeon area, with different deviations by region and industry. The results of the aggregation of industrial innovation activities, weighted by corporate activity by region, show that the level of innovation activity in some manufacturing industries, such as petrochemicals, manufacturing of medical, precision and optical instruments, watches and clocks, is high, but the level of innovation in other sectors within the manufacturing industry is generally low.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.19-29
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• 2006

As the security of personal information is becoming more important in mobile phones, we are starting to apply iris recognition technology to these devices. In conventional iris recognition, magnified iris images are required. For that, it has been necessary to use large magnified zoom & focus lens camera to capture images, but due to the requirement about low size and cost of mobile phones, the zoom & focus lens are difficult to be used. However, with rapid developments and multimedia convergence trends in mobile phones, more and more companies have built mega-pixel cameras into their mobile phones. These devices make it possible to capture a magnified iris image without zoom & focus lens. Although facial images are captured far away from the user using a mega-pixel camera, the captured iris region possesses sufficient pixel information for iris recognition. However, in this case, the eye region should be detected for accurate iris recognition in facial images. So, we propose a new fast iris detection method, which is appropriate for mobile phones based on corneal specular reflection. To detect specular reflection robustly, we propose the theoretical background of estimating the size and brightness of specular reflection based on eye, camera and illuminator models. In addition, we use the successive On/Off scheme of the illuminator to detect the optical/motion blurring and sunlight effect on input image. Experimental results show that total processing time(detecting iris region) is on average 65ms on a Samsung SCH-S2300 (with 150MHz ARM 9 CPU) mobile phone. The rate of correct iris detection is 99% (about indoor images) and 98.5% (about outdoor images).