• Journal of Venture Innovation
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• 제2권2호
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• pp.21-29
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• 2019

In the public certificate technology commonly used in Korea, users have a cumbersome problem of always resetting when they forget their password. In this paper, as a solution to this problem, we propose a secure authentication certificate password recovery protocol using blockchain, PKI, and DID for distributed storage. DID is a schema for protecting block ID in blockchain system. The private key used in the PKI is configured as a user's biometric, for example, a fingerprint, so that it can completely replace the memory of the complex private key. To this end, based on the FIDO authentication technology that most users currently use on their smartphones, the process of authenticating a user to access data inside the block minimizes the risk of an attacker taking over the data.

• Journal of the Korea Convergence Society
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• 제8권8호
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• pp.83-88
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• 2017

The personal activity information is expanding as a way to utilize wearable devices that are emerging as next generation smart devices. This paper develops an application for collecting heartbeat rate and location information of a user using SmartWatch, which is a smartphone and wearable device, and analyzing it through machine learning to infer user's emotion information. By using smart phone and smart watch, developed application can collect biometric data and location information by simply executing application and doing everyday life. In addition, adding the location information to the hearbit rate data, it proves higher utilization than existing ones.

• KIPS Transactions on Software and Data Engineering
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• 제7권9호
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• pp.345-350
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• 2018

This study is an algorithm for detecting vein pattern features important for finger vein recognition. The feature detection algorithm is important because it greatly affects recognition results in pattern recognition. The recognition rate is degraded because the reference is changed according to the finger position change. In addition, the image obtained by irradiating the finger with infrared light is difficult to separate the image background and the blood vessel pattern, and the detection time is increased because the image preprocessing process is performed. For this purpose, the presented algorithm can be performed without image preprocessing, and the detection time can be reduced. SWDA (Down Slope Trace Waveform) algorithm is applied to the finger vein images to detect the fingertip position and vein pattern. Because of the low infrared transmittance, relatively dark vein images can be detected with minimal detection error. In addition, the fingertip position can be used as a reference in the classification stage to compensate the decrease in the recognition rate. If we apply algorithms proposed to various recognition fields such as palm and wrist, it is expected that it will contribute to improvement of biometric feature detection accuracy and reduction of recognition performance time.

• Journal of Service Research and Studies
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• 제2권2호
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• pp.45-51
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• 2012

U-healthcare is real-time monitoring of personal biometric information using by portable devices, home network and information and communication technology based healthcare systems, and fused together automatically to overcome the constraints of time and space are connected with hospitals and doctors. As u-healthcare gives health service in anytime and anywhere, it becomes to be a new type of medical services in patients management and disease prevention. In this paper, recent changes in prevention-oriented care is analyzed in becoming early response for Healthcare Information System by requirements analysis for technology development trend. According to the healthcare system, PACS, OCS, EMR and emergency medical system, U-healthcare is presenting the design of a patient-centered integrated client system. As the relationship between the meaning of the terms is used in the ontology, information models in the system is providing a common vocabulary with various levels of formality. In this paper, we propose an ontology-based system for patient-centered services, including the concept of clustering to clustering the data to define the relationship between these ontologies for more systematic data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2013년도 추계학술대회
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• pp.307-309
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• 2013

Diligence/Indolence records are the basic data at a human resource management and the essential data for measure salaries of employees. However, since the D/I systems using RFIDs or biometric sensors require hish costs to build and operate the D/I systems, it is difficult for to small business or self-employed business to use them. In this paper, we propose the Diligence/Indolence system to use the location identification of a smart phon. To locate the position of an employee, the WiFi signal of a smart phone and the wireless access point are exploited. Because the pre-owned hardware resources are used and initial building costs are low, it is easy for small business to use the proposed D/I system with low cost.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2018년도 추계학술대회
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• pp.400-403
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• 2018

The VR / AR market has grown significantly due to the development of Virtual Reality and Augmented Reality, the core technologies of the Fourth Industrial Revolution. According to a report released by the Korea Science and Engineering Corporation (KISTEP), the global VR / AR market will grow to $ 105 billion by 2022. An important key to the growth of the VR / AR market is user immersion. VR is dependent on technology of hardware such as display and sensor for biometric signal recognition. In order to improve user's immersion feeling, it is important to transmit sensor data to display device more accurately and quickly. In this paper, we consider various sensor hardware dependencies of VR, and compare various correction methods and filtering methods to lower the Motion to Photon (MTP) time that user movement is fully reflected on the display using sensor devices.

• Journal of the Korea Society of Computer and Information
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• 제27권6호
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• pp.43-52
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• 2022

We can sense somebody's feeling fatigue, which means that fatigue can be detected through sensing human biometric signals. Numerous researches for assessing fatigue are mostly focused on diagnosing the edge of disease-level fatigue. In this study, we adapt quantitative analysis approaches for estimating qualitative data, and propose video analysis models for measuring fatigue state. Proposed three deep-learning based classification models selectively include stages of video analysis: object detection, feature extraction and time-series frame analysis algorithms to evaluate each stage's effect toward dividing the state of fatigue. Using frontal face videos collected from various fatigue situations, our CNN model shows 0.67 accuracy, which means that we empirically show the video analysis models can meaningfully detect fatigue state. Also we suggest the way of model adaptation when training and validating video data for classifying fatigue.

• Journal of the Korea Convergence Society
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• 제13권3호
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• pp.67-75
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• 2022

Medical information is variously generated not only from medical devices but also from electronic devices. Recently, related convergence technologies from big data collection in healthcare to medical AI products for patient's condition analysis are rapidly increasing. However, there are difficulties in applying them because of independent developmental procedures. In this paper, we propose an intelligent hospital information system (iHIS) model to simplify and integrate research, development and application of medical AI technology. The proposed model includes (1) real-time patient data management, (2) specialized data management for medical AI development, and (3) real-time monitoring for patient. Using this, real-time biometric data collection and medical AI specialized data generation from patient monitoring devices, as well as specific AI applications of camera-based patient gait analysis and brain MRA-based cerebrovascular disease analysis will be introduced. Based on the proposed model, it is expected that it will be used to improve the HIS by increasing security of data management and improving practical use through consistent interface platformization.

• SUVANNABHUMI
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• 제14권2호
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• pp.117-148
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• 2022

The full impact of COVID-19 has yet to be felt: while it may not define the new decade, it is clear that its immediate significance was to test many of the basic operating assumptions and procedures of global civilization. Even as vaccines are developed and utilized and even as it is possible to see the beginning of the end of COVID-19 as a discrete historical event, it remains unclear as to its ultimate importance. That said, it is evident that the academic exploration of Southeast Asia will also be affected by both the global and regional experiences of the pandemic. "Breakthroughs of Area Studies and ASEAN in the Era of Homo Untact" promises to help reconceptualize the study of the region by highlighting the importance of redefined spatial relationships and new potentially depersonalized modes of communication. This paper acknowledges these issues by suggesting that the transformations caused by the pandemic should motivate scholars to raise new questions about how to understand humanity-particularly as it is defined by societies, nations and regions. Given that COVID-19 (and the response to it) has altered many of the fundamental rhythms of globalized regions, there is sufficient warrant for re-examining both the ways in which disease, health and their related spaces affect the perceptions of Southeast Asia. To achieve "breakthroughs" into the investigation of the region, it makes sense to have another glance at the ways in which the discourses about diseases and health may have helped to inscribe definitions of Southeast Asia-or, at the very least, the nations, societies and peoples who live within it. In order to at least consider these larger issues, the discussion will concentrate on a formative moment in the conceptualization of Southeast Asia-British engagement with the region in the late 18^th and early 19^th centuries. To that end three themes will be highlighted: (1) the role that British diplomatic and military narratives played in establishing the information priorities required for the construction of colonial knowledge; (2) the importance not only of "colonial knowledge" but information making in its own right; (3) in anticipation of the use of big data, the manner in which manufactured information (related to space and disease) could function in shaping early British perceptions of Southeast Asia-particularly in Batavia and Java. This discussion will suggest that rather than see social distancing or increased communication as the greatest outcome of COVID-19, instead it will be the use of data-that is, big, aggregated biometric data which have not only shaped responses to the pandemic, but remain likely to produce the reconceptualization of both information and knowledge about the region in a way that will be at least as great as that which took place to meet the needs of the "New Imperialism." Furthermore, the definition and articulation of Southeast Asia has often reflected political and security considerations. Yet, the experience of COVID-19 could prove that data and security are now fused into a set of interests critical to policy-makers. Given that the pandemic should accelerate many existing trends, it might be foreseen these developments will herald the triumph of homo indicina: an epistemic condition whereby the human subject has become a kind of index for its harvestable data. If so, the "breakthroughs" for those who study Southeast Asia will follow in due course.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제15권4호
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• pp.257-270
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• 2022

In this paper, we design a smart factory risk improvement system and risk improvement method using AI edge devices. The smart factory risk improvement system collects, analyzes, prevents, and promptly responds to the worker's work performance process in the smart factory using AI edge devices, and can reduce the risk that may occur during work with improving the defect rate when workers perfom jobs. In particular, based on worker image information, worker biometric information, equipment operation information, and quality information of manufactured products, it is possible to set an abnormal risk condition, and it is possible to improve the risk so that the work is efficient and for the accurate performance. In addition, all data collected from cameras and IoT sensors inside the smart factory are processed by the AI edge device instead of all data being sent to the cloud, and only necessary data can be transmitted to the cloud, so the processing speed is fast and it has the advantage that security problems are low. Additionally, the use of AI edge devices has the advantage of reducing of data communication costs and the costs of data transmission bandwidth acquisition due to decrease of the amount of data transmission to the cloud.