• International Journal of Quality Innovation
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• 제4권1호
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• pp.191-204
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• 2003

The target costing technique, mathematically discussed by Sauers, only uses the $C_p index along with Taguchi loss function and $\bar{X}$-P control charts to setup goal control limits. The new specification limits derived from Taguchi loss function is linked through the $C_p value to $\bar{X}$-P control charts to obtain goal control limits. Studies have shown that the point estimator of the $C_p index, $C_p, could vary from time to time due to the sampling error. The suggested approach is to use confidence intervals, especially the lower confidence intervals, to replace the point estimator. Therefore, an improvement on target costing technique is presented by applying the lower confidence interval of the $C_p index and using both Taguchi and Spiring's loss functions together with $\bar{X}$-P charts to make this technique more robust in practice. An example is also provided to illustrate how the improved target costing technique works.

• 한국IT서비스학회지
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• 제15권2호
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• pp.219-233
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• 2016

As social problems including aging, depopulation, healthcare, poverty, a lot of government, organizations is trying to solve the problems. Recently, social innovation is emerging as strategy for solving social problems around the world. Social innovation means more effective, sustainable and new solutions that increase total values of society. This study attempts to introduce microworks of the Samasource as a case of the business-community innovation model using IT. Samasource is one of three social ventures under the nonprofit organization Sama Group established in 2008. Its mission is to alleviate worldwide poverty by connecting unemployed people in impoverished countries to digital work. Based on the internet model "microwork", they split huge digital projects into small scales, and deliver them to BOP(Bottom Of Pyramid) groups through the internet. This case describes a business model, revenue model, and impact of Samasource's Microwork. Implications of the case were suggested in the conclusion. To this end, I would like to provide a meaningful implication to researchers and founders of the South Korea.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.322-329
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• 2017

Recently, the importance of personalized healthcare(wellness) services is increasing in the era of the 4th Industrial Revolution. However, the authoring of wellness contents fused with variety of contents and the study of the system which provides the customized recommendation are insufficient. In this paper, we proposes the recommendation service system for the customized convergence wellness contents. The proposed system makes to the wellness contents by the existing cultural/tourism/leisure contents and recommends the customized wellness contents based on a user's profile and the situation information such as location and weather. The proposed systems is expected to contribute to designing the innovative and new service models for the tailored wellness content.

• The Korean Journal of Physiology and Pharmacology
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• 제23권5호
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• pp.311-315
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• 2019

Recently, digital health has gained the attention of physicians, patients, and healthcare industries. Digital health, a broad umbrella term, can be defined as an emerging health area that uses brand new digital or medical technologies involving genomics, big data, wearables, mobile applications, and artificial intelligence. Digital health has been highlighted as a way of realizing precision medicine, and in addition is expected to become synonymous with health itself with the rapid digitization of all health-related data. In this article, we first define digital health by reviewing the diverse range of definitions among academia and government agencies. Based on these definitions, we then review the current status of digital health, mainly in Korea, suggest points that are missing from the discussion or ought to be added, and provide future directions of digital health in clinical practice by pointing out certain key points.

• Current Optics and Photonics
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• 제7권2호
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• pp.176-182
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• 2023

Optical coherence tomography (OCT) is being developed to guide various ophthalmic surgical procedures. However, the high cost of the intraoperative OCT system limits its availability mostly to the largest hospitals and healthcare systems. In this paper, we present a design and evaluation of a low-cost intraoperative common-path free-hand scanning OCT system. The lensed fiber imaging probe is designed and fabricated for intraocular use and the free-hand scanning algorithm that could operate at a low scanning speed was developed. Since the system operates at low frequencies, the cost of the overall system is significantly lower than other commercial intraoperative OCT systems. The assembled system is characterized and shows that it meets the design specifications. The handheld OCT imaging probe is tested on multilayer tape phantom and ex-vivo porcine eyes. The results show that the system could be used as an intraoperative intraocular OCT imaging device.

• 인터넷정보학회논문지
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• 제22권4호
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• pp.99-110
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• 2021

Governments around the world are actively establishing strategies and initiatives to spread the use of artificial intelligence (AI), for AI is not a mere new technology, but is an innovative technology that brings about extensive changes in industrial and social structures and is a core engine that will lead the 4th Industrial Revolution. The South Korean government has also been paying attention to AI as a technology and tool for innovative growth, but its application to the industries is still rather sluggish. The government has prepared multifarious AI-related policies with the aim of constructing South Korea as an AI powerhouse, but there is no clear strategy on which detailed policies to implement first and which industries to apply AI preferentially. With these limitations of South Korea's AI policies in mind, this paper analyzed the priorities of industries in AI adoption and the priorities of AI-related national policies, using Delphi-AHP method for 30 top-level AI experts in South Korea. The results of analysis show that AI application is urgent and necessary in the fields of medical/healthcare, public and safety, and manufacturing, which seems to reflect the peak of the COVID-19 crisis in the second half of 2020 at the time of the investigation. And it turns out that policies related to AI talent cultivation, data, and R&D investment are important and urgent above all in order for organizations to apply AI. This suggests that strategies are required to focus limited national resources on these industries and policies first.

• Journal of Information Processing Systems
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• 제9권1호
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• pp.1-30
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• 2013

The capitalization of know-how, knowledge management, and the control of the constantly growing information mass has become the new strategic challenge for organizations that aim to capture the entire wealth of knowledge (tacit and explicit). Thus, knowledge mapping is a means of (cognitive) navigation to access the resources of the strategic heritage knowledge of an organization. In this paper, we present a new mapping approach based on the Boolean modeling of critical domain knowledge and on the use of different data sources via the data mining technique in order to improve the process of acquiring knowledge explicitly. To evaluate our approach, we have initiated a process of mapping that is guided by machine learning that is artificially operated in the following two stages: data mining and automatic mapping. Data mining is be initially run from an induction of Boolean case studies (explicit). The mapping rules are then used to automatically improve the Boolean model of the mapping of critical knowledge.

• 한국임상약학회지
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• 제30권4호
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• pp.217-225
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• 2020

The fourth industrial revolution, with its characteristics of "hyper-connectivity", "hyper-intelligence" and "automation", is a hot topic worldwide. It will fundamentally change industry, economy, and business models through technological innovations, such as big data, cloud computing, Internet of Things (IoT), artificial intelligence (AI), and 3D printing. In particular, the development of highly advanced information technology (IT) and AI is expected to replace human roles, thereby changing employment and occupation prospects in the future. Based on this, some predict that the profession of the pharmacist will soon disappear. To counter this, pharmacists' attention and efforts are required to seek innovative transformations in their functions by responding sensitively and promptly to changes of the fourth industrial revolution. It is also necessary to recognize the new roles of pharmacists and to develop the competencies to perform them. The fourth industrial revolution is an inevitable change of the times. At this time, we should take comprehensive and open perspectives on how the future society will change economically, culturally, and socially, and use it as an opportunity to shape the new future of pharmacists.

• Nuclear Engineering and Technology
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• 제53권8호
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• pp.2646-2651
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• 2021

A rectangular-shaped PET system with an adjustable gantry (AGPET) has been developed for imaging small animals. The AGPET system employs a new depth of interaction (DOI) method using a depth dependent reflector patterns and a new digital time pickoff method based on the pulse reconstruction method. To evaluate the performance of the AGPET, timing resolution, intrinsic spatial resolution and point source images were acquired. The timing resolution and intrinsic spatial resolution were measured using two detector modules and Na-22 gamma source. The PET images were acquired in two field of view (FOV) sizes, 30 mm and 90 mm, to demonstrate the characteristic of the AGPET. As a result of in the experiment results, the timing resolution was 0.9 ns using the pulse reconstruction method based on the bi-exponential model. The intrinsic spatial resolution was an average of 1.7 mm and the spatial resolution of PET images after DOI correction was 2.08 mm and 2.25 mm at the centers of 30 mm and 90 mm FOV, respectively. The results show that the proposed AGPET system provided higher sensitivity and resolution for small animal imaging.

• ETRI Journal
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• 제45권6호
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• pp.1079-1089
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• 2023

Stroke is one of the leading causes of long-term disability worldwide, placing huge burdens on individuals and society. Further, automatic human activity recognition is a challenging task that is vital to the future of healthcare and physical therapy. Using a baseline long short-term memory recurrent neural network, this study provides a novel dataset of stretching, upward stretching, flinging motions, hand-to-mouth movements, swiping gestures, and pouring motions for improved model training and testing of stroke-affected patients. A MATLAB application is used to output textual and audible prediction results. A wearable sensor with a triaxial accelerometer is used to collect preprocessed real-time data. The model is trained with features extracted from the actual patient to recognize new actions, and the recognition accuracy provided by multiple datasets is compared based on the same baseline model. When training and testing using the new dataset, the baseline model shows recognition accuracy that is 11% higher than the Activity Daily Living dataset, 22% higher than the Activity Recognition Single Chest-Mounted Accelerometer dataset, and 10% higher than another real-world dataset.