• Journal of Korean Academy of Nursing
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• v.54 no.2
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• pp.266-278
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• 2024

Purpose: This study aimed to investigate healthcare consumers' interest in patient safety on social media using structural topic modeling (STM) and to identify changes in interest over time. Methods: Analyzing 105,727 posts from Naver news comments, blogs, internet cafés, and Twitter between 2010 and 2022, this study deployed a Python script for data collection and preprocessing. STM analysis was conducted using R, with the documents' publication years serving as metadata to trace the evolution of discussions on patient safety. Results: The analysis identified a total of 13 distinct topics, organized into three primary communities: (1) "Demand for systemic improvement of medical accidents," underscoring the need for legal and regulatory reform to enhance accountability; (2) "Efforts of the government and organizations for safety management," highlighting proactive risk mitigation strategies; and (3) "Medical accidents exposed in the media," reflecting widespread concerns over medical negligence and its repercussions. These findings indicate pervasive concerns regarding medical accountability and transparency among healthcare consumers. Conclusion: The findings emphasize the importance of transparent healthcare policies and practices that openly address patient safety incidents. There is clear advocacy for policy reforms aimed at increasing the accountability and transparency of healthcare providers. Moreover, this study highlights the significance of educational and engagement initiatives involving healthcare consumers in fostering a culture of patient safety. Integrating consumer perspectives into patient safety strategies is crucial for developing a robust safety culture in healthcare.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.268-277
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• 2020

This study emphasizes that the survival strategy of universities should be a co-evolution strategy based on ecological thinking. Therefore, the purpose of the research is to present a theoretical framework for dividing the university innovation ecosystem into four stages and building a co-evolution strategy for each step, as universities play a prominent role in regional innovation ecosystems. Thus, our research method focused on literature research, and the theoretical framework for the university innovation ecosystem used Moore's Enterprise Ecosystem Model (1996). The university's ecological innovation strategy is divided into four stages of development, and a step-by-step co-evolution strategy is presented. Findings are summarized as follows. The pioneering stage involves the creation of values of the university-led innovation ecosystem. The expansion stage focuses on the establishment of critical mass. The authority stage covers maintaining authority and bargaining power. The renewal stage features continuous performance improvement. In particular, this theoretical model of the university-regional innovation ecosystem is meaningful in that it provides a theoretical basis for enhancing the effectiveness of government financial support projects, and for individual universities, it provides a framework for strategies suitable for their ecosystem building process.

• Proceedings of the Korean DIstribution Association Conference
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• 2001.11b
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• pp.91-122
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• 2001

This paper's object is to study the Advanced Foreign's Third Party Logistics Trend & View at Global Logistics Times. So, I analysed the Advanced Foreign U.S. & EU and the results are as follows: First, a growth in the number of outsourcing relationships has contributed to the development of more flexible organizations, based on core competencies and mutually beneficial longer-term relationships. So, the development of logistics relationships has brought mixed results. Across many industries, logistics outsourcing is a rapidly expanding source of cost savings, competitive advantage, and customer service improvements. Thus, it appears that Third Party Logistics(TPL) concepts could be useful in meeting the goals of the 1ogistics function. Second, the field of logistics and supply chain management is becoming strategically important. At the same time, it is becoming increasingly complex because of the rapid advances in management methods, e-commerce, technology, and enabling information systems. However, Third Party Logistics provider, many a times, lack broad set of skills, integrating technologies, strategies and global reach. So, Fourth Party Logistics(4PL) is the next significant evolution in supply chain outsourcing. 4PL delivers a comprehensive supply chain solution, and delivers value through the ability to impact the entire supply chain. The 4PL industry is likely to grow as more companies use e-commerce at Global Logistics Times.

• Journal of Korean Society of Rural Planning
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• v.11 no.4 s.29
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• pp.33-45
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• 2005

This study investigates the core elements of the formation and development of cluster using a multi-disciplinary approach and suggests a promoting strategy by development stage of cluster. As a sub-category of regional innovation system, the cluster has been considered as one of the most noticeable methodological argument to make the regional innovation system come true. In the meantime, this study examines the core elements of cluster shown in the theories and examples through six academic fields such as economics, geography, regional development, business administration, sociology and pedagogy and their educational back-ground. By means of establishing the incubation stage in the development of cluster, core elements are composed in the stages of birth, incubation and evolution in subsequent manner. A promoting strategy will be suggested through the implication of core elements in the reestablished stages.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1699-1708
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• 2007

The optimal power flow(OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, the OPF problem has been intensively studied and widely used in power system operation and planning. In these days, OPF is becoming more and more important in the deregulation environment of power pool and there is an urgent need of faster solution technique for on-line application. To solve OPF problem, many heuristic optimization methods have been developed, such as Genetic Algorithm(GA), Evolutionary Programming(EP), Evolution Strategies(ES), and Particle Swarm Optimization(PSO). Especially, PSO algorithm is a newly proposed population based heuristic optimization algorithm which was inspired by the social behaviors of animals. However, population based heuristic optimization methods require higher computing time to find optimal point. This shortcoming is overcome by a straightforward parallel processing of PSO algorithm. The developed parallel PSO algorithm is implemented on a PC cluster system with 6 Intel Pentium IV 2GHz processors. The proposed approach has been tested on the IEEE 30-bus system. The results showed that computing time of parallelized PSO algorithm can be reduced by parallel processing without losing the quality of solution.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2771-2776
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• 2014

Background: Breast cancer screening and higher quality mammography have resulted in an increase in the diagnosis of ductal carcinoma in situ worldwide. We compared the incidence and other factors in our cases of ductal carcinoma in situ between two recent decades. Materials and Methods: Medical records of cases of ductal carcinoma in situ who had been admitted to the surgery wards of the Cancer Institute of Tehran, Iran were evaluated from March 1993 to March 2003 as phase 1, and from April 2003 to April 2013 as phase 2. Results: Ratio of ductal carcinoma in situ to overall breast cancer was 1.27 and 3.93 in phases 1 and 2, respectively. Rates of excisional or incisional biopsies versus core needle biopsies and clinically versus mammographically detected cases as well as median size of tumors dropped between the 2 phases while a substantial rise in the number of patients attending for screening was seen in this time period. Surgical treatments followed a trend from modified radical mastectomy and axillary lymphatic dissection toward breast conserving surgery and sentinel node dissection or no axillary intervention. Conclusions: Our study shows a considerable trend toward earlier detection of breast cancer and evolution of treatment strategies toward standard less invasive surgery of DCIS in Iran.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.39-50
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• 2015

Genetic algorithm (GA) and particle swarm optimization (PSO) are two excellent approaches to multimodal optimization problems. However, slow convergence or premature convergence readily occurs because of inappropriate and inflexible evolution. In this paper, a novel optimization algorithm with a flexible grid optimization (FGO) is suggested to provide adaptive trade-off between exploration and exploitation according to the specific objective function. Meanwhile, a uniform agents array with adaptive scale is distributed on the gird to speed up the calculation. In addition, a dominance centroid and a fitness center are proposed to efficiently determine the potential guides when the population size varies dynamically. Two types of subregion division strategies are designed to enhance evolutionary diversity and convergence, respectively. By examining the performance on four benchmark functions, FGO is found to be competitive with or even superior to several other popular algorithms in terms of both effectiveness and efficiency, tending to reach the global optimum earlier. Moreover, FGO is evaluated by applying it to a parameter decision in a least squares support vector machine (LS-SVM) to verify its practical competence.

• The Journal of Industrial Distribution & Business
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• v.8 no.6
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• pp.7-16
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• 2017

Purpose - Today's world revolves around search engines which are the driving force behind any marketer. The thirst for marketing has led to the evolution of online 'Pay per click' over last few years and is the most widely used instrument. Research design, data, and methodology - Exploratory research design highlights many marketing variables getting affected by pay per click marketing. To analyze the said phenomenon, the data was gathered through questionnaire from the sample of 338 respondents which were selected by simple random sampling method mostly from the National Capital Region (NCR) of Delhi in India. The data collected from the respondents was loaded on SAS base for exploratory factor analysis and multiple regression analysis. Results - Pay per click as a marketing tool has significant impact on the consumers. The most prominent factors of pay per click marketing identified in the research are Ad quality, Competition, Targeting, Trend and Budget. Conclusions - Organic as well as inorganic ads, keeping in mind the end goal to gage the exchange of these two postings in the marked look territory. Additionally, here we dissected supported pursuit promotions in all. It would be beneficial to break down the impact of promotion position on the pay per click marketing.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.111-114
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• 1997

Usually, Evolutionary Algorithms are considered more efficient for optimal system design, However, the performance of the system is determined by fitness function and system environment. In this paper, in order to overcome the limitation of the performance by this factor, we propose a co-evolutionary method that two populations constantly interact and coevolve. In this paper, we apply coevolution to neural network's evolving. So, one population is composed of the structure of neural networks and other population is composed of training patterns. The structure of neural networks evolve to optimal structure and, at the same time, training patterns coevolve to feature patterns. This method prevent the system from the limitation of the performance by random design of neural network structure and inadequate selection of training patterns. In this time neural networks are trained by evolution strategies that are able to apply to the unsupervised learning. And in the coding of neural networks, we propose the method to maintain nonredundancy and character preservingness that are essential factor of genetic coding. We show the validity and the effectiveness of the proposed scheme by applying it to the visual servoing of RV-M2 robot manipulators.

• Biomolecules & Therapeutics
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• v.26 no.1
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• pp.45-56
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• 2018

Cancer is the leading cause of human deaths worldwide. Understanding the biology underlying the evolution of cancer is important for reducing the economic and social burden of cancer. In addition to genetic aberrations, recent studies demonstrate metabolic rewiring, such as aerobic glycolysis, glutamine dependency, accumulation of intermediates of glycolysis, and upregulation of lipid and amino acid synthesis, in several types of cancer to support their high demands on nutrients for building blocks and energy production. Moreover, oncogenic mutations are known to be associated with metabolic reprogramming in cancer, and these overall changes collectively influence tumor-microenvironment interactions and cancer progression. Accordingly, several agents targeting metabolic alterations in cancer have been extensively evaluated in preclinical and clinical settings. Additionally, metabolic reprogramming is considered a novel target to control cancers harboring un-targetable oncogenic alterations such as KRAS. Focusing on lung cancer, here, we highlight recent findings regarding metabolic rewiring in cancer, its association with oncogenic alterations, and therapeutic strategies to control deregulated metabolism in cancer.