• Title/Summary/Keyword: Learning.growth factor

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A Study on Impact of Deep Learning on Korean Economic Growth Factor

  • Dong Hwa Kim;Dae Sung Seo
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.4
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    • pp.90-99
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    • 2023
  • This paper deals with studying strategy about impact of deep learning (DL) on the factor of Korean economic growth. To study classification of impact factors of Korean economic growth, we suggest dynamic equation of microeconomy and study methods on economic growth impact of deep learning. Next step is to suggest DL model to dynamic equation with Korean economy data with growth related factors to classify what factor is import and dominant factors to build policy and education. DL gives an influence in many areas because it can be implemented with ease as just normal editing works and speak including code development by using huge data. Currently, young generations will take a big impact on their job selection because generative AI can do well as much as humans can do it everywhere. Therefore, policy and education methods should be rearranged as new paradigm. However, government and officers do not understand well how it is serious in policy and education. This paper provides method of policy and education for AI education including generative AI through analysing many papers and reports, and experience.

Effects of Yongohkgo on Growth and Learning Ability in Growth Deficiency Rat With Linsufficient Nutrition Diet (영양소 결핍으로 유도한 성장장애 흰쥐에서 용옥고(龍玉膏)가 성장 및 학습효과에 미치는 영향)

  • Kong, In-Pyeo;Cha, Yun-Yeop
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.22 no.3
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    • pp.624-629
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    • 2008
  • Effects of Kyungohkgo Ga Nokyong(Yongohkgo) on growth development and learning ability were investigated growth and intellectual impairment rat with insufficient nutrition diet. We divided male Sprague-Dawley rats into 4 groups. They were Normal group, Growth deficiency rat with insufficient nutrition diet group, Growth deficiency rat with 0.1% Yongohkgo group and 0.2% Yongohkgo group. They were administered for 5 weeks. We measured body weight, and morris water maze test in escape distance, escape time and escape speed, serum growth hormone, insulin-like growth factor and thyroid stimulating hormone, RBC, concentration of Hb and PCV ratio, total WBC and its composition, the values of GOT and GPT activities. The results are as follows that Yongohkgo 0.1%, 0.2% groups were showed significantly different than control groups in body weight and the counts of RBC. In the morris water maze test, in escape distance and escape time, in concentration of Hb and PCV ratio, 0.2% Yongohkgo group were significantly different than control groups. Serum growth hormone, insulin- like growth factor and thyroid stimulating hormone showed a tendency to increase in Yongohkgo groups. The counts of total WBC and its composition, GOT, GPT activities showed no significantly different in all treatment groups. These results suggested that Yongohkgo have an effect of promoting growth and learning ability of rats and might be effect to treat various kinds of growth and learning ability delay in children.

The Binomial Sensitivity Factor Hyper-Geometric Distribution Software Reliability Growth Model for Imperfect Debugging Environment (불완전 디버깅 환경에서의 이항 반응 계수 초기하분포 소프트웨어 신뢰성 성장 모델)

  • Kim, Seong-Hui;Park, Jung-Yang;Park, Jae-Heung
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.4
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    • pp.1103-1111
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    • 2000
  • The hyper-geometric distribution software reliability growth model (HGDM) usually assumes that all the software faults detected are perfectly removed without introducing new faults. However, since new faults can be introduced during the test-and-debug phase, the perfect debugging assumption should be relaxed. In this context, Hou, Kuo and Chang [7] developed a modified HGDM for imperfect debugging environment, assuming tat the learning factor is constant. In this paper we extend the existing imperfect debugging HGDM for tow respects: introduction of random sensitivity factor and allowance of variable learning factor. Then the statistical characteristics of he suggested model are studied and its applications to two real data sets are demonstrated.

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Effects of BSC Model's Non-financial Factors on Financial Performance in General Hospitals (종합병원의 비재무적 요인이 재무성과에 미치는 영향 - BSC 기법을 중심으로)

  • Yang, Jong-Hyun;Chang, Dong-Min
    • Korea Journal of Hospital Management
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    • v.16 no.3
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    • pp.57-74
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    • 2011
  • The purpose of this study is to analyze the relationship between the BSC model's non-financial factors such as learning and growth, internal process, customer and financial factor in general hospitals. To achieve research purpose, the data were collected from 293 employees of 5 hospitals using a standardized questionnaires which were constructed to include BSC model, and applied the structural equation modeling to examine the relationship between non-financial and financial factor. The results show that the learning and growth factor of the model has positive effects of the internal process and customer factor. The internal process and customer factor are strongly related to financial factor. Hospitals have to know non-financial factor which has positively relate to financial factor. Therefore, the results of this study help to enhance the health care center to become aligned and focused on implementing the long-term competitive strategy. This study proposes an effective performance indicators for general hospitals and it is expected to be likely to have positive influence upon enhancing services of general hospitals.

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The effects of step learning according to level mainly performed at math room on the growth of problem-solving ability (수학실 중심의 수준별 단계학습이 문제해결력에 미치는 영향)

  • 박기석;신숙철
    • Journal of the Korean School Mathematics Society
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    • v.2 no.1
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    • pp.79-91
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    • 1999
  • The aim of this study focused on student-centered learning not teacher-centered teaching in middle school math classes. This study was performed to check the growth of students' problem-solving abilities, learning attitudes and changes in learning motivation among affective characteristics. The results of this study is as followings: 1) The controlled group a heterogeneous group which had classes in a math room, had more meaningful growth than the uncontrolled group. The results of the study show that the problem-solving abilities of the high-leveled group were better than those of the low-leveled group. 2) The controlled group has shown meaningful difference in their mean in learning aptitude test and attitude test converted their score into 100 points than uncontrolled group, and various kinds of learning materials suitable for problem solving are proved as a good learning factor to induce students' motivation and interest. 3) Students prefer to have classes in a math room to the small-sized and large-numbered classrooms. The atmosphere in a math room is more suitable to improving their problem-solving abilities. In this context, the classes performed in a math room are fairly positive. Consequently, students' leveled learning activities performed in a math room can get their learning motivation and attention from those who are lack of interest and think math is difficult and be effective to increase their problem-solving abilities as a learning method for acquiring the whole course of solving the problems.

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과학기술정책을 위한 국가학습조직모형

  • 오형식;신상문
    • Journal of Technology Innovation
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    • v.5 no.2
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    • pp.22-47
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    • 1997
  • This paper suggests a model of Living & Learning Nation as a new ploicy framework. It is a combination of Living Nation and Learning Nation. Living Nation model takes the nation as a living entity composed of spirit, resource, and communication : it grows but healthy and balanced growth is needed, its organs are closely connected, it has a circulation system, the 'spirit' factor plays the central role, etc.. Learning Nation model is a national level version of learning organization concept. The model defines new perspectives on the objectives, span of means, and the role of government in S&T policy. Therefore, the model can be used to give new insights to policymakers of developing countries facing the knowledge-based economy.

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A Study on the Relationship between Intra-team Conflict and Team Innovative Performance and the Mediating Role of Team Learning Behaviors in R&D Teams (연구개발팀에서 팀내 갈등과 팀 혁신성과간의 관계에서 팀 학습행동의 매개역할)

  • Lee, Jun Ho;Kim, Hack Soo;Kim, Ji Yeon
    • Knowledge Management Research
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    • v.14 no.5
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    • pp.81-100
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    • 2013
  • In this era of cut-throat competition, innovation is a source of competitive advantage, and securing core competency through innovation plays a pivotal role in ensuring the survival and growth of an organization. In an organization, R&D team is a core division driving innovation, and creative tension and conflict among researchers fuels innovative performance. Despite heated debate over the positive and negative effects of conflict, insufficiently-identified process factors have left sophisticated mechanisms between conflicts and effects unaddressed. This study assumes that team learning behaviors can bean important process factor given that conflict propels learning, and that learning is a decisive factor in creating competitive advantage. This study conducted an empirical analysis of the relationship between relationship/task conflict and team innovative performance, and the mediating role of team learning behaviors using data collected from a questionnaire sent out to the heads of 262 R&D teams and second highest-ranking officials thereof. The analysis conducted based on structural equation model indicates that relationship conflict has negatively affected team learning behaviors, whereas task conflict has positively influenced team learning behaviors(full mediation effect), team learning behaviors has positively influenced team innovative performance. Based on these results, the study has suggested implications of intra-team conflict and team learning behaviors for team innovative performance.

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A Review of Exercise and Neural Plasticity (운동과 신경가소성에 대한 고찰)

  • Song, Ju-min
    • PNF and Movement
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    • v.6 no.2
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    • pp.31-38
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    • 2008
  • Purpose: The purpose of this study were to overview the effect of exercise on neural plasticity and the proteins related to neural plasticity. Results: Exercise increased levels of BDNF(brain-derived neurotrophic factor), Insulin-like growth factor-I (IGF-I), Synapsin, Synaptophysin, VEGF(vascular endothelial growth factor) and other growth factors, stimulate neurogenesis, increase resistance to brain insult and improve learning and mental performance. These proteins improved synaptic plasticity by directly affecting synaptic structure and potentiating synaptic strength, and by strengthening the underlying systems that support plasticity including neurogenesis, metabolism and vascular function. Conclusion: Exercise-induced structural and functional change by these proteins can effect on functional movement, cognition in healthy and brain injured people and animals.

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Factors Affecting Financial Performance of ERP System Based on BSC Framework: The Moderate Effect of Strategic Alignment and the Mediating Effect of Customer and Business Process Perspectives (BSC프레임워크 기반 ERP시스템의 재무 성과 영향요인: 전략적 연계성의 상호작용효과와 고객 및 비즈니스 프로세스 관점의 매개 효과)

  • Park, Ki Ho
    • The Journal of Information Systems
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    • v.30 no.3
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    • pp.93-112
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    • 2021
  • Purpose Recently, many organizations are actively adopting enterprise architecture (EA) as a methodology to manage IT assets and build IT-based business system. This study intended to empirically examine how the role of EA operating unit and utilization capability of organizational members impact on system performance at the post-adoption stage. A balanced score card (BSC) is being used as a framework for a company's key performance indicator (KPI). Design/methodology/approach This study tried to investigate the causal relationship between the four perspectives of the balanced scorecard as an influencing factor of the introduction of the Enterprise Resource Planning (ERP) on the financial value. In particular, the mediating effect between the customer's point of view and the business process point of view was investigated between the learning growth point of view and the financial point of view, and the interaction effect (regulating effect) of strategic linkage in the system introduction process was investigated. Findings The results of the study were first, that the organizational learning and growth perspective had a positive effect on the customer perspective, business process, and financial perspective. In addition, the customer perspective and the process perspective also had a positive influence on the financial perspective. Second, between the learning growth and financial perspectives, the customer perspective and the process perspective showed a partial mediating effect. Third, as for strategic linkage, the interaction effect between the customer perspective, the learning growth perspective, and the process perspective and the financial perspective was not significant. The results of this study are expected to provide a framework for performance evaluation to organizations that have introduced ERP systems.

Extraction of the OLED Device Parameter based on Randomly Generated Monte Carlo Simulation with Deep Learning (무작위 생성 심층신경망 기반 유기발광다이오드 흑점 성장가속 전산모사를 통한 소자 변수 추출)

  • You, Seung Yeol;Park, Il-Hoo;Kim, Gyu-Tae
    • Journal of the Semiconductor & Display Technology
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    • v.20 no.3
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    • pp.131-135
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    • 2021
  • Numbers of studies related to optimization of design of organic light emitting diodes(OLED) through machine learning are increasing. We propose the generative method of the image to assess the performance of the device combining with machine learning technique. Principle parameter regarding dark spot growth mechanism of the OLED can be the key factor to determine the long-time performance. Captured images from actual device and randomly generated images at specific time and initial pinhole state are fed into the deep neural network system. The simulation reinforced by the machine learning technique can predict the device parameters accurately and faster. Similarly, the inverse design using multiple layer perceptron(MLP) system can infer the initial degradation factors at manufacturing with given device parameter to feedback the design of manufacturing process.