63 research outputs found
Implementation of Shipβs Lift Safety Management System based on NMEA 2000
Lift industry is a field that is mechanical, electrical and electronic technology and constantly requires inspection and maintenance considering various applications and various types. Recently, various lift control and monitoring technologies with IT are developing for lifts on land. But technologies with IT have been hardly done in shipβs lift that is consistently assured safety and reliability of life cycle for its parts in poor environment. Unlike general lifts, shipβs lifts should be able to operate reliably in rolling and pitching according to the operation of the ship. except the stop button operation by hand.
In addition, it has been designed and operated to withstand marine environments that are worse than general land lifts, as it has to satisfy specific performance requirements such as dust, vibration, shock, electromagnetic waves and noise on board.
However, the PLC-based lift which is limited to the simple function of lift operation control has no safety related control and monitoring system. In this paper, we implemented embedded main cotroller, floor controller and car controller that meet the requirements and use NMEA network protocol by analyzing home and abroad integrated lift operation and management systems. Especially, we secured reliability of maintenance by real-time fault diagnosis and control that was implemented with limit switch, gyro sensor, temperature / humidity / barometric pressure sensor and fire detection sensor thinking over the environmental conditions of terrestrial and shipβs lift. The remote safety diagnosis and maintenance system for maritime lift introduced in this paper is based on real - time remote safety diagnosis based on marine - land maritime broadband communication based on real - time remote diagnosis and quick maintenance system, which enables rapid maintenance, reduction of maintenance cost, And establishing a formalized safety inspection system.1. μ λ‘
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1.2 μ°κ΅¬μ νμμ± 2
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2.1 μΉκ°κΈ°μ κΈ°μ λν₯ λ° κ΅¬μ‘° 5
2.2 μ λ° νμ€λ€νΈμν¬ 9
2.3 ν΄μ κ΄λμ ν΅μ μμ€ν
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2.4 μμ λͺ¨λν°λ§ μμ€ν
15
3. μ λ°μ© μΉκ°κΈ° μμ κ΄λ¦¬ μμ€ν
μ€κ³ λ° κ΅¬ν
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κ°μ 18
3.2 ν
μ€νΈλ² λ μΌμ μ€μΉ ꡬν 19
3.3 μΉκ°κΈ° μμ κ΄λ¦¬ μ μ΄κΈ° 41
3.4 μ λ°μ© μΉκ°κΈ° μμ κ΄λ¦¬ λͺ¨λν°λ§ μ₯μΉ 61
4. μ λ°μ© μΉκ°κΈ° μμ κ΄λ¦¬ μμ€ν
μ€ν λ° λ°μ΄ν° κ²μ¦
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μ°λ 76
4.2 λ°μ΄ν° κ²μ¦ 78
5. κ²° λ‘ 124
μ°Έκ³ λ¬Έν 125
κ°μ¬μ κΈ 129Docto
Development and application of stent-based image guided navigation system for oral and maxillofacial surgery
Purpose : The purpose of this study was to develop a stent-based image guided surgery system and to apply it to oral and maxillofacial surgeries for anatomically complex sites.
Materials and Methods : We devised a patient-specific stent for patient-to-image registration and navigation. Threedimensional positions of the reference probe and the tool probe were tracked by an optical camera system and the relative position of the handpiece drill tip to the reference probe was monitored continuously on the monitor of a PC. Using 8 landmarks for measuring accuracy, the spatial discrepancy between CT image coordinate and physical coordinate was calculated for testing the normality.
Results : The accuracy over 8 anatomical landmarks showed an overall mean of 0.56Β±0.16 mm. The developed system was applied to a surgery for a vertical alveolar bone augmentation in right mandibular posterior area and possible interior alveolar nerve injury case of an impacted third molar. The developed system provided continuous monitoring of invisible anatomical structures during operation and 3D information for operation sites. The clinical challenge showed sufficient accuracy and availability of anatomically complex operation sites.
Conclusion : The developed system showed sufficient accuracy and availability in oral and maxillofacial surgeries for anatomically complex sites.
(Korean J Oral Maxillofac Radiol 2009; 39 : 149-56)grant of the Korea healthcare technology R & D Project Ministry for Health. Welfare & Family Affairs. Republic of Korea(A08-4491-AL2023-08N1-00030B)
Designing Transparent Electrodes Materials Toward Broadband Light Trapping
νμλ
Όλ¬Έ (λ°μ¬)-- μμΈλνκ΅ λνμ : μ¬λ£κ³΅νλΆ, 2015. 8. λ°λ³μ°.Transparent conducting oxides (TCOs) have been used for various
optoelectronic applications, such as flat-panel displays and thin-film solar cells.
Especially for a-Si thin-films solar cells, light-scattering capability of TCOs via
surface texturing is one of the most important characteristics due to effective
scattering enhances power-conversion efficiency. Among various TCOs, ZnO:Al
has received strong attention because of its larger feature size by wet-chemical
etching. Basically, textured morphology by wet etching depends on the
nanostructure of TCOs due to the anisotropy of etching rates. However,
nanostructural control of TCOs in mass manufacturing is pretty limited with
consideration of electrical conductivity and high throughput. Therefore, surface
texturing by simple etching for the given TCO nanostructures offers a great merit
for the strategy of TCO development.
In this thesis, the novel etching system by organic acid for the surface-textured
ZnO:Al films is investigated. The Chap. 1 describes the general scientific context
and the research field in which this thesis is included. First, a brief overview of
the photovoltaic technologies and the current issues of the Si thin-film solar cells.
Second, the TCOs are introduced and their use as a front electrode in Si thin-film
solar cells is explained. Finally, the motivation and objectives of this work are
summarized.
In Chap. 2, an organic acid for the surface texturing of ZnO:Al is introduced
as an alternative to conventional HCl. The texturing behavior by oxalic acid is
investigated in terms of vertical roughness, lateral correlation length, and thickness
change according to the crater evolution. Etching with oxalic acid results in
superior light-scattering performance (by ~8% increase at Ξ» = 1000 nm) with
maintaining transparency and resistance, compared to etching with HCl. This
fascinating behavior is understood by crater evolution with the difference in relative
etching rates. Significantly, this simple and reproducible texturing tactic extends
tunability for desirable TCO morphology, enabling efficient light trapping, and
therefore appears potentially applicable for large-scale photovoltaic devices in
industry. Lastly, all results and conclusion of the thesis are summarized in Chap.
3.Abstract i
List of Figures v
List of Table xiv
Chapter 1. Overview 1
1.1. General Introduction to Solar Cells 1
1.1.1. Basic Operation Principle of the Solar Cells 1
1.1.2. Classification of Solar Cells 7
1.2. Si Thin Film Solar Cells 11
1.2.1. Introduction of the Si Thin Film Solar Cells 11
1.2.2. Light Management Technology in Si Thin Film Solar Cells 13
1.3. Overview of Transparent Conducting Oxide in Si Thin Film Solar Cells 17
1.3.1. The Factors determining Textured Morphology 21
1.3.2. The Wet-Chemical Etching of ZnO:Al Films 27
1.4. References 39
Chapter 2. Organic-Acid Texturing of ZnO:Al Toward Broadband Light Scattering for Si
Thin-Film Solar Cells 44
2.1. Introduction 44
2.2. Experimental Section 46
2.3. Results and Discussion 46
2.4. Conclusions 68
2.5. References 69
Chapter 3. Summary 73
Appendix
A. 1. Facile Conversion Synthesis of Densely-Formed Branched ZnO Nanowire Arrays for
Quantum-Dot-Sensitized Solar Cells 74
A.1.1. Introduction 74
A.1.2. Experimental Section 76
A.1.2.1. Synthesis of 1-D Nanostructures 76
A.1.2.2. Branched ZnO Nanowire Growth 77
A.1.2.3. Device Fabrication 77
A.1.2.4. Characterization 78
A.1.3. Results and Discussion 79
A.1.4. Conclusions 101
A.1.5. References 102
A. 2. List of Publications and Presentations 109
A.3.1. Publications (International) 109
A.3.2. Presentation (International) 113
A.3.3. Presentation (Domestic) 113
κ΅λ¬Έ μ΄λ‘ 114Docto
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Thesis (doctoral)--μμΈλνκ΅ λνμ :μλͺ
κ³ΌνλΆ,2002.Docto
κ° λμΆν λͺ¨λΈμμ μΈν¬ ν νμμ λΉκ°μνΌκΈ°μ μ κ²½μ€κΈ°μΈν¬ μ΄μ ν¨κ³Ό μ°κ΅¬
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Όλ¬Έ (μμ¬)-- μμΈλνκ΅ λνμ : μνκ³Ό μ€κ°μν μ 곡, 2016. 2. μ΄μ건.Cell-based therapy for intracerebral hemorrhage (ICH) has a substantial therapeutic potential. However, methods to effectively deliver, and improve survival and differentiation of stem cells have not been established. We developed a cell sheet for neural stem cells, with successful application in a canine ICH model. We designed a composite cell sheet made of neural progenitors derived from human olfactory epithelium and human adipose tissueβderived stroma cells. We also generated a canine model of ICH, by manually injecting and then infusing autologous blood under an arterial pressure. We transplanted cells sheets (cell sheet group) or saline (control group) at the cortex over the hematoma, at 2 weeks from ICH induction. At 4 weeks from the cell transplantation, cell survival, migration and differentiation were evaluated. Hemispheric atrophy and neurobehavioral recovery were also compared between two groups. The cell sheet was rich of extracellular matrices and highly expressed neuroprotective cytokines, as well as marker for neuron development. The transplanted cells successfully survived for 4 weeks, and the significant portion of them migrated in the perihematomal site and differentiated to neurons and pericytes. Transplantation of cell sheets alleviated hemorrhage-related hemispheric atrophy and modestly improved functional recovery. In conclusion, cell sheet delivers neural stem cells directly to the target area with increased cell survival and differentiation, as well as effectively reduce the hemispheric atrophy and modestly improves functional recovery.INTRODUCTION 1
MATERIALS AND METHODS 2
RESULTS 9
DISCUSSION 11
REFERENCES 16
κ΅λ¬Έμ΄λ‘ 27Maste
(The) effect of intravenous patient-controlled analgesia on patients with coronary bypass grafting surgery
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[μλ¬Έ]Thoracotomy is considered one of the most painful surgical procedures.Thus optimal pain control is essential in the postoperative care of thoracotomy patients. Pain is the most important factor responsible for ineffective ventilation and cough in patients undergoing thoracotomy.Due to severe pain after open thoracotomy the postoperative pain control is essential to decrease pulmonary complications, and improve a patients recovery.γIntravenous patient-controlled analgesia is widely used for postoperative pain control.The purpose of this methodological study is to compare the effect of patient-controlled analgesia on postoperative patients, coronary artery bypass graft. To compare the effect of patient controlled analgesia, 60 patients undergoing coronary artery bypass graft were chosen randomly. They underwent pain management with either intravenous patient-controlled analgesia or intermittent intravenous opioid regimen. Pain intensity(VAS), heart rate, blood pressure, and additional used of opioid dose, postoperative hospital stay were measured at predetermined time intervals for postoperative 48 hours after measurement of preoperative baseline values. Comparisons were then made between the two groups and among individuals within each group.Data were of analyzed by statistical methods of multiple comparison using the SPSS 12.0 program.IV-PCA improved postoperative pain relief, but did not suppress efficiently the heart rate, blood pressure. and IV-PCA group did small dose of opioid than intermittent intravenous opioid regimen. There were no significant statistical differences between the two groups in the durations of their ICU stay but IV-PCA groups is shorted their hospital stay than ones.The use of PCA provided better pain relief on patients undergoing coronary artery bypass graft.ope
APPLICATION OF REDUCED ORDER MODEL FOR METHANE JET FLAME BASED ON DEEP CONVOLUTIONAL AUTOENCODER
In this work, the convolutional autoencoder is applied to the reduced order model for a turbulentγmethane jet flame. Autoencoder is a machine learning algorithm, which reduces the problem dimension by non-linear projection. It has an advantage in reconstruction of data with significant non-linearity. Additionally, with a convolutional layer the characteristics of original data can be trained with a relatively small number of hyper-parameters. To check accuracy of the reduced order model using the convolutional autoencoder, we applied it to surrogate model and sparse reconstruction problem, and compared it with other dimension reduction algorithms. For model training, five parameters are selected as the model training parameters and 20 and 40 sensor data are extracted for the sparse reconstruction problem. The proposed convolutional autoencoder shows better accuracy than the linear projection-based dimension reduction algorithm.22Nkc
A study on Chinese international students residing in Korea about their drinking habits and depression before and after studying in Korea
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곡νκ³Ό, 2020. 8. μ΄μ¬μ±.Deep learning society has grown tremendously in recent years, leading to increasing demand for large amounts of data. However, it is difficult to gather enough labeled data similar to unlabeled real-world test data. We have to apply the domain adaptation to overcome this limitation. Domain adaptation learns by taking into account differences in probability distributions between different domains, so it outcomes a model that can be applied to both domains. In this dissertation, we first focus on developing domain adaptation methods in terms of learning appropriate representation. We propose a class-conditional domain invariant learning method that can learn a feature space in which features in the same class are expected to be mapped nearby. Improving the performance of domain adaptation has an expected impact that the application area of machine learning will be widened because a large number of unsupervised data can be used for machine learning. In addition to these direct expected impacts, domain adaptation techniques can be used in many aspects of deep learning. The key characteristic of domain adaptation is that it builds a machine learning model that can be applied to two different distributions. Therefore, domain adaptation based approaches can be widely used in machine learning areas that handle two different distributions, such as defense against adversarial attacks or fair machine learning. Robustness of deep learning is important since it can induce various security and safety problems. We focus on modeling deep networks that are robust against adversarial attacks by using domain adaptation methods. Considering normal samples as the source domain and adversarial samples as target domain, we suggest novel Wasserstein distance-based domain adaptation method that can enhance model robustness. As the increase in machine learning influences decisions about important aspects of our lives, the demand for a fair machine learning model has increased rapidly in recent years. We investigate a methodology for developing a fair classification model for data with limited or no labels, by transferring knowledge from another data domain where information is fully available, which is done by controlling the Wasserstein distances between relevant distributions. In real-world applications of machine learning, there are many cases where we need to handle data from various distributions. In these cases, domain adaptation can be the right solution because it considers the difference of probabilistic distributions of two domains. We expect, our algorithms can be helpful to overcome these limitations and be applied to build fair and robust models.μ΅κ·Ό λ₯ λ¬λμ νμ©μ μμ²λκ² μ¦κ°νμ¬ λλμ λ°μ΄ν°μ λν μμκ° μ μ μ¦κ°νκ³ μλ€. κ·Έλ¬λ νμ€μ μ μ©ν΄μΌ ν ν
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λ³Έ μ°κ΅¬μμλ λλ©μΈ μ μμ νμ©νμ¬ λ λλ©μΈμ μ μ© λ μ μλ νν νμ΅μ μ μνλ€. μ°λ¦¬λ ν΄λμ€ μμ‘΄μ (class-conditional)μΈ λλ©μΈ μ μ νννμ΅ λ°©λ²μ μ μνλ€. μ΄ νννμ΅μ λ λλ©μΈμμ κ°μ ν΄λμ€λ₯Ό κ°μ§λ μνλ€μ μλ² λ©μ μ μ¬νκ² λ§λ€ μ μλ€. λλ©μΈ μ μ λ°©λ²μ μ§κΈκΉμ§ νμ©λμ§ λͺ»νλ λλμ λΌλ²¨μ΄ μλ λ°μ΄ν°λ€μ νμ΅μ νμ©ν μ μμΌλ―λ‘ κΈ°κ³ νμ΅μ νμ©μ΄ νμ₯λλ€λ κΈ°λν¨κ³Όκ° μλ€.
μ§μ μ μΈ κΈ°λν¨κ³Ό μ΄μΈμλ λλ©μΈ μ μ λ°©λ²μ λ₯λ¬λμ μ¬λ¬ μΈ‘λ©΄μλ νμ©λ μ μλ€. λλ©μΈ μ μμ μ£Όμ νΉμ§μ λ κ°μ§ λ€λ₯Έ λΆν¬μ μ μ©ν μ μλ κΈ°κ³ νμ΅ λͺ¨λΈμ ꡬμΆνλ€λ κ²μ
λλ€. λ°λΌμ λλ©μΈ μ μ κΈ°λ°μ μ κ·Ό λ°©μμ μ λμ 곡격(adversarial attack)μ λν μμ μ±(robustness) μ΄λ 곡μ ν(fair) κΈ°κ³ νμ΅ κ°μ΄ λ κ°μ§ λ€λ₯Έ λΆν¬λ₯Ό μ²λ¦¬νλ κΈ°κ³ νμ΅ μμμμ λ리 μ¬μ©λ μ μλ€.
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κΈ°κ³ νμ΅μ νμ©μ΄ μ°λ¦¬ μΆμ μ€μν μΈ‘λ©΄μ κ΄ν κ²°μ μ μν₯μ λ―ΈμΉλ©΄μ, μ΅κ·Όμλ λͺ¨λΈμ 곡μ μ±μ κ΄ν κ΄μ¬μ΄ κΈκ²©ν μ¦κ°νλ€. λ³Έ μ°κ΅¬μμλ λλ©μΈ μ μ λ°©λ²λ‘ μ νμ©νμ¬ μ±λ³μ΄λ νΌλΆμ κ°μ λ―Όκ° λ³μ (sensitive attribute)κ° μλ‘ λ€λ₯Έ λ°μ΄ν°λ€μμ λͺ¨λ 곡μ νκ² μλν μ μλ λ°©λ²λ‘ μ μ μνλ€. κΈ°μ‘΄μ νκ°μ§ λ³μλ§ μ§μ€νλ κ²μ λμ΄ μ΄λ₯Ό νμ©νλ©΄ λ€μν λ―Όκ° λ³μμ λνμ¬ κ³΅μ ν κΈ°κ³νμ΅μ νμ΅ν μ μλ€.
λ₯λ¬λ λͺ¨λΈμ νμ€λ¬Έμ μ μ μ©ν λμλ λ€μν λΆν¬λ₯Ό λ°λ₯΄λ λ°μ΄ν°λ₯Ό λμμ μ²λ¦¬ν΄μΌνλ μν©μ΄ μμ£Ό λ°μνλ€. λλ©μΈ μ μμ λ λλ©μΈμ νλ₯ λΆν¬ μ°¨μ΄λ₯Ό κ³ λ €νκΈ° λλ¬Έμ μ΄λ¬ν μν©μ μ μ°νκ² μ¬μ©λ μ μλ€. λν, λλ©μΈ μ μ κΈ°μ μ μμ μ μ΄λ©° 곡μ ν λ₯λ¬λ λͺ¨λΈμ νμ΅μ ν΅μ¬ κΈ°μ λ‘ νμ©λ μ μλ€. λ°λΌμ λ³Έ μ°κ΅¬μμ μ μν μκ³ λ¦¬μ¦μ΄ λ₯λ¬λμ νκ³λ₯Ό 극볡νκ³ κ³΅μ νκ³ μμ μ μΈ λͺ¨λΈμ ꡬμΆνλ λ° νμ©λκΈ°λ₯Ό κΈ°λνλ€.Chapter 1 Introduction 1
1.1 Motivation of the Dissertation 1
1.2 Aims of the Dissertation 7
1.3 Organization of the Dissertation 9
Chapter 2 Class-conditional Domain Invariant Representation Learning 11
2.1 Chapter Overview 11
2.2 Theoretical Background 16
2.2.1 Domain Adaptation Setting 16
2.2.2 New Generalization Upper Bounds 19
2.3 Proposed Method 22
2.3.1 Motivation 22
2.3.2 Class-conditional loss function 24
2.3.3 Model Architecture 27
2.4 Experimental Results 28
2.4.1 Toy example 29
2.4.2 Digit Classi cation 31
2.4.3 Image classification 36
2.5 Chapter Summary 39
Chapter 3 Domain Adaptation for Defending Against Adversarial Attacks 47
3.1 Chapter Overview 47
3.2 Preliminaries 51
3.3 Proposed Method 54
3.3.1 Wasserstein Distance 54
3.3.2 Upper Bound 56
3.3.3 Sliced Wasserstein Adversarial Training (SWAT) 58
3.4 Experimental Results 63
3.5 Chapter Summary 68
Chapter 4 Domain Adaptation in Transferring Model knowledge and Fairness 73
4.1 Chapter Overview 73
4.2 Preliminaries 78
4.3 Theoretical Background 80
4.3.1 Notation 80
4.3.2 Fairness in terms of Wasserstein distance 82
4.3.3 Generalization bound for domain transfer 85
4.4 Proposed Method 90
4.5 Experimental Results 97
4.5.1 Experimental Settings 97
4.5.2 Results 101
4.6 Chapter Summary 105
Chapter 5 Conclusion 115
5.1 Summary 115
5.2 Future Work 116
Bibliography 119Docto
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