33 research outputs found
μ±λ΄μ΄ μ λ’° μλ°μΌλ‘λΆν° ν볡νλ λ° μ¬κ³Όμ 곡κ°μ΄ λ―ΈμΉλ μν₯
νμλ
Όλ¬Έ(μμ¬) -- μμΈλνκ΅λνμ : μ¬νκ³Όνλν μ¬λ¦¬νκ³Ό, 2022. 8. νμμ.In the present study, we investigated how chatbots can recover user trust after making errors. In two experiments, participants had a conversation with a chatbot about their daily lives and personal goals. After giving an inadequate response to the userβs negative sentiments, the chatbot apologized using internal or external error attribution and various levels of empathy. Study 1 showed that the type of apology did not affect usersβ trust or the chatbotβs perceived competence, warmth, or discomfort. Study 2 showed that short apologies increased trust and perceived competence of the chatbot compared to long apologies. In addition, apologies with internal attribution increased the perceived competence of the chatbot. The perceived comfort of the chatbot increased when apologies with internal attribution were longer as well as when apologies with external attribution were shorter. However, in both Study 1 and Study 2, the apology conditions did not significantly increase usersβ trust or positively affect their perception of the chatbot in comparison to the no-apology condition.
Our research provides practical guidelines for designing error recovery strategies for chatbots. The findings demonstrate that Human-Robot Interaction may require an approach to trust recovery that differs from Human-Human Interaction.λ³Έ μ°κ΅¬μμλ μ±λ΄μ΄ λν μ€ μ€λ₯κ° μμμ λ μ¬μ©μμ μ λ’°λ₯Ό ν볡ν μ μλ λ°©λ²μ λνμ¬ νμνμλ€. λ λ²μ μ€νμμ μ°Έμ¬μλ€μ μΌμμνκ³Ό μμ μ λͺ©νμ κ΄νμ¬ μ±λ΄κ³Ό λνλ₯Ό λλμλ€. μ±λ΄μ μ°Έμ¬μμ λΆμ μ κ°μ μ λν΄ λΆμ μ ν μλ΅μ ν ν, κ³΅κ° μμ€μ λ¬λ¦¬νλ©° λ΄μ κ·μΈ νΉμ μΈμ κ·μΈμ μ¬μ©νμ¬ μ¬κ³Όνλ€. μ°κ΅¬ 1μ λ°λ₯΄λ©΄ μ¬κ³Όμ μ’
λ₯λ μ¬μ©μμ μ λ’°λ μ±λ΄μ μ§κ°λ μ λ₯ν¨, λ°λ»ν¨, λΆνΈκ°μ μ μλ―Έν μν₯μ μ£Όμ§ μμλ€. μ°κ΅¬ 2 κ²°κ³Ό 짧μ μ¬κ³Όλ κΈ΄ μ¬κ³Όλ³΄λ€ μ±λ΄μ λν μ¬μ©μμ μ λ’°μ μ§κ°λ μ λ₯ν¨μ λ ν¬κ² λμλ€. λν, λ΄μ κ·μΈμ μ¬μ©νλ μ¬κ³Όκ° μ±λ΄μ μ§κ°λ μ λ₯ν¨μ λ ν¬κ² ν₯μμμΌ°λ€. λ΄μ κ·μΈμ μ¬μ©νλ μ¬κ³Όμ κ²½μ° κΈΈμ΄κ° κΈΈ λ, μΈμ κ·μΈμ μ¬μ©νλ μ¬κ³Όμ κ²½μ° κΈΈμ΄κ° 짧μ λ μ¬μ©μλ€μκ² λ νΈμνκ² λκ»΄μ‘λ€. κ·Έλ¬λ μ°κ΅¬ 1κ³Ό μ°κ΅¬ 2 λͺ¨λμμ μ¬κ³Ό 쑰건μ μ¬μ©μμ μ λ’°λ₯Ό μ μλ―Ένκ² μ¦κ°μν€κ±°λ μ±λ΄μ μΈμμ μ μλ―Ένκ² κΈμ μ μΈ μν₯μ λ―ΈμΉμ§ μμλ€.
λ³Έ μ°κ΅¬λ μ±λ΄ μ€λ₯λ₯Ό ν΄κ²°νκΈ° μν μ λ’° ν볡 μ λ΅μ μ립νκΈ° μν μ€μ©μ μΈ μ§μΉ¨μ μ 곡νλ€. λν, λ³Έ μ°κ΅¬ κ²°κ³Όλ μΈκ°-λ‘λ΄ μνΈμμ©μμ μꡬλλ μ λ’° ν볡 μ λ΅μ μΈκ°-μΈκ° μνΈ μμ©μμ μ¬μ©λλ μ λ΅κ³Όλ μμ΄ν μ μμμ 보μ¬μ€λ€.Abstract i
Table of Contents ii
List of Tables iii
List of Figures iii
Chapter 1. Introduction 1
1. Motivation 1
2. Previous Research 2
3. Purpose of Study 11
Chapter 2. Study 1 12
1. Hypotheses 12
2. Methods 12
3. Results 18
4. Discussion 23
Chapter 3. Study 2 25
1. Hypotheses 25
2. Methods 26
3. Results 30
4. Discussion 38
Chapter 4. Conclusion 40
Chapter 5. General Discussion 42
References 46
Appendix 54
κ΅λ¬Έμ΄λ‘ 65μ
Bias due to Mismatch and its Sensitivity in Matched Field Processing
Matched field processing(MFP) is a parameter estimation technique for localizing the range, depth, and bearing of a point source from the signal field propagating in an acoustic waveguide. MFP involves the correlation of the actual acoustic pressure field measured at a receiver array with a predicted field based on a postulated source position and an assumed ocean model.
A high degree of correlation between the measured field and the predicted field indicates a likely source location. Thus an increased complexity of the ocean's structure provides a greater variability of the acoustic fields, which aids the estimation procedure. When the environmental data are inaccurate or incomplete, a "mismatch" occurs between the measured data and the predicted pressure field, that causes a degradation in MFP correlation and an appreciable bias.
In this thesis, I was concerned with quantitative evaluation of the effects of mismatches arising from inaccuracies in a number of important system and ocean environmental parameters in a shallow water. The motivation for this study is to examine the biases in the source localization and the sensitivities of the matching results from various mismatches.
Using a conventional estimator, I have investigated the bias of range and depth estimates caused by perturbations in array position, as well as ocean environmental parameters through the simulation. Replica fields are calculated using the normal mode methods with the exception of bathymetry case. Also this study examined the sensitivity of MFP to geometric, geoacoustic, and ocean sound speed parameters using the genetic algorithm. And this method is applied to measured data to overcome mismatch and accurately estimate source location with limited a priori environmental information by expanding the parameter search space of MFP to include environmental parameters.
As a result, significant biases can be introduced into the depth and range localization predictions of a MFP through erroneous estimates of environmental parameters. It can also be concluded that the impact of mismatch, both summer sound speed and sensor position in water layer, is more serious than the geoacoustic parameters. This implies that simulations of mismatch which consider only a few errors will provide very misleading results on source position. Water depth and bottom bathymetry errors can be offset significantlyit shifted progressively farther away and deeper from the actual source location as the true water depth became shallower. Errors in estimates of the sediment attenuation and density, and basement parameters appear to be of relatively minor importance.
From an experimental implementation viewpoint, these result should enable resources to be concentrated on obtaining reliable values for those parameters which are important to know accurately, avoiding unnecessary effort to overdetermine relatively unimportant ones. It is also necessary to understand the types of mismatches in MFP that may be introduced by inaccuracies in the various forward modeling parameters, so that specific types of information deficiencies may be identified and attempts can be made to compensate for them.λͺ©μ°¨
Abstract = i
λͺ©μ°¨ = iii
List of Figures = vi
List of Tables = viii
List of Symbols = ix
I. μλ‘ = 1
1.1 μ°κ΅¬ λ°°κ²½ = 1
1.2 μ°κ΅¬ λͺ©μ = 2
1.3 μ°κ΅¬ λ΄μ© λ° κ΅¬μ± = 4
II. μ ν©μ₯μ²λ¦¬ μκ³ λ¦¬μ¦ = 6
2.1 ν΄μμμ μν μ λ¬κ³Ό λͺ¨λΈλ§ = 6
2.2 μ ν©μ₯μ²λ¦¬μ κ΅¬μ± μμ = 8
2.3 μ ν©μ₯ νλ‘μΈμ = 10
2.3.1 νλμ νλ‘μΈμ = 10
2.3.2 κ΄λμ νλ‘μΈμ = 17
2.4 μ μ μ μκ³ λ¦¬μ¦μ μ΄μ©ν 맀κ°λ³μ μμ° = 24
2.4.1 λͺ©μ ν¨μ = 26
2.4.2 맀κ°λ³μ μ΄κΈ°ν = 27
2.4.3 μ μ μ°μ°μ = 28
2.4.4 μ¬ν ν΅κ³ = 29
III. 맀κ°λ³μ μ€μ ν©μ λν μμΉμ€ν λ° λΆμ = 32
3.1 μ€μ ν© μ°κ΅¬ λν₯ = 32
3.2 μμΉμ€ν νκ²½ = 34
3.3 κ°λ³ 맀κ°λ³μ μ€μ ν© = 36
3.3.1 μμ€ν
맀κ°λ³μ μ€μ ν© = 36
3.3.1.1 μ£Όνμ μ€μ ν© = 36
3.3.1.2 λ°°μ΄ μμ¬ μ€μ ν© = 38
3.3.1.3 λ°°μ΄ κ²½μ¬ μ€μ ν© = 40
3.3.2 μμΈ΅ 맀κ°λ³μ μ€μ ν© = 43
3.3.2.1 μμλΆν¬ μ€μ ν© = 43
3.3.2.2 μμ¬ μ€μ ν© = 50
3.3.2.3 ν΄μ λ©΄ κ²½μ¬ μ€μ ν© = 53
3.3.3 ν΄μ ν΄μ μΈ΅ 맀κ°λ³μ μ€μ ν© = 58
3.3.3.1 ν΄μ ν΄μ μΈ΅ λκ» μ€μ ν© = 58
3.3.3.2 ν΄μ ν΄μ μΈ΅ μλΆμμ μ€μ ν© = 61
3.3.3.3 ν΄μ ν΄μ μΈ΅ νλΆμμ μ€μ ν© = 61
3.3.3.4 ν΄μ ν΄μ μΈ΅ λ°λ μ€μ ν© = 63
3.3.3.5 ν΄μ ν΄μ μΈ΅ κ°μ κ³μ μ€μ ν© = 63
3.3.4 μ μΈ΅ 맀κ°λ³μ μ€μ ν© = 66
3.3.4.1 μ μΈ΅ μμ μ€μ ν© = 66
3.3.4.2 μ μΈ΅ λ°λ μ€μ ν© = 67
3.3.4.3 μ μΈ΅ κ°μ κ³μ μ€μ ν© = 68
3.4 κ²°ν©λ 맀κ°λ³μ μ€μ ν© = 69
3.4.1 μμΈ΅ μμ¬κ³Ό λ°°μ΄ μμ¬κ³Όμ μ€μ ν© = 70
3.4.2 μμΈ΅ μμ¬κ³Ό λ°°μ΄ κ²½μ¬μμ μ€μ ν© = 70
3.4.3 μμΈ΅ μμ¬κ³Ό ν΄μ μΈ΅ μμκ³Όμ μ€μ ν© = 73
3.4.4 μμΈ΅ μμ¬κ³Ό ν΄μ μΈ΅ λ°λμμ μ€μ ν© = 73
3.5 μ’
ν©λ 맀κ°λ³μ μ€μ ν© = 76
IV. μ€μ ν©μ λν 맀κ°λ³μμ λ―Όκ°λ λΆμ = 81
4.1 μ°κ΅¬λν₯ = 81
4.2 맀κ°λ³μμ λ―Όκ°λ λΆμ κ²°κ³Ό = 82
V. μ€μΈ‘μλ£μ 맀κ°λ³μ μ΅μ ν λ° μ€μ ν© μν₯ = 90
5.1 μ€ν ν΄μμ νκ²½ λ° μ νΈ λΆμ = 90
5.1.1 μ€ν ν΄μκ³Ό μμμ κ²½λ‘ = 90
5.1.2 μμ§ μ λ°°μ΄κ³Ό μμΈ μμ = 91
5.1.3 μ€ν νκ²½ = 92
5.1.4 μ νΈμ μ€ννΈλ‘κ·Έλ¨ λΆμ = 94
5.2 맀κ°λ³μ μμ°κ³Ό μμ μμΉ μΆμ = 95
5.3 μμ°λ μ€ν μλ£μ μ€μ ν© μν₯ λΆμ = 101
VI. κ²°λ‘ = 106
μ°Έκ³ λ¬Έν = 10
Incidental Diagnosis of Pediatric Arytenoid Cartilage Dislocation During Videofluoroscopic Swallowing Study: A Case Report
Arytenoid cartilage dislocation is one of the most common mechanical causes of vocal fold immobility. The most common etiologies are intubation and external trauma, but its incidence is lower than 0.1%. Its symptoms include dysphonia, vocal fatigue, loss of vocal control, breathiness, odynophagia, dysphagia, dyspnea, and cough. Although there are some reports of arytenoid cartilage dislocation in adults, there are only few reports on its occurrence in children. It is particularly difficult to detect the symptoms of arytenoid cartilage dislocation in uncooperative pediatric patients with brain lesions without verbal output or voluntary expression. We report a case of arytenoid cartilage dislocation with incidental findings in a videofluoroscopic swallowing study performed to evaluate the swallowing function.ope
Determinants of Hip and Femoral Deformities in Children With Spastic Cerebral Palsy
Objective: To find factors affecting hip and femoral deformities in children with spastic cerebral palsy (CP) by comparing various clinical findings with imaging studies including plain radiography and computed tomography (CT) imaging. Methods: Medical records of 709 children with spastic CP who underwent thorough baseline physical examination and functional assessment between 2 to 6 years old were retrospectively reviewed. Fifty-seven children (31 boys and 26 girls) who had both plain radiography of the hip and three-dimensional CT of the lower extremities at least 5 years after baseline examination were included in this study. Results: The mean age at physical examination was 3.6 years (SD=1.6; range, 2-5.2 years) and the duration of follow-up imaging after baseline examination was 68.4 months (SD=22.0; range, 60-124 months). The migration percentage correlated with motor impairment and the severity of hip adductor spasticity (R1 angle of hip abduction with knee flexion). The femoral neck and shaft angle correlated with the ambulation ability and severity of hip adductor spasticity (R1 and R2 angles of hip abduction with both knee flexion and extension). Conclusion: Hip subluxation and coxa valga deformity correlated with both dynamic spasticity and shortening of hip adductor muscles. However, we found no correlation between femoral deformities such as femoral anteversion, coxa valga, and hip subluxation.ope
Mozart Piano Concerto 1μ μ₯μ Oiginal Cadenzaμ κ΄ν μ°κ΅¬
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Όλ¬Έ(μμ¬)--μμΈλνκ΅ λνμ :μμ
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λ°μ€λ¬μ€ μΈλ μ°μ€ λ°ν 리μ€νμ§ BPS13μμ λΆλ¦¬ν μλλΌμ΄μ , LysBPS13μ νΉμ± κ·λͺ
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곡νλΆ, 2012. 2. μ μλ ¬.Use of bacteriophages as biocontrol agents is promising tool to control pathogenic bacteria including antibiotics-resistant bacteria. Not only bacteriophages but also endolysins, which are the peptidoglycan hydrolyzing enzymes encoded by bacteriophages, have high potential for applications as biocontrol agents for foodborne pathogens. In this study, a putative endolysin gene was identified from the genome of the bacteriophage BPS13, which infects Bacillus cereus. In silico analysis of this endolysin, designated LysBPS13 showed that LysBPS13 consists with N-terminal catalytic domain (PRGP domain) and C-terminal cell wall binding domain (SH3_5 domain). Further characterization with the purified LysBPS13 revealed that this endolysin is an N-acetylmuramyl-L-alanine amidase, whose activity was not dependent on metal ions. Especially LysBPS13 has remarkable thermostability in the presence of glycerol as LysBPS13 showed lytic activity even after boiling for 30 min. Taken together, LysBPS13 can be considered as a favorable candidate as a new antimicrobial agent to control B. cereus in food products.μ΅κ·Ό νμμ λ΄μ± κ· μ£Όμ μΆνλΉλκ° λμμ§κ³ λ³μκ· μ μ μ΄νκΈ° μν μΉνκ²½ μμ¬μ λν κ΄μ¬μ΄ κΈμ¦ν¨μ λ°λΌ μ΄μ λν μ°κ΅¬κ° μ€μμ λκ³ μλ€.
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νμλ€. λ°μ΄μ€μΈν¬λ©ν±μ€ νλ‘κ·Έλ¨μ ν΅ν λΆμ κ²°κ³Ό, 834 μΌκΈ°μμ LysBPS13μ N-acetylmuramyl-L-alanine amidaseκ³Ό λμ μλμ±μ 보μμΌλ©°, κ°κ° Nλ§λ¨κ³Ό Cλ§λ¨ λΆλΆμ ν¨μ νμ± λλ©μΈκ³Ό μΈν¬λ²½ κ²°ν© λλ©μΈμ κ°κ³ μμλ€. κ·Έ μμ£Ό λ²μλ λ
μλ₯Ό μμ±νλ λ°μ€λ¬μ€ μΈλ μ°μ€μ μ¨λ¦°μ§μΈμμ€μ κ΅νλμμΌλ©° ν¨μ νμ± λνλΌ λ μ‘°ν¨μλ₯Ό νμλ‘ νμ§ μμλ€. νΉν LysBPS13μ κΈλ¦¬μΈλ‘€κ³Ό ν¨κ» μμ λ 30λΆ λμ μ΄μ κ°νκ³ λ νμλ μμ λ νκ· νμ±μ 보μμ νμΈν μ μμλ€. μ΄λ¬ν LysBPS13μ νΉμ±μ ν΅ν΄ μλ‘μ΄ νκ· λ¬Όμ§λ‘μμ κ°λ₯μ±μ μ μ ν μ μλ€.Maste