91 research outputs found
Guitars and Textures: A Special Spring Concert (April 5, 2016)
No full textFrom Three Way Stretch / Phil Dennys 2. Clowning Around 3. Bumpy Road Dominique Moran, Ed Salate, and Zenan Sun, piano
Viennese Waltz / Robert Fuchs Zenan Sun and Ed Salate, piano
Sometimes I Feel Like a Motherless Child arr. Harry Burleigh Dominique Durden, soprano Zenan Sun, piano
Poetry The Resistance – Dominique Durden Privilege – Christopher Melville
Sunset Boulevard / Composed by Textures Ensemble Nahthan Paul and Dominique Durden, sopranos Dominique Moran, piano Christopher Melville, guitar
At Last / Harry Warren Nahthan Paul, soprano
Etude Op. 10, No. 1 in C Major / F. Chopin Hannah To, piano
Naokolo (Around Dance) / Dusan Bogdanovic Introduction Kolo (Round Dance) Fugue Song BSU Guitar Ensemble
Danza de la Seduccion from Danzas Gitanas, Op. 55 / J. Turina BSU Guitar Ensemble
Movement 1 from Suite, Op. 14 / Béla Bartók BSU Guitar Ensemblehttps://vc.bridgew.edu/student_concerts/1111/thumbnail.jp
Evaluation of The Simplified Text of Ahmet Mithat Efendi’s Work “Felsefe-i Zenan” In The Context of Intra-Linguistic Translation
No full textIntralingual translation is the retelling of linguistic elements through other elements of the same language. How literary texts that use language as material are presented to readers in different periods shows the development of both language and literature. Examining diachronic intralingual translation practices is important in terms of the course of the literary journey of texts and readers. Felsefe-i Zenan is one of the stories in Ahmet Mithat Efendi’s collection called Letâif-i Rivâyat, which consists of thirty stories and novels published between 1870 and 1894. The work, which was republished as a facsimile and a simplified version by Sel Publishing in 2008, is one of the first texts in Turkish literature to talk about women’s rights and equality between men and women. The aim of this study, in which we examine how this text written in the 19th century was transferred to the 21st century reader in the context of interlingual translation, is to determine how intralingual translation was applied to a two-hundred-year-old text and the effects of this application on literary language. As a result of the study, it was determined that the primary aim was to understand the text while transferring the story of Felsefe-i Zenan to the 21st century reader and changes were made in the language elements accordingly. Therefore, this intralingual translation; It has been seen that the work was written by taking into account the literary concerns of the author in order to be understood by today’s readers and to achieve its purpose. In addition, it has been observed how changes in the word and supra-word structures in the literary language have occurred over a period of two centuries
Theory of Linear Models for Estimating Regression Parameters with Applications to Two-Factor Studies with Unequal Sample Sizes
No full textIn this thesis we explored some topics in regression analysis. In particular, we studied what linear regression is from a matrix theory perspective, and applied analysis of variance in a setting with two factors and unbalanced sample sizes. In addition, we applied Box-Cox variable transformation as a solution when the regression model violated the normality and equal variance (also called homoscedasticity) assumption. Our main goal is to use these theories to construct models and investigate questions related to lifetime earnings of people living in America by using real data. In doing so, we used the statistical software R to perform calculation involved in variable selection models, to identify and quantify relationships between variables as well as to test hypotheses
Group Distributionally Robust Optimization for Solving Out-Of-Domain Generalization and Finding Causal Invariant Relationships
No full textOut-of-Domain (OOD) generalization is a challenging problem in machine learning about learning a model from one or more domains and making the model perform well on an unseen domain. Empirical Risk Minimization (ERM), the standard machine learning method, suffers from learning spurious correlation in the training domain, therefore may perform badly when the unseen domain has different distribution from the training domain. Group Distributionally Robust Optimization (group DRO) is a method proposed to handle the OOD generalization problem. In this paper, the goals are to 1) measure if group DRO has a better OOD generalization performance than ERM. 2) evaluate if group DRO finds causally invariant relationships between the input and output. Semi-synthetic bird images with different backgrounds are used to form our data sets to construct a binary image classification problem for experiments. Results show that group DRO improves OOD generalization performance over ERM, and group DRO can find invariant relationships. However, the ability of group DRO to find invariant relationships is limited when the spurious correlation in the training domain is strong.CSE3000 Research ProjectComputer Science and Engineerin
Information sharing in private value lottery contest
No full textWe investigate players' incentives to disclose information on their private valuations of the prize ahead of a rent-seeking contest: Information sharing arises in equilibrium if types are concentrated enough, whereas sharing information is strictly dominated if types are sufficiently dispersed. (C) 2017 Elsevier B.V. All rights reserved.School of Economics, Peking University; National Natural Science Foundation of China [71203112, 61661136002]; Tsinghua University Initiative Scientific Research Grant [20151080397]; Hong Kong Research Grants Council General Research Fund [14500516]SSCIARTICLE36-4015
A Study of Protein-Protein Interactions in Salmonella Typhimurium
No full textabstract: The Multiple Antibiotic Resistance Regulator Family (MarR) are transcriptional regulators, many of which forms a dimer. Transcriptional regulation provides bacteria a stabilized responding system to ensure the bacteria is able to efficiently adapt to different environmental conditions. The main function of the MarR family is to create multiple antibiotic resistance from a mutated protein; this process occurs when the MarR regulates an operon. We hypothesized that different transcriptional regulator genes have interactions with each other. It is known that Salmonella pagC transcription is activated by three regulators, i.e., SlyA, MprA, and PhoP. Bacterial Adenylate Cyclase-based Two-Hybrid (BACTH) system was used to research the protein-protein interactions in SlyA, MprA, and PhoP as heterodimers and homodimers in vivo. Two fragments, T25 and T18, that lack endogenous adenylate cyclase activity, were used for construction of chimeric proteins and reconstruction of adenylate cyclase activity was tested. The significant adenylate cyclase activities has proved that SlyA is able to form homodimers. However, weak adenylate cyclase activities in this study has proved that MprA and PhoP are not likely to form homodimers, and no protein-protein interactions were detected in between SlyA, MprA and PhoP, which no heterodimers have formed in between three transcriptional regulators.Dissertation/ThesisMasters Thesis Biology 201
The impact of digital literacy on farmers' pro-environmental behavior: an analysis with the Theory of Planned Behavior
No full textIntroductionThe rapid development of agriculture has brought about significant negative impacts on the environment, such as land pollution and ecological degradation. The root cause of environmental issues lies in human behavior, with improper farming practices by farmers being a major contributor to agricultural pollution. This paper explores the relationship between farmers' digital literacy and their pro-environmental behaviors, examining the mediating roles of subjective norms, behavioral attitudes, and perceived behavioral control. Additionally, it investigates the varying impacts of digital literacy on PEB among farmers with different levels of education, social capital, and household income.MethodsBased on data from the China Land Economic Survey (CLES), this study utilizes an ordered probit regression analysis method to analyze data from 923 sample respondents in 24 villages in Jiangsu Province. All analyses were conducted using Stata 15.0.ResultsThe research findings indicate that digital literacy enhances the likelihood of farmers engaging in PEB. This practice is achieved by reinforcing farmers' subjective norms, strengthening their behavioral attitudes, and enhancing their perceived behavioral control (as the core elements in the Theory of Planned Behavior theory), thereby promoting the implementation of PEB among farmers. Further analysis reveals that digital literacy plays a crucial role in enhancing PEB among farmers with higher levels of education, social capital, and household income.DiscussionThe results of this study suggest that policymakers should enhance farmers' digital literacy and implement specific measures to improve farmers' subjective norms, behavioral attitudes, and perceived behavioral control. When the digital literacy and willingness for PEB are improved, farmers may engage in environmentally friendly practices
A two-seater light-weight solar powered clean car: preliminary design and economic analysis
No full textThis conference paper was presented in the 3rd International Conference on the Developments in Renewable Energy Technology, ICDRET 2014; Dhaka; Bangladesh; 29 May 2014 through 31 May 2014 [© 2014 Institute of Electrical and Electronics Engineers Inc.] The conference paper's website available at: http://ieeexplore.ieee.org/document/6861646/This paper outlines the design of a prototype solar powered light-weight economically affordable clean car for the daily office commuters of Dhaka city. Calculation in this paper shows that the solar power alone will be sufficient to operate a light-weight car from one end of the capital city Dhaka, to the other, for a journey to and from the office. A preliminary design of the solar car has been performed in this paper by calculating and estimating the required panel size, battery capacity and motor power. A plug-in charging option has been supplemented to the car for extracting electricity from the mains during times of insufficient energy receptions from the sun. Economic analysis performed on the life cycle cost of solar cars, as opposed to traditional fuel-based cars shows that over the long-term, solar cars come out to be much less expensive. Over a period of 20 years, combined cost of solar component replacements and electricity charges amount to a total over BDT 2 lac, which is approximately 1/9th the total cost of operating a fuel-based car in Dhaka, considering the fuel cost, maintenance and annual inflation over the same duration.Publishe
A new multilevel solar panel system for urban areas
No full textThis conference paper was presented in the 39th IEEE Photovoltaic Specialists Conference, PVSC 2013; Tampa, FL; United States; 16 June 2013 through 21 June 2013 [© 2013 IEEE] The conference paper's definite version is available at: http://dx.doi.org/10.1109/PVSC.2013.6744435. The Journal's website is at: http://ieeexplore.ieee.org/document/6744435/A new multilevel solar panel system is proposed for its use in urban residential solar home systems. The proposed system consists of three panels mounted in a rack one above another at a fixed distance from each other to minimize the floor area while shifted horizontally from each other by half the panel width to avoid shading of the lower panels. In the proposed system, the panels will be fitted with a tracking system to track the sun to maximize the energy collection. Further, a gliding mechanism is perceived for the panels that will enable the panels glide both ways and realign as the sun moves from east to west to avoid shading. Initial calculation, done for March 21st, shows that the proposed multilevel three panel system can harness 18.6% more energy than the three conventional fixed panel systems with 33% less area. The proposed system will be useful for large urban city dwellers, especially in third world countries, where not only electricity is in short supply, availability of roof top space to install solar panels is also very limited.Publishe
Boosting Offline Reinforcement Learning for Autonomous Driving with Hierarchical Latent Skills
No full textLearning-based vehicle planning is receiving increasing attention with the
emergence of diverse driving simulators and large-scale driving datasets. While
offline reinforcement learning (RL) is well suited for these safety-critical
tasks, it still struggles to plan over extended periods. In this work, we
present a skill-based framework that enhances offline RL to overcome the
long-horizon vehicle planning challenge. Specifically, we design a variational
autoencoder (VAE) to learn skills from offline demonstrations. To mitigate
posterior collapse of common VAEs, we introduce a two-branch sequence encoder
to capture both discrete options and continuous variations of the complex
driving skills. The final policy treats learned skills as actions and can be
trained by any off-the-shelf offline RL algorithms. This facilitates a shift in
focus from per-step actions to temporally extended skills, thereby enabling
long-term reasoning into the future. Extensive results on CARLA prove that our
model consistently outperforms strong baselines at both training and new
scenarios. Additional visualizations and experiments demonstrate the
interpretability and transferability of extracted skills
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