Boundary States for AdS₂ Branes in AdS₃

We construct boundary states for the AdS₂ D-branes in AdS₃. We show that, in the semi-classical limit, the boundary states correctly reproduce geometric configurations of these branes. We use the boundary states to compute the one loop free energy of open string stretched between the branes. The result agrees precisely with the open string computation in hep-th/0106129

Novel optofluidic sensor systems for quantitative chemical imaging and on-chip sensor calibration

The design, fabrication and characterization of optofluidic biosensor systems for quantitative oxygen imaging with a color charge-coupled device (CCD) camera as well as on-chip self-calibration of sensors utilizing gas bubbles was investigated. This dissertation was prepared in publication format. The first and second papers demonstrate that color imaging devices can be used in quantitative chemical analysis. The final paper explores the feasibility of using electrolytically generated bubbles for a novel functionality of reagentless, on-chip, in situ calibration of optical biosensors. Work in the first paper includes the use of a color CCD camera for fluorescence intensity imaging. This involves extracting the red color element to determine the dissolved oxygen content from the color image of a sample. The linearity and sensitivity of oxygen detection based on the red intensity analysis was improved to those of spectrometric measurement and total color intensity analysis. In the second paper, the color extraction technique used in the dissolved oxygen sensor was extended to gaseous oxygen detection to eliminate the need of optical filters and replace the blue light emitting diode (LED) excitation source with a general broad-band white LED. This new method has potential applications in multi-analyte monitoring and simultaneous structural/functional imaging of biological samples with a single broad-band light source. In the final paper, a double-layered optofluidic system was developed to demonstrate on-chip, self-calibration of dissolved oxygen sensor. A multilayers of dry film resist was used for preparing a 3-D fluidic structure. A thin black polydimethylsiloxane membrane was used for oxygen diffusion and optical isolation. The sensor calibration result with the on-chip bubble was shown to be in good agreement with that of standard calibrants --Abstract, page iv

Influence of Oxygen Microenvironment on Microfluidic Glucose Sensor Performance

We propose a novel method to overcome significant problems of baseline drift and sensitivity degradation in amperometric biosensors based on oxidase enzyme reactions. A novel glucose microsensor with a built-in electrochemical oxygen manipulation microsystem is introduced to demonstrate three novel functionalities; one-point in situ self-calibration (zero-point), broadening of dynamic range and increase in sensitivity. The influence of electrochemically generated oxygen microenvironment on the sensor output within a fluidic structure is investigated

Helping students generate physics inquiry problems

Physicists’ research usually begins when there are imperfections in previous experiments or theories, when new theories, data, materials, and experimental techniques are invented or developed, or when they discover conflicts between theories and experiments or within theories. However, these situations do not apply for school students, who need different conditions to generate their own physics inquiry problems (PIPs). This is despite the fact that students themselves perceive that generating good PIPs is the most difficult part of physics inquiry activities. Some students are often observed trying to discover inquiry problems that are improperly informed, or simply don’t make sense. In this workshop, therefore, we will introduce specific strategies that can help students generate IPSs at the student’s level of knowledge and inquiry experience. Intended Audience: Secondary-school Educator

Resolving Class Imbalance for LiDAR-based Object Detector by Dynamic Weight Average and Contextual Ground Truth Sampling

An autonomous driving system requires a 3D object detector, which must perceive all present road agents reliably to navigate an environment safely. However, real-world driving datasets often suffer from the problem of data imbalance, which causes difficulties in training a model that works well across all classes, resulting in an undesired imbalanced sub-optimal performance. In this work, we propose a method to address this data imbalance problem. Our method consists of two main components: (i) a LiDAR-based 3D object detector with per-class multiple detection heads where losses from each head are modified by dynamic weight average to be balanced. (ii) Contextual ground truth (GT) sampling, where we improve conventional GT sampling techniques by leveraging semantic information to augment point cloud with sampled ground truth GT objects. Our experiment with KITTI and nuScenes datasets confirms our proposed method's effectiveness in dealing with the data imbalance problem, producing better detection accuracy compared to existing approaches.Comment: 10 page

Document Summarization Using NMF and Pseudo Relevance Feedback Based on K-Means Clustering

According to the increment of accessible text data source on the internet, it has increased the necessity of the automatic text document summarization. However, the performance of the automatic methods might be poor because the semantic gap between high level user's summary requirement and low level vector representation of machine exists. In this paper, to overcome that problem, we propose a new document summarization method using a pseudo relevance feedback based on clustering method and NMF (non-negative matrix factorization). Relevance feedback is effective technique to minimize the semantic gap of information processing, but the general relevance feedback needs an intervention of a user. Additionally, the refined query without user interference by pseudo relevance feedback may be biased. The proposed method provides an automatic relevance judgment to reformulate query using the clustering method for minimizing a bias of query expansion. The method also can improve the quality of document summarization since the summarized documents are influenced by the semantic features of documents and the expanded query. The experimental results demonstrate that the proposed method achieves better performance than the other document summarization methods