Profiles of Asian American Subgroups in Massachusetts: Korean Americans in Massachusetts

This report looks at Korean Americans in Massachusetts with a focus on the Metro Boston area. Using the 2000 U.S. Census and the American Community Survey 2005–2007 Three-Year Estimates in combination with interviews and secondary research, this profile looks at Korean American demographics and community perspectives

Asian Adoptees and Post-Adoption Services in Massachusetts: Data from Providers and Reflections from Adult Adoptees

In the summer of 2009, the Institute for Asian American Studies at the University of Massachusetts Boston in consultation with Boston Korean Adoptees, Inc. (BKA), commenced a project aimed at documenting post-adoption services and programs available to Asian adoptees, principally Korean, in Massachusetts and assessing their content and relevance. In the first part of the project, a questionnaire was sent to providers of post-adoption services and program currently available requesting information about their services—number, content, clientele, resources, and staffing. In addition providers were asked to comment on the frequency of requests for services and on challenges faced in offering them. The project’s second part focused on learning from adult adoptees about their personal experiences with post-adoption services. Discussion groups with adoptees gave them an opportunity to discuss the importance of these services during childhood, adolescence, and adulthood. This report presents the findings from the survey and discussions, after providing some brief background information about the history and magnitude of Asian adoptions in the United States. It concludes with recommendations on how service providers and other organizations can better address adoptees’ interests through improving and expanding services and by working in collaboration with each other, the adult adoptee community, and the Asian American community at large

A Clustering Comparison Measure Using Density Profiles and its Application to the Discovery of Alternate Clusterings

Data clustering is a fundamental and very popular method of data analysis. Its subjective nature, however, means that different clustering algorithms or different parameter settings can produce widely varying and sometimes conflicting results. This has led to the use of clustering comparison measures to quantify the degree of similarity between alternative clusterings. Existing measures, though, can be limited in their ability to assess similarity and sometimes generate unintuitive results. They also cannot be applied to compare clusterings which contain different data points, an activity which is important for scenarios such as data stream analysis. In this paper, we introduce a new clustering similarity measure, known as ADCO, which aims to address some limitations of existing measures, by allowing greater flexibility of comparison via the use of density profiles to characterize a clustering. In particular, it adopts a ‘data mining style’ philosophy to clustering comparison, whereby two clusterings are considered to be more similar, if they are likely to give rise to similar types of prediction models. Furthermore, we show that this new measure can be applied as a highly effective objective function within a new algorithm, known as MAXIMUS, for generating alternate clusterings

FOUND: Foot Optimization with Uncertain Normals for Surface Deformation Using Synthetic Data

Surface reconstruction from multi-view images is a challenging task, with solutions often requiring a large number of sampled images with high overlap. We seek to develop a method for few-view reconstruction, for the case of the human foot. To solve this task, we must extract rich geometric cues from RGB images, before carefully fusing them into a final 3D object. Our FOUND approach tackles this, with 4 main contributions: (i) SynFoot, a synthetic dataset of 50,000 photorealistic foot images, paired with ground truth surface normals and keypoints; (ii) an uncertainty-aware surface normal predictor trained on our synthetic dataset; (iii) an optimization scheme for fitting a generative foot model to a series of images; and (iv) a benchmark dataset of calibrated images and high resolution ground truth geometry. We show that our normal predictor outperforms all off-the-shelf equivalents significantly on real images, and our optimization scheme outperforms state-of-the-art photogrammetry pipelines, especially for a few-view setting. We release our synthetic dataset and baseline 3D scans to the research community.Comment: 14 pages, 15 figure

A Tool for Generating Reduced-Order Models from Building Energy Simulation Input Files to Enable Optimal Design and Control Analysis

Representing multi-zone building envelope systems with linear time invariant state-space forms provides a way of applying various advanced control methodologies for better design and control of buildings. For example, system properties such as time constant and frequency response of building envelopes can be easily investigated with the help of control toolkits such as Matlab/Simulink and a reduced-order model can be developed by applying a model order reduction technique, once a reliable LTI building representation is developed. However, in order to make the LTI representation approach useful for industry, an interfacing tool that automatically extracts building system information from input files of popular building energy simulation (BES) tools and constructs a physical thermal network from the data is needed. This paper presents a conceptual strategy to interpret object (class) of a building energy simulation software and a methodology to develop a high fidelity LTI thermal network model. A case study applying this approach is provided which utilizes a model-order reduction method that converts a BES building envelope model for a multi-zone building into a reduced-order LTI model (ROM). Comparisons of predicted building load profiles and computation times between the BES model and ROM are also provided

Dissociation of structural and functional integrities of the motor system in amyotrophic lateral sclerosis and behavioral-variant frontotemporal dementia

Background and Purpose: This study investigated the structural and functional changes in the motor system in amyotrophic lateral sclerosis (ALS; n=25) and behavioral-variant fronto-temporal dementia (bvFTD; n=17) relative to healthy controls (n=37). Methods: Structural changes were examined using a region-of-interest approach, applying voxel-based morphometry for gray-matter changes and diffusion tensor imaging for white-matter changes. Functional changes in the motor system were elucidated using threshold-tracking transcranial magnetic stimulation (TMS) measurements of upper motor-neuron excitability. Results: The structural analyses showed that in ALS there were more white-matter changes in the corticospinal and motor-cortex regions and more gray-matter changes in the cerebellum in comparison to controls. bvFTD showed substantial gray- and white-matter changes across virtually all motor-system regions compared to controls, although the brainstem was affected less than the other regions. Direct comparisons across patient groups showed that the gray- and white-matter motor-system changes inclusive of the motor cortex were greater in bvFTD than in ALS. By contrast, the functional integrity of the motor system was more adversely affected in ALS than in bvFTD, with both patient groups showing increased excitability of upper motor neurons compared to controls. Conclusions: Cross-correlation of structural and functional data further revealed a neural dissociation of different motor-system regions and tracts covarying with the TMS excitability across both patient groups. The structural and functional motor-system integrities appear to be dissociated between ALS and bvFTD, which represents useful information for the diagnosis of motor-system changes in these two disorders