Lost in Translation: How Mistranslations Can Become Disinformation

This project explores the relationship between mistranslations and information disorder, focusing on how disregarding nuances in language can produce starkly different narratives and lead to serious consequences. Different languages have different grammatical structures and a word in one language can have several meanings in another language, depending on context, such that translations of important messages demand thorough understanding of discrepancy between languages. This project focuses on several cases of inaccurate translations that benefit the parties of the translators, bringing about consequences that range from problematic to damning. On one end of the spectrum, Chinese social media circulated a mistranslation and misappropriation of Western media, giving a false sense of legitimacy to Chinese conspiracy theories that say that COVID-19 originated in the United States. On the other end of the spectrum, a mistranslation between Japanese Premier Kantaro Suzuki and allied leaders in 1945 resulted in a misunderstanding of the Premier’s sentiments, which led to the dropping of a nuclear bomb on Hiroshima. Many cases of mistranslation with damaging consequences produce a benefit to related parties, which could explain a potentially intentional mistranslation in order to produce a specific outcome. This project argues that stopping subjective translations requires understanding not only direct translations, but also understanding the small nuances and multiple meanings of words between different languages in order to more accurately capture the meaning of a statement in one language translated into another language. Thorough understanding of other languages also requires cross-cultural sensitivity and cultural context that affects viewpoints of the original message. Culture and language scholars could be instrumental in ensuring that important messages are not lost in translation.https://orb.binghamton.edu/research_days_posters_2022/1118/thumbnail.jp

Total Automation: The Possibility of Lights-Out Manufacturing in the Near Future

As technology advances, fully automated manufacturing processes become more and more feasible as the norm; that is, the advantages of the technology outweigh the disadvantages for use by the majority of manufacturers. Many in the manufacturing industry have spoken about the dangers technological advancements could pose to the economy and employment in the future. This prompts the question: Could fully automated processes become the norm in the next five to ten years? The answer to this question affects the livelihood of manufacturing workers, as stories of machines replacing humans fill the news. This review considers scholarly and news articles covering lights-out technologies, manufacturing technology initiatives, and the effect of automation on jobs. The purpose of this review is to empirically determine if total lights-out technology, or technology that can function practically without any human input, can become the norm in the near future. This review determines that total lights-out technology will not become used by the majority of manufacturer’s in the near future

the forest burns bright

The investigation I am undertaking is concerned with the demonstration of the effects of the intersections of a person's identity on their personhood and their lives through the avenue of poetry. This is executed through the creation of a book of poems entitled "the forest burns bright", which is divided into three sections which create the metaphor of a forest before, during, and after a fire. The poems themselves are a culmination of my own life experiences as a fat, feminine, gay man from the south that grew up in a working family in a very small town. These experiences are described in a poetic manner that link themselves to the aforementioned forest fire--which ends in the rebirth of the forest (an extended metaphor that describes my trauma and how it has shaped me into who I am today.

Tangential curved planar reformation for topological and orientation invariant visualization of vascular trees

Recently, extensions to curved planar reformation (CPR) were proposed to improve vascular visualization of medical images. While these projective transformations provide enhanced visualization of vascular trees, non-planar alignment and arbitrary topology can cause visualization artifacts. Vascular trees in medical images are not aligned to planar cross-sections of volumetric image slices and thus aggravate simultaneous visualization of diagnostic features. Complex tree topology and non-planar alignment requires the need for an adaptive projection scheme to prevent visualization artifacts while preserving correctness of anatomical information. In this paper, we present algorithmic details for topological and orientation invariant visualization of vascular trees. Vascular high-level description of the medial axis guides the reformation process by flattening the vascular tree interior to successive image planes for respective radial sampling angles. Tree orientations are estimated from intrinsic shape properties of the vascular tree for rotation invariant projection. Radial sampling planes perpendicular to the medial axis tangents are the basis for topological invariant visualization of complete vascular interiors. We present experimental results on two different vascular tree topologies and demonstrate that our method is able to produce artifact free visualization of vascular interiors

The Greater Boston Housing Report Card 2013: What Follows The Housing Recovery?

This report is the 11th in the series of annual "Greater Boston Housing Report Cards," the first of which appeared in 2002 at a time when housing prices in the region were skyrocketing. In the course of this series, we have reported on the local housing bubble from 2000 through 2005, during which time home prices appreciated at annual double-digit rates; the retreat in home prices that begain in 2006; and then the beginning of a housing recovery in 2010. Like past report cards, this 2013 report probes Greater Boston's housing landscape, keeping tabs on housing construction, home prices, and rents. We have analyzed the relationship between the region's economy, demography, and housing, and we have kept track of federal, state and local government policies that affect the region's housing market. This report also includes a new analysis of local zoning regulations in Greater Boston communities because of the critical role zoning can play, particularly in the development - or lack of developmeent - of multifamily housing. The 2013 Report Card attempts to answer six questions about Greater Boston's housing market and its effect on the region's well-being: 1. What are the most recent trends in home sales, housing production, and foreclosures? 2. What does the future trajectory of home prices and rents look like? 3. Given current economic conditions, is another housing bubble on the horizon? 4. Given the changing demographics and economic health of Greater Boston, have we begun to build appropriate new housing stock to meet expected demand and to help moderate furure price and rent hikes? 5. Do we still face zoning constraints at the local level that hinder the production of an appropriate housing stock for the region? 6. What roles are the federal government and the Commonwealth playing in the housing market today

i-JEN: Visual interactive Malaysia crime news retrieval system

Supporting crime news investigation involves a mechanism to help monitor the current and past status of criminal events. We believe this could be well facilitated by focusing on the user interfaces and the event crime model aspects. In this paper we discuss on a development of Visual Interactive Malaysia Crime News Retrieval System (i-JEN) and describe the approach, user studies and planned, the system architecture and future plan. Our main objectives are to construct crime-based event; investigate the use of crime-based event in improving the classification and clustering; develop an interactive crime news retrieval system; visualize crime news in an effective and interactive way; integrate them into a usable and robust system and evaluate the usability and system performance. The system will serve as a news monitoring system which aims to automatically organize, retrieve and present the crime news in such a way as to support an effective monitoring, searching, and browsing for the target users groups of general public, news analysts and policemen or crime investigators. The study will contribute to the better understanding of the crime data consumption in the Malaysian context as well as the developed system with the visualisation features to address crime data and the eventual goal of combating the crimes

True-false lumen segmentation of aortic dissection using multi-scale wavelet analysis and generative-discriminative model matching

Computer aided diagnosis in the medical image domain requires sophisticated probabilistic models to formulate quantitative behavior in image space. In the diagnostic process detailed knowledge of model performance with respect to accuracy, variability, and uncertainty is crucial. This challenge has lead to the fusion of two successful learning schools namely generative and discriminative learning. In this paper, we propose a generative-discriminative learning approach to predict object boundaries in medical image datasets. In our approach, we perform probabilistic model matching of both modeling domains to fuse into the prediction step appearance and structural information of the object of interest while exploiting the strength of both learning paradigms. In particular, we apply our method to the task of true-false lumen segmentation of aortic dissections an acute disease that requires automated quantification for assisted medical diagnosis. We report empirical results for true-false lumen discrimination of aortic dissection segmentation showing superior behavior of the hybrid generative-discriminative approach over their non hybrid generative counterpart

Safety and efficacy of stereotactic body radiation therapy in the treatment of pulmonary metastases from high grade sarcoma.

Introduction. Patients with high-grade sarcoma (HGS) frequently develop metastatic disease thus limiting their long-term survival. Lung metastases (LM) have historically been treated with surgical resection (metastasectomy). A potential alternative for controlling LM could be stereotactic body radiation therapy (SBRT). We evaluated the outcomes from our institutional experience utilizing SBRT. Methods. Sixteen consecutive patients with LM from HGS were treated with SBRT between 2009 and 2011. Routine radiographic and clinical follow-up was performed. Local failure was defined as CT progression on 2 consecutive scans or growth after initial shrinkage. Radiation pneumonitis and radiation esophagitis were scored using Common Toxicity Criteria (CTC) version 3.0. Results. All 16 patients received chemotherapy, and a subset (38%) also underwent prior pulmonary metastasectomy. Median patient age was 56 (12-85), and median follow-up time was 20 months (range 3-43). A total of 25 lesions were treated and evaluable for this analysis. Most common histologies were leiomyosarcoma (28%), synovial sarcoma (20%), and osteosarcoma (16%). Median SBRT prescription dose was 54 Gy (36-54) in 3-4 fractions. At 43 months, local control was 94%. No patient experienced G2-4 radiation pneumonitis, and no patient experienced radiation esophagitis. Conclusions. Our retrospective experience suggests that SBRT for LM from HGS provides excellent local control and minimal toxicity