1,418 research outputs found
Local Measurements of the Impact of Quantitative and Qualitative Characteristics of Investment and Technological Decisions on the Environment Under the Risk-Related Conditions of Mining Industry
No full textThe impact of globalization in a worldwide scale is even more noticeable in the each country during period of world economic crisis due to the differences in the economic status, deformed by the crisis phenomena. In that case, the conflict between global tendencies and local manifestations in the regional aspect of economic phenomena is even more evidently noticeable as a direct reflection of the resource deficiency. The mineral resources are directly related to that process, not only as a first phase of the transformation of the raw material potential for each country, but also as a serious violator of the ecological equilibrium as a result of the applied technologies. Each country is enforced to resolve the various issues related to preserving the own resource potential as much as possible and to subordinate its investment and technological decisions to an integrated and in-depth utilization in compliance with the sustainable development of society.mineral resources, mining industry, environmental friendly consumption, impact on the environment.
ICSS: The International Community ‘Space’ Station: Publicness and formation of a resilient and sustainable community in a space habitat
No full textThe goal of this thesis is to propose a design for an orbital space station that incubates the future space civilization and is the base for space regulations and governance. A place that is democratizing access to space and resources, and allows for any interested individual to join and contribute to the world at large and their personal wellbeing. The goal is to design a place where a closely knitted community of makers, scientists, and artists is cultivated. They will be the decision-makers and the actors in space exploration.To learn how to do that, initially, the thesis embarks on the research of some community aspects on Earth and the way public space contributes to their cultivation in our cities. Specifically, the focus of the study is to observe and analyze the function that Het Park in Rotterdam serves to people. It is a look into the congenital and human side of living in an industrialized world and the values this brings to the community. In space, that natural side will inevitably be different or non-existing and to maintain the values that nature and the park bring to our lives we need to develop a translated alternative. The goal is to add a playful and authentic element to a potentially very machine and virtual future in space.After an introduction to the direction in which we have been heading since the industrial revolution, the research examines 4 major values taken from the park- social value, health, freedom, and engagement, to understand the importance of addressing the natural and human qualities. Those values are analyzed through park visits and sketches of people utilizing their environment and adapting it with simple means. Conclusively, the research highlights the importance of the presence of the public park in people’s lives even if we forget it or do not notice it on a daily basis and it shows how such a place can strengthen the community and make people more caring and more respectful (Cohen, et. all 2006). It identifies which are the key elements that play a role in the value that the park brings to the citizens. Thus they can be taken and appropriated to the space environment and the space station design. This research is a continuation of a previous essay by the author - “Cohousing in ‘Space’ and Time”.Architecture, Urbanism and Building Sciences | Explorela
LCT-GAN - Improving the efficiency of tabular data synthesis via latent embeddings
No full textIn the past decade data-driven approaches have been at the core of many business and research models. In critical domains such as healthcare and banking, data privacy issues are very stringent. Synthetic tabular data is an emerging solution to privacy guarantee concerns. Generative Adversarial Networks (GANs) are one of the emerging solutions for synthesizing data. However in order to capture all relevant relationships between columns, tabular data needs to be numerically encoded. As columns might be of different types, this is a challenging task as proven by recent approaches. Throughout this paper, we focus on the dimensionality explosion problem, which leads to high-dimensional datasets alongside computational overhead and increase in training time. We introduce a novel synthesis pipeline - LCT-GAN - an improvement to the current state-of-the-art in tabular data synthesis CTAB-GAN. Our approach addresses the dimensionality explosion problem by introducing a low-dimensional embedding step via an autoencoder prior to training. It is then combined with a novel conditional GAN architecture, operating in latent space. After thorough evaluation, we observe that our solution achieves more than 30\% improvement in certain statistical metrics in comparsion to CTAB-GAN, accompanied by 5 fold decrease in size and 150 times speedup in training time for a single epoch. We successfully show that it is possible to embed data using autoencoders, and that GANs are able to learn complex relationships in latent space in the context of tabular data.CSE3000 Research ProjectComputer Science and Engineerin
Search for narrow resonances below the Upsilon mesons
No full textWe have investigated the invariant mass spectrum of dimuons collected by the CDF experiment during the 1992-1995 run of the Fermilab Tevatron collider to improve the limit on the existence of narrow resonances set by the experiments at the SPEAR e(+)e(-) collider. In the mass range 6.3-9.0 GeV/c(2), we derive 90% upper credible limits to the ratio of the production cross section times muonic branching fraction of possible narrow resonances to that of the Upsilon(1S) meson. In this mass range, the average limit varies from 1.7 to 0.5%. This limit is much worse at the mass of 7.2 GeV/c(2) due to an excess of 250 +/- 61 events with a width consistent with the detector resolution
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Prospect for discovering a light higgs at the Tevatron in Run II
No full textThe present upgrades of the CDF and DO detectors as well as of the Fermilab Tevatron have dramatically improved their sensitivity for Standard Model and minimal supersymmetry Higgs bosons searches in Run II. This paper reviews the recent estimates of this sensitivity in terms of Higgs discovery and exclusion reach based on a total expected Run II Tevatron luminosity of 15 fb{sup {minus}1} delivered to each experiment
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Recent CDF and D0 Run I results
No full textWe summarize some of the most recent CDF and D0 results from the 1992-1995 collider run at the Fermilab Tevatron. These include a detailed examination of the heavy flavor content of W+jet data made by CDF. We found in this study that the rate and the kinematic properties of the event subsample, featuring soft lepton and secondary vertex in the same jet, are statistically difficult to accommodate with the Standard Model simulation. CDF has also searched for new physics in events with a photon, a lepton and E{sub T}. Finally, the results of the two collaborations in their search for the first, second and third generations leptoquarks are presented
The Ianos Cyclone (September 2020, Greece) from Perspective of Utilizing Social Networks for DM
No full textInternational audienceMain purpose of current research is to present evolutions in previous presented approaches of the author for manipulating social media content for disaster management of natural events. Those innovations suggest the adoption of machine learning for classifying both photos and text posted in social networks along with hybrid geo-referencing. As case study the author chose the Ianos cyclone, occurred between Italy and Greece, during September 2020. The geographic focus of the research was in Greece where the cyclone caused 4 human losses and damages in the urban environment. A dataset consisted of 4655 photos, with their corresponding captions, timestamps and location information was crawled from Instagram. The main hashtag used was #Ianos. Two data samples, one for each type, were classified manually for calibrating the classification models. The classes regarding photos were initially: (i) related and (ii) not related to Ianos, while the general classification schema for photos and text was: (i) Ianos event identification, (ii) consequences, scaled according to the impact of each report, (iii) precaution, (iv) disaster management: announcements, measures, volunteered actions. Author’s approach regarding classification suggests the use of convolutional neural networks and support vector machine algorithms for image and text classification respectively. The classified dataset, was geo-referenced by using commercial geocoding API and list-based geoparsing. The results of the research in current status are at an initial level, a subset of data though of automatically or manually processed information is presented in four related maps
Epidemiological factors associated with human cystic echinococcosis: A semi-structured questionnaire from a large population-based ultrasound cross-sectional study in eastern Europe and Turkey
No full textBackground: Cystic echinococcosis (CE) is a neglected parasitic zoonosis prioritized by the WHO for control. Several studies have investigated potential risk factors for CE through questionnaires, mostly carried out on small samples, providing contrasting results. We present the analysis of risk factor questionnaires administered to participants to a large CE prevalence study conducted in Bulgaria, Romania and Turkey. Methods: A semi-structured questionnaire was administered to 24,687 people from rural Bulgaria, Romania and Turkey. CE cases were defined as individuals with abdominal CE cysts detected by ultrasound. Variables associated with CE at P < 0.20 in bivariate analysis were included into a multivariable logistic model, with a random effect to account for clustering at village level. Adjusted odds ratios (AOR) with 95% CI were used to describe the strength of associations. Data were weighted to reflect the relative distribution of the rural population in the study area by country, age group and sex. Results: Valid records from 22,027 people were analyzed. According to the main occupation in the past 20 years, "housewife" (AOR: 3.11; 95% CI: 1.51-6.41) and "retired" (AOR: 2.88; 95% CI: 1.09-7.65) showed significantly higher odds of being infected compared to non-agricultural workers. "Having relatives with CE" (AOR: 4.18; 95% CI: 1.77-9.88) was also associated with higher odds of infection. Interestingly, dog-related and food/water-related factors were not associated with infection. Conclusions: Our results point toward infection being acquired in a "domestic" rural environment and support the view that CE should be considered more a "soil-transmitted" than a "food-borne" infection. This result helps delineating the dynamics of infection transmission and has practical implications in the design of specific studies to shed light on actual sources of infection and inform control campaigns
Comparative Study of Strategies for Formal Verification of High-Level Processors
No full textCompared are different methods for evaluation of formulas expressing microprocessor correctness in the logic of Equality with Uninterpreted Functions and Memories (EUFM) by translation to propositional logic, given recently developed efficient Boolean-to-CNF translations, in order to identify the best overall translation strategy from EUFM to CNF. The translation from EUFM to propositional logic is done by exploiting the property word-level values as distinct constants while performing complete formal verification. For EUFM formulas from correct microprocessors, the best translation was by using the e ij encoding of g-equations (dual-polarity equations), the nested-ITE scheme for elimination of uninterpreted predicates, preserving the ITE-tree structure of equation arguments, and Boolean-to-CNF translation by encoding the unobservability of logic blocks by merging them with adjacent gates on the only path to the primary output. For EUFM formulas from buggy microprocessors, the best translation was by using the e ij encoding of g-equations, the Ackermann scheme for elimination of uninterpreted predicates, preserving the ITE-tree structure of equation arguments, and Boolean-to-CNF translation by applying optimizations to reduce the number of clauses—merging of ITE-trees with one level of their AND/OR leaves, and exploiting the polarity of gates and logic blocks to reduce the number of their clauses
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