1,750,969 research outputs found
Deep Reinforcement Learning and Multi-Camera Integration for Enhanced 3D Reconstruction and Visual Navigation in Uncharted Territories
No full textThis comprehensive review examines advanced methodologies for optimizing visual navigation and 3D reconstruction in unmapped environments using deep reinforcement learning and multi-camera systems. The focus is on addressing the challenges faced in dynamic and unpredictable contexts, particularly through the integration of deep reinforcement learning techniques and multi-camera systems. As advancements in these technologies proliferate, their potential impact across industries such as robotics, autonomous vehicles, and telepresence is significant. The review summarizes the evolution of 3D reconstruction techniques, the application of deep reinforcement learning in navigation strategies, and the importance of multi-camera systems in creating comprehensive spatial representations, thereby providing a theoretical foundation and practical guidance for achieving efficient autonomous navigation and environmental mapping
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No full textThe sustainability of External Debt and its impact on Economic Growth is an important theme in development economics and public policy research, particularly for emerging and low-income nations. The purpose of this study was to empirically investigate the dynamic effects of external debt and to analyse the moderating role of institutional quality on economic growth across a panel of countries. The study was based on the prevailing economic theories of debt-growth and the neoclassical growth model and a dynamic panel data methodology employing System Generalized Method of Moments (System GMM) and standard panel data models was followed. The findings show that the Panel Fixed Effects model yielded several significant results: external debt and debt services demonstrated a significant negative association with GDP, while short-term debt and political stability showed a significant positive relationship with growth. Organisations and policymakers can use these findings to design more effective debt management policies that prioritize short-term, productive debt and implement governance reforms to strengthen institutional quality, thereby mitigating the adverse effects of high external indebtedness on economic expansionNOT Applicablenot applicabl
Sworn recording of Seth King, to Jas. Vanhouse, Mr. Whitfield and W.A. Cochran, against the Tuskaloosa, Bridge Company
No full textAromatic amine data sharing for 2015
No full textYearly donation for the aromatric amine consortium. We share Ames test data on aromatic amine scaffolds between several pharmaceutical companies. These scaffolds could be used in our DS and therefore it is beneficial to know whether they are mutagenic.
Alll shared chemicals are of low molecular weight, have CAS no and are not close to any of our DS. In fact 5 have been purchased and only tested for this sharing exercise
ENGINEERING FUNDERMENTAL AND APPRAISAL ISSUES INVOLVED IN PLANT AND EQUIPMENT PROCUREMENT FOR CONSTRUCTION WORKS
Full text linkKnowledge of engineering funder-mental helps situate study of plant and equipment within the framework of task peculiarity and choice of suitable plants and equipment to achieve the task. Critical to choice of equipment is the financial implication, thus the need for in-depth appraisal of available alternative for cost effective alternative. This presentation attempt to present pivotal issue in engineering funder-mental vis a vis appraisal techniques for selection of an optimum alternative with practical illustration
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No full textAnalyzing public transit accessibility to marginalized communities is critical to exploring the link between transportation inclusion and wellbeing in automobile-centered cultures. This study is an attempt to examine public transit accessibility to Indigenous residents in Winnipeg's North End. Apart from analyzing the current level of transit accessibility, the study explores barriers that hinder the use of public transit in the North End and examines strategies to improving transit accessibility to its residents.
This study adopts a holistic approach to understanding 'accessibility' and recognizes the importance of socio-economic, perceptional, and demographic factors in shaping the demand for transit facilities in an area. Findings of the study illustrate the need to include transportation inclusion as an essential component of the urban Indigenous welfare policies in the country. The lessons learned will also provide an initial framework to understand the link between community wellbeing and transportation inclusion of other socio-economically vulnerable communities.February 201
Marine Habitat Mapping Using Image Enhancement Techniques & Machine Learning
No full textAbstractThe mapping of habitats is the first step that is done in policies that target theenvironment, as well as in spatial planning and management. The biodiversityplans are always centered around habitats. Therefore, constant monitoring ofthese delicate species in terms of health, changes, and extinction is a must inbiodiversity plans. Human activities are constantly growing, resulting in theextinction of land and marine habitats. Land habitats are being destroyed using airpollution and the cutting of forests. At the same time, marine habitats are beingdestroyed due to acidification of ocean waters and waste materials from theindustries and pollution. The author has focused on aquatic habitats in thisdissertation, mainly coral reefs. An estimate of 27% of coral reef ecosystems havebeen destroyed, and a further 30% are at risk of being damaged in the comingyears. Coral reefs occupy 1% of the ocean floor, and yet they provide a home to30% of marine organisms. To analyze the health of these aquatic habitats, theyneed to be assessed through habitat mapping. Habitat mapping shows thegeographic distribution of different habitats within a particular area. Marinehabitats are typically mapped using camera imagery. The quality of underwaterimages suffers from the characteristics of the marine environment. This results inblurry images or containing particles that cover many parts of an image. Toovercome this, underwater image enhancement algorithms are used to preprocessimages beforehand. Now, there are many underwater image enhancementalgorithms that target different characteristics of the marine environment, butthere is no consensus among researchers about a single underwater technique thatcan be used for any marine dataset. In this dissertation, multiple experiments onvarious popular image enhancement techniques (seven) were conducted and usedto reach a decision about a single underwater approach for all datasets. Thedatasets include EILAT, EILAT2, RSMAS, and MLC08. Also, two state-of-the-artdeep convolutional neural networks for habitat mapping, i.e., DenseNet andMobileNet tested. Maximum results from the combination of Contrast LimitedAdaptive Histogram Equalization (CLAHE) achieved as underwater imageenhancement technique and DenseNet as deep convolutional network. Not applicabl
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