1,352 research outputs found

    "Toward a New Instrumental Macroeconomics: Abba Lerner and Adolph Lowe on Economic Method, Theory, History, and Policy"

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    This paper argues that the ideas of Abba Lerner and Adolph Lowe contain overlapping and complementary insights and themes that may contribute to the development of a new approach to macroeconomics and that have rather specific practical policy implications. Lerner's notions of functional finance and money as a creature of the state are combined with Lowe's structural analysis to forge an approach to macroeconomic theory and policy that considers both aggregate proportionality and balance and sectoral relations and that addresses issues regarding monetary production and effective demand as well as ongoing structural and technological change. Such a "new instrumental macroeconomics," focusing on full employment, price stability, and a decent standard of living for all, has important points of contact with recent proposals promoting job opportunities through direct job creation with a public service corps that benefits communities while serving as a buffer stock of labor providing price stability.

    Vision-based control of multi-agent systems

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    Scope and Methodology of Study: Creating systems with multiple autonomous vehicles places severe demands on the design of decision-making supervisors, cooperative control schemes, and communication strategies. In last years, several approaches have been developed in the literature. Most of them solve the vehicle coordination problem assuming some kind of communications between team members. However, communications make the group sensitive to failure and restrict the applicability of the controllers to teams of friendly robots. This dissertation deals with the problem of designing decentralized controllers that use just local sensor information to achieve some group goals.Findings and Conclusions: This dissertation presents a decentralized architecture for vision-based stabilization of unmanned vehicles moving in formation. The architecture consists of two main components: (i) a vision system, and (ii) vision-based control algorithms. The vision system is capable of recognizing and localizing robots. It is a model-based scheme composed of three main components: image acquisition and processing, robot identification, and pose estimation.Using vision information, we address the problem of stabilizing groups of mobile robots in leader- or two leader-follower formations. The strategies use relative pose between a robot and its designated leader or leaders to achieve formation objectives. Several leader-follower formation control algorithms, which ensure asymptotic coordinated motion, are described and compared. Lyapunov's stability theory-based analysis and numerical simulations in a realistic tridimensional environment show the stability properties of the control approaches

    Drone-based panorama stitching: A study of SIFT, FLANN, and RANSAC techniques

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    This paper documents the tasks I accomplished during my internship and project at UPC. It provides an overview of the project's structure, objectives, and task distribution. A summary is given for the Web Application part of the project, which was handled by my teammate. This paper also details the drone and payloads used in the project and their functionalities. In the parts I was responsible for, I conducted thorough investigations and tests on the Raspberry Pi camera to obtain the best image quality during every flight test. I delved into the entire process of basic panorama stitching, encompassing features detection, descriptors matching, and transformation estimation based on the homography matrix. I compared popular feature detectors and descriptor matchers in terms of processing speed and performance, subsequently developing a panorama stitching algorithm for images captured by the drone. Finally, I provided a detailed discussion on some extra tasks that were not completed and points that could be improved upon. The paper not only stands as a detailed account of our contributions but also serves as an inspiration and a guide for future enhancements of drone-based panorama stitching

    MapSnapper: Engineering an Efficient Algorithm for Matching Images of Maps from Mobile Phones

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    The MapSnapper project aimed to develop a system for robust matching of low-quality images of a paper map taken from a mobile phone against a high quality digital raster representation of the same map. The paper presents a novel methodology for performing content-based image retrieval and object recognition from query images that have been degraded by noise and subjected to transformations through the imaging system. In addition the paper also provides an insight into the evaluation-driven development process that was used to incrementally improve the matching performance until the design specifications were met

    Suggested strategies and best practices in private supply chain disaster response

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    Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.Vitae. Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 85-89).In times of disaster, demand for goods and services in affected areas spikes. Private companies generally have contingencies in place for business continuity; however, most lack a strategic approach to join the general population's relief efforts. Why are some companies more effective within disaster relief supply chains than others? How can a company approach this area of opportunity? This thesis explores what a disaster is and how disaster management works; recognizing what stakeholders participate during disaster recovery efforts; and extrapolating best practices applied during past disasters by companies that have been deemed successful. Based on the strategies identified during our research, we came up with a framework of nine best practices and suggest how to apply it across a range of ten industries.by Karn Budhiraj and Gabriel de la Torre Castro.M.Eng.in Logistic

    A Novel Efficient Algorithm for Locating and Tracking Object Parts in Low Resolution Videos

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    This is the published version. Copyright De GruyterIn this paper, a novel efficient algorithm is presented for locating and tracking object parts in low resolution videos using Lowe's SIFT keypoints with a nearest neighbor object detection approach. Our interest lies in using this information as one step in the process of automatically programming service, household, or personal robots to perform the skills that are being taught in easily obtainable instructional videos. In the reported experiments, the system looked for 14 parts of inanimate and animate objects in 40 natural outdoor scenes. The scenes were frames from a low-resolution instructional video on cleaning golf clubs containing 2,405 frames of 180 by 240 pixels. The system was trained using 39 frames that were half-way between the test frames. Despite the low resolution quality of the instructional video and occluded training samples, the system achieved a recall of 49 % with a precision of 71 % and an Fl of 0.58, which is better than that achieved by less demanding applications. In order to verify that the reported results were not dependent on the specific video, the proposed technique was applied to another video and the results are reported

    The Wellness Companion

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    Issues such as obesity, high blood pressure, and heart disease have been correlated with a sedentary lifestyle. Additionally, many contemporary office jobs consist of deskwork on a computer for almost the entire workday. This can result in back and neck issues. The goal of this project is to limit the harmful effects of sitting for extended periods of time by making an active lifestyle easy and convenient. The Wellness Companion is a portable treadmill that is easy to transport and use in a variety of environments, such as at the library, in school, or at the office

    Technological Advancements Of Order Fulfillment With The Utilization Of Business Process Management: A Business Practicum Of Lowe’s Companies, Inc.

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    This thesis reflects the evolution of order fulfillment at Lowe’s Companies, Inc. with the aid of business process management from an intern’s perspective. In retail, the process of order fulfillment changes almost daily, which makes it very difficult to keep information systems that manage these operations up to date. However, until the recent CEO of Lowe’s Companies, Inc. was brought in, the company had failed to update its technological systems for order fulfillment in an effective way. The study presents managerial insights into the technological advancements being implemented at Lowe’s Companies, Inc., with an emphasis on the new order management system (OMS) that they are creating to support their order fulfillment. Further, recommendations are given for ways the company can continue to succeed
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