197,312 research outputs found
Policies to promote cereal intensification in Ethiopia: A review of evidence and experience
No full textDawit Alemu: DCA, EthiopiaCereal crops, Agricultural development, Agricultural extension work, Fertilizers, Seed industry and trade Developing countries, Public investment, Food policy,
Multi-feature fusion for image retrieval using constrained dominant sets
No full textAggregating different image features for image retrieval has recently shown its effectiveness. While highly effective, though, the question of how to uplift the impact of the best features for a specific query image persists as an open computer vision problem. in this paper, we propose a computationally efficient approach to fuse several hand-crafted and deep features, based on the probabilistic distribution of a given membership score of a constrained cluster in an unsupervised manner. First, we introduce an incremental nearest neighbor (NN) selection method, whereby we dynamically select k-NN to the query. We then build several graphs from the obtained NN sets and employ constrained dominant sets (CDS) on each graph G to assign edge weights which consider the intrinsic manifold structure of the graph, and detect false matches to the query. Finally, we elaborate the computation of feature positive-impact weight (PIW) based on the dispersive degree of the characteristics vector. To this end, we exploit the entropy of a cluster membership-score distribution. In addition, the final NN set bypasses a heuristic voting scheme. Experiments on several retrieval benchmark datasets show that our method can improve the state-of-the-art result. (C) 2019 Elsevier B.V. All rights reserved
Deep Constrained Dominant Sets for Person Re-Identification
No full textIn this work, we propose an end-to-end constrained clustering scheme to tackle the person re-identification (re-id) problem. Deep neural networks (DNN) have recently proven to be effective on person re-identification task. In particular, rather than leveraging solely a probe-gallery similarity, diffusing the similarities among the gallery images in an end-to-end manner has proven to be effective in yielding a robust probe-gallery affinity. However, existing methods do not apply probe image as a constraint, and are prone to noise propagation during the similarity diffusion process. To overcome this, we propose an intriguing scheme which treats person-image retrieval problem as a constrained clustering optimization problem, called deep constrained dominant sets (DCDS). Given a probe and gallery images, we re-formulate person re-id problem as finding a constrained cluster, where the probe image is taken as a constraint (seed) and each cluster corresponds to a set of images corresponding to the same person. By optimizing the constrained clustering in an end-to-end manner, we naturally leverage the contextual knowledge of a set of images corresponding to the given person-images. We further enhance the performance by integrating an auxiliary net alongside DCDS, which employs a multi-scale ResNet. To validate the effectiveness of our method we present experiments on several benchmark datasets and show that the proposed method can outperform state-of-the-art methods
Dominant Sets for 'Constrained' Image Segmentation
No full textImage segmentation has come a long way since the early days of computer vision, and still remains a challenging task. Modern variations of the classical (purely bottom-up) approach, involve, e.g., some form of user assistance (interactive segmentation) or ask for the simultaneous segmentation of two or more images (co-segmentation). At an abstract level, all these variants can be thought of as constrained versions of the original formulation, whereby the segmentation process is guided by some external source of information. In this paper, we propose a new approach to tackle this kind of problems in a unified way. Our work is based on some properties of a family of quadratic optimization problems related to dominant sets, a graph-theoretic notion of a cluster which generalizes the concept of a maximal clique to edge-weighted graphs. In particular, we show that by properly controlling a regularization parameter which determines the structure and the scale of the underlying problem, we are in a position to extract groups of dominant-set clusters that are constrained to contain predefined elements. In particular, we shall focus on interactive segmentation and co-segmentation (in both the unsupervised and the interactive versions). The proposed algorithm can deal naturally with several types of constraints and input modalities, including scribbles, sloppy contours and bounding boxes, and is able to robustly handle noisy annotations on the part of the user. Experiments on standard benchmark datasets show the effectiveness of our approach as compared to state-of-the-art algorithms on a variety of natural images under several input conditions and constraints
Causes of household food insecurity in Koredegaga Peasant Association, Oromiya Zone, Ethiopia
No full textThe main objective of the study was to examine the determinants of households' food security using a logistic regression procedure. The model was initially fitted with eleven factors, of which six were found to be significant, and all exhibited the expected signs. These include farmland size, ox ownership, fertilizer application, education level of household heads, household size, and per capita production. The result was analyzed further to compute partial effects and to conduct simulation studies on significant determinant factors. Analysis of partial effects revealed that an introduction to fertilizer use and an improvement in the educational levels of household heads lead to relatively greater probability of food security. On the other hand, simulations were conducted on the basis of the base category of farmers, representing food secure households, revealed that both educational levels of household heads and fertilizer application by farmers have relatively high potential to more than double the number of food secure households in the study area following improvements in these factors.Food Security and Poverty,
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.
No full text"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states.
By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement.
To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Dr. Glendon Swarthout
No full textHosted by Roger M. Busfield, MSU Assistant Professor of Speech and Theater, Meet the Author is designed to introduce a general audience to a contemporary author and their work through in-depth interviews. This episode features a conversation between Dr. Glendon Swarthout, prolific author and English professor at MSU, and assistant professors Sam S. Baskett and Theodore B. Strandness
Simulation of thermal plant optimization and hydraulic aspects of thermal distribution loops for large campuses
No full textFollowing an introduction, the author describes Texas A&M University and its utilities system. After that, the author presents how to construct simulation models for chilled water and heating hot water distribution systems. The simulation model was used in a $2.3 million Ross Street chilled water pipe replacement project at Texas A&M University. A second project conducted at the University of Texas at San Antonio was used as an example to demonstrate how to identify and design an optimal distribution system by using a simulation model. The author found that the minor losses of these closed loop thermal distribution systems are significantly higher than potable water distribution systems. In the second part of the report, the author presents the latest development of software called the Plant Optimization Program, which can simulate cogeneration plant operation, estimate its operation cost and provide optimized operation suggestions. The author also developed detailed simulation models for a gas turbine and heat recovery steam generator and identified significant potential savings. Finally, the author also used a steam turbine as an example to present a multi-regression method on constructing simulation models by using basic statistics and optimization algorithms. This report presents a survey of the author??s working experience at the Energy Systems Laboratory (ESL) at Texas A&M University during the period of January 2002 through March 2004. The purpose of the above work was to allow the author to become familiar with the practice of engineering. The result is that the author knows how to complete a project from start to finish and understands how both technical and nontechnical aspects of a project need to be considered in order to ensure a quality deliverable and bring a project to successful completion. This report concludes that the objectives of the internship were successfully accomplished and that the requirements for the degree of Degree of Engineering have been satisfied
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