118,273 research outputs found
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
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,
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
Political instability, corruption and inclusive growth in Ethiopia: Transmission channels and moderating roles
No full textThis paper examines the direct and moderating roles of political instability and corruption on inclusive growth in Ethiopia from 1992–2020. We also test whether corruption sands or greases the wheels of inclusive growth and whether the impacts of political instability and corruption vary across the low and high regimes of political instability. Different econometric approaches are applied to address these objectives, including simultaneous equation modelling, moderation analysis, and two-regime threshold regression. The findings robustly confirm negative impacts of political instability and corruption on inclusive growth. The effects of political instability and corruption are also channelled through investment and tourism and appear to be more severe in a higher political instability regime. Further, the study supports the ‘sanding the wheels’ hypothesis, which argues that corruption is harmful to economic activities. The results generally suggest that, unless proper efforts are taken to relieve the current political upheaval and ethnic conflicts in the country, the detrimental impacts of political instability and corruption will aggravate the country’s dire situation
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,
Age and hafnium isotopic evolution of the Didesa and Kemashi Domains, western Ethiopia
No full textAvailable online: 25 September 2015Abstract not availableMorgan L. Blades, Alan S. Collins, John Foden, Justin L. Payne, Xiaochen Xu, Tadesse Alemu, Girma Woldetinsae, Chris Clark, Richard J.M. Taylo
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Square Dancing with the Stars to Enhance Dynamic Hirschman Linkages?
No full textIn this Presidential Address, the author takes the reader on a reconnaissance of his life and time as a regional scientist. He points out scenery he found scintillating along the way, hoping that some may pick up the banner and chew on a few of the ideas for a while. He suggests a revisit to Albert O. Hirschman’s notion of key sectors and more empirical analysis related to Marcus Berliant’s and Masahisa Fujita’s notion of knowledge creation and transfer.Presidential Address, San Antonio, Texas, March 29, 2014 (53rd Meetings of the Southern Regional Science Association
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Letter from unknown writer to Jesse L. Boyce
No full textLetter to Jesse L. Boyce from unknown author (possibly Jack) about the investigation into the powder magazine located in the Grand Canyon. Some personal news is included in the letter such as the writer's marriage to the daughter of C.A. Taylor, former Supervisor of Cochise County
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