19,524 research outputs found
Can social safety nets alleviate seasonal deprivation ? evidence from northwest Bangladesh
This paper examines the role of social safety-net programs in Bangladesh run by the government and nongovernmental organizations to mitigate seasonal deprivation in the country's highly vulnerable northwest region. Specifically, the paper explores whether social safety nets are limited to averting seasonal deprivation or can also address seasonality of income and employment more generally. Using a recent survey from the greater Rangpur (northwest) region, the paper finds that social safety nets have a positive effect on mitigating both seasonal and non-seasonal food deprivation. The results are robust, owing to the recent expanded coverage of social safety-net programs run by nongovernmental organizations active in the region. But given the annual recurrence of monga (seasonal food insecurity) in the northwest region owing to agricultural seasonality and an overwhelming dependence on agriculture for livelihoods, social safety nets are not a reliable tool for monga eradication. Programs are also needed to promote the income and productivity of the poor through diversification of income and employment.Safety Nets and Transfers,Rural Poverty Reduction,Food&Beverage Industry,Regional Economic Development,Housing&Human Habitats
Black hole - D-brane correspondence: An example
We explore the connection between D-branes and black holes in one particular
case: a -brane compactified to four dimensions on . Using the
-brane boundary state description we show the equivalence with a double
extremal N=2 black hole solution of four dimensional supergravity.Comment: 15 pages, LaTeX. Contribution by C. Nunez to the conference Quantum
Gravity in the Southern Cone, Bariloche 7-10 January 1998; to appear in the
proceeding
Land and water productivity of wheat in the Western Indo-Gangetic Plains of India and Pakistan: a comparative analysis
Wheat / Crop yield / Productivity / Climate / Irrigation canals / Watercourses / Water distribution / Water allocation / Policy / India / Pakistan / Gangetic Plains / Kaithal Irrigation Circle / Bhakra Canal / Chaj Sub-Basin / Lower Jehlum Canal
Dynamics of coherent structures in a plane mixing layer
An incompressible, time developing 3-D mixing layer with idealized initial conditions was simulated numerically. Consistent with the suggestions from experimental measurements, the braid region between the dominant spanwise vortices or rolls develops longitudinal vortices or ribs, which are aligned upstream and downstream of a roll and produce spanwise distortion of the rolls. The process by which this distortion occurs is explained by studying a variety of quantities of dynamic importance (e.g., production of enstrophy, vortex stretching). Other quantities of interest (dissipation, helicity density) are also computed and discussed. The currently available simulation only allows the study of the early evolution (before pairing) of the mixing layer. New simulations in progress will relieve this restriction
Seasonal and extreme poverty in Bangladesh : evaluating an ultra-poor microfinance project
Microfinance is often criticized for not adequately addressing seasonality and hard-core poverty. In Bangladesh, a program known as PRIME was introduced in 2006 to address both concerns. Unlike regular microfinance, PRIME introduces a microfinance scheme that offers a flexible repayment schedule and consumption smoothing, as well as production, loans. It targets the ultra-poor, many of whom are also seasonally poor, with a severe inability to smooth consumption during certain months of the year. Besides providing loans, PRIME offers extension and training services. This paper uses a quasi-experimental survey design to evaluate PRIME against regular microfinance programs. The results show that PRIME is more effective than regular microfinance in reaching the ultra-poor, as well as the seasonal poor. PRIME also helps reduce seasonal deprivation and extreme poverty. Although the program has demonstrated its promise, it is too early to conclude whether the accrued benefits are large enough to contain both seasonal and chronic poverty on a sustained basis.Rural Poverty Reduction,Regional Economic Development,Food&Beverage Industry,Debt Markets
Hybrid mamdani fuzzy rules and convolutional neural networks for analysis and identification of animal images
Accurate, fast, and automatic detection and classification of animal images is challenging, but it is much needed for many real-life applications. This paper presents a hybrid model of Mamdani Type-2 fuzzy rules and convolutional neural networks (CNNs) applied to identify and distinguish various animals using different datasets consisting of about 27,307 images. The proposed system utilizes fuzzy rules to detect the image and then apply the CNN model for the object’s predicate category. The CNN model was trained and tested based on more than 21,846 pictures of animals. The experiments’ results of the proposed method offered high speed and efficiency, which could be a prominent aspect in designing image-processing systems based on Type 2 fuzzy rules characterization for identifying fixed and moving images. The proposed fuzzy method obtained an accuracy rate for identifying and recognizing moving objects of 98% and a mean square error of 0.1183464 less than other studies. It also achieved a very high rate of correctly predicting malicious objects equal to recall = 0.98121 and a precision rate of 1. The test’s accuracy was evaluated using the F1 Score, which obtained a high percentage of 0.99052
Deep learning versus spectral techniques for frequency estimation of single tones: Reduced complexity for software-defined radio and iot sensor communications
Despite the increasing role of machine learning in various fields, very few works considered artificial intelligence for frequency estimation (FE). This work presents comprehensive analysis of a deep-learning (DL) approach for frequency estimation of single tones. A DL network with two layers having a few nodes can estimate frequency more accurately than well-known classical techniques can. While filling the gap in the existing literature, the study is comprehensive, analyzing errors under different signal-to-noise ratios (SNRs), numbers of nodes, and numbers of input samples under missing SNR information. DL-based FE is not significantly affected by SNR bias or number of nodes. A DL-based approach can properly work using a minimal number of input nodes N at which classical methods fail. DL could use as few as two layers while having two or three nodes for each, with the complexity of O{N} compared with discrete Fourier transform (DFT)-based FE with O{Nlog2 (N)} complexity. Furthermore, less N is required for DL. Therefore, DL can significantly reduce FE complexity, memory cost, and power consumption, which is attractive for resource-limited systems such as some Internet of Things (IoT) sensor applications. Reduced complexity also opens the door for hardware-efficient implementation using short-word-length (SWL) or time-efficient software-defined radio (SDR) communications
Bounds On Fuzzy Dominator Chromatic Number of Fuzzy Soft Bipartite Graphs
An FSG GS(T,V) fuzzy’s soft dominator colouring (FSDC) is a suitable Fuzzy Soft Colouring (FSC) where every node of a colour groupis dominated by a vertex of GS(T,V). In the current work, we characterize the sharp bounds for the Fuzzy Dominator Chromatic Number(FDCN) of fuzzy soft bipartite graphs and we present limits on theFDCN of fuzzy soft bipartite graph in terms of the γe(GS(T; V )).Furthermore, we classify fuzzy soft bipartite graphs into three classesbased on FDC
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