Modeling adoption of innovations in agriculture using discrete choice models

This paper is concerned with the development of varieties and fertilization techniques of greenhouse tomatoes, and their spatial diffusion in the northwestern region of the Negev in Israel. The main objective of the paper is to identify the factors affecting the farmers’ decision to adopt innovations and the factors inducing the process of knowledge-diffusion in the rural region. The approach adopted is the use of discrete choice models based on random utility theory. Results of the empirical analysis when applying the disaggregate Logit Model indicate that the regional, local and individual attributes have a significant bearing on the farmers’ decision-making process in regard to choosing among alternative tomato varieties and fertilization techniques. The findings indicate that the models constructed for this study may be used as a planning tool for the purpose of evaluating the effect of different factors on the spatial diffusion of innovations in rural regions. The results of the research could also assist decision-makers in formulating development policies for rural regions. Keywords: Spatial diffusion; discrete choice models; greenhouse tomatoes; nested logit

Breakdown of the Internet under intentional attack

We study the tolerance of random networks to intentional attack, whereby a fraction p of the most connected sites is removed. We focus on scale-free networks, having connectivity distribution of P(k)~k^(-a) (where k is the site connectivity), and use percolation theory to study analytically and numerically the critical fraction p_c needed for the disintegration of the network, as well as the size of the largest connected cluster. We find that even networks with a<=3, known to be resilient to random removal of sites, are sensitive to intentional attack. We also argue that, near criticality, the average distance between sites in the spanning (largest) cluster scales with its mass, M, as sqrt(M), rather than as log_k M, as expected for random networks away from criticality. Thus, the disruptive effects of intentional attack become relevant even before the critical threshold is reached.Comment: Latex, 4 pages, 3 eps figure

Anomalous biased diffusion in networks

We study diffusion with a bias towards a target node in networks. This problem is relevant to efficient routing strategies in emerging communication networks like optical networks. Bias is represented by a probability $p$ of the packet/particle to travel at every hop towards a site which is along the shortest path to the target node. We investigate the scaling of the mean first passage time (MFPT) with the size of the network. We find by using theoretical analysis and computer simulations that for Random Regular (RR) and Erd\H{o}s-R\'{e}nyi (ER) networks, there exists a threshold probability, $p_{th}$, such that for $p<p_{th}$ the MFPT scales anomalously as $N^\alpha$, where $N$ is the number of nodes, and $\alpha$ depends on $p$. For $p>p_{th}$ the MFPT scales logarithmically with $N$. The threshold value $p_{th}$ of the bias parameter for which the regime transition occurs is found to depend only on the mean degree of the nodes. An exact solution for every value of $p$ is given for the scaling of the MFPT in RR networks. The regime transition is also observed for the second moment of the probability distribution function, the standard deviation.Comment: 13 Pages, To appear in PR

Modeling adoption of innovations in agriculture using discrete choice models

This paper is concerned with the development of varieties and fertilization techniques of greenhouse tomatoes, and their spatial diffusion in the northwestern region of the Negev in Israel. The main objective of the paper is to identify the factors affecting the farmers’ decision to adopt innovations and the factors inducing the process of knowledge-diffusion in the rural region. The approach adopted is the use of discrete choice models based on random utility theory. Results of the empirical analysis when applying the disaggregate Logit Model indicate that the regional, local and individual attributes have a significant bearing on the farmers’ decision-making process in regard to choosing among alternative tomato varieties and fertilization techniques. The findings indicate that the models constructed for this study may be used as a planning tool for the purpose of evaluating the effect of different factors on the spatial diffusion of innovations in rural regions. The results of the research could also assist decision-makers in formulating development policies for rural regions. Keywords: Spatial diffusion; discrete choice models; greenhouse tomatoes; nested logi

Distributed Computations with Layered Resolution

Modern computationally-heavy applications are often time-sensitive, demanding distributed strategies to accelerate them. On the other hand, distributed computing suffers from the bottleneck of slow workers in practice. Distributed coded computing is an attractive solution that adds redundancy such that a subset of distributed computations suffices to obtain the final result. However, the final result is still either obtained within a desired time or not, and for the latter, the resources that are spent are wasted. In this paper, we introduce the novel concept of layered-resolution distributed coded computations such that lower resolutions of the final result are obtained from collective results of the workers -- at an earlier stage than the final result. This innovation makes it possible to have more effective deadline-based systems, since even if a computational job is terminated because of timing, an approximated version of the final result can be released. Based on our theoretical and empirical results, the average execution delay for the first resolution is notably smaller than the one for the final resolution. Moreover, the probability of meeting a deadline is one for the first resolution in a setting where the final resolution exceeds the deadline almost all the time, reducing the success rate of the systems with no layering