Remote sensing and geographic information systems techniques for landslide hazard evaluation and prediction models

I would like to express my sincere gratitude to Professor Takaaki Amada,my academic advisor for his immutable inspiration,guidance and support in this research.This research would not have been possible without his support and encouragement. ...Thesis (Ph. D. in Agriculture)--University of Tsukuba, (A), no. 2270, 2000.3.24Titlepage,Contents -- Acknowledgments,Abstract -- List of Tables,List of Figures -- Glossary -- 1.Introduction -- 2. Study Area -- 3. Research Reviews,Approaches Employed and Issues -- 4. Assessment of Landslide Affected Areas Using Satellite Digital Data -- 5. Landslide Hazard Assessment,Mapping and Evaluation of Hazard Maps -- 6. Summary and Conclusions -- Reference

Maximizing Service Reliability in Distributed Computing Systems with Random Node Failures: Theory and Implementation

In distributed computing systems (DCSs) where server nodes can fail permanently with nonzero probability, the system performance can be assessed by means of the service reliability, defined as the probability of serving all the tasks queued in the DCS before all the nodes fail. This paper presents a rigorous probabilistic framework to analytically characterize the service reliability of a DCS in the presence of communication uncertainties and stochastic topological changes due to node deletions. The framework considers a system composed of heterogeneous nodes with stochastic service and failure times and a communication network imposing random tangible delays. The framework also permits arbitrarily specified, distributed load-balancing actions to be taken by the individual nodes in order to improve the service reliability. The presented analysis is based upon a novel use of the concept of stochastic regeneration, which is exploited to derive a system of difference-differential equations characterizing the service reliability. The theory is further utilized to optimize certain load-balancing policies for maximal service reliability; the optimization is carried out by means of an algorithm that scales linearly with the number of nodes in the system. The analytical model is validated using both Monte Carlo simulations and experimental data collected from a DCS testbed

Weed Management in Pulses: Overview and Prospects

Pulses, the world’s second-most consumed food, are an important source of food. They face several major challenges, including weed infestations, as a wide variety of weeds compete with them. Because of their competition with weeds, pulses can suffer a significant yield reduction. So as to alleviate such a menace, growers rely on different management tools, such as tillage, intercropping systems, and herbicides. Each method has been effective, albeit to varying degrees, in resolving the issue. Chemical herbicides, however, have served as double-edged swords over the past few decades due to their indiscriminate use. The repetitive use of the same herbicide or herbicides with the same mode of action confers resistance, thereby, leading to a serious impact on only nontargets. Therefore, it requires well-thought-out planning for a weed management strategy to maximize yields without creating environmental issues concomitantly. At the present, the integrated weed management approach has been accepted as the most reasonable tool for many farmers, which includes using preventive strategies, mechanical tools, crop rotation, intercropping, and herbicides with different modes of action, but cautiously. Modeling and robotics are the cutting-edge technologies that growers will be using for weed management in the coming days, thanks to the advent of such new innovation

Dynamic time delay models for load balancing, Part II: A stochastic analysis of the effect of delay uncertainty

In large-scale distributed computing systems, in which the computational elements are physically or virtually distant from each other, there are communication-related delays that can significantly alter the expected performance of load-balancing policies that do not account for such delays. This is a particularly significant problem in systems for which the individual units are connected by means of a shared broadband communication medium (e.g., the Internet, ATM, wireless LAN or wireless Internet). In such cases, the delays, in addition to being large, fluctuate randomly, making their one-time accurate prediction impossible. In this work, the stochastic dynamics of a load-balancing algorithm in a cluster of computer nodes are modeled and used to predict the effects of the random time delays on the algorithm’s performance. A discrete-time stochastic dynamical-equation model is presented describing the evolution of the random queue size of each node. Monte Carlo simulation is also used to demonstrate the extent of the role played by the magnitude and uncertainty of the various time-delay elements in altering the performance of load balancing. This study reveals that the presence of delay (deterministic or random) can lead to a significant degradation in the performance of a load-balancing policy. One way to remedy such a problem is to weaken the load-balancing mechanism so that the load-transfer between nodes is down-scaled (or discouraged) appropriately

Maximizing service reliability in distributed computing systems with random failures: Theory and implementation,”

Abstract-In distributed computing systems (DCSs) where server nodes can fail permanently with nonzero probability, the system performance can be assessed by means of the service reliability, defined as the probability of serving all the tasks queued in the DCS before all the nodes fail. This paper presents a rigorous probabilistic framework to analytically characterize the service reliability of a DCS in the presence of communication uncertainties and stochastic topological changes due to node deletions. The framework considers a system composed of heterogeneous nodes with stochastic service and failure times and a communication network imposing random tangible delays. The framework also permits arbitrarily specified, distributed load-balancing actions to be taken by the individual nodes in order to improve the service reliability. The presented analysis is based upon a novel use of the concept of stochastic regeneration, which is exploited to derive a system of difference-differential equations characterizing the service reliability. The theory is further utilized to optimize certain load-balancing policies for maximal service reliability; the optimization is carried out by means of an algorithm that scales linearly with the number of nodes in the system. The analytical model is validated using both Monte Carlo simulations and experimental data collected from a DCS testbed

Compendium of Climate-smart Agriculture Technologies and Practices

Nepal is a vulnerable country to the impacts of climate change. The adverse effects of climate change have decreased agricultural production and productivity. Therefore, technologies and strategies to develop resilience agriculture and increased agriculture productivity are urgently needed to create climate-smart technologies and help the existing technologies to adapt to climate change. This compendium presents climate-smart agriculture (CSA) technologies and interventions for enhancing food security with adaptation and mitigation as co-benefits. CSA involves smart farming practices and strategies that help develop resilience agriculture, increase crop and livestock productivity, reduce greenhouse gas emissions, and enhance food security goals. This compendium has been developed for extension workers to support up-scaling climate-smart technologies and build climate resilience villages that enhance food, nutrition, and income, mainly for marginal communities striving in marginal areas