Estimating Spatial Changes Over Time of Arctic Sea Ice using Hidden 2×2 Tables

Arctic sea ice extent has been of considerable interest to scientists in recent years, mainly due to its decreasing temporal trend over the past 20 years. In this article, we propose a hierarchical spatio‐temporal generalized linear model for binary Arctic sea‐ice‐extent data, where statistical dependencies in the data are modeled through a latent spatio‐temporal linear mixed effects model. By using a fixed number of spatial basis functions, the resulting model achieves both dimension reduction and non‐stationarity for spatial fields at different time points. An EM algorithm is proposed to estimate model parameters, and an empirical–hierarchical‐modeling approach is applied to obtain the predictive distribution of the latent spatio‐temporal process. We illustrate the accuracy of the parameter estimation through a simulation study. The hierarchical model is applied to spatial Arctic sea‐ice‐extent data in the month of September for 20 years in the recent past, where several posterior summaries are obtained to detect the changes of Arctic sea ice cover. In particular, we consider a time series of latent 2 × 2 tables to infer the spatial changes of Arctic sea ice over time.     

控制醋酸生产的滗析器相分离

正专利披露了控制醋酸生产的滗析器相分离方法,醋酸是甲醇羰基化反应生产的。方法包括测量反应器混合物中醋酸甲酯浓度,根据测量得到的醋酸甲酯浓度,计算滗析器重,有机相的密度,调节反应器或滗析器的操作条件,保证滗     

Learning from Innate Behaviors: A Quantitative Evaluation of Neural Network Controllers

The aim was to investigate a method of developing mobile robot controllers based on ideas about how plastic neural systems adapt to their environment by extracting regularities from the amalgamated behavior of inflexible (nonplastic) innate subsystems interacting with the world. Incremental bootstrapping of neural network controllers was examined. The objective was twofold. First, to develop and evaluate the use of prewired or innate robot controllers to bootstrap backpropagation learning for Multilayer Perceptron (MLP) controllers. Second, to develop and evaluate a new MLP controller trained on the back of another bootstrapped controller. The experimental hypothesis was that MLPs would improve on the performance of controllers used to train them. The performances of the innate and bootstrapped MLP controllers were compared in eight experiments on the tasks of avoiding obstacles and finding goals. Four quantitative measures were employed: the number of sensorimotor loops required to complete a task; the distance traveled; the mean distance from walls and obstacles; the smoothness of travel. The overall pattern of results from statistical analyses of these quantities supported the hypothesis; the MLP controllers completed the tasks faster, smoother, and steered further from obstacles and walls than their innate teachers. In particular, a single MLP controller incrementally bootstrapped by a MLP subsumption controller was superior to the others.     

Artificial intelligence and natural magic

Robotics with AI is part of a long tradition that has run from ancient times that treated the precursors of robots, the automata, as part of Natural Magic or conjury. Deception is an integral part of AI and robotics; in some ways they form a science of illusion. There are many robot tasks, such as caring for the elderly, minding children, doing domestic chores and being companionable, that involve working closely with humans and so require some illusion of animacy and thought. We discuss how the natural magic of robotics is assisted by the cultural myth of AI together with innate human predispositions such as zoomorphism, the willing suspension of disbelief and a tendency to interpret AI devices as part of the social world. This approach provides a justifiable way of meeting the goals of AI and robotics provided that researchers do not allow themselves to be deceived by their own illusions.     

Fusion of ANNs as decoder of retinal spike trains for scene reconstruction

Applied Intelligence - The retina is one of the most developed sensing organs in the human body. However, the knowledge on the coding and decoding of the retinal neurons are still rather limited....     

A comparative evaluation of interactive segmentation algorithms

In this paper we present a comparative evaluation of four popular interactive segmentation algorithms. The evaluation was carried out as a series of user-experiments, in which participants were tasked with extracting 100 objects from a common dataset: 25 with each algorithm, constrained within a time limit of 2 min for each object. To facilitate the experiments, a “scribble-driven” segmentation tool was developed to enable interactive image segmentation by simply marking areas of foreground and background with the mouse. As the participants refined and improved their respective segmentations, the corresponding updated segmentation mask was stored along with the elapsed time. We then collected and evaluated each recorded mask against a manually segmented ground truth, thus allowing us to gauge segmentation accuracy over time. Two benchmarks were used for the evaluation: the well-known Jaccard index for measuring object accuracy, and a new fuzzy metric, proposed in this paper, designed for measuring boundary accuracy. Analysis of the experimental results demonstrates the effectiveness of the suggested measures and provides valuable insights into the performance and characteristics of the evaluated algorithms.     

Ongoing verification of a multiphysics community code: FLASH

When developing a complex, multi‐authored code, daily testing on multiple platforms and under a variety of conditions is essential. It is therefore necessary to have a regression test suite that is easily administered and configured, as well as a way to easily view and interpret the test suite results. We describe the methodology for verification of FLASH, a highly capable multiphysics scientific application code with a wide user base. The methodology uses a combination of unit and regression tests and an in‐house testing software that is optimized for operation under limited resources. Although our practical implementations do not always comply with theoretical regression‐testing research, our methodology provides a comprehensive verification of a large scientific code under resource constraints.Copyright © 2013 John Wiley & Sons, Ltd.     

A self‐scalable load injection service

Load testing of applications is an important and costly activity for software provider companies. Classical solutions are very difficult to set up statically, and their cost is prohibitive in terms of both human and hardware resources. Virtualized cloud computing platforms provide new opportunities for stressing an application's scalability, by providing a large range of flexible and less expensive (pay‐per‐use model) computation units. On the basis of these advantages, load testing solutions could be provided on demand in the cloud. This paper describes a Benchmark‐as‐a‐Service solution that automatically scales the load injection platform and facilitates its setup according to load profiles. Our approach is based on: (i) virtualization of the benchmarking platform to create self‐scaling injectors; (ii) online calibration to characterize the injector's capacity and impact on the benched application; and (iii) a provisioning solution to appropriately scale the load injection platform ahead of time. We also report experiments on a benchmark illustrating the benefits of this system in terms of cost and resource reductions. Copyright © 2013 John Wiley & Sons, Ltd.     

Experimenting with Isabelle in ZF set theory

The theorem prover Isabelle has been used to axiomatise ZF set theory with natural deduction and to prove a number of theorems concerning functions. In particular, the well-founded recursion theorem has been derived, allowing the definition of functions over recursive types (such as the length and the append functions for lists). The theory of functions has been developed sufficiently within ZF to include PP, the theory of continuous functions forming the basis of LCF. Most of the theorems have been derived using backward proofs, with a small amount of automation.The work has been carried out at the Computer Laboratory of the University of Cambridge.     

Bilingual text detection from natural scene images using faster R-CNN and extended histogram of oriented gradients

Pattern Analysis and Applications - In today's world, scene text detection is important for a wide range of scientific and industrial processes. Compared with text detection in documents, text...