Measuring consistency in TTL-based caches

We propose a general modeling framework to evaluate the performance of cache consistency algorithms. In addition to the usual hit rate, we introduce the hit^* rate as a consistency measure, which captures the fraction of non-stale downloads from the cache. We apply these ideas to the analysis of the fixed TTL consistency algorithm in the presence of network delays. The hit and hit^* rates are evaluated when requests and updates are modeled by renewal processes. Classical results on the renewal function lead to various bounds.     

Advection‐Based Function Matching on Surfaces

A tangent vector field on a surface is the generator of a smooth family of maps from the surface to itself, known as the flow. Given a scalar function on the surface, it can be transported, or advected, by composing it with a vector field's flow. Such transport is exhibited by many physical phenomena, e.g., in fluid dynamics. In this paper, we are interested in the inverse problem: given source and target functions, compute a vector field whose flow advects the source to the target. We propose a method for addressing this problem, by minimizing an energy given by the advection constraint together with a regularizing term for the vector field. Our approach is inspired by a similar method in computational anatomy, known as LDDMM, yet leverages the recent framework of functional vector fields for discretizing the advection and the flow as operators on scalar functions. The latter allows us to efficiently generalize LDDMM to curved surfaces, without explicitly computing the flow lines of the vector field we are optimizing for. We show two approaches for the solution: using linear advection with multiple vector fields, and using non‐linear advection with a single vector field. We additionally derive an approximated gradient of the corresponding energy, which is based on a novel vector field transport operator. Finally, we demonstrate applications of our machinery to intrinsic symmetry analysis, function interpolation and map improvement.     

Personalization and privacy: a survey of privacy risks and remedies in personalization-based systems

Personalization technologies offer powerful tools for enhancing the user experience in a wide variety of systems, but at the same time raise new privacy concerns. For example, systems that personalize advertisements according to the physical location of the user or according to the user??s friends?? search history, introduce new privacy risks that may discourage wide adoption of personalization technologies. This article analyzes the privacy risks associated with several current and prominent personalization trends, namely social-based personalization, behavioral profiling, and location-based personalization. We survey user attitudes towards privacy and personalization, as well as technologies that can help reduce privacy risks. We conclude with a discussion that frames risks and technical solutions in the intersection between personalization and privacy, as well as areas for further investigation. This frameworks can help designers and researchers to contextualize privacy challenges of solutions when designing personalization systems.     

Effect of Fe-doping on Magnetocaloric Properties of AMn1?x Fe x O3 Compounds (0≤x≤0.2)

We have investigated the effect of iron substitution on the magnetocaloric properties of manganites with La_0.75Ca_0.08Sr_0.17Mn_1?x Fe _x O₃ (x=0, 0.075, 0.15, 0.175, and 0.2) nominal composition. The magnetocaloric effect (MCE) was estimated, in terms of isothermal magnetic entropy change (???S _M ), using the M(T,?? ₀ H) data and employing the thermodynamic Maxwell equation. The large magnetic entropy in AMn_1?x Fe _x O₃ is attributed to the field-induced suppression of short-range charge-orbital ordering and antiferromagnetic fluctuations present above T _C . The increase of the Fe concentration x is accompanied by a decrease of (???S _M ), from 5.205 to 0.95?J/kg?K for x=0 and 0.20, respectively, with ?? ₀ H=5?T. For all samples, we find quite large values of (???S _M ), which are very close to that provided for Gd, the prototypical magnetocaloric material.     

Sleeved co-clustering of lagged data

The paper focuses on mining clusters that are characterized by a lagged relationship between the data objects. We call such clusters lagged co-clusters. A lagged co-cluster of a matrix is a submatrix determined by a subset of rows and their corresponding lag over a subset of columns. Extracting such subsets may reveal an underlying governing regulatory mechanism. Such a regulatory mechanism is quite common in real-life settings. It appears in a variety of fields: meteorology, seismic activity, stock market behavior, neuronal brain activity, river flow, and navigation, but a limited list of examples. Mining such lagged co-clusters not only helps in understanding the relationship between objects in the domain, but assists in forecasting their future behavior. For most interesting variants of this problem, finding an optimal lagged co-cluster is NP-complete problem. We present a polynomial-time Monte-Carlo algorithm for mining lagged co-clusters. We prove that, with fixed probability, the algorithm mines a lagged co-cluster which encompasses the optimal lagged co-cluster by a maximum 2 ratio columns overhead and completely no rows overhead. Moreover, the algorithm handles noise, anti-correlations, missing values, and overlapping patterns. The algorithm is extensively evaluated using both artificial and real-world test environments. The first enable the evaluation of specific, isolated properties of the algorithm. The latter (river flow and topographic data) enable the evaluation of the algorithm to efficiently mine relevant and coherent lagged co-clusters in environments that are temporal, i.e., time reading data and non-temporal.     

Scale and scope of environmental planning transformations: The Israeli case

This paper explores the scale and scope of transformations in the environmental planning field, and the factors that may advance or impede their widespread adoption. A conceptual model is offered which examines scope (defined as type, breadth and structure of the transformation), and the scale of its impact (categorized as stakeholder, organizational, institutional or societal) and applies it to the analysis of several cases in Israel where environmental transformations, affecting the way in which planning is conducted, have been adopted. Conclusions include identification of conditions for facilitating and advancing transformations, including knowledge of innovative alternatives, initiative, willingness to adopt new practices, and identification of policy windows that emerge during conflict, reform, or crisis. The fostering of relations between environmental non-government organizations and planning systems and leadership roles are also significant in catalyzing environmental transformation.     

DSP的独特价值及陷阱

本文涵盖了关于DSP的各种问题，包括DSP如何定义、为何需要DSP、如何实现DSP功能等，并介绍了一些认知上的陷阱。     

Optical generation of fuzzy-based rules

In the last third of the 20th century, fuzzy logic has risen from a mathematical concept to an applicable approach in soft computing. Today, fuzzy logic is used in control systems for various applications, such as washing machines, train-brake systems, automobile automatic gear, and so forth. The approach of optical implementation of fuzzy inferencing was given by the authors in previous papers, giving an extra emphasis to applications with two dominant inputs. In this paper the authors introduce a real-time optical rule generator for the dual-input fuzzy-inference engine. The paper briefly goes over the dual-input optical implementation of fuzzy-logic inferencing. Then, the concept of constructing a set of rules from given data is discussed. Next, the authors show ways to implement this procedure optically. The discussion is accompanied by an example that illustrates the transformation from raw data into fuzzy set rules.     

Harnessing the need for immediate gratification: Cognitive reconstrual modulates the reward value of temptations.

Many of us succumb to temptations, despite knowing that we will later regret doing so. How can such behavior be avoided? In three studies, the authors tested the hypothesis that reconstruing temptation as a test of a valued internal quality ("willpower") would decrease the tendency to succumb by reducing the appeal of the temptation. In Study 1, participants who construed a challenging handgrip task as a test of willpower resisted the temptation to terminate the painful task longer than participants who did not. In Study 2, participants performed a handgrip task twice. Only participants who changed their construal of the task into a test of willpower improved their performance. In Study 3, participants took a timed math test while being tempted by comedy clips. Participants who reconstrued the situation as willpower test compared with participants who did not, (a) enjoyed the videos less, and (b) were better able to resist the tempting videos. These studies demonstrate that cognitive reconstrual can be used to modify reward contingencies, so that succumbing to temptation becomes less appealing, and resisting temptation becomes more appealing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)