Bayesian Inference For Exponential Distribution Based On Upper Record Range

This paper deals with Bayesian estimations of scale parameter of the exponential distribution based on upper record range (Rn). This has been done in two steps; point and interval. In the first step the quadratic, squared error and absolute error, loss functions have been considered to obtain Bayesian-point estimations. Also in the next step the shortest Bayes interval (Hight Posterior Density interval) and Bayes interval with equal tails based on upper record range have been found. Therefore, the Homotopy Perturbation Method(HPM) has been applied to obtain the limits of Hight Posterior Density intervals. Moreover, efforts have been made to meet the admissibility conditions for linear estimators based on upper record range of the form mRn+d by obtained Bayesian point estimations. So regarding the consideration of loss functions, the prior distribution between the conjunction family has been chosen to be able to produce the linear estimations from upper record range statistics. Finally, some numerical examples and simulations have been presented

Knowledgezoom for java: A concept-based exam study tool with a zoomable open student model

This paper presents our attempt to develop a personalized exam preparation tool for Java/OOP classes based on a fine-grained concept model of Java knowledge. Our goal was to explore two most popular student model-based approaches: open student modeling and problem sequencing. The result of our work is a Java exam preparation tool, Knowledge Zoom. The tool combines an open concept-level student model component, Knowledge Explorer and a concept-based sequencing component, Knowledge Maximizer into a single interface. This paper presents both components of Knowledge Zoom, reports results of its evaluation, and discusses lessons learned. © 2013 IEEE

Phase-change computing

PosterThis is the final version. Available from E\PCOS via the URL in this record.Phase-change materials and devices are currently generating much interest for their potential to provide practicable alternatives to traditional von-Neumann computing (i.e. alternatives to computing in which memory and processing functions are carried out at physically separated locations). Indeed, many years after Ovshinsky and colleagues first showed the remarkable computing capabilities of phase-change devices (see for example [1-3]), other researchers have recently experimentally demonstrated the potential of phase-change devices to perform not only arithmetic computing [4], but also to provide hardware mimics of both synapses [5, 6] and neurons [4] (so opening the way to so-called bio-inspired or neuromorphic computing). We ourselves recently demonstrated reliable execution of the four basic arithmetic operations of addition, subtraction, multiplication and division using phase-change materials and micrometrescale optical excitation with (groups of) femtosecond pulses [4]. In this paper however we demonstrate that this arithmetic capability is also accessible via the electrical domain and on the nanoscale. [...

A comparative study of visual cues for annotation-based navigation support in adaptive educational hypermedia

Adaptive link annotation is one of the most well-known adaptive navigation support technologies that aims to guide hypermedia users to the most relevant information by personalizing the appearance of hyperlinks. Past work assumed no difference between different interface implementations of personalization approaches that are conceptually the same. The goal of the current study was to determine whether the choice of visual cues does matter by conducting a user study with several alternative designs for link annotation in interactive code examples

The Making of Cloud Applications An Empirical Study on Software Development for the Cloud

Cloud computing is gaining more and more traction as a deployment and provisioning model for software. While a large body of research already covers how to optimally operate a cloud system, we still lack insights into how professional software engineers actually use clouds, and how the cloud impacts development practices. This paper reports on the first systematic study on how software developers build applications in the cloud. We conducted a mixed-method study, consisting of qualitative interviews of 25 professional developers and a quantitative survey with 294 responses. Our results show that adopting the cloud has a profound impact throughout the software development process, as well as on how developers utilize tools and data in their daily work. Among other things, we found that (1) developers need better means to anticipate runtime problems and rigorously define metrics for improved fault localization and (2) the cloud offers an abundance of operational data, however, developers still often rely on their experience and intuition rather than utilizing metrics. From our findings, we extracted a set of guidelines for cloud development and identified challenges for researchers and tool vendors