Investment-Linked Takaful Plan Patronage: Evidence From Malaysia

Investment-linked Takaful is a recent innovation introduced in Malaysia. This study focuses on Investment-linked takaful plan selection in Malaysia. We have used a self-administered questionnaire to collect data from 143 respondents from the Klang Valley area. Data collected through the survey was analyzed through descriptive statistics, correlation and regression analysis. Results indicate that fee payment and benefits play a significant role in Takaful operator selection while coverage and benefits affect the investment-linked product selection in Malaysia. This study is unique as it provides empirical evidence on the investment-linked takaful investment which is limited in supply. Results provided by this study can be useful for takaful operators in designing the most appropriate investment-linked product for attracting customers

Linked open government data: lessons from Data.gov.uk

The movement to publish government data is an opportunity to populate the linked data Web with data of good provenance. The benefits range from transparency to public service improvement, citizen engagement to the creation of social and economic value. There are many challenges to be met before the vision is implemented, and this paper describes the efforts of the EnAKTing project to extract value from data.gov.uk, through the stages of locating data sources, integrating data into the linked data Web, and browsing and querying it

Free education, pensions and the university as a business

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Valuation of boundary-linked assets

This article studies the valuation of boundary-linked assets and their derivatives in continuous-time markets. Valuing boundary-linked assets requires the solution of a stochastic differential equation with boundary conditions, which, often, is not Markovian. We propose a wavelet-collocation algorithm for solving a Milstein approximation to the stochastic boundary problem. Its convergence properties are studied. Furthermore, we value boundary-linked derivatives using Malliavin calculus and Monte Carlo methods. We apply these ideas to value European call options of boundary-linked asset

Collaboratively Patching Linked Data

Today's Web of Data is noisy. Linked Data often needs extensive preprocessing to enable efficient use of heterogeneous resources. While consistent and valid data provides the key to efficient data processing and aggregation we are facing two main challenges: (1st) Identification of erroneous facts and tracking their origins in dynamically connected datasets is a difficult task, and (2nd) efforts in the curation of deficient facts in Linked Data are exchanged rather rarely. Since erroneous data often is duplicated and (re-)distributed by mashup applications it is not only the responsibility of a few original publishers to keep their data tidy, but progresses to be a mission for all distributers and consumers of Linked Data too. We present a new approach to expose and to reuse patches on erroneous data to enhance and to add quality information to the Web of Data. The feasibility of our approach is demonstrated by example of a collaborative game that patches statements in DBpedia data and provides notifications for relevant changes.Comment: 2nd International Workshop on Usage Analysis and the Web of Data (USEWOD2012) in the 21st International World Wide Web Conference (WWW2012), Lyon, France, April 17th, 201

Energy Bounds of Linked Vortex States

Energy bounds of knotted and linked vortex states in a charged two-component system are considered. It is shown that a set of local minima of free energy contains new classes of universality. When the mutual linking number of vector order parameter vortex lines is less than the Hopf invariant, these states have lower-lying energies.Comment: 4 pages, Latex2

AGN Absorption Linked to Host Galaxies

Multiwavelength identification of AGN is crucial not only to obtain a more complete census, but also to learn about the physical state of the nuclear activity (obscuration, efficiency, etc.). A panchromatic strategy plays an especially important role when the host galaxies are star-forming. Selecting far-Infrared galaxies at 0.3<z<1, and using AGN tracers in the X-ray, optical spectra, mid-infrared, and radio regimes, we found a twice higher AGN fraction than previous studies, thanks to the combined AGN identification methods and in particular the recent Mass-Excitation (MEx) diagnostic diagram. We furthermore find an intriguing relation between AGN X-ray absorption and the specific star formation rate (sSFR) of the host galaxies, indicating a physical link between X-ray absorption and either the gas fraction or the gas geometry in the hosts. These findings have implications for our current understanding of both the AGN unification model and the nature of the black hole-galaxy connection. These proceedings review selected results by Juneau et al. (2013, ApJ 764, 176), and their implications. The original work involved several members from the GOODS and AEGIS teams.Comment: Proceedings to be published for the IAU Symposium 304: Multiwavelength AGN Surveys and Studies. 4 pages. 2 figures. v2: Fixed a referenc

Predicate Abstraction for Linked Data Structures

We present Alias Refinement Types (ART), a new approach to the verification of correctness properties of linked data structures. While there are many techniques for checking that a heap-manipulating program adheres to its specification, they often require that the programmer annotate the behavior of each procedure, for example, in the form of loop invariants and pre- and post-conditions. Predicate abstraction would be an attractive abstract domain for performing invariant inference, existing techniques are not able to reason about the heap with enough precision to verify functional properties of data structure manipulating programs. In this paper, we propose a technique that lifts predicate abstraction to the heap by factoring the analysis of data structures into two orthogonal components: (1) Alias Types, which reason about the physical shape of heap structures, and (2) Refinement Types, which use simple predicates from an SMT decidable theory to capture the logical or semantic properties of the structures. We prove ART sound by translating types into separation logic assertions, thus translating typing derivations in ART into separation logic proofs. We evaluate ART by implementing a tool that performs type inference for an imperative language, and empirically show, using a suite of data-structure benchmarks, that ART requires only 21% of the annotations needed by other state-of-the-art verification techniques