Generalized Lineage-Aware Temporal Windows: Supporting Outer and Anti Joins in Temporal-Probabilistic Databases

The result of a temporal-probabilistic (TP) join with negation includes, at each time point, the probability with which a tuple of a positive relation ${\bf p}$ matches none of the tuples in a negative relation ${\bf n}$, for a given join condition $\theta$. TP outer and anti joins thus resemble the characteristics of relational outer and anti joins also in the case when there exist time points at which input tuples from ${\bf p}$ have non-zero probabilities to be $true$ and input tuples from ${\bf n}$ have non-zero probabilities to be $false$, respectively. For the computation of TP joins with negation, we introduce generalized lineage-aware temporal windows, a mechanism that binds an output interval to the lineages of all the matching valid tuples of each input relation. We group the windows of two TP relations into three disjoint sets based on the way attributes, lineage expressions and intervals are produced. We compute all windows in an incremental manner, and we show that pipelined computations allow for the direct integration of our approach into PostgreSQL. We thereby alleviate the prevalent redundancies in the interval computations of existing approaches, which is proven by an extensive experimental evaluation with real-world datasets

Financial Crisis and Risk Management: Reassessing the Asian Financial Crisis in Light of the American Financial Crisis

No abstract available

Effect of cell residence time variance on the performance of an advanced paging algorithm

The use of advanced sequential paging algorithms has been suggested as a means to reduce the signaling cost in future mobile cellular networks. In a proposed algorithm (Koukoutsidis and Theologou, 2003), the system can use the additional information of the last interaction cell combined with a mobility model to predict the short-term location probabilities at the time of an incoming call arrival. The short-term location probabilities reduce the uncertainty in mobile user position and thus greatly improve the search. In this paper, an analytical model is derived that allows for a general distribution of cell residence times. By considering a Gamma distribution, we study the effect of the variance of cell residence times and derive useful results on the performance of the algorithm.Comment: 8 pages, 3 figure

Lineage-Aware Temporal Windows: Supporting Set Operations in Temporal-Probabilistic Databases

In temporal-probabilistic (TP) databases, the combination of the temporal and the probabilistic dimension adds significant overhead to the computation of set operations. Although set queries are guaranteed to yield linearly sized output relations, existing solutions exhibit quadratic runtime complexity. They suffer from redundant interval comparisons and additional joins for the formation of lineage expressions. In this paper, we formally define the semantics of set operations in TP databases and study their properties. For their efficient computation, we introduce the lineage-aware temporal window, a mechanism that directly binds intervals with lineage expressions. We suggest the lineage-aware window advancer (LAWA) for producing the windows of two TP relations in linearithmic time, and we implement all TP set operations based on LAWA. By exploiting the flexibility of lineage-aware temporal windows, we perform direct filtering of irrelevant intervals and finalization of output lineage expressions and thus guarantee that no additional computational cost or buffer space is needed. A series of experiments over both synthetic and real-world datasets show that (a) our approach has predictable performance, depending only on the input size and not on the number of time intervals per fact or their overlap, and that (b) it outperforms state-of-the-art approaches in both temporal and probabilistic databases

Broadband enhancement of the magneto-optical activity of hybrid Au loaded Bi:YIG

We unravel the underlying near-field mechanism of the enhancement of the magneto-optical activity of bismuth-substituted yttrium iron garnet films (Bi:YIG) loaded with gold nanoparticles. The experimental results show that the embedded gold nanoparticles lead to a broadband enhancement of the magneto-optical activity with respect to the activity of the bare Bi:YIG films. Full vectorial near- and far-field simulations demonstrate that this broadband enhancement is the result of a magneto-optically enabled cross-talking of orthogonal localized plasmon resonances. Our results pave the way to the on-demand design of the magneto-optical properties of hybrid magneto-plasmonic circuitry.Comment: 6 Pages, 3 Figure

Commodity-based Sovereign Wealth Funds: Managing Financial Flows in the Context of the Sovereign Balance Sheet

Commodity-based sovereign wealth funds (SWFs) have been at a crossroads following the recent fall in commodity prices. This paper provides a framework for commodity-based SWF management, focusing on stabilization and savings funds, by (i) examining macrofiscal linkages for SWFs; (ii) presenting an integrated sovereign asset and liability management (SALM) approach to SWF management; and (iii) applying this framework to a scenario where assets are being accumulated and to a scenario where the SWF is drawn on to cover a financing gap due to lower commodity prices

Sovereign Risk and Asset and Liability Management—Conceptual Issues

Country practices towards managing financial risks on a sovereign balance sheet continue to evolve. Each crisis period, and its legacy on sovereign balance sheets, reaffirms the need for strengthening financial risk management. This paper discusses some salient features embedded in the current generation of sovereign asset and liability management (SALM) approaches, including objectives, definitions of relevant assets and liabilities, and methodologies used in obtaining optimal SALM outcomes. These elements are used in developing an analytical SALM framework which could become an operational instrument in formulating asset management and debtor liability management strategies at the sovereign level. From a portfolio perspective, the SALM approach could help detect direct and derived sovereign risk exposures. It allows analyzing the financial characteristics of the balance sheet, identifying sources of costs and risks, and quantifying the correlations among these sources of risk. The paper also outlines institutional requirements in implementing an SALM framework and seeks to lay the ground for further policy and analytical work on this topi

Towards Greening Finance: Integration of Environmental Factors in Risk Management & Impact of Climate Risks on Asset Portfolios

It is increasingly realized that financial-asset investors individually are not likely able to affect climate developments significantly, while the financial sector collectively cannot hedge all climate-related risks. Nevertheless, the financial sector could help channel savings into green projects through both equity and bond markets, and thus facilitate divestment from heavy carbon-footprint producers. This paper provides a novel framework for understanding climate-related adaptation, mitigation, and transition risks and outlines a method for valuing these risks in investors’ portfolios. Our proposed comprehensive set up can serve as a call for action to longer-term institutional investors to obtain accurate information on climate-related risks, develop appropriate frameworks for understanding these risks, and regularly value them. We maintain that through improvements in the assessment of risks, financial stakeholders would be able to help better manage climate-related risks and facilitate an easier transition from brown to sustainable green finance

Supporting Set Operations in Temporal-Probabilistic Databases

In temporal-probabilistic (TP) databases, the combination of the temporal and the probabilistic dimension adds significant overhead to the computation of set operations. Although set queries are guaranteed to yield linearly sized output relations, all of the existing solutions exhibit a quadratic runtime complexity. They suffer from redundant interval comparisons and additional joins for the formation of lineage expressions. In this paper, we formally define TP set operations and study their properties. For their efficient computation, we introduce the lineage-aware temporal window, a mechanism that binds intervals with lineage expressions. We suggest the lineage-aware window advancer (LAWA) for producing lineage-aware temporal windows, which enable direct filtering of irrelevant intervals and finalization of output lineage expressions. This way, we compute TP set operations in linearithmic time. A series of experiments over both synthetic and real-world datasets show that (a) our approach has predictable performance, which depends only on the size of the input relations and not on the number of time intervals per fact or the overlap of the time intervals, and that (b) it outperforms state-of-the-art approaches