Tenant-centric Sub-Tenancy Architecture in Software-as-a-Service

AbstractMulti-tenancy architecture (MTA) is often used in Software-as-a-Service (SaaS) and the central idea is that multiple tenant applications can be developed using components stored in the SaaS infrastructure. Recently, MTA has been extended to allow a tenant application to have its own sub-tenants, where the tenant application acts like a SaaS infrastructure. In other words, MTA is extended to STA (Sub-Tenancy Architecture). In STA, each tenant application needs not only to develop its own functionalities, but also to prepare an infrastructure to allow its sub-tenants to develop customized applications. This paper applies Crowdsourcing as the core to STA component in the development life cycle. In addition, to discovering adequate fit tenant developers or components to help build and compose new components, dynamic and static ranking models are proposed. Furthermore, rank computation architecture is presented to deal with the case when the number of tenants and components becomes huge. Finally, experiments are performed to demonstrate that the ranking models and the rank computation architecture work as design

Priori information and sliding window based prediction algorithm for energy-efficient storage systems in cloud

One of the major challenges in cloud computing and data centers is the energy conservation and emission reduction. Accurate prediction algorithms are essential for building energy efficient storage systems in cloud computing. In this paper, we first propose a Three-State Disk Model (3SDM), which can describe the service quality and energy consumption states of a storage system accurately. Based on this model, we develop a method for achieving energy conservation without losing quality by skewing the workload among the disks to transmit the disk states of a storage system. The efficiency of this method is highly dependent on the accuracy of the information predicting the blocks to be accessed and the blocks not be accessed in the near future. We develop a priori information and sliding window based prediction (PISWP) algorithm by taking advantage of the priori information about human behavior and selecting suitable size of sliding window. The PISWP method targets at streaming media applications, but we also check its efficiency on other two applications, news in webpage and new tool released. Disksim, an established storage system simulator, is applied in our experiments to verify the effect of our method for various users’ traces. The results show that this prediction method can bring a high degree energy saving for storage systems in cloud computing environment

Flutter Influence Mode Analysis of High Speed Wing Model

AbstractIn flutter wind tunnel test, the matching degree between scaled model and prototype would directly affect the reliability of test results. It is difficult to achieve completely dynamic similarity because of some material or technological constrains, and only lower order modes including mode shape and frequency are accurately simulated to construct a compromised model. Theoretical support would be necessary to answer the question which modes must be simulated to guarantee data validity of wind tunnel flutter test. An analytical study of a sweepback winghas been undertaken to estimate the flutter influence mode needed for accurate flutter prediction by analyzing generalized aerodynamic stiffness coefficient, unsteady aerodynamic force and flutter results. The results show that the aerodynamic stiffness coefficient with expression of mode shape could be taken as a quick criterion for mode selection in flutter model design and analysis

Segmental and transmural motion of the rat myocardium estimated using quantitative ultrasound with new strategies for infarct detection

Introduction: The estimation of myocardial motion abnormalities has great potential for the early diagnosis of myocardial infarction (MI). This study aims to quantitatively analyze the segmental and transmural myocardial motion in MI rats by incorporating two novel strategies of algorithm parameter optimization and transmural motion index (TMI) calculation.Methods: Twenty-one rats were randomly divided into three groups (n = 7 per group): sham, MI, and ischemia–reperfusion (IR) groups. Ultrasound radio-frequency (RF) signals were acquired from each rat heart at 1 day and 28 days after animal model establishment; thus, a total of six datasets were represented as Sham1, Sham28, MI1, MI28, IR1, and IR28. The systolic cumulative displacement was calculated using our previously proposed vectorized normalized cross-correlation (VNCC) method. A semiautomatic regional and layer-specific myocardium segmentation framework was proposed for transmural and segmental myocardial motion estimation. Two novel strategies were proposed: the displacement-compensated cross-correlation coefficient (DCCCC) for algorithm parameter optimization and the transmural motion index (TMI) for quantitative estimation of the cross-wall transmural motion gradient.Results: The results showed that an overlap value of 80% used in VNCC guaranteed a more accurate displacement calculation. Compared to the Sham1 group, the systolic myocardial motion reductions were significantly detected (p < 0.05) in the middle anteroseptal (M-ANT-SEP), basal anteroseptal (B-ANT-SEP), apical lateral (A-LAT), middle inferolateral (M-INF-LAT), and basal inferolateral (B-INF-LAT) walls as well as a significant TMI drop (p < 0.05) in the M-ANT-SEP wall in the MI1 rats; significant motion reductions (p < 0.05) were also detected in the B-ANT-SEP and A-LAT walls in the IR1 group. The motion improvements (p < 0.05) were detected in the M-INF-LAT wall in the MI28 group and the apical septal (A-SEP) wall in the IR28 group compared to the MI1 and IR1 groups, respectively.Discussion: Our results show that the MI-induced reductions and reperfusion-induced recovery in systolic myocardial contractility could be successfully evaluated using our method, and most post-MI myocardial segments could recover systolic function to various extents in the remodeling phase. In conclusion, the ultrasound-based quantitative estimation framework for estimating segmental and transmural motion of the myocardium proposed in our study has great potential for non-invasive, novel, and early MI detection

A Review of Current Electric Power Network Expansion Models

Electric power transmission expansion planning (TEP), which involves identifying the areas where the existing transmission infrastructure is inadequate, determining the optimal locations and routes for new transmission lines and substations, and evaluating each option in detail. TEP is important for ensuring the reliable and cost-effective delivery of electricity to consumers, and it requires consideration of technical, economic, environmental, and social factors. In this paper, we briefly compare different TEP models, while addressing the advantages and disadvantages of each approach

Application of statins in management of glioma: Recent advances

Gliomas are common primary intra-cerebral tumors in adults, and seriously threaten the health and life of affected patients, especially highly-malignant gliomas, such as glioblastoma multiforme. The clinical prognosis of glioma patients is poor, even for those who have received comprehensive treatment including surgery and concurrent chemo- and/or radio-therapy. As a structural analog of β-hydroxy-β- methylglutaryl coenzyme A (HMG CoA) reductase, statins are a restrictive enzyme in the metabolism of cholesterol. Recent laboratory studies and clinical trials have demonstrated that statins can exert antitumor effect, improve clinical prognosis and significantly prolong the survival time of glioma patients. This article is aimed to highlight the mechanisms of the anti-glioma effect of statins and review recent advances in the management of the disease.Keywords: Glioma, Glioblastoma multiforme, Intra-cerebral tumors, Statins, Prognosis, Survival time, β-Hydroxy-β-methylglutaryl coenzyme A (HMG CoA) reductas

Higher-order Topological and Nodal Superconductors MS (M = Nb and Ta) Transition-metal Sulfides

Intrinsic topological superconducting materials are exotic and vital to develop the next-generation topological superconducting devices, topological quantum calculations, and quantum information technologies. Here, we predict the topological and nodal superconductivity of MS (M = Nb and Ta) transition-metal sulfides by using the density functional theory for superconductors combining with the symmetry indicators. We reveal their higher-order topology nature with an index of Z4 = 2. These materials have a higher Tc than the Nb or Ta metal superconductors due to their flat-band and strong electron-phonon coupling nature. Electron doping and lighter isotopes can effectively enhance the Tc. Our findings show that the MS (M = Nb and Ta) systems can be new platforms to study exotic physics in the higher-order topological superconductors, and provide a theoretical support to utilize them as the topological superconducting devices in the field of advanced topological quantum calculations and information technologies.Comment: 5 pages, 3 figure