MATEX: A Distributed Framework for Transient Simulation of Power Distribution Networks

We proposed MATEX, a distributed framework for transient simulation of power distribution networks (PDNs). MATEX utilizes matrix exponential kernel with Krylov subspace approximations to solve differential equations of linear circuit. First, the whole simulation task is divided into subtasks based on decompositions of current sources, in order to reduce the computational overheads. Then these subtasks are distributed to different computing nodes and processed in parallel. Within each node, after the matrix factorization at the beginning of simulation, the adaptive time stepping solver is performed without extra matrix re-factorizations. MATEX overcomes the stiff-ness hinder of previous matrix exponential-based circuit simulator by rational Krylov subspace method, which leads to larger step sizes with smaller dimensions of Krylov subspace bases and highly accelerates the whole computation. MATEX outperforms both traditional fixed and adaptive time stepping methods, e.g., achieving around 13X over the trapezoidal framework with fixed time step for the IBM power grid benchmarks.Comment: ACM/IEEE DAC 2014. arXiv admin note: substantial text overlap with arXiv:1505.0669

Properties of the Molecular Cores of Low Luminosity Objects

We present a survey toward 16 Low Luminosity Objects (LLOs with an internal luminosity, Lint, lower than 0.2 Lsun) with N2H+ (1-0), N2H+ (3-2), N2D+ (3-2), HCO+ (3-2) and HCN (3-2) using the Arizona Radio Observatory Kitt Peak 12m Telescope and Submillimeter Telescope. Our goal is to probe the nature of these faint protostars which are believed to be either very low mass or extremely young protostars. We find that the N2D+/N2H+ column density ratios of LLOs are similar to those of typical starless cores and Class 0 objects. The N2D+/N2H+ column density ratios are relatively high (> 0.05) for LLOs with kinetic temperatures less than 10 K in our sample. The distribution of N2H+ (1-0) line widths spreads between that of starless cores and young Class 0 objects. If we use the line width as a dynamic evolutionary indicator, LLOs are likely young Class 0 protostellar sources. We further use the optically thick tracers, HCO+ (3-2) and HCN (3-2), to probe the infall signatures of our targets. We derive the asymmetry parameters from both lines and estimate the infall velocities by fitting the HCO+ (3-2) spectra with two-layer models. As a result, we identify eight infall candidates based on the infall velocities and seven candidates have infall signatures supported by asymmetry parameters from at least one of HCO+ (3-2) and HCN (3-2).Comment: 15 pages, 8 figures, accepted to Ap

Virtualizing Smartphone Applications to the Cloud

Smartphone technologies have enabled sophisticated pervasive applications for mobile users. Still, many intensive applications perform poorly on smartphones due to the shortage of resources for computation, data storage, network bandwidth, and battery capacity. While such applications can be re-designed with client-server models to benefit from subscribed cloud services, the users are no longer in full control of the entire application execution, which has raised a serious concern. Meanwhile, privacy and security are also important issues, and it is an ongoing debate if public cloud services could be trusted with sensitive data. For mobile users to take full advantage of cloud services, these issues need to be resolved. In this paper, we propose an innovative framework for mobile users to execute existing Android applications on a personal virtual phone safely in the cloud. Instead of using a client-server model, the entire virtual phone is mostly controlled by the user to minimize the intervention from the service provider. Virtualization and encryption are employed to protect against eavesdropping from cloud providers and network attackers. To quickly migrate an Android application between the physical phone and the virtual phone, we use a new application-level checkpointing mechanism and minimize the state of the application

Task Scheduling for Context Minimization in Dynamically Reconfigurable Platforms

Abstract. Dynamically reconfigurable hardware provides useful means to reduce the time-to-prototype and even the time-to-market in product designs. It also offers a good alternative in reconfiguring hardware logics to optimize the system performance. This paper targets an essential issue in reconfigurable computing, i.e., the minimization of configuration contexts. We explore different constraints on the CONTEXT MINIMIZATION problem. When the resulting subproblems are polynomial-time solvable, optimal algorithms are presented

Effects of Bi3+ Ion-Doped on the Microstructure and Photoluminescence of La0.97Pr0.03VO4 Phosphor

The objective of this paper is to enhance the emission intensity of La0.97Pr0.03VO4 single-phased white light emitting phosphor. The Bi3+ ion-doped La0.97Pr0.03VO4 single-phased white light emitting phosphors are synthesized using a sol-gel method. The structure and photoluminescence properties of (La0.97-yBiy)Pr0.03VO4 (y = 0-0.05) phosphor are also examined. The XRD results show that the structure of La0.97Pr0.03VO4 phosphors with different concentrations of Bi3+ ion doping keeps the monoclinic structure. The SEM results show that the phosphor particles become smoother when the Bi3+ ion is doped. The excitation band for La0.97Pr0.03VO4 phosphor exhibits a blue shift from 320 nm to 308 nm as the Bi3+ ion contents are increased. The maximum emission intensity is achieved for a Bi3+ ion content of 0.5 mol%, which is about 30% greater than that with no Bi3+ ion doped. The CIE chromaticity coordinates are all located in the near white light region for different Bi3+ ion-doped La0.97Pr0.03VO4 phosphors

Benthic Fluxes of Dissolved Organic Carbon from Gas Hydrate Sediments in the Northern South China Sea

Hydrocarbon vents have recently been reported to contribute considerable amounts of dissolved organic carbon (DOC) to the oceans. Many such hydrocarbon vents widely exist in the northern South China Sea (NSCS). To investigate if these hydrocarbon vent sites release DOC, we used a real-time video multiple-corer to collect bottom seawater and surface sediments at vent sites. We analyzed concentrations of DOC in these samples and estimated DOC fluxes. Elevated DOC concentrations in the porewaters were found at some sites suggesting that DOC may come from these hydrocarbon vents. Benthic fluxes of DOC from these sediments were 28 to 1264 µmol m−2 d−1 (on average ~321 µmol m−2 d−1 which are several times higher than most DOC fluxes in coastal and continental margin sediments. The results demonstrate that the real-time video multiple-corer can precisely collect samples at vent sites. The estimated benthic DOC flux from the methane venting sites (8.6 x 106 mol y-1, is 24% of the DOC discharge from the Pearl River to the South China Sea, indicating that these sediments make an important contribution to the DOC in deep waters

Technical aspects of single-port thoracoscopic surgery for lobectomy

Thoracoscopic Surgery is in common use in routine surgical practice. With the advancement of the various techniques and instruments required, mini wounds and fewer thoracoports become practical in recent years. Here, we report our experience of performing lobectomy with radical lymph node dissection in 3 patients using regular straight endoscopic instruments. We demonstrate the feasibility of such techniques and discuss the key points of effectively performing the procedures. Because of the favorable outcomes, we encourage such procedures to be widely applied in surgical operations of various types

Artificial Intelligence and Visual Analytics: A Deep-Learning Approach to Analyze Hotel Reviews & Responses

With a growing number of online reviews, consumers often rely on these reviews to make purchase decisions. However, little is known about managerial responses to online hotel reviews. This paper reports on a framework to integrate visual analytics and machine learning techniques to investigate whether hotel managers respond to positive and negative reviews differently and how to use a deep-learning approach to prioritize responses. In this study, forty 4- and 5-star hotels in London with 91,051 reviews and 70,397 responses were collected and analyzed. Visual analyses and machine learning were conducted. The results indicate most hotels (72.5%) showing no preference to respond to positive and negative reviews. Our proposed deep-learning approach outperformed existing algorithms to prioritize responses