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

Effects of red and blue light ratio on the morphological traits and flower sex expression in Cucurbita moschata Duch.

Squash (Cucurbita moschata Duch.) is an important fruit vegetable that can be long-term transport and storage. Light-emitting diodes (LEDs) are commercially used light sources applied to improve the producing of leaf vegetables in plant factory. However, the influences of LEDs on the plant growth and flower development of fruit vegetables remain unknown. In this study, five effective light quality treatments, including white light, a 10:8 ratio of blue (B) to red (R) light, a 10:4 mixture of blue/red light, red light, and blue light, were used for growing squash and inducing female flowers to maximize production. Our results show that varying light quality influence morphological traits and flower appearance. Both blue and red light improved the development of first and second internodes and induced larger leaves and petiole lengths, whereas 10:4 mixture caused shorter plant heights and decreased internode and petiole lengths. Although 10:8 mixture treatment reduced chlorophyll content, this spectral regime increased leaf number and influenced flower sex development, inducing more female flowers and more fruits. Light quality manipulation thus beneficially influences the growth and flower sex proportion in squash plants. Squash plants under 10:8 mixture treatment exhibited increase in yield, and can be used as a supplementary light treatment in plant factory

Personalized Acoustic Modeling by Weakly Supervised Multi-Task Deep Learning using Acoustic Tokens Discovered from Unlabeled Data

It is well known that recognizers personalized to each user are much more effective than user-independent recognizers. With the popularity of smartphones today, although it is not difficult to collect a large set of audio data for each user, it is difficult to transcribe it. However, it is now possible to automatically discover acoustic tokens from unlabeled personal data in an unsupervised way. We therefore propose a multi-task deep learning framework called a phoneme-token deep neural network (PTDNN), jointly trained from unsupervised acoustic tokens discovered from unlabeled data and very limited transcribed data for personalized acoustic modeling. We term this scenario "weakly supervised". The underlying intuition is that the high degree of similarity between the HMM states of acoustic token models and phoneme models may help them learn from each other in this multi-task learning framework. Initial experiments performed over a personalized audio data set recorded from Facebook posts demonstrated that very good improvements can be achieved in both frame accuracy and word accuracy over popularly-considered baselines such as fDLR, speaker code and lightly supervised adaptation. This approach complements existing speaker adaptation approaches and can be used jointly with such techniques to yield improved results.Comment: 5 pages, 5 figures, published in IEEE ICASSP 201

Stationary Light Pulses in Cold Atomic Media

Stationary light pulses (SLPs), i.e., light pulses without motion, are formed via the retrieval of stored probe pulses with two counter-propagating coupling fields. We show that there exist non-negligible hybrid Raman excitations in media of cold atoms that prohibit the SLP formation. We experimentally demonstrate a method to suppress these Raman excitations and realize SLPs in laser-cooled atoms. Our work opens the way to SLP studies in cold as well as in stationary atoms and provides a new avenue to low-light-level nonlinear optics.Comment: 4 pages, 4 figure

Paging and Location Management in IEEE 802.16j Multihop Relay Network

IEEE 802.16j is an emerging wireless broadband networking standard that integrates infrastructure base stations with multihop relay technology. Based on the idle mode operation in IEEE 802.16j, we propose a novel location management and paging scheme. It integrates the paging area-based and the timer-based location update mechanism. In paging area-based scheme, an idle mode mobile station updates when it moves to a new paging area. In timer-based scheme, an idle mode MS updates when the location update timer expires. In this work, we formulate the mathematical model to evaluate the performance of the proposed paging scheme. A new random walk mobility model that is suitable for modeling in multihop relay network is created. Optimization of location update timer is also investigated