High-transfer-rate high-capacity holographic disk data-storage system

We describe the design and implementation of a high-data-rate high-capacity digital holographic storage disk system. Various system design trade-offs that affect density and data-rate performance are described and analyzed. In the demonstration system that we describe, high-density holographic recording is achieved by use of high-resolution short-focal-length optics and correlation shift multiplexing in photopolymer disk media. Holographic channel decoding at a 1-Gbit/s data rate is performed by custom-built electronic hardware. A benchmark sustained optical data-transfer rate of 10 Gbits/s has been successfully demonstrated.     

Complexation of copper by zwitterionic aminosulfonic (good) buffers

Copper binding properties were investigated for several popular zwitterionic buffers. The two buffers 4-morpholinoethanesulfonic acid (MES) and 3-N-morpholinopropanesulfonic acid (MOPS) did not bind copper and would be good choices for metal speciation studies within their operational pH range. Conversely, 3-(N-morpholino)-2-hydroxypropanesulfonic acid (MOPSO) was observed to weakly bind copper directly (log Kc 2.02). Moreover, strong copper binding was observed for 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), 4-(2-hydroxyethyl)piperazine-1-propanesulfonic acid (HEPPS), and N-(2-hydroxyethyl)piperazine-N'-(2-hydroxypropanesulfonic acid) (HEPPSO). Log Kc values range from 7.04 to 7.68 and are indicative of strong copper binding ligands. The latter buffer also exhibited weak binding characteristics with a log Kc of 2.05. The strong Cu binding ligands were present in HEPES, HEPPS, and HEPPSO at much lower concentrations than the total buffer concentration. MES, HEPES, MOPSO, and HEPPSO were analyzed by electrospray-ionization quadrapole time-of-flight mass spectroscopy. The most prominent feature of the spectra for each buffer analyzed was the presence of multiple oligomers, indicating a propensity of interaction between buffer molecules. In addition, the presence of several contaminants was identified in the mass spectrum of the HEPES matrix, including a prominent contaminant (at m/z 131) present in levels similar to those obtained from the modeling of the copper titration data. Other contaminants were found in the other matrixes but were not identified as possible copper binding agents.     

Neural network approach to background modeling for video object segmentation.

This paper presents a novel background modeling and subtraction approach for video object segmentation. A neural network (NN) architecture is proposed to form an unsupervised Bayesian classifier for this application domain. The constructed classifier efficiently handles the segmentation in natural-scene sequences with complex background motion and changes in illumination. The weights of the proposed NN serve as a model of the background and are temporally updated to reflect the observed statistics of background. The segmentation performance of the proposed NN is qualitatively and quantitatively examined and compared to two extant probabilistic object segmentation algorithms, based on a previously published test pool containing diverse surveillance-related sequences. The proposed algorithm is parallelized on a subpixel level and designed to enable efficient hardware implementation.     

Efficient asynchronous executions of AMR computations and visualization on a GPU system

Adaptive Mesh Refinement is a method which dynamically varies the spatio-temporal resolution of localized mesh regions in numerical simulations, based on the strength of the solution features. In-situ visualization plays an important role for analyzing the time evolving characteristics of the domain structures. Continuous visualization of the output data for various timesteps results in a better study of the underlying domain and the model used for simulating the domain. In this paper, we develop strategies for continuous online visualization of time evolving data for AMR applications executed on GPUs. We reorder the meshes for computations on the GPU based on the users input related to the subdomain that he wants to visualize. This makes the data available for visualization at a faster rate. We then perform asynchronous executions of the visualization steps and fix-up operations on the CPUs while the GPU advances the solution. By performing experiments on Tesla S1070 and Fermi C2070 clusters, we found that our strategies result in 60% improvement in response time and 16% improvement in the rate of visualization of frames over the existing strategy of performing fix-ups and visualization at the end of the timesteps.     

Nucleic Acid Nanostructures for Chemical and Biological Sensing

The nanoscale features of DNA have made it a useful molecule for bottom‐up construction of nanomaterials, for example, two‐ and three‐dimensional lattices, nanomachines, and nanodevices. One of the emerging applications of such DNA‐based nanostructures is in chemical and biological sensing, where they have proven to be cost‐effective, sensitive and have shown promise as point‐of‐care diagnostic tools. DNA is an ideal molecule for sensing not only because of its specificity but also because it is robust and can function under a broad range of biologically relevant temperatures and conditions. DNA nanostructure‐based sensors provide biocompatibility and highly specific detection based on the molecular recognition properties of DNA. They can be used for the detection of single nucleotide polymorphism and to sense pH both in solution and in cells. They have also been used to detect clinically relevant tumor biomarkers. In this review, recent advances in DNA‐based biosensors for pH, nucleic acids, tumor biomarkers and cancer cell detection are introduced. Some challenges that lie ahead for such biosensors to effectively compete with established technologies are also discussed.     

High Performance MPI over the Slingshot Interconnect

Journal of Computer Science and Technology - The Slingshot interconnect designed by HPE/Cray is becoming more relevant in high-performance computing with its deployment on the upcoming exascale...     

Effect of Density and Processing Conditions on Oxide Transformations and Mechanical Properties in Cr–Mo-Alloyed PM steels

To improve the mechanical properties and performances of water-atomized powder metallurgy steels, it is necessary to enhance the density. Consolidating water-atomized steel powders via conventional pressing and sintering to a relative density level > 95 pct involves processing challenges. Consolidation of gas-atomized powders to full density by hot isostatic pressing (HIP) is an established process route but utilizing water-atomized powders in HIP involves challenges that result in the formation of prior particle boundaries due to higher oxygen content. In this study, the effect of density and processing conditions on the oxide transformations and mechanical properties from conventional press and sintering, and HIP are evaluated. Hence, water-atomized Cr–Mo-alloyed powder is used and consolidated into different density levels between 6.8 and 7.3 g cm⁻³ by conventional die pressing and sintering. Fully dense material produced through HIP is evaluated not only of mechanical properties but also for microstructural and fractographic analysis. An empirical model based on power law is fitted to the sintered material properties to estimate and predict the properties up to full density at different sintering conditions. A model describing the mechanism of oxide transformation during sintering and HIP is proposed. The challenges when it comes to the HIP of water-atomized powder are addressed and the requirements for successful HIP processing are discussed.

     

Multi-radio diversity in wireless networks

This paper describes the Multi-Radio Diversity (MRD) wireless system, which uses path diversity to improve loss resilience in wireless local area networks (WLANs). MRD coordinates wireless receptions among multiple radios to improve loss resilience in the face of path-dependent frame corruption over the radio. MRD incorporates two techniques to recover from bit errors and lower the loss rates observed by higher layers, without consuming much extra bandwidth. The first technique is frame combining, in which multiple, possibly erroneous, copies of a given frame are combined together in an attempt to recover the frame without retransmission. The second technique is a low-overhead retransmission scheme called request-for-acknowledgment (RFA), which operates above the link layer and below the network layer to attempt to recover from frame combining failures. We present an analysis that determines how the parameters for these algorithms should be chosen. We have designed and implemented MRD as a fully functional WLAN infrastructure based on 802.11a. We evaluate the MRD system under several different physical configurations, using both UDP and TCP, and measured throughput gains up to 3× over single radio communication schemes employing 802.11’s autorate adaptation scheme. Computer and Communication Sciences, EPFL, Switzerland. Allen Miu received his Ph.D. degree at the Massachusetts Institute of Technology in 2006 and is currently a wireless systems architect at Ruckus Wireless, Inc. He received his S.M. in Computer Science from MIT and a B.Sc. with highest honors in Electrical Engineering and Computer Science from the University of California at Berkeley. He previously worked on the Cricket Indoor Location System and was a research intern at Microsoft Research, Redmond in 2000 and Hewlett-Packard Laboratories, Palo Alto in 2002. His research interests include wireless networks, location systems, mobile computing, and embedded systems. Hari Balakrishnan is an Associate Professor in the EECS Department and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. His research interests is in the area of networked computer systems. In addition to many widely cited papers, several systems developed as part of his research are available in the public domain. He received a Ph.D. in Computer Science from the University of California at Berkeley in 1998 and a B.Tech. from the Indian Institute of Technology (Madras) in 1993. His honors include an Alfred P. Sloan Research Fellowship (2002), an NSF CAREER Award (2000), the ACM doctoral dissertation award for his work on reliable data transport over wireless networks (1998), and seven award-winning papers at various top conferences and journals, including the IEEE Communication Society’s William R. Bennett Prize (2004). He has also received awards for excellence in teaching and research at MIT (Spira, Junior Bose, and Harold Edgerton faculty achievement awards). C. Emre Koksal received his B.S. degree in Electrical Engineering from the Middle East Technical University, Ankara in 1996. He received his S.M. and Ph.D. degrees from MIT in Electrical Engineering and Computer Science in 1998 and 2002 respectively. He was a postdoctoral fellow in the Networks and Mobile Systems Group in the Computer Science and Artificial Intelligence Laboratory at MIT until 2003. Since then he has been a senior researcher jointly in the Laboratory for Computer Communications and the Laboratory for Information Theory at EPFL, Switzerland. His general areas of interest are wireless communications, computer networks, information theory, stochastic processes and financial economics. He also has a certificate on Financial Technology from the Sloan School of Management at MIT.     

Associative Zone Based Energy Balancing Routing for Expanding Energy Efficient and Routing Optimization Over the Sensor Network

Wireless Personal Communications - A channel prediction scheme with channel matrix doubling and temporal-spatial smoothing is proposed. With the assumption that the underlying channel model...