Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability and linear independence associated with scaling vectors

In this paper, we discuss stability and linear independence of the integer translates of a scaling vector $\Phi =(\phi_1,\ldots,\phi_r)^T$, which satisfies a matrix refinement equation $$\Phi(x)=\sum_{k=0}^n P_k\Phi(2x-k), $$ where $(P_k)$ is a finite matrix sequence. We call $P(z)=\frac{1}{2}\sum P_kz^k $ the symbol of $\Phi$. Stable scaling vectors often serve as generators of multiresolution analyses (MRAs) and therefore play an important role in the study of multiwavelets. Most useful MRA generators are also linearly independent.The purpose of this paper is to characterize stability and linear independence of the integer translates of a scaling vector via its symbol. A polynomial matrix P(z) is said to be two-scale similar to a polynomial matrix Q(z) if there is a polynomial matrix T(z) such that P(z)=T(z2 )Q(z)T-1 (z). This kind of factorization of P(z) is called two-scale factorization. We give a necessary and sufficient condition, in terms of two-scale factorization of the symbol, for stability and.
Flexibility of working memory encoding in a sentence–picture–sound verification task

Dual-process accounts of working memory have suggested distinct encoding processes for verbal and visual information in working memory, but encoding for nonspeech sounds (e.g., tones) is not well understood. This experiment modified the sentence–picture verification task to include nonspeech sounds with a complete factorial examination of all possible stimulus pairings. Participants studied simple stimuli–pictures, sentences, or sounds–and encoded the stimuli verbally, as visual images, or as auditory images. Participants then compared their encoded representations to verification stimuli–again pictures, sentences, or sounds–in a two-choice reaction time task. With some caveats, the encoding strategy appeared to be as important or more important than the external format of the initial stimulus in determining the speed of verification decisions. Findings suggested that: (1) auditory imagery may be distinct from verbal and visuospatial processing in working memory; (2) visual perception but not visual imagery may automatically activate concurrent verbal codes; and (3) the effects of hearing a sound may linger for some time despite recoding in working memory. We discuss the role of auditory imagery in dual-process theories of working memory.
Indiana University Computer Science Department an Introduction to Behavior Tables an Introduction to Behavior Tables

In this paper, we introduce behavior tables, an extension of register transfer tables, as a basis for system representation for reasoning about control, datapath, protocol, and data abstraction facets of system synthesis. The novelty in our approach is that it uni es di erent aspects of system synthesis and alleviates the need to change bases to reason about di erent facets of a design. Behavior tables can model indirection in system speci cation, by allowing names of registers and states to be treated as values. Behavior tables provide an environment for transformational design to derive a formally \correct" implementation from a speci cation. The emphasis of our work is on design correctness rather than design automation. Herein, we develop implementation relations over di erent facets of behavior tables. A set of transformations on the di erent facets of behavior tables, that preserve the implementation relations on the facets, are presented. Behavior tables and the transformations presented in this paper are based on a nite state machine model. Starting from a speci cation with symbolic data values, transformations are used by the designer to direct the design towards an implementation of interacting behavior tables with boolean data representation and appropriate control and datapath abstractions. To illustrate the use of behavior tables and some of the transformations, we use a behavior table description of the FM9001 processor. The resulting boolean level behavior tables can be synthesized using sequential logic synthesis tools. Research reported herein was supported, in part, by NSF: The National Science Foundation, under grants numbered MIP 89-21842 and MIP 92-08745.
Design of Resonant Inverters for Optimal Efficiency Over Lamp Life in Electronic Ballast With Phase Control

The paper presents the design guidelines of phase controlled resonant inverters to drive high intensity discharge lamps. Considering the variation of the lamp resistance over its lifetime, the resonant phase is determined and the condition of minimum phase lag is imposed to minimize the current through the circuit. The optimum input voltage is analyzed according to phase lag, frequency variation, and control complexity. A design procedure is presented and experimentally validated with results from two electronic ballast designs operating from 300-V and 400-V dc bus and driving a 150-W high pressure sodium lamp
Observer-Based Optimal Fault Detection and Diagnosis Using Conditional Probability Distributions

A new optimal fault detection and diagnosis (FDD) scheme is studied in this paper for the continuous-time stochastic dynamic systems with time delays, where the available information for the FDD is the input and the measured output probability density functions (pdf's) of the system. The square-root B-spline functional approximation technique is used to formulate the output pdf's with the dynamic weightings. As a result, the concerned FDD problem can be transformed into a robust FDD problem subjected to a continuous time uncertain nonlinear system with time delays. Feasible criteria to detect and diagnose the system fault are provided by using linear matrix inequality (LMI) techniques. In order to improve FDD performances, two optimization measures, namely guaranteed cost performance and Hinfin performance, are applied to optimize the observer design. Simulations are given to demonstrate the efficiency of the proposed approach
Relationships between movements of the lower limb joints and the pelvis in open and closed kinematic chains during a gait cycle

Abstract Lots of athletic skills performed during practice or competition are initiated by the legs, where athletes either walk or run prior to executing specific skills. Kinematic chains are used to describe the relationships between body segments and joints during movement. The aim of this study was to determine the relationships between movements of lower limb segments and the pelvis in open and closed kinematic chains while walking. The experimental group consisted of 32 males (age 23.3 ± 2.5 years, body mass 78.1 ± 8.7 kg, body height 182 ± 6 cm). For 3D analysis, an optoelectronic system Vicon MX (7 cameras, frequency 200 Hz) was used. Positioning of the segments was determined by the PlugInGait Model. Each participant executed five trials at speeds ranging from 1.38 to 1.52 m·s-1. The relationships between angle variables of the lower limbs and the pelvis in selected gait cycle phases were evaluated using STATISTICA software (version 10.0) and the Spearman correlation. The highest numbers of moderate and large correlations were found at opposite toe off, heel rise and initial contact for the sagittal and transversal planes in comparison to the frontal plane. The closed kinematic chain had a stronger impact on determining the movement pattern. The instructions or interventions focusing on closed kinematic chain alternation are more effective for changes in a movement pattern. The preferred limb initiates kinematics in the direction of propulsion, while the non-preferred limb in internal and external rotation.
An Intelligent Multicast Ad-hoc On demand Distance Vector Protocol for MANETs

Recently multicast ro uting protocols in Mobile Ad-hoc Networks (MANETs) are emerging for wireless group communication. This includes application such as multipoint data dissemination and multiparty conferencing which made the analytical design and development of the MANETs in a very efficient manner. For MANETs there are several multicast routing protocols are available, but they perform well under specific scenarios only. The topology of a MANET changes adequately based on the random mobility of network nodes, unlike the network topology of a wired network which is static. Multicast routing protocol outperforms the basic broadcast routing by sharing the resources along general links, while sending information to a set of predefined multiple destinations in a concurrent way. Due to the lack of redundancy in multipath and multicast structures, the multicast routing protocols are vulnerable to the component failure in ad-hoc networks. So it is the dire need to solve the problem optimally. One of the efficient techniques for solving the optimization problem is the Genetic Algorithm (GA). The key factors that determine the performance of GA is by the well designed architecture of chromosomes and operators in the intelligent algorithm. This paper proposes a new genetic algorithm based Multicast Ad-hoc On demand Distance Vector Protocol for MANETs (GA-MAODV), which improves the packet delivery ratio of the routing messages. The GAbased MAODV allows each node in the network to send out multicast data packets, and the multicast data packets are broadcast when propagating along the multicast group tree.
Informing development decisions: From data to information

Software engineers generate vast quantities of development artifacts such as source code, bug reports, test cases, usage logs, etc., as they create and maintain their projects. The information contained in these artifacts could provide valuable insights into the software quality and adoption, as well as development process. However, very little of it is available in the way that is immediately useful to various stakeholders. This research aims to extract and analyze data from software repositories to provide software practitioners with up-to-date and insightful information that can support informed decisions related to the business, management, design, or development of software systems. This data-centric decision-making is known as analytics. In particular, we demonstrate that by employing software development analytics, we can help developers make informed decisions around user adoption of a software project, code review process, as well as improve developers' awareness of their working context.
Strategic Security Resource Allocation for Internet of Things

In many Internet of Thing (IoT) application domains security is a critical requirement, because malicious parties can undermine the effectiveness of IoT-based systems by compromising single components and/or communication channels. Thus, a security infrastructure is needed to ensure the proper functioning of such systems even under attack. In this paper, we focus on the problem of efficiently and effectively securing IoT networks by carefully allocating security tools.
Use of Very High Level Languages and Program Generation by Management Professionals

The introduction of very high level languages (VHLL) and automatic program generation are expected to reduce significantly the needed programming skills and considerably increase software development productivity. The paper explores the hypothesis that the preferred mode of developing management systems will be for the management professional to directly specify, generate, and debug the needed software without involvement of professional programmers. The investigation is experimental, by having an accountant develop an accounting system, using the equational type MODEL VHLL and program generator, and by monitoring carefully the times that it takes to perform certain steps or debug certain types of errors. The investigation consisted of progressive development of an accounting system in three stages: first a general ledger, extended for inventory management, and concluding with a major modification to incorporate reporting for the effects of changing prices in accordance with Financial Accounting Standard 33 (FAS 33). In this way the work pattern in modifying and maintaining a system was investigated as well. The developer was an M.B.A. candidate majoring in accounting with a limited computer background who determined the requirements of the accounting system and used MODEL to generate the programs, along with their extensions and modifications. A description of the accounting system design is presented first. Next, a sample MODEL specification is discussed in order to communicate generally the style of specifying computations in MODEL. This sample is used also to demonstrate the incorporation of FAS 33.
THE SEGUE STELLAR PARAMETER PIPELINE. I. DESCRIPTION AND COMPARISON OF INDIVIDUAL METHODS

We describe the development and implementation of the Sloan Extension for Galactic Exploration and Understanding (SEGUE) Stellar Parameter Pipeline (SSPP). The SSPP is derived, using multiple techniques, radial velocities, and the fundamental stellar atmospheric parameters (effective temperature, surface gravity, and metallicity) for AFGK-type stars, based on medium-resolution spectroscopy and ugriz photometry obtained during the course of the original Sloan Digital Sky Survey (SDSS-I) and its Galactic extension (SDSS-II/SEGUE). The SSPP also provides spectral classification for a much wider range of stars, including stars with temperatures outside the window where atmospheric parameters can be estimated with the current approaches. This is Paper I in a series of papers on the SSPP; it provides an overview of the SSPP, and tests of its performance using several external data sets. Random and systematic errors are critically examined for the current version of the SSPP, which has been used for the sixth public data release of the SDSS (DR-6).
Isocube: Exploiting the Cubemap Hardware

This paper proposes a novel six-face spherical map, isocube, that fully utilizes the cubemap hardware built in most GPUs. Unlike the cubemap, the proposed isocube uniformly samples the unit sphere (uniformly distributed), and all samples span the same solid angle (equally important). Its mapping computation contains only a small overhead. By feeding the cubemap hardware with the six-face isocube map, the isocube can exploit all built-in texturing operators tailored for the cubemap and achieve a very high frame rate. In addition, we develop an anisotropic filtering that compensates aliasing artifacts due to texture magnification. This filtering technique extends the existing hardware anisotropic filtering and can be applied not only to the proposed isocube, but also to other texture mapping applications.
Diabetes Diminishes the Portal-Systemic Collateral Vascular Response to Vasopressin via Vasopressin Receptor and Gα Proteins Regulations in Cirrhotic Rats

Liver cirrhosis may lead to portal-systemic collateral formation and bleeding. The hemostatic effect is influenced by the response of collateral vessels to vasoconstrictors. Diabetes and glucose also influence vasoresponsiveness, but their net effect on collaterals remains unexplored. This study investigated the impact of diabetes or glucose application on portal-systemic collateral vasoresponsiveness to arginine vasopressin (AVP) in cirrhosis. Spraque-Dawley rats with bile duct ligation (BDL)-induced cirrhosis received vehicle (citrate buffer) or streptozotocin (diabetic, BDL/STZ). The in situ collateral perfusion was done after hemodynamic measurements: Both were perfused with Krebs solution, D-glucose, or D-glucose and NaF, with additional OPC-31260 for the BDL/STZ group. Splenorenal shunt vasopressin receptors and Gα proteins mRNA expressions were evaluated. The survival rate of cirrhotic rats was decreased by STZ injection. The collateral perfusion pressure changes to AVP were lower in STZ-injected groups, which were reversed by OPC-31260 (a V2R antagonist) and overcome by NaF (a G protein activator). The splenorenal shunt V2R mRNA expression was increased while Gα proteins mRNA expressions were decreased in BDL/STZ rats compared to BDL rats. The Gαq and Gα11 mRNA expressions also correlated with the maximal perfusion pressure changes to AVP. Diabetes diminished the portal-systemic collateral vascular response to AVP in rats with BDL-induced cirrhosis, probably via V2 receptor up-regulation and Gα proteins down-regulation.
A Branch and Bound Method for Fault Isolation through Missing Variable Analysis

Fault detection and diagnosis (FDD) is a critical approach to ensure safe and efficient operation of manufacturing and chemical processing plants. Multivariate statistical process monitoring (MSPM) has received considerable attention for FDD since it does not require a mechanistic process model. The diagnosis of the source or cause of the detected process fault in MSPM largely relies on contribution analysis, which is ineffective in identifying the joint contribution of multiple variables to the occurrence of fault. In this work, a missing variable analysis approach based on probabilistic principal component analysis is proposed for fault isolation. Furthermore, a branch and bound method is developed to handle the combinatorial nature of the problem involving finding the variables, which are most likely responsible for the occurrence of fault. The efficiency of the method proposed is shown through a case study on the Tennessee Eastman process.
Improving 3D medical image registration CUDA software with genetic programming

Genetic Improvement (GI) is shown to optimise, in some cases by more than 35percent, a critical component of healthcare industry software across a diverse range of six nVidia graphics processing units (GPUs). GP and other search based software engineering techniques can automatically optimise the current rate limiting CUDA parallel function in the NiftyReg open source C++ project used to align or register high resolution nuclear magnetic resonance NMRI and other diagnostic NIfTI images. Future Neurosurgery techniques will require hardware acceleration, such as GPGPU, to enable real time comparison of three dimensional in theatre images with earlier patient images and reference data. With millimetre resolution brain scan measurements comprising more than ten million voxels the modified kernel can process in excess of 3 billion active voxels per second.
Design and develop an OpenFlow Testbed within virtualized architecture

Virtualization has brought the revolution of utilizing computing elements, and also incurred the trends of cloud computing with distributed data centers built for enterprises. Recently, the network virtualization has become an issue for decreasing the cost and adding the flexibility of networking inside either the service platform or the infrastructure. Hence, research and education demands for testing new ideas about Software Defined Network in testbed have become more and more popular. This paper proposes a time- and resource-shared network testbed which integrates with Emulab system, Xen hypervisor and OpenFlow. This OpenFlow Testbed aims to provide an isolated, clean, quick-built and independent environment for each user to emulate OpenFlow networks. The implementation also has been verified with real use cases which are tutorials of courses in college. Users can build OpenFlow environment upon the shared and virtual infrastructure for network research and education purposes. Results also revealed that not only this network emulation testbed meets most requirements that real machine environment could provide, but also acquires benefits from virtualization.
Radial Age and Metal Abundance Gradients in the Stellar Content of M32

We present long-slit spectroscopy of the elliptical galaxy M32, obtained with the 8 m Subaru telescope at Mauna Kea, the 1.5 m Tillinghast telescope at the F. L. Whipple Observatory, and the 4 m Mayall telescope at the Kitt Peak National Observatory. The spectra cover the Lick index red spectral region, as well as higher order Balmer lines in the blue. Spectra have been taken with the slit offset from the nucleus to avoid scattered-light contamination from the bright nucleus of M32. An analysis of numerous absorption features, particularly involving the Hγ and Hβ Balmer lines, reveals that systematic radial trends are evident in the integrated spectrum of M32. Population synthesis models indicate a radial change in both the age and chemical composition of the light-weighted mean stellar population in M32, from the nucleus out to 33″, i.e., an approximately 1.0 effective radius, Re. Specifically, the light-weighted mean stellar population at 1Re is older by ∼3 Gyr and more metal-poor by about -0.25 dex in [Fe/H] than the central value of ∼4 Gyr and [Fe/H] ∼ 0.0. We show that this apparent population trend cannot be attributed to a varying contribution from either hot stars or emission-line contamination. The increase in age and decrease in metal abundance with radius are sufficiently well matched to explain the flat radial color profiles previously observed in M32. In addition, the ratio of Mg to Fe abundance, [Mg/Fe], increases from about -0.25 in the nucleus to about -0.08 at 1Re. Finally, we find spuriously pronounced line-strength gradients in the Mayall data that are an artifact of scattered light from the bright nucleus. Scattered-light issues may explain the lack of consistency among previously published studies of radial line strength gradients in M32.
Recent Developments in Using Advanced Sequencing Technologies for the Genomic Studies of Lignin and Cellulose Degrading Microorganisms

Lignin is a complex polyphenyl aromatic compound which exists in tight associations with cellulose and hemicellulose to form plant primary and secondary cell wall. Lignocellulose is an abundant renewable biomaterial present on the earth. It has gained much attention in the scientific community in recent years because of its potential applications in bio-based industries. Microbial degradation of lignocellulose polymers was well studied in wood decaying fungi. Based on the plant materials they degrade these fungi were classified as white rot, brown rot and soft rot. However, some groups of bacteria belonging to the actinomycetes, α-proteobacteria and β-proteobacteria were also found to be efficient in degrading lignocellulosic biomass but not well understood unlike the fungi. In this review we focus on recent advancements deployed for finding and understanding the lignocellulose degradation by microorganisms. Conventional molecular methods like sequencing 16s rRNA and Inter Transcribed Spacer (ITS) regions were used for identification and classification of microbes. Recent progression in genomics mainly next generation sequencing technologies made the whole genome sequencing of microbes possible in a great ease. The whole genome sequence studies reveals high quality information about genes and canonical pathways involved in the lignin and other cell wall components degradation.