High-performance Personal Computer Research Articles

High speed, high power 2D beam steering for mitigation of optomechanical parametric instability in gravitational wave detectors.

In this paper, we propose what we believe to be a novel strategy to control optomechanical parametric instability (PI) in gravitational wave (GW) detectors based on radiation pressure. The fast deflection of a high-power beam is the key element of our approach. We built a 2D deflection system based on a pair of acousto-optic modulators (AOMs) that combines high rapidity and a large scan range. As a fast frequency switching configurable AOM driver, we used a Universal Software Radio Peripheral (USRP) combined with a high-performance personal computer (PC). In this way, we demonstrate a 2D beam steering system with flat efficiency over the whole scan range and with a transition time of 50 ns between two arbitrary consecutive deflection positions for a beam power of 3.6 W.

Evaluation of underwater image enhancement algorithms based on Retinex and its implementation on embedded systems

The improvement of underwater imaging has advanced significantly due to its contribution to marine engineering and underwater exploration. This fact has been reflected in recent years with the proposal of numerous algorithms that improve the quality of underwater images. A benchmarking of three algorithms based on the Retinex models implemented on five high-performance embedded systems is presented herein. These algorithms are the Single Scale Retinex Model (SSR), Multi-Scale Retinex Model (MSR), and the Multi-Scale Retinex Model with Color Restoration (MSRCR). These algorithms perform the histogram equalization to distribute pixels, reduce the predominant color, perform color and contrast correction, and achieve an automatic white balance to improve illumination. This paper employs five edge devices such as Beagle Board, Odroid-XU4, Raspberry Pi 4, Jetson Nano, and Jetson TX2 to enhance underwater images and benchmark their performance. Four quality metrics without a reference image such as UIQM, UCIQUE, BRISQUE and Entropy are used to evaluate the quality of the enhanced underwater images. The MSRCR algorithm achieves the best quality results when it is implemented on Jetson TX2 embedded system. It has a difference of 0.46 s in the processing time of 147 × 196 pixels images concerning a high-performance personal computer (PC). Implementing these algorithms on embedded systems offers an excellent cost-benefit ratio versus a traditional PC, considering image quality metrics, precision, accuracy, energy consumption, price, lightweight, size, portability, and reliability. These findings hold great promise for unmanned and self-propelled underwater vehicles with artificial vision for exploration.

Assessing future landscapes using enhanced mixed reality with semantic segmentation by deep learning

Architecture, engineering, and construction projects need to be promoted in harmony with the natural environment and with the aim of preserving people’s living environment. At the planning and design stage, decision-makers and stakeholders share and assess landscape images during and after construction in order to avoid as much uncertainty as possible when performing environmental impact assessment. Given the lack of a standard visualization method for future landscapes that do not yet exist, mixed reality (MR), which overlays virtual content onto a real scene, has attracted attention in the field of landscape design. One challenge in MR is occlusion, which occurs when virtual objects obscure physical objects that should be rendered in the foreground. In MR-based landscape visualization, the distance between the MR camera and real objects located in front of the virtual objects might vary and might be large, causing difficulty for existing occlusion handling methods. In the process of landscape design, an evidence-based approach has also become important. Landscape index estimation using semantic segmentation by deep learning, which can recognize the surrounding environment, has been actively studied for landscape assessment. In this study, semantic segmentation by deep learning was integrated into an MR system to enable dynamic occlusion handling and landscape index estimation for both existing and designed landscape assessment. This system can be operated on a mobile device with video communication over the internet by connecting to real-time semantic segmentation on a high-performance personal computer. The applicability of the developed system is demonstrated through accuracy verification and case studies.

On the concept of the interactive information and simulation system for gas dynamics and multiphysics problems

This paper describes the general idea and the first implementation of the Interactive information and simulation system – an integrated environment that combines computational modules for modeling the aerodynamics and aerothermodynamics of re-entry space vehicles with the large collection of different information materials on this topic. The internal organization and the composition of the system are described and illustrated. Examples of the computational and information output are presented. The system has the unified implementation for Windows and Linux operation systems and can be deployed on any modern high-performance personal computer.

Genome-wide joint analysis of single-nucleotide variant sets and gene expression for hypertension and related phenotypes.

BackgroundWith the advance of next-generation sequencing technologies, the study of rare variants in targeted genome regions or even the whole genome becomes feasible. Nevertheless, the massive amount of sequencing data brings great computational and statistical challenges for association analyses. Aside from sequencing variants, other high-throughput omic data (eg, gene expression data) also become available, and can be incorporated into association analysis for better modeling and power improvement. This motivates the need of developing computationally efficient and powerful approaches to model the joint associations of multilevel omic data with complex human diseases.MethodsA similarity-based weighted U approach is used to model the joint effect of sequencing variants and gene expression. Using a Mexican American sample provided by Genetic Analysis Workshop 19 (GAW19), we performed a whole-genome joint association analysis of sequencing variants and gene expression with systolic (SBP) and diastolic blood pressure (DBP) and hypertension (HTN) phenotypes.ResultsThe whole-genome joint association analysis was completed in 80 min on a high-performance personal computer with an i7 4700 CPU and 8 GB memory. Although no gene reached statistical significance after adjusting for multiple testing, some top-ranked genes attained a high significance level and may have biological plausibility to hypertension-related phenotypes.ConclusionsThe weighted U approach is computationally efficient for high-dimensional data analysis, and is capable of integrating multiple levels of omic data into association analysis. Through a real data application, we demonstrate the potential benefit of using the new approach for joint association analysis of sequencing variants and gene expression.

A likelihood ratio-based Mann-Whitney approach finds novel replicable joint gene action for type 2 diabetes.

The potential importance of the joint action of genes, whether modeled with or without a statistical interaction term, has long been recognized. However, identifying such action has been a great challenge, especially when millions of genetic markers are involved. We propose a likelihood ratio-based Mann-Whitney test to search for joint gene action either among candidate genes or genome-wide. It extends the traditional univariate Mann-Whitney test to assess the joint association of genotypes at multiple loci with disease, allowing for high-order statistical interactions. Because only one overall significance test is conducted for the entire analysis, it avoids the issue of multiple testing. Moreover, the approach adopts a computationally efficient algorithm, making a genome-wide search feasible in a reasonable amount of time on a high performance personal computer. We evaluated the approach using both theoretical and real data. By applying the approach to 40 type 2 diabetes (T2D) susceptibility single-nucleotide polymorphisms (SNPs), we identified a four-locus model strongly associated with T2D in the Wellcome Trust (WT) study (permutation P-value < 0.001), and replicated the same finding in the Nurses' Health Study/Health Professionals Follow-Up Study (NHS/HPFS) (P-value = 3.03×10-11). We also conducted a genome-wide search on 385,598 SNPs in the WT study. The analysis took approximately 55 hr on a personal computer, identifying the same first two loci, but overall a different set of four SNPs, jointly associated with T2D (P-value = 1.29×10-5). The nominal significance of this same association reached 4.01×10-6 in the NHS/HPFS.

Partial discharge source discrimination using a support vector machine

Partial discharge (PD) measurements are an important tool for assessing the health of power equipment. Different sources of PD have different effects on the insulation performance of power apparatus. Therefore, discrimination between PD sources is of great interest to both system utilities and equipment manufacturers. This paper investigates the use of a wide bandwidth PD on-line measurement system consisting of a radio frequency current transducer (RFCT) sensor, a digital storage oscilloscope and a high performance personal computer to facilitate automatic PD source identification. Three artificial PD models were used to simulate typical PD sources which may exist within power system apparatus. Wavelet analysis was applied to pre-process measurement data obtained from the wide bandwidth PD sensor. This data was then processed using correlation analysis to cluster the discharges into different groups. A machine learning technique, namely the support vector machine (SVM) was then used to identify between the different PD sources. The SVM is trained to differentiate between the inherent features of each discharge source signal. Laboratory experiments where the trained SVM was tested using measurement data from the RFCT as opposed to conventional measurement data indicate that this approach has a robust performance and has great potential for use with field measurement data.

Hybrid Reactor Simulation of Boiling Water Reactor Power Oscillations

Hybrid reactor simulation (HRS) of boiling water reactor (BWR) instabilities, including in-phase and out-of-phase (OOP) oscillations, has been implemented on The Pennsylvania State University TRIGA reactor. The TRIGA reactor’s power response is used to simulate reactor neutron dynamics for in-phase oscillation or the fundamental mode of the reactor modal kinetics for OOP oscillations. The reactor power signal drives a real-time boiling channel simulation, and the calculated reactivity feedback is in turn fed into the TRIGA reactor via an experimental changeable reactivity device. The thermal-hydraulic dynamics, together with first harmonic mode power dynamics, is digitally simulated in the real-time environment. The real-time digital simulation of boiling channel thermal hydraulics is performed by solving constitutive equations for different regions in the channel and is realized by a high-performance personal computer. The nonlinearity of the thermal-hydraulic model ensures the capability to simulate the oscillation phenomena, limit cycle and OOP oscillation, in BWR nuclear power plants. By adjusting reactivity feedback gains for both modes, various oscillation combinations can be realized in the experiment. The dynamics of axially lumped power distribution over the core is displayed in three-dimensional graphs. The HRS reactor power response mimics the BWR core-wide power stability phenomena. In the OOP oscillation HRS, the combination of reactor response and the simulated first harmonic power using shaping functions mimics BWR regional power oscillations. With this HRS testbed, a monitoring and/or control system designed for BWR power oscillations can be experimentally tested and verified.

Statistical Thermodynamics as a Tool for Evaluating Atom Clustering around Interstitial Atom

In statistical thermodynamic analysis for condensed phase (either liquid or solid), atomistic (or microscopic) information of the condensed phase is derived from experimentally determined macroscopic equilibrium P-T-C (pressure-temperature-composition) relationships. This analysis procedure is especially adequate for non-stoichiometric compound containing at least one interstitial constituent. Atomistic information derived by statistical thermodynamics includes clustering pattern of metal atoms around an interstitial atom as well as pair-wise interaction among constituent atoms. Desired calculation in the statistical thermodynamic analysis is not very demanding and thence, compared with some other branches of computational materials science and engineering research, statistical thermodynamics requires only modest computational capacity of currently available advanced high-performance PC (personal computer). In this article, I would like to review aspects of atom clustering evaluation by statistical thermodynamics and also potentiality of statistical thermodynamics for predicting optimised material manufacturing condition.

Proper acquisition and handling of scanning electron microscopy images using a high‐performance personal computer

AbstractThe modern high‐performance personal computer (PC) has very recently expanded the range of utilization of digital scanning electron microscopy (SEM) images, and the PC will be used increasingly with SEMs. However, the image quality of digital SEM images may be considerably influenced by scanning and digitization conditions. In particular, the effects of the aliasing error peculiar to digital data are often serious in the low‐magnification acquisition (undersampling) of SEM images, and moreover even a high‐magnification image (oversampling) is disturbed by the undersampled noise (a sort of aliasing error). Furthermore, the signal‐to‐noise ratio of a digitized SEM image is closely related to the performance of the analog‐to‐digital converter. To prevent a flood of low‐quality digital images with artifacts by the aliasing and additional noise, we propose a method using very high‐density sampling (scanning). In addition, we will discuss how to handle digital SEM images from the point of view of the sampling and quantization.

An integrated computer system for Fudan nuclear microprobe

With the help of modern personal computer (PC) and object oriented programming (OOP) technology, we have recently developed a compact, integrated, user-friendly computer system for Fudan nuclear microprobe, which was originally modeled after the SUNY/Albany system. The system software has been thoroughly rewritten so as to take advantage of today's high-performance PC and facilitate easy upgrading and expansion in the case of future development of both hardware and software. Most functions of this system such as sample searching, scanning control, data acquisition, image processing and displaying, are based on a single 80386 IBM style PC with a 1-MB DRAM TVGA high-resolution monitor. Data from up to 4 ADCs, 4 sensors and a CCD camera can be acquired simultaneously. Two stepper motors are employed to move the target; a CCD camera system is also included to locate the area of interest on the sample; the secondary electron image could act as a reference to fine adjustment. Rectangular raster scanning or irregular scanning is facilitated with beam motion triggered either by a timer or by pulses from a current integrator. A variety of built-in image displaying, processing and printing methods have also been implemented in order to make the maps easier to interpret for the eyes. All of these functions are administrated by an integrated, completely menu-driven software package-MBSYS.

Real-Time Simulation of VLF Atmospheric Noise for Use in the Calibration and Characterization of LORAN-C Receivers for Aircraft Navigation

This paper describes a real-time simulation technique for generating realistic VLF band atmospheric noise. Noise in this band consists of a background Gaussian component plus a non-stationary impulsive component. The simulator implements as a real time simulation the theoretical model described in Feldman[1]. Stored channel simulation using a high performance personal computer (PC ) drives an off the shelf multi-channel signal generator, providing a high degree of sophistication at low cost. The simulator developed at the Volpe National Transportation Center has been used to characterize Loran-C receivers for use in aircraft navigation. Examples of use of the new simulator in the characteriza tion of Loran-C receivers are presented.

A blackboard-based robot position estimator

This papers presents a software architecture for robot position estimator. The architecture is targeted at applications characterized by multiple, low resolution and erroneous sensory inputs and variability in possible sensor configurations. This may be the case, e.g., with a house robot equipped, for cost reasons, with several inexpensive sensors. The architecture is based on two blackboards. Specialist knowledge sources, which embody signal interpretation and other expertise, cooperatively construct position estimation hypotheses on the domain blackboard. Scheduling knowledge sources opportunistically control the estimating activity based on the data recorded on the control blackboard. In their operation, knowledge sources refer to a database containing customized descriptions of the premises in which the robot works. A prototype position estimator has been implemented on a testbed consisting of a mobile robot with several low cost sensors (Health Hero-1) and a high performance personal computer (IBM PC XT). The prototype position estimator software was written in GCLISP, a subset of Common Lisp. Initial position estimation results are presented and discussed.

A structural view of the Cedar programming environment

This paper presents an overview of the Cedar programming environment, focusing on its overall structure—that is, the major components of Cedar and the way they are organized. Cedar supports the development of programs written in a single programming language, also called Cedar. Its primary purpose is to increase the productivity of programmers whose activities include experimental programming and the development of prototype software systems for a high-performance personal computer. The paper emphasizes the extent to which the Cedar language, with run-time support, has influenced the organization, flexibility, usefulness, and stability of the Cedar environment. It highlights the novel system features of Cedar, includingautomatic storage managementof dynamically allocated typed values, arun-time type systemthat provides run-time access to Cedar data type definitions and allows interpretive manipulation of typed values, and apowerful device-independent imaging modelthat supports the user interface facilities. Using these discussions to set the context, the paper addresses the language and system features and the methodologies used to facilitate the integration of Cedar applications. A comparison of Cedar with other programming environments further identifies areas where Cedar excels and areas where work remains to be done.

An Instruction Fetch Unit for a High-Performance Personal Computer

The instruction fetch unit (IFU) of the Dorado personal computer speeds up the emulation of instructions by prefetching, decoding, and preparing later instructions in parallel with the execution of earlier ones. It dispatches the machine's microcoded processor to the proper starting address for each instruction, and passes the instruction's fields to the processor on demand. A writeable decoding memory allows the IFU to be specialized to a particular instruction set, as long as the instructions are an integral number of bytes long. There are implementations of specialized instruction sets for the Mesa, Lisp, and Smalltalk languages. The IFU is implemented with a six-stage pipeline, and can decode an instruction every 60 ns. Under favorable conditions the Dorado can execute instructions at this peak rate (16 mips).

A retrospective on the Dorado, a high-performance personal computer

In late 1975, members of the Xerox Palo Alto Research Center embarked on the specification of a high-performance successor to the Alto personal minicomputer, in use since 1973. After four years, the resulting machine, called the Dorado, was in use within the research community at PARC. This paper begins with an overview of the design goals, architecture, and implementation of the Dorado and then provides a retrospective view and critique of the Dorado project as a whole. The major machine architectural features are evaluated, other project aspects such as design automation and management structures are explained, a chronological history with milestones is included, and a variety of accomplishments, red herrings, and shortfalls is discussed. The paper concludes with some speculations on what the project might have done differently and what might be done differently today instead of in the late 1970s. Although more than a dozen scientists and technicians contributed to the project, the evaluative and speculative parts of this paper are the sole responsibility of the author.

The Memory System of a High-Performance Personal Computer

The memory system of the Dorado, a compact high- performance personal computer, has very high I/O bandwidth, a large paged virtual memory, a cache, and heavily pipelined control; this paper discusses all of these in detail. Relatively low-speed I/O devices transfer single words to or from the cache; fast devices, such as a color video display, transfer directly to or from main storage while the processor uses the cache. Virtual addresses are used in the cache and for all I/O transfers. The memory is controlled by a seven-stage pipeline, which can deliver a peak main-storage bandwidth of 533 million bits/s to service fast I/O devices and cache misses. Interesting problems of synchronization and scheduling in this pipeline are discussed. The paper concludes with some performance measurements that show, among other things, that the cache hit rate is over 99 percent.