Automatic Performance Research Articles

A perfSONAR-Based Network Performance Weathermap System

The deployment of an automatic network performance measurement system is crucial to the early detection and analysis of network quality degradations and failures. Once the overall network health status can be summarized and visualized in an easily accessible graphic user interface, the difficulty of network maintenance and troubleshooting can be significantly reduced. This study provided a detailed introduction to how the perfSONAR is implemented in TWAREN backbone and how the individual data are integrated and eventually visualized as a handy weathermap for network operators to use.

보조 동력 장치 성능시험기 개발 및 측정 시스템 분석

Purpose: In this study, an automatic performance tester (APT) was developed for an auxiliary power unit (APU) applied to self-propelled artillery, and the precision and stability of the APT were evaluated using measurement system analysis (MSA).<BR>Methods: The APT was developed as a package system comprising indicators, control devices, and a remote-control panel. Gage R&R analysis was conducted on the measurements of the rated voltage, output current, engine revolutions, and recovery time. In addition, to calibrate the APT, the data from the APT were compared with those from general-purpose measurement devices. <BR>Results: The percentage R&R values of the rated voltage, engine speed, and recovery time were less than 10 (i.e., acceptable) and that of the output current was 14.34 (i.e., conditionally acceptable). The differences in the measured values between the APT and general-purpose measurement devices were within 10% of the tolerance, so the APT calibration was considered to be acceptable.<BR>Conclusion: The results of this study are expected to provide some preliminary data for the development of APT measurement standards for self-propelled artillery APUs with defense-quality standards.

Airborne Laser Communication System with Automated Tracking

The acquisition, alignment, and tracking system is an important part of airborne laser communication and is the prerequisite and guarantee for the normal communication link. In order to solve the problem of automatic tracking of laser communication links in the airborne environment, the rapid capture, alignment, and tracking of beams between terminals are realized. This article proposes a stepping motor as a control servo system and a four-quadrant detector as an automatic tracking method for the detection unit. The pulse width modulation signal controls the rotation speed of the stepping motor and combines the position distribution of the light spot on the four-quadrant detector to achieve high-precision beam tracking. On this basis, indoor simulation experiments are carried out. After many experiments, the tracking accuracy is better than 2.5 μrad, which shows that the system can be applied to airborne laser communication, and it is verified that this method has good automatic tracking performance for airborne laser communication.

PID Controllers with a Constant Speed Actuator: Implementation Versions and Self-Tuning of Pulse Duration

The article considers three implementation versions of controllers operating with constant speed actuators that are used in automation systems of a technological process: with a relay-pulse control unit (RPCU) with a lagging feedback and topping differentiator (a real differentiating element, RD), with calculating the output according to a PID algorithm and using the actuator model for its implementation, and with calculating the control output speed and using a pulse-width modulator. Formulas for calculating the parameters of the RPCU and RD primary components from the condition of approaching the equivalent PID algorithm are given. The system version with a PID controller with the actuator control proceeding from its model is considered in two options: with individual integrators for the controller’s integral component and the actuator model, and with a common integrator for the controller’s integral component and the actuator model. In the latter option, the signal from the actuator model is subtracted from the controller’s integral component, due to which the possibility of the integrator’s output to reach the integral component’s limit values is ruled out. The versions are compared by analyzing the automatic control system performance in the pulsed actuator’s operation mode based on simulation for the superheated steam temperature control section of a steam boiler equipped with a surface steam desuperheater. The analysis was carried out taking into account both the usual dynamic accuracy indicators and the number of actuators switched into operation during the transient. It is shown that the advantage of the version with the PID algorithm and common integrator for the integral component and the actuator model is that there is no need in this case to calculate the controlled variable second derivative; in addition, this version is free from the problem connected with accumulation of the difference between the signals from the actuator and its model. This version can be considered to be more preferred in implementing a PID algorithm in the software of programmed controllers. Recommendations for self-tuning of pulse duration and the control unit relay element parameters during the control process depending on the algorithm’s individual components are given. By using the proposed recommendations, it becomes possible to achieve an essentially lower actuator switching frequency during the control process.

Multisphere Representation of Convex Polyhedral Particles for DEM Simulation

The representation of particles of complex shapes is one of the key challenges of numerical simulations based on the discrete element method (DEM). A novel algorithm has been developed by the authors to accurately represent 2D arbitrary particles for DEM modelling. In this paper, the algorithm is extended from 2D to 3D to model convex polyhedral particles based on multisphere methods, which includes three steps: the placement of spheres at the corners, along the edges, and on the facets in sequence. To give a good representation of a polyhedral particle, the spheres are placed tangent to the particle surface in each step. All spheres placed in the three steps are clumped together into a clump in DEM. In addition, the mass properties of the clump are determined based on the corresponding polyhedral particle to obtain accurate simulation results. Finally, an example is used to validate the robust and automatic performance of the algorithm in generating a sphere clump model for an assembly of polyhedral particles. A current FORTRAN version of the algorithm is available by contacting the authors.

Performance Degradation Monitoring and Recovery of Vision-Based Control Systems

As an emerging need in vision-based control that is been intensively deployed in various applications, a systematic way of automatic performance recovery after system maintenance/control performance degradation is highly desired. On the one hand, vision-based control is an interdisciplinary field and the control performance of vision-based control systems is affected by not only uncertain environmental conditions but also the image processing latency, as well as the coordination of control and image processing algorithms. On the other hand, integration of image processing, control, and performance degradation recovery remains an open problem. In light of these observations, this brief deals with performance degradation monitoring and recovery with respect to the aforementioned factors. We first introduce a performance indicator by postfiltering the residual signal with the stable image representation of the feedback controller. It reveals a new interpretation of performance degradation recovery in the input- and output-recovery context. From this perspective, a real-time performance recovery approach is presented to enhance system performance over the lifetime. In the end, a vision-based inverted pendulum control system is implemented to verify the effectiveness of the proposed approach.

Energy and performance improvements in stencil computations on multi-node HPC systems with different network and communication topologies

Energy and performance improvements in stencil computations are relevant for both application developers and data center administrators. They appear as the fundamental scheme in many large-scale scientific simulations and workloads. Many research efforts have focused on some estimation techniques of the energy usage of HPC systems based on specific characteristics of parallel applications. In case of stencils, we have previously concentrated on detailed estimations of energy consumption and the energy-aware distribution of stencil computations on heterogeneous processors. However, we have restricted our comprehensive studies to a single heterogeneous computing node only. In this paper, we show how scheduling and optimization techniques can be applied for energy and performance improvements of stencil computations on multi-node HPC systems using different network topologies. We formulate a scheduling model together with a new Tabu Search algorithm, called Task Movement (TM), taking into account the communication hierarchies, to minimize the overall energy usage and the execution time of stencil computations. Experimental studies show that this algorithm solves the considered problem more efficiently comparing to other, simpler heuristics. We present computational experiments for a reference 7 point stencil computation pattern on three commonly used low-diameter network topologies: Fat-tree, Dragonfly, and Torus. According to our studies, the most promising multi-node HPC architecture for stencil computations is based on the Torus network concept. Finally, we argue that the proposed scheduling model and TM algorithm can be easily adopted within existing high-level parallel execution environments for stencils automatic performance tuning.

Modeling and analysis of ionospheric parameters based on multicomponent model

The results of modeling and analysis of ionospheric parameters during disturbed geomagnetic field are presented. Hourly and 15-min data of the ionospheric critical frequency (foF2) at Paratunka site (Kamchatka, Russia, 53.0 N and 158.7 E) for the period 1968–2019 were applied. The modeling was based on ionospheric parameter multicomponent model developed by the authors. In order to refine model parameters, three classes of anomalies were introduced. They characterize strong, moderate and weak ionospheric disturbances. On the basis of the modeling, we detected short-period ionospheric disturbances of moderate and weak intensity, preceding magnetic storms. They characterize occurrences of oscillatory processes in the ionosphere at the background of increased solar activity. Comparisons with the International Reference Ionosphere model (IRI-2016) and the median method were made. That showed the efficiency of the proposed model. For automatic performance of the approach, computational solutions were suggested to detect and to estimate ionospheric disturbance parameters.

APMT: an automatic hardware counter-based performance modeling tool for HPC applications

The ever-growing complexity of HPC applications and the computer architectures cost more efforts than ever to learn application behaviors. In this paper, we propose the APMT, an Automatic Performance Modeling Tool, to understand and predict performance efficiently in the regimes of interest to developers and performance analysts while outperforming many traditional techniques. In APMT, we use hardware counter-assisted profiling to identify the key kernels and non-scalable kernels and build each kernel model according to our performance modeling framework. Meantime, we also provide an optional refinement modeling framework to further understand the key performance metric, cycles-per-instruction (CPI). Our evaluations show that by only performing a few small-scale profiling, APMT is able to keep the average error rate around 15% with average performance overheads of 3% in different scenarios, including NAS parallel benchmarks, dynamical core of atmosphere model of the Community Earth System Model (CESM), and the ice component of CESM on commodity clusters. APMT improve the model prediction accuracies by 25–52% in strong scaling tests comparing to the well-known analytical model and the empirical model.

Shared Intentionality and Automatic Imitation: The case ofLa Ola

This article argues that such large-scale cases of crowd behavior as the Mexican Wave ( La Ola) constitute forms of shared intentionality which cannot be explained solely with the use of the standard intentionalistic ontology. It claims that such unique forms of collective intentionality require a hybrid explanatory lens in which an account of shared goals, intentions, and other propositional attitudes is combined with an account of the motor psychology of collective agents. The paper describes in detail the intentionalistic ontology of La Ola and discusses the conditions of cooperation it meets. The discussion allows the author to defend the view that large-scale collective intentionality can be based on automaticity to a significant degree: to properly understand such phenomena like La Ola, the idea of probabilistically interpreted decisions and propensities to act should give way to the automatic aspects of behavior. This paves the way for future studies in the philosophy of action to fully recognize the role of automatic performances at the level of collective actions just as they do for individual actions.

Quantitative analysis of automatic performance evaluation systems based on the h-index

Since the h-index has been invented, it is the most frequently discussed bibliometric value and one of the most commonly used metrics to quantify a researcher’s scientific output. The more it is increasingly gaining popularity to use the metric as an indication of the quality of a job applicant or an employee the more important it is to assure its correctitude. Many platforms offer the h-index of a scientist as a service, sometimes without the explicit knowledge of the respective person. In this article we show that looking up the h-index for a researcher on the five most commonly used platforms, namely AMiner, Google Scholar, ResearchGate, Scopus and Web of Science, results in a variance that is in many cases as large as the average value. This is due to the varying definitions of what a scientific article is, the underlying data basis, and different qualities of the entity recognition problem. To perform our study, we crawled the h-index of the worlds top researchers according to two different rankings, all the Nobel Prize laureates except Literature and Peace, and the teaching staff of the computer science department of the TU Kaiserslautern Germany with whom we additionally computed their h-index manually. Thus we showed that the individual h-indices differ to an alarming extent between the platforms. We observed that researchers with an extraordinary high h-index and researchers with an index appropriate to the scientific career path and the respective scientific field are affected alike by these problems.

Efficient and Portable Workgroup Size Tuning

The performance of an OpenCL program is strongly influenced by both hardware and software attributes. To achieve superior performance, developers may leverage automatic performance tuning techniques to determine the optimal parameters on the target device. Although existing approaches have shown promising tuning results in their target scenarios, other requirements such as efficiency, portability, and usability should also be considered because of the rapid growth of heterogeneous computing applications and platforms. In this paper, we re-examine the workgroup size tuning problem and propose a novel approach to meet the aforementioned requirements. We abstract the architectural details into a set of hardware parameters so that the proposed approach can be applied without the presence of target devices, which makes it more accessible to developers. The proposed approach is evaluated on 20 OpenCL kernels and six devices, including both CPUs and GPUs. Experimental results demonstrate that, with negligible overhead, our approach filters out 88.6 percent of the possible workgroup sizes on average. Among all the workgroup size candidates, the best- and worst-performing candidates can achieve average performance of 95.5 and 92.1 percent, respectively, compared with the optimal workgroup size.

Analysis of the Effects of Supraglottal Tract Surgical Procedures in Automatic Speaker Recognition Performance

This article evaluates the impact in the performance of state-of-the-art automatic speaker recognition schemes of three surgical procedures modifying the supraglottal tract structures of speakers. To do so, a new corpus (Cuco) was recorded, containing the speech of 107 speakers before and after surgery. Speakers were divided into four groups depending on the type of surgery: tonsillectomy, functional endoscopy sinus surgery (FESS), septoplasty, and controls. The analyzed speaker recognition schemes were i-vectors, i-vectors with supervised Universal Background Model, i-vectors employing Time-delay Deep Neural Networks and x-vectors. In all cases, probabilistic linear discriminant analysis was employed in the back-end. Results show changes in the speech of patients who underwent tonsillectomy or FESS after surgery in contrast to controls or patients who had a septoplasty, where not significant variations are observed. These changes increase the Equal Error Rate (EER) of the analyzed speaker recognition schemes for the septoplasty and FESS groups when employing enrollment data recorded before the surgery. Moreover, surgery has a similar influence in the speech of female and male speakers with respect to the analyzed schemes. In consequence, results suggest that it is advisable to update the speaker's enrollment speech after three months following supraglottal tract surgery to ensure that the effects of the operation and post-operative recovery period do not influence the performance of the automatic speaker recognition systems.

Spatio-Temporal Processing for Automatic Vehicle Detection in Wide-Area Aerial Video

Vehicle detection in aerial videos often requires post-processing to eliminate false detections. This paper presents a spatio-temporal processing scheme to improve automatic vehicle detection performance by replacing the thresholding step of existing detection algorithms with multi-neighborhood hysteresis thresholding for foreground pixel classification. The proposed scheme also performs spatial post-processing, which includes morphological opening and closing to shape and prune the detected objects, and temporal post-processing to further reduce false detections. We evaluate the performance of the proposed spatial processing on two local aerial video datasets and one parking vehicle dataset, and the performance of the proposed spatio-temporal processing scheme on five local aerial video datasets and one public dataset. Experimental evaluation shows that the proposed schemes improve vehicle detection performance for each of the nine algorithms when evaluated on seven datasets. Overall, the use of the proposed spatio-temporal processing scheme improves average F-score to above 0.8 and achieves an average reduction of 83.8% in false positives.

Force and Impedance Control for Automatic Violin Performance

Bowing a string requires not only the control of the position and velocity of the bow but also the control of impedance. Once the string starts vibrating, the vibration propagates through the bow to the arm holding the bow. Depending on the responsiveness or the impedance of the arm, the resulting motion changes. Therefore, this paper proposes the use of force and impedance control for reproducing the task of violin performance. We used a simple two-link manipulator to conduct experiments. The first experiment aims to identify the range of force and velocity necessary for the string to follow a periodic motion. Within the range, the second experiment examines the relationship between impedance gains and the timbre of the violin. In the last experiment, the performance of the robot is compared with the performance of an experienced violin player. Through the experiments, this paper verifies the effectiveness of force and impedance control in reproducing violin performance.

Pravna odgovornost u kontekstu veze blokčejn tehnologije i pametnih ugovora - uvodna razmatranja

Blockchain technology becomes relevant in economic exchange as it lowers costs and contributes to cost-efficiency and effectiveness of economic transactions. The key quality of Blockchain lies in ensuring the authenticity of digital data: trust in the traditional legal relationship has been replaced by digital verification of data in blocks. As an important phenomenon, Blockchain calls for legal answers on the issues arising from its application. An example of this development is the legal regime of smart contracts. A smart contract is a transaction in which any rights and obligations of the contracting parties are programmed in a code. Being the result of Blockchain technology application, such a contract implies the need for trust between the contracting parties. As a legal phenomenon, Blockchain (smart contract) technology raises the issue of liability for performing contractual obligations. Smart contracts can minimize certain contract risks and additionally simplify contract execution. They are immediately put into effect, without the need for any further interaction between the parties. The essential components of smart contracts are the digitally verifiable data and the automatic performance of legally relevant actions based on digitally received and processed information. All of the enlisted issues are important for proper understanding of liability of Blockchain actors.

Расчет параметров контейнерной площадки

This work is devoted to the development of software for automatic performance for the calculation of container freight station parameters. The article provides a brief description of the functional features of the program. The technical composition of a typical container terminal is described. Detailed flowcharts for implementing the main calculation procedures are presented. The distinctive features and areas of practical application of the program are formulated.

Legal Creation of Smart Contracts and the Legal Effects

Smart contracts are software codes based on the Blockchain technology which are involved in the field of information technology. The Blockchain smart contract is still in the contractual scope in nature, although its origin and automatic performance functions are different from existing contracts, but it can be identified as a typical unnamed contract. Therefore, at the legal level, a smart contract is a new form of contract that can automatically and automatically perform all or part of the contract. While discussing the technical aspects of smart contracts, we cannot ignore the relevant issues at the legal level. Smart contracts are developments and innovations in the form of traditional contracts. Smart contracts exist in electronic form and automatically fulfill contracts through software that is accurately encoded on the Blockchain. How to create smart contracts according to law and evaluate the legal effect of smart contracts are the main research issue of this paper.

Early reflection detection using autocorrelation to improve robustness of speaker verification in reverberant conditions

A speech signal captured by a distant microphone is generally smeared by reverberation, which severely degrades automatic speaker recognition performance. To improve system performance, an effective and robust method is proposed to extract features for speech processing. In this paper, a room impulse response is presumed to comprise of three parts: a direct-path response, early reflections and late reverberations. Since late reverberations are known to be a major cause of system performance degradation, this paper focuses on dealing with the effect of early reflection because the early reflections and their properties play a necessary role within the acoustics of an enclosure. The proposed method first estimates the early reflection using autocorrelation function from the presentation of speech signals in the first stage, the estimates are combined with an anechoic signal for use into training the system in the second stage. The employed method looks to be promising, achieving a substantial improvement in system performance relating to reduced equal error rate and detection trade-off, especially at longer reverberation time.

Probability learning and feedback processing in dyslexia: A performance and heart rate analysis.

Recent studies suggest that individuals with dyslexia may be impaired in probability learning and performance monitoring. These observations are consistent with findings indicating atypical neural activations in frontostriatal circuits in the brain, which are important for associative learning. The current study further examined probability learning and performance monitoring in adult individuals with dyslexia (n=23) and typical readers (n=31) using two varieties of a typical probabilistic learning task. In addition to performance measures, we measured heart rate, focusing on cardiac slowing with negative feedback as a manifestation of the automatic performance monitoring system. One task required participants to learn associations between artificial script and speech sounds and the other task required them to learn associations between geometric forms and bird sounds. Corrective feedback (informative or random) was provided in both tasks. Performance results indicated that individuals with dyslexia and typical readers learned the associations equally well in contrast to expectations. We found the typical cardiac response associated with feedback processing consisting of a heart rate slowing with the presentation of the feedback and a return to baseline thereafter. Interestingly, the heart rate slowing associated with feedback was less pronounced and the return to baseline was delayed in individuals with dyslexia relative to typical readers. These findings were interpreted in relation to current theorizing of performance monitoring linking the salience network in the brain to autonomic functioning.