Parallel Time Research Articles

Learning the Ropes of Tatparya: Revival of the Mimansa Rules of Interpretation

Abstract The primary task of the judiciary while interpreting the statute is to ascertain the true intention of the legislature. Maxwell on the interpretation of Statutes, setting out the principles evolved by the English Courts, is of immense help in the interpretation of statutes. An indigenous alternative that has been used by the Indian judiciary time and again is the Mimansa Rules which are the traditional rules of interpretation laid down by Jaimini to interpret Brahmanas. Despite dating back to the 5th century BC, these principles are considered scientific to an extent that they can be used to interpret the modern statutes and judgments. The Indian judiciary has adopted the principles of Mimansa to adjudicate several disputes about statutory interpretation. In light of these judgments, the researcher examines the scientific nature and application of the Mimansa Rules of Interpretation in contemporary times in parallel with the Maxwell’s Principles.

Exact and heuristic algorithms for the parallel machine total completion time scheduling problem with dual resources, ready times, and sequence-dependent setup times

This paper considers a dual resource constrained scheduling problem prevalent in high-capital cost manufacturing industry such as the photolithography area in the semiconductor industry. Specifically, the problem consists of assigning jobs to parallel machines that use common and constrained auxiliary resources such as lithography lens. Very often these auxiliary resources require heavy capital investment and setup times further complicates an already complex dual resource constrained scheduling problem. This paper advocates for the use of deterministic scheduling theory for the design and development of more efficient scheduling strategies. An Integer Programming (IP) model, a heuristic and a hybrid model were developed to schedule identical parallel machines with shared, constrained, auxiliary resources, with sequence-dependent setups, and job release dates with the goal of minimizing the sum of completion times.An IP model primed with a heuristic can add value to practitioners looking to solve real world resource constrained parallel machine scheduling problems with sequence-dependent setups. It is extremely important to control problem instance size and time horizon in order to obtain near-optimal or efficient solutions within acceptable run times. The proposed heuristic provides an initial feasible solution for the IP model which reduces the space search by decreasing the time horizon and eliminates the time needed to find an initial feasible solution. A tighter formulation is also proposed by reducing the time horizon formulation.

Toward informed partitioning for load balancing: A proof-of-concept

Most parallel applications suffer from load imbalance, a crucial performance degradation factor. In particle simulations, this is mainly due to the migration of particles between processing elements, which eventually gather unevenly and create workload imbalance. Dynamic load balancing is used at various iterations to mitigate load imbalance, employing a partitioning method to divide the computational space evenly while minimizing communications. In this paper, we propose a novel partitioning methodology called “informed partitioning”. It uses information based on the evolution of the computation to reduce the load balancing growth and the number of load balancing calls. In this paper, we illustrate informed partitioning by proposing a new geometric partitioning technique for particles simulations. This technique is derived from the well-known recursive coordinate bisection and employs the velocity of the particles to guide the bisection axis. To properly compare the performance of our new method with existing partitioning techniques during application execution, we introduce an effort metric based on a theoretical model of load balanced parallel application time. We propose a proof-of-concept of informed partitioning, through a numerical study, on three N-Body simulations with various particle dynamics, and we discuss its performance against popular geometric partitioning techniques. Moreover, we show that our effort metric can be used to rank partitioning techniques by their efficiency at any time point during the simulation. Eventually, this could be used to choose the best partitioning on the fly. In the numerical study, we report that our novel concept increases the performance of two experiments out of three by up to 76% and 15%, while being marginally slower by only 3% in one experiment. Also, we discuss the limitations of our implementation of informed partitioning and our effort metric.

A parallel time series algorithm for searching similar sub-sequences

<p><span>Dynamic time warping (DTW) is an important metric for measuring similarity for most time series applications. The computations of DTW cost too much especially with the gigantic of sequence databases and lead to an urgent need for accelerating these computations. However, the multi-core cluster systems, which are available now, with their scalability and performance/cost ratio, meet the need for more powerful and efficient performance. This paper proposes a highly efficient parallel vectorized algorithm with high performance for computing DTW, addressed to multi-core clusters using the Intel quad-core Xeon co-processors. It deduces an efficient architecture. Implementations employ the potential of both message passing interface (MPI) and OpenMP libraries. The implementation is based on the OpenMP parallel programming technology and offloads execution mode, where part of the code sub-sequences on the processor side, which are uploaded to the co-processor for the DTW computations. The results of experiments confirm the effectiveness of the algorithm.</span></p>

A comparative study on the energy flow of a hybrid heavy truck between AMT and MT shift mode under local driving test cycle

In this study, the energy flow of a hybrid heavy truck between the AMT and MT shift modes under a local road driving cycle was experimentally investigated in a climate chamber. The energy flow distributions, specific drive mode, operating conditions, energy efficiency of the power system, and components in the AMT and MT shift modes were comparatively discussed in detail. Based on the experimental results, the average 100 km fuel consumption of local driving test cycle under AMT and MT shift mode was 46.17 L/100 km and 45.06 L/100 km, respectively. The local driving test cycle had a significant influence on the operating conditions of the power units and key components. Moreover, the proportion of rear-axle work that was used to drive the hybrid heavy truck under MT shift mode (35.62%) was higher than that of AMT (34.31%), primarily because under the MT shift mode, there is a higher recovered energy, higher motor mechanical efficiency, much more parallel dive time, and less engine direct drive time, leading to more economical engine operating points. The total effective thermal efficiencies of the engine under AMT and MT shift modes were 39% and 39.7%, respectively, and the recovered energies were 16425 kJ and 24893 kJ, respectively. The total mechanical efficiencies under the parallel drive mode of AMT and MT cycle modes were 94.2% and 95.3%, respectively, whereas those of under the energy recovery mode were 92.1% and 94.2%, respectively.

Stimulating a future-oriented mindset and goal attainment through a smartphone-based intervention: Study protocol for a randomized controlled trial

BackgroundShort-term mindsets interfere with the consideration of future consequences and therefore predict negative behaviors. We developed a smartphone-based intervention aiming to increase a future-oriented mindset and personal goal attainment by strengthening future self-identification and stimulating episodic future thinking. The aims of the study are 1) to examine users' experiences with the application and their treatment adherence, 2) to examine the effectiveness of the intervention, and 3) to explore which intervention modules generate the strongest changes in key outcomes. MethodsFirst-year university students (N = 166) will be randomly assigned to two conditions: 1) the smartphone-based intervention, or 2) a goal-setting control group. The intervention consists of three week-long modules. Data will be collected at the start of the intervention, at weekly intervals during the intervention, immediately after the intervention, and at 3-month follow-up (and at parallel time points for the control group). We will assess users' experiences, application usage data, primary intervention outcomes (e.g., self-defeating behavior, future orientation, future self-identification), and secondary intervention outcomes (e.g., psychosocial wellbeing, self-efficacy). DiscussionThe study will provide information about users' experiences with the application, the intervention's general effectiveness, and which intervention modules show most promise. This information will be used to further develop the application and optimize this novel intervention. Trial registrationThe trial is registered in the Netherlands Trial Register (number: NL9671) on 16 August 2021.

The Influence of COVID-19 on Influenza and Respiratory Syncytial Virus Activities

Background: Respiratory viral diseases have considerably declined since the COVID-19 outbreak, perhaps through influence by nonpharmaceutical interventions. We conducted a cross-sectional study using the CDC database to compare the pre- vs. post-pandemic flu activity (incidence) between the US states. Our secondary objectives were to estimate the association between flu activity and flu vaccination rates and compare the national trends of flu and RSV activities since the pandemic outbreak. Methods: We estimated the difference between pre-pandemic (April 2019–March 2020) and post-pandemic (April 2020–March 2021) flu activity between individual states using the Wilcoxon signed-rank test. The association between flu activity and immunization rates was also measured. Finally, parallel time trend graphs for flu and RSV activities were illustrated with a time series modeler. Results: The median (IQR) pre-pandemic flu activity was 4.10 (1.38), higher than the post-pandemic activity (1.38 (0.71)) (p-value < 0.001). There was no difference between pre-pandemic (45.50% (39.10%)) and post-pandemic (45.0% (19.84%)) flu vaccine acceptance (p-value > 0.05). Flu activity and vaccination rates were not associated (p-value > 0.05). Flu activity has declined since the COVID-19 outbreak, while RSV made a strong comeback in June 2021. Conclusion: Flu activity has significantly diminished throughout the pandemic while a sudden upsurge in RSV is a public health concern indicative of possible resurgence of other viruses. Flu vaccine acceptance neither changed during the pandemic nor influenced the diminished Flu activity.

Automatic Identification of Similar Pull-Requests in GitHub’s Repositories Using Machine Learning

Context: In a social coding platform such as GitHub, a pull-request mechanism is frequently used by contributors to submit their code changes to reviewers of a given repository. In general, these code changes are either to add a new feature or to fix an existing bug. However, this mechanism is distributed and allows different contributors to submit unintentionally similar pull-requests that perform similar development activities. Similar pull-requests may be submitted to review in parallel time by different reviewers. This will cause redundant reviewing time and efforts. Moreover, it will complicate the collaboration process. Objective: Therefore, it is useful to assign similar pull-requests to the same reviewer to be able to decide which pull-request to choose in effective time and effort. In this article, we propose to group similar pull-requests together into clusters so that each cluster is assigned to the same reviewer or the same reviewing team. This proposal allows saving reviewing efforts and time. Method: To do so, we first extract descriptive textual information from pull-requests content to link similar pull-requests together. Then, we employ the extracted information to find similarities among pull-requests. Finally, machine learning algorithms (K-Means clustering and agglomeration hierarchical clustering algorithms) are used to group similar pull-requests together. Results: To validate our proposal, we have applied it to twenty popular repositories from public dataset. The experimental results show that the proposed approach achieved promising results according to the well-known metrics in this subject: precision and recall. Furthermore, it helps to save the reviewer time and effort. Conclusion: According to the obtained results, the K-Means algorithm achieves 94% and 91% average precision and recall values over all considered repositories, respectively, while agglomeration hierarchical clustering performs 93% and 98% average precision and recall values over all considered repositories, respectively. Moreover, the proposed approach saves reviewing time and effort on average between (67% and 91%) by K-Means algorithm and between (67% and 83%) by agglomeration hierarchical clustering algorithm.

Optimized Hardware Vision System for Vehicle Detection based on FPGA and Combining Machine Learning and PSO

Vision-based hardware driver assistance systems are the most important systems in the world because of their low cost and ability to provide information on driving environments. Improving safety and reducing accidents are the two main objectives of these systems. For this, in this paper a new Vision-based Hardware Advanced Driver Assistance System (VH-ADAS) based machine learning incorporating the hybridization of Support Vector Machine (SVM)-Histogram of Oriented Gradient (HOG) classifier and Particle Swarm Optimization (PSO) technique is proposed for traffic scenes from both video and captured images. First, the proposed system uses a feature extraction method based on the HOG. Then, the Particle Swarm Optimization technique is used for selection and so to optimize the features. The SVM method is applied to obtain fast detection and high accuracy. Finally, a hardware synthesizable architecture of the complete system was developed and then co-simulation validity was succeeded using the Matlab-Vivado System Generator (VSG) and a Field Programmable Gate Array (FPGA). The results show that the proposed new system supports real-time detection in both images and video. Also, they show that the proposed vehicle detection method is competitive in terms of parallel run time with only 1.483 ms and in terms of accuracy rate with only 97.84%.

Transmission and application of a P-wave across joints based on a modified g-λ model

Accurately predicting the location of a fault in front of a tunnel face is an essential part of deep-buried tunnel excavation . This paper proposes a modified g- λ ( 0 < λ < 1 ) model with in situ stress to investigate the propagation and attenuation of a P-wave across jointed rock masses , including a single joint or multiple parallel joints. Based on the modified g- λ model, the differential expressions of the transmitted wave’s particle velocity reflecting the interactions between the P-wave and the joints are deduced by using the characteristics method and the displacement discontinuity model. Parametric studies examining the in situ stress, the value of λ , the incident wave frequency and amplitude, and the number of joints are conducted to evaluate the application of the modified g- λ model. This provides support for predicting the location of the fault during the in situ stress tunnel construction when ignoring the shape and width of the fault. The results show that the effective wave velocity of the jointed rock masses increases with increasing in situ stress when a normally incident P-wave impinges upon a single joint. Considering multiple parallel joints, the magnitude and time of the maximum peak of the transmitted wave are decreases and delayed correspondingly with the increase in the number of joints, respectively. Moreover, multisource seismic interferometry is used to predict the location of the fault at different surrounding rock wave velocities and dip angles of the fault, which contribute to the identification of unfavorable geological bodies on the tunnel advanced geological predictions.

Is Chronic Varicocele a Risk Factor for Secondary Hyperparathyroidism?

Objective: To assess whether varicocele affects testicular 25-hydroxylase activity. Methods: Twenty normozoospermic patients with bilateral varicocele (grade III according to the Dubin and Amelar classification) without indications to undergo varicocele repair (normal sperm parameters and testicular volume; no scrotal pain) were consecutively enrolled and followed-up for four years. Serum levels of parathyroid hormone (PTH), calcium, and 25-hydroxy-cholecalciferol [25(OH)D] along with serum luteinizing hormone (LH), follicle-stimulating hormone (FSH), total testosterone (TT), conventional sperm parameters, sperm DNA fragmentation (SDF) rate, and testicular volume (TV) were measured annually for three years. PTH, calcium, and 25(OH)D serum levels over time were compared with those of age- and body mass index (BMI)-matched control group of twenty varicocelectomized patients. Main results: Both intra- and between-group analyses showed that serum PTH levels increased significantly over time in parallel with a significant decline in 25(OH)D levels. Serum calcium levels did not change significantly. At the same time, signs of mild Leydig and Sertoli cell dysfunction were found, such as an increase in gonadotropins and decreased TT and VT. However, conventional sperm parameters and SDF rate did not change significantly. Conclusion: This prospective controlled study provides the first evidence of a negative impact of bilateral grade III varicocele on testicular 25-hydroxylase activity. Accordingly, the patients included in this study showed a significant increase in PTH and a decrease in 25(OH)D levels over time. Patients with varicocele deserve endocrinologic counseling.

Parallel Changes in Positive Youth Development and Self-awareness: the Role of Emotional Self-regulation, Self-esteem, and Self-reflection.

The aim of the present study was to examine whether early adolescents’ positive development (i.e., resilience and psychological wellbeing) could be enhanced by stimulating three dimensions of self-awareness: emotional self-regulation, self-esteem, and self-reflection. An experimental field study (randomized controlled trial) was conducted. Seventh grade students (N = 1299; Mage = 12.38; 54% boys) completed multiple assessments at the beginning, during, and immediately after the intervention or at parallel time points for students in the control condition. Changes in the assessed constructs were examined with parallel process latent growth curve models. The results showed that increases in emotional self-regulation and self-esteem were related to concurrent increases in both resilience and psychological wellbeing. Changes in self-reflection were, however, not related to changes in these outcomes. The trajectories of change and parallel processes were similar in the intervention and control condition. These findings suggest that interventions aiming to stimulate positive youth development might be optimized by also focusing on youth’s self-awareness, though more knowledge about how self-awareness can be stimulated best is needed. This trial was registered in the Dutch Trial Register, number NL6371 (old number: NTR6554), on July 3, 2017.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11121-022-01345-9.

Molecular phylogenetics ofEuploca(Boraginaceae): homoplasy in many characters, including the C4 photosynthetic pathway

AbstractWe present a phylogenetic analysis using plastid (matK, rbcL) and nuclear (nrITS) DNA for diverse Euploca spp. (formerly Heliotropium section Orthostachys) from the worldwide distribution of a genus and including species encompassing the wide physiological and morphological diversity of the genus. Our results indicate that some remarkably complex features arose multiple times in parallel in Euploca, including attributes of its subsections under section Orthostachys, notably plants that, above ground, consist almost entirely of inflorescences. To elucidate in greater detail the distribution of C4 species in Euploca and Heliotropium s.s., we made &amp;gt; 800 δ 13C determinations, including some from the traditional genus Tournefortia. We greatly increase the number of proven C4 species in Euploca, but found none outside Euploca. Of the tested Euploca spp., c. 28% are C3 or intermediate in carbon fixation pathway. Our phylogenetic results indicate four parallel/convergent acquisitions of C4 photosynthesis or fewer origins with subsequent loss in some species.

Animist Time and the White Anthropocene

This article considers the Western civilisational ethos of the human person as an ethos of mastery with respect to the natural world. The age of climate disaster has begun to turn this ethos into an object for thought, as is evidenced by an increasing number of eco-poetic and eco-philosophical writings and reflections that seek to re-think or un-think prevailing Western construals of the human. My own entry point into the conversation is through Afro-diasporic knowledge systems that evidence construals of the human being not rooted in the Western paradigm of the individual. I ask how such knowledge systems help us to achieve a necessary thought revolution with respect to the current dangers of our technological civilisation (particularly climate disaster and capitalist extractivism). I emphasise the fact that animist thinking systems have for centuries, due to the violences of modernity, existed in a parallel space and time to what I call 'capitalist time' and propose that the failures and crises of Western industrial/technological civilisation warrant renewed examinations of their benefits in human living practices.

Animist Time and the White Anthropocene

This article considers the Western civilisational ethos of the human person as an ethos of mastery with respect to the natural world. The age of climate disaster has begun to turn this ethos into an object for thought, as is evidenced by an increasing number of eco-poetic and eco-philosophical writings and reflections that seek to re-think or un-think prevailing Western construals of the human. My own entry point into the conversation is through Afro-diasporic knowledge systems that evidence construals of the human being not rooted in the Western paradigm of the individual. I ask how such knowledge systems help us to achieve a necessary thought revolution with respect to the current dangers of our technological civilisation (particularly climate disaster and capitalist extractivism). I emphasise the fact that animist thinking systems have for centuries, due to the violences of modernity, existed in a parallel space and time to what I call 'capitalist time' and propose that the failures and crises of Western industrial/technological civilisation warrant renewed examinations of their benefits in human living practices.

Impact of emerging virus pandemics on cause-specific maternal mortality time series: a population-based natural experiment using national vital statistics, Argentina 1980-2017

BackgroundEmerging pandemic viruses may have multiple deleterious effects on maternal health. This study examines the effects of a pandemic influenza virus on cause-specific maternal mortality time series, using Argentinian vital statistics. MethodsWe conducted a population-based natural experiment from national vital records of maternal deaths between 1980 and 2017. Joinpoint regression models were used to model time series of the maternal mortality ratio (MMR). The sensitivity of the registry to detect the effects of the pandemic H1N1 2009 influenza virus on cause-specific MMR was analysed using a panel of parallel interrupted time series (ITS). FindingsOver this 38-year study, the MMR decreased by 58·6% (69·5 to 28·8 deaths/100,000 live births), transitioning from direct obstetric causes (67·0 to 21·1/100,000 live births; 68·4% decrease) to indirect causes (2·6 to 7·7/100,000 live births; 196·2% increase). The regression analysis showed an average reduction of -2·2%/year (95% CI: -2·9 to -1·4) with 2 join points in the total trend (1998 and 2009). Parallel ITS analyses revealed the pandemic H1N1 virus had an increasing effect on mortality from the respiratory system- and sepsis-related complications (level change 4·7 and 1·6/100,000 live births respectively), reversing after the outbreak. No effect was found on MMR from hypertensive disorders, haemorrhage, abortive outcomes, other direct obstetric causes, and indirect non-respiratory comorbidities. InterpretationThe Argentinian maternal death registry appears sensitive to detect different effects of emerging infectious epidemics on maternal health. In a population-based natural experiment, pandemic H1N1 virus impacted maternal mortality almost exclusively from the respiratory system- and sepsis-related complications. FundingSupported by FISAR www.fisarchile.org

Research on real time simulation modeling method of large scale MMC electromagnetic transient

Modular multilevel converter (MMC) contains a large number of power electronic switching devices. The modeling method based on switching circuit model needs a lot of resources and the simulation speed is slow, so it is difficult to realize large-scale real-time simulation of electromagnetic transient. A MMC electromagnetic transient numerical modeling method based on ideal transformer model (ITM) is presented. Firstly, the MMC system is divided into the main circuit network and the sub module group network by ITM method, and the error caused by decoupling delay in serial and parallel real time simulation is compensated respectively by interpolation prediction and advanced interpolation prediction. Secondly, the capacitor in sub module is discreted respectively by trapezoidal integration method, backward Euler method and Gear-2 method. Based on the above numerical integration, the difference equations of capacitance voltage, capacitance current and output voltage of half bridge and full bridge sub modules are derived. Then, in order to improve the calculation speed, a simplified numerical model of half bridge and full bridge sub module based on switching function is proposed. Finally, the MMC based on switching circuit model runs off-line simulation in the simulation software, and the above MMC numerical modeling method runs real-time simulation in Speedgoat real-time simulator. The off-line and real-time simulation results of the MMC numerical modeling method and the switching circuit model are compared. And the simulation results verify the feasibility and effectiveness of the above MMC numerical modeling method in real time simulation.

A MAC Protocol for Underwater Sensor Networks Using Parallel Transmission Variable Time Slots

Dong, W.; Yang, Q.; Huang, X.; Chen, Y., and Sun, S., 2022. A MAC protocol for underwater sensor networks using parallel transmission variable time slots. Journal of Coastal Research, 38(2), 449–457. Coconut Creek (Florida), ISSN 0749-0208. Underwater wireless sensor networks (UWSNs) play an important role in coastal research and ocean utilization. The disadvantages of the long propagation delay in underwater acoustic communication make the MAC protocol based on time slots unsuitable for UWSNs. Thus, a MAC protocol with a variable time slot is proposed to solve this problem. In the proposed protocol, a parallel transmission node selection algorithm realizes the collision-free transmission of multiple nodes in the same time slot according to the delay information between nodes and the duration of the packet. It determines the length of each time slot at the same time. Then, the cluster head node schedules the sending time of each node according to the parallel transmission node selection algorithm. Compared with the Time Division Multiple Access (TDMA) and prescheduling-based MAC, the simulation results show that the throughput is increased by approximately 47% and 25%, respectively, under the same load. When the load is low, variable time slot-MAC also has better performance related to end-to-end delay.

Scheduling optimisation of multi-type special vehicles in an airport

An insufficient number of ground support vehicles and improper dispatch have a significant impact on the quality of airport services. The reasonable dispatch of airport special vehicles can greatly improve the efficiency of airport services. In this paper, a bi-objective mixed-integer programming model is proposed which takes the minimum number of vehicles required and minimum total extra time cost of special vehicles as objectives. Additionally, the service constraint relationship of various vehicles and the reusable nature of vehicles to make full use of existing special vehicle resources are considered. To easily solve the model, the comprehensive scheduling problem is reduced to several sub-problems with parallel services and timing constraints. A non-dominated sorting genetic algorithm with multiple chromosomes and an elite strategy are developed to solve them separately. Finally, using the actual flight data of a domestic airport, we demonstrate the effectiveness of the proposed model and offer useful managerial insights.

A Comprehensive Inspection of the Straggler Problem

Parameter server is a popular distributed processing paradigm for operating distributed deep learning (DL) applications. As a growing number of DL models are trained via shared clusters, machines are in confrontation with the heterogeneous environment, which incurs the unexpected phenomenon with a slow task processing speed called straggler. Straggler addressing is a crucial issue in distributed DL applications, since stragglers significantly hamper system performance. While many techniques have been deployed to mitigate stragglers, they may not achieve their goals with the presence of heterogeneity, where systems consume much longer time until DL training convergence than in a homogeneous environment, as evidenced by our experimental study. With the methodology of straggler projection and abstraction of parallelism, a new synchronization mechanism called elastic parallelism synchronous parallel (EPSP) is proposed, which exploits the superiority of iteration acceleration in stale synchronous parallel and conquers the shortage of barrier wasting time in bulk synchronous parallel. More precisely, EPSP supports both enforced and slack synchronization by adjusting the parameter of staleness.