scholarly journals All-gather Algorithms Resilient to Imbalanced Process Arrival Patterns

2021 ◽  
Vol 18 (4) ◽  
pp. 1-22
Author(s):  
Jerzy Proficz
Keyword(s):  
Experimental Evaluation ◽  
Data Exchange ◽  
State Of The Art ◽  
Monitoring And Evaluation ◽  
The Other ◽  
Early Data ◽  
Cluster Architecture ◽  
Novel Algorithms

Two novel algorithms for the all-gather operation resilient to imbalanced process arrival patterns (PATs) are presented. The first one, Background Disseminated Ring (BDR), is based on the regular parallel ring algorithm often supplied in MPI implementations and exploits an auxiliary background thread for early data exchange from faster processes to accelerate the performed all-gather operation. The other algorithm, Background Sorted Linear synchronized tree with Broadcast (BSLB), is built upon the already existing PAP-aware gather algorithm, that is, Background Sorted Linear Synchronized tree (BSLS), followed by a regular broadcast distributing gathered data to all participating processes. The background of the imbalanced PAP subject is described, along with the PAP monitoring and evaluation topics. An experimental evaluation of the algorithms based on a proposed mini-benchmark is presented. The mini-benchmark was performed over 2,000 times in a typical HPC cluster architecture with homogeneous compute nodes. The obtained results are analyzed according to different PATs, data sizes, and process numbers, showing that the proposed optimization works well for various configurations, is scalable, and can significantly reduce the all-gather elapsed times, in our case, up to factor 1.9 or 47% in comparison with the best state-of-the-art solution.

scholarly journals A Reinforced Topic-Aware Convolutional Sequence-to-Sequence Model for Abstractive Text Summarization

2018 ◽  
Author(s):  
Li Wang ◽  
Junlin Yao ◽  
Yunzhe Tao ◽  
Li Zhong ◽  
Wei Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Experimental Evaluation ◽  
State Of The Art ◽  
Text Summarization ◽  
The Other ◽  
Learning Approach ◽  
Automatic Summarization ◽  
Word Level ◽  
Proposed Model ◽  
Abstractive Summarization

In this paper, we propose a deep learning approach to tackle the automatic summarization tasks by incorporating topic information into the convolutional sequence-to-sequence (ConvS2S) model and using self-critical sequence training (SCST) for optimization. Through jointly attending to topics and word-level alignment, our approach can improve coherence, diversity, and informativeness of generated summaries via a biased probability generation mechanism. On the other hand, reinforcement training, like SCST, directly optimizes the proposed model with respect to the non-differentiable metric ROUGE, which also avoids the exposure bias during inference. We carry out the experimental evaluation with state-of-the-art methods over the Gigaword, DUC-2004, and LCSTS datasets. The empirical results demonstrate the superiority of our proposed method in the abstractive summarization.

Computer Vision and robotics in postal automation

1999 ◽  
Vol 18 (3-4) ◽  
pp. 265-273
Author(s):  
Giovanni B. Garibotto
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Material Handling ◽  
State Of The Art ◽  
Short Description ◽  
The Other ◽  
Functional Requirements ◽  
Postal Automation ◽  
And Robotics

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.

Occupant pre-crash kinematics in rotated seat arrangements

2021 ◽  
pp. 095440702110045
Author(s):  
Alexander Diederich ◽  
Christophe Bastien ◽  
Karthikeyan Ekambaram ◽  
Alexis Wilson
Keyword(s):  
State Of The Art ◽  
The Other ◽  
Human Model ◽  
Multi Objective ◽  
Emergency Braking ◽  
Seating Arrangement ◽  
Current State ◽  
Occupant Comfort ◽  
Occupant Kinematics ◽  
Belt System

The introduction of automated L5 driving technologies will revolutionise the design of vehicle interiors and seating configurations, improving occupant comfort and experience. It is foreseen that pre-crash emergency braking and swerving manoeuvres will affect occupant posture, which could lead to an interaction with a deploying airbag. This research addresses the urgent safety need of defining the occupant’s kinematics envelope during that pre-crash phase, considering rotated seat arrangements and different seatbelt configurations. The research used two different sets of volunteer tests experiencing L5 vehicle manoeuvres, based in the first instance on 22 50th percentile fit males wearing a lap-belt (OM4IS), while the other dataset is based on 87 volunteers with a BMI range of 19 to 67 kg/m2 wearing a 3-point belt (UMTRI). Unique biomechanics kinematics corridors were then defined, as a function of belt configuration and vehicle manoeuvre, to calibrate an Active Human Model (AHM) using a multi-objective optimisation coupled with a Correlation and Analysis (CORA) rating. The research improved the AHM omnidirectional kinematics response over current state of the art in a generic lap-belted environment. The AHM was then tested in a rotated seating arrangement under extreme braking, highlighting that maximum lateral and frontal motions are comparable, independent of the belt system, while the asymmetry of the 3-point belt increased the occupant’s motion towards the seatbelt buckle. It was observed that the frontal occupant kinematics decrease by 200 mm compared to a lap-belted configuration. This improved omnidirectional AHM is the first step towards designing safer future L5 vehicle interiors.

scholarly journals Development of Multiple Behaviors in Evolving Robots

Robotics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Victor Massagué Respall ◽  
Stefano Nolfi
Keyword(s):  
Evolutionary Algorithms ◽  
State Of The Art ◽  
Evolutionary Robotics ◽  
The Other ◽  
Evolutionary Strategies ◽  
Multiple Behaviors ◽  
Pareto Fronts ◽  
Expected Fitness

We investigate whether standard evolutionary robotics methods can be extended to support the evolution of multiple behaviors by forcing the retention of variations that are adaptive with respect to all required behaviors. This is realized by selecting the individuals located in the first Pareto fronts of the multidimensional fitness space in the case of a standard evolutionary algorithms and by computing and using multiple gradients of the expected fitness in the case of a modern evolutionary strategies that move the population in the direction of the gradient of the fitness. The results collected on two extended versions of state-of-the-art benchmarking problems indicate that the latter method permits to evolve robots capable of producing the required multiple behaviors in the majority of the replications and produces significantly better results than all the other methods considered.

scholarly journals Density Guarantee on Finding Multiple Subgraphs and Subtensors

2021 ◽  
Vol 15 (5) ◽  
pp. 1-32
Author(s):  
Quang-huy Duong ◽  
Heri Ramampiaro ◽  
Kjetil Nørvåg ◽  
Thu-lan Dam
Keyword(s):  
Lower Bound ◽  
State Of The Art ◽  
The State ◽  
The Other ◽  
Exact Methods ◽  
Practical Solution ◽  
Novel Approach ◽  
Wide Range ◽  
Real World Datasets ◽  
Tensor Data

Dense subregion (subgraph & subtensor) detection is a well-studied area, with a wide range of applications, and numerous efficient approaches and algorithms have been proposed. Approximation approaches are commonly used for detecting dense subregions due to the complexity of the exact methods. Existing algorithms are generally efficient for dense subtensor and subgraph detection, and can perform well in many applications. However, most of the existing works utilize the state-or-the-art greedy 2-approximation algorithm to capably provide solutions with a loose theoretical density guarantee. The main drawback of most of these algorithms is that they can estimate only one subtensor, or subgraph, at a time, with a low guarantee on its density. While some methods can, on the other hand, estimate multiple subtensors, they can give a guarantee on the density with respect to the input tensor for the first estimated subsensor only. We address these drawbacks by providing both theoretical and practical solution for estimating multiple dense subtensors in tensor data and giving a higher lower bound of the density. In particular, we guarantee and prove a higher bound of the lower-bound density of the estimated subgraph and subtensors. We also propose a novel approach to show that there are multiple dense subtensors with a guarantee on its density that is greater than the lower bound used in the state-of-the-art algorithms. We evaluate our approach with extensive experiments on several real-world datasets, which demonstrates its efficiency and feasibility.

scholarly journals Fast Accurate and Automatic Brushstroke Extraction

2021 ◽  
Vol 17 (2) ◽  
pp. 1-24
Author(s):  
Yunfei Fu ◽  
Hongchuan Yu ◽  
Chih-Kuo Yeh ◽  
Tong-Yee Lee ◽  
Jian J. Zhang
Keyword(s):  
Neural Network ◽  
Efficient Algorithm ◽  
Deep Neural Network ◽  
High Efficiency ◽  
State Of The Art ◽  
High Reliability ◽  
The Other ◽  
Manual Annotation ◽  
Stroke Extraction ◽  
Art Research

Brushstrokes are viewed as the artist’s “handwriting” in a painting. In many applications such as style learning and transfer, mimicking painting, and painting authentication, it is highly desired to quantitatively and accurately identify brushstroke characteristics from old masters’ pieces using computer programs. However, due to the nature of hundreds or thousands of intermingling brushstrokes in the painting, it still remains challenging. This article proposes an efficient algorithm for brush Stroke extraction based on a Deep neural network, i.e., DStroke. Compared to the state-of-the-art research, the main merit of the proposed DStroke is to automatically and rapidly extract brushstrokes from a painting without manual annotation, while accurately approximating the real brushstrokes with high reliability. Herein, recovering the faithful soft transitions between brushstrokes is often ignored by the other methods. In fact, the details of brushstrokes in a master piece of painting (e.g., shapes, colors, texture, overlaps) are highly desired by artists since they hold promise to enhance and extend the artists’ powers, just like microscopes extend biologists’ powers. To demonstrate the high efficiency of the proposed DStroke, we perform it on a set of real scans of paintings and a set of synthetic paintings, respectively. Experiments show that the proposed DStroke is noticeably faster and more accurate at identifying and extracting brushstrokes, outperforming the other methods.

scholarly journals Cache-efficient sweeping-based interval joins for extended Allen relation predicates

2021 ◽  
Author(s):  
Danila Piatov ◽  
Sven Helmer ◽  
Anton Dignös ◽  
Fabio Persia
Keyword(s):  
Data Structure ◽  
Experimental Evaluation ◽  
State Of The Art ◽  
Temporal Databases ◽  
Access Method ◽  
Wide Range ◽  
Interval Relation ◽  
Cache Efficient ◽  
Join Algorithms ◽  
Better Than

AbstractWe develop a family of efficient plane-sweeping interval join algorithms for evaluating a wide range of interval predicates such as Allen’s relationships and parameterized relationships. Our technique is based on a framework, components of which can be flexibly combined in different manners to support the required interval relation. In temporal databases, our algorithms can exploit a well-known and flexible access method, the Timeline Index, thus expanding the set of operations it supports even further. Additionally, employing a compact data structure, the gapless hash map, we utilize the CPU cache efficiently. In an experimental evaluation, we show that our approach is several times faster and scales better than state-of-the-art techniques, while being much better suited for real-time event processing.

scholarly journals Follitropin Delta as a State-of-the-Art Incorporated Companion for Assisted Reproductive Procedures: A Two Year Observational Study

Medicina ◽  
2021 ◽  
Vol 57 (4) ◽  
pp. 379
Author(s):  
Bogdan Doroftei ◽  
Ovidiu-Dumitru Ilie ◽  
Ana-Maria Dabuleanu ◽  
Roxana Diaconu ◽  
Radu Maftei ◽  
...  
Keyword(s):  
Observational Study ◽  
Ovarian Hyperstimulation Syndrome ◽  
Twin Pregnancy ◽  
Assisted Reproductive Technologies ◽  
State Of The Art ◽  
Follicle Stimulating Hormone ◽  
Exact Result ◽  
Reproductive Technologies ◽  
The Other ◽  
Ovarian Hyperstimulation

Background and objectives: The latest reports suggest that follitropin delta is a highly efficient recombinant human follicle-stimulating hormone (r-hFSH) that became a part of the current assisted reproductive technologies (ARTs). Therefore, the present study aims to assess a series of parameters (follicles, oocytes, and embryos) and further by the outcomes in women following the administration of follitropin delta. Materials and methods: This observational study included 205 women. They were aged between 21 and 43 years (mean 33.45) and an anti-Müllerian hormone (AMH) level ranging from 0.11 to 16.00 ng/dL (mean 2.89). Results: In accordance with the established methodology and following the centralization of data, a total of fifty-eight pregnancies (28.29%) were achieved; forty-five (36.88%) were achieved in women under 35 years and thirteen (15.66%) in women above 35 years. These figures are positively correlated with women’s age considering that the number of follicles >18 mm, oocytes fertilized and embryo(s) varies among groups. Regarding the interest parameters, we noted n = 1719 follicles > 18 mm, n = 1279 retrieved oocytes, and n = 677 embryos at day 3. On the other hand, the following figures have been registered in women above 35 years: 814–follicles > 18 mm, 612 oocytes retrieved and 301 embryos at day 3. During this study, we registered only three cases of abortions (n = 1–0.81% in women under 35 years and n = 2–2.40% in women above 35 years). Nine pregnancies (7.37%) were stopped from evolution in females under 35 years, and twelve pregnancies (n = 8–6.55% in women under 35 years, while n = 4 in women above 35 years) were unsuccessful. A twin pregnancy has been confirmed (1.20%) in women above 35 years, six ongoing pregnancies (4.91%) in those under 35 years, and two in both groups (one per group–n = 1–0.81%, and 1.20%–n = 1) in which we did not know the exact result were registered at the end of the established studied interval. However, there were also situations in which the treatment cause an over-reactivity or had no effect; n = 2 were non-responders, and n = 1 exhibited moderate ovarian hyperstimulation syndrome (OHSS). Conclusions: Based on our results, we strongly encourage the use of this recombinant gonadotropin on a much larger scale.

scholarly journals Extraction of causal relations based on SBEL and BERT model

Database ◽  
2021 ◽  
Vol 2021 ◽  
Author(s):  
Yifan Shao ◽  
Haoru Li ◽  
Jinghang Gu ◽  
Longhua Qian ◽  
Guodong Zhou
Keyword(s):  
State Of The Art ◽  
Causal Relation ◽  
Relation Extraction ◽  
The Other ◽  
Biomedical Text ◽  
Intermediate Form ◽  
Biomedical Text Mining ◽  
Causal Relations ◽  
The One ◽  
Stage 1

Abstract Extraction of causal relations between biomedical entities in the form of Biological Expression Language (BEL) poses a new challenge to the community of biomedical text mining due to the complexity of BEL statements. We propose a simplified form of BEL statements [Simplified Biological Expression Language (SBEL)] to facilitate BEL extraction and employ BERT (Bidirectional Encoder Representation from Transformers) to improve the performance of causal relation extraction (RE). On the one hand, BEL statement extraction is transformed into the extraction of an intermediate form—SBEL statement, which is then further decomposed into two subtasks: entity RE and entity function detection. On the other hand, we use a powerful pretrained BERT model to both extract entity relations and detect entity functions, aiming to improve the performance of two subtasks. Entity relations and functions are then combined into SBEL statements and finally merged into BEL statements. Experimental results on the BioCreative-V Track 4 corpus demonstrate that our method achieves the state-of-the-art performance in BEL statement extraction with F1 scores of 54.8% in Stage 2 evaluation and of 30.1% in Stage 1 evaluation, respectively. Database URL: https://github.com/grapeff/SBEL_datasets

THE APPLICATION OF PETRI NETS TO WORKFLOW MANAGEMENT

1998 ◽  
Vol 08 (01) ◽  
pp. 21-66 ◽  
Author(s):  
W. M. P. VAN DER AALST
Keyword(s):  
Petri Nets ◽  
Petri Net ◽  
Business Processes ◽  
State Of The Art ◽  
Workflow Management ◽  
Explicit Representation ◽  
The Other ◽  
Application Domain ◽  
Analysis Techniques ◽  
The One

Workflow management promises a new solution to an age-old problem: controlling, monitoring, optimizing and supporting business processes. What is new about workflow management is the explicit representation of the business process logic which allows for computerized support. This paper discusses the use of Petri nets in the context of workflow management. Petri nets are an established tool for modeling and analyzing processes. On the one hand, Petri nets can be used as a design language for the specification of complex workflows. On the other hand, Petri net theory provides for powerful analysis techniques which can be used to verify the correctness of workflow procedures. This paper introduces workflow management as an application domain for Petri nets, presents state-of-the-art results with respect to the verification of workflows, and highlights some Petri-net-based workflow tools.

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