scholarly journals Seed Selection Strategies for Overlap Detection

2018 ◽  
Author(s):  
Jonathan Teutenberg
Keyword(s):  
State Of The Art ◽  
Data Sets ◽  
Seed Selection ◽  
Selection Strategies ◽  
Current State ◽  
Long Read ◽  
Selection Of

AbstractThe current state-of-the-art assemblers of long, error-prone reads rely on detecting all-vs-all overlaps within the set of reads with overlaps represented by a sparse selection of short subsequences or “seeds”. Though the quality of selection of these seeds can impact both accuracy and speed of overlap detection, existing algorithms do little more than ignore over-represented seeds. Here we propose several more informed seed selection strategies to improve precision and recall of overlaps. These strategies are evaluated against real long-read data sets with a range of fixed seed sizes. We show that these strategies substantially improve the utility of individual seeds over uninformed selection.

scholarly journals Smoothing additive manufactured parts using ns-pulsed laser radiation

2021 ◽  
Author(s):  
Florian Kuisat ◽  
Fernando Lasagni ◽  
Andrés Fabián Lasagni
Keyword(s):  
Surface Roughness ◽  
Mechanical Performance ◽  
State Of The Art ◽  
Pulsed Laser ◽  
Industrial Applications ◽  
Laser Source ◽  
Pulsed Laser Radiation ◽  
Current State ◽  
The Impact

AbstractIt is well known that the surface topography of a part can affect its mechanical performance, which is typical in additive manufacturing. In this context, we report about the surface modification of additive manufactured components made of Titanium 64 (Ti64) and Scalmalloy®, using a pulsed laser, with the aim of reducing their surface roughness. In our experiments, a nanosecond-pulsed infrared laser source with variable pulse durations between 8 and 200 ns was applied. The impact of varying a large number of parameters on the surface quality of the smoothed areas was investigated. The results demonstrated a reduction of surface roughness Sa by more than 80% for Titanium 64 and by 65% for Scalmalloy® samples. This allows to extend the applicability of additive manufactured components beyond the current state of the art and break new ground for the application in various industrial applications such as in aerospace.

scholarly journals Ensemble-Based Out-of-Distribution Detection

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 567
Author(s):  
Donghun Yang ◽  
Kien Mai Mai Ngoc ◽  
Iksoo Shin ◽  
Kyong-Ha Lee ◽  
Myunggwon Hwang
Keyword(s):  
Detection Method ◽  
State Of The Art ◽  
Metric Learning ◽  
Feature Space ◽  
Confidence Score ◽  
Distance Metric Learning ◽  
Current State ◽  
Overall Performance ◽  
Deep Learning Model

To design an efficient deep learning model that can be used in the real-world, it is important to detect out-of-distribution (OOD) data well. Various studies have been conducted to solve the OOD problem. The current state-of-the-art approach uses a confidence score based on the Mahalanobis distance in a feature space. Although it outperformed the previous approaches, the results were sensitive to the quality of the trained model and the dataset complexity. Herein, we propose a novel OOD detection method that can train more efficient feature space for OOD detection. The proposed method uses an ensemble of the features trained using the softmax-based classifier and the network based on distance metric learning (DML). Through the complementary interaction of these two networks, the trained feature space has a more clumped distribution and can fit well on the Gaussian distribution by class. Therefore, OOD data can be efficiently detected by setting a threshold in the trained feature space. To evaluate the proposed method, we applied our method to various combinations of image datasets. The results show that the overall performance of the proposed approach is superior to those of other methods, including the state-of-the-art approach, on any combination of datasets.

Website traffic measurement and rankings: competitive intelligence tools examination

2018 ◽  
Vol 14 (4) ◽  
pp. 423-437 ◽  
Author(s):  
David Prantl ◽  
Martin Prantl
Keyword(s):  
Design Methodology ◽  
State Of The Art ◽  
Competitive Intelligence ◽  
Data Sets ◽  
Traffic Data ◽  
Content Type ◽  
Traffic Measurement ◽  
Data Estimation ◽  
Research Studies

PurposeThe purpose of this paper is to examine and verify the competitive intelligence tools Alexa and SimilarWeb, which are broadly used for website traffic data estimation. Tested tools belong to the state of the art in this area.Design/methodology/approachThe authors use quantitative approach. Research was conducted on a sample of Czech websites for which there are accurate traffic data values, against which the other data sets (less accurate) provided by Alexa and SimilarWeb will be compared.FindingsThe results show that neither tool can accurately determine the ranking of websites on the internet. However, it is possible to approximately determine the significance of a particular website. These results are useful for another research studies which use data from Alexa or SimilarWeb. Moreover, the results show that it is still not possible to accurately estimate website traffic of any website in the world.Research limitations/implicationsThe limitation of the research lies in the fact that it was conducted solely in the Czech market.Originality/valueSignificant amount of research studies use data sets provided by Alexa and SimilarWeb. However, none of these research studies focus on the quality of the website traffic data acquired by Alexa or SimilarWeb, nor do any of them refer to other studies that would deal with this issue. Furthermore, authors describe approaches to measuring website traffic and based on the analysis, the possible usability of these methods is discussed.

scholarly journals Soft Threshold Ternary Networks

2020 ◽  
Author(s):  
Weixiang Xu ◽  
Xiangyu He ◽  
Tianli Zhao ◽  
Qinghao Hu ◽  
Peisong Wang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Mobile Devices ◽  
State Of The Art ◽  
Performance Gap ◽  
Training Time ◽  
Current State ◽  
The Arts ◽  
Soft Threshold ◽  
And Storage ◽  
Selection Of

Large neural networks are difficult to deploy on mobile devices because of intensive computation and storage. To alleviate it, we study ternarization, a balance between efficiency and accuracy that quantizes both weights and activations into ternary values. In previous ternarized neural networks, a hard threshold Δ is introduced to determine quantization intervals. Although the selection of Δ greatly affects the training results, previous works estimate Δ via an approximation or treat it as a hyper-parameter, which is suboptimal. In this paper, we present the Soft Threshold Ternary Networks (STTN), which enables the model to automatically determine quantization intervals instead of depending on a hard threshold. Concretely, we replace the original ternary kernel with the addition of two binary kernels at training time, where ternary values are determined by the combination of two corresponding binary values. At inference time, we add up the two binary kernels to obtain a single ternary kernel. Our method dramatically outperforms current state-of-the-arts, lowering the performance gap between full-precision networks and extreme low bit networks. Experiments on ImageNet with AlexNet (Top-1 55.6%), ResNet-18 (Top-1 66.2%) achieves new state-of-the-art.

Modular Prosthetic Design for Transtibial Child Amputees

2017 ◽  
Author(s):  
Brendan M. Hickey ◽  
Samuel T. Woo ◽  
Sally F. Shady
Keyword(s):  
Quality Of Life ◽  
Health Care ◽  
Lower Limb ◽  
State Of The Art ◽  
Insurance Coverage ◽  
Review Article ◽  
Prosthetic Design ◽  
Current State ◽  
Limb Deficiencies

Lower limb deficiencies and below knee amputations are the most common form of deficiency that may arise from disease or trauma, and returning a patient close to a normal quality-of-life requires prosthetics, which can be quite challenging. Children present even further difficulty to prosthetists and physicians than adults. Although the underlying prosthetic principles for adults are the same for children, additional considerations must be made for practicality, such as downsizing while maintaining its degree of complexity, and frequent appointments to account for the rapid growth of an adolescent. This review article will evaluate the current state-of-the-art in the field of transtibial-amputee prosthetics, review the insurance coverage a typical family would face, and suggest potential improvements to children’s biomimetic prostheses that aid in reducing the frequency of health care provider intervention.

scholarly journals A review on the use of additive manufacturing to produce lower limb orthoses

2019 ◽  
Vol 5 (2) ◽  
pp. 85-94 ◽  
Author(s):  
Mohammed S. Alqahtani ◽  
Abdulsalam Al-Tamimi ◽  
Henrique Almeida ◽  
Glen Cooper ◽  
Paulo Bartolo
Keyword(s):  
Additive Manufacturing ◽  
Lower Limb ◽  
State Of The Art ◽  
Production Costs ◽  
Current State ◽  
Research Challenges ◽  
Fixation Devices ◽  
Alignment Correction ◽  
And Performance

Abstract Orthoses (exoskeletons and fracture fixation devices) enhance users’ ability to function and improve their quality of life by supporting alignment correction, restoring mobility, providing protection, immobilisation and stabilisation. Ideally, these devices should be personalised to each patient to improve comfort and performance. Production costs have been one of the main constraints for the production of personalised orthoses. However, customisation and personalisation of orthoses are now possible through the use of additive manufacturing. This paper presents the current state of the art of additive manufacturing for the fabrication of orthoses, providing several examples, and discusses key research challenges to be addressed to further develop this field.

scholarly journals Biomechanical behaviours of the bone–implant interface: a review

2019 ◽  
Vol 16 (156) ◽  
pp. 20190259 ◽  
Author(s):  
Xing Gao ◽  
Manon Fraulob ◽  
Guillaume Haïat
Keyword(s):  
Bone Tissue ◽  
Medical Devices ◽  
State Of The Art ◽  
Biomechanical Properties ◽  
Review Article ◽  
Implant Stability ◽  
Bone Implant ◽  
Current State ◽  
Mechanical Methods

In recent decades, cementless implants have been widely used in clinical practice to replace missing organs, to replace damaged or missing bone tissue or to restore joint functionality. However, there remain risks of failure which may have dramatic consequences. The success of an implant depends on its stability, which is determined by the biomechanical properties of the bone–implant interface (BII). The aim of this review article is to provide more insight on the current state of the art concerning the evolution of the biomechanical properties of the BII as a function of the implant's environment. The main characteristics of the BII and the determinants of implant stability are first introduced. Then, the different mechanical methods that have been employed to derive the macroscopic properties of the BII will be described. The experimental multi-modality approaches used to determine the microscopic biomechanical properties of periprosthetic newly formed bone tissue are also reviewed. Eventually, the influence of the implant's properties, in terms of both surface properties and biomaterials, is investigated. A better understanding of the phenomena occurring at the BII will lead to (i) medical devices that help surgeons to determine an implant's stability and (ii) an improvement in the quality of implants.

scholarly journals Elephants respond to resource trade-offs in an aseasonal system through daily and annual variability in resource selection

Koedoe ◽  
2017 ◽  
Vol 59 (1) ◽  
Author(s):  
Timothy J. Fullman ◽  
Gregory A. Kiker ◽  
Angela Gaylard ◽  
Jane Southworth ◽  
Peter Waylen ◽  
...  
Keyword(s):  
Resource Selection ◽  
Management Strategies ◽  
Rare Plants ◽  
Data Sets ◽  
Dynamic Selection ◽  
Daily Movement ◽  
Selection Strategies ◽  
Trade Offs ◽  
Selection Of ◽  
Annual Patterns

Animals and humans regularly make trade-offs between competing objectives. In Addo Elephant National Park (AENP), elephants (Loxodonta africana) trade off selection of resources, while managers balance tourist desires with conservation of elephants and rare plants. Elephant resource selection has been examined in seasonal savannas, but is understudied in aseasonal systems like AENP. Understanding elephant selection may suggest ways to minimise management trade-offs. We evaluated how elephants select vegetation productivity, distance to water, slope and terrain ruggedness across time in AENP and used this information to suggest management strategies that balance the needs of tourists and biodiversity. Resource selection functions with time-interacted covariates were developed for female elephants, using three data sets of daily movement to capture circadian and annual patterns of resource use. Results were predicted in areas of AENP currently unavailable to elephants to explore potential effects of future elephant access. Elephants displayed dynamic resource selection at daily and annual scales to meet competing requirements for resources. In summer, selection patterns generally conformed to those seen in savannas, but these relationships became weaker or reversed in winter. At daily scales, resource selection in the morning differed from that of midday and afternoon, likely reflecting trade-offs between acquiring sufficient forage and water. Dynamic selection strategies exist even in an aseasonal system, with both daily and annual patterns. This reinforces the importance of considering changing resource availability and trade-offs in studies of animal selection.Conservation implications: Guiding tourism based on knowledge of elephant habitat selection may improve viewing success without requiring increased elephant numbers. If AENP managers expand elephant habitat to reduce density, our model predicts where elephant use may concentrate and where botanical reserves may be needed to protect rare plants from elephant impacts.

scholarly journals OPWUM: Opportunistic MAC Protocol Leveraging Wake-Up Receivers in WSNs

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Fayçal Ait Aoudia ◽  
Matthieu Gautier ◽  
Olivier Berder
Keyword(s):  
Power Consumption ◽  
Analytical Study ◽  
State Of The Art ◽  
Mac Protocol ◽  
Promising Technique ◽  
Improve Energy Efficiency ◽  
Current State ◽  
Unreliable Links ◽  
Careful Design ◽  
Selection Of

Opportunistic forwarding has emerged as a promising technique to address the problem of unreliable links typical in wireless sensor networks and improve energy efficiency by exploiting multiuser diversity. Timer-based solutions, such as timer-based contention, form promising schemes to allow opportunistic next hop relay selection. However, they can incur significant idle listening and thus reduce the lifetime of the network. To tackle this problem, we propose to exploit emerging wake-up receiver technologies that have the potential to considerably reduce the power consumption of wireless communications. A careful design of MAC protocols is required to efficiently employ these new devices. In this work, we propose Opportunistic Wake-Up MAC (OPWUM), a novel multihop MAC protocol using timer-based contention. It enables the opportunistic selection of the best receiver among its neighboring nodes according to a given metric (e.g., the remaining energy), without requiring any knowledge about them. Moreover, OPWUM exploits emerging wake-up receivers to drastically reduce nodes power consumption. Through analytical study and exhaustive networks simulations, we show the effectiveness of OPWUM compared to the current state-of-the-art protocols using timer-based contention.

scholarly journals Long-read genome sequencing for the diagnosis of neurodevelopmental disorders

2020 ◽  
Author(s):  
Susan M. Hiatt ◽  
James M.J. Lawlor ◽  
Lori H. Handley ◽  
Ryne C. Ramaker ◽  
Brianne B. Rogers ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Neurodevelopmental Disorders ◽  
De Novo ◽  
Genomic Analysis ◽  
Data Sets ◽  
Short Read ◽  
Long Read ◽  
Variant Detection ◽  
Circular Consensus Sequencing

AbstractPurposeExome and genome sequencing have proven to be effective tools for the diagnosis of neurodevelopmental disorders (NDDs), but large fractions of NDDs cannot be attributed to currently detectable genetic variation. This is likely, at least in part, a result of the fact that many genetic variants are difficult or impossible to detect through typical short-read sequencing approaches.MethodsHere, we describe a genomic analysis using Pacific Biosciences circular consensus sequencing (CCS) reads, which are both long (>10 kb) and accurate (>99% bp accuracy). We used CCS on six proband-parent trios with NDDs that were unexplained despite extensive testing, including genome sequencing with short reads.ResultsWe identified variants and created de novo assemblies in each trio, with global metrics indicating these data sets are more accurate and comprehensive than those provided by short-read data. In one proband, we identified a likely pathogenic (LP), de novo L1-mediated insertion in CDKL5 that results in duplication of exon 3, leading to a frameshift. In a second proband, we identified multiple large de novo structural variants, including insertion-translocations affecting DGKB and MLLT3, which we show disrupt MLLT3 transcript levels. We consider this extensive structural variation likely pathogenic.ConclusionThe breadth and quality of variant detection, coupled to finding variants of clinical and research interest in two of six probands with unexplained NDDs strongly support the value of long-read genome sequencing for understanding rare disease.

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