scholarly journals Comparison of foot kinematics and the morphology of intrinsic musculature of the foot using a foot-type classification based on function

2020 ◽  
Vol 32 (3) ◽  
pp. 238-242
Author(s):  
Shintarou Kudo ◽  
Kodai Sakamoto ◽  
Takeshi Shirakawa
Keyword(s):  
Foot Kinematics ◽  
Type Classification ◽  
Intrinsic Musculature

scholarly journals Moroccan Video Intelligent Transport System: Vehicle Type Classification Based on Three-Dimensional and Two-Dimensional Features

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 72528-72537 ◽  
Author(s):  
Hatim Derrouz ◽  
Abderrahim Elbouziady ◽  
Hamd Ait Abdelali ◽  
Rachid Oulad Haj Thami ◽  
Sanaa El Fkihi ◽  
...  
Keyword(s):  
Transport System ◽  
Three Dimensional ◽  
Intelligent Transport System ◽  
Two Dimensional ◽  
Intelligent Transport ◽  
Vehicle Type ◽  
Vehicle Type Classification ◽  
Type Classification

scholarly journals When SEM becomes a deceptive tool of analysis: the unexpected discovery of epidermal glands with stalked ducts on the ultimate legs of geophilomorph centipedes

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Andy Sombke ◽  
Carsten H. G. Müller
Keyword(s):  
Sensory Function ◽  
Sexually Dimorphic ◽  
Non Invasive ◽  
Defensive Role ◽  
Transmission Electron ◽  
Sensory Structures ◽  
Taxonomic Studies ◽  
Invasive Techniques ◽  
Epidermal Glands ◽  
Intrinsic Musculature

Abstract Background The jointed appendage is a key novelty in arthropod evolution and arthropod legs are known to vary enormously in relation to function. Among centipedes, the ultimate legs always are distinctly different from locomotory legs, and different centipede taxa evolved different structural and functional modifications. In Geophilomorpha (soil centipedes), ultimate legs do not participate in locomotion and were interpret to serve a sensory function. They can be sexually dimorphic and in some species, male ultimate legs notably appear “hairy”. It can be assumed that the high abundance of sensilla indicates a pronounced sensory function. This study seeks for assessing the sensory diversity, however, documents the surprising and unique case of an extensive glandular epithelium in the ultimate legs of three phylogenetically distant species. Results The tightly aggregated epidermal glands with stalked ducts – mistakenly thought to be sensilla – were scrutinized using a multimodal microscopic approach comprising histology as well as scanning and transmission electron microscopy in Haplophilus subterraneus. Hence, this is the first detailed account on centipede ultimate legs demonstrating an evolutionary transformation into a “secretory leg”. Additionally, we investigated sensory structures as well as anatomical features using microCT analysis. Contrary to its nomination as a tarsus, tarsus 1 possesses intrinsic musculature, which is an indication that this podomere might be a derivate of the tibia. Discussion The presence and identity of ultimate leg associated epidermal glands with stalked ducts is a new discovery for myriapods. A pronounced secretory as well as moderate sensory function in Haplophilus subterraneus can be concluded. The set of characters will improve future taxonomic studies, to test the hypotheses whether the presence of these specialized glands is a common feature in Geophilomorpha, and that tarsus 1 may be a derivate of the tibia. As the number of epidermal glands with stalked ducts is sexually dimorphic, their function might be connected to reproduction or a sex-specific defensive role. Our results, in particular the unexpected discovery of ‘glandular hairs’, may account for a striking example for how deceptive morphological descriptions of epidermal organs may be, if based on non-invasive techniques alone.

scholarly journals Two-Pass Technique for Clone Detection and Type Classification Using Tree-Based Convolution Neural Network

2021 ◽  
Vol 11 (14) ◽  
pp. 6613
Author(s):  
Young-Bin Jo ◽  
Jihyun Lee ◽  
Cheol-Jung Yoo
Keyword(s):  
Neural Network ◽  
Average Rate ◽  
Convolution Neural Network ◽  
Clone Detection ◽  
Code Clones ◽  
Classification Technique ◽  
Development Costs ◽  
Code Quality ◽  
Type Information ◽  
Type Classification

Appropriate reliance on code clones significantly reduces development costs and hastens the development process. Reckless cloning, in contrast, reduces code quality and ultimately adds costs and time. To avoid this scenario, many researchers have proposed methods for clone detection and refactoring. The developed techniques, however, are only reliably capable of detecting clones that are either entirely identical or that only use modified identifiers, and do not provide clone-type information. This paper proposes a two-pass clone classification technique that uses a tree-based convolution neural network (TBCNN) to detect multiple clone types, including clones that are not wholly identical or to which only small changes have been made, and automatically classify them by type. Our method was validated with BigCloneBench, a well-known and wildly used dataset of cloned code. Our experimental results validate that our technique detected clones with an average rate of 96% recall and precision, and classified clones with an average rate of 78% recall and precision.

scholarly journals Identification of peat type and humification by laboratory VNIR/SWIR hyperspectral imaging of peat profiles with focus on fen-bog transition in aapa mires

2020 ◽  
Author(s):  
L. Granlund ◽  
M. Keinänen ◽  
T. Tahvanainen
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Support Vector ◽  
High Resolution Imaging ◽  
Factors Affecting ◽  
Vector Machines ◽  
Resolution Imaging ◽  
Shortwave Infrared ◽  
Type Classification ◽  
Wide Potential

Abstract Aims Hyperspectral imaging (HSI) has high potential for analysing peat cores, but methodologies are deficient. We aimed for robust peat type classification and humification estimation. We also explored other factors affecting peat spectral properties. Methods We used two laboratory setups: VNIR (visible to near-infrared) and SWIR (shortwave infrared) for high resolution imaging of intact peat profiles with fen-bog transitions. Peat types were classified with support vector machines, indices were developed for von Post estimation, and K-means clustering was used to analyse stratigraphic patterns in peat quality. With separate experiments, we studied spectral effects of drying and oxidation. Results Despite major effects, oxidation and water content did not impede robust HSI classification. The accuracy between Carex peat and Sphagnum peat in validation was 80% with VNIR and 81% with SWIR data. The spectral humification indices had accuracies of 82% with VNIR and 56%. Stratigraphic HSI patterns revealed that 36% of peat layer shifts were inclined by over 20 degrees. Spectral indices were used to extrapolate visualisations of element concentrations. Conclusions HSI provided reliable information of basic peat quality and was useful in visual mapping, that can guide sampling for other analyses. HSI can manage large amounts of samples to widen the scope of detailed analysis beyond single profiles and it has wide potential in peat research beyond the exploratory scope of this paper. We were able to confirm the capacity of HSI to reveal shifts of peat quality, connected to ecosystem-scale change.

scholarly journals Two Ensemble-CNN Approaches for Colorectal Cancer Tissue Type Classification

2021 ◽  
Vol 7 (3) ◽  
pp. 51
Author(s):  
Emanuela Paladini ◽  
Edoardo Vantaggiato ◽  
Fares Bougourzi ◽  
Cosimo Distante ◽  
Abdenour Hadid ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Deep Learning ◽  
Digital Pathology ◽  
Texture Features ◽  
Tissue Type ◽  
Cancer Tissue ◽  
Learning Methods ◽  
Feature Based ◽  
Type Classification ◽  
Whole Slide Images

In recent years, automatic tissue phenotyping has attracted increasing interest in the Digital Pathology (DP) field. For Colorectal Cancer (CRC), tissue phenotyping can diagnose the cancer and differentiate between different cancer grades. The development of Whole Slide Images (WSIs) has provided the required data for creating automatic tissue phenotyping systems. In this paper, we study different hand-crafted feature-based and deep learning methods using two popular multi-classes CRC-tissue-type databases: Kather-CRC-2016 and CRC-TP. For the hand-crafted features, we use two texture descriptors (LPQ and BSIF) and their combination. In addition, two classifiers are used (SVM and NN) to classify the texture features into distinct CRC tissue types. For the deep learning methods, we evaluate four Convolutional Neural Network (CNN) architectures (ResNet-101, ResNeXt-50, Inception-v3, and DenseNet-161). Moreover, we propose two Ensemble CNN approaches: Mean-Ensemble-CNN and NN-Ensemble-CNN. The experimental results show that the proposed approaches outperformed the hand-crafted feature-based methods, CNN architectures and the state-of-the-art methods in both databases.

scholarly journals IMU-Based Effects Assessment of the Use of Foot Orthoses in the Stance Phase during Running and Asymmetry between Extremities

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3277
Author(s):  
Juan Luis Florenciano Restoy ◽  
Jordi Solé-Casals ◽  
Xantal Borràs-Boix
Keyword(s):  
Contact Time ◽  
Stance Phase ◽  
Inertial Sensors ◽  
Sagittal Plane ◽  
Plantar Flexion ◽  
Foot Orthoses ◽  
Foot Kinematics ◽  
Running Injuries ◽  
The Right ◽  
Movement Differences

The objectives of this study were to determine the amplitude of movement differences and asymmetries between feet during the stance phase and to evaluate the effects of foot orthoses (FOs) on foot kinematics in the stance phase during running. In total, 40 males were recruited (age: 43.0 ± 13.8 years, weight: 72.0 ± 5.5 kg, height: 175.5 ± 7.0 cm). Participants ran on a running treadmill at 2.5 m/s using their own footwear, with and without the FOs. Two inertial sensors fixed on the instep of each of the participant’s footwear were used. Amplitude of movement along each axis, contact time and number of steps were considered in the analysis. The results indicate that the movement in the sagittal plane is symmetric, but that it is not in the frontal and transverse planes. The right foot displayed more degrees of movement amplitude than the left foot although these differences are only significant in the abduction case. When FOs are used, a decrease in amplitude of movement in the three axes is observed, except for the dorsi-plantar flexion in the left foot and both feet combined. The contact time and the total step time show a significant increase when FOs are used, but the number of steps is not altered, suggesting that FOs do not interfere in running technique. The reduction in the amplitude of movement would indicate that FOs could be used as a preventive tool. The FOs do not influence the asymmetry of the amplitude of movement observed between feet, and this risk factor is maintained. IMU devices are useful tools to detect risk factors related to running injuries. With its use, even more personalized FOs could be manufactured.

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