Correction to: A Range and Performance Optimized Version of the Computer‑Aided Speckle Interferometry Algorithm for Real‑Time Displacement‑Strain Field Monitoring

Physiotherapy is the trending medication for curing bone-related injuries and pain. In many cases, due to sudden jerks or accidents, the patient might suffer from severe pain. Therefore, it is the miracle medication for curing patients. The aim here is to build a framework using artificial intelligence and machine learning for providing patients with a digitalized system for physiotherapy. Even though various computer-aided assessment of physiotherapy rehabilitation exist, recent approaches for computer-aided monitoring and performance lack versatility and robustness. In the authors' approach is to come up with proposition of an application which will record patient physiotherapy exercises and also provide personalized advice based on user performance for refinement of therapy. By using OpenPose Library, the system will detect angle between the joints, and depending upon the range of motion, it will guide patients in accomplishing physiotherapy at home. It will also suggest to patients different physio-exercises. With the help of OpenPose, it is possible to render patient images or real-time video.

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Computer-Aided Software Engineering - An approach to real-time software development

10.2514/6.1989-2961 ◽

1989 ◽

Cited By ~ 1

Author(s):

CARRIE WALKER ◽

JOHN TURKOVICH

Keyword(s):

Software Engineering ◽

Software Development ◽

Real Time ◽

Computer Aided ◽

Computer Aided Software Engineering

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Breast Cancer Detection and Classification using Traditional Computer Vision Techniques: A Comprehensive Review

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405616666200406110547 ◽

2020 ◽

Vol 16 ◽

Cited By ~ 3

Author(s):

Saliha Zahoor ◽

Ikram Ullah Lali ◽

Muhammad Attique Khan ◽

Kashif Javed ◽

Waqar Mehmood

Keyword(s):

Breast Cancer ◽

Computer Aided Diagnosis ◽

Diagnose Breast Cancer ◽

Initial Stage ◽

Computer Aided ◽

Diagnosis And Classification ◽

And Performance ◽

Tools And Techniques ◽

Aided Diagnosis

: Breast Cancer is a common dangerous disease for women. In the world, many women died due to Breast cancer. However, in the initial stage, the diagnosis of breast cancer can save women's life. To diagnose cancer in the breast tissues there are several techniques and methods. The image processing, machine learning and deep learning methods and techniques are presented in this paper to diagnose the breast cancer. This work will be helpful to adopt better choices and reliable methods to diagnose breast cancer in an initial stage to survive the women's life. To detect the breast masses, microcalcifications, malignant cells the different techniques are used in the Computer-Aided Diagnosis (CAD) systems phases like preprocessing, segmentation, feature extraction, and classification. We have been reported a detailed analysis of different techniques or methods with their usage and performance measurement. From the reported results, it is concluded that for the survival of women’s life it is essential to improve the methods or techniques to diagnose breast cancer at an initial stage by improving the results of the Computer-Aided Diagnosis systems. Furthermore, segmentation and classification phases are challenging for researchers for the diagnosis of breast cancer accurately. Therefore, more advanced tools and techniques are still essential for the accurate diagnosis and classification of breast cancer.

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Computer-aided parametric prosthetic socket design based on real-time soft tissue deformation and an inverse approach

The Visual Computer ◽

10.1007/s00371-021-02059-9 ◽

2021 ◽

Author(s):

Abbass Ballit ◽

Imad Mougharbel ◽

Hassan Ghaziri ◽

Tien-Tuan Dao

Keyword(s):

Soft Tissue ◽

Real Time ◽

Tissue Deformation ◽

Soft Tissue Deformation ◽

Inverse Approach ◽

Prosthetic Socket ◽

Computer Aided

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Observer-based robust integral of the sign of the error control of class I of underactuated mechanical systems: Theory and real-time experiments

Transactions of the Institute of Measurement and Control ◽

10.1177/01423312211031396 ◽

2021 ◽

pp. 014233122110313

Author(s):

Afef Hfaiedh ◽

Ahmed Chemori ◽

Afef Abdelkrim

Keyword(s):

Real Time ◽

Error Control ◽

Degrees Of Freedom ◽

Sliding Mode ◽

Mechanical Systems ◽

Class I ◽

Control Input ◽

Underactuated Mechanical Systems ◽

Control Scheme ◽

And Performance

In this paper, the control problem of a class I of underactuated mechanical systems (UMSs) is addressed. The considered class includes nonlinear UMSs with two degrees of freedom and one control input. Firstly, we propose the design of a robust integral of the sign of the error (RISE) control law, adequate for this special class. Based on a change of coordinates, the dynamics is transformed into a strict-feedback (SF) form. A Lyapunov-based technique is then employed to prove the asymptotic stability of the resulting closed-loop system. Numerical simulation results show the robustness and performance of the original RISE toward parametric uncertainties and disturbance rejection. A comparative study with a conventional sliding mode control reveals a significant robustness improvement with the proposed original RISE controller. However, in real-time experiments, the amplification of the measurement noise is a major problem. It has an impact on the behaviour of the motor and reduces the performance of the system. To deal with this issue, we propose to estimate the velocity using the robust Levant differentiator instead of the numerical derivative. Real-time experiments were performed on the testbed of the inertia wheel inverted pendulum to demonstrate the relevance of the proposed observer-based RISE control scheme. The obtained real-time experimental results and the obtained evaluation indices show clearly a better performance of the proposed observer-based RISE approach compared to the sliding mode and the original RISE controllers.

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Experimental and computer aided solubility quantification of diverse lignins and performance prediction

Chemical Communications ◽

10.1039/d0cc04228e ◽

2021 ◽

Vol 57 (14) ◽

pp. 1782-1785

Author(s):

Olumoye Ajao ◽

Marzouk Benali ◽

Naïma El Mehdi

Keyword(s):

Performance Prediction ◽

Solvent Fractionation ◽

Computer Aided ◽

And Performance

New insights on the variability of solubility elucidated for diverse lignins, quantification thereby makes it possible to predict performance for solvent fractionation processes and polymers formulation.

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Passthrough+

Proceedings of the ACM on Computer Graphics and Interactive Techniques ◽

10.1145/3384540 ◽

2020 ◽

Vol 3 (1) ◽

pp. 1-17

Author(s):

Gaurav Chaurasia ◽

Arthur Nieuwoudt ◽

Alexandru-Eugen Ichim ◽

Richard Szeliski ◽

Alexander Sorkine-Hornung

Keyword(s):

Real Time ◽

Video Encoding ◽

View Synthesis ◽

Performance Constraints ◽

Trade Offs ◽

Stereoscopic View ◽

Target User ◽

Spatio Temporal ◽

And Performance ◽

3D Scene

We present an end-to-end system for real-time environment capture, 3D reconstruction, and stereoscopic view synthesis on a mobile VR headset. Our solution allows the user to use the cameras on their VR headset as their eyes to see and interact with the real world while still wearing their headset, a feature often referred to as Passthrough. The central challenge when building such a system is the choice and implementation of algorithms under the strict compute, power, and performance constraints imposed by the target user experience and mobile platform. A key contribution of this paper is a complete description of a corresponding system that performs temporally stable passthrough rendering at 72 Hz with only 200 mW power consumption on a mobile Snapdragon 835 platform. Our algorithmic contributions for enabling this performance include the computation of a coarse 3D scene proxy on the embedded video encoding hardware, followed by a depth densification and filtering step, and finally stereoscopic texturing and spatio-temporal up-sampling. We provide a detailed discussion and evaluation of the challenges we encountered, as well as algorithm and performance trade-offs in terms of compute and resulting passthrough quality.;AB@The described system is available to users as the Passthrough+ feature on Oculus Quest. We believe that by publishing the underlying system and methods, we provide valuable insights to the community on how to design and implement real-time environment sensing and rendering on heavily resource constrained hardware.

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Gaze awareness and metacognitive suggestions by a pedagogical conversational agent: an experimental investigation on interventions to support collaborative learning process and performance

International Journal of Computer-Supported Collaborative Learning ◽

10.1007/s11412-020-09333-3 ◽

2020 ◽

Vol 15 (4) ◽

pp. 469-498 ◽

Cited By ~ 1

Author(s):

Yugo Hayashi

Keyword(s):

Collaborative Learning ◽

Real Time ◽

Learning Process ◽

Common Ground ◽

Learning Performance ◽

Conversational Agent ◽

Learning Gains ◽

Computer Supported Collaborative Learning ◽

Collaborative Process ◽

And Performance

AbstractResearch on collaborative learning has revealed that peer-collaboration explanation activities facilitate reflection and metacognition and that establishing common ground and successful coordination are keys to realizing effective knowledge-sharing in collaborative learning tasks. Studies on computer-supported collaborative learning have investigated how awareness tools can facilitate coordination within a group and how the use of external facilitation scripts can elicit elaborated knowledge during collaboration. However, the separate and joint effects of these tools on the nature of the collaborative process and performance have rarely been investigated. This study investigates how two facilitation methods—coordination support via learner gaze-awareness feedback and metacognitive suggestion provision via a pedagogical conversational agent (PCA)—are able to enhance the learning process and learning gains. Eighty participants, organized into dyads, were enrolled in a 2 × 2 between-subject study. The first and second factors were the presence of real-time gaze feedback (no vs. visible gaze) and that of a suggestion-providing PCA (no vs. visible agent), respectively. Two evaluation methods were used: namely, dialog analysis of the collaborative process and evaluation of learning gains. The real-time gaze feedback and PCA suggestions facilitated the coordination process, while gaze was relatively more effective in improving the learning gains. Learners in the Gaze-feedback condition achieved superior learning gains upon receiving PCA suggestions. A successful coordination/high learning performance correlation was noted solely for learners receiving visible gaze feedback and PCA suggestions simultaneously (visible gaze/visible agent). This finding has the potential to yield improved collaborative processes and learning gains through integration of these two methods as well as contributing towards design principles for collaborative-learning support systems more generally.

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