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Keywords = symmetry and asymmetry loading

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19 pages, 2223 KiB  
Article
Transfer Learning-Based Steering Angle Prediction and Control with Fuzzy Signatures-Enhanced Fuzzy Systems for Autonomous Vehicles
by Ahmet Mehmet Karadeniz, Áron Ballagi and László T. Kóczy
Symmetry 2024, 16(9), 1180; https://doi.org/10.3390/sym16091180 - 9 Sep 2024
Cited by 1 | Viewed by 642
Abstract
This research introduces an innovative approach for End-to-End steering angle prediction and its control in electric power steering (EPS) systems. The methodology integrates transfer learning-based computer vision techniques for prediction and control with fuzzy signatures-enhanced fuzzy systems. Fuzzy signatures are unique multidimensional data [...] Read more.
This research introduces an innovative approach for End-to-End steering angle prediction and its control in electric power steering (EPS) systems. The methodology integrates transfer learning-based computer vision techniques for prediction and control with fuzzy signatures-enhanced fuzzy systems. Fuzzy signatures are unique multidimensional data structures that represent data symbolically. This enhancement enables the fuzzy systems to effectively manage the inherent imprecision and uncertainty in various driving scenarios. The ultimate goal of this work is to assess the efficiency and performance of this combined approach by highlighting the pivotal role of steering angle prediction and control in the field of autonomous driving systems. Specifically, within EPS systems, the control of the motor directly influences the vehicle’s path and maneuverability. A significant breakthrough of this study is the successful application of transfer learning-based computer vision techniques to extract respective visual data without the need for large datasets. This represents an advancement in reducing the extensive data collection and computational load typically required. The findings of this research reveal the potential of this approach within EPS systems, with an MSE score of 0.0386 against 0.0476, by outperforming the existing NVIDIA model. This result provides a 22.63% better Mean Squared Error (MSE) score than NVIDIA’s model. The proposed model also showed better performance compared with all other three references found in the literature. Furthermore, we identify potential areas for refinement, such as decreasing model loss and simplifying the complex decision model of fuzzy systems, which can represent the symmetry and asymmetry of human decision-making systems. This study, therefore, contributes significantly to the ongoing evolution of autonomous driving systems. Full article
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<p>VGG16 architecture.</p>
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<p>Example corresponding fuzzy signature tree.</p>
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<p>NVIDIA neural network training method.</p>
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<p>Our model architecture with VGG16.</p>
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<p>Algorithm flowchart of the complete system.</p>
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<p>System architecture of the overall system.</p>
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<p>Step motor Simulink model with fuzzy signatures-enhanced fuzzy system controller.</p>
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<p>Membership function “<span class="html-italic">u</span>”.</p>
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<p>Membership function “<math display="inline"><semantics> <mrow> <mo>Δ</mo> <mi>u</mi> </mrow> </semantics></math>”.</p>
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<p>Membership function “output” (as “<math display="inline"><semantics> <mi>θ</mi> </semantics></math>”).</p>
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<p>Rules surface of motor position (angle) for error and change in error.</p>
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<p>Fuzzy signatures tree used in this study.</p>
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<p>Fuzzy signature tree after aggregation.</p>
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<p>Experimental steps flow chart.</p>
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<p>Training and validation losses of the models.</p>
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9 pages, 221 KiB  
Article
Carrying Police Load Increases Gait Asymmetry in Ground Reaction Forces and Plantar Pressures Beneath Different Foot Regions in a Large Sample of Police Recruits
by Mario Kasović, Andro Štefan and Lovro Štefan
Bioengineering 2024, 11(9), 895; https://doi.org/10.3390/bioengineering11090895 - 5 Sep 2024
Viewed by 618
Abstract
Background: Although carrying external load has negative effects on gait biomechanics, little evidence has been provided regarding its impact on body asymmetry. The main purpose of the present study was to examine, whether standardized equipment produced greater gait asymmetries in ground reaction force [...] Read more.
Background: Although carrying external load has negative effects on gait biomechanics, little evidence has been provided regarding its impact on body asymmetry. The main purpose of the present study was to examine, whether standardized equipment produced greater gait asymmetries in ground reaction force and plantar pressure. Methods: For the purpose of this study, we recruited 845 police recruits (609 men and 236 women; 72.1% men and 27.9% women) measured in two conditions: (i) ‘no load’ and (ii) ‘a 3.5 kg load’. Absolute values in ground reaction forces and plantar pressures beneath the different foot regions were assessed with pedobarographic platform (Zebris FDM). Asymmetry was calculated as (xright − xleft)/0.5 × (xright + xleft) × 100%, where ‘x’ represented a given parameter being calculated and a value closer to 0 denoted greater symmetry. Results: Significant differences in ground reaction forces and plantar pressures between the left and right foot were observed, when adding ‘a 3.5 kg load’. Compared to the ‘no load’ condition, carrying ‘a 3.5 kg load’ significantly increased gait asymmetries for maximal ground reaction forces beneath the forefoot (ES = 0.29), midfoot (ES = 0.20) and hindfoot (ES = 0.19) regions of the foot. For maximal plantar pressures, only the asymmetry beneath the midfoot region of the foot significantly increased (ES = 0.19). Conclusions: Findings of this study indicate that ‘a 3.5 kg load’ significantly increases ground reaction force and plantar pressure gait asymmetries beneath the forefoot and midfoot regions, compared to ‘no load’ condition. Due to higher loads, increases in kinetic gait asymmetries may have negative effects on future pain and discomfort in the foot area, possibly causing stress fractures and deviated gait biomechanics in police recruits. Full article
(This article belongs to the Special Issue Biomechanics and Motion Analysis)
13 pages, 844 KiB  
Article
Associations between Racing Thoroughbred Movement Asymmetries and Racing and Training Direction
by Bronte Forbes, Winnie Ho, Rebecca S. V. Parkes, Maria Fernanda Sepulveda Caviedes, Thilo Pfau and Daniel R. Martel
Animals 2024, 14(7), 1086; https://doi.org/10.3390/ani14071086 - 3 Apr 2024
Cited by 1 | Viewed by 1137
Abstract
Background: Racehorses commonly train and race in one direction, which may result in gait asymmetries. This study quantified gait symmetry in two cohorts of Thoroughbreds differing in their predominant exercising direction; we hypothesized that there would be significant differences in the direction of [...] Read more.
Background: Racehorses commonly train and race in one direction, which may result in gait asymmetries. This study quantified gait symmetry in two cohorts of Thoroughbreds differing in their predominant exercising direction; we hypothesized that there would be significant differences in the direction of asymmetry between cohorts. Methods: 307 Thoroughbreds (156 from Singapore Turf Club (STC)—anticlockwise; 151 from Hong Kong Jockey Club (HKJC)—clockwise) were assessed during a straight-line, in-hand trot on firm ground with inertial sensors on their head and pelvis quantifying differences between the minima, maxima, upward movement amplitudes (MinDiff, MaxDiff, UpDiff), and hip hike (HHD). The presence of asymmetry (≥5 mm) was assessed for each variable. Chi-Squared tests identified differences in the number of horses with left/right-sided movement asymmetry between cohorts and mixed model analyses evaluated differences in the movement symmetry values. Results: HKJC had significantly more left forelimb asymmetrical horses (Head: MinDiff p < 0.0001, MaxDiff p < 0.03, UpDiff p < 0.01) than STC. Pelvis MinDiff (p = 0.010) and UpDiff (p = 0.021), and head MinDiff (p = 0.006) and UpDiff (p = 0.017) values were significantly different between cohorts; HKJC mean values indicated left fore- and hindlimb asymmetry, and STC mean values indicated right fore- and hindlimb asymmetry. Conclusion: the asymmetry differences between cohorts suggest that horses may adapt their gait to their racing direction, with kinematics reflecting reduced ‘outside’ fore- and hindlimb loading. Full article
(This article belongs to the Section Equids)
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<p>Count of asymmetrical horses identified from poll sensor asymmetry measures which included vertical displacement minimum difference (MinDiff), vertical displacement maximum difference (MaxDiff), and upward displacement amplitude difference (UpDiff) (blue = Hong Kong Jockey Club, HKJC, Orange = Singapore Turf Club, STC, Solid = Right, Hashed = Left), * denotes significance level of <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Count of asymmetrical horses identified from pelvis sensor asymmetry measures which included vertical displacement minimum difference (MinDiff), vertical displacement maximum difference (MaxDiff), an upward displacement amplitude difference (UpDiff), and hip hike difference (HHD) (blue = Hong Kong Jockey Club, HKJC, Orange = Singapore Turf Club, STC, Solid = Right, Hashed = Left), * denotes significance level of <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Mean asymmetry metric differences between cohorts for the asymmetry measures which included vertical displacement minimum difference (MinDiff), vertical displacement maximum (MaxDiff), upward displacement amplitude difference (UpDiff) for the head and pelvis, and hip hike difference (HHD) for the pelvis (Hong Kong Jockey Club−Singapore Turf Club; HKJC−STC) based on sensor location and asymmetry measure (blue = Pelvis, Orange = Poll), * denotes significance level of <span class="html-italic">p</span> &lt; 0.05.</p>
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12 pages, 3104 KiB  
Article
Seat Pressure Asymmetries after Cycling at Constant Intensity
by Laura Lepasalu, Jaan Ereline, Märt Reinvee and Mati Pääsuke
Symmetry 2024, 16(3), 270; https://doi.org/10.3390/sym16030270 - 24 Feb 2024
Viewed by 1001
Abstract
The aim of this study was to compare seat pressure asymmetries before and after 30 min cycling at constant intensity in association with pelvic anthropometric parameters and skeletal muscle fatigue. Twelve male road cyclists aged 18–30 years (mean training experience 9.9 ± 2.5 [...] Read more.
The aim of this study was to compare seat pressure asymmetries before and after 30 min cycling at constant intensity in association with pelvic anthropometric parameters and skeletal muscle fatigue. Twelve male road cyclists aged 18–30 years (mean training experience 9.9 ± 2.5 years) participated. Pelvic anthropometric data and body composition were measured with dual-energy X-ray absorptiometry. Participants performed 30 min cycling at 50% peak power output at constant intensity on a cyclus-2 ergometer. Muscle fatigue during cycling was assessed by surface electromyogram spectral mean power frequency (MPF) for the back, gluteal, and thigh muscles. The pressure mapping system was used to assess sitting symmetry before and after the cycling exercise. At the end of cycling, MPF was decreased (p < 0.05) in the dominant side’s erector spinae muscle and the contralateral gluteal muscle. After the exercise, a significant (p < 0.05) asymmetry in seat pressure was observed under the ischial tuberosity based on the peak pressure right to left ratio, whereas peak pressure decreased under the left ischial tuberosity. After the exercise, the relationship (p < 0.05) between pelvis width and pressure under the ischial tuberosity occurred on the dominant side of the body. In conclusion, an asymmetry was revealed after the constant-load cycling exercise by peak pressure ratio right to left side. Further studies should address the role of seat pressure asymmetries before and after cycling exercises at different intensities and durations. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Sport Sciences)
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<p>Experimental design of this study. VO<sub>2max</sub>—highest level of oxygen uptake; W<sub>peak</sub>—peak power output; DEXA—dual energy X-ray absorptiometry; sEMG—surface electromyography.</p>
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<p>An example assessment of pelvis height and width and ischial tuberosity size of male road cyclists using a DXA machine (<b>a</b>) and cyclist position on the table during assessment of sitting distribution with a pressure mapping device (<b>b</b>).</p>
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<p>Pressure mapping illustrates distribution of contact area of four horizontal regions (right and left femoral (F), and right and left gluteal (G) parts) after exercise in one participant. (<b>a</b>) Distribution of contact area in %; (<b>b</b>) distribution of contact area in N/cm<sup>2</sup>. Red indicates peak pressure area; orange, yellow, green, blue and black indicate decreasing pressure areas.</p>
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<p>Mean (±SD) peak pressure under right ischial tuberosity and left ischial tuberosity before and after 30 min constant-load cycling exercise in male road cyclists (<span class="html-italic">n</span> = 12). * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Mean (±SD) gluteal mean pressure before and after 30 min constant-load cycling exercise in male road cyclists (<span class="html-italic">n</span> = 12). * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Mean (±SD) peak pressure ratio right to left before and after 30 min constant-load cycling exercise in male road cyclists (<span class="html-italic">n</span> = 12). *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Correlations with maximum pedal force during the cycling exercise; ischial tuberosity size and skeletal muscle fatigue. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Mean (±SD) distribution of contact area of the left and right gluteal area, and left and right femoral area. There were no significant differences in distribution of contact area before and after the exercise.</p>
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25 pages, 10463 KiB  
Article
Electromagnetic Performance Analysis of a Multichannel Permanent Magnet Synchronous Generator
by Mariusz Korkosz, Elżbieta Sztajmec and Jan Prokop
Energies 2023, 16(23), 7816; https://doi.org/10.3390/en16237816 - 28 Nov 2023
Viewed by 808
Abstract
In this paper, we present an analysis of the properties of the prototype three-phase Multichannel Permanent Magnet Synchronous Generator (MCPMSG) prototype designed and constructed by the authors. Each channel of the generator has electrically separated windings, which allows us to create an island [...] Read more.
In this paper, we present an analysis of the properties of the prototype three-phase Multichannel Permanent Magnet Synchronous Generator (MCPMSG) prototype designed and constructed by the authors. Each channel of the generator has electrically separated windings, which allows us to create an island system of electricity generation. The analyzed MCPMSG is intended for critical applications, and it is designed for four-channel operation. The purpose of this work is to analyze various configurations of the generator channels to improve the redundancy of the electricity generation system. The MCPMSG operation with one or two independent sources of energy consumption in the case of a dual-channel or double dual-channel operation was investigated. For the analyzed cases, the original mathematical models of the three-phase MCPMSG were developed. On the basis of numerical and laboratory tests, the influence of individual configurations on the MCPMSG output parameters was determined. An original method for diagnosing the operation of the MCPMSG channels was developed. Numerical and laboratory tests of the proposed diagnostic method based on a single voltage signal were carried out. As part of the laboratory tests, selected operating states under conditions of full winding symmetry and internal asymmetry were analyzed. The advantage of the proposed diagnostic method is the control of the operating state of the channels both under load and in the de-energized state. The proposed diagnostic method for control of the individual channel requires measurement of only one voltage signal. Full article
(This article belongs to the Topic Advanced Electrical Machines and Drives Technologies)
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<p>Multichannel MCPMSG: (<b>a</b>) cross-section, (<b>b</b>) prototype.</p>
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<p>Diagram of the connection of windings of conventional channel A.</p>
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<p>Phase EMF waveforms of the MCPMSG.</p>
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<p>Analyzed configurations of the channels of the generator operating with one source of energy consumption.</p>
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<p>Analyzed configurations of the generator channels operating with two independent energy-receiving sources.</p>
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<p>Test stand.</p>
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<p>Self- and mutual inductance for (<b>a</b>) SCO A, (<b>b</b>) DCO AB, and DCO AC.</p>
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<p>Electromagnetic torque for DCO AB and DCO AC for one source of energy consumption.</p>
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<p>Current waveforms for (<b>a</b>) DCO AB and (<b>b</b>) DCO AC.</p>
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<p>External characteristics for (<b>a</b>) numerical test, (<b>b</b>) laboratory test for DCO AB, and (<b>c</b>) laboratory test for DCO AC.</p>
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<p>External characteristics for (<b>a</b>) numerical test, (<b>b</b>) laboratory test for DCO AB, and (<b>c</b>) laboratory test for DCO AC.</p>
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<p>RMS channel current vs. RMS line current for (<b>a</b>) DCO AB and (<b>b</b>) DCO AC.</p>
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<p>RMS channel current vs. RMS line current for (<b>a</b>) DCO AB and (<b>b</b>) DCO AC.</p>
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<p>Electromagnetic torque for the DDCO AB/CD and the DDCO AC/BD for two independent sources of energy consumption.</p>
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<p>Current waveforms for (<b>a</b>) DDCO AB/CD and (<b>b</b>) DDCO AC/BD for two independent sources of energy consumption.</p>
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<p>Output power vs. RMS value of current of the DDCO AB/CD at <span class="html-italic">U<sub>dc</sub></span><sup>CD</sup> = const and DDCO AC/BD at <span class="html-italic">U<sub>dc</sub></span><sup>BD</sup> = const.</p>
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<p>Proposition for the location of the diagnostic voltage signal by using the MCPMSG.</p>
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<p>Diagnostic voltage signal <span class="html-italic">u</span><sub>0I</sub> of DCO—numerical calculations.</p>
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<p>Diagnostic voltage signal <span class="html-italic">u</span><sub>0I</sub> of DCO—laboratory test.</p>
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<p>FFT of the diagnostic voltage signal <span class="html-italic">u</span><sub>0I</sub>—numerical calculations.</p>
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<p>FFT of diagnostic voltage signal <span class="html-italic">u</span><sub>0I</sub>—laboratory test.</p>
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4555 KiB  
Proceeding Paper
Research on Asymmetrical Reinforced Concrete Low-Rise Frames under Multiple Seismic Events
by Paraskevi K. Askouni
Eng. Proc. 2023, 53(1), 29; https://doi.org/10.3390/IOCBD2023-15191 - 24 Oct 2023
Cited by 1 | Viewed by 613
Abstract
Current seismic regulations neglect the influence of multiple seismic events on the seismic response, which, as already recognized in the literature, may influence the seismic behavior of reinforced concrete structures. Symmetrical and asymmetrical low-rise reinforced concrete frames are investigated here via nonlinear time-history [...] Read more.
Current seismic regulations neglect the influence of multiple seismic events on the seismic response, which, as already recognized in the literature, may influence the seismic behavior of reinforced concrete structures. Symmetrical and asymmetrical low-rise reinforced concrete frames are investigated here via nonlinear time-history (NLTH) analysis considering multiple earthquake events, as well as under a respective single seismic event, for comparison purposes. The two horizontal directions, as well as the vertical one, of the ground excitation are considered in the dynamic analysis, assuming the elastoplastic action of reinforced concrete sections under heavy loading. A simple ratio is defined to express the geometrical in-plane asymmetry of the buildings. The nonlinear response outcomes of the time-history analyses are appropriately plotted by using unitless parameters for an objective estimation of the structural behavior under multiple earthquakes. The dimensionless response results and plots are presented and discussed in view of the relative geometrical asymmetry of the 3D frames. The effect of the multiple seismic events, as well as the one of a simple geometrical symmetry/asymmetry, is identified and discussed in the presented plots resulting from the dynamic analysis. Thus, practical remarks are presented regarding the significance of the in-plane symmetry/asymmetry of frames for improvements in the provisions of the current seismic regulations to develop safer structures. Full article
(This article belongs to the Proceedings of The 1st International Online Conference on Buildings)
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<p>Asymmetrical RC buildings with (<b>a</b>) one story and (<b>b</b>) three stories.</p>
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<p>(<b>a</b>) Interstory drift ratio on X, θ = 45°, (<b>b</b>) interstory drift ratio on Y, θ = 0°.</p>
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<p>(<b>a</b>) Residual interstory drift ratio on X, θ = 90°, (<b>b</b>) residual interstory drift ratio on Y, θ = 90°.</p>
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<p>(<b>a</b>) Interstory drift ratio on <span class="html-italic">X</span> axis, θ = 0°, (<b>b</b>) interstory drift ratio on <span class="html-italic">Y</span> axis, θ = 90°, 1st story.</p>
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<p>(<b>a</b>) Interstory drift ratio on <span class="html-italic">X</span> axis, θ = 0°, (<b>b</b>) interstory drift ratio on <span class="html-italic">Y</span> axis, θ = 90°, 2nd story.</p>
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<p>(<b>a</b>) Interstory drift ratio on <span class="html-italic">X</span> axis, θ = 90°, (<b>b</b>) interstory drift ratio on <span class="html-italic">Y</span> axis, θ = 90°, 3rd story.</p>
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<p>(<b>a</b>) Residual interstory drift ratio on <span class="html-italic">X</span> axis, θ = 45°, (<b>b</b>) residual interstory drift ratio on <span class="html-italic">Y</span> axis, θ = 45°, 1st story.</p>
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<p>(<b>a</b>) Residual interstory drift ratio on <span class="html-italic">X</span> axis, θ = 45°, (<b>b</b>) residual interstory drift ratio on <span class="html-italic">Y</span> axis, θ = 0°, 3rd story.</p>
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10 pages, 1246 KiB  
Article
Mechanical Asymmetries during Treadmill Running: Effects of Running Velocity and Hypoxic Exposure
by Chris Chow Li Tee, Mee Chee Chong, Viswanath Sundar, Chuen Leang Chok, Wee Kian Yeo and Olivier Girard
Symmetry 2023, 15(7), 1303; https://doi.org/10.3390/sym15071303 - 23 Jun 2023
Cited by 1 | Viewed by 1738
Abstract
Studies evaluating mechanical asymmetry across a range of running velocities during treadmill runs have yielded inconsistent findings, while the impact of additional hypoxic exposure has never been investigated. The aim of this study was to characterize the effects of manipulating running velocity and [...] Read more.
Studies evaluating mechanical asymmetry across a range of running velocities during treadmill runs have yielded inconsistent findings, while the impact of additional hypoxic exposure has never been investigated. The aim of this study was to characterize the effects of manipulating running velocity and hypoxic exposure on gait asymmetry during treadmill running. Eleven trained individuals performed seven runs at different velocities (8, 10, 12, 14, 16, 18, and 20 km·h−1) in a randomized order, each lasting 45 s. The running took place on an instrumented treadmill for normoxia (FiO2 = 20.9%), moderate hypoxia (FiO2 = 16.1%), high hypoxia (FiO2 = 14.1%), and severe hypoxia (FiO2 = 13.0%). Vertical and antero-posterior ground reaction force recordings over 20 consecutive steps (i.e., after running ∼25 s) allowed the measurement of running mechanics. Lower-limb asymmetry was assessed from the ‘symmetry angle’ (SA) score. Two-way repeated-measures ANOVA (seven velocities × four conditions) was used. There was no significant difference in SA scores for any of the biomechanical variables for velocity (except contact time and braking phase duration; p = 0.003 and p = 0.002, respectively), condition, or interaction. Mean SA scores varied between ∼1% and 2% for contact time (1.5 ± 0.8%), flight time (1.6 ± 0.6%), step length (0.8 ± 0.2%), peak vertical force (1.2 ± 0.5%), and mean vertical loading rate (2.1 ± 1.0%). Mean SA scores ranged from ∼2% to 5% for duration of braking (1.6 ± 0.7%) and push-off phases (1.9 ± 0.6%), as well as peak braking (5.0 ± 1.9%) and push-off forces (4.8 ± 1.7%). In conclusion, the trained runners exhibited relatively even strides, with mechanical asymmetries remaining low-to-moderate across a range of submaximal, constant running velocities (ranging from 8 to 20 km·h−1) and varying levels of hypoxia severity (between normoxia and severe hypoxia). Full article
(This article belongs to the Special Issue Biology and Symmetry/Asymmetry:Feature Papers 2022)
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<p>Symmetry angle scores (%) for (<b>A</b>) contact time, (<b>B</b>) flight time, (<b>C</b>) step length, (<b>D</b>) peak vertical force, and (<b>E</b>) mean vertical loading rate at seven running velocities and four altitude conditions. Values are means ± SDs (<span class="html-italic">n</span> = 11). White bars = normoxia (NM); light grey bars = moderate hypoxia (MH); dark grey bars = high hypoxia (HH); black bars = severe hypoxia. ANOVA main effects of condition, velocity, and interaction are stated along with partial eta-squared values for effect sizes in brackets with significant effects (<span class="html-italic">p</span> &lt; 0.05). * denotes a statistically significant difference (<span class="html-italic">p</span> &lt; 0.05) compared to 8 km·h<sup>−1</sup>.</p>
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<p>Symmetry angle scores (%) for (<b>A</b>) braking phase duration, (<b>B</b>) push-off phase duration, (<b>C</b>) peak braking force, and (<b>D</b>) peak push-off force at seven running velocities and four altitude conditions. Values are means ± SDs (<span class="html-italic">n</span> = 11). White bars = normoxia (NM); light grey bars = moderate hypoxia (MH); dark grey bars = high hypoxia (HH); black bars = severe hypoxia. ANOVA main effects of condition, velocity and interaction are stated along with partial eta-squared values for effect sizes in brackets with significant effects (<span class="html-italic">p</span> &lt; 0.05).</p>
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17 pages, 3924 KiB  
Article
Overground Robotic Gait Trainer mTPAD Improves Gait Symmetry and Weight Bearing in Stroke Survivors
by Danielle Marie Stramel, Lauren Winterbottom, Joel Stein and Sunil K. Agrawal
Bioengineering 2023, 10(6), 698; https://doi.org/10.3390/bioengineering10060698 - 8 Jun 2023
Cited by 3 | Viewed by 2158
Abstract
Stroke is a leading cause of disability, impairing the ability to generate propulsive forces and causing significant lateral gait asymmetry. We aim to improve stroke survivors’ gaits by promoting weight-bearing during affected limb stance. External forces can encourage this; e.g., vertical forces can [...] Read more.
Stroke is a leading cause of disability, impairing the ability to generate propulsive forces and causing significant lateral gait asymmetry. We aim to improve stroke survivors’ gaits by promoting weight-bearing during affected limb stance. External forces can encourage this; e.g., vertical forces can augment the gravitational force requiring higher ground reaction forces, or lateral forces can shift the center of mass over the stance foot, altering the lateral placement of the center of pressure. With our novel design of a mobile Tethered Pelvic Assist Device (mTPAD) paired with the DeepSole system to predict the user’s gait cycle percentage, we demonstrate how to apply three-dimensional forces on the pelvis without lower limb constraints. This work is the first result in the literature that shows that with an applied lateral force during affected limb stance, the center of pressure trajectory’s lateral symmetry is significantly closer to a 0% symmetry (5.5%) than without external force applied (9.8%,p<0.05). Furthermore, the affected limb’s maximum relative pressure (p) significantly increases from 233.7p to 234.1p (p<0.05) with an applied downward force, increasing affected limb loading. This work highlights how the mTPAD increases weight-bearing and propulsive forces during gait, which is a crucial goal for stroke survivors. Full article
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<p>Illustrative diagram for the mTPAD’s open-loop controller and the mTPAD system. <math display="inline"><semantics> <msub> <mi>A</mi> <mi>i</mi> </msub> </semantics></math> maps the servo angle to the cable length for each motor. The pelvis position relative to the mTPAD frame is determined using forward kinematics [<a href="#B44-bioengineering-10-00698" class="html-bibr">44</a>]. The pelvis position and the goal wrench are input to the quadratic programmer used to optimize cable tensions. <math display="inline"><semantics> <msub> <mi>B</mi> <mi>i</mi> </msub> </semantics></math> maps the cable tensions to the servo currents. A low-level PID controller is implemented on the servo currents at the motor level.</p>
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<p>Forces applied to the pelvis and their associated quadratic programming wrench constraints. Here, <span class="html-italic">x</span> refers to the mediolateral axis and <span class="html-italic">z</span> refers to the vertical axis. For the lateral force, <math display="inline"><semantics> <msub> <mi>F</mi> <mi>x</mi> </msub> </semantics></math> is limited within a small range of <math display="inline"><semantics> <mrow> <msub> <mi>F</mi> <mrow> <mi>g</mi> <mi>o</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>±</mo> <mn>0.5</mn> </mrow> </semantics></math> N. All other forces and moments are limited within <math display="inline"><semantics> <mrow> <mo>±</mo> <mn>5</mn> </mrow> </semantics></math> N or Nm. These ranges were selected to minimize forces in other directions while ensuring that the goal lateral and downward forces could be achieved by the mTPAD’s controller. Similarly for the downward force, <math display="inline"><semantics> <msub> <mi>F</mi> <mi>z</mi> </msub> </semantics></math> is limited within <math display="inline"><semantics> <mrow> <mo>±</mo> <mn>0.5</mn> </mrow> </semantics></math> N from <math display="inline"><semantics> <msub> <mi>F</mi> <mrow> <mi>g</mi> <mi>o</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> </semantics></math>. The orange arrows depict the frontal plane pelvic forces that are applied by the mTPAD. The blue arrows depict the cable tensions, with the relative size representing the relative tension required to apply the pelvic forces. These pelvic forces are synchronized with the user’s gait cycle percentage corresponding to single stance. All seven cables are actuated to minimize all other forces and moments.</p>
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<p>Experimental setup for the single session experiment evaluating effects of external forces applied to the pelvis on the gait of stroke survivors. (<b>A</b>) The DeepSole system sent the predicted gait cycle percentage to the mTPAD in real time. The predicted GCP of the affected side was an input to the mTPAD’s open-loop controller, which outputs each cable’s optimized tension. These data were time synchronized with the instrumented mat via UDP. (<b>B</b>) The front view of the mTPAD illustrates the local coordinate frame used and the seven cables that route from the frame to the pelvic belt. (<b>C</b>) A participant is walking overground in the mTPAD. Each participant walked on a Zeno Walkway. The DeepSole system is outlined in blue and the mTPAD pelvic belt is highlighted in green.</p>
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<p>The top graph illustrates the theoretical gait cycle percentage as a sawtooth function for two full gait cycles. The lower graph shows the corresponding goal force magnitude calculated by Equation (3) for a 70-kg adult. At the affected side heel strikes, shown here as 0% and 100%, the force magnitude increases to a peak of 70 Newtons at 25% and 125%. After these points, the magnitude decreases and reaches 0 Newtons at 50% and 150% of the gait cycle.</p>
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<p>COP Cyclogram and Cyclogram Characteristics. (<b>A</b>) A symmetric COP cyclogram with gait event labels. The <span class="html-italic">x</span>-axis of the cyclogram is the ML direction, and the <span class="html-italic">y</span>-axis is the AP direction. The SS (vertical) COP trajectories along the left and right feet are approximately the same length. The CISP, represented by a red circle, lies approximately at (0,0) on the cyclogram. This means the individual can comparably progress their center of mass forward during their left and right stances. (<b>B</b>) An asymmetric COP cyclogram with labeled characteristics. The right foot’s COP traveled distance is shorter than the left foot’s, forcing the ML CISP laterally toward the affected side. This illustrates that the individual’s ability to propel themselves forward during their single right stance is impaired compared to the left side. Therefore, the lateral placement of the CISP on the COP cyclogram represents the symmetry of generated single-stance GRFs and the overall COP trajectory.</p>
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<p>An illustration of the protocol used in this work. The protocol started with a gait Baseline. The DeepSole and Mat data were then used to retrain the ERM model. This new prediction model was used for the last three sessions. By retraining the model with each participant’s gait Baseline, the prediction is tailored to their gait and has training data with irregular or asymmetric gait cycles.</p>
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<p>The <span class="html-italic">x</span>-axis is the gait cycle percentage segmented by right heel strikes. The <span class="html-italic">y</span>-axis is the pressure of the affected (right foot, bottom plot) and non-affected (left foot, top plot) feet. The solid lines represent each condition’s average pressure curve for all strides for this participant, and the shaded regions around each line represent the standard deviations.</p>
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<p>ML CISP Percentage per Condition. The left plots represent the lateral force, and the right plots show the downward force. The left plot in each set shows the group differences. The right plot in each set shows the mean and standard deviation per participant, where each color denotes a different participant. The following notation is used for statistical comparisons: *: <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.05</mn> </mrow> </semantics></math>; **: <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.01</mn> </mrow> </semantics></math>; and ***: <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.001</mn> </mrow> </semantics></math>.</p>
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<p>Non-Affected and Affected Max Pressure per Condition. (<b>A</b>) Non-affected side foot pressure per force condition. The top row represents the lateral force, and the bottom row shows the downward force. The left column shows the group differences. The right column shows the mean and standard deviation per participant. (<b>B</b>) Affected side foot pressure per force condition. The top row represents the lateral force, and the bottom row shows the downward force. The left column shows the group differences. The right column shows the mean and standard deviation per participant, where each color denotes a different participant. The following notation is used for statistical comparisons: *: <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.05</mn> </mrow> </semantics></math>; **: <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.01</mn> </mrow> </semantics></math>; and ***: <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.001</mn> </mrow> </semantics></math>.</p>
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<p>Free Body Diagram with External Applied Forces to the Pelvis. Basic free body diagram for the center of mass while in single stance, as an inverted pendulum. The first segment, i.e., the leg body, shows the external and internal forces on the leg, balancing the gravitational force applied at the center of mass. The second segment, i.e., the foot body, shows the equal but opposite forces and moments at the ankle and the location and magnitude of the ground reaction force created. This model illustrates that if <math display="inline"><semantics> <mrow> <msub> <mi>F</mi> <mrow> <mi>e</mi> <mi>x</mi> </mrow> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, the COP is the projection of the COM onto the horizontal plane.</p>
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12 pages, 642 KiB  
Article
Lower Limb Unilateral and Bilateral Strength Asymmetry in High-Level Male Senior and Professional Football Players
by Mário C. Espada, Marco Jardim, Rafael Assunção, Alexandre Estaca, Cátia C. Ferreira, Dalton M. Pessôa Filho, Carlos E. L. Verardi, José M. Gamonales and Fernando J. Santos
Healthcare 2023, 11(11), 1579; https://doi.org/10.3390/healthcare11111579 - 28 May 2023
Cited by 6 | Viewed by 3664
Abstract
This study sought to assess the relationship between different jumping asymmetries and associated performance variables in high-level male senior and professional football players. Nineteen football players with at least 12 years of training experience (23.2 ± 3.1 years of age; 75.2 ± 4.8 [...] Read more.
This study sought to assess the relationship between different jumping asymmetries and associated performance variables in high-level male senior and professional football players. Nineteen football players with at least 12 years of training experience (23.2 ± 3.1 years of age; 75.2 ± 4.8 kg of body mass and 181 ± 0.06 cm of height) participated in this study performing countermovement jump (CMJ), squat jump (SJ), single-leg CMJ and drop jump (DJ), associated performance variable eccentric utilization ratio (EUR), stretch-shortening cycle (SSC), bilateral deficit (BLD), and limb symmetry index (LSI) were determined. High correlations were observed between different methodologies of jump tests and associated performance indicators (SSC, BLD, EUR), except LSI. Moreover, CMJ and SJ results were different (p < 0.05), but no differences were found between interlimb in CMJ (p = 0.19) and DJ (p = 0.14). Between the same limbs and different jumps differences were detected in CMJ and DJ (p < 0.01), and it has also been found that the laterality effect size on strength was small in CMJ (ES = 0.30) and DJ (ES = 0.35). LSI between CMJ and DJ was not different despite higher mean values in CMJ, and although mean BLD was positive (>100%), the results highlight the need for individual evaluation since eight players scored negatively. An in-depth and accurate analysis of performance in preseason screening jump tests should be considered, aiming to detect injury risk, specifically evaluating different jumping test methodologies, and determining jumping associated performance variables for each test, namely EUR, SSC, BLD, and LSI. Specific muscle-strengthening exercises could be implemented based on this study results and outcomes, aiming to reduce injury risks and lower extremity asymmetries and to enhance individual football performance in high-level male senior and professional football players. Sports institutions should pay special attention regarding potential health problems in athletes exposed to daily high training loads. Full article
(This article belongs to the Special Issue Improving Athletes’ Performance and Avoiding Health Issues)
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<p>Linear regression of squat jump and countermovement jump on eccentric utilization ratio.</p>
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29 pages, 8166 KiB  
Article
A State Machine-Based Droop Control Method Aided with Droop Coefficients Tuning through In-Feasible Range Detection for Improved Transient Performance of Microgrids
by Mandarapu Srikanth and Yellapragada Venkata Pavan Kumar
Symmetry 2023, 15(1), 1; https://doi.org/10.3390/sym15010001 - 20 Dec 2022
Cited by 7 | Viewed by 2581
Abstract
 The cascaded droop-voltage-current controller plays a key role in the effective operation of microgrids, where the controller performance is critically impacted by the desigheme, a constant value n of the droop controller. Moreover, in critical loading (e.g.: connection/disconnection of large inductive load), the [...] Read more.
 The cascaded droop-voltage-current controller plays a key role in the effective operation of microgrids, where the controller performance is critically impacted by the desigheme, a constant value n of the droop controller. Moreover, in critical loading (e.g.: connection/disconnection of large inductive load), the pre-set value of the droop coefficient brings asymmetry in transient performance leading to instability. Hence, to improve symmetry by reducing the trade-off between transient response and stability margin, this paper proposes a state machine-based droop control method (SMDCM) aided with droop coefficients’ tuning through in-feasible range detection. Here, to realize the issues and the role of the droop controller’s dynamics on the microgrid’s stability, a small-signal stability analysis is conducted, thereby, an in-feasible range of droop values is identified. Accordingly, safe values for droop coefficients are implemented using the state machine concept. This proposed SMDCM is compared with the conventional constant droop control method (CDCM) and fuzzy logic-based droop control method (FLDCM) in terms of frequency/power/voltage characteristics subjected to different power factor (PF) loading conditions. From the results, it is seen that CDCM failed in many metrics under moderate and poor PF loadings. FLDCM is satisfactory under moderate PF loading, but, showed 54 Hz/48 Hz as maximum/minimum frequency values during poor PF loading. These violate the standard limit of ±2%, but SMDCM satisfactorily showed 50.02 Hz and 49.8 Hz, respectively. Besides, FLDCM levied an extra burden of 860 W on the system while it is 550 W with SMDCM. System recovery has taken 0.04 s with SMDCM, which completely failed with FLDCM. Similarly, voltage THD with FLDCM is 58.9% while with SMDCM is 3.08%. Peak voltage due to capacitive load switching is 340V with FLDCM and 150 V with SMDCM. These findings confirm that the proposed SMDCM considerably improved the transient performance of microgrids.  Full article
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<p>The layout of the microgrid includes cascaded droop, voltage, and current controllers.</p>
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<p>Plot of change in frequency (∆ω) with a step change in active power (∆P) for various values of L at a fixed value of <span class="html-italic">kp</span> (=0.0001).</p>
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<p>Plot of change in frequency (∆ω) with a step change in active power (∆P) for various values of L at a fixed value of <span class="html-italic">kp</span> (=0.0001).</p>
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<p>Pole-Zero plot of the system for various values of <span class="html-italic">L</span> and <span class="html-italic">kp</span>.</p>
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<p>Schematic of the proposed SMDCM and its major parts.</p>
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<p>Typical frequency waveform under transient operating conditions.</p>
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<p>Implementation of the proposed state machine for SMDCM development.</p>
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<p>Flowcharts showing the sequence of transitions among various states of the state machine.</p>
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<p>Various combinations of the trajectories obtained under 3 frequency zones.</p>
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<p>Realization of various transient conditions through the proposed combination of states.</p>
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<p>Frequency responses obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 1. (<b>d</b>) zoom in of all frequency responses around 125 s.</p>
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<p>Output power responses obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 1. (<b>d</b>) zoom in of all power responses around 125 s.</p>
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<p>PCC voltage responses obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 1. (<b>d</b>) zoom in of all voltage responses around 80 s and (<b>e</b>) zoom in of all voltage responses around 125 s.</p>
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<p>PCC voltage responses obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 1. (<b>d</b>) zoom in of all voltage responses around 80 s and (<b>e</b>) zoom in of all voltage responses around 125 s.</p>
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<p>Frequency responses obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 2. (<b>d</b>) zoom in of all frequency responses after 90 s.</p>
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<p>Output power responses obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 2. (<b>d</b>) zoom in of all power responses around 125 s.</p>
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<p>PCC voltage responses obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 2. (<b>d</b>) zoom in of voltage responses around 80 s, (<b>e</b>) zoom in of voltage responses around 86 s and (<b>f</b>) zoom in of voltage responses around 95.8 s.</p>
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<p>Frequency response obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 3.</p>
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<p>Output power responses obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 3.</p>
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<p>PCC voltage responses obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 3. (<b>d</b>) zoom in of all voltage responses around 80 s.</p>
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<p>PCC voltage responses obtained with (<b>a</b>) CDCM, (<b>b</b>) FLDCM, and (<b>c</b>) SMDCM when subjected to Case 3. (<b>d</b>) zoom in of all voltage responses around 80 s.</p>
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<p>Voltage THDs obtained with CDCM, FLDCM, and SMDCM subjected to Case 3.</p>
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11 pages, 1294 KiB  
Article
Rider Variables Affecting the Stirrup Directional Force Asymmetry during Simulated Riding Trot
by Paolo Baragli, Alberto Alessi, Marco Pagliai, Martina Felici, Asahi Ogi, Lesley Hawson, Angelo Gazzano and Barbara Padalino
Animals 2022, 12(23), 3364; https://doi.org/10.3390/ani12233364 - 30 Nov 2022
Viewed by 2395
Abstract
Riders’ asymmetry may cause back pain in both human and equine athletes. This pilot study aimed at documenting in a simple and quick way asymmetry in riders during a simulation of three different riding positions on wooden horseback using load cells applied on [...] Read more.
Riders’ asymmetry may cause back pain in both human and equine athletes. This pilot study aimed at documenting in a simple and quick way asymmetry in riders during a simulation of three different riding positions on wooden horseback using load cells applied on the stirrup leathers and identifying possible associations between riders’ asymmetry and their gender, age, level of riding ability, years of riding experience, riding style, motivation of riding, primary discipline and handedness. After completing an interview to obtain the previously mentioned information, 147 riders performed a standardized test on a saddle fixed on a wooden horseback-shaped model. The riding simulation was split into three phases of 1 min each: (1) sit in the saddle, (2) standing in the stirrups and (3) rising trot. The directional force on the left and the right stirrup leathers was recorded every 0.2 s. A paired t-test was performed on the recorded data to test the difference (i.e., asymmetry) in each phase. In phases 1, 2 and 3, 99.3% (53.4% heavier on the right (R)), 98% (52.8% heavier on the left (L)) and 46.3% (51.5% heavier on the left (L)) of the riders were asymmetrical, respectively. Chi-square tests showed a significant association between riding ability and riding experience, but no significant association between reported handedness and calculated leg-sidedness (p > 0.05). Univariate logistic (1: asymmetry, 0: symmetry) regression analysis was performed only on the phase 3 data. One-hand riders were found twice more likely to be asymmetrical than two-hand riders (Odds Ratio (OR): 2.18, Confidence Interval (CI): 1.1–4.29; p = 0.024). This preliminary study confirmed that the majority of the riders are asymmetrical in load distribution on stirrups and suggested the riding style as a possible risk factor for asymmetry. Full article
(This article belongs to the Special Issue Research on the Factors Affecting the Performance of Sport Horses)
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<p>The wooden horse back.</p>
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<p>The stirrup leathers equipped with the load cell and the load cell amplifier.</p>
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<p>Association between riding ability and riding experience of the 147 volunteer riders who performed the simulation riding tests on a wooden horse back.</p>
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11 pages, 5688 KiB  
Article
Influence of Elastic–Plastic Deformation on the Structure and Magnetic Characteristics of 13Cr-V Alloyed Steel Pipe
by Evgeniia Putilova and Kristina Kryucheva
Symmetry 2022, 14(6), 1201; https://doi.org/10.3390/sym14061201 - 10 Jun 2022
Cited by 1 | Viewed by 1971
Abstract
The principle of symmetry is one of the general methodological principles of science. The effects of any external influences, such as deformation, stresses, temperature, etc., could lead to the anisotropy (asymmetry) of properties in constructional materials. During operation, metal structures and machine parts [...] Read more.
The principle of symmetry is one of the general methodological principles of science. The effects of any external influences, such as deformation, stresses, temperature, etc., could lead to the anisotropy (asymmetry) of properties in constructional materials. During operation, metal structures and machine parts are exposed to time-varying external mechanical loads, which can cause changes in the metal structure, the initiation of cracks, and, as a result, the destruction of the product. The application of nondestructive testing methods prevents changes in the stress–strain state and, consequently, the destruction of the object. This article contains the results of studying the effects of elastic–plastic deformation by uniaxial tension and torsion on the change in the structure and magnetic parameters of low-alloy 13Cr-V pipe steel. Modern methods of metallography and magnetic nondestructive testing methods were used as part of this study. The results of the EBSD analysis showed that deformation during torsion, in contrast to uniaxial tension, is unevenly distributed over the sample cross section. In the cross section of the sample, the most severely deformed grains with a change in their geometry are observed near the surface; in the center, there is no change in geometry. During tension, the deformation over the cross section of the sample is uniformly distributed. Correlations between the applied normal and tangential stresses and magnetic characteristics of the 13Cr-V structural steel were determined. Informative parameters that could be used for the development of nondestructive testing methodologies for solving concrete tasks were determined. Different methods of deformation lead to diverse structural changes in grain structure. Full article
(This article belongs to the Section Engineering and Materials)
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<p>Appearance (<b>a</b>) and layout (<b>b</b>) of the installation for studying the effect of elastic–plastic deformation on the magnetic characteristics of materials, and the type of investigated sample (<b>c</b>) (all dimensions are in mm).</p>
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<p>The stress–strain diagram of the investigated 13Cr-V steel. The curve originates from the tensile test in accordance with GOST 1497-84.</p>
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<p>Scheme of sample cutting for the preparation of a thin section of the sample after fracturing for use in microscopic studies. This figure shows the example after the uniaxial tensile test. For torsion, the cutting method is similar (all dimensions are in mm).</p>
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<p>The microstructure of 13Cr-V steel in the initial state: (<b>a</b>) optical microstructure, (<b>b</b>) EBSD maps of misorientations, and (<b>c</b>) the map of recrystallization.</p>
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<p>EBSD maps of misorientations of the central sections of ruptured samples after uniaxial tension (<b>a</b>) and torsion (<b>b</b>), prepared in the plane of the transverse axis of the sample. The scheme of sample cutting used for these investigations is shown in <a href="#symmetry-14-01201-f003" class="html-fig">Figure 3</a>.</p>
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<p>EBSD maps of misorientations near the surface sections of ruptured samples after uniaxial tension (<b>a</b>) and torsion (<b>b</b>), prepared in the plane of the transverse axis of the sample. The scheme of sample cutting for these investigations is shown in <a href="#symmetry-14-01201-f003" class="html-fig">Figure 3</a>.</p>
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<p>Angles of misorientation of elements of the subgrain structure of 13Cr-V steel samples in the initial state (<b>a</b>), after uniaxial tension (<b>b</b>) and after torsion (<b>c</b>). The studies were carried out on samples after the fracture in the plane of the transverse axis of the sample. The cutting scheme of the sample used for EBSD analysis is shown in <a href="#symmetry-14-01201-f003" class="html-fig">Figure 3</a>.</p>
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<p>Dependences of magnetic parameters (coercive force <span class="html-italic">H</span><sub>c</sub>, residual induction <span class="html-italic">B</span><sub>r</sub>, and maximum magnetic permeability µ<sub>max</sub>) on applied normal (tension) (<b>a</b>) and tangential (torsion) (<b>b</b>) stresses. The error in the determination of magnetic properties was no more than 3%.</p>
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12 pages, 1841 KiB  
Article
Symmetry Analysis of Manual Wheelchair Propulsion Using Motion Capture Techniques
by Mateusz Kukla and Wojciech Maliga
Symmetry 2022, 14(6), 1164; https://doi.org/10.3390/sym14061164 - 5 Jun 2022
Cited by 7 | Viewed by 2122
Abstract
There is no consensus among researchers on the biomechanics of wheelchair propulsion concerning the bilateral symmetry assumption. On one hand, the assumption is advantageous, as it allows for the simplification of data collection, processing, and analysis. It also facilitates the modelling of wheelchair [...] Read more.
There is no consensus among researchers on the biomechanics of wheelchair propulsion concerning the bilateral symmetry assumption. On one hand, the assumption is advantageous, as it allows for the simplification of data collection, processing, and analysis. It also facilitates the modelling of wheelchair propulsion biomechanics. On the other hand, there are reports that the validity of the bilateral symmetry assumption is unclear. Therefore, the present study aims to analyse the biomechanics of wheelchair propulsion for side-to-side differences. Motion capture techniques based on ArUco with the use of OpenCV libraries were used for this purpose. The research was carried out on a group of 10 healthy and inexperienced volunteers with a semi-circular propulsion pattern, who declared right-handedness. The tests were carried out on a hard, even surface, without an additional load, within the frequency of the propelling phases dictated by sound signals, amounting to 30 BPM. The positions of markers on the hand, elbow, and wrist were analysed. As a result, a cloud of points of the markers’ displacement on the sagittal plane in the propulsion push progress function was obtained. The results were averaged with a breakdown by the right and left hand for individual persons, but also for the entire group of volunteers. A comparative analysis and the mutual position of the confidence intervals of the determined mean values were also performed. The collected data suggest that the mean values for individual participants show greater asymmetry than the mean positions of the markers for the entire group of participants. Therefore, the assumption about the symmetry of upper limb propulsion may not be true when analysing the biomechanics of propulsion for individuals, although it may be accurate when analysing larger groups of persons (participants free of upper-extremity pain or impairment). Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Sport Sciences)
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Graphical abstract
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<p>The locations of markers on the researched person’s limb and the assumed marking of the coordinate axes are shown for (<b>a</b>) the left hand and (<b>b</b>) the right hand.</p>
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<p>A view of the set of averaged results for the right and left hands of research participants A1, A2, A3, and A6.</p>
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<p>The average curve of the ID1 marker position change during the propelling cycle on the x axis for the left and right hand (the thick line); the thin lines are ± confidence interval; Participant A2.</p>
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<p>The average curve of the ID4 marker position change during the propelling cycle on the y axis for the left and right hand (the thick line); the thin lines are ± confidence interval; Participant A2.</p>
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<p>The averaged positions of the ID1 marker for the left and right side of participant A9; the error bars marked in grey are ± measurement uncertainty for the left limb.</p>
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<p>The averaged positions of the ID2 marker for the left and right side of participant A9; the error bars marked in grey are ± measurement uncertainty for the left limb.</p>
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<p>The averaged positions of the ID4 marker for the left and right side of participant A7; the error bars marked in grey are ± measurement uncertainty for the left limb.</p>
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<p>Change in the position of the ID1 marker on the x axis of the set of averaged results for all research participants for the left and right hands, respectively (the thick line); the thin lines are ± confidence interval.</p>
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<p>Change in the position of the ID1 marker on the y axis of the set of averaged results for all research participants for the left and right hands, respectively (the thick line); the thin lines are ± confidence interval.</p>
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<p>Position of the ID2 marker for the left and right hands averaged for all research participants; the error bars marked in grey are ± measurement uncertainty for the left limb.</p>
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22 pages, 9202 KiB  
Article
Vertical Oscillation of Railway Vehicle Chassis with Asymmetry Effect Consideration
by Frantisek Klimenda, Jan Skocilas, Blanka Skocilasova, Josef Soukup and Roman Cizek
Sensors 2022, 22(11), 4033; https://doi.org/10.3390/s22114033 - 26 May 2022
Cited by 4 | Viewed by 1564
Abstract
This paper deals with the problem of vertical oscillation of rail and road vehicles under symmetrical and asymmetrical loading and symmetrical and asymmetrical kinematic excitation. The term asymmetry is understood as the asymmetric distribution of vehicle mass and elastic and dissipative elements with [...] Read more.
This paper deals with the problem of vertical oscillation of rail and road vehicles under symmetrical and asymmetrical loading and symmetrical and asymmetrical kinematic excitation. The term asymmetry is understood as the asymmetric distribution of vehicle mass and elastic and dissipative elements with respect to the axes of geometric symmetry, including asymmetric kinematic excitation. The various models used (spatial, planar, quarter-plane) are discussed and their analytical solutions are outlined. The theory of the spatial model is applied to the chassis of a model railway vehicle. The basic relations for the calculation of the equations of motion of this vehicle are given. In the next section, the experimental solution of a four-axle platform rail car is described and the measurements of vertical displacement and accelerations when crossing wedges (representing unevenness) are given. Full article
(This article belongs to the Section Vehicular Sensing)
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<p>Simple general model of the vehicle.</p>
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<p>The scheme of the model.</p>
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<p>Chassis support: (<b>a</b>) Original springs; (<b>b</b>) substituted springs.</p>
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<p>(<b>a</b>) Bogie fixed to the car platform; (<b>b</b>) loading unit.</p>
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<p>Wedge locations at rail.</p>
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<p>Sensor locations.</p>
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<p>Acceleration sensor location: (<b>a</b>) at frame of backward car; (<b>b</b>) at platform of car—transversal axis.</p>
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<p>Measured combination of loading and kinematic excitation.</p>
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<p>Location of relative vertical deflection and vertical acceleration sensors at selected points. B—handbrake, 1L/R—chassis frame vertical deflection sensor, first wheelset, left/right side, 2L/R—chassis frame and body vertical deflection sensor, left/right side, 3L/R—car body vertical acceleration sensor, left/right side.</p>
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<p>Relative vertical displacement between chassis frame and wheelset—variant A–I.</p>
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<p>Relative displacement between car body and chassis frame—variant A–I.</p>
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<p>Relative displacement between chassis frame and wheelset—variant A–IV.</p>
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<p>Relative displacement between car body and chassis frame—variant A-IV.</p>
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<p>Relative displacement between chassis frame and wheelset—variant D-I.</p>
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<p>Relative displacement between car body and chassis frame—variant D-I.</p>
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<p>Relative displacement between chassis frame and wheelset—variant D-IV.</p>
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<p>Relative displacement between car body and chassis frame—variant D-IV.</p>
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<p>Relative displacement between chassis frame and wheelset—variant B-III.</p>
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<p>Relative deflections between car body and chassis frame—variant B-III.</p>
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<p>Vertical acceleration in the middle of the car body on the left and right side—variant B-III.</p>
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19 pages, 3303 KiB  
Article
A Rapid Deployment Mechanism of Forwarding Rules for Reactive Mode SDN Networks
by Ming-Tsung Kao, Shang-Juh Kao, Hsueh-Wen Tseng and Fu-Min Chang
Symmetry 2022, 14(5), 1026; https://doi.org/10.3390/sym14051026 - 17 May 2022
Viewed by 2171
Abstract
In reactive mode software-defined networking (SDN) networks, a new initiated flow requires back-and-forth communications between the controller and the switches along the forwarding route. As SDN is getting popularly accepted, many studies have reported on how to reduce the amount of communication traffic [...] Read more.
In reactive mode software-defined networking (SDN) networks, a new initiated flow requires back-and-forth communications between the controller and the switches along the forwarding route. As SDN is getting popularly accepted, many studies have reported on how to reduce the amount of communication traffic and to release the controller’s loading. Several techniques have been proposed, such as proactive and active mode integration, MPLS adoption, and various forwarding rule installation techniques. In this paper, we adopt the idea of the tunnel penetration technique, called the tunnel boring machine in SDN or SDN-TBM, to effectively cut down the traffic between switches and the controller as well as to speed up packet delivery. Using the TBM mechanism, the communication symmetry between the controller and the switches on the path is broken and transformed into asymmetry. Only the first and last switches of each application flow need to make forwarding queries to the controller, and all intermediate switches simply forward packets consisting of the forwarding information needed to determine the next-hop switch. An M/M/1 queueing model is developed to verify the feasibility and efficiency of the proposal. Under the simulation of more than a million flows with 3–8 intermediate switches, the packet sojourn time using SDN-TBM mechanism is less than that of adopting the conventional SDN and JumpFlow model. Additionally, by adopting SDN-TBM, both the number of packet-in and packet-out packets and the controller’s loading are significantly reduced. Full article
(This article belongs to the Topic IOT, Communication and Engineering)
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<p>The system architecture of SDN-TBM.</p>
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<p>Data structure of PHS.</p>
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<p>Data structure of BP payload.</p>
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<p>Flowchart of the TBMP.</p>
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<p>Flowchart of the BP processor.</p>
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<p>Queuing models of system. (<b>a</b>) Conventional SDN model, (<b>b</b>) SDN-TBM model.</p>
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<p>Procession flow of the first packet. (<b>a</b>) Conventional SDN model, (<b>b</b>) SDN-TBM model.</p>
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<p>Procession flow of the first packet. (<b>a</b>) Conventional SDN model, (<b>b</b>) SDN-TBM model.</p>
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<p>Effect of controller load on packet sojourn time. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>1.0</mn> <mo> </mo> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>0.5</mn> <mo> </mo> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>0.2</mn> <mo> </mo> </mrow> </semantics></math>.</p>
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<p>Comparison of sojourn time for flow forwarding on a path. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>1.0</mn> <mo> </mo> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>0.5</mn> <mo> </mo> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>0.2</mn> <mo> </mo> </mrow> </semantics></math>.</p>
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<p>Comparison of sojourn time for flow forwarding on a path. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>1.0</mn> <mo> </mo> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>0.5</mn> <mo> </mo> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>0.2</mn> <mo> </mo> </mrow> </semantics></math>.</p>
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<p>Comparison of RESTful data simulations for SDN, JumpFlow and SDN-TBM models. (<b>a</b>) traffic flow data, (<b>b</b>) average sojourn time, (<b>c</b>) packet-in messages.</p>
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<p>Impact of unfamiliar flows on the average sojourn time.</p>
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<p>Impact of unfamiliar flows on the average of the packet-in message.</p>
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