A Computational Approach for Human-like Motion Generation in Upper Limb Exoskeletons Supporting Scapulohumeral Rhythms

This paper proposes a computational approach for generation of reference path for upper-limb exoskeletons considering the scapulohumeral rhythms of the shoulder. The proposed method can be used in upper-limb exoskeletons with 3 Degrees of Freedom (DoF) in shoulder and 1 DoF in elbow, which are capable of supporting shoulder girdle. The developed computational method is based on Central Nervous System (CNS) governing rules. Existing computational reference generation methods are based on the assumption of fixed shoulder center during motions. This assumption can be considered valid for reaching movements with limited range of motion (RoM). However, most upper limb motions such as Activities of Daily Living (ADL) include large scale inward and outward reaching motions, during which the center of shoulder joint moves significantly. The proposed method generates the reference motion based on a simple model of human arm and a transformation can be used to map the developed motion for other exoskeleton with different kinematics. Comparison of the model outputs with experimental results of healthy subjects performing ADL, show that the proposed model is able to reproduce human-like motions.Comment: In 2017 IEEE International Symposium on Wearable & Rehabilitation Robotics (WeRob2017

Reappraisal of the astm/aashto standard rolling device method for plastic limit determination of fine-grained soils

Given its apparent limitations, various attempts have been made to develop alternative testing approaches to the standardized rolling-thread plastic limit (PLRT) method (for fine-grained soils), targeting higher degrees of repeatability and reproducibility. Among these, device-rolling techniques, including the method described in ASTM D4318/AASHTO T90 standards, based on original work by Bobrowski and Griekspoor (BG) and which follows the same basic principles as the standard thread-rolling (by hand) test, have been highly underrated by some researchers. To better understand the true potentials and/or limitations of the BG method for soil plasticity determination (i.e., PLBG), this paper presents a critical reappraisal of the PLRT–PLBG relationship using a comprehensive statistical analysis performed on a large and diverse database of 60 PLRT– PLBG test pairs. It is demonstrated that for a given fine-grained soil, the BG and RT methods produce essentially similar PL values. The 95% lower and upper (water content) statistical agreement limits between PLBG and PLRT were, respectively, obtained as −5.03% and +4.51%, and both deemed “statistically insignificant” when compared to the inductively-defined reference limit of ±8% (i.e., the highest possible difference in PLRT based on its repeatability, as reported in the literature). Furthermore, the likelihoods of PLBG underestimating and overestimating PLRT were 50% and 40%, respectively; debunking the notion presented by some researchers that the BG method generally tends to greatly underestimate PLRT. It is also shown that the degree of underestimation/overestimation does not systematically change with changes in basic soil properties; suggesting that the differences between PLBG and PLRT are most likely random in nature. Compared to PLRT, the likelihood of achieving consistent soil classifications employing PLBG (along with the liquid limit) was shown to be 98%, with the identified discrepancies being cases that plot relatively close to the A-Line. As such, PLBG can be used with confidence for soil classification purposes. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Modeling the compaction characteristics of fine-grained soils blended with tire-derived aggregates

This study aims at modeling the compaction characteristics of fine-grained soils blended with sand-sized (0.075–4.75 mm) recycled tire-derived aggregates (TDAs). Model development and calibration were performed using a large and diverse database of 100 soil–TDA compaction tests (with the TDA-to-soil dry mass ratio ≤ 30%) assembled from the literature. Following a comprehensive statistical analysis, it is demonstrated that the optimum moisture content (OMC) and maximum dry unit weight (MDUW) for soil–TDA blends (across different soil types, TDA particle sizes and compaction energy levels) can be expressed as universal power functions of the OMC and MDUW of the unamended soil, along with the soil to soil–TDA specific gravity ratio. Employing the Bland– Altman analysis, the 95% upper and lower (water content) agreement limits between the predicted and measured OMC values were, respectively, obtained as +1.09% and −1.23%, both of which can be considered negligible for practical applications. For the MDUW predictions, these limits were calculated as +0.67 and −0.71 kN/m3, which (like the OMC) can be deemed acceptable for prediction purposes. Having established the OMC and MDUW of the unamended fine-grained soil, the em-pirical models proposed in this study offer a practical procedure towards predicting the compaction characteristics of the soil–TDA blends without the hurdles of performing separate laboratory compaction tests, and thus can be employed in practice for preliminary design assessments and/or soil– TDA optimization studies. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Moisture content determination of oilseeds based on dielectric measurement

Oilseeds have an important role in edible oil production.  Moisture content measurement of oilseed is an inevitable operation in harvesting and almost all postharvest processing such as handling, storage, milling and oil extraction.  In this paper, a cylindrical capacitive sensor was used to predict the moisture content of sesame, soybean and canola seed as a simple, low cost, rapid and reliable method.  Two varieties of each oilseed were selected and extracted equation from a variety was evaluated for another variety.  The hyperbolic regression and paired t-test were utilized to extract the calibration equations and perform a comparison between predicted moisture with actual values.  The R2 of calibration for Dashtestan and Ultan sesame were 0.998 and 0.999, respectively, for L17 and Sahar soybean were 0.972 and 0.965, respectively and for Okapi and Talaiyeh canola were 0.993 and 0.994, respectively.  The R2 of prediction for Dashtestan and Ultan sesame were 0.966 and 0.932, respectively, for L17 and Sahar soybean were 0.963 and 0.952, respectively and for Okapi and Talaiyeh canola were 0.993 and 0.994, respectively.  Results of paired t-test confirmed that the measured and predicted moisture content of all oilseeds were not statistically different at the 5% level (p > 0.05).  Based on obtained results the designed system using capacitive sensor is valid and reliable for moisture measurement of the studied oilseeds.   Keywords: oilseed, sesame, soybean, canola, moisture content, capacitive senso

Mechanical behavior of tire rubber–reinforced expansive soils

Expansive soils are amongst the most significant, widespread, costly, and least publicized geologic hazards. Where exposed to seasonal environments, such soils exhibit significant volume changes as well as desiccation–induced cracking, thereby bringing forth instability concerns to the overlying structures and hence incurring large amounts of maintenance costs. Consequently, expansive soils demand engineering solutions to alleviate the associated socio–economic impacts on human life. Common solutions to counteract the adversities associated with problematic soils include soil replacement and/or soil stabilization. The latter refers to any chemical, mechanical or combined chemical–mechanical practice of altering the soil fabric to meet the intended engineering criteria. Though proven effective, conventional stabilization schemes often suffer from sustainability issues related to high manufacturing and/or transportation costs, and environmental concerns due to greenhouse gas emissions. The transition towards sustainable stabilization necessitates reusing solid wastes and/or industrial by–products as part of the infrastructure system, and more specifically as replacements for conventional stabilization agents such as cement, lime, geogrids and synthetic fibers. Among others, discarded tires constitute for one of the largest volumes of disposals throughout the world, and as such, demand further attention. Given the high–volume generation (and disposal) of waste tire rubbers every year throughout the world, a major concern hitherto has been the space required for storing and transporting such waste materials, and the resulting health hazards and costs. Those characteristics which make waste tire rubbers such a problem while being landfilled, make them one of the most reusable waste materials for engineering applications such as soil stabilization, as the rubber is resilient, lightweight and skin–resistive. Beneficial reuse of recycled tire rubbers for stabilization of expansive soils would not only address the geotechnical–related issue, but would also encourage recycling, mitigate the burden on the environment and assist with waste management. The present study intends to examine the rubber’s capacity of ameliorating the inferior engineering characteristics of expansive soils, thereby solving two widespread hazards with one solution. Two rubber types of fine and coarse categories, i.e. rubber crumbs/powder and rubber buffings, were each examined at various rubber contents (by weight). The experimental program consisted of consistency limits, standard Proctor compaction, oedometer swell– shrink/consolidation, soil reactivity (or shrink–swell index), cyclic wetting–drying, cracking intensity, unconfined compression (UC), split tensile (ST), direct shear (DS) and scanning electron microscopy (SEM) tests. Improvement in the swell–shrink/consolidation capacity, cracking intensity and shear strength (DS test) were all in favor of both a higher rubber content and a larger rubber size. However, rubber contents greater than 10% (by weight) often raised failure concerns when subjected to compression (UC test) and/or tension (ST test), which was attributed to the clustering of rubber particles under non–confinement testing conditions. Although the rubber of coarser category slightly outperformed the finer rubber, the effect of larger rubber size was mainly translated into higher ductility, lower stiffness and higher energy adsorption capacity rather than peak strength improvements. The volume change properties were cross–checked with the strength–related characteristics to arrive at the optimum rubber content. A rubber inclusion of 10%, preferably the rubber of coarser category, satisfied a notable decrease in the swell–shrink/consolidation capacity as well as improving the strength–related features, and thus was deemed as the optimum choice. Based on the experimental results, along with the SEM findings, the soil–rubber amending mechanisms were discussed in three aspects: i) increase in non–expansive fraction; ii) frictional resistance generated as a result of soil–rubber contact; and iii) mechanical interlocking of rubber particles and soil grains. A series of empirical models were suggested to quantify the compaction characteristics of soil–rubber mixtures as a function of their consistency limits. Moreover, the dimensional analysis concept was extended to the soil–rubber shear strength problem, thereby leading to the development of a series of practical dimensional models capable of simulating the shear stress–horizontal displacement response as a function of normal stress (or confinement) and the composite’s basic index properties, i.e. rubber content, specific surface area and initial placement (or compaction) condition. The predictive capacity of the proposed empirical and dimensional models was examined and further validated by statistical techniques. The proposed empirical and dimensional models contain a limited number of fitting/model parameters, which can be calibrated by minimal experimental effort as well as simple explicit calculations, and thus implemented for preliminary assessments (or predictive purposes). To justify the use of higher rubber contents in practice, a sustainable polymer agent, namely Polyacrylamide (PAM) of anionic character, was introduced as the binder. A series of additional tests were then carried out to examine the combined capacity of rubber inclusion and PAM treatment in solving the swelling problem of South Australian expansive soils. As a result of PAM treatment, the connection interface between the rubber particles and the clay matrices were markedly improved, which in turn led to lower swelling/shrinkage properties, higher resistance to cyclic wetting–drying, and reduced tendency for cracking compared to that of the conventional soil–rubber blend. A rubber inclusion of 20%, paired with 0.2 g/l PAM, was suggested to effectively stabilize South Australian expansive soils.Thesis (Ph.D.) -- University of Adelaide, School of Civil, Environmental and Mining Engineering, 201

A Machine Learning Method for Modeling Wind Farm Fatigue Load

Wake steering control can significantly improve the overall power production of wind farms. However, it also increases fatigue damage on downstream wind turbines. Therefore, optimizing fatigue loads in wake steering control has become a hot research topic. Accurately predicting farm fatigue loads has always been challenging. The current interpolation method for farm-level fatigue loads estimation is also known as the look-up table (LUT) method. However, the LUT method is less accurate because it is challenging to map the highly nonlinear characteristics of fatigue load. This paper proposes a machine-learning algorithm based on the Gaussian process (GP) to predict the farm-level fatigue load under yaw misalignment. Firstly, a series of simulations with yaw misalignment were designed to obtain the original load data, which considered the wake interaction between turbines. Secondly, the rainflow counting and Palmgren miner rules were introduced to transfer the original load to damage equivalent load. Finally, the GP model trained by inputs and outputs predicts the fatigue load. GP has more accurate predictions because it is suitable for mapping the nonlinear between fatigue load and yaw misalignment. The case study shows that compared to LUT, the accuracy of GP improves by 17% (RMSE) and 0.6% (MAE) at the blade root edgewise moment and 51.87% (RMSE) and 1.78% (MAE) at the blade root flapwise moment

The accuracy of ultra-sonographic findings in detection of abdominal tumor size in children (our experience in Children Medical Center)

Introduction: Since abdominal tumors are one of the common causes of childhood death, studying the clinico-pathologic features of them is important for early diagnosis. Our aim in this study was to determine these features in Iranian children and to evaluate the accuracy of ultrasonography in diagnosing abdominal masses in children.Materials and Methods: In this retrospective case series study, data about sex, age, primary chief complaint, physical examination, imaging report and pathology finding of 156 children with abdominal tumor, who were admitted to the Children Medical Center in the last 6 years were gathered.Results: Male to female ratio was 0.69. The most common type of tumor in this study was Willm’s (37.5%) and Neuroblastoma (35.7%). Mean age of children with Willm’s tumor and Neuroblastoma was 38.95 and 26.65 months respectively. Ultrasonography has a lower accuracy in patients with tenderness, children with Willm’s tumor, female patients and children under 5 years old.Conclusion: Our different findings regarding tumor type and distribution as opposed to previous studies may be due to genetic and geographic variations. In addition, this study shows that the accuracy of Ultrasonography in children with abdominal tumors depends on children’s sex, age, pain and the type of tumor