Miracle-dz/UniFAR-FTUs huggingface dataset:
Balancing and Hopping Motion Control Algorithms for an Under-actuated Robot

The main contribution of this thesis is a new and simple angular momentum based control algorithm for balancing an under-actuated planar robot. The proposed controller is able to stabilize the robot at any unstable balanced configuration and to control the robot to follow motion trajectory commands. This controller is also capable of balancing the robot on a rolling contact. A modified version of the controller is used to control the robot during a single hop motion. The proposed planar controller is then used as a part of a 3D balancing controller for a spatial under-actuated robot. The 3D control algorithm, which is based on the angular momentum of the robot, can balance the robot within any vertical plane and also rotate the robot from a vertical plane to any other one. Performance of the control algorithm in planar balancing, spatial balancing and planar hopping motions is demonstrated by simulation results. Although hopping motion of a spatial under-actuated robot is not considered in this thesis, it is shown in simulations that, starting from an upright configuration, the 3D controller is able to move the robot within any arbitrary vertical plane. Therefore, by confining the robot’s motion to a vertical plane, the robot is potentially able to perform hopping motion in 3D using the same algorithm that is proposed for planar hopping motion. Another major contribution of this thesis is a new nonlinear model for the contact normal force. This new model accurately predicts the measured values of the coefficient of restitution between spheres and plates of various materials. The new contact model is used in this thesis to model the contact between the robot’s foot and the ground during a hopping motion.
Retrospective Power Surveys

One of the main goals of a retrospective survey of statistical power is to establish the average power of tests used in a given area of research. In many disciplines (e.g. the behavioural sciences) where theories are not sufficiently advanced to provide an exact prediction of effect size, retrospective surveys generally calculate the power of a test in terms of the test's ability to detect the conjectured effect size as estimated from the data. However, to attain their declared goal, such surveys should instead compute the expected power of a test over the distribution of plausible effect sizes. It is demonstrated that the current practice of using a point estimate of effect size in the standard power formula leads to an overestimation of the average power of statistical tests in retrospective surveys, often by a considerable amount.
Levitation Diffusion Chamber Measurements of the Mass Growth of Small Ice Crystals from Vapor

AbstractA levitation diffusion chamber designed to examine the mass growth from the vapor of small ice particles (diameter < 100 μm) at ambient pressure (≃970 hPa) and low temperature (T < −30°C) is presented. The diffusion chamber is unique in that charged ice particles are levitated by an opposing voltage on the lower copper plate with lateral stability provided by button quadrupole electrodes attached to the upper copper plate. The button electrodes are far from the ice particle growth region, allowing ice particles to grow free of substrate influences. Experiments have been conducted for temperatures from −30° to −35.7°C, ice supersaturations from 2.5% to 28.6%, and over growth times ranging from 5 to 15 min. The experiments indicate that mass varies nonlinearly in time and exhibits a dependence on initial particle radius and ice supersaturation in accord with expectations from theory. In contrast to expectations from spherical capacitance theory, the derived mass growth rates do not scale linearly wi.
A hybrid approach to quantify lamination of the cerebral cortex

Alterations of cytoarchitectonic (CA) patterns in digital images of histological sections of the human cerebral cortex (CX) might indicate changes of brain functions. These lamination patterns can be extracted by calculating orthogonal testlines through CX by a stepwise scanning. 3D CA data of whole human brains at a histological resolution are not available and 2D sections deliver partial information only. The problem is to find an optimal method of scanning producing a minimum of distortions and noise by the transformation of the curvilinear CX to a rectangular presentation of CA layering. So far, the cortical surfaces are modeled as electrically charged regions to use the resulting field lines as testlines. However, local information of cell distributions was not considered. A hybrid approach constructs significantly better testlines in CX images with mixtures of columnar rich (local orientation rich) and orientation poor parts of strongly curved regions. The new hybrid approach is based on combining streamlines of the electric field with the structure tensor and constrained anisotropic diffusion. In addition, the introducing of projective transformations yields a significant improvement of cortical fingerprints. The statistical evaluation of the new method turns out to be robust with respect to artifacts and low local orientation information. The new technique can be generalized and applied to many different types of CX with local orientation information.
Physiological and Cultural Variabilities among Fusarium oxysporum f.sp. cepae Isolates in Onion

The effect of culture media, carbon sources, nitrogen sources, temperature and pH on the mycelial growth of Fusarium oxysporum f.sp. cepae was investigated. The fungus grew the best on Czapek’s dox medium and glucose was the best source of carbon whereas peptone was the best source of nitrogen. Growth was maximum at 30°C which was reduced drastically below 20°C and above 35°C. The most suitable pH for optimum growth of fungus was 6.5.
Analysis and Design of Secure Sampled-Data Control Subject to Denial-of-Service Attacks

This study addresses the issue of secure control design for cyber-physical systems (CPS) against denial of service (DoS) attacks. We take into account a continuous-time linear system with a convex quadratic performance measure and a sampled linear state feedback control. DoS attacks impose constraints on the CPS, where packets may be jammed between the sensor and controller by a malicious entity, potentially resulting in system instability and performance degradation. We assume that the attacker can perform DoS attacks with a limited time and frequency due to energy restrictions. We devise an efficient procedure using the linear matrix inequality approach to compute an upper bound on the performance degradation brought on by the DoS attack. We also propose a redesign of the controller to minimize this performance degradation. Finally, a simulation example illustrates the computation of the performance degradation under a bounded DoS attack and the design of a secure controller. Simulation results show that the designed controller effectively keeps the feedback loop’s performance and stability under attack.
Three-point locally adaptive searching in gray scale projection algorithm for electronic image stabilization

The gray scale projection algorithm is a key technique for detecting motion vector of image sequential frames and realize electronic image stabilization. Through analyzing the related curves, three-point locally adaptive searching algorithm is proposed on the basis of single peak characteristics. The procedures are as follows: through equably selecting three points in searching coverage, calculating and comparing their correlation values, judging the variation direction of the correlation curve gradient, the searching parameters will be correspondingly adjusted to obtain the motion vector between frames. And then motion filtering and image compensation can be carried out on this basis and electronic image stabilization can be performed. When searching coverage is 2n-1(n=1, 2,厖,and 2n-1 less than one half of image width in searching direction), its operation load is 3n instead of 2n+1-1 of global searching algorithm. In this way the faults of large operation load and long operation time have been overcome. The algorithm has been demonstrated by simulation experiments.
A low-power high speed full adder cell using carbon nanotube field effect transistors

The adder circuit is basic component of arithmetic logic design and that is the most important block of processor architecture. Moreover, power consumption is the main concern for real-time digital systems. In recent times, carbon nanotube field effect transistors (CNTFET) used for arithmetic circuit designs with high performance. A creative substitute for highspeed, less power, and small size in area designs is the CNTFET. This paper presents 1- bit full adder with CNTFETs for low power and high performance. Using the computer aided design (CAD) tool the proposed 1-bit full adder design model is simulated using 32 nm with CNTFET technology, a voltage supply of +0.9V. Performance comparisons between various proposed designs and existing 1-bit full adder design have been made in terms of the delay, power, and power delay product (PDP). The proposed CNFET logic also design for n-bit carry look adder (CLA) and compare it to other CLAs to evaluate performance and reliability. The simulation results shows that the proposed adder consume less power than existing adders.
A Privacy-Preserving and Reputation-Based Truth Discovery Framework in Mobile Crowdsensing

In mobile crowdsensing (MCS), truth discovery (TD) plays an important role in sensing task completion. Most of the existing studies focus on the privacy preservation of mobile users, and the reliability of mobile users is evaluated by their weights which are calculated based on the submitted sensing data. However, if mobile users are unreliable, the submitted sensing data and their weights are also unreliable, which may influence the accuracy of the ground truths of sensing tasks. Therefore, this article proposes a privacy-preserving and reputation-based truth discovery framework named PRTD which can generate the ground truths of sensing tasks with high accuracy while preserving privacy. Specifically, we first preserve sensing data privacy, weight privacy, and reputation value privacy by utilizing the Paillier algorithm and Pedersen commitment. Then, to verify whether the reputation values of mobile users are tampered with and select mobile users that satisfy the corresponding reputation requirements, we design a privacy-preserving reputation verification algorithm based on reputation commitment and zero-knowledge proof and propose a concept of reliability level to select mobile users. Finally, a general TD algorithm with reliability level is presented to improve the accuracy of the ground truths of sensing tasks. Moreover, theoretical analysis and performance evaluation are conducted, and the evaluation results demonstrate that the PRTD framework outperforms the existing TD frameworks in several evaluation metrics in the synthetic dataset and real-world dataset.
Effect of the Tilt Angle on the Wind Turbine Performance and Wakes

Simulations of a horizontal axis wind turbine using direct modeling of the rotor blades are presented. The computational numerical solution was carried out in order to get a better understanding of wake development as well as the possibility to predict the power available in the wakes for the turbines located in the downstream direction. The amount of power extracted from the wind turbine and the power available in the wake were studied for different tilt angles of the blades varied from 0 to 15 degrees. However the wind turbine extracted less power by tilting the rotor blades, the power available in the wake downstream the turbine was significantly increased compared with zero tilt angle. The results show that control of the tilt angle can maximize the total power output of the wind farm. This study provides a method to control the wake actively and thus optimize the efficiency of a wind farm.
Periodic solutions of the Brillouin electron beam focusing equation

Quite unexpectedly with respect to the numerical and analytical results found in literature, we establish a new range for the real parameter $b$ for which the existence of $2\pi-$periodic solutions of the Brillouin focusing beam equation \begin{eqnarray} \ddot{x}+b(1+\cos t)x=\frac{1}{x} \end{eqnarray} is guaranteed. This is possible thanks to suitable nonresonance conditions acting on the rotation number of the solutions in the phase plane.
Development of an Instrument for Formative Evaluation and Its Diagnostic Standard of Physical Education Class in Elementary School

The present study was to develop a questionnaire instrument for formative evaluation and its diagnostic standard of physical education class in elementary school. The questionnaire consisting of 9 items was prepared and applied to 9127 pupils from 3rd to 6th grade in 291 physical education classes. Four factors extracted by the factor analysis could be named as follows; 1) ‘outcome, ’ 2) ‘way of learning, ’ 3) ‘cooperation’ and 4) ‘motivation, ’ These factors were consistent with those in previous research (Takahashi et al., 1994). It was examined whether there were significant differences for these 4 factor scores in terms of pupils’ sex, school grade, and subject matters taught in classes. The results revealed that girls generally scored higher than boys, and middle grade pupils (3rd and 4th) scored higher on ‘motivation’ than high grade pupils (5th and 6th). As for ‘motivation’ pupils scored highest in ball game class, but in terms of ‘way of learning’ highest in apparatus gymnastics.Finally, the 9 item questionnaire was developed for a convenient and effective formative evaluation of physical education class in elementary school. The 5 point scale diagnostic standards based on variance of score were made for all classes as well as for each subject matter taught in classes; apparatus gymnastics, track and field and ball games.
Identifying cluster members of NGC 869 and NGC 884 using a combined machine learning method

This work describes a method for calculating cluster membership probability from big, high dimensional newly released GAIA-EDR3 observations that combine the Gaussian Mixture Model (GMM) with the Random Forest (RF). This technique has the considerable advantage of rapidly identifying possible cluster members in big data sets using modest training samples. The result indicates that the double clusters NGC 869 has 20270 points ultra-high (p≥ 0.8) probable members, 9294 are high (p≥ 0.6) probable members, and 6181 stars are moderate (0.2 <= p < 0.6) members. NGC 884 has ultra-high (p≥ 0.8) probable members of 21317, high (p≥ 0.6) probable members with 10871 and moderate (0.2 <= p < 0.6) of 5998. Cluster centers of NGC 884 and NGC 869 were also determined to be at α = 2h 22m 17s, δ = 57h 8m 60s and α = 2h 19m 2s, δ = 57h 7m 48s respectively. The double cluster also has a mean proper motion of -0.690 ± 12 mas/yr, or -1.150 ± 16 mas/yr, and a mean parallax of 0.410 ± 04 mas. The old cluster member in NGC 884 was quantified to be ± 621, and the new cluster member to be ± 1129. The new members of NGC 869 are ± 1511, up from the previous 920 members. We also found that the combined GMM and RF are effective in identifying cluster membership using the GAIA-EDR3 observations.
Parametric Regularized Calibration of Merton Jump-Diffusion Model with Relative Entropy: What Difference Does It Make?

This paper answers to the simple question, “What difference does the regularization with relative entropy make? ” For this purpose, we parametrically calibrate the Merton (1976) jump-diffusion model the S&P 500 futures options with or without regularization and judge the impact of the regularization. The calibration result indicates that with or without regularization, calibrated risk-neutral parameters, calibrated log return probability densities, and calibrated Levy measures are not significantly different using the risk-neutral prior except for near maturity options. Another finding is that the regularized calibration with the statistical prior is not implementable because of the remarkable deviation of the statistical prior from the risk-neutral prior.
Transfer Deep Learning Network for Rolling Bearing Fault Diagnosis of Wind Turbines

Fault diagnosis of rolling bearings has become a critical measure to ensure the security, efficiency, and availability of wind turbine systems. In this work, an approach called a transfer deep learning network is reported to resolve the drawbacks of existing rolling bearing fault algorithms on the basis of deep learning, such as large training parameters, long training time, and insufficient training samples. The reported approach mainly consists of two steps: feature transfer using transfer component analysis and network transfer using the pre-trained convolutional neural network. One dataset of rolling bearings with four fault types is gathered to estimate the classification performance, and the peer model is employed for a comparison study. The derived research results show that the reported algorithm based on the feature transfer and the network transfer can yield outstanding results in the rolling bearing fault diagnosis.
Deep brain stimulation modulates directional limbic connectivity in major depressive disorder

Deep brain stimulation (DBS) is being investigated as treatment for patients with refractory major depressive disorder (MDD). However, little is known about how DBS exerts its antidepressive effects.Here, we investigated whether ventral anterior limb of the internal capsule (vALIC) stimulation modulates a limbic network centered around the amygdala in patients with treatment resistant MDD. Nine patients underwent resting state functional magnetic resonance imaging (fMRI) before DBS surgery and after one year of treatment. In addition, they were scanned twice within two weeks during the subsequent double blind crossover phase with active and sham treatment. Eleven matched controls underwent fMRI scans at same time intervals to account for test-retest effects. The imaging data was investigated with functional connectivity analysis and dynamic causal modelling (DCM). Results showed that one year of DBS treatment was associated with increased functional connectivity of the left amygdala with precentral cortex and left insula along with decreased bilateral connectivity between nucleus accumbens and ventromedial prefrontal cortex. No changes in functional connectivity were observed during the crossover phase. Effective connectivity analyses using DCM revealed widespread amygdala-centric changes between pre-surgery and one year follow-up, while the crossover phase was associated with insula-centric changes between active and sham stimulation. These results suggest that vALIC DBS results in complex rebalancing of the limbic network involved in emotion, reward and interoceptive processing.
Lundberg bounds on the tails of compound distributions

Exponential bounds are derived for the tail probabilities of various compound distributions, generalizing the classical Lundberg inequality of insurance risk theory. Failure rate properties of the compounding distribution including log-convexity and log-concavity are considered in some detail. Mixed Poisson compounding distributions are also considered. A ruin theoretic generalization of the Lundberg inequality is obtained in the case where the number of claims process is a mixed Poisson process. An application to the M/G/1 queue length distribution is given.
Presence and activity of Fibrinogen like protein 2 in platelets

Background Fibrinogen-like protein 2 (FGL2) is a serine protease capable of converting prothrombin into thrombin (i.e., prothrombinase-like activity) while bypassing the classic coagulation cascade. It has been reported to be expressed by mononuclear blood cells and endothelial cells. There are multiple reports that FGL2 supports tumor development and metastasis. However, in the blood, the origin and functional significance of FGL2 has not been established. Objective To determine if FGL2, a malignancy related enzyme, is present in platelets. Methods Peripheral blood samples were collected in K2 EDTA tubes. Blood cells and platelets were separated and thoroughly washed to produce plasma-free samples. Procoagulant activity was measured in the cell lysates using a thrombin generation test or an adjusted prothrombin time (PT) test in plasma deficient of factor X. The findings were further supported by confocal microscopy, immunoprecipitation, flow cytometry, enzyme-linked immunosorbent assays and specific inhibition assays. Results FGL2 protein was readily detected in platelets. Also, despite being expressed by lymphocytes, FGL2 prothrombinase-like activity was solely detected in platelet samples, but not in white blood cell samples. Quiescent platelets were shown to contain the FGL2 protein in an active form. Upon activation, platelets secreted the active FGL2 into the milieu. Conclusions Active FGL2 is found in platelets. This suggests another role for the involvement of platelets in malignancies.
On the fractal patterns of language structures

Natural Language Processing (NLP) makes use of Artificial Intelligence algorithms to extract meaningful information from unstructured texts, i.e., content that lacks metadata and cannot easily be indexed or mapped onto standard database fields. It has several applications, from sentiment analysis and text summary to automatic language translation. In this work, we use NLP to figure out similar structural linguistic patterns among several different languages. We apply the word2vec algorithm that creates a vector representation for the words in a multidimensional space that maintains the meaning relationship between the words. From a large corpus we built this vectorial representation in a 100-dimensional space for English, Portuguese, German, Spanish, Russian, French, Chinese, Japanese, Korean, Italian, Arabic, Hebrew, Basque, Dutch, Swedish, Finnish, and Estonian. Then, we calculated the fractal dimensions of the structure that represents each language. The structures are multi-fractals with two different dimensions that we use, in addition to the token-dictionary size rate of the languages, to represent the languages in a three-dimensional space. Finally, analyzing the distance among languages in this space, we conclude that the closeness there is tendentially related to the distance in the Phylogenetic tree that depicts the lines of evolutionary descent of the languages from a common ancestor.