Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Neural Control of Quadcopter with Unknown Nonlinearities

This paper presents a robust control technique that uses adaptive neural control to stabilize and track the path of the quadcopter when the aerodynamic drag coefficient is assumed to be unknown. The proposed controller is designed for unknown nonlinearities associated with translational and rotational motion. The unknown nonlinearities are approximated using a Chebyshev neural network which is used for designing the controller by feedback linearization technique. The weights of the neural network are tuned by adaptive laws that utilize the Lyapunov analysis such that the closed loop stability convergence of the system using the adaptive controller is established. The proposed controller confirms asymptotic tracking and robustness under parameter uncertainties and external disturbances. The outcomes of numerical simulation demonstrate the efficacy of the proposed control approach.
Kinetics-Induced Block Matching and 5-D Transform Domain Filtering for Dynamic PET Image Denoising

Dynamic positron emission tomography (PET) scans of short-time frames are required to quantitatively estimate the uptake of PET ligands. Because such short-frame scans tend to be noisy, we propose kinetics-induced block matching and 5-D transform domain filtering (KIBM5D) specialized for dynamic PET image denoising. In the proposed algorithm, kinetics-induced block matching (KIBM) and 5-D transform domain filtering are alternately repeated in two cascading stages. In each stage of KIBM5D, all time frames are included in a patch of the KIBM to collect similar patch-wise time activity curves. These similar 4-D patches are then five-dimensionally grouped and transformed to the 5-D spectrum. In the 5-D transform domain, the 5-D spectrum is shrunk by hard thresholding and Wiener filtering in the first and second stage of KIBM5D, respectively. The sparsity of the 5-D spectrum is improved because signals of similar 4-D patches are correlated, while noises of these are uncorrelated. To evaluate the performance of KIBM5D, we used both computer simulation data of a dynamic digital brain phantom using [18F]FDG kinetics, and experimental data of a normal healthy volunteer using [11C]MeQAA, and compared the results of KIBM5D, Gaussian filter (GF), bilateral filter, nonlocal means, block matching and 4-D filtering, and 4-D Gaussian filtering. For simulation data, KIBM5D performed superiorly to the other methods in terms of the peak signal to noise ratio and structural similarity measures, in all time frames. Additionally, KIBM5D generated the best image quality not only in simulations but also with human data. Accordingly, KIBM5D enables the efficient denoising of dynamic PET images.
Design of Inset Feed Tri-Band Microstrip Patch Antenna for GPS and IRNSS Application

A low profile tri-band microstrip patch antenna is designed and fabricated for GPS and IRNSS application. The design involves Inset feeding technique and substrate FR_4 which is dielectric in nature. The slotted patch is designed using Keysight Technologies, Advanced Design System© where considerable antenna parameters were obtained for the simulated design and for the prototype when measured using Keysight N9917A Vector Network Analyser. Simulated results show that the patch resonates in L1 Band (1.575 GHz), L5 Band (1.176 GHz) and S-Band (2.49 GHz) with reasonable antenna parameter values.
Complete coverage path planning for pests-ridden in precision agriculture using UAV

The contribution of this work focuses on generating the best path for an UAV to distribute medicine to all the infected areas of an agriculture environment which contains non-convex obstacles, pest-free areas and pests-ridden areas. The algorithm for generating this trajectory can save the working time and the amount of medicine to be distributed to the whole agriculture infected areas. From the information on the map regarding the coordinates of the obstacles, non-infected areas, and infected areas, the infected areas are divided into several non-overlapping regions by using a clustering technique. There is a trade-off between the number of classes generated and the area of all the pests-ridden areas. After that, a polygon will be found to cover each of these infected regions. However, obstacles may occupy part of the area of these polygons that have been created previously. Each polygon that is occupied in part by obstacles can be further divided into a minimum number of obstacle-free convex polygons. Then, an optimal path length of boustrophedon trajectory will be created for each convex polygon that has been created for the UAV to follow. Finally, this paper deals with the process of creating a minimal path for the UAV to move between all the constructed convex polygons and generate the final trajectory for the UAV which ensures that all the infected agriculture areas will be covered by the medicine. The algorithm of the proposed method has been tested on MATLAB and can be used in precision agriculture.
Analysis of Stability and Control of Helicopter Flight Dynamics Through Mathematical Modeling in Matlab

This paper presents the mathematical model of helicopter flight dynamics. Helicopters are nonlinear systems. Generally, helicopters are considered to be more unstable than fixed wing aircraft and require a constant control strategy to counter the inherent instability. As a result, ensuring stability with proper control technique is the highest concern. In order to address these issues, the mathematical modeling begins by linearizing the translational and rotational equations with small perturbation theory. For simplification, some assumptions have been made. In this paper, the longitudinal and lateral coupling effect and tail rotor are neglected. Simulation results have been acquired from MATLAB© using the mentioned equations coupled with existing data available from previous published literatures of helicopter. A comparative analysis is then presented by estimating the results with three different models of helicopters. Also Linear Quadratic Regulator control is applied to improve the stability of the flight dynamics. The simulation results for the stability found satisfactory from the eigenvalue, stability derivatives and time response result.
Hand detection and segmentation using multimodal information from Kinect

Nowadays, hand gestures are becoming one of the most natural and intuitive ways of communication between human and computer. To this end, a complex process including hand gesture acquisition, hand detection, gesture representation and recognition must be carried out. This paper presents a method that detects hand and segments hand regions from images captured by a Kinect sensor. As Kinect sensor provides not only RGB images as conventional camera, but also depth and skeleton, in our work, we incorporate multi-modal data from Kinect to deal with hand detection and segmentation. Specifically, we use skeleton to approximately determine hand palm. Then a skin based detector will be applied to discard non-skin pixels from the region of interest. Using depth data helps to limit the human body regions and remove false positive regions from the previous steps. Finally, morphological operations will be applied to fill holes in the hand region. The main advantage of this method is very easy to implement and it performs in real-time on an ordinary computer. We evaluate the proposed method on a dataset of hand gestures captured from different viewpoints. Experiment shows that it provides reasonable accuracy at very high frame rate. It also produces comparable performance in comparison with deep learning based methods.
Design of Fractional-order Notch Filters

In this work we have discussed fractional-order notch filters of orders $(1+\alpha)$ and $(\alpha+\beta)$. The order range covered in both transfer functions is $1 < (1+\alpha) < 2$ and $0 < (\alpha+\beta) < 2$. Order $(\alpha+\beta)$ gives us a larger control over implementation of lower fractional orders (i.e. orders lesser than one). Both the transfer functions have been designed using second-order notch filter as a reference. Coefficient computation has been carried out using least squared error objective function and Genetic Algorithm Optimization technique. All the plots have been simulated with respect to the second-order notch filter magnitude response. Simulated designs of fractional-order notch filters thus obtained, may be used for a variety of applications.
Enabling Multistep Model Predictive Control for Transient Operation of Power Converters

Recently, an efficient multistep direct model predictive control (MPC) scheme for power converters has been proposed. It relies on the Sphere Decoding Algorithm (SDA) to solve the associated long-horizon optimal control problem. Since the SDA evaluates only a small number of candidate solutions to find the optimal one, a significant reduction in the average computational burden can be achieved compared to the basic exhaustive search approach. However, this is only true during steady-state operation. In fact, the SDA still requires a large execution time during transients. This paper shows that if not properly addressed, the dynamic performance of the system may be degraded, which clearly limits its practical application. To mitigate this issue, which particularly arises during transients, an efficient preconditioning approach for the SDA is proposed. This approach ensures that only a small number of candidate solutions are evaluated during both steady-state, and transients. This allows the multistep direct MPC to become a viable control alternative for power converters operating at low semiconductor switching frequencies, e.g., below 450 Hz. The proposal is validated using a grid-connected three-level converter as a case study. Both processor-in-the-loop simulations, and experimental results on a scaled-down 2.24 kVA laboratory setup are presented.
Multi-Robot Control for Adaptive Caging and Tracking of a Flood Area

In this paper, a control strategy for tracking the propagation of an expanding flood zone by using a group of unmanned aerial vehicles (UAVs), is developed. The control strategy addresses the following two issues. One is to averagely distribute a group of UAVs along the expanding boundary of the flood zone without collisions among each other. The other is to track the propagation of the flood region by keeping its boundary within the field of vision for each UAV. A combined control algorithm is proposed for dealing with both the flocking-based control and adaptive vision-based tracking problems. The feasibility of the algorithm is verified under simulations in the ROS/Gazebo environment.
Decentralized Robust k-connected Network with Unmanned Vehicles Using Vertex Connectivity

A robust network control law considering the failure of unmanned vehicles is proposed. The unmanned vehicles form a network and exchange information with neighbors. If some vehicles fail, the entire network may be disconnected and information cannot be exchanged. Therefore, the robust k-connected network which the network is connected even if less than k unmanned vehicles fail is configured in decentralized system. Each vehicle determines the velocity input according to the partial vertex connectivity which is evaluation of connectivity for each vehicle. Numerical simulations show that the proposed robust network control law is valid.
Study on the Relation Between Affective and Cognitive States for Automated EEG Analysis

The presented study examines the relation between states of affect, used in the dimensional model of emotions and cognitive brain activity. The analysis is performed using data provided in the DEAP database. In particular, an examination of the relation between the self-annotated ratings for EEG recordings made while the participants are watching music videos is performed. The recordings are scored using five criteria – “ arousal”, “ valence” “ dominance” “ liking” and “familiarity”. Analysis of the relations and dependencies between different ratings is conducted, with results showing that a correlation between the “familiarity” and “liking” scores exists.
Improving Passive Ankle Foot Orthosis System Using Estimated Ankle Velocity Reference

This study aims to investigate an appropriate ankle velocity reference (<inline-formula> <tex-math notation="LaTeX">$\omega _{\mathrm {ref}}$ </tex-math></inline-formula>), which is the average ankle velocity of a certain healthy subject when walking with a certain walking speed. The goal is to improve a Passive Controllable Ankle Foot Orthosis (PICAFO) by implementing the ankle velocity reference. Firstly, the function to estimate <inline-formula> <tex-math notation="LaTeX">$\omega _{\mathrm {ref,}}$ </tex-math></inline-formula> based on walking speed and body mass index (BMI), is obtained from 16 able-bodied subjects walking gait data. The effect of controlled stiffness (based on <inline-formula> <tex-math notation="LaTeX">$\omega _{\mathrm {ref}}$ </tex-math></inline-formula>) to the user’s ankle kinematics and muscle activity was evaluated by comparing it to other settings, such as walking barefooted and various constant damping stiffness (0%, 30%, 60%, and 100% of the maximum damping stiffness). Two able-bodied subjects (normal and overweight) participated in the evaluation, where they had to walk at two different walking speeds (1 and 2 km/h). The result showed that ankle kinematics and muscle activity were improved when <inline-formula> <tex-math notation="LaTeX">$\omega $ </tex-math></inline-formula> was controlled during walking speed of 1 km/h for both subjects. In terms of ankle kinematics, the toe clearance occurred, and walking stability increased. In terms of muscle activity, the average muscle activity had reduced by ~29% for the normal subject and by ~57% for an overweight subject, which shows that PICAFO provides necessary damping stiffness to replace the muscle works partially. In the future, by using the <inline-formula> <tex-math notation="LaTeX">$\omega _{\mathrm {ref}}$ </tex-math></inline-formula> based on walking speed and BMI, the therapists can skip the trial and error process of finding an appropriate PICAFO prescription for a post-stroke patient.
Is Quarantine for COVID-19 Pandemic Associated with Psychological Burden in Primary Ciliary Dyskinesia?

Background: Information on psychological impact of COVID-19 quarantine in primary ciliary dyskinesia (PCD), a chronic disorder with recurrent pulmonary exacerbations, is lacking. Psychological well-being was prospectively assessed during COVID-19 lockdown in Italy in a PCD population. Methods: we recruited 27 PCD patients and 27 healthy controls. To assess psychological well-being, psychological general well-being index and parenting stress index-short questionnaires were administered to participants ≥15 years-old and to mothers of participants <15 years-old, respectively. The PCD exacerbations since outbreak onset and frequency of quarantine weekly chest physiotherapy were compared to the same period of 2019. Outcomes: 70% of PCD mothers and 90% of PCD patients did not show parental stress levels or distress levels, respectively, and these groups showed no significant difference in stress compared to controls. The PCD pulmonary exacerbations occurred less frequently and weekly chest physiotherapy sessions significantly increased compared to the same period during 2019 (p < 0.05). Interpretation: During COVID-19 quarantine, a PCD population showed psychological well-being. Low exacerbation rate, explained by lower infectious exposure or improved compliance to chest physiotherapy, likely contributed to psychological well-being. Evaluating psychological burden and parental stress is a valuable tool for measuring the emotional impact of PCD and improving PCD medical care.
Volatile Gas Sensing through Terahertz Pipe Waveguide

Gas sensing to recognize volatile liquids is successfully conducted through pipe-guided terahertz (THz) radiation in a reflective and label-free manner. The hollow core of a pipe waveguide can efficiently deliver the sensing probe of the THz confined waveguide fields to any place where dangerous vapors exist. Target vapors that naturally diffuse from a sample site into the pipe core can be detected based on strong interaction between the probe and analyte. The power variation of the THz reflectance spectrum in response to various types and densities of vapors are characterized experimentally using a glass pipe. The most sensitive THz frequency of the pipe waveguide can recognize vapors with a resolution at a low part-per-million level. The investigation found that the sensitivity of the pipe-waveguide sensing scheme is dependent on the vapor absorption strength, which is strongly related to the molecular amount and properties including the dipole moment and mass of a gas molecule.
Global soil‐derived ammonia emissions from agricultural nitrogen fertilizer application: A refinement based on regional and crop‐specific emission factors

Ammonia (NH3) emissions from fertilized soils to the atmosphere and the subsequent deposition to land surface exert adverse effects on biogeochemical nitrogen (N) cycling. The region‐ and crop‐specific emission factors (EFs) of N fertilizer for NH3 are poorly developed and therefore the global estimate of soil NH3 emissions from agricultural N fertilizer application is constrained. Here we quantified the region‐ and crop‐specific NH3 EFs of N fertilizer by compiling data from 324 worldwide manipulative studies and focused to map the global soil NH3 emissions from agricultural N fertilizer application. Globally, the NH3 EFs averaged 12.56% and 14.12% for synthetic N fertilizer and manure, respectively. Regionally, south‐eastern Asia had the highest NH3 EFs of synthetic N fertilizer (19.48%) and Europe had the lowest (6%), which might have been associated with the regional discrepancy in the form and rate of N fertilizer use and management practices in agricultural production. Global agricultural NH3 emissions from the use of synthetic N fertilizer and manure in 2014 were estimated to be 12.32 and 3.79 Tg N/year, respectively. China (4.20 Tg N/year) followed by India (2.37 Tg N/year) and America (1.05 Tg N/year) together contributed to over 60% of the total global agricultural NH3 emissions from the use of synthetic N fertilizer. For crop‐specific emissions, the NH3 EFs averaged 11.13%–13.95% for the three main staple crops (i.e., maize, wheat, and rice), together accounting for 72% of synthetic N fertilizer‐induced NH3 emissions from croplands in the world and 70% in China. The region‐ and crop‐specific NH3 EFs of N fertilizer established in this study offer references to update the default EF in the IPCC Tier 1 guideline. This work also provides an insight into the spatial variation of soil‐derived NH3 emissions from the use of synthetic N fertilizer in agriculture at the global and regional scales.
Idiosyncratic preferences in transparent motion and binocular rivalry are dissociable

Previous studies revealed that there are idiosyncratic preferences to perceive certain motion directions in front during motion transparency depth rivalry (Mamassian & Wallace, 2010; Schütz, 2014). Meanwhile, other studies reported idiosyncratic preferences in binocular rivalry during the onset stage (Carter & Cavanagh, 2007; Stanley, Carter, & Forte, 2011). Here we investigated the relationship of idiosyncratic preferences in transparent motion and binocular rivalry. We presented two dot clouds that were moving in opposite directions. In the transparent motion condition, both dot clouds were presented to both eyes and participants had to report the dot cloud they perceived in front. In the binocular rivalry condition, the dot clouds were presented to different eyes and participants had to report the dominant dot cloud. There were strong idiosyncratic directional preferences in transparent motion and rather weak directional preferences in binocular rivalry. In general, binocular rivalry was dominated by biases in contrast polarity, whereas transparent motion was dominated by biases in motion direction. A circular correlation analysis showed no correlation between directional preferences in transparent motion and binocular rivalry. These findings show that idiosyncratic preferences in a visual feature can be dissociated at different stages of processing.
Prospective Analysis of an Evidence-Based Symptom Set in Superior Canal Dehiscence Syndrome

Supplemental Digital Content is available in the text Introduction: Superior canal dehiscence syndrome (SCDS) is characterized by a defect in the bone overlying the superior semicircular canal. This third mobile window generates an abnormal low-impedance pathway for sound/pressure transmission into the inner ear resulting in the characteristic symptoms. Objective: To perform a prospective analysis of symptoms in patients with SCDS. Methods: An aggregated symptom set was studied prospectively and compared with a healthy control group. The 31 items inquired about the presence and severity of symptoms. Initial comparison between both groups was performed using the Kolmogorov–Smirnov test and nonparametric Mann–Whitney U test. For analysis of the internal consistency, the Cronbach's alpha coefficient was determined. Finally, the prevalence of symptoms obtained in the present study was compared to the prevalence of symptoms obtained as part of a recent retrospective systematic review. Results: Responses from the 29 patients with SCDS in the case group and the 58 healthy controls were not normally distributed. Those with SCDS had a higher prevalence and more severe symptoms for almost all items. The Cronbach's alpha coefficient of 0.969 indicates an excellent internal consistency. The prospective prevalence of most symptoms was higher than the retrospective prevalence reported earlier. Conclusions: SCDS causes a variety of vestibular and auditory symptoms. This prospective study demonstrates that their prevalence and severity are higher than reported previously. This symptom set demonstrates excellent internal consistency and will serve as a foundation toward developing a disease-specific patient-reported outcome measure for SCDS. Level of evidence: NA
Perceptions of control and disordered eating behaviors during college transitions

Abstract Objectives Disordered eating behaviors are prevalent among college-age individuals. Issues of control (e.g., perceptions of control; desire for control) are often salient for these individuals. Concerns regarding control can be exacerbated during transitions. The current study examined the extent to which disordered eating behaviors in college were predicted by locus of control, desire for control, and their interaction. We also explored whether these associations might be impacted by student life transitions (e.g., into/out of college). Participants and methods: A sample of 156 college students (72% women) was surveyed. Results: Both locus of and desire for control were predictive of disordered eating, but hypothesized moderations among locus of control, desire for control, and life transitions were primarily not supported. Conclusions: Issues surrounding perceptions of control are important for disordered eating treatments or prevention programs, while more research is needed on the role life transitions may play in exacerbating risk.