Miracle-dz/UniFAR-FTUs huggingface dataset:
Gait cycle prediction model based on gait kinematic using machine learning technique for assistive rehabilitation device

The gait cycle prediction model is critical for controlling assistive rehabilitation equipment like orthosis. The human gait model has recently used statistical models, but the dynamic properties of human physiology limit the current approach. Current human gait cycle prediction models need detailed kinematic and kinetic data of the human body as input parameters, and measuring them requires special instruments, making them difficult to use in real-world applications. In our study, three separate machine learning algorithms were used to create a human gait model: Gaussian process regression, support vector machine, and decision tree. The algorithm used to create the model's input parameters are height, weight, hip and knee angle, and ground reaction force (GRF). For better gait cycle model prediction, the models produced were enhanced by incorporating different sliding window data. The best gait period prediction model was DT with sliding window data (t−3), which had a root mean square error of 3.3018 and the R-squared (R-Value) of 0.97. The projection model focused on hip and knee angle and GRF was a feasible solution to controlling assistive rehabilitation devices during the gait cycle.
Climatology of Near‐Surface Daily Peak Wind Gusts Across Scandinavia: Observations and Model Simulations

An observed daily peak wind gusts (DPWG) dataset over Scandinavia, consisting of time series from 127 meteorological stations across Finland, Norway and Sweden, has been created. This dataset provides high‐quality and homogenized near‐surface DPWG series for Scandinavia, spanning the longest available time period (1996–2016). The aim of this study is to evaluate the ability of two regional climate models (RCMs) in simulating DPWG winds. According to the observed DPWG climatology, meteorological stations are classified into three regions for which wind conditions are influenced by similar physical processes: coast, inland and mountain. Smaller‐scale DPWG features of the three regions are only captured when coarser general circulation models or reanalyses are downscaled by a RCM. Dynamic downscaling is thus needed to achieve more realistic simulations of DPWG when compared to their driving models. The performances of the RCMs are found to be more dependent on model dynamics and physics (such as gust parametrization) than on the boundary conditions provided by the driving models. We also found that the RCMs cannot accurately simulate observed DPWG in inland and mountainous areas, suggesting the need for higher horizontal resolution and/or better representation of relevant boundary‐layer processes.
A comprehensive review of vehicle detection using computer vision

A crucial step in designing intelligent transport systems (ITS) is vehicle detection. The challenges of vehicle detection in urban roads arise because of camera position, background variations, occlusion, multiple foreground objects as well as vehicle pose. The current study provides a synopsis of state-of-the-art vehicle detection techniques, which are categorized according to motion and appearance-based techniques starting with frame differencing and background subtraction until feature extraction, a more complicated model in comparison. The advantages and disadvantages among the techniques are also highlighted with a conclusion as to the most accurate one for vehicle detection.
Modeling Ammonia and Its Uptake by Secondary Organic Aerosol Over China

Atmospheric ammonia (NH3) can affect nitrogen deposition, particle acidity, and gas‐particle partitioning. Although the inorganic chemistry of NH3 in fine particulate (PM2.5) formation are well‐constrained, the understanding of interactions between NH3 and secondary organic aerosol (SOA) are rather insufficient until recently. Laboratory studies indicate that NH3 molecule can react with SOA then forms nitrogen‐containing organic compounds (NOCs), which can further react to form heterocyclic organic compounds. In this study, we use a modified version of the CMAQ model to simulate the potential importance of the SOA‐ammonia uptake mechanism on air quality over China in summer and winter 2017, considering a range of assumed NH3 uptake coefficients (10−3–10−5). Our results show that uptake of NH3 by SOA leads to a decrease in gas‐phase NH3 mixing ratio, by as much as 27.5% and 19.0% for the highest uptake coefficient scenario (10−3) in summer and winter, respectively. The largest reduction of ammonia occurs over the Sichuan Basin and the North China Plain. The reduction of gas‐phase NH3 engenders a decrease of ammonium nitrate, by up to 30%, but has little impact on the ammonium sulfate concentration. Uptake of NH3 does not significantly affect SOA concentrations owing to overall moderate changes in aerosol acidity, and thus small effects on SOA formation from isoprene. Altogether, NH3 uptake led to a reduction in the average PM2.5 concentration up to 8.9% and 8.7% for the highest uptake coefficient (10−3) in summer and winter, respectively. These results highlight the need for better constraints on the NH3‐SOA interactions.
Engagement Detection through Facial Emotional Recognition Using a Shallow Residual Convolutional Neural Networks

: Online teaching and learning has recently turned out to be the order of the day, where majority of the learners undergo courses and trainings over the new environment. Learning through these platforms have created a requirement to understand if the learner is interested or not. Detecting engagement of the learners have sought increased attention to create learner centric models that can enhance the teaching and learning experience. The learner will over a period of time in the platform, tend to expose various emotions like engaged, bored, frustrated, confused, angry and other cues that can be classified as engaged or disengaged. This paper proposes in creating a Convolutional Neural Network (CNN) and enabling it with residual connections that can enhance the learning rate of the network and improve the classification on three Indian datasets that predominantly work on classroom engagement models. The proposed network performs well due to introduction of Residual learning that carries additional learning from the previous batch of layers into the next batch, Optimized Hyper Parametric (OHP) setting, increased dimensions of images for higher data abstraction and reduction of vanishing gradient problems resulting in managing overfitting issues. The Residual network introduced, consists of a shallow depth of 50 layers which has significantly produced an accuracy of 91.3% on ISED & iSAFE data while it achieves a 93.4% accuracy on the Daisee dataset. The average accuracy achieved by the classification network is 0.825 according to Cohens Kappa measure.
Combined Ionic and Hydrogen Bonding in Polymer Multilayer Thin Film for High Gas Barrier and Stretchiness

A unique polymer multilayer thin film with high gas barrier at high strain (>10%) was achieved with a combination of ionic and hydrogen bonding. Layer-by-layer assembly was used to deposit quadlayers (QL) of polyethylenimine (PEI), poly(acrylic acid) (PAA), poly(ethylene oxide) (PEO), and PAA. Altering the deposition pH of the various layers resulted in different physical and mechanical properties. PEI/PAA/PEO/PAA quadlayers assembled at pH 10/4/2.5/2.5 grow much thicker than the same film with all components deposited at pH 3, which is due to a porosity transition during assembly and in-and-out diffusion of the partially charged polyelectrolytes with high chain mobility (PEI at pH 10 and PAA at pH 4). The change in pH during the film assembly induces a porous structure in the 10/4/2.5/2.5 film that results in poor gas barrier. Films deposited on 1 mm thick polyurethane rubber at pH 3 have a densely packed structure with no pores. A 20 QL film (∼1 μm thick) achieves an oxygen transmission rate 15 times lo.
Effects of pyriproxyfen and Bacillus thuringiensis Berliner, 1915 on enzymatic antioxidant defense system and hemocytes of Galleria mellonella (L., 1758) (Lepidoptera: Pyralidae)

With the increasing uses of biological control methods, knowing the physiological and immunological effects of these insecticides on insects is essential for them to be used safely in agricultural areas. The aim of the study is to determine the effects of pyriproxyfen and Bacillus thuringiensis subsp. kurstaki individually and as a mixture on malondialdehyde levels (MDA), glutathione-s-transferase, acetylcholinesterase, cytochrome P450 enzyme activities in hemolymph, midgut, and fat body and total (THC) and differential hemocyte counts (DHC) of fifth instar larvae of Galleria mellonella (L., 1758) (Lepidoptera: Pyralidae) 24, 48 and 72 h after exposure under laboratory conditions (30 ± 1ºC, 65 ± 5% RH). The study was conducted in the Animal Physiology Research Laboratory of the Department of Biology, Faculty of Science and Letter, University of Çukurova between 2016-2018. Effects of these insecticides on antioxidant, detoxification enzyme activities and MDA levels were changed depends on exposure time and the differences of tissues. THC decreased after 24 h, whereas it had increased after 48 and 72 h. DHC induced depends on exposure time and applied insecticide. This study revealed that pyriproxyfen and B. thuringiensis applications caused biochemical, physiological reactions and effected the immune defense system of larvae by the alterations in hemocyte counts.
In silico comparative analysis of SARS-CoV-2 Nucleocapsid (N) protein using bioinformatics tools

The world has been encountered to one of the biggest pandemics that causing by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 is placed in the Beta-CoV genus in the Coronaviridae family. N protein is one of the crucial structural proteins of SARS-CoV-2 that binds to the genome thereby generating helical ribonucleoprotein core. It is involved in viral transcription/replication, translation, and viral assembly after entering the host cell through interacting with host proteins. N protein sequences of SARS-CoV-2 and taxonomically related CoVs are examined using bioinformatics tools and approaches including sequence alignment, sequence and phylogenetic analyzes, and predicting of putative N-Glycosylation and phosphorylation positions and also predictions and comparative analyzes are performed on 3D structures of N proteins from SARS-CoV-2 related CoVs through using of some of applied bioinformatics analyzes. Results of mega BLAST search revealed that the most similar N protein sequence to SARS-CoV-2 is Bat-CoV RaTG13 N protein sequence in the taxonomically related CoVs. SARS-CoV-2 is grouped with SARS, pangolin, civet and bat CoVs (RATG13, SL ZC45 and SL ZXC21) in N protein, nucleotide and protein based ML phylogenetic trees. Some of SARS-CoV-2 N proteins were showed divergence from other SARS-CoV-2 N proteins analyzed due to amino acid substitutions detected in SARS-CoV-2 N proteins samples in phylogenetic trees. The highest amino acid substitutions were detected in Richmont/USA (QJA42209.1) and Greece (QIZ16579.1) samples, with 2 and 3 place substitutions, respectively. By domain analyzes, three domains were detected as Corona_nucleocora (Pfam), N terminal CoV RNA-binding domain (HAMAP) and C terminal N protein dimerization domain (HAMAP). Possible N-glycosylation positions of SARS-CoV-2 N protein were predicted at two positions. Assessments of possible serine, threonine and tyrosine phosphorylations were found to be at 100 positions, 34 of them were higher than 80% possibility. 3D structure analysis based on TM scores revealed that although the results of 3D structure analysis were shown consistency with the taxonomy of the CoVs, the 3D structures of SARS-CoV-2 N protein and taxonomically related CoVs were not at the same fold.
A Comparison of Trajectory Planning and Control Frameworks for Cooperative Autonomous Driving

This work considers the cooperative trajectory-planning problem along a double lane change scenario for autonomous driving. In this paper, we develop two frameworks to solve this problem based on distributed model predictive control (MPC). The first approach solves a single nonlinear MPC problem. The general idea is to introduce a collision cost function in the optimization problem at the planning task to achieve a smooth and bounded collision function, and thus to prevent the need to implement tight hard constraints. The second method uses a hierarchical scheme with two main units: a trajectory-planning layer based on mixed-integer quadratic program (MIQP) computes an on-line collision-free trajectory using simplified motion dynamics, and a tracking controller unit to follow the trajectory from the higher level using the nonlinear vehicle model. Connected and automated vehicles (CAVs) sharing their planned trajectories lay the foundation of the cooperative behavior. In the tests and evaluation of the proposed methodologies, matlab-carsim cosimulation is utilized. carsim provides the high-fidelity model for the multibody vehicle dynamics. matlab-carsim conjoint simulation experiments compare both approaches for a cooperative double lane change maneuver of two vehicles moving along a one-way three-lane road with obstacles.
Öz-Düzenlemeli Öğrenme Uygulamaları Öğretmen Öz-Yeterlik Ölçeği’nin Türk Kültürüne Uyarlanması

Bu arastirma ogretmenlerin siniflarinda oz-duzenlemeli ogrenme uygulamalari bakimindan oz-yeterliklerini belirlemeyi saglayacak “Oz-duzenlemeli Ogrenme Uygulamalari Ogretmen Oz-yeterlik Olcegi”ni Turk kulturune uyarlamak ve olcegin psikometrik ozelliklerini ortaya koymak amaciyla yurutulmustur. Arastirma kapsaminda veriler 561 sinif ogretmeninden toplanmistir. Olcegin yapi gecerligini incelemek uzere 300 ogretmenden toplanan veri seti ile acimlayici faktor analizi, sonrasinda 261 ogretmenden toplanan ayri bir veri seti ile ise dogrulayici faktor analizi islemleri yurutulmustur. Yurutulen gecerlik ve guvenirlik calismalarina gore 22 madde ve 3 boyuttan (dogrudan ogretim oz-yeterligi; secenekler sunma oz-yeterligi; etkinlik sunumu ve degerlendirme sureci oz-yeterligi) olusan bir yapi elde edilmistir. Sonucta, Oz-duzenlemeli Ogrenme Uygulamalari Ogretmen Oz-yeterlik Olcegi Turkce formunun ogretmenlerin oz-duzenlemeli ogrenme uygulamalari bakimindan oz-yeterliklerini belirlemek amaciyla kullanilabilecek gecerli ve guvenilir bir olcme araci oldugu soylenebilir.
SHIFTING OF LAND USE IN SUSTAINABLE TOURISM: A LOCAL CULTURAL APPROACH IN INDONESIA

Tourism becomes a hotly discussed topic because it has a significant impact on the economy, social, and culture. This study analyzes changes in yard land use to support sustainable tourism based on local culture, namely the culture of harmony. This research was conducted through two approaches. The first was carried out qualitatively to see changes in depth in the use of Ubud community yards. The second is done quantitatively with the help of statistics to determine the impact of these changes. Data were collected through in-depth interviews with people who own land changes and through questionnaires. The selection of informants was based on recommendations from the traditional village leadership using the snowballing method. A total of 38 land owners have filled out the questionnaire correctly. The results of the qualitative research explained that most land-use changes were in palemahan 0r teba, which were initially used as a breeding place, remove dirt, and gardening functioned as a place to stay for tourists. The quantitative results explain that land changes based on a culture of harmony have a positive impact on the economy, social, culture, and environment. The results of this study support the development of sustainable tourism which is an important issue in today's era.
Design of a high performance AC-DC LED driver based on SEPIC topology

Light emitting diodes (LEDs) are current driven devices. So, it is essential to maintain the stability of LED voltage and current. Variation of temperature may cause of instabilities and bifurcations in the LED driver. Driving LEDs from an offline power source faces design challenges like it have to maintain low harmonics in input current, to achieve high power factor, high efficiency and to maintain constant LED current and to ensure long lifetime. This paper proposes the technique of harmonics reduction by using parametric optimization of Single ended primary inductor converter (SEPIC) based LED driver. Without optimization of SEPIC parameters input energy will not be properly transferred to the load and this un-transferred energy will be transmitted to the source. Consequently, the quality of input current will be hampered i.e. harmonics will contaminate the input current. Focussing this, the paper has presented the design of a non-isolated integrated-stage single-switch constant current LED driver operating in discontinuous conduction mode (DCM) in SEPIC incorporating the design of control circuit with soft start mechanism. This LED driver has achieved a good efficiency (90.6%) and high-power factor (0.98) with reduced harmonics (3.35%). System stability has been determined and simulation studies are performed to confirm the validity of the LED driver circuit. A laboratory prototype is built.
On Using a Low-Density Flash Lidar for Road Vehicle Tracking

This study uses a low-density solid-state flash lidar for estimating the trajectories of road vehicles in vehicle collision avoidance applications. Low-density flash lidars are inexpensive compared to the commonly used radars and point-cloud lidars, and have attracted the attention of vehicle manufacturers recently. However, tracking road vehicles using the sparse data provided by such sensors is challenging due to the few reflected measurement points obtained. In this paper, such challenges in the use of low-density flash lidars are identified and estimation algorithms to handle the same are presented. A method to use the amplitude information provided by the sensor for better localization of targets is evaluated using both physics-based simulations and experiments. A two-step hierarchical clustering algorithm is then employed to group multiple detections from a single object into one measurement, which is then associated with the corresponding object using a Joint Integrated Probabilistic Data Association (JIPDA) algorithm. A Kalman filter is used to estimate the longitudinal and lateral motion variables and the results are presented, which show that good tracking, especially in the lateral direction, can be achieved using the proposed algorithm despite the sparse measurements provided by the sensor.
Application of Chitosan on Paper Dyeing

The bleached kraft pulp was first treated by chitosan,then dyed by Cartasol Red 2FGN liquid and Cartasol Blue K-2R liquid repectively with aim to study the infuence of chitosan on dye process.It was found that the color chromaticity of paper dyed by direct dye increased with chitosan viscosity and dosage increasing respectively.Chitosan viscosity had little effect on chromaticity of paper dyed by cationic direct dye,while the dosage of chitosan was more sensitive to color chromaticity.It was also showed that color chromaticity didn't inrease significantly by raising the acidity of chitosan solution in both two dyes.Furthermore,the synergistic effect between Al2(SO3)4 and chitosan was good while using direct dye,but it was poor while using the cationtic direct dye.
Ionic liquid mediated synthesis of AgBr–Ag3PO4 nanostructures as highly efficient visible-light photocatalysts

AgBr–Ag3PO4 nanostructures, prepared by an ionic liquid-assisted precipitation method, were used as the effective visible-light driven photocatalytic system for the treatment of wastewaters. The prepared samples were characterised by X-ray diffraction powder (XRD), Diffuse Reflectance Spectroscopy (DRS), Fourier transform infrared (FTIR) spectroscopy, Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM) and nitrogen adsorption–desorption isotherms (BET) methods. The photoactivity of the products was studied by degradation of rhodamine B dye and Staphylococcus aureus (S. aureus) Gram-positive bacteria. The photoreaction kinetics and mechanism over the nanostructures was investigated and according to the results, the kinetic of dye degradation was realised to be pseudo-first order. Moreover, we observed that the bacterial regrowth was at the lowest level after the photocatalytic treatment. The photogenerated electron–holes reacted with the species in the solution and produced the reactive radicals such as OH•, HO2• and O2•‾ which can attack the organic pollutants and pathogenic micro-organisms. The reuse ability tests indicated that the prepared nanostructures had considerable capacity for the photodegradation of the dye after five times of repeated using.
Rain-induced characteristics in C- and X-band synthetic aperture radar observations of tropical cyclones

ABSTRACT This work focused on the rain-induced characteristics of synthetic aperture radar (SAR) at the C- and X-bands. Six SAR images were collected in tropical cyclones: four C-band dual-polarized Sentinel-1 (S-1) images during the 2016 hurricane season and two vertical–vertical) polarized TerraSAR-X (TS-X) images of Hurricane Sandy (2012). Wind speeds were retrieved from the S-1 images at the vertical–horizontal polarization channel, and winds from the TS-X images were obtained from the Hurricane Research Division of the National Oceanic and Atmospheric Administration . Simultaneously, Tropical Rainfall Measuring Mission (TRMM) rain rates, current data from the HYbrid Coordinate Ocean Model and wave spectra simulated by the WAVEWATCH-III (WW3) model were collocated. The three-scale backscattering model was employed to simulate the normalized radar cross-section (NRCS)without considering the rain effect, yielding a 2.21-dB root mean square errorand 2.23-dB for S-1 and TS-X, respectively. The difference between model-simulated and observed NRCS was analysed using the TRMM rain rate. The results indicate a linear relationship of the difference at the X-band with the TRMM rain rate, while the difference at the C-band exhibited a ‘V’ relationship with the TRMM rain rate. It was also discovered that the difference at the X-band decreased with increasing wind speed, while the difference at the C-band increased with increasing wind speed.
Enhanced switching performance of resistance random access memories by an inserted copper tellurium layer

In this work, we systematically investigate the effects of the insertion of the solid-state electrolyte material copper–tellurium (CuTe) in resistance random access memory (RRAM). The CuTe layer is inserted as Cu/CuTe/SiO2/TiN (top-to-bottom) and the device exhibits excellent resistance switching (RS) characteristics such as lower forming bias, a larger memory window and faster RS speed, compared to the Cu/SiO2/TiN device. This validates the effects of the inserted CuTe layer with a Cu electrode. Furthermore, an additionally fabricated Cu/CuTe/TiN device demonstrates that the CuTe layer can also successfully act as a middle insulator for the RRAM device, based on the obtained experimental results.