Miracle-dz/UniFAR-FTUs huggingface dataset:
Chaotic Oscillations of a Shallow Cylindrical Shell-Panel With a Concentrated Elastic-Support

This paper presents numerical solutions on chaotic oscillations of a shallow cylindrical shell-panel excited by a periodic acceleration. The shell with rectangular boundary is simply supported along all edges, and the center of the shell is supported by an elastic spring. The Donnell-Mushtari-Vlasov type equation is used with the modification of an inertia force. The governing equation is reduced to a nonlinear differential equation of a multi-degree-of-freedom system by the Bubnov-Galerkin procedure. To estimate regions of the chaotic response, periodic solutions of steady state response are first calculated by the harmonic balance method. Next, time evolutions of the chaotic motion are obtained numerically by the Runge-Kutta-Gill method. The chaotic response accompanied with a dynamic snap-through is identified both by means of Lyapunov exponents and Poincaré projections. For the shell with a spring, the Lyapunov dimension is smaller than for the case without the spring. Multiple modes of vibration contributes to the generation of chaos, in paticular, the higher modes of vibration are significant.
Enhancing transconductance of ultra-low-power two-stage folded cascode OTA

Using the Gm-C compensation technique, an ultra-low-power two-stage operational transconductance amplifier (OTA) with rail-to-rail input/output swing is presented. The input stage of the proposed OTA has the benefit of transconductance enhancement compared to the conventional OTA with the same power consumption and silicon area. Simulation results in a 0.18 μm CMOS technology show a DC gain enhancement of 9.5 dB as well as 88% improvement in gain bandwidth compared to the conventional folded cascode input stage structure.
Ventilation and window opening in schools, Experiments and Analysis

The objective of this thesis is to study the application of ventilation in schools buildings. A number of studies of the application of different forms of ventilation are presented. The main part of the thesis focuses on window opening in a classroom. Analytical models for calculation of the air change caused by window airing are proposed. The models are intended to be a tool for designers and occupants which they can use when they want to know how long a window should be open and how many windows should be opened. Tracer gas experiments have been performed both in a small test room and in classrooms. The specific conditions concerning airing require a special calculation method to determine the air change obtained during the tracer gas measurements. New methods for dealing with this have been proposed. The analytical models have been compared with the measurements. The results show that agreement is quite good and that the models can be used when rough estimates are of interest. The effect window airing has on a mechanical supply and exhaust system has been investigated by calculations with the computer program PFS. It is only when wind velocities are high that airing disturbs the flows in the system. The thesis include two studies concerning mechanical ventilation. A duct system with no means of balancing has been studied by calculation with the program PFS. A number of classrooms are assumed to be located next to each other. It is assumed that the flows to each room are equal and that the branch ducts to each room are equally spaced. The results show that a supply duct system may be designed without balancing. An exhaust duct system however requires balancing if the flows exhausted from the classrooms are to be of the same magnitude. Heat recovery in a ventilation system has also been studied by calculations. The energy need and the total costs including the whole service life have been calculated. It was found that heat recovery pays off even for a rather limited operating time. A sensitivity analysis has shown what factors are of significance when a heat exchanger is designed.
Effect of Strength Matching of Welded Joint on Stress Corrosion Cracking in Nuclear Power Structures

Stress corrosion cracking (SCC) is one of the key issues of welded structure failure in nuclear power plants. To understand the effect of strength matching on SCC growth rate in welded joint of primary coolant circuit safe end in pressured water reactor, a model of the safe end welded joint with mismatched strength was established by using elastic-plastic finite element method (EPFEM). The effect of weld strength matching on SCC growth rate was analyzed in this paper, by adopting crack tip strain rate as SCC mechanical driving force. The investigated results indicate that the distribution of plastic strain and plastic strain rate nearby the crack front is similar when the crack located at welded metal, and the driving force of SCC along the crack front in the over-match, even-match and under-match welded joint are from small to large, respectively, which implicit SCC growth rate along the crack front in the over-match, even-match and under-match welded joint also are from slow to fast, respectively. The investigating establishes a foundation for improving the predicting capability of SCC growth rate in nuclear power structures.
A direct-reading particle sizer with elemental composition analysis for large inhalable particles

Abstract There is a lack of aerosol measurement technology capable of quantifying, in real time, the size, concentration, and composition of large inhalable particles – specifically those with aerodynamic diameter larger than 20 µm. Aerosols of this size penetrate into the upper respiratory system upon inhalation and present surface contamination hazards upon settling. The objective of this work was to validate the performance of a prototype direct-reading particle sizer (DRPS) that counts and sizes particles via time-of-flight light scattering and determines single-particle elemental composition via laser-induced breakdown spectroscopy (LIBS). Counting, sizing, and spectral measurement efficiency were evaluated using test aerosols of multiple materials in the size range 25–125 µm. Particle sizing results showed good agreement with optical microscopy images, and LIBS measurements allow simultaneous elemental composition measurements. The relationship between the median aerodynamic diameters measured by the DRPS time-of-flight and optical microscopy was linear (Deming regression slope of 0.998) and strongly correlated (r 2 > 0.999). The mean absolute difference between the median aerodynamic diameters measured by the instrument by time-of-flight and microscopy over all eight test aerosol types was 0.9 µm with a mean difference in interquartile range of 1.9 µm. LIBS spectra have been collected and analyzed to reveal spectral features of species from silver-coated glass and titanium samples. The expected system performance for future field use is considered through numeric simulations based on the instrument parameters and assumed particle size distributions. Finally, potential hardware changes to optimize detection efficiency and facilitate field use are discussed.
TreeLoc: An Ensemble Learning-based Approach for Range Based Indoor Localization

: Learning-based localization plays a significant role in wireless indoor localization problems over deterministic or probabilistic-based methods. Recent works on machine learning-based indoor localization show the high accuracy of predicting over traditional localization methods existing. This paper presents a Received Signal Strength (RSS) based improved localization method called TreeLoc(Tree-Based Localization). This novel method is based on ensemble learning trees. Popular Decision Tree Regressor (DTR), Random Forest Regression (RFR), and Extra Tree Regressor have been investigated to develop the novel TreeLoc method. Out of the tested algorithm, the TreeLoc algorithm showed better performances in position estimation for indoor environments with RMSE 8.79 for the x coordinate and 8.83 for the y coordinate.
Alternative Displays for Discrete Movement Control

This research examined performance in a single-axis discrete positioning task using three different mappings for the visual display of the movement space. In a normal display condition, displayed distance was proportional to actual distance. In a split-screen condition, 66.5% of the initial distance to the target was mapped into 50% of the visual space and 33.5% of the distance (containing the target) was mapping into the remaining 50% of visual space. Finally, in a log screen condition there was a logarithmic mapping from actual to visual space. The split-screen and log screen conditions resulted in magnification of the space containing the target and compression of space distance from the target. Results for movement time (MT) showed a significant effect of target width. MTs were longer for smaller targets. Performance with normal and log screens was equivalent in terms of overall level and in terms of rate of increase in MT with reduction in target size. A smaller rate of increase, however, was found for the split-screen display. MTs for the smallest target were faster with the split-screen display. Evidence suggests that fewer corrective movements were required for the smaller targets when using the split screen.
Using the Archydro tool for watershed delineationCase of the Kherzet Youcef mine, North-eastern Algeria

This research article is attempted on the study of the morphological characteristics of the oued Loussif sub-watershed, located in the Wilaya of Sétif, Algeria. This study is part of a more general study on the hydrogeological study of the Kherzet Youcef deposit. In all fields interested in the study of spatial phenomena, a need for automation is emerging, especially for geographical structures of the ‘network’ type, given their systemic organization of space that is not explained in databases of geographical data. In order to meet this need for automation, the use of Geographic Information Systems has proven to be cost-effective. Morphological characteristics such as flow accumulation, flow direction and stream network were extracted on the basis of the digital elevation model (DEM), and the results were interpreted and analyzed. The geographic information system (GIS) based approach with the use of DME facilitates the understanding of the different morphological features represented in the thematic matrix data maps, and the correlation between flow accumulations, flow direction, stream order and stream network has been well explored. The study represents the morphological characteristics extracted from the DEM. The software used to perform the global analysis was ESRI ArcGIS version 10.8 with the ESRI Spatial Analyst and ArcHydro extension. Morphological features are effective in understanding the spatial distribution of the watercourse network and identifying potential groundwater locations.
Isotopic Evidence for the High Contribution of Wintertime Photochemistry to Particulate Nitrate Formation in Northern China

Stable isotopic constraint and observationally coupled atmospheric chemistry model are two robust means to identify the oxidation mechanisms for atmospheric particulate nitrate (NO3−) production. However, large discrepancies between the two approaches have been noted in the heavily polluted environments of North China Plain (NCP). Herein, daily PM2.5 samples (n = 418) were collected at five urban cities across NCP during the winter of 2017–2018; the ionic species (e.g., NO3− and methanesulfonic acid: MSA) and the dual‐isotopic signatures of NO3− were quantified. In this study, we revisited the O isotopic signatures of atmospheric O‐bearing molecules, especially that of OH radical in accordance with the up‐to‐date field measurements conducted in NCP regions. In brief, the δ18O‐OH was determined by the competition between the OH loss reaction rate and its isotopic equilibration reaction with H2O. Our improved isotopic results suggested that the daytime OH oxidation pathway was as important as the nocturnal channels in wintertime nitrate production in NCP (46.4% vs. 53.6%), whereas the exceedingly high loadings of NO3− in haze days were attributed to the heterogeneous chemistry of N2O5 hydrolysis. Chemical analysis also confirmed the importance of active photochemistry in secondary components production, as the MSA (a photooxidation product) linearly correlated with the NO3− (R2 = 0.86, p < 0.05). Our preliminary results compared well with the recent model simulations (e.g., sophisticated 3D model and observationally constraint model). To alleviate the winter haze in NCP, future emission regulations should aim to reduce the photochemical oxidants, particularly their precursors of NOx and VOCs simultaneously.
A Methodology for Consistent Georegistration in Underwater Hyperspectral Imaging

This article proposes a novel methodology for precise georegistration in underwater hyperspectral imaging (UHI) using a red–green–blue (RGB) camera to build a photogrammetry model that estimates the pose and a 3-D seabed model. The two main scientific contributions are: 1) the development of two methods for geometric calibration of the hyperspectral imager (HSI) with the RGB camera and 2) the development of a methodology for consistent georegistration of the pushbroom hyperspectral imagery on the seabed using the photogrammetry model and the geometrically calibrated HSI. The georegistration uses a calibrated RGB camera, fixed to the HSI, with an overlapping field of view. The RGB images are used to build a photogrammetry model. Through utilizing the geometric HSI parameters from the calibration, the hyperspectral imagery is ray cast onto the 3-D model. This methodology is exemplified for UHI from a remotely operated vehicle on a cold-water coral reef in the Trondheim Fjord, Norway. The precision is unprecedented for georegistration in UHI, demonstrated by the first-ever spatially consistent UHI mosaic to contain multiple transects.
Polarization shift keying: an efficient coherent optical modulation

Multilevel digital coherent optical modulation schemes based on the state of polarization of a fully polarized lightwave are proposed and analyzed. Based on the complete statistical characterization of the Stokes parameters, extracted through appropriate signal processing in the presence of shot and additive Gaussian noise, the optimum maximum likelihood receiver operating symbol by symbol is derived. A spectral analysis of the IF (intermediate frequency) signals is also presented. Exact performance in terms of average error probability is found for the proposed multilevel schemes, which turn out to be promising as compared to other standard modulation techniques. <<ETX>>
Acute and Subacute Studies of Thevetia peruviana Seed Methanol Extracts on Wistar Male Albino Rats

Thevetia peruviana seed kernels are widely used for suicide attempts in many countries including India. The aim of the present study was to evaluate the level of toxicity exposure of seed kernels by acute and subacute studies on male Wistar albino rats. Haematological parameters and serum biochemical studies were performed in all treated and control groups. In acute toxicity studies, no mortality was observed in groups treated with 100 and 250 mg/kg animals, but the mortality rate was 100 % in 500 mg/kg category. Lethality (lethal dose 50 %) associated with 70 % methanol extract was calculated as 375 mg/kg, revealed the narrow margin of safety lies in between 250 and 500 mg/kg. Exposure to subacute doses did not make any significant changes (p>0.05) in physical parameters like body weight and feeding habits of all treated groups (25, 50 and 100 mg/kg for consecutive 14 d). All groups recorded a progressive weight gain and normal food consumption and water intake (p>0.05) as compared with control. Total erythrocytes, haemoglobin concentration, lipid profile, serum electrolytes, bicarbonates, liver functioning enzymes, total protein, albumin, bilirubin, renal urea and creatinine levels were recorded normal in acute and subacute groups. From this experiment it is concluded that the level of toxicity and safety margin is very narrow and the seeds really take lives of organisms, whether the intake is accidental or deliberate.
Semantic-Based Opinion Summarization

The amount of information available online can be overwhelming for users to digest, specially when dealing with other users’ comments when making a decision about buying a product or service. In this context, opinion summarization systems are of great value, extracting important information from the texts and presenting them to the user in a more understandable manner. It is also known that the usage of semantic representations can benefit the quality of the generated summaries. This paper aims at developing opinion summarization methods based on Abstract Meaning Representation of texts in the Brazilian Portuguese language. Four different methods have been investigated, alongside some literature approaches. The results show that a Machine Learning-based method produced summaries of higher quality, outperforming other literature techniques on manually constructed semantic graphs. We also show that using parsed graphs over manually annotated ones harmed the output. Finally, an analysis of how important different types of information are for the summarization process suggests that using Sentiment Analysis features did not improve summary quality.
Interstate safety improvement program

The purpose of this paper is to prepare prioritized rankings of recommended improvements that could be implemented for the Interstate Safety Improvement Program in Kentucky. Considerable detail is presented that documents analysis procedures used to determine sites, sections, and elements of the roadway in need of improvement. The average number of accidents per interchange, bridge, 1.6-km (1.0-mile) section, and 0.48-km (0.3-mile) spot was summarized for large urban, medium urban, and rural sections of the Interstate system. At specified levels of statistical significance, critical numbers of accidents and critical accident rates were calculated to assist in identifying high-accident locations. A limited field inventory of the Interstate system was conducted, and the results are incorporated into the program. Dynamic programming was used to develop prioritized rankings for safety improvements that totaled approximately $27,500,000. A user's guide for preparation of a safety improvement program was developed. (Author)
Channel modelling and equalisation techniques for broadband mobile communications at 60 GHz

Currently within the RACE project, the feasibility of extending the broadband data services offered by fibre optic networks to mobile users is being investigated. The millimetric frequency band has been identified as a possible bearer for such a service, with the oxygen absorption region at 60 GHz being the current focus of attention. As data rates of up to 150 Mb/s may need to be supported, a central issue in the provision of such a service is the need for equalisation techniques to be employed at the receiver in order to mitigate against the severe intersymbol-interference that may result from multipath propagation. This paper, in addition to addressing the equalisation issues, also gives preliminary results of a channel modelling exercise, based upon channel measurements conducted at 60 GHz. It is envisaged that the channel modelling exercise will allow a statistical model to be constructed, describing the behaviour of the radio channel, which when incorporated into a Monte Carlo simulation of a radio link would allow assessments of various equalisers to be made. As this exercise is not yet complete, Monte Carlo simulations have been performed using measured channel responses instead and the results are reported here.
Learning to exploit dynamics for robot motor coordination

Humans exploit dynamics—gravity, inertia, joint coupling, elasticity, and so on—as a regular part of skillful, coordinated movements. Such movements comprise everyday activities, like reaching and walking, as well as highly practiced maneuvers as used in athletics and the performing arts. Robots, especially industrial manipulators, instead use control schemes that ordinarily cancel the complex, nonlinear dynamics that humans use to their advantage. Alternative schemes from the machine learning and intelligent control communities offer a number of potential benefits, such as improved efficiency, online skill acquisition, and tracking of nonstationary environments. However, the success of such methods depends a great deal on structure in the form of simplifying assumptions, prior knowledge, solution constraints and other heuristics that bias learning. My premise for this research is that crude kinematic information can supply the initial knowledge needed for learning complex robot motor skills—especially skills that exploit dynamics as humans do. This information is readily available from various sources such as a coach or human instructor, from theoretical analysis of a robot mechanism, or from conventional techniques for manipulator control. In this dissertation I investigate how each type of kinematic information can facilitate the learning of efficient “dynamic” skills. This research is multidisciplinary with contributions along several dimensions. With regard to biological motor control, I demonstrate that motor synergies, i.e. functional units that exploit dynamics, evolve when trial-and-error learning is applied to a particular model of motor skill acquisition. To analyze the effects of velocity on dynamic skills and motor learning, I derive an extension to the notion of dynamic manipulability that roboticists use to quantify a robot's capabilities before specification of a task. And along the machine learning dimension, I develop a supervised actor-critic architecture for learning a standard of correctness from a conventional controller while improving upon it through trial-and-error learning. Examples with both simulated and real manipulators demonstrate the benefits that this research holds for the development of skillful, coordinated robots.
Neural networks for truck backer-upper control system

Artificial neural networks have been studied for many years in the hope of achieving human-like performance in many fields. One of these fields is to use neural networks to solve highly nonlinear control systems. The multilayer feedforward neural network has proven to be a very powerful tool in this field. Nevertheless, such a network suffers from a very time-consuming training procedure. In this paper, based on radial-basis function and recurrent neural networks, the authors develop two different neural network systems for backing up a computer simulated truck to a loading dock in a planar parking lot. In the authors' simulations, these two neural networks are capable of learning from the training samples and performing generalization, and therefore provide viable alternatives to the multilayer feedforward neural network for real-world applications.