Miracle-dz/UniFAR-FTUs huggingface dataset:
Material and optical properties of low-temperature NH3-free PECVD SiNx layers for photonic applications

SiNx layers intended for photonic applications are typically fabricated using LPCVD and PECVD. These techniques rely on high-temperature processing (>400 °C) to obtain low propagation losses. An alternative version of PECVD SiNx layers deposited at temperatures below 400 °C with a recipe that does not use ammonia (NH3-free PECVD) was previously demonstrated to be a good option to fabricate strip waveguides with propagation losses <3 dB cm−1. We have conducted a systematic investigation of the influence of the deposition parameters on the material and optical properties of NH3-free PECVD SiNx layers fabricated at 350 °C using a design of experiments methodology. In particular, this paper discusses the effect of the SiH4 flow, RF power, chamber pressure and substrate on the structure, uniformity, roughness, deposition rate, refractive index, chemical composition, bond structure and H content of NH3-free PECVD SiNx layers. The results show that the properties and the propagation losses of the studied SiNx layers depend entirely on their compositional N/Si ratio, which is in fact the only parameter that can be directly tuned using the deposition parameters along with the film uniformity and deposition rate. These observations provide the means to optimise the propagation losses of the layers for photonic applications through the deposition parameters. In fact, we have been able to fabricate SiNx waveguides with H content <20%, good uniformity and propagation losses of 1.5 dB cm−1 at 1550 nm and <1 dB cm−1 at 1310 nm. As a result, this study can potentially help optimise the properties of the studied SiNx layers for different applications.
Modelling of breather for transformer health assessment

A mathematical model for estimating the moisture content in silica-gel inside a breather of a power transformer has been developed. The model equations are derived considering the possible real-time operating conditions of the transformer. These operating conditions are the fast rise or decrease of oil temperature due to a step change in the electrical loads and the cyclic heating and cooling of the oil due to the natural loading of the transformer. An experimental setup has been developed for monitoring the variations in moisture concentration in silica-gel inside an artificially constructed breather. Finally, the validation of the model has been done with the experimentally obtained data and the standard input signals. The model has been analysed using the equilibrium relations of the moisture concentration between the silica-gel and the environment of the breather. The response of the model indicates the dynamic behaviour of a moisture sensor placed in the breather. The model has been used in predicting the moisture level in the silica-gel, the moisture concentration inside the breather and the degradation in the performance of the silica-gel.
Comparative Analysis of Bitcoin and Ethereum

Since Bitcoin was launched in 2009, several new cryptocurrencies have been initiated with variations to Bitcoin’s original design. Although Bitcoin still remains the most prominent actor in the market, some technical problems have been raised to the design of the protocol. The objective of this thesis is to determine whether the newer cryptocurrencies handle the technical problems of Bitcoin, or if they also suffer from the same issues. Instead of evaluating several cryptocurrencies for this comparison, the cryptocurrency Ethereum has been chosen as a proxy for the others. Ethereum was started in 2014, is widely backed in the community and is second in line to Bitcoin when it comes to market capitalization. As a basis for the comparative analysis a rigorous study of the Bitcoin and Ethereum protocols have been performed, and parallel descriptions of the systems have been devised. Three technical problem have shaped the focus of the analysis: computational waste, concentration of power and ambiguity of transactions. Real world statistical data has been gathered and synthesized to enlighten the findings in the comparison. The main result of the comparison is that both systems suffer from the same problems to a certain degree, due to the fact that they utilize the same consensus mechanism. However, Ethereum utilizes several newer techniques to try and reduce the severity of these problems compared to Bitcoin, with varying degrees of success.
MOTION VECTOR PREDICTION USING RESELECTION AMONG CANDIDATE SET

For video coding standards with high compression ratio and good image quality, prediction is an essential step. If the prediction is more accurate, then lower bit-rate will be achieved. In this paper, a method is proposed to improve the coding efficiency for motion vectors using predicted motion vector candidate set (PMVCS). PMVCS consists of the motion vectors of blocks, which are the spatial and temporal neighbors of an encoding block. Using the proposed method, a better predicted motion vector can be obtained, which will result in fewer bits allocated for motion vectors. Compared with JIM18.4, the proposed method can reduce the bit allocation for motion vectors by 1.37% in average using the image sequence “Bus. ” The proposed method can reduce the bit allocation for motion vector of error correction technique by about 0.31% using the same image sequence.
A new Nested Graph Model for Data Integration

Despite graph data gained increasing interest in several fields, no data model suitable for both querying and integrating differently structured graph and (semi)structured data has been currently conceived. The lack of operators allowing combinations of (multiple) graphs in current graph query languages (graph joins), and on graph data structure allowing neither data integration nor nested multidimensional representations (graph nesting) are a possible motivation. In order to make such data integration possible, this thesis proposes a novel model (General Semistructured data Model) allowing the representation of both graphs and arbitrarily nested contents (e.g., one node can be contained by more than just one parent node), thus allowing the definition of a nested graph model, where both vertices and edges may include (overlapping) graphs. We provide two graph joins algorithms (Graph Conjunctive Equijoin Algorithm and Graph Conjunctive Less-equal Algorithm) and one graph nesting algorithm (Two HOp Separated Patterns). Their evaluation on top of our secondary memory representation showed the inefficiency of existing query languages’ query plan on top of their respective data models (relational, graph and document-oriented). In all three algorithms, the enhancement was possible by using an adjacency list graph representation, thus reducing the cost of joining the vertices with their respective outgoing (or ingoing) edges, and by associating hash values to both vertices and edges. As a secondary outcome of this thesis, a general data integration scenario is provided where both graph data and other semistructured and structured data could be represented and integrated into the General Semistructured data Model. A new query language outlines the feasibility of this approach (General Semistructured Query Language) over the former data model, also allowing to express both graph joins and graph nestings. This language is also capable of representing both traversal and data manipulation operators.
Metric Scales for Emotion Measurement

The scale quality of indirect and direct scalings of the intensity of emotional experiences was investigated from the perspective of representational measurement theory. Study 1 focused on sensory pleasantness and disgust, Study 2 on surprise and amusement, and Study 3 on relief and disappointment. In each study, the emotion intensities elicited by a set of stimuli were estimated using Ordinal Difference Scaling, an indirect probabilistic scaling method based on graded pair comparisons. The obtained scale values were used to select test cases for the quadruple axiom, a central axiom of difference measurement. A parametric bootstrap test was used to decide whether the participants’ difference judgments systematically violated the axiom. Most participants passed this test. The indirect scalings of these participants were then linearly correlated with their direct emotion intensity ratings to determine whether they agreed with them up to measurement error, and hence might be metric as well. The majority of the participants did not pass this test. The findings suggest that Ordinal Difference Scaling allows to measure emotion intensity on a metric scale level for most participants. As a consequence, quantitative emotion theories become amenable to empirical test on the individual level using indirect measurements of emotional experience.
Hypoplastic interface models for fine‐grained soils

Contact descriptions for interfaces between structural elements (e.g. piles, anchors and tunnel‐linings) and soils are widely used in geotechnical engineering. Most of these constitutive interface models, developed for sands, consider 2D conditions. For clays, only a limited number of 3D interface models exist. In this paper, the fine‐grained continuum models based on hypoplastic theories are adapted for the constitutive modelling of fine‐grained interfaces. To this end, we develop a general approach to convert the existing continuum soil models into an interface model adopting reduced stress and strain‐rate vectors and redefining tensorial operations in such a way that the formulation of the existing continuum models can be used without much modification. The hypoplastic Cam‐clay and the explicitly formulated hypoplastic models are adapted to model the interface behaviour. In addition to the reduced stress and strain tensor formulations, we introduce an additional variable reducing the strength and stiffness of the interfaces when compared with the strength and stiffness of the soil. For verification, experiments in constant volume and constant normal stress conditions have been simulated. A comparison of the available experimental data from the literature and the simulations is presented. It is shown that the new hypoplastic interface models can describe a number of important phenomena of clay–structure interfaces. Copyright © 2016 John Wiley & Sons, Ltd.
The length-biased weighted exponentiated inverted Weibull distribution

Abstract Length-Biased distributions are a special case of the more general form known as weighted distributions. We can exploit the conceptuality of Length-Biased distribution in the development of appropriate models for lifetime data. Its method is adjusting the original probability density function from real data and the expectation of those data. This modification can lead to correct conclusions of the models. Therefore, we introduced the Length-Biased version of the weighted Exponentiated inverted Weibull distribution in this paper. Various properties and the expressions for moments, coefficient of skewness, coefficient of kurtosis, moment generating function, hazard rate function, etc. are derived. The maximum likelihood estimates of the parameters of the proposed distribution are determined. The study results suggest that this distribution is an efficacious model in life time data analysis and other related fields.
Normalized cross-correlation based filtering process for face localization

In the real-time face recognition systems, locating faces in the input image should be fast and accurate. `Therefore, the need to introduce a face localization method with less complexity rises. Recently, Template-matching Approach has been used by different researchers to find the region of interest (face location) with different positions, lighting and cluttered backgrounds. However, some matching errors always occur with regard to the appearance of parts of the image as face location because of the variations of image pixels values. In this paper, faster and reliable pre-processing method is proposed to reduce the effects of the noise on image pixels values by applying a filtering process. The result showed an important and significant improvement in localization accuracy or precision compared to using the traditional NCC alone. Since this method was implemented, there has been an eleven percent (11%) increase in accuracy compared to the traditional NCC (80% localization accuracy). In this study, Yale University’s database is used to evaluate the proposed method.
Assessment of Traffic Noise Levels in the City of Pila

The last few decades have been characterized by the rapid development of technology and various industries around the world, as well as increasing levels of urbanization. The development of technology has resulted in the emergence of many inventions, vehicles and equipment. This has resulted in many unforeseen consequences generating threats to the environment in which humans’ function. One of these hazards is the noise emitted by vehicles. For this reason, environmental protection was created in response to threats to human existence [1]. For this reason, the main objective of this work is to determine the level of noise resulting from traffic transportation in the city of Sawtooth. In order to achieve the given objective in the city, sound values will be adopted and an acoustic map will be developed based on them. A large amount of noise in the city of Pila is caused by road transportation, but from the results of the study it can be said that it is minimally exceeded only on two streets by less than 5 decibels and on 3 other streets where it is equal to the permissible noise value. The main places where the most noise is generated are two-lane roads and traffic lights and traffic circles. A lot of noise is generated when there are a large number of vehicles slowing down and starting in these places. A very big plus in the fight against noise in Pila is public transportation.
Significant enhancement of the charging efficiency in the cavities of ferroelectrets through gas exchange during charging

Ferroelectrets are non-polar polymer foams or polymer systems with internally charged cavities. They are charged through a series of dielectric barrier discharges (DBDs) that are caused by the electrical breakdown of the gas inside the cavities. Thus, the breakdown strength of the gas strongly influences the charging process of ferroelectrets. A gas with a lower breakdown strength has a lower threshold voltage, thus decreasing the onset voltage for DBD charging. However, a lower threshold voltage also leads to a lower value for the remanent polarization, as back discharges that are caused by the electric field of the internally deposited charges can take place already at lower charge levels. On this basis, a charging strategy is proposed where the DBDs start in a gas with a lower breakdown strength (in the present example, helium) and are completed at a higher breakdown strength (e.g., nitrogen or atmospheric air). Thus, the exchange of the gas in the cavities during charging can significantly enhance the.
Application of Anisotropic Thin Plate Theory for Development of Displacements for Silicon <111> Crystals Plates in Cylindrical Systems

Abstract Silicon <111> crystal is one of the crystal orientations, which shows potential for application in micro device developments of pressure diaphragms for measurement purposes. To date, no theoretical basis has been examined to develop the deflections for computational analysis purposes [1]. This paper presents the development of the diaphragm deflections for Silicon <111> Crystal in Cylindrical coordinates system. The Silicon <111> crystal possesses transverse isotropic properties. Thus, an anisotropic thin plate theory is used here to develop the plate deflection. A numerical example is given to compare the theoretical results with Finite Element Analysis (FEA) results.
Large-Scale Insect Detection With Fine-Tuning YOLOX

With the aim of detecting insect pests at an early stage, there has been an increasing demand for insect pest detection and classification, particularly in large-scale setups. Therefore, the aim of this research is to introduce a new real-time pest detection technique using a deep convolutional neural network, which not only offers improved accuracy but also faster speed and less computational effort. The networks were constructed using various modern object detector models such as YOLOv4, YOLOv5, and YOLOX. Our proposed networks were evaluated on a standard large-scale insect pest dataset, IP102, as well as on our collected dataset, Insect10. The experimental results demonstrate that our system surpasses previous methods and achieves satisfactory performance with 84.84% mAP on the Insect10 dataset and 54.19% mAP on the IP102 dataset. Our system can deliver precise and real-time pest detection and identification for agricultural crops, enabling highly accurate end-to-end pest detection that can be applied in realistic farming scenarios.
Particle-mesh and meshless methods for a class of barotropic fluids

Recently, the Hamiltonian Particle-Mesh (HPM) method was proposed by J.Frank, G.Gottwald and S.Reich. It incorporates the procedure of artificial smoothing over a regular grid into the classical Smoothed Particle Hydrodynamics (SPH) formalism to improve the long-time stability of the method. HPM was applied to numerical solution of Shallow Water Equations (SWE), which are extensively used to simulate geophysical processes. So far, little research has been done to analyze and optimize HPM. The primary focus of our work is on the convergence of HPM method to solutions of a class of barotropic fluid equations. The convergence is investigated as smoothing scales vanish and as the number of particles grows unboundedly. The aim is to find an explicit relationship between these parameters to provide the best rate of convergence. For that purpose we adapt the convergence result for SPH obtained by K. Oelschlager. We consider HPM applied to the fluid model including SWE as a partial case and generalize the result to a self-gravitating fluid. Two new high-order meshfree methods for two-dimensional rotating shallow flows are proposed. They combine the conservation of Ertel potential vorticity with adaptive quadrature weights or moving least square approach for interpolation of scattered data. Generalizations for three-dimensional flows are discussed.
Flow Loss Analysis and Structural Optimization of Multiway Valves for Integrated Thermal Management Systems in Electric Vehicles

The multiway valve is the core component of the integrated thermal management system in an electric vehicle, and its heat transfer loss and pressure loss significantly impact the performance of the whole thermal management system. In this paper, heat transfer loss and pressure loss in multiway valves are investigated using three-dimensional unsteady numerical simulations. Heat transfer loss and pressure loss under different operating modes are revealed, and relationships between pressure loss and mass flow rate, inlet temperature, and valve materials are studied. The results show that the significant temperature gradient around the control shaft results in heat transfer loss and pressure loss mainly occurs around the junction of the control shaft and the shell, where the flow direction changes sharply. The pressure loss is nonlinearly and positively correlated with the mass flow rate. Furthermore, the main geometric parameters of the pipeline and the control shaft are optimized. The pressure loss firstly increases and then decreases, with the increasing curvature of the inner walls of the pipe corners in four flow channels. Compared with the structural optimization at the pipe corners, increasing the curvature of the inner wall of the control shaft and the shell corners reduces pressure loss continuously. Moreover, this study obtains an optimal structure with minimum pressure loss using coupled structure optimization at the control shaft and shell corners.
Potential of the Askaryan Fraction of the Radio Emission from Cosmic-Ray Air Shower for Xmax Reconstruction

There is an ongoing effort to improve the sensitivity of the IceTop surface array at the South Pole by the addition of surface radio antennas. With a simulation study, we investigated the dependencies of the Akaryan relative to the geomagnetic emission in the band of 70-350 MHz at the South Pole. We used CoREAS to simulate the radio emission from cosmic ray air showers at that location using a star-shape pattern and used the polarization of the radio emission on the ground to calculate the relative Askaryan fraction at the Cherenkov ring of the radio footprint. We then investigated the dependence of the Askaryan fraction on several shower parameters, among them, the distance to the shower maximum ( 𝑑 𝑋 max ). Based on the finding, we have developed a model that uses the average fraction as well as the shower geometry to reconstruct the mass-sensitive depth of shower maximum ( 𝑋 max ) for a given atmosphere. The theoretically achievable precision can compete with other methods for 𝑋 max measurement by radio arrays. Therefore, the Askaryan fraction - or more generally - the polarization of the radio signal may serve as an additional input for future multivariate approaches of 𝑋 max reconstruction.
Super-Resolution Imaging Reveals the Nanoscale Distributions of Dystroglycan and Integrin Itga7 in Zebrafish Muscle Fibers

Cell signaling is determined partially by the localization and abundance of proteins. Dystroglycan and integrin are both transmembrane receptors that connect the cytoskeleton inside muscle cells to the extracellular matrix outside muscle cells, maintaining proper adhesion and function of muscle. The position and abundance of Dystroglycan relative to integrins is thought to be important for muscle adhesion and function. The subcellular localization and quantification of these receptor proteins can be determined at the nanometer scale by FPALM super-resolution microscopy. We used FPALM to determine localizations of Dystroglycan and integrin proteins in muscle fibers of intact zebrafish (Danio rerio). Results were consistent with confocal imaging data, but illuminate further details at the nanoscale and show the feasibility of using FPALM to quantify interactions of two proteins in a whole organism.
An all-solid-state optical range camera for 3D real-time imaging with sub-centimeter depth resolution (SwissRanger)

A new miniaturized camera system that is capable of 3-dimensional imaging in real-time is presented. The compact imaging device is able to entirely capture its environment in all three spatial dimensions. It reliably and simultaneously delivers intensity data as well as range information on the objects and persons in the scene. The depth measurement is based on the time-of-flight (TOF) principle. A custom solid-state image sensor allows the parallel measurement of the phase, offset and amplitude of a radio frequency (RF) modulated light field that is emitted by the system and reflected back by the camera surroundings without requiring any mechanical scanning parts. In this paper, the theoretical background of the implemented TOF principle is presented, together with the technological requirements and detailed practical implementation issues of such a distance measuring system. Furthermore, the schematic overview of the complete 3D-camera system is provided. The experimental test results are presented and discussed. The present camera system can achieve sub-centimeter depth resolution for a wide range of operating conditions. A miniaturized version of such a 3D-solid-state camera, the SwissRanger 2, is presented as an example, illustrating the possibility of manufacturing compact, robust and cost effective ranging camera products for 3D imaging in real-time.