Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Tracking for Nonlinear Interconnected Dynamic Systems using State Dependent Riccati Equation

This paper considers the problem of optimal control of nonlinear single and multiple interconnected dynamic systems using state dependent Riccati equation (SDRE). SDRE method mimics the classical LQR method of optimal linear control for a large class of nonlinear systems. It relies on a non-unique factorization of nonlinear systems known as the state dependent coefficient (SDC) parametrization. The paper initially provides a comprehensive derivation of SDRE for a single nonlinear system represented by SDC. Then, the necessary equations are given for multiple interconnected dynamic system based on the generalized SDC representation. We show the effectiveness of SDRE method and compare it with the method of control law partitioning or the method of computed-torque control (CTC), which has been used in control of robotics manipulators. Illustrative examples are given to demonstrate the usefulness of SDRE method as applied to single and multiple interconnected inverted pendulum as well as robotic manipulator.
Visualizing Electron-Molecule Dynamics with In-situ Fluorescence in a Few eV-SEM

Understanding and directing the pathways of reactions between molecules and energetic electrons is important for a wide variety of technological applications such as electron microscopy, electronand XUV-lithography, and electron-beam induced deposition. In most cases, reactions with low-energy secondary electrons (energies of <50eV) generated in the environment of the molecule, have cross sections dominating over contributions from higher energy electrons. For these low energy electrons, there can be many different degradation and/or dissociation pathways involved at the molecular level [1]. Disentangling the different contributions can be challenging, especially for complex but relevant samples such as polymers, organic compounds, and biological tissues. Typically, one evaluates in some experimental way the end products obtained after reaction, leaving transient dynamics obscured. Here, we present a novel approach to study low-energy electron induced molecular degradation by combining in-situ fluorescence microscopy with electron irradiation of organic fluorescent molecules to report on the reaction kinetics occurring in the sample.
Human Detection for Video Surveillance in Hospital

This paper presents a human detection system in a vision-based hospital surveillance environment. The system is composed of three subsystems, i.e. background segmentation subsystem (BSS), human feature extraction subsystem (HFES), and human recognition subsystem (HRS). The codebook background model is applied in the BSS, the histogram of oriented gradients (HOG) features are used in the HFES, and the support vector machine (SVM) classification is employed in the HRS. By means of the integration of these subsystems, the human detection in a vision-based hospital surveillance environment is performed. Experimental results show that the proposed system can effectively detect most of the people in hospital surveillance video sequences.
Intra lake spatial variations in pollution patterns of eel A. anguilla

1 Institute for Forestry and Game Management, Duboislaan 14, B-1560 Groenendaal-Hoeilaart, Belgium 2 Catholic University of Leuven, Laboratory for Ecology and Aquaculture, De Beriotstraat 32, B-3000 Leuven, Belgium 3 Veterinary and Agrochemical Research Centre, Leuvensesteenweg 17, B-3080 Tervuren, Belgium 4 Centre for Agricultural Research, Sea Fisheries Department, Ankerstraat 1, B-8400 Ostend, Belgium
Nanoscale Quantification of Interstitial Oxygen in Hyperstoichiometric UO2+x

The safe use and disposal of oxide-based nuclear fuels depends on comprehensive models for oxidative processes, which can guide operation, long-term waste storage, and accident cleanup efforts. Because of their strategic importance and potential ecological impact, the oxidative behavior of the actinides (Th, Pa, U, Np, Pu) has been studied for many decades. These elements possess a complex 5f electron configuration and exist in multiple valence states, leading to a range of exotic electronic and magnetic phase transitions that are influenced by oxygen defects. The oxidative behavior of the uraninite (UO2+x) system has received particular attention because of its use as a nuclear fuel, as well as its ability to readily adopt oxidation states spanning U4+ à U6+. The latter property has significant implications for the contamination of groundwater at waste storage sites, necessitating improved atomistic models for oxidation in ambient conditions.
Developing A MOOC Initiative: Lessons Learned from the Universitat Politècnica de València Experience

Universitat Politecnica de Valencia (UPV) was the European institution with more MOOC course runs done by December 2016. This paper describes and analyses the decision-making process, and rationale of the development of this low budget real MOOC institutional initiative carried out by a traditional higher educational medium sized institution. This analysis is done using an Evaluative Research (ER) method based on an iterative approach of 6 cycles of formative evaluation. It has been a multiple stage process that includes many aspects. In this paper, we will analyze two of them: the creation, organization and management of a fast and cheap MOOC production process, including the several tools, plans, and procedures that have enabled UPV to create courses fast and with a low-cost; and the technical evolution of the initiative, with the different platforms that have been used. As a consequence of this process, UPV has its own platform (upvx.es) based on openedX and is a member of edx.org, with 50 courses, 177 editions, and more than 632.000 enrollments. The completion rate is 8.69%, and post-course surveys reveal a high level of satisfaction from students. The paper will finish addressing the challenges of making this an entirely self-sustainable initiative and reflecting about what is required for evaluating this experience globally.
Atomistic modeling of interfacial and thermal transport properties of engineered graphene structures

The immense amount of research on graphene in the last decade has led to advancement in techniques to control the thermo-physical properties of graphene by making use of engineered graphene structures. Carefully designed defective graphene, van der Waals heterostructures, functionalized graphene and engineered graphene surfaces have potential applications in photoelectronics and thermoelectrics devices, as electrode materials, phase-change materials for thermal energy storage, sensors, coatings etc. In this study, we focus on the interfacial and thermal transport phenomena within these engineered graphene nano-structures. The main objective of this dissertation is to understand the mechanism of heat transfer across the nano-structures and analyze the molecular interactions at the interface which governs the surface properties like interfacial thermal resistance, viscosity and wettability. We use atomistic modelling to evaluate these materials and compare the results with experiments. The degradation of thermal conductivity with concentration of isotope and vacancy defects in graphene was analyzed using molecular dynamics (MD). The results qualitatively match with collaborative experimental and theoretical efforts based on Boltzmann transport equation (BTE). We next investigate contrasting behavior of thermal conductivity and sheet conductance in graphene/MoS2 van der Waals heterostructure. The phonon relaxation times and thermal conductivity in graphene are suppressed due to the weak van der Waals interaction with the adjacent layers. We also experimentally and computationally characterize thermo-physical properties of a mixture of neicosane phase change material and graphite particles (GP). Our results show a large enhancement in k (450%) and μ (1200%) for a 3.5% vol. concentration of GP fillers. The surprising reduction in interfacial thermal resistance (Reff) with increasing filler concentration, together with the high
Numerical Modeling of Heat and Water Transport with Heat Exchange in Unsaturated-Saturated Porous Media Including Heat Influence on Flow

We discuss the numerical modelling of heat transport with contaminated water into unsaturated-saturated porous media. We focus on the determination of a heat exchange with the matrix of the porous media and adsorption of a contaminant. Numerical modelling includes the influence of temperature and adsorbed contaminant on hydraulic permeability. We also discuss the water volume extension due to the temperature change. This is motivated by hydrothermal isolation properties of building facades under the influence of external weather conditions. Also, contaminant dissolved in the water could be interpreted, e.g., as the salt which can degrade the quality of concrete and other building elements. Dependence of hydraulic permeability on the temperature, concentration of a contaminant, amount of adsorbed contaminant and saturation is discussed on the base of van Genuchten empirical law for unsaturated porous media. An efficient numerical approximation is proposed by means of which we solve the direct and inverse problems of the complex model. The determination of the model parameters we solve by inverse methods. In our numerical experiments, we show the significant sensitivity of hydraulic permeability on temperature and adsorption and the weak sensitivity on water extensions in the physically relevant temperature change. For the solution of inverse problems in laboratory experiments, we suggest the 3D sample in a cylindrical form which enables many experimental scenarios created by suitable boundary conditions.
Information-Centric Scheduling: Queue Shortening in WSNs via Spatio-Temporal Compression

In this paper, we address the problem of minimizing the queue length for data gathering in wireless sensor networks (WSNs) while considering the quality of the information received at the sink. We extend the nominated Slepian-Wolf-Cover bound for distributed source coding (DSC) into a blockwise streaming scheme, where distributed sources could be compressed without loss exploiting the spatio-temporal correlations between samples from individual sensor nodes. Moreover, unlike the classic bound which requires statistical information of the correlated sources a priori, our novel time-average inequality can dynamically adapt to arbitrary ergodic statistics for every scheduling period. On the other hand, since radio resource is often finite, not all information stored in the queues can be delivered to the base station. As long as the desired fidelity requirement is satisfied, we find the queues can be further shortened by proactively discarding some data within. We contrive a stochastic online optimization problem and resolve it with the proposed information-centric scheduling algorithm. Evaluation results show such an information-centric design can significantly decrease the time-averaged queue length.
A Real-Time Target Tracking Method for SEM Images Based on Template Matching

Micro-nano materials and their manufacture have become increasingly commonly used in the field of chip manufacturing as nanotechnology has advanced. In this area, the use of carbon nanotubes (CNTs) to build high-performance three-dimensional micro-nano devices has gotten a lot of interest. The micro-nano manipulation robot system built in the scanning electron microscope (SEM) is currently used to assemble carbon nanotube devices. Secondary electron detectors in SEMs are used to record secondary electron scanning pictures as a perceptual tool for automated assembly visual guidance. This paper describes how SEM images are used to provide visual guidance for the assembly of CNTs. SEM image noise sources and components were investigated. A carbon nanotube image tracking system based on template matching with scale invariance and rotation invariance was suggested, based on noise components and denoising. Its accuracy error is not more than 6 pixels and the frame rate reaches 26.39 FPS which meets the real-time requirements.
A Review of Techniques for Parameter Determination and Efficiency Mapping in PMSM

Recent developments in the field of electric vehicles have led to a renewed interest in permanent magnet synchronous machines due to its unique characteristics and performance. In this paper, the state of the art of modelling and efficiency mapping techniques for permanent magnet synchronous motors are re-viewed. Then an efficiency mapping test is done experimentally to validate a simple direct-quadrature model. The good correlation obtained from this model, with an error lower than 2% for the majority of the operating points, shows that the model is adequate for representing the behavior of the machine. Future work will be oriented to develop more complex models and to validate simpler experimental parameters determination techniques.
Urban tree pests and natural enemies respond to habitat at different spatial scales

Trees provide many ecosystem services in our urban environments. However, city trees are often stressed by pests that are typically higher than those in nearby natural areas. Our research highlights a potential mismatch in scale between the habitat elements that affect the densities of pests and their natural enemies on city trees. We tested a well-known ecological concept, the enemies hypothesis, in the city, where relationships of pests and their enemies have not been thoroughly studied. To test our hypothesis that natural enemies and aphid predation services on urban trees increase with more local structural complexity around trees, we collected data on crape myrtle trees on NC State University’s campus from 2016 to 2017. We measured local structural complexity of vegetation around study trees, quantified impervious cover among other urban habitat elements, collected crape myrtle aphids (Tinocallis kahawaluokalani) and their natural enemies on trees, and performed predation experiments. We found that aphid abundance was positively correlated with more impervious cover within 100 m of crape myrtle trees. Alternatively, greater local structural complexity within the 10 × 10 m area around crape myrtles correlated with a higher abundance of natural enemies. Aphid predation was mostly predicted by local structural complexity and impervious cover within 20 m of crape myrtle trees. Together, these findings suggest that although the impervious nature of our cities may mean higher densities of some pests, local landscapes around trees can play an important role in maintaining natural enemies and predation services that help regulate pest populations.
Text Simplification without Simplified Corpora

Text simplification is the task of rewriting complex text into a simpler form while preserving its meaning. Systems that automatically pursue this task can potentially be used for assisting reading comprehension of less language-competent people, such as learners and children. Such systems would also improve the performance of other Natural Language Processing applications. As with machine translation and abstractive summarization, this task is positioned as a Text-to-Text Generation task in natural language processing. Current work has two approaches: lexical substitution and monolingual translation. In the former, a simpler synonymous sentence is generated by the pipeline of complex word identification, substitution generation, and substitution ranking. In the latter, a simpler synonymous sentence is generated using machine translation tools. In both approaches, mainstream methods acquire simplification rules from a large-scale parallel corpus. Therefore, text simplification was studied mainly in English for where rich resources are available. However, a large-scale simplified corpus for text simplification cannot be used in many language other than English. In this research, we propose text simplification methods by lexical substitution approach and monolingual translation approach for languages that cannot use large-scale simplified corpora, especially Japanese. As a lexical substitution approach without simplified corpora, we propose novel paraphrase acquisition, meaning preservation filtering, simplicity filtering, and grammaticality ranking methods for Japanese. In addition, as a monolingual translation approach without simplified corpora, we construct a pseudo-parallel corpus for text simplification from a raw corpus using readability assessment and sentence alignment, and enable text simplification using machine translation tools in any language. ∗Doctoral Dissertation, Department of Information and Communication Systems, Graduate School of System Design, Tokyo Metropolitan University, March 22, 2018.
Sensorless Vector Control of IPMSM in Full Speed Range

For the Interior permanent magnet synchronous motor (IPMSM), according to the principle of minimizing the current vector amplitude required to output the same torque, the vector control strategy of maximum torque per ampere control (MTPA) below the base speed and flux weakening above the base speed is adopted. At this time, the copper loss of the motor is the smallest and the efficiency of the motor is the best. For the rotor position information required in vector control, the sliding mode observer is used to estimate the rotor position and speed in the medium and high-speed section, the high-frequency square wave voltage signal injection method is used to estimate the rotor position information in the low-speed section, and the weighting coefficient method is used to realize the smooth switching of the observation algorithms in the low-speed section and the medium and high-speed section. The Simulink simulation results show that the proposed method can accurately track the current working point and rotor position of vector control, and the rotor position error is controlled within 0.02 radian in steady-state operation.
Data Aggregation in Wireless Sensor Networks

The basic role of a wireless sensor network is to collect information from the environment by many sensor nodes (SNs). The SN typically has a finite battery life and nodes' failures can lead to network partition. Therefore, it is important to minimize the energy usage of each sensor node and to manage the power of SN in critical position that their failure could divide the network. This drives research on how to design routing protocols to gather data efficiently, so that the life of the network can be prolonged. A usual concept to collect data by a sink node is to transfer data from sensor nodes to the sink node by multi-hop. To resolves the problems, a new energy balanced and efficient data aggregation scheme for WSN is used. With a predetermined set of paths based on the specific Application.
Multi-Color Electron Microscopy of Cellular Ultrastructure Using 4D-STEM

Transmission electron microscopy (TEM) is the primary method for acquiring high-resolution images of cellular ultrastructure of biological samples. Alternatively, fluorescence light microscopy techniques are capable of labeling different cellular components with different dyes, and distinguishing them to form multicolor images; however, at a much lower resolution [1]. This serious limitation was recently addressed through the development of “multi-color EM,” which uses selective lanthanide ion tagging and electron energy-loss filtered imaging [1,2] to generate data analogous to multi-color fluorescence microscopy, but at ~100× the magnification. While this technique promises to reveal novel structural information, it depends on a very small fraction of the electrons (typically << 1%) that have lost energy due to a coreloss excitation to create the elemental maps. This makes the method extremely tedious and slow to execute, while producing noisy images that sometimes can be difficult to interpret.
Parameter extraction, modelling and circuit design for electrolyte-gated transistors on paper

Flexible and paper electronics have been getting a lot of attention in the last years. Not only from the scientific community, but also from the end consumer. This ultimately converges in efforts pushing towards the discovery of new and better materials for the TFT technology. With this fast development of new devices, compact models for circuit simulation based on older FETs become obsolete. The availability of fast and accurate models is an essential part of going from single, proof-of-concept devices, to fully operational circuits. In this work, done in the Department of Engineering of the University of Cambridge, the electrical characterization and parameter extraction of state-of-the-art electrolytegated transistors (EGT) on paper substrate, fabricated at UNINOVA/I3N, led to the development of a compact model capable of describing the behaviour of the devices. A detailed overview of the model is provided throughout this work, from the characterization of the device, to simple circuit simulations using a dozen of devices. This, together with the provided Verilog-A code for CAD software implementation, will allow both new and experienced users in circuit design to simulate simple circuits with these EGTs or any other TFT device with similar behaviour with simple tweaks on the model.
MRI-based Tumour Prediction based on U-Net and VGG-Net

In the detection and treatment of life-threatening disorders, biomedical technology plays a critical role. Brain tumours have recently become one of the most frequent and dangerous disorders. The treatment of brain tumours is dependent on the experience and understanding of doctors. As a result, for radiologists and clinicians to assist in the identification of brain tumours, an automated tumour detection system is critical. To detect brain tumours, accurate analysis of magnetic resonance imaging (MRI) scans is required, and this study provides an effective approach for predicting brain malignancies using U-Net and VGG-Net. Image pre-processing algorithms that find extreme shapes to remove black borders from pictures are examples of data augmentation. Photos are then resized to their proper dimensions. A ReLU Optimizer has indeed been added to our network in order to speed the training process. To get the model as accurate as possible, it is trained and tested on an MRI image dataset. The performance of the maximized system is evaluated with 0.92 accuracies.
Ultrahigh-Q photonic crystal nanocavities based on 4H silicon carbide

Photonic nanocavities with high quality (Q) factors are essential components for integrated optical circuits. The use of crystalline silicon carbide (SiC) for such nanocavities enables the realization of devices with superior properties. We fabricate ultrahigh-Q SiC photonic crystal nanocavities by etching air holes into a 4H-SiC slab that is prepared without using hydrogen ion implantation, which usually causes higher absorption losses. In addition, compared to usual designs, a relatively thin slab is utilized to avoid losses through cross-polarized mode coupling induced by the tapered air holes. We obtain a heterostructure nanocavity with a high experimental Q factor of 6.3×105, which is 16 times larger than the highest Q among the previously reported values for nanocavities based on crystalline SiC. We also show that our nanocavity exhibits a high normalized second-harmonic conversion efficiency of 1900%/W.
RESEARCH AND ANALYSIS METHOD COMPARISON IN FINNISH RELIABILITY WORTH STUDY

In Finland, Helsinki University of Technology and Tampere University of Technology as well as several Finnish distribution network companies worked on a common project concerning the updating of reliability worth values in 2004-2005 [1]. This paper presents the research, analysis and strategic response elimination methods used in this study. There are several methods to calculate and normalize the reliability worth parameters, and the results may differ significantly depending on which method is applied. The principles of the calculating methods are also presented.