Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust nonlinear state estimation for a class of infinite-dimensional systems using reduced-order models

A methodology for designing robust, low-order observers for a class of spectral infinite-dimensional nonlinear systems is presented. This approach uses the low-dimensional subspace explicitly in the observer design. Then, robustness to bounded model uncertainties is incorporated using the Lyapunov reconstruction method from robust control theory. Furthermore, the proposed design includes a data-driven learning algorithm that auto-tunes the observer gains to optimise the performance of the state estimation. A numerical study using a model from fluid dynamics -Burgers equation- demonstrates the effectiveness of the proposed observer.
Initial post‐buckling of the micro‐scaled beams based on the strain gradient elasticity

An analysis of initial post‐buckling of a micro‐scaled beam with hinged‐hinged ends based on the strain gradient elasticity is presented. At the first bifurcation point, the second variation of the potential energy is analytically proved to be positive semidefinite when the compression equals to the critical load. The fourth variation of the potential energy is positive when the disturbance of the lateral deflection matches the buckling mode. Based on Koiter initial post‐buckling stability theory, the neutral equilibrium of straight state of the micro‐scaled beam is stable at the stability limit. The bending shape in the initial post‐buckling is stable when the compressive force exceeds slightly the critical load. Although the critical load of the micro‐scale beam with hinged‐hinged ends is influenced by size effects, the initial post‐buckling behavior of it is similar to that of the classical beam.
Detecting Slow DDos Attacks on Mobile Devices

Denial of service attacks, distributed denial of service attacks and reflector attacks are well known and documented events. More recently these attacks have been directed at game stations and mobile communication devices as strategies for disrupting communication. In this paper we ask, How can slow DDos attacks be detected? The similarity metric is adopted and applied for potential application. A short review of previous literature on attacks and prevention methodologies is provided and strategies are discussed. An innovative attack detection method is introduced and the processes and procedures are summarized into an investigation process model. The advantages and benefits of applying the metric are demonstrated and the importance of trace back preparation discussed.
Singlet and Triplet Exciton Dissociation

The boundary between molecular behavior and supramolecular behavior is not welldefined. A detailed understanding of molecular structure is necessary to understand and design new solid-state materials, but it is not sufficient. Solid-state materials display emergent properties not easily described by their individual molecular components. This work seeks to understand which solid-state properties directly follow from single-molecule predictions, and which properties arise from intermolecular interactions. Both types of properties can be leveraged for optoelectronic applications once the distinction between the two is made. In the first part of this work, we explore the role of intermolecular coupling in both charge and exciton dynamics. We address a long-standing photophysical mystery: the mechanism of free charge generation in low-dielectric solid-state environments. Charge transfer in such environments should result in a tightly bound exciton from a coulombic standpoint. Instead, the result is often a large population of separated electron-hole pairs. Though many parameters modulate the dynamics of free charge carriers, this work identifies intermolecular coupling as the crucial parameter required for their creation. We extend this idea to exciton dynamics in singlet fission (SF), which has the potential to produce two electron-hole pairs per photon instead of one. However, instead of using intermolecular coupling to induce free charge generation, we use this feature to induce triplet exciton separation. Since SF triplets are born in pairs, this separation may prove crucial to ensuring eventual independent triplet dissociation.
AN IMPROVED GENETIC ALGORITHM FOR TEST DATA GENERATION FOR SIMULINK MODELS

Mutation testing is a powerful and effective software testing technique to assess the quality of test suites. Although many research works have been done in the field of search-based testing, automatic test data generation based on the mutation analysis method is not straightforward. In this paper, an Improved Genetic Algorithm (IGA) is proposed to increase the quality of test data based on mutation coverage criterion. This algorithm involves some modifications of genetic operators and the employment of memory mechanism to enhance its effectiveness. The proposed approach is implemented to generate test data for Simulink models. The obtained results indicated that IGA outperformed the conventional genetic algorithm in terms of the quality of test sets, and the execution time.
Convergence of the Newton Structure Transfer Function to the Ideal Fractional Delay Filter

This letter presents a rigorous demonstration of the convergence of the Newton fractional delay filter to the ideal fractional delay filter. The Newton structure is a very efficient implementation of Lagrange interpolation using a variable fractional delay filter structure. Through the developed demonstration, a new approach is proposed to define the ideal fractional delay filter as the limit of any digital filter implementing on Lagrange interpolation. This letter also proves that the Z-transform expression of the ideal fractional delay has a fully defined frequency response on the unit circle.
A Multi-Level Semantic Scene Interpretation Strategy for Change Interpretation in Remote Sensing Imagery

Remotely sensed images represent an important source of information for monitoring land changes that may occur. There is, therefore, a need to analyze and interpret such information in order to extract useful semantic change interpretations. However, extracting such semantics from satellite images is a complex task that requires prior and contextual knowledge. In this paper, we focus on the issue of semantic scene interpretation for change interpretation. Consequently, a strategy for semantic remote-sensing imagery scene interpretation is proposed. This strategy is based on a representative framework that is structured around several levels of interpretation: the pixel level, the visual primitive level, the object level, the scene level, and the change interpretation level. Each level integrates a logical mechanism to extract useful knowledge for interpretation. The proposed model has been evaluated using two Landsat scene images acquired in 2000 [Landsat Enhanced Thematic Mapper plus (ETM+)] and 2017 (Landsat 8) in order to check its relevance for semantic scene and change interpretation. Precision, recall, and F-measure metrics were used in order to show the capacity of the proposed methodology for semantic classification. A visual evaluation was also performed to evaluate the performance of the presented interpretation strategy, and the query results for each level show a promising capability for semantic object classification, spatial and temporal relations’ extraction, and change interpretation.
Observation of topological Hall effect in antiferromagnetic FeRh film

Noncollinear magnetic structures can give rise to peculiar Hall effects and hold promise for next-generation spintronic devices. We report the observation of the topological Hall effect (THE) through electrical transport measurements in antiferromagnetic B2-ordered FeRh thin films grown by sputtering techniques on a MgO (001) substrate. Combining with the spin glass behavior below the metamagnetic transition temperature from ferromagnetism to antiferromagnetism, we ascribe THE to the emergence of noncollinear spin texture arising from the competitions among various exchange interactions in the antiferromagnetic state. This observation opens the possibility to discover the topological Hall effect in centrosymmetric antiferromagnets in contrast to the widely reported B20-type chiral magnets, promoting the application of antiferromagnets in spintronic devices.Noncollinear magnetic structures can give rise to peculiar Hall effects and hold promise for next-generation spintronic devices. We report the observation of the topological Hall effect (THE) through electrical transport measurements in antiferromagnetic B2-ordered FeRh thin films grown by sputtering techniques on a MgO (001) substrate. Combining with the spin glass behavior below the metamagnetic transition temperature from ferromagnetism to antiferromagnetism, we ascribe THE to the emergence of noncollinear spin texture arising from the competitions among various exchange interactions in the antiferromagnetic state. This observation opens the possibility to discover the topological Hall effect in centrosymmetric antiferromagnets in contrast to the widely reported B20-type chiral magnets, promoting the application of antiferromagnets in spintronic devices.
Optimierung eines neuronalen Netzes zur Objekterkennung unter Verwendung evolutionärer Algorithmen

In recent years, neural networks have been widely used as the method of choice for classification tasks in computer vision and image processing. The networks that currently provide the best results are very deep residual Convolutional Neural Networks. New network structures, based on the previously used topologies are developed each year, using different approaches. In this thesis the application of a canonical genetic algorithm to optimize the topology of neural networks is investigated. Current state of the art networks are used as a baseline to start the optimization form. The generated architectures achieve an improved classification accuracy, compared to reference networks. The developed network structures differ from commonly used architectures in their higher level architecture. In contrast to the reference networks they are not homogeneously from a sequence of different blocks. The improved classification accuracy suggests that the use of heterogeneous structures may be advantageous. Furthermore it is shown that the generated neural networks converge in fewer iterations, producing better results.
Ontology Driven Reputation Model for VANET

As Vehicle Ad Hoc Networks (VANETs) become a key component of Intelligent Transportation System (ITS), trust is important in applications that besides traditional security requirements need to evaluate the behavior of different entities in VANETs. Highly dynamic environments of vehicles need an adapted form of trust establishment. There are efforts for evaluating trust in VANETs, based on reputation mechanisms. In this paper, we propose a definition of the reputation relying on the use of an ontology of VANETs, ensuring both an optimal coverage of the domain and a deep semantic rooting. This definition is based on the identification of the key aspects requiring the support of the ontology for their evaluation. Keywordstrust; ontology; VANETs; reputation model
ResearchGate and Academia.edu as networked socio-technical systems for scholarly communication: a literature review

ResearchGate and Academia.edu have been increasingly acknowledged as the most popular academic social network sites (ASNS) for scholarly communication. Along with their benefits for supporting communication and knowledge sharing within academic communities, concerns over quality and credibility remain a pertinent issue. In terms of research investigation, ASNS have attracted strong attention for new scholarly practice and their potential for building, maintaining and enhancing reputation. However, a thorough understanding is still lacking of how these sites operate as networked socio-technical systems reshaping scholarly practices and academic identity. This article analyses 39 empirical studies published in peer-reviewed journals with a specific focus on ResearchGate and Academia.edu. The aim is to describe the status of the research and to identify gaps and priorities in the areas of scholarly networked learning and shared knowledge. Results show that the number of studies focusing on ResearchGate was more than double those dedicated to Academia.edu. While both sites have attracted attention in the library and information sciences as deployments for reputation building and alternative ranking systems, such as ResearchGate metrics, there is a dearth of research investigating practices and new modes of communication in the light of a networked participatory approach to scholarship. Most of the studies analysed focused on the general uptake or impact assessment of alternative metrics, while very few investigated individual and collective scholarly practices. This study points to the need for specific research on open and distributed learning achieved in ASNS according to a networked learning perspective. Published : 20 February 2018 Citation : Research in Learning Technology 2018, 26 : 2008 - https://dx.doi. org/10.25304/rlt.v26. 2008
Cognitive Modeling Repository

Cognitive Modeling Repository Jay Myung Ohio State University Mark Pitt Ohio State University Abstract: Quantitative modeling has contributed substantially to the advancement of the cognitive sciences. Papers introducing and testing cognitive models regularly appear in the top journals. The growth and success of cognitive modeling demonstrate why modeling itself should be a primary quantitative method in the researcher’s toolbox. Yet this method of scientific investigation remains under-utilized by the research community at large, in part because of the hassles in obtaining data sets to model and the difficulties in implementing models. The goal of this project is to assist scientists in their cognitive modeling efforts by creating an online repository containing data sets that can be modeled and the cognitive models themselves. The current state of the project and future plans will be presented. Funded by the Mathematical Modeling of Cognition and Decision of the Air Force Office of Scientific Research.
An Adaptive Large Neighbourhood Search for the Pickup and Delivery Problem with Time Windows

In this research the Adaptive Large Neighbourhood Search (ALNS) of Ropke & Pisinger (2006a) is used to solve the Pickup and Delivery Problem with Time Windows (PDPTW), replicating the research of Ropke and Pisinger. ALNS uses a set of removal and insertion procedures to iteratively construct new solutions by deleting part of a high-quality old solution and rebuilding it. It is examined whether the ALNS implementation of this research can obtain similar results for problem instances of the pickup and delivery problem with time-windows constructed by Li & Lim (2003) and Ropke & Pisinger (2006a) and how the method might be improved. It was found that although the algorithm seemed to perform somewhat poorer than in the research of Ropke and Pisinger. A variant of the problem with timedependent travel times is introduced, to examine whether this problem can also be solved efficiently by ALNS. Our finding is that time-dependent pickup and delivery problems with time windows can be solved successfully by ALNS, although the running times might increase substantially if the travel time distribution is complicated. Moreover, it was found that increases in the number of iterations might substantially increase the quality of the solutions found. A potential way to increase the performance of ALNS further, is using more sophisticated insertion procedures.
Robust control of grid connected doubly fed induction generator DFIG based power systems

Sizeable portion of world’s electric power generation is being contributed by nonrenewable energy resources such as coal, gas, oil etc. The use of these fossil fuels results in increased emission of CO2 and other harmful gases in the atmosphere while the residues as a result of these fuels are mainly released into water. This results in several health related issues to human and other living bodies on earth as well as raises global warming issues. It is projected that world electricity demand is expected to grow more than 2% annually. The ever increasing demand for electric power in the face of global warming and health related issues in use of fossil fuel based power generation, demand for a paradigm shift towards the use of natural renewable resources based electricity generation e.g. using wind, solar, hydro, geothermal and bio-gas etc. The renewable energy based generation admits distributed or hybrid
Precise Extraction of Dynamic Rdson Under High Frequency and High Voltage by a Double-Diode-Isolation Method

A double-diode-isolation method with low parasitic capacitance devices and reverse clamping is proposed to accurately extract the high-frequency and high-voltage dynamic on-resistance (<inline-formula> <tex-math notation="LaTeX">$R_{\mathrm{ dson}}$ </tex-math></inline-formula>) of AlGaN/GaN high electron mobility transistor (HEMT) power devices. The response time required for the drain voltage to drop back to the on-voltage of this testing circuit can reach 100 ns, and the forward voltage drop of the isolation diode is monitored in real time using low-voltage probes. A low value constant current source is built to power the testing circuit at only several mA to avoid additional self-heating effect. With these improvements, we can obtain a test frequency of more than 1 MHz, a test voltage of more than 600 V and an accuracy of higher than 97.8% for the extraction of dynamic <inline-formula> <tex-math notation="LaTeX">$\text{R}_{\mathrm{ dson}}$ </tex-math></inline-formula>.
Spell-Out and the Minimalist Program

© 2013 by the English Linguistic Society of Japan * I would like to thank Akihiko Arano, Hiroaki Emoto, Yoshihisa Goto, Shin-ichi Kitada, Cornelia Daniela Lupsa, Nobuhiro Miyoshi, Tadao Nomura, Takahiro Tozawa, Juan Uriagereka, and Kazuhiko Yamaguchi for their valuable comments and suggestions. I would also like to thank two anonymous EL reviewers for their helpful comments. This study is supported by a Grant-in-Aid for Scientific Research (C) (No. 23520574). All remaining errors are my own.
Speech recognition method and speech recognitnion apparatus

In an interactive process using speech recognition together with a graphical user interface including a plurality of settable graphical user interface items, the recognition rate is improved by reducing recognition target vocabulary. And is detected settable graphical user interface item not displayed on a display screen, audio information is received and recognized by the speech recognition grammar corresponding to the detected item, and data is set to the item using the recognition result. Speech recognition, recognition grammar, the recognition vocabulary, the graphic user interface, Push To Talk key
Analisis Pengaruh Moment Gyroscope Pada Keseimbangan Pendulum Cartessian

Crane is identical to the pendulum in term of its control mechanism. Based on modelling, these two devices are very similar and therefore, the pendulum can be used as a prototype for controlling a crane. This research aims to control the balance or to reduce the swing on the pendulum by utilizing the moment of gyroscope with a mass pendulum up to 1.5 kg. Gyroscope was designed and made in the form of a disc, in which dimensions and materials used were determined according to the desired moment force. The PID controller was used to control the speed of gyroscope based on the angle of the pendulum (θ). Based on the results of the experiment, it was obtained that the resulting settling time was 2.29 times faster than without control in average. The overshoot and rise time resulted by the system using gyroscope were very similar to the system which is without gyroscope. However, the steady state error was totally eliminated. It can be concluded that the moment of gyroscope is able to be used for controlling the pendulum or crane.
Measurements of Sea Surface Currents in the Baltic Sea Region Using Spaceborne Along-Track InSAR

The main challenging problems in ocean current retrieval from along-track interferometric (ATI)-synthetic aperture radar (SAR) are phase calibration and wave bias removal. In this paper, a method based on differential InSAR (DInSAR) technique for correcting the phase offset and its variation is proposed. The wave bias removal is assessed using two different Doppler models and two different wind sources. In addition to the wind provided by an atmospheric model, the wind speed used for wave correction in this work is extracted from the calibrated SAR backscatter. This demonstrates that current retrieval from ATI-SAR can be completed independently of atmospheric models. The retrieved currents, from four TanDEM-X (TDX) acquisitions over the Öresund channel in the Baltic Sea, are compared to a regional ocean circulation model. It is shown that by applying the proposed phase correction and wave bias removal, a good agreement in spatial variation and current direction is achieved. The residual bias, between the ocean model and the current retrievals, varies between 0.013 and 0.3 m/s depending on the Doppler model and wind source used for wave correction. This paper shows that using SAR as a source of wind speed reduces the bias and root-mean-squared-error (RMSE) of the retrieved currents by 20% and 15%, respectively. Finally, the sensitivity of the sea current retrieval to Doppler model and wind errors are discussed.
BRAIN-COMPATIBLE TEACHING AND PSYCHO-DIDACTIC ASPECTS OF EDUCATION AS DETERMINANTS SUPPORTING THE DEVELOPMENT OF CRITICAL THINKING IN STUDENTS

In the educational process, the teacher should respect the brain-compatible and psychodidactic aspects: how to select and organize the subject, respect the learning styles and teaching styles, develop the metacognitive processes of the students, and support the development of critical thinking. In the present paper, the authors focus on students' work with text, which is strongly determined by several attributes described in the paper. The authors carried out research about the perception of text and text structure at students of the Slovak pedagogical college.
Complementarity Model of a Photovoltaic Power Electronic System With Model Predictive Control

The modeling and control problem for a grid-connected photovoltaic (PV) power electronic system, which includes a dc/dc boost converter, an inverter and a filter are considered. A linear complementarity (LC) dynamic model of the PV system allows the design of a model predictive controller (MPC). Dynamic models of the subsystems are obtained and merged in order to represent the whole PV system in a compact and comprehensive LC model, which is valid for all operating modes of power converters and PV cells involved in the energy conversion process. A finite-control-set MPC problem is formulated as a mixed-integer quadratic program subject to the dynamic LC model and pulse width modulators. The minimization of an objective function aimed at tracking dc voltage and grid current references provides directly the commands for the switches of the boost converter and inverter. Numerical results show the effectiveness of the proposed strategy for maximum power point tracking and synchronization to the grid under dynamic scenarios characterized by variations of the solar irradiance.
Managerial and Cultural Pre-Conditions for Superior Performance in a Global Setting: An Experimental Study with the Aid of Business Games

In this paper, we analyze the various strategic approaches actually adopted by the Brazilian managers of 23 firms simulated n a set of business games. For the purposes of this paper, their approaches are classified as local or global. Based on a review of literature and an experiment conducted by the authors. It was concluded that the ability to translate a global view into operating policies is paramount, and that the immediate presence of a global stance, as reflected in the plans submitted by the teams, as well as in the ability to manage conflicts and diversity, are important determinants of performance.