Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Robust Time-Varying Safety-Critical Control With Application to Dynamic Walking on Moving Stepping Stones

This paper presents a novel methodology to handle timevarying safety-critical constraints under high level of model uncertainty with application to dynamic bipedal walking with strict foot-placement constraints. This paper builds off recent work on optimal robust control through quadratic programs that can handle stability, input / state dependent constraints, as well as safety-critical constraints, in the presence of high level of model uncertainty. Under the assumption of bounded uncertainty, the proposed controller strictly guarantees time-varying constraints without violating them. We evaluate our proposed control design for achieving dynamic walking of an underactuated bipedal robot subject to (a) torque saturation constraints (input constraints), (b) contact force constraints (state constraints), and (c) precise time-varying footstep placements (time-varying and safetycritical constraints). We present numerical results on RABBIT, a five-link planar bipedal robot, subject to a large unknown load on its torso. Our proposed controller is able to demonstrate walking while strictly enforcing the above constraints with an unknown load of up to 15 Kg (47% of the robot mass.)
Decision Analysis And Behavioral Research

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The Type Ia Supernova Rate at z ~ 0.4

We present the first measurement of the rate of Type Ia supernovae at high redshift. The result is derived by using a large subset of data from the Supernova Cosmology Project. Three supernovae were discovered in a surveyed area of 1.7 deg2. The survey spanned a ~3 week baseline and used images with 3 σ limiting magnitudes of R ~ 23. We present our methods for estimating the numbers of galaxies and the number of solar luminosities to which the survey is sensitive, as well as the supernova detection efficiency, which is used to determine the control time, the effective time for which the survey is sensitive to a Type Ia event. We derive a rest-frame Type Ia supernova (SN) rate at z ~ 0.4 of 0.82−0.37–0.25+0.54 + 0.37 h2 SNu (1 SNu = 1 SN per century per 1010LB☉), where the first uncertainty is statistical and the second includes systematic effects. For the purposes of observers, we also determine the rate of SNe, per sky area surveyed, to be 34.4+23.9−16.2 SNe yr −1 deg −2 for SN magnitudes in the range 21.3 < R < 22.3.
On the Utility of Power Spectral Techniques With Feature Selection Techniques for Effective Mental Task Classification in Noninvasive BCI

In this paper, classification of mental task-root brain–computer interfaces (BCIs) is being investigated. The mental tasks are dominant area of investigations in BCI, which utmost interest as these system can be augmented life of people having severe disabilities. The performance of BCI model primarily depends on the construction of features from brain, electroencephalography (EEG), signal, and the size of feature vector, which are obtained through multiple channels. The availability of training samples to features are minimal for mental task classification. The feature selection is used to increase the ratio for the mental task classification by getting rid of irrelevant and superfluous features. This paper suggests an approach to augment the performance of a learning algorithm for the mental task classification on the utility of power spectral density (PSD) using feature selection. This paper also deals a comparative analysis of multivariate and univariate feature selection for mental task classification. After applying the above stated method, the findings demonstrate substantial improvements in the performance of learning model for mental task classification. Moreover, the efficacy of the proposed approach is endorsed by carrying out a robust ranking algorithm and Friedman’s statistical test for finding the best combinations and compare various combinations of PSD and feature selection methods.
Adaptive sliding mode control for asymptotic stabilization of underactuated mechanical systems via higher-order nonlinear disturbance observer

The development of a nonlinear controller of stabilization of underactuated mechanical systems (UMSs) is a challenging endeavor due to a larger number of output variables to be controlled than the control input space. This paper proposes an adaptive sliding mode control based on a higher-order nonlinear disturbance observer (HONDO) for stabilizing the rotational pendulum (RP) system falling under the class of UMSs. Firstly, the HONDO is designed in such a way that it can improve accuracy in estimations with its incremental order. As a result, the proposed controller obtained from the sliding surface which is developed with system’s states and estimations, forces the states attaining the sliding mode and hence keeps them to their origin forever against disturbances. To achieve this, the sliding coefficients are obtained using inertia matrix of the system. The zero dynamics is stabilized by the proposed controller. This alleviates the chattering problem in the control input. Finally, numerical performance on the underactuated RP model is analyzed to show the efficiency of the proposed controller and it is compared with the established control technique found in the literature.
An Improved Nonlinear Model for Image Inpainting

An important task in image processing is the process of lling in missing parts of damaged images based on the information obtained from the surrounding areas. It is called inpainting. The goals of inpainting are numerous such as removing scratches in old photographic image, removing text and logos, restoration of damaged paintings. In this paper we present a nonlinear diusion model for image inpainting based
Voice Traces of Anxiety: Acoustic Parameters Affected by Anxiety Disorder

Although the emotions and learning based on emotional reaction are individual-specific, the main features are consistent among all people. Depending on the emotional states of the persons, various physical and physiological changes can be observed in pulse and breathing, blood flow velocity, hormonal balance, sound properties, face expression and hand movements. The diversity, size and grade of these changes are shaped by different emotional states. Acoustic analysis, which is an objective evaluation method, is used to determine the emotional state of people’s voice characteristics. In this study, the reflection of anxiety disorder in people’s voices was investigated through acoustic parameters. The study is a case-control study in cross-sectional quality. Voice recordings were obtained from healthy people and patients. With acoustic analysis, 122 acoustic parameters were obtained from these voice recordings. The relation of these parameters to anxious state was investigated statistically. According to the results obtained, 42 acoustic parameters are variable in the anxious state. In the anxious state, the subglottic pressure increases and the vocalization of the vowels decreases. The MFCC parameter, which changes in the anxious state, indicates that people can perceive this situation while listening to the speech. It has also been shown that text reading is also effective in triggering the emotions. These findings show that there is a change in the voice in the anxious state and that the acoustic parameters are influenced by the anxious state. For this reason, acoustic analysis can be used as an expert decision support system for the diagnosis of anxiety.
Dielectric-Loaded Microwave Rectangular Waveguide and Higher Order Mode Resonator

Resonant transmission through a dielectric-loaded slot in a thick conducting diaphragm embedded in a rectangular waveguide is modeled using an analytical approximation based on the slot being small compared to a free-space wavelength. An image theory relates this problem to a metasurface consisting of an array of such slots. We demonstrate the existence of ordinary (Fabry–Perot) transmission resonances associated with the fundamental mode of the slot, as well as extremely narrowband (Fano) resonances involving the higher order modes in the slot. The theoretical predictions are confirmed through full-wave numerical simulation and by experimental measurement. Measurements on dielectrics consisting of multiple pieces reveal an additional set of sharp resonances, not predicted by our theory but verified by finite-element simulation. The results have potential application to sensors and material property measurement.
КОРПОРАТИВНАЯ ОТЧЕТНОСТЬ АГРОХОЛДИНГА В ФОРМАТЕ МСФО:МЕТОДОЛОГИЧЕСКИЕ И МЕТОДИЧЕСКИЕ АСПЕКТЫ

Рассмотрены методологические и методические аспекты формирования консолидированной финансовой отчетности агрохолдинга в соответствии с международными стандартами учета и отчетности. Сделан вывод, что консолидированная финансовая отчетность агрохолдинга, представленная в формате МСФО, содержит натуральные и стоимостные показатели, позволяющие пользователям как эффективно управлять имущественным комплексом, так и иметь сведения о стоимости его гудвилла, финансовом положении и возможности привлечения средств потенциальных инвесторов.
Verification of Structured Processes: A Method Based on an Unsoundness Profile

The verification of business processes has been widely studied in the last two decades achieving significant results. Despite this, existing verification techniques based on state space exploration suffer, for large processes, the state space explosion problem. New techniques improved verification performance by structuring processes as trees. However, they do not support complex constructs for advanced synchronization and exception management. To cope with this issue we propose the definition of an unsoundness profile of a given process language, which specifies all possible combinations of control flow constructs that can lead to errors in the behavior of structured processes defined with such a language. In addition, we introduce the sequential and hierarchical soundness properties, which make use of this profile to determine soundness of a structured process with complex constructs in polynomial time. As an example, we defined an unsoundness profile for a subset of the BPMN language and verified the behavior of a BPMN process model.
Selective functionalization of halogens on zigzag graphene nanoribbons: A route to the separation of zigzag graphene nanoribbons

Using the ab initio pseudopotential density functional method, we investigate the functionalization of halogen molecules into graphene-based nanostructures with zigzag and armchair edges. We find that halogen molecules adsorb through chemisorption on the zigzag edge carbon atoms with a binding energy of ∼1–5 eV, in sharp contrast to physisorption on the armchair edge and elsewhere where they adsorb with a binding energy of ∼0.07 eV. Our findings would be utilized for an approach to the separation of zigzag graphene nanoribbons with regular edges with the change of the solubility of the functionalized nanoribbons.
Comparative analysis of soft computing techniques RBF, MLP, and ANFIS with MLR and MNLR for predicting grade-control scour hole geometry

The main aims and contributions of the present paper are to use new soft computing methods for the simulation of scour geometry (depth/height and locations) in a comparative framework. Five models were used for the prediction of the dimension and location of the scour pit. The five developed models in this study are multilayer perceptron (MLP) neural network, radial basis functions (RBF) neural network, adaptive neuro fuzzy inference systems (ANFIS), multiple linear regression (MLR), and multiple non-linear regression (MNLR) in comparison with empirical equations. Four non-dimensional geometry parameters of scour hole shape are predicted by these models including the maximum scour depth (S), the distance of S from the weir (XS), the maximum height of downstream deposited sediments (hd), and distance of hd from the weir (XD). The best results over train data derived for XS/Z and hd/Z by the MLP model with R2 are 0.95 and 0.96 respectively; the best predictions for S/Z and XD/Z are from the ANFIS model with R2 0.91 and 0.96 respectively. The results indicate that the application of MLP and ANFIS results in the accurate prediction of scour geometry for the designing of stable grade control structures in alluvial irrigation channels.
Efficient Demodulation of Brillouin Phase Spectra and Performance Enhancement in BOTDA Incorporating Phase Noise Elimination

A Brillouin phase spectra (BPS) demodulation approach in Brillouin optical time-domain analysis (BOTDA) based on phase to intensity conversion is proposed and demonstrated. By utilizing the cascaded modulation of the probe light and coherent detection in a symmetric double-sidebands BOTDA, the Brillouin phase shift is transferred into the signal intensity so that it can be recovered with a simple envelope detection. Moreover, the measurement accuracy is significantly improved by the reduction of phase noise caused by the fiber transmission. A 2-m spatial resolution over 39.1-km fiber and 0.7 °C temperature accuracy at the end of the fiber are achieved using the BPS measurement. Compared with the conventional IQ demodulation without phase noise elimination, the precision is improved ∼6.3 dB and the maximum variation of the Brillouin frequency shift (BFS) is reduced from 13 MHz down to 2 MHz. Meanwhile, the comparison experiment with the Brillouin gain spectrum (BGS) detection is also implemented. The proposed method achieves smaller BFS uncertainty in comparison with the conventional BGS detection. At the end of the fiber, uncertainty is reduced from 1 MHz down to 0.7 MHz.
Enhanced Charge Collection in SiC Power MOSFETs Demonstrated by Pulse-Laser Two-Photon Absorption SEE Experiments

A two-photon absorption technique is used to understand the mechanisms of single-event effects (SEEs) in silicon carbide power metal–oxide–field-effect transistors (MOSFETs) and power junction barrier Schottky diodes. The MOSFETs and diodes have similar structures enabling the identification of effects associated specifically with the parasitic bipolar structure that is present in the MOSFETs, but not the diodes. The collected charge in the diodes varies only with laser depth, whereas it varies with depth and lateral position in the MOSFETs. Optical simulations demonstrate that the variations in collected charge observed are from the semiconductor device structure and not from metal/passivation-induced reflection. The difference in the spatial dependence of collected charge between the MOSFET and diode is explained by bipolar amplification of the charge carriers in the MOSFETs. Technology computer-aided design (TCAD) device simulations extend this analysis to heavy-ion-induced charge collection. In addition, there is discussion comparing this analysis with experimental results from prior works that show enhanced charge collection resulting from heavy-ion irradiation.
Analysis of MapReduce Model on Big Data Processing within Cloud Computing

Nowadays cloud computing is becoming a trend on big data processing. Google created MapReduce model to simplify the complex computation of big data processing by configuring and splitting the data into key/values pair to be processed in parallel, usually within a network of computers, then merge the results. However, MapReduce model has its limitations. Researchers have been trying to improve the model resulting in some newer models, such as Mantri, Camdoop, Sudo, and Nectar model. Each model exploits the different characteristics of MapReduce model to create improvements in different way and cases. Challenges and improvements still remain within these enhanced models, which open new possibilities on area of research.
Failure of the stochastic approach to inflation in constant-roll and ultra-slow-roll

After giving a pedagogical review we clarify that the stochastic approach to inflation is generically valid only at zeroth order in the (geometrical) slow-roll parameter $\epsilon_1$ if and only if $\epsilon_1\ll 6/\epsilon_2^2$, with the notable exception of slow-roll. This is due to the failure of the separate universe approach. As a byproduct, by keeping the formalism in its regime of validity, we show that quantum diffusion in ultra-slow-roll might only contribute to the power spectrum at sub-leading orders in slow-roll, and thus, it is irrelevant.
Reason Truth And History

Thank you for reading reason truth and history. As you may know, people have search hundreds times for their favorite novels like this reason truth and history, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they are facing with some infectious virus inside their laptop. reason truth and history is available in our digital library an online access to it is set as public so you can get it instantly. Our digital library hosts in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the reason truth and history is universally compatible with any devices to read.
Full-text Retrieval System Research and Design Base on Compass

Compared with the full-text search toolkit Lucene,Compass is a search engine framework of open source,high-performance,flexible configuration.After analyzing the technical of Compass,proposes FTP full-text retrieval system structure based on Compass,discusses the key technologies for system implementation.Compass is achieved by JAVA,so,has it and combines with the 1 ightweight J2EE framework,in order to enhance system decoupling,improve the scalability of the application and reduce the cost of system reconfiguration,and also has to be transplanted.
Automatic Generation of Ontology Based on Database

Ontology resources are more and more important for organizing knowledge. It has become an important task to improve the efficiency of ontology construction for ontology applications. How to generate ontology automatically from database resources is an emerging task in ontology construction. Aiming at solving the problem, a method for automatic ontology building using the relational database resources to improve the efficiency is proposed in the paper. Firstly, mapping analysis of ontology and database is done. Secondly, construction rules of ontology elements based on relational database, which are used to generate ontology concepts, properties, axioms, instances are put forward. Thirdly，Ontology automatic Generation System based on Relational Database (OGSRD) is designed and implemented. Finally, the practical experiments prove the method and system feasibility.
Issues in high performance multimedia

Multimedia applications are becoming more and more popular as the reach of technology extends. The characteristics of multimedia applications vary widely, but they tend to involve huge amounts of data and computation. It is necessary to build hardware that efficiently meets the needs of these new and demanding applications. This work considers two approaches to multimedia application acceleration, specialized hardware vs. optimized general hardware. In addition, some issues pertaining to high performance computing are examined such as optimizations for low-power as well as the design of individual units. Chapter 1 discusses techniques to improve the performance of Physical Modeling, which is one particular multimedia application. This application is an interesting example since Physical Modeling is generally too computationally intensive for interactive simulation in general purpose machines. Chapter 2 further develops the idea of specialized architecture for multimedia. In this chapter, a specialized reconfigurable machine is adapted to accelerate a number of graphic applications. Highly specialized architecture is not the only approach to high performance multimedia. Chapter 3 discusses a new general purpose architecture that is tuned to exploit the superior instruction level parallelism available in multimedia applications. In order to accelerate multimedia applications, it is also necessary to understand the execution characteristics of those programs. In Chapter 4, a simulation of the MediaBench multimedia benchmark set was conducted. This chapter shows that a number of significant differences exist between multimedia and SPEC applications. Chapters 5 and 6 address problems at the component level of the multimedia processor. Chapter 5, deals with the efficient design of a register renaming unit, which is an important component of the superscalar processor. Chapter 6 discusses the reduction of on-chip power consumption through the application of bus coding and charge recovery techniques. Each of these chapters contributes to the design of an efficient processor for multimedia applications.
Machine Classification of Transient Images

Abstract Using transient imaging data from the 2nd and 3rd years of the SDSS supernova survey, we apply various machine learning techniques to the problem of classifying transients (e.g. SNe) from artefacts, one of the first steps in any transient detection pipeline, and one that is often still carried out by human scanners. Using features mostly obtained from PCA, we show that we can match human levels of classification success, and find that a K-nearest neighbours algorithm and SkyNet perform best, while the Naive Bayes, SVM and minimum error classifier have performances varying from slightly to significantly worse.
NaNbO3–KNbO3: Can spinodal decomposition generate relaxor ferroelectricity?

First principles based phase diagram calculations were performed for the system (1−X) NaNbO3–(X) KNbO3. Plane wave pseudopotential calculations of formation energies were used as a basis for fitting a cluster expansion Hamiltonian, and a phase diagram was calculated. The predicted phase diagram has an unusual asymmetric miscibility gap, which suggests that it might be possible to synthesize a lead-free compositionally modulated sample with bulk composition X≈0.23; such a sample is likely to exhibit relaxor characteristics.
Review of Link Structure Based Ranking Algorithms and Hanging Pages

In this era of Web computing, Cyber Security is very important as more and more data is moving into the Web. Some data are confidential and important. There are many threats for the data in the Web. Some of the basic threats can be addressed by designing the Web sites properly using Search Engine Optimization techniques. One such threat is the hanging page which gives room for link spamming. This chapter addresses the issues caused by hanging pages in Web computing. This Chapter has four important objectives. They are 1) Compare and review the different types of link structure based ranking algorithms in ranking Web pages. PageRank is used as the base algorithm throughout this Chapter. 2) Study on hanging pages, explore the effects of hanging pages in Web security and compare the existing methods to handle hanging pages. 3) Study on Link spam and explore the effect of hanging pages in link spam contribution and 4) Study on Search Engine Optimization (SEO) / Web Site Optimization (WSO) and explore the effect of hanging pages in Search Engine Optimization (SEO).