Miracle-dz/UniFAR-FTUs huggingface dataset:
PID and PDFF Compensators for Motion Control

Traditionally in servo systems, the PI(D) controller has been widely used, while other types such as the PDF controller has been applied in some applications. In this article, the PDFF controller which has feedforward term in addition to a conventional PDF(Pseudo-Derivative Feedback) controller is introduced. Tracking and regulation characteristics of the PDFF controller in motion control applications are analyzed in terms of classical frequency domain approach. The PDFF controller is shown to be a generalized PI(D) controller, and relative performance of the well-known cascade PI(D) controller and the PDF controller are dealt with as two special cases. A tuning method of this controller to meet desired performance criteria such as dynamic reference tracking, steady-state error and load torque disturbance rejection capability is discussed along with experimental results.
Delay-dependent robust H∞ control for uncertain T-S fuzzy systems with time-varying delay

The delay-dependent robust H infin control problem for a class of nonlinear time-delay system is investigated in this paper. An uncertain Takagi-Sugeno (T-S) fuzzy model is adopted for representing a nonlinear system with time-varying delay, in which the modeling errors are absorbed in the uncertain part. The design method of delay-dependent robust H infin controller is firstly established via the parallel distributed compensation (PDC) technique. Meanwhile, a stabilization method is developed in terms of linear matrix inequalities (LMIs). Two examples are provided to prove the effectiveness of the present results.
A Dependable Coarse-Grain Reconfigurable Multicore Array

Recent trends in semiconductor technology have dictated the constant reduction of device size. One negative effect stemming from the reduction in size and increased complexity is the reduced device reliability. This paper is centered around the matter of permanent fault tolerance and graceful system degradation in the presence of permanent faults. We take advantage of the natural redundancy of homogeneous multicores following a sparing strategy to reuse functional pipeline stages of faulty cores. This is done by incorporating reconfigurable interconnects next to which the cores of the system are placed, providing the flexibility to redirect the data-flow from the faulty pipeline stages of damaged cores to spare (still) functional ones. Several micro-architectural changes are introduced to decouple the processor stages and allow them to be interchangeable. The proposed approach is a clear departure from previous ones by offering full flexibility as well as highly graceful performance degradation at reasonable costs. More specifically, our coarsegrain fault tolerant multicore array provides up to ×4 better availability compared to a conventional multicore and up to ×2 higher probability to deliver at least one functioning core in high fault densities. For our benchmarks, our design (synthesized for STM 65nm SP technology) incurs a total execution-time overhead for the complete system ranging from ×1.37 to ×3.3 compared to a (baseline) non-fault-tolerant system, depending on the permanent-fault density. The area overhead is 19.5% and the energy consumption, without incorporating any power/energy- saving technique, is estimated on average to be 20.9% higher compared to the baseline, unprotected design.
Authorship Verification, Average Similarity Analysis

Authorship analysis is an important task for different text applications, for example in the field of digital forensic text analysis. Hence, we propose an authorship analysis method that compares the average similarity of a text of unknown authorship with all the text of an author. Using this idea, a text that was not written by an author, would not exceed the average of similarity with known texts and only the text of unknown authorship would be considered as written by the author, if it exceeds the average of similarity obtained between texts written by him. The experiments were realized using the data provided in PAN 2014 competition for Spanish articles for the task of authorship verification. We realize experiments using different similarity functions and 17 linguistics features. We analyze the results obtained with each pair function-features against the baseline of the competition. Additionally, we introduce a text filtering phase that delete all the sample text of an author that are more similar to the samples of other author, with the idea to reduce confusion or non-representative text, and finally we analyze new experiments to compare the results with the data obtained without filtering.
MEANTIME: Achieving Both Minimal Energy and Timeliness with Approximate Computing

Energy efficiency and timeliness (i.e., predictable job latency) are two essential - yet opposing - concerns for embedded systems. Hard timing guarantees require conservative resource allocation while energy minimization requires aggressively releasing resources and occasionally violating timing constraints. Recent work on approximate computing, however, opens up a new dimension of optimization: application accuracy. In this paper, we use approximate computing to achieve both hard timing guarantees and energy efficiency. Specifically, we propose MEANTIME: a runtime system that delivers hard latency guarantees and energy-minimal resource usage through small accuracy reductions. We test MEANTIME on a real Linux/ARM system with six applications. Overall, we find that MEANTIME never violates real-time deadlines and sacrifices a small amount (typically less than 2%) of accuracy while reducing energy to 54% of a conservative, full accuracy approach.
Author ' s personal copy Ultra-strength materials

Recent experiments on nanostructured materials, such as nanoparticles, nanowires, nanotubes, nanopillars, thin films, and nanocrystals have revealed a host of ‘‘ultra-strength” phenomena, defined by stresses in a material component generally rising up to a significant fraction > 1 10 of its ideal strength – the highest achievable stress of a defect-free crystal at zero temperature. While conventional materials deform or fracture at sample-wide stresses far below the ideal strength, rapid development of nanotechnology has brought about a need to understand ultra-strength phenomena, as nanoscale materials apparently have a larger dynamic range of sustainable stress (‘‘strength”) than conventional materials. Ultra-strength phenomena not only have to do with the shape stability and deformation kinetics of a component, but also the tuning of its physical and chemical properties by stress. Reaching ultrastrength enables ‘‘elastic strain engineering”, where by controlling the elastic strain field one achieves desired electronic, magnetic, optical, phononic, catalytic, etc. properties in the component, imparting a new meaning to Feynman’s statement ‘‘there’s plenty of room at the bottom”. This article presents an overview of the principal deformation mechanisms of ultra-strength materials. The fundamental defect processes that initiate and sustain plastic flow and fracture are described, and the mechanics and physics of both displacive and diffusive mechanisms are reviewed. The effects of temperature, strain rate and sample size are discussed. Important unresolved issues are identified. 2010 Elsevier Ltd. All rights reserved. 0079-6425/$ see front matter 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.pmatsci. 2010.04. 001 * Corresponding authors. E-mail addresses: ting.zhu@me.gatech. edu (T. Zhu), liju@seas.upenn. edu (J. Li). Progress in Materials Science 55 (2010) 710–757
The evolution with time of the spatial distribution of the largest Lyapunov exponent on the human epileptic cortex

The topic of this presentation is the investigation of the epileptic human brain as a nonlinear system that undergoes a phase transition (epileptic seizure). The estimated values of the largest Lyapunov exponent L over time indicated a more chaotic state postictally than ictally or preictally. The start of a seizure corresponds to a simultaneous drop in the values of L at the focal electrode sites. The observed slow cyclic variations in the temporal Lyapunov profiles imply attempts of the system to undergo a phase transition minutes before the seizure’s onset. The analysis of the maximum rate of entropy production over space revealed an initial phase difference of minutes preictally at the sites overlying the seizure focus, which progressed to phase locking with a slow entrainment of the rest of the cortical sites shortly before the onset of a seizure. It is also conjectured that the abnormal spiking electrical activity of the brain plays a major role in the unfolding of the phenomenon. The above results suggest that localization and prediction of an impending seizure may be possible up to 10 minutes before the actual event. A model for the generation of a focal epileptic seizure is proposed based on these findings.
Automated Robust Design and Optimization of Integrated Circuits by Means of Penalty Functions

Abstract The ever-shorter time-to-market calls for efficient robust IC design algorithms. Robust circuits satisfy all design requirements across a range of operating conditions and manufacturing process variations. In the paper we propose an automated robust IC design and optimization process derived from the design algorithms utilized manually by experienced analog IC designers. We achieve this by transforming the robust design and optimization problem into a constrained optimization problem using tradeoff planes and penalty functions. We illustrate the method on a robust differential amplifier design problem. Circuits resulting from several different optimization runs show that a computer can not only improve existing circuit designs but it can also size a circuit with very little initial knowledge. The resulting circuits have comparable or even superior performance to humanly designed circuits. The method could easily take advantage of parallel processing but is still efficient enough to be run on a single computer.
Characterize System Dynamic of Pseudo Periodic Time Series with Evolution Networks

The appearing sequence of data points in time series is denoted as data evolution. Modeling data evolution is important to discover complex system dynamic. Inspired by the complex networks, in this paper, we try to map data evolution to a process of network evolution. To transform pseudo periodic time series to complex network, each cycle is regarded as a node of the network. Two different definitions of edges are discussed. One is the neighborhood of the cycles in time series, and the other is the similarity. Based on the evolution network models, data evolution model is defined and composed three steps: start, growth, preference. With a given transforming rule, the network evolution is only constrained by system dynamic. So data evolution model can help us discover hidden dynamic and understand complex system. An appropriate example about heart rate variation is analyzed to illustrate the effect of the model.
Antonyms as lexical constructions: or, why paradigmatic construction is not an oxymoron

This paper argues that antonymy is a syntagmatic as well as a paradigmatic relation, and that antonym pairs constitute a particular type of construction. This position relies on three observations about antonymy in discourse: (1) antonyms tend to co-occur in sentences, (2) they tend to co-occur in particular contrastive constructions, and (3) unlike other paradigmatic relations, antonymy is lexical as well as semantic in nature. CxG offers a means to treat both the contrastive constructions and conventionalised antonym pairings as linguistic constructions, thus providing an account of how semantically paradigmatic relations come to be syntagmatically realised as well. After reviewing the relevant characteristics of CxG, it looks at some of the phrasal contexts in which antonyms tend to co-occur and argues that at least some of these constitute constructions with contrastive import. It then sketches a new type of discontinuous lexical construction that treats antonym pairs as lexical items, and raises issues for further discussion.
Modelling the development of the retinogeniculate pathway

Acknowledgements Thanks to all who have helped me to get this far. First, I would like to thank both of my supervisors, Harry Barrow and David Young, for their support throughout the thesis. Inspiration for this work has also come from I would particularly like to thank Julian for his constant support in all manner of ways, without which I would have faced a much more difficult task. Both my examiners, Peter Földiák and Hilary Buxton, also provided very useful feedback on the thesis. Many fellow students have helped me on my way. First, thanks to Jo Brook for all her help with L A T E X and postscript. and Rosemary Tate have all made the many hours in the lab so much more enjoyable. should all be thanked for pushing me in the early days. Most of all, thanks to Valéria Judice and my family. Summary How does the visual system develop before the onset of visually-driven activity? By the time photoreceptors can respond to visual stimulation, some pathways, including the retinogeniculate pathway, have already reached a near-adult form. This rules out visually-driven activity guiding pathway development. During this period however, spontaneous waves of activity travel across the retina, correlating the activity of neighbouring retinal cells. Activity-dependent mechanisms can exploit these correlations to guide retinogeniculate refinement. In this thesis I investigate, by means of computer simulation, the role of spontaneous retinal activity upon the development of ocular dominance and topography in the retinogeniculate pathway. Keesing, Stork, and Shatz (1992) produced an initial model of retinogeniculate development driven by retinal waves. In this thesis, in addition to replicating their initial results, several new results are presented. First, the importance of presynaptic normalisation is highlighted. This is in contrast to most previous work on ocular dominance requiring postsynaptic normalisation. Second , the covariance rule is adapted so that development can occur under conditions of sparse input activity. Third, the model is shown to replicate development under conditions of monocular deprivation. Fourth, model development is analysed using different spatio-temporal inputs including anticorrelations between on-and off-centre retinal units. The layered pattern of ocular dominance in the LGN is quite different to the stripe patterns found in the cortex. The factors controlling the patterns of ocular dominance are investigated using a feature-based model of map formation (Obermayer, Ritter, & Schulten, 1991). In common with other models, variance of the ocularity feature controls the …
Reducing Maladaptive Behaviors in Preschool-Aged Children with Autism Spectrum Disorder Using the Early Start Denver Model

The presence of maladaptive behaviors in young people with autism spectrum disorder (ASD) can significantly limit engagement in treatment programs, as well as compromise future educational and vocational opportunities. This study aimed to explore whether the Early Start Denver Model (ESDM) treatment approach reduced maladaptive behaviors in preschool-aged children with ASD in a community-based long day care setting. The level of maladaptive behavior of 38 children with ASD was rated using an observation-based measure on three occasions during the intervention: on entry, 12 weeks post-entry, and on exit (post-intervention) over an average treatment duration of 11.8 months. Significant reductions were found in children’s maladaptive behaviors over the course of the intervention, with 68% of children showing a treatment response by 12 weeks and 79% on exit. This change was accompanied by improvement in children’s overall developmental level as assessed by the Mullen scales of early learning, but not by significant changes on the Vineland Adaptive Behavior Scales-II or Social Communication Questionnaire. Replication with a larger sample, control conditions, and additional measures of maladaptive behavior is necessary in order to determine the specific factors underlying these improvements; however, the findings of the present study suggest that the ESDM program may be effective in improving not only core developmental domains, but also decreasing maladaptive behaviors in preschool-aged children with ASD.
Improving business rating predictions using graph based features

Many types of recommender systems rely on a rich ensemble of user, item, and context features when generating recommendations for users. The features can be either manually engineered or automatically extracted from the available data, such that feature engineering becomes an important step in the recommendation process. In this work, we propose to leverage graph based representation of the data in order to generate and automatically populate features. We represent the standard user-item rating matrix and some domain metadata, as graph vertices and edges. Then, we apply a suite of graph theory and network analysis metrics to the graph based data representation, to populate features that augment the original user-item ratings data. The augmented data is fed into a classifier that predicts unknown user ratings, which are used for the generation of recommendations. We evaluate the proposed methodology using the recently released Yelp business ratings dataset. Our results indicate that the automatically populated graph features allow for more accurate and robust predictions, with respect to both the variability and sparsity of ratings.
Price and Quantity Measurements: Theoretical Biases in Empirical Procedures

The presence of qualitative changes in the nature of many commodities hinders our ability to construct meaningful price and quantity indices. This paper assesses some of the quality-change literature that seeks to resolve this problem. Several writers have endeavoured to develop objective, theory-neutral procedures designed to measure qualitative changes in some timeless, quantitative units. These measures, they argued, could be used to properly adjust ordinary price and quantity statistics for distortions introduced by quality changes. A careful examination suggests, however, that such procedures are neither objective nor free of theoretical biases. First, all existing attempts to develop ‘objective’ commodity measures in the presence of quality changes are besieged by a constant resort – explicit or implicit – to ‘subjective’ considerations. Second, both the idea that quality can be measured and the methods developed for that purpose are closely tied with the neoclassical theoretical paradigm, particularly with its emphasis on perfect competition and equilibrium.
Design , Optimization , and Implementation of Channel Decoding in Wireless Systems

Today’s mobile information society has a steady demand for everincreasing data rates and better quality-of-service in wireless systems. To meet this demand standards organizations involved with the wireless industry are increasingly relying on modern high-performance channel codes such as low-density parity-check (LDPC) and turbo codes. These forward error-correction codes achieve near-optimal performance and thus enable highly robust wireless information transfer. Unfortunately, the excellent error-correction capabilities of LDPC codes and turbo codes come at the expense of substantial computational complexity in mobile receivers as the decoding of these codes is based on sophisticated iterative algorithms. In addition, practical decoder implementations must usually support a wide range of operation modes in order to enable the wireless system to adapt to various transmission environments. This combination of high computational requirements and high flexibility demands renders the implementation of LDPC and turbo decoders for wireless systems a considerable research challenge. During the last decade, significant progress has been made in the development of low-complexity LDPC and turbo decoding algorithms and the implementation of these algorithms in flexible dedicated very-large-scale integration (VLSI) circuits. Nevertheless, the implementation complexity of LDPC and turbo decoders remains high. Typically, these decoders are found among the most area and power intensive components in wireless baseband receivers and thus significantly strain the tight cost and power budgets of mobile batterypowered devices. Hence, the main part of this thesis is concerned with reducing the high VLSI implementation costs associated with LDPC and turbo
Circuit Tolerance Design Using an Improved Genetic Algorithm

In this paper, we present an improved genetic algorithm to solve the worst-case circuit tolerance design problem, which has many design parameters and constraints. The evolutionary design approach, which is called a quality-engineering-based genetic algorithm (QEGA), with a penalty function is proposed for solving the constrained optimization problem. The QEGA approach is able to explore a wide design parameter space without any prior knowledge about position and size of the region of acceptability. The QEGA approach is a method of combining the traditional genetic algorithm (TGA), which has a powerful global exploration capability, with the quality engineering method, which can exploit the optimum offspring. The quality engineering method is inserted between crossover and mutation operations of the TGA. Then, the systematic reasoning ability of the quality engineering method is incorporated in the crossover operations to select the better genes to achieve crossover, and consequently enhance the genetic algorithms. Therefore, the QEGA approach can be more robust and quickly convergent. In the worst-case circuit tolerance design problem, the vertex analysis has been used to check the feasibility of any candidate tolerance region. For this reason, if, as for a large part of cases, the region of acceptability is convex and simply connected, the QEGA approach ensures an optimal design with 100% yield. The proposed QEGA approach with a penalty function is effectively applied to solve the worst-case circuit tolerance design problem. The computational experiments also show that the presented QEGA approach can obtain better results than previous design methods
Calculating Ensemble Averaged Descriptions of Protein Rigidity without Sampling

Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG) algorithm. However, thermodynamic properties require averaging over many samples from the ensemble of accessible conformations to accurately account for fluctuations in network topology. We have developed a mean field Virtual Pebble Game (VPG) that represents the ensemble of networks by a single effective network. That is, all possible number of distance constraints (or bars) that can form between a pair of rigid bodies is replaced by the average number. The resulting effective network is viewed as having weighted edges, where the weight of an edge quantifies its capacity to absorb degrees of freedom. The VPG is interpreted as a flow problem on this effective network, which eliminates the need to sample. Across a nonredundant dataset of 272 protein structures, we apply the VPG to proteins for the first time. Our results show numerically and visually that the rigidity characterizations of the VPG accurately reflect the ensemble averaged properties. This result positions the VPG as an efficient alternative to understand the mechanical role that chemical interactions play in maintaining protein stability.