Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy Internal Model Control of Nonlinear Plants with Time Delay based on Parallel Distributed Compensation

The parallel-distributed compensation (PDC) together with Takagi-Sugeno-Kang (TSK) fuzzy modelling proved to be a modern model-based systematic approach for the design of fuzzy nonlinear controllers from stability and robustness requirements. The usual local linear controllers comprise a state feedback. This requires measurements of the state variables or an observer design. The aim of the present investigation is to develop a fuzzy internal model controller (FIMC) for a nonlinear plant with time delay under uncertainties. The FIMC is PDC-TSK based with dynamic local linear controllers, which are designed on the principle of the internal model controllers to ensure local linear systems stability and robustness. The main contribution of the paper is a method for the design of a FIMC, designed FIMC for the control of the air temperature in a laboratory furnace and MATLAB based simulation investigations of the closed loop system stability and dynamic performance. The FIMC reduces the settling time and the overshoot and improves the system robustness compared to a linear PI controller.
Analytics for NetApp E-Series AutoSupport Data Using Big Data Technologies

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Spectral Minutiae Fingerprint Recognition System

Biometrics refers to the automatic recognition of individual s based on their physiological and/or behavioral characteristics, such as faces, finger prints, iris, and gait. In this paper, we focus on the application of finger p rint recognition system. The spectral minutiae fingerprint re cognition is a method to represent a minutiae set as a fi xedlength feature vector, which is invariant to translation, a d in which rotation and scaling become translations, so th at they can be easily compensated for. Based on the spectra l minutiae features, this paper introduces two feature redu ction algorithms: the Column Principal Component Analysis and the Lin Discrete Fourier Transform feature reductions, which can efficiently compress the template size with a reduction rate of 94%. With reduced features, we can also achieve a fast minutiae-based matching algorithm. This p aper presents the performance of the spectral minutiae fingerprint recognition system, this fast operation renders ou system suitable for a large-scale fingerprint identi fica on system, thus significantly reducing the time to perform matc hing, especially in systems like, police patrolling, airp orts etc,. The spectral minutiae representation system tends o significantly reduce the false acceptance rate with a marginal increase in the false rejection rate.
Phosphogenesis in the 2460 and 2728 million-year-old banded iron formations as evidence for biological cycling of phosphate in the early biosphere

The banded iron formation deposited during the first 2 billion years of Earth's history holds the key to understanding the interplay between the geosphere and the early biosphere at large geological timescales. The earliest ore-scale phosphorite depositions formed almost at ∼2.0–2.2 billion years ago bear evidence for the earliest bloom of aerobic life. The cycling of nutrient phosphorus and how it constrained primary productivity in the anaerobic world of Archean–Palaeoproterozoic eons are still open questions. The controversy centers about whether the precipitation of ultrafine ferric oxyhydroxide due to the microbial Fe(II) oxidation in oceans earlier than 1.9 billion years substantially sequestrated phosphate, and whether this process significantly limited the primary productivity of the early biosphere. In this study, we report apatite radial flowers of a few micrometers in the 2728 million-year-old Abitibi banded iron formation and the 2460 million-year-old Kuruman banded iron formation and their similarities to those in the 535 million-year-old Lower Cambrian phosphorite. The lithology of the 535 Million-year-old phosphorite as a biosignature bears abundant biomarkers that reveal the possible similar biogeochemical cycling of phosphorus in the Later Archean and Palaeoproterozoic oceans. These apatite radial flowers represent the primary precipitation of phosphate derived from the phytoplankton blooms in the euphotic zones of Neoarchean and Palaoeproterozoic oceans. The unbiased distributions of the apatite radial flowers within sub-millimeter bands do not support the idea of an Archean Crisis of Phosphate. This is the first report of the microbial mediated mineralization of phosphorus before the Great Oxidation Event when the whole biosphere was still dominated by anaerobic microorganisms.
Electro-Photonic NoC Designs for Kilocore Systems

The increasing core count in manycore systems requires a corresponding large Network-on-chip (NoC) bandwidth to support the overlying applications. However, it is not possible to provide this large bandwidth in an energy-efficient manner using electrical link technology. To overcome this issue, photonic link technology has been proposed as a replacement. This work explores the limits and opportunities for using photonic links to design the NoC architecture for a future Kilocore system. Three different NoC designs are explored: ElecNoC, an electrical concentrated two-dimensional- (2D) mesh NoC; HybNoC, an electrical concentrated 2D mesh with a photonic multi-crossbar NoC; and PhotoNoC, a photonic multi-bus NoC. We consider both private and shared cache architectures and, to leverage the large bandwidth density of photonic links, we investigate the use of prefetching and aggressive non-blocking caches. Our analysis using contemporary Big Data workloads shows that the non-blocking caches with a shared LLC can best leverage the large bandwidth of the photonic links in the Kilocore system. Moreover, compared to ElecNoC-based and HybNoC-based Kilocore systems, a PhotoNoC-based Kilocore system achieves up to 2.5× and 1.5× better performance, respectively, and can support up to 2.1× and 1.1× higher bandwidth, respectively, while dissipating comparable power in the overall system.
Self-Adaptive Cost-Efficient Consistency Management in the Cloud

Many data-intensive applications and services in the cloud are geo-distributed and rely on geo-replication. Traditional synchronous replication that ensures strong consistency exposés these systems to the bottleneck of wide areas network latencies that affect their performance, availability and the monetary cost of running in the cloud. In this context, several weaker consistency models were introduced to hide such effects. However, these solutions may tolerate far too much stale data to be read. In this PhD research, we focus on the investigation of better and efficient ways to manage consistency. We propose self-adaptive methods that tune consistency levels at runtime in order to achieve better performance, availability and reduce the monetary cost without violating the consistency requirements of the application. Furthermore, we introduce a behavior modeling method that automatically analyzes the application and learns its consistency requirements. The set of experimental evaluations on Grid'5000 and Amazon EC2 cloud platforms show the effectiveness of the proposed approaches.
Multilayer Antenna-Filter Antenna for Beam-Steering Transmit-Array Applications

This paper presents a study on reconfigurable transmit-array (TA) antennas based on multilayer tunable elements. The proposed configuration can be referred to as a multilayer antenna-filter antenna (MAFA) and it can be viewed as an extension of the antenna-filter antenna concept. It consists of multiple antenna layers cascaded to form a spatially distributed bandpass filter. Phase agility is achieved by tuning the resonant frequency of each layer. The main objective of this paper is to introduce a new design technique for MAFA TA antennas. As will be shown, the key feature of the proposed approach is that it allows to simultaneously take into account three key design parameters: the phase tuning range, the maximum acceptable losses per unit cell, and the operating bandwidth. Simulations and experimental results for MAFAs based on varactor-loaded slot antennas will be illustrated to prove the validity of the proposed method. In particular, numerical results will demonstrate that MAFA cells can be designed to provide full phase agility over operating bandwidths of up to 10% with maximum insertion losses of 3 dB. Furthermore, a specific example will show how introducing an inter-layer medium with a higher dielectric permittivity it is possible to reduce the array longitudinal size. Finally, experimental results obtained using a waveguide simulator will be presented for a 1 × 3 five-layer MAFA cell.
Designing an assistive device for the blind based on object localization and augmented auditory reality

There are many electronic devices for the visually impaired but few actually get used on a daily basis. This is due in part to the fact that many devices often fail to address the real needs of the users. In this study, we begin with a review of the existing literature followed by a survey of 54 blind people which suggests that one particular function could be particularly useful in a new device, namely, the ability to localize objects. We have tested the possibility of using a sound rendering system to indicate a particular spatial location, and propose to couple this with a biologically inspired image processing system that can locate visual patterns that correspond to particular objects and places. We believe that such a system can address one of the major problems faced by the visually handicapped, namely their difficulty in localizing specific objects.
Encoding Difficulty Promotes Postlearning Changes in Sleep Spindle Activity during Napping

Learning-dependent increases in sleep spindle density have been reported during nocturnal sleep immediately after the learning session. Here, we investigated experience-dependent changes in daytime sleep EEG activity after declarative learning of unrelated word pairs. At weekly intervals, 13 young male volunteers spent three 24 h sessions in the laboratory under carefully controlled homeostatic and circadian conditions. At approximately midday, subjects performed either one of two word-pair learning tasks or a matched nonlearning control task, in a counterbalanced order. The two learning lists differed in the level of concreteness of the words used, resulting in an easier and a more difficult associative encoding condition, as confirmed by performance at immediate cued recall. Subjects were then allowed to sleep for 4 h; afterward, delayed cued recall was tested. Compared with the control condition, sleep EEG spectral activity in the low spindle frequency range and the density of low-frequency sleep spindles (11.25–13.75 Hz) were both significantly increased in the left frontal cortex after the difficult but not after the easy encoding condition. Furthermore, we found positive correlations between these EEG changes during sleep and changes in memory performance between pre-nap and post-nap recall sessions. These results indicate that, like during nocturnal sleep, daytime sleep EEG oscillations including spindle activity are modified after declarative learning of word pairs. Furthermore, we demonstrate here that the nature of the learning material is a determinant factor for sleep-related alterations after declarative learning.
R-CHOP with or without bevacizumab in patients with previously untreated diffuse large B-cell lymphoma: final MAIN study outcomes

Vascular endothelial growth factor is involved in lymphoma growth, suggesting a potential role for anti-vascular endothelial growth factor therapies in hematologic malignancies. In this phase III study, patients with CD20-positive diffuse large B-cell lymphoma were randomized to rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone plus either placebo (R-CHOP) or bevacizumab (RA-CHOP). Treatment was administered every 21 (8 cycles) or 14 days (6 cycles plus 2 rituximab cycles) as per institutional practice. An early analysis of risk/benefit by the Data and Safety Monitoring Board showed that RA-CHOP increased cardiotoxicity without prolonging progression-free survival compared with R-CHOP, and the trial was stopped early. The study protocol was amended to allow for 12 additional months of follow up to evaluate safety. With 787 patients enrolled, median follow up was 23.7 and 23.6 months for R-CHOP and RA-CHOP, respectively. Median progression-free survival for R-CHOP and RA CHOP was 42.9 and 40.2 months, respectively (hazard ratio=1.09; P=0.49). The proportion of deaths was identical for R-CHOP (83 of 387, 21%) and RA-CHOP (82 of 390, 21%). Relative to R-CHOP, RA-CHOP had a higher rate of left ventricular ejection fraction perturbation (18% vs. 8%; odds ratio=2.51; 95% confidence interval (CI): 1.60–3.93) and congestive heart failure (16% vs. 7%; odds ratio=2.79; 95%CI: 1.72–4.54). Bevacizumab added to R-CHOP increased cardiac events, without increasing efficacy, arguing against further evaluation of RA-CHOP in patients with diffuse large B-cell lymphoma. The MAIN study is registered at clinicaltrials.gov identifier:00486759.
Biochemical Properties and Potential Applications of Recombinant Leucine Aminopeptidase from Bacillus kaustophilus CCRC 11223

Experiments were carried out to investigate the effects of various factors on the activity and conformation of recombinant leucine aminopeptidase of Bacillus kaustophilus CCRC 11223 (BkLAP) and potential utilization of BkLAP in the hydrolysis of anchovy protein. Optimal temperature and pH of BkLAP were 70 °C and 8.0 in potassium-phosphate buffer, respectively, and the activity was strongly stimulated by Ni2+, followed by Mn2+ and Co2+. Conformational studies via circular dichroism spectroscopy indicated that various factors could influence the secondary structure of BkLAP to different extents and further induce the changes in enzymatic activity. The secondary structure of BkLAP was slightly modified by Ni2+ at the concentration of 1×10−4 M, however, significant changes on the secondary structures of the enzyme were observed when Hg2+ was added to the concentration of 1×10−4 M. The potential application of BkLAP was evaluated through combination with the commercial or endogenous enzyme to hydrolysis the anchovy protein. Results showed that combining the BkLAP with other enzymes could significantly increase the degree of hydrolysis and amino acid component of hydrolysate. In this regard, BkLAP is a potential enzyme that can be used in the protein hydrolysate industry.
EMbOdiEd iMPrESSiON fOrMaTiON: SOCial JudgMENTS aNd MOTOr CuES TO aPPrOaCh aNd avOidaNCE

Motor movements that embody approach and avoidance shape individuals' affective and evaluative responses to objects. In two studies we investigate how approach and avoidance impact participants' judgments of ecologically valid targets: other humans. One trait relevant to the approach or avoidance of other humans is trustworthiness. Trustworthy people can be safely approached, and untrustworthy people should be avoided. We examined whether arm contractions of approach and avoidance enhanced or diminished trust toward others, respectively. Perceived trustworthiness, relative to untrustworthiness, potentiated arm flexion (approach; Study 1). Conversely, arm flexion relative to extension led to increased perceptions of trust (Study 2). Thus, beyond motivational, cognitive, and emotional processes, embodied cues impact impression formation.
Effects of prison work programmes on the employability of ex-prisoners

This paper presents the results of a study that links information from the prison system with information from the Spanish Social Security System in order to study the employability of former inmates of prisons in Catalonia, Spain. Few studies of this type have been carried out in the world and this is the first in Spain. The results show that 43.6 percent of ex-prisoners find a job after serving their sentence, but their integration in the labour market tends to be fragile, confirming that it is a very vulnerable group. It was also found that prison work has a favourable effect on employability and that vocational training has a lesser or no effect.
High availability-aware optimization digest for applications deployment in cloud

Cloud computing is continuously growing as a business model for hosting information and communication technology applications. Although on-demand resource consumption and faster deployment time make this model appealing for the enterprise, other concerns arise regarding the quality of service offered by the cloud. One major concern is the high availability of applications hosted in the cloud. This paper demonstrates the tremendous effect that the placement strategy for virtual machines hosting applications has on the high availability of the services provided by these applications. In addition, a novel scheduling technique is presented that takes into consideration the interdependencies between applications components and other constraints such as communication delay tolerance and resource utilization. The problem is formulated as a linear programming multi-constraint optimization model. The evaluation results demonstrate that the proposed solution improves the availability of the scheduled components compared to OpenStack Nova scheduler.
Large-Scale Analysis of Formations in Soccer

Due to the demand for better and deeper analysis in sports, organizations (both professional teams and broadcasters) are looking to use spatiotemporal data in the form of player tracking information to obtain an advantage over their competitors. However, due to the large volume of data, its unstructured nature, and lack of associated team activity labels (e.g. strategic/tactical), effective and efficient strategies to deal with such data have yet to be deployed. A bottleneck restricting such solutions is the lack of a suitable representation (i.e. ordering of players) which is immune to the potentially infinite number of possible permutations of player orderings, in addition to the high dimensionality of temporal signal (e.g. a game of soccer last for 90 mins). Leveraging a recent method which utilizes a "role-representation", as well as a feature reduction strategy that uses a spatiotemporal bilinear basis model to form a compact spatiotemporal representation. Using this representation, we find the most likely formation patterns of a team associated with match events across nearly 14 hours of continuous player and ball tracking data in soccer. Additionally, we show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.
Roll Force AWC and RHC Tension Control in Hot Strip Mills

This paper proposes a new width control system composed of a RF (roll force) AWC (automatic width control) in the roughing mill and a RHC (receding horizon control) with a 4SID (subspace-based state space system identification) model identifier. The RF AWC is designed by the control model on the basis of a gauge meter equation using the roll force of a vertical mill. The RHC is employed to satisfy the constraints on the control input/state, guarantee the stability, and attenuate the effect of the disturbances. It is shown through the field test of the Pohang no.1 hot strip mill of POSCO that the width margin is considerably improved by the proposed control scheme.
Encountering the Internet Ethnographically

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A Parallel Approach to Hierarchical Radiosity

A parallel algorithm solving the radiosity equation is presented. It is based on the hierarchical approach (HR) 5] and realized on a massively parallel supercomputer | the ConnectionMachine 5. Our algorithm considers the HR approach as a process that manipulates an huge graph structure. Simulated annealing is used in the graph's rearranging procedure to achieve a good work-balance and nearly optimal communication costs. The implementation shows a signiicant step to facilitate the application of a radiosity solver, produced on one hand by the few user-support that HR needs, on the other hand by the fast calculation times the parallel implementation ooers. On 64 processors we obtained a speed-up of 8.4.
The Convergence Guarantees of a Non-Convex Approach for Sparse Recovery

In the area of sparse recovery, numerous researches hint that non-convex penalties might induce better sparsity than convex ones, but up until now those corresponding non-convex algorithms lack convergence guarantees from the initial solution to the global optimum. This paper aims to provide performance guarantees of a non-convex approach for sparse recovery. Specifically, the concept of weak convexity is incorporated into a class of sparsity-inducing penalties to characterize the non-convexity. Borrowing the idea of the projected subgradient method, an algorithm is proposed to solve the non-convex optimization problem. In addition, a uniform approximate projection is adopted in the projection step to make this algorithm computationally tractable for large scale problems. The convergence analysis is provided in the noisy scenario. It is shown that if the non-convexity of the penalty is below a threshold (which is in inverse proportion to the distance between the initial solution and the sparse signal), the recovered solution has recovery error linear in both the step size and the noise term. Numerical simulations are implemented to test the performance of the proposed approach and verify the theoretical analysis.