Miracle-dz/UniFAR-FTUs huggingface dataset:
Uncorrelated Multilinear Discriminant Analysis with Regularization for Gait Recognition

This paper proposes a novel uncorrelated multilinear discriminant analysis (UMLDA) algorithm for the challenging problem of gait recognition. A tensor-to-vector projection (TVP) of tensor objects is formulated and the UMLDA is developed using TVP to extract uncorrelated discriminative features directly from tensorial data. The small-sample-size (SSS) problem present when discriminant solutions are applied to the problem of gait recognition is discussed and a regularization procedure is introduced to address it. The effectiveness of the proposed regularization is demonstrated in the experiments and the regularized UMLDA algorithm is shown to outperform other multilinear subspace solutions in gait recognition.
Efficient traffic simulation using the GCA model

The GCA (Global Cellular Automata) model consists of a collection of cells which change their states synchronously depending on the states of their neighbors like in the classical CA (Cellular Automata) model. In contrast to the CA model the neighbors can be freely and dynamically selected at runtime. The GCA model is applicable to a wide range of parallel algorithms. We present a mapping of the the well known Nagel-Schreckenberg algorithm for traffic simulation onto the GCA model using agents. The vehicles are considered as agents that are modeled as GCA cells with a certain state. The proposed GCA algorithm uses multiple data and link fields per cell to interconnect the relevant cells. An agent is connected to its agent in front, and an empty cell is connected to its agent behind. In the current generation t the position of an agent is already computed for the generation t+2 (one generation in advance). Thereby the agents movements and all cell updates can directly be calculated as defined by the cell rule. No searching of specific cells during the computation is necessary. The complexity is of O(N) when simulating the N cells of an GCA sequentially. Compared to an optimized CA algorithm (with searching for agents) the GCA algorithm executes significantly faster, especially for low traffic densities and high vehicle speeds. Simulating 2048 cells and 204 agents on a multiprocessor system resulted in a speed-up (measured in clock ticks) of 14.75 for a system with 16 NIOS II processors configured on an FPGA.
AC-Feasibility on Tree Networks is NP-Hard

Recent years have witnessed significant interest in convex relaxations of the power flows, with several papers showing that the second-order cone relaxation is tight for tree networks under various conditions on loads or voltages. This paper shows that ac-feasibility, i.e., to find whether some generator dispatch can satisfy a given demand, is NP-hard for tree networks.
Oxazolidinone Antibiotics Target the P Site on Escherichiacoli Ribosomes

ABSTRACT The oxazolidinones are a novel class of antimicrobial agents that target protein synthesis in a wide spectrum of gram-positive and anaerobic bacteria. The oxazolidinone PNU-100766 (linezolid) inhibits the binding of fMet-tRNA to 70S ribosomes. Mutations to oxazolidinone resistance in Halobacteriumhalobium, Staphylococcusaureus, and Escherichiacoli map at or near domain V of the 23S rRNA, suggesting that the oxazolidinones may target the peptidyl transferase region responsible for binding fMet-tRNA. This study demonstrates that the potency of oxazolidinones corresponds to increased inhibition of fMet-tRNA binding. The inhibition of fMet-tRNA binding is competitive with respect to the fMet-tRNA concentration, suggesting that the P site is affected. The fMet-tRNA reacts with puromycin to form peptide bonds in the presence of elongation factor P (EF-P), which is needed for optimum specificity and efficiency of peptide bond synthesis. Oxazolidinone inhibition of the P site was evaluated by first binding fMet-tRNA to the A site, followed by translocation to the P site with EF-G. All three of the oxazolidinones used in this study inhibited translocation of fMet-tRNA. We propose that the oxazolidinones target the ribosomal P site and pleiotropically affect fMet-tRNA binding, EF-P stimulated synthesis of peptide bonds, and, most markedly, EF-G-mediated translocation of fMet-tRNA into the P site.
Generic faultloads based on software faults for dependability benchmarking

The most critical component of a dependability benchmark is the faultload, as it should represent a repeatable, portable, representative, and generally accepted set of faults. These properties are essential to achieve the desired standardization level required by a dependability benchmark but, unfortunately, are very hard to achieve. This is particularly true for software faults, which surely accounts for the fact that this important class of faults has never been used in known dependability benchmark proposals. This paper proposes a new methodology for the definition of faultloads based on software faults for dependability benchmarking. Faultload properties such as repeatability, portability and scalability are also analyzed and validated through experimentation using a case study of dependability benchmarking of Web-servers. We concluded that software fault-based faultloads generated using our methodology are appropriate and useful for dependability benchmarking. As our methodology is not tied to any specific software vendor or platform, it can be used to generate faultloads for the evaluation of any software product such as OLTP systems.
Chinese Spell Checking Based on Noisy Channel Model

Chinese spell checking is an important component of many Chinese NLP applications, including word processors, search engines, and automatic essay rating. Compared to English, Chinese has no word boundaries, and there are various Chinese input methods that cause different kinds of typos. Therefore, it is more difficult to develop a spell checker for Chinese. In this paper, we introduce a novel method for correcting Chinese errors based on sound or shape similarity. In our approach, potential typos in a given sentence are then corrected using a channel model and a character-based language model in the noisy channel model. In the training phase, we estimate the channel probabilities for each character based on ngrams in Web corpus. At run-time, the system generates correction candidates for each character in the given sentence and selects the appropriate correction using the channel model and the language model. The experimental results show that the proposed method achieves significantly better accuracy and recall than more complicated methods in the previous work.
Gaussian Sum Cubature Belief Propagation for Distributed Vehicular Network Navigation

Taking advantage of cooperation, vehicle network navigation can be used for applications where conventional navigation techniques usually are not competent: collision avoidance or mitigation, lane change management or emergency breaking assistance systems. This paper presents a low-complexity belief propagation (BP) algorithm, named Gaussian sum cubature belief propagation (GSCBP), for vehicle network localization. The GSCBP adopts a third-degree spherical-radical cubature rule to numerically compute the nonlinear multivariate moment integrals encountered in BP algorithm, and use the Gaussian sum to represent the messages propagated through neighboring vehicles which can provide flexibility between the accuracy and communication cost. Finally, simulations are conducted to validate the proposed algorithm.
Temporal Integration of Cholinergic and GABAergic Inputs in Isolated Insect Mushroom Body Neurons Exposes Pairing-Specific Signal Processing

GABAergic modulation of neuronal activity plays a crucial role in physiological processes including learning and memory in both insects and mammals. During olfactory learning in honeybees (Apis mellifera) and Drosophila melanogaster the temporal relation between excitatory cholinergic and inhibitory GABAergic inputs critically affects learning. However, the cellular mechanisms of temporal integration of these antagonistic inputs are unknown. To address this question, we use calcium imaging of isolated honeybee and Drosophila Kenyon cells (KCs), which are targets of cholinergic and GABAergic inputs during olfactory learning. In the whole population of honeybee KCs we find that pairing of acetylcholine (ACh) and γ-aminobutyric acid (GABA) Comment: Please use the greek letter for gamma reduces the ACh-induced calcium influx, and depending on their temporal sequence, induces different forms of neuronal plasticity. After ACh–GABA pairing the calcium influx of a subsequent excitatory stimulus is increased, while GABA–ACh pairing affects the decay time leading to elevated calcium levels during the late phase of a subsequent excitatory stimulus. In an exactly defined subset of Drosophila KCs implicated in learning we find similar pairing-specific differences. Specifically the GABA–ACh pairing splits the KCs in two functional subgroups: one is only weakly inhibited by GABA and shows no neuronal plasticity and the other subgroup is strongly inhibited by GABA and shows elevated calcium levels during the late phase of a subsequent excitatory stimulus. Our findings provide evidence that insect KCs are capable of contributing to temporal processing of cholinergic and GABAergic inputs, which provides a neuronal mechanism of the differential temporal role of GABAergic inhibition during learning.
Performance Analysis of CMA Blind Equalizer for Mobile-WiMAX over Multipath Fading Channels using Simulink

Present and future communication standards demand high quality of services with higher data rates. In order to reduce noise in communications and to equalize channels, new equalization algorithms are being developed, namely, Blind Channel Equalization. In this paper, WiMAX end to end physical layer is modeled with blind equalization and space time block coding (STBC) using Simulink. Results analyzed the performance of WiMAX physical layer in terms of scatter plots over AWGN and multipath faded channels separately. This paper concluded that constant modulus algorithm (CMA) blind equalizer offers good synchronization between the transmitted and received symbols with better spectral efficiency.
Research Progress of Application of Ultrasonic Technology to Biomass Resources Processing

Technologies and applications of ultrasonic processing on biomass resources at home and abroad were reviewed.The theory of ultrasonic processing for plant extraction and their related extraction equipments in China were described.The ultrasonic applications for extraction of essential oil,natural pigment,polysaccharide,flavonoids,alkaloids,polyphenols,organic acids,vegetable oil,etc.were introduced.The ultrasonic processings for preparation of biodiesel fuel,hydrolysis of biomass resources and modification of biomass materials were also introduced.
Calibration of Real Scenes for the Reconstruction of Dynamic Light Fields

SUMMARY The classic light field and lumigraph are two well–known approaches to image–based rendering, and subsequently many new rendering techniques and representations have been proposed based on them. Nevertheless the main limitation remains that in almost all ofthem only static scenes are considered. In this contribution we describe a method for calibrating a scene which includes moving or deforming objects from multiple image sequences taken with a hand–held camera. For each image sequence the scene is assumed to be static, which allows the reconstruction ofa conventional static light field. The dynamic light field is thus composed ofmultiple static light fields, each of which describes the state ofthe scene at a certain point in time. This allows not only the modeling ofrigid moving objects, but any kind ofmotion including def ormations. In order to facilitate the automatic calibration, some assumptions are made for the scene and input data, such as that the image sequences for each respective time step share one common camera pose and that only the minor part ofthe scene is actually in motion.
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

Many machine learning algorithms are vulnerable to almost imperceptible perturbations of their inputs. So far it was unclear how much risk adversarial perturbations carry for the safety of real-world machine learning applications because most methods used to generate such perturbations rely either on detailed model information (gradient-based attacks) or on confidence scores such as class probabilities (score-based attacks), neither of which are available in most real-world scenarios. In many such cases one currently needs to retreat to transfer-based attacks which rely on cumbersome substitute models, need access to the training data and can be defended against. Here we emphasise the importance of attacks which solely rely on the final model decision. Such decision-based attacks are (1) applicable to real-world black-box models such as autonomous cars, (2) need less knowledge and are easier to apply than transfer-based attacks and (3) are more robust to simple defences than gradient- or score-based attacks. Previous attacks in this category were limited to simple models or simple datasets. Here we introduce the Boundary Attack, a decision-based attack that starts from a large adversarial perturbation and then seeks to reduce the perturbation while staying adversarial. The attack is conceptually simple, requires close to no hyperparameter tuning, does not rely on substitute models and is competitive with the best gradient-based attacks in standard computer vision tasks like ImageNet. We apply the attack on two black-box algorithms from Clarifai.com. The Boundary Attack in particular and the class of decision-based attacks in general open new avenues to study the robustness of machine learning models and raise new questions regarding the safety of deployed machine learning systems. An implementation of the attack is available as part of Foolbox at this https URL .
Experimental Study of Reputation Mechanisms in an Exchange Economy

We experimentally evaluate reputation mechanisms in an exchange market in which participants have the option of not fulfilling their contracts. These mechanisms vary in the information they provide on past behavior. Participants can choose who they trade with, allowing endogenous response to low reputation through ostracizing or price discriminating behaviors. The participants responded strategically to the provided information. In particular, mechanisms revealing more information had a statistically significant increase in fulfillment rates. Our experimental design allowed identifying the effect of reputation mechanism on endogenous market behavior. We found that decreasing fulfillment led to lower efficiency and increased market volume but did not affect the prices.
FIR system modeling and identification in the presence of noise and with band-limited inputs

System identification, that is, the modeling and identification of a system from knowledge of its input and output signals, is a subject that is of considerable importance in many areas of signal and data processing. Because of the diversity of applications, a number of different methods for system identification with different advantages and disadvantages have been described and used in the literature. In this paper we investigate the performance of three well-known system identification methods based on an FIR (finite impulse response) model of the system. The methods will be referred to in this paper as the least squares analysis (LSA) method, the least mean squares adaptation algorithm (LMS), and the short-time spectral analysis (SSA) procedure. Our particular interest in this paper concerns the performance of these algorithms in the presence of high noise levels and in situations where the input signal may be band-limited. Both white and nonwhite random noise signals as well as speech signals are used as test signals to measure the performance of each of the system identification techniques as a function of the signal-to-noise ratio of the systems output. Quantitative results in terms of an accuracy measure of system identification are presented and a simple analytical model is used to explain the measured results.
Potential of Phytase-Mediated Iron Release from Cereal-Based Foods: A Quantitative View

The major part of iron present in plant foods such as cereals is largely unavailable for direct absorption in humans due to complexation with the negatively charged phosphate groups of phytate (myo-inositol (1,2,3,4,5,6)-hexakisphosphate). Human biology has not evolved an efficient mechanism to naturally release iron from iron phytate complexes. This narrative review will evaluate the quantitative significance of phytase-catalysed iron release from cereal foods. In vivo studies have shown how addition of microbially derived phytases to cereal-based foods has produced increased iron absorption via enzyme-catalysed dephosphorylation of phytate, indicating the potential of this strategy for preventing and treating iron deficiency anaemia. Despite the immense promise of this strategy and the prevalence of iron deficiency worldwide, the number of human studies elucidating the significance of phytase-mediated improvements in iron absorption and ultimately in iron status in particularly vulnerable groups is still low. A more detailed understanding of (1) the uptake mechanism for iron released from partially dephosphorylated phytate chelates, (2) the affinity of microbially derived phytases towards insoluble iron phytate complexes, and (3) the extent of phytate dephosphorylation required for iron release from inositol phosphates is warranted. Phytase-mediated iron release can improve iron absorption from plant foods. There is a need for development of innovative strategies to obtain better effects.
Treatment approaches for traumatized anterior teeth with excessive tissue loss: three case reports

Use of direct composite and indirect laminate veneers has been an alternative to metal- and all-ceramic crowns for anterior teeth restorations. Dental traumas are the most common reasons for excessive tissue loss. Treatment options depend on the amount of remaining tissue, the extent of the damage to dental pulp and periapical tissues and the time elapsed before dental treatment. The aim of this case report was to evaluate the direct and indirect techniques used in the treatments of traumatically fractured anterior teeth. In Case 1, a 29-year-old male patient attended to the clinics of the Department of Restorative Dentistry, Faculty of Dentistry, Istanbul University for the replacement of old composite restorations. According to anamnesis, the anterior teeth had fractured because of falling from bicycle. Dentinal pins used to retain the composite restorations were screwed out and indirect composite laminate veneers were placed. In Case 2, a 27-year-old male patient attended to our clinic for the treatment of his anterior teeth which were fractured due to a fall. A different type of technique, a silicon guide, was used to mimic the natural teeth surfaces precisely. In Case 3, a 16-year-old female patient attended to our clinic for the treatment of her anterior teeth which were fractured in a car accident. On clinical evaluation, related teeth were found to be non-vital and application of fiber posts was considered suitable before direct composite restorations. In conclusion, all of these techniques may be used for traumatized anterior teeth. Esthetical necessities and functional forces should be taken into consideration in material choice.
Faster Algorithms for Rectangular Matrix Multiplication

Let α be the maximal value such that the product of an n × n<sup>α</sup> matrix by an n<sup>α</sup> × n matrix can be computed with n<sup>2+o(1)</sup> arithmetic operations. In this paper we show that α >; 0.30298, which improves the previous record α >; 0.29462 by Coppersmith (Journal of Complexity, 1997). More generally, we construct a new algorithm for multiplying an n × n<sup>k</sup> matrix by an n<sup>k</sup> × n matrix, for any value k ≠ 1. The complexity of this algorithm is better than all known algorithms for rectangular matrix multiplication. In the case of square matrix multiplication (i.e., for k = 1), we recover exactly the complexity of the algorithm by Coppersmith and Winograd (Journal of Symbolic Computation, 1990). These new upper bounds can be used to improve the time complexity of several known algorithms that rely on rectangular matrix multiplication. For example, we directly obtain a O(n<sup>2.5302</sup>)-time algorithm for the all-pairs shortest paths problem over directed graphs with small integer weights, where n denotes the number of vertices, and also improve the time complexity of sparse square matrix multiplication.
Biomechanical Evaluation of Ascending Aortic Aneurysms

The biomechanical properties of ascending aortic aneurysms were investigated only in the last decade in a limited number of studies. Indeed, in recent years, there has been a growing interest in this field in order to identify new predictive parameters of risk of dissection, which may have clinical relevance. The researches performed so far have been conducted according to the methods used in the study of abdominal aortic aneurysms. In most cases, uniaxial or biaxial tensile tests were used, while in a smaller number of studies other methods, such as opening angle, bulge inflation, and inflation-extension tests, were used. However, parameters and protocols of these tests are at present very heterogeneous in the studies reported in the literature, and, therefore, the results are not comparable and are sometimes conflicting. The purpose of this review then thence to provide a comprehensive analysis of the experimental methodology for determination of biomechanical properties in the specific field of aneurysms of the ascending aorta to allow for better comparison and understanding of the results.
Capacity Regions of Families of Continuous-Time Multi-User Gaussian Channels

In this paper, we propose to use Brownian motions to model families of continuoustime multiuser Gaussian channels without bandwidth limit. It turns out that such a formulation allows parallel translation of many fundamental notions and techniques from the discrete-time setting to the continuous-time regime, which enables us to derive the capacity regions of a continuous-time white Gaussian multiple access channel with/without feedback, a continuous-time white Gaussian interference channel without feedback and a continuous-time white Gaussian broadcast channel without feedback. In theory, these capacity results give the fundamental transmission limit modulation/coding schemes can achieve for families of continuous-time Gaussian one-hop channels without bandwidth limit; in practice, the explicit capacity regions derived and capacity achieving modulation/coding scheme proposed may provide engineering insights on designing multi-user communication systems operating on an ultra-wideband regime.
Performance analysis of differential-phase-shift-keying optical receivers in the presence of in-band crosstalk noise

In-band crosstalk can pose important limitations in an all-optical wavelength-division-multiplexed (WDM) network. Recent studies have demonstrated that differential phase shift keying (DPSK), can tolerate higher in-band crosstalk-noise levels compared to amplitude shift keying (ASK). In this paper, the performance of a DPSK receiver, limited by in-band crosstalk noise, is studied theoretically. The model takes into account both the in-band crosstalk noise as well as the amplified-spontaneous-emission (ASE) noise of the optical amplifiers. The model is based on the evaluation of the moment-generating function (MGF) of the decision variable through which, the error probability (EP) can be calculated by applying the saddle point approximation. This provides a rigorous model for the evaluation of the EP of a DPSK receiver in the presence of ASE and in-band crosstalk noises. In the absence of the ASE noise, a closed-form formula for the EP is also given that is useful for estimating the error floor set by the in-band crosstalk noise.