Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of Robot Paths Computed by Randomized Planners

Randomized path planners have been successfully used to compute feasible paths for difficult planning problems. Such paths are typically computed without taking into account any optimality criteria and may contain many “jagged” segments because of the randomness involved in their generation. This paper presents a two-phase path planning algorithm, which uses a randomized planner to compute low-cost paths, and gradient descent to locally optimize these paths by minimizing a Hamiltonian function. The algorithm is tested on motion planning for a non-holonomic car-like robot. The results indicate that the two-phase approach is practical; however, gradient descent seems to be inefficient for the optimization of long paths.
SVEN: Informative Visual Representation of Complex Dynamic Structure

Abstract : Graphs change over time, and typically variations on the small multiples or animation pattern is used to convey this dynamism visually. However, both of these classical techniques have significant drawbacks, so a new approach, Storyline Visualization of Events on a Network (SVEN) is proposed. SVEN builds on storyline techniques, conveying nodes as contiguous lines over time. SVEN encodes time in a natural manner, along the horizontal axis, and optimizes the vertical placement of storylines to decrease clutter (line crossings, straightness, and bends) in the drawing. This paper demonstrates SVEN on several different flavors of real-world dynamic data, and outlines the remaining near-term future work.
Two Related Lexico-Syntactic Approaches to Entailment

Two approaches to Textual Entailment are presented. They both rely on lexicosyntactic information. The two approaches differ mainly in the way the syntactic relationships are derived. In one approach, the syntactic relationships are drawn from a phrase-based parse tree. In the other, we use information provided by a dependency parser. The first approach performs at 0.59 precision and 0.6047 average precision. The second system’s performance is 0.5837 precision and 0.5785 average precision.
Control and orchestration of multidomain optical networks with GMPLS as inter-SDM controller communication [Invited]

Emerging use cases, such as the orchestration of heterogeneous domains or the interconnection of remote data centers, require the design of new network control, management, and orchestration architectures that are adapted to the requirements associated with end-to-end services. This heterogeneity, stemming from actual deployments, is related to the involved data and control technologies or due to network segmentation. It is acknowledged that, in these scenarios, the deployment of a single software- defined networking (SDN) controller may not be practical or may have fundamental limitations, in terms of either scalability, complexity, or interoperability. To address this trend, and as a means to cope with the complexity growth, research in this area is considering the concept of SDN orchestration (the coordinated control of heterogeneous systems), abstraction (the selection of entityrelevant attributes), and the use of multiple controllers, commonly arranged in hierarchical or flat configurations. In this paper, we consider a hybrid approach combining elements from distributed control with elements from centralized control, relying on the concepts of abstraction and aggregation and hierarchical traffic engineering (TE). We propose a multidomain and multivendor network control architecture organized in layers, the abstract network layer and the control-specific layer, resulting in a mesh of generic SDN controllers that use generalized multiprotocol label switching (GMPLS) protocols as their east/west interfaces (open shortest path first TE and Resource Reservation Protocol with extensions for TE as inter- SDN controller communications protocols), forming an abstracted topology. To validate the approach, and to evaluate factors such as end-to-end network service deployment delay or control overhead, the proposed architecture is implemented and validated in a control plane testbed. While emphasis is given to the control of optical (flexi-grid) networks, the proposed approach can be generalized to other transport technologies.
Specular highlight enhancement from video sequences

We propose a novel method for detecting and enhancing specular highlights from a video sequence, thereby obtaining a better visual perception of the specularity. To this end, we first generate a specularity map, defined over the space-time domain, by leveraging information provided by the temporal acquisition. We then amplify the highlights in each video frame to create the visual sensation of high dynamic range data. Results are illustrated on several videos taken under different acquisition scenarios.
Investigation of PO43- Removal in Aerated and Unaerated High Fe EAF-Slag Filter System

Phosphorus in wastewater is one the main culprit which accelerates eutrophication in waterbody if it is not being treated properly. Steel slag filter emerged as one alternative treatment for wastewater. However, the variousness of metal oxides including Fe in steel slag will affect the phosphorus removal efficiency. Thus, this study was conducted to investigate the ability of a series of lab-scale high Fe electric arc furnace (EAFslag) column filters in removing PO43from synthetic wastewater. The systems were operated under aerated and unaerated within acidic and alkaline conditions. Synthetic wastewater contained 25 mg/L was prepared as the feed and monitored weekly basis for the PO4 removal efficiency and the total metals (Ca, Fe, and Mg) concentrations in the effluents. The results show that both aerated and unaerated high Fe EAF-slag filter systems have high PO4 removal efficiency under acidic condition, which unaerated system performed slightly better. It can be observed that unaerated systems performed better in removing PO4 at acidic and neutral pH values but not at extremely high pH. As for the PO4 removal mechanism was achieved by adsorption and precipitation at acidic pH and the concentration of Ca, Mg and Fe in effluents was related to the PO4 removal efficiency at different pH values.
Negative bias temperature instability: Road to cross in deep submicron silicon semiconductor manufacturing

We present an overview of negative bias temperature instability (NBTI) commonly observed in p-channel metal–oxide–semiconductor field-effect transistors when stressed with negative gate voltages at elevated temperatures. We discuss the results of such stress on device and circuit performance and review interface traps and oxide charges, their origin, present understanding, and changes due to NBTI. Next we discuss the effects of varying parameters (hydrogen, deuterium, nitrogen, nitride, water, fluorine, boron, gate material, holes, temperature, electric field, and gate length) on NBTI. We conclude with the present understanding of NBTI and its minimization.
Efficient cross-validation of kernel fisher discriminant classifiers

Mika et al. [1] introduce a non-linear formulation of the Fisher discriminant based the well-known "kernel trick", later shown to be equivalent to the Least-Squares Support Vector Machine [2, 3]. In this paper, we show that the cross-validation error can be computed very efficiently for this class of kernel machine, specifically that leave-one-out cross-validation can be performed with a computational complexity of only O(l3) operations (the same as that of the basic training algorithm), rather than the O(l4) of a direct implementation. This makes leave-one-out cross-validation a practical proposition for model selection in much larger scale applications of KFD classifiers.
Time-eecient State Space Search

We present two time-e cient state space algorithms for searching minimax trees. Because they are based on SSS* and Dual*, both dominate Alpha-Beta on a node count basis. Moreover, one of them is always faster in searching random trees, even when the leaf node evaluation time is negligible. The fast execution time is attributed to the recursive nature of our algorithms and to their e cient data structure (a simple array) for storing the bestrst node information. In practical applications with more expensive leaf evaluations we conjecture that the recursive state space search algorithms perform even better and might eventually supersede the popular directional search methods.
Computação Urbana: Técnicas para o Estudo de Sociedades com Redes de Sensoriamento Participativo

Urban computing is a recent research topic that aims to obtain and analyze urban data from various sources, such as traditional wireless sensor networks (WSNs) and emerging participatory sensor networks (PSNs) to understand and address issues that cities face. PSNs are particularly interesting because they rely on the participation of users in urban sensing, allowing the observation of large-scale actions of people in (almost) real time over long periods of time. PSN data increase our knowledge about different aspects of our lives in urban scenarios, which can be very useful in developing more sophisticated applications to various sectors, especially those related to the understanding of urban societies. The purpose of this short course is to discuss the concept of urban computing and urban sensing with participatory sensor networks. We aim to show the relevance of urban computing and motivate the construction of new applications that address issues related to the dynamics of cities and urban social behavior. In addition, this short course will discuss how to work with PSNs, by analyzing their properties and their usefulness in the development of new applications in urban computing.
Generalizations of some irreducibility results by Schur

(1.2) f(x) = an xn (n+ a)! + an−1 xn−1 (n− 1 + a)! + · · ·+ a1 x (1 + a)! + a0 1 a! can have a factor of given degree over the rationals. In 1929 Schur [26], [27] proved that a polynomial of the form (1.2) satisfying (1.1) is irreducible if a = 0 and also if a = 1 unless n + 1 is a power of 2 when it may have a linear factor or n = 8 when it may even have a quadratic factor. Also for a = 2 and many other values of a the polynomial f may have a linear factor. On the other hand, a factor of degree > n/2 of f has a cofactor of degree at most n/2. Therefore we consider the question whether f has a factor of degree k with 2 ≤ k ≤ n/2, which we always assume unless specified otherwise. One of our results reads as follows. Theorem 1.1. Let a and k be integers such that 2 ≤ k ≤ n/2, 0 ≤ a ≤ 3k/2. Let f(x) be given by (1.2) where a0, a1, . , an are integers satisfying (1.1). Assume that f(x) has a factor of degree k. Then (n, k, a) ∈ {(6, 2, 3), (7, 2, 2), (7, 2, 3), (7, 3, 3), (8, 2, 1), (1.3) (8, 3, 2), (12, 3, 4), (13, 2, 3), (22, 2, 3), (46, 3, 4), (78, 2, 3)}. We shall show that all the cases listed in (1.3) can indeed be realized by some factorizations. The factorizations for the last two cases are due to
Learning stochastic functions by smooth simultaneous estimation

To learn, it suffices to estimate the error of all candidate hypotheses simultaneously. We study the problem of when this “simultaneous estimation” is possible and show that it leads to new learning procedures and weaker sufficient conditions for a broad class of learning problems. We modify the standard Probably Approximately Correct (PAC) setup to allow concepts that are “stochastic functions. ” A deterministic function maps a set X into a set Y, whereas a stochastic function is a probability distribution on X x Y. We approach the simultaenous estimation problem by concentrating on a subset of all estimators, those that satisfy a natural “smoothness” constraint. The common empirical estimator falls within this class. We show that smooth simultaneous estimability can be characterized by a sampling-based criterion. Also, we describe a canonical estimator for this class of problems. This canonical estimator has a unique form: it uses part of the samples to select a finite subset of hypotheses that approximates the class of candidate hypotheses, and then it uses the rest of the samples to estimate the error of each hypothesis in the subset. Finally, we show that a learning procedure based on the canonical estimator will work in every case where empirical error minimization does.
Neural networks with nonlinear synapses and a static noise.

The theory of neural networks is extended to include a static noise as well as nonlinear updating of synapses by learning. The noise appears either in the form of spin-glass interactions, which are independent of the learning process, or as a random decaying of synapses. In an unsaturated network, the nonlinear learning algorithms may modify the energy surface and lead to interesting new computational capabilities. Close to saturation, they act as an additional source of a static noise. The effect of the noise on memory storage is calculated.
Robust image de-blurring with inaccurate blur kernels

Most existing non-blind image deblurring methods assume that the blur kernel is free of error. However, it is often unavoidable in practice that the input blur kernel is erroneous to some extent. Sometimes the error could be severe, e.g, for images degraded by non-uniform motion blurring. When an inaccurate blur kernel is used as the input, significant distortions will appear in the image recovered by existing methods. In this paper, we present a novel convex minimization model that explicitly takes account of errors in the blur kernel. The resulting minimization problem can be be efficiently solved by the so-called APG method. Also, a new boundary extension scheme is incorporated in the proposed model to further improve the results. The experiments on both synthesized and real images showed the efficiency and robustness of our algorithm to both the image noise and the model error in blur kernel.
State and Output Feedback Nonlinear Model Predictive Control: An Overview

The purpose of this paper is twofold. In the first part, we give a review on the current state of nonlinear model predictive control (NMPC). After a brief presentation of the basic principle of predictive control we outline some of the theoretical, computational, and implementational aspects of this control strategy. Most of the theoretical developments in the area of NMPC are based on the assumption that the full state is available for measurement, an assumption that does not hold in the typical practical case. Thus, in the second part of this paper the focus on the output feedback problem in NMPC. After a brief overview on existing output feedback NMPC approaches we derive conditions that guarantee stability of the closed-loop if an NMPC state feedback controller is used together with a full state observer for the recovery of the system state.
Automated tru-cut imaging-guided core needle biopsy of canine orbital neoplasia. A prospective feasibility study

The purpose of this study was to evaluate the diagnostic value of imaging-guided core needle biopsy for canine orbital mass diagnosis. A second excisional biopsy obtained during surgery or necropsy was used as the reference standard. A prospective feasibility study was conducted in 23 canine orbital masses at a single centre. A complete ophthalmic examination was always followed by orbital ultrasound and computed tomography (CT) examination of the head. All masses were sampled with the patient still on the CT table using ultrasound (US) guided automatic tru-cut device. The most suitable sampling approach to the orbit was chosen each time based on the CT image analysis. One of the following different approaches was used: trans-orbital, trans-conjunctival or trans-masseteric. In all cases, the imaging-guided biopsy provided a sufficient amount of tissue for the histopathological diagnosis, which concurred with the biopsies obtained using the excisional technique. CT examination was essential for morphological diagnosis and provided detailed topographic information that allowed us to choose the safest orbital approach for the biopsy. US guided automatic tru-cut biopsy based on CT images, performed with patient still on the CT table, resulted in a minimally invasive, relatively easy, and accurate diagnostic procedure in dogs with orbital masses.
A reconfigurable VLSI learning array

We present a reconfigurable array for low-power feedforward neural networks in analog VLSI. This architecture implements a flexible computational model with coarse-grained reconfigurability, and features high computational density for a broad range of applications. Our prototype of the array, fabricated in a 0.35/spl mu/m process, consumes 0.25mm/sup 2/ of area and dissipates 150/spl mu/W of power on a 5V supply. In this paper, we discuss the circuits and architecture of our system, as well as experimental results.
Interpreting instruction sequences in spatial language discourse with pragmatics towards natural human-robot interaction

We present a methodology for enabling service robots to interpret spatial language instruction sequences expressed through natural language discourse from non-expert users. As part of our approach, we propose a novel probabilistic algorithm for the automatic extraction of contextually and semantically valid instruction sequences from unconstrained spatial language discourse. Additionally, we present the design and implementation details of a procedure for reference resolution of anaphoric expressions encountered within the user discourse. Towards application of our human-robot interaction (HRI) methodology on robot platforms in practice with end users, we discuss a generalized procedure for transfer to physical systems and provide solutions for key pragmatic considerations including the generation of safe robot execution paths for both the robot and people in the environment. The paper concludes with an evaluation of our spatial language-based HRI framework implemented on a PR2 robot to demonstrate the generalizability and usefulness of our approach in real world applications.
An Improved Call Admission Control Scheme Based on Reinforcement Learning for Multimedia Wireless Networks

This paper presents an improved call admission control scheme to optimize the network operators’ revenue while guarantying the quality of service (QoS) to the mobile terminals. The problem of call admission control (CAC) is modeled as a Semi-Markov decision process (SMDP), and the SMDP is solved by a reinforcement learning (RL) algorithm known as Q-learning. In the Q-learning algorithm, the reward functions for the acceptance and the rejection of new calls for each class of service not only depend on used bandwidth, new call arrival rate, average service time and price, but also the ratio of new call load and the handoff call load and the requested bandwidth of each class of traffic. The CAC scheme would be well performed through the reward functions. Simulations results show that the CAC scheme can obtain high revenue while greatly reducing handoff call dropping probability when the traffic loads are heavy.
Ontogeny of Modulatory Inputs to Motor Networks: Early Established Projection and Progressive Neurotransmitter Acquisition

Modulatory information plays a key role in the expression and the ontogeny of motor networks. Many developmental studies suggest that the acquisition of adult properties by immature networks involves their progressive innervation by modulatory input neurons. Using the stomatogastric nervous system of the European lobsterHomarus gammarus, we show that contrary to this assumption, the known population of projection neurons to motor networks, as revealed by retrograde dye migration, is established early in embryonic development. Moreover, these neurons display a large heterogeneity in the chronology of acquisition of their full adult neurotransmitter phenotype. We performed retrograde dye migration to compare the neuronal population projecting to motor networks located in the stomatogastric ganglion in the embryo and adult. We show that this neuronal population is quantitatively established at developmental stage 65%, and each identified projection neuron displays the same axon projection pattern in the adult and the embryo. We then combined retrograde dye migration with FLRFamide-like, histamine, and GABA immunocytochemistry to characterize the chronology of neurotransmitter expression in individual identified projection neurons. We show that this early established population of projection neurons gradually acquires its neurotransmitter phenotype complement. This study indicates that (1) the basic architecture of the known population of projection inputs to a target network is established early in development and (2) ontogenetic plasticity may depend on changes in neurotransmitter phenotype expression within preexisting neurons rather than in the addition of new projection neurons or fibers.
Highly similar structural frames link the template tunnel and NTP entry tunnel to the exterior surface in RNA-dependent RNA polymerases

RNA-dependent RNA polymerase (RdRp) is essential to viral replication and is therefore one of the primary targets of countermeasures against these dangerous infectious agents. Development of broad-spectrum therapeutics targeting polymerases has been hampered by the extreme sequence variability of these sequences. RdRps range in length from 400–800 residues, yet contain only ∼20 residues that are conserved in most species. In this study, we made structure-based comparisons that are independent of sequence composition using a recently developed algorithm. We identified residue-to-residue correspondences of multiple protein structures and created (two-dimensional) structure-based alignment maps of 37 polymerase structures that provide both sequence and structure details. Using these maps, we determined that ∼75% of each polymerase species consists of seven protein segments, each of which has high structural similarity to segments in other species, though they are widely divergent in sequence composition and order. We define each of these segments as a ‘homomorph’, and each includes (though most are much larger than) the well-known conserved polymerase motifs. All homomorphs contact the template tunnel or nucleoside triphosphate (NTP) entry tunnel and the exterior of the protein, suggesting they constitute a structural and functional skeleton common among the polymerases.
Matrix metalloproteinases: structures, evolution, and diversification

A comprehensive sequence alignment of 64 members of the family of matrix metalloproteinases (MMPs) for the entire sequences, and subsequently the catalytic and the hemopexin‐like domains, have been performed. The 64 MMPs were selected from plants, invertebrates, and vertebrates. The analyses disclosed that as many as 23 distinct subfamilies of these proteins are known to exist. Information from the sequence alignments was correlated with structures, both crystallographic as well as computational, of the catalytic domains for the 23 representative members of the MMP family. A survey of the metal binding sites and two loops containing variable sequences of amino acids, which are important for substrate interactions, are discussed. The collective data support the proposal that the assembly of the domains into multidomain enzymes was likely to be an early evolutionary event. This was followed by diversification, perhaps in parallel among the MMPs, in a subsequent evolutionary time scale. Analysis indicates that a retrograde structure simplification may have accounted for the evolution of MMPs with simple domain constituents, such as matrilysin, from the larger and more elaborate enzymes. —Massova, I. , Kotra, L. P., Fridman, R. , Mobashery, S. Matrix metalloproteinases: structures, evolution, and diversification. FASEB J. 12, 1075–1095 (1998)