Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of features discretization on accuracy of random forest classifier for web user identification

Web user identification based on linguistic or stylometric features helps to solve several tasks in computer forensics and cybersecurity, and can be used to prevent and investigate high-tech crimes and crimes where computer is used as a tool. In this paper we present research results on influence of features discretization on accuracy of Random Forest classifier. To evaluate the influence were carried out series of experiments on text corpus, contains Russian online texts of different genres and topics. Was used data sets with various level of class imbalance and amount of training texts per user. The experiments showed that the discretization of features improves the accuracy of identification for all data sets. We obtained positive results for extremely low amount of online messages per one user, and for maximum imbalance level.
Neural Biomimetic Materials for Investigating Cell Behaviors in 3D

ii Dedication . v Acknowledgments. vi Vita . ix List of Tables . xxi List of Figures . xxiii Chapter 1: Introduction . 1 1.1 CNS disorders resulting from loss of neuronal functions . 3 1.2 CNS disorders resulting from cancer . 7 1.3 Dissertation overview . 14 Chapter 2: Adhesion Molecule-Modified Biomaterials for Neural Engineering . 20 2.
A context-aware meeting alert using semantic web and rule technology

This paper describes a context-aware meeting alert, which aims at alerting the user in time about upcoming scheduled calendar events, considering the state of the user's context. This application integrates semantic web technology in RDF (for representing calendars), semantic web rules (for making a context dependent decision about the precise timing of the alert), and mobile technology for location sensing and message delivery. The outlined work is an experiment seeking to demonstrate the feasibility of applying efficient, semantically sound semantic web reasoning to mobile applications.
September 21, 2004 ACTIVITY RATES WITH VERY HEAVY TAILS

Consider a data network model in which sources begin to transmit at renewal time points {Sn}. Transmissions proceed for random durations of time {Tn} and transmissions are assumed to proceed at fixed rate unity. We study M(t), the number of active sources at time t, a process we term the activity rate process, since M(t) gives the overall input rate into the network at time t. Under a variety of heavy-tailed assumptions on the inter-renewal times and the duration times, we can give results on asymptotic behavior of M(t) and the cumulative input process A(t) = R t 0 M(s) ds. 1. The model, notation, preliminary results. Consider an ordinary renewal process {Sn, n ≥ 0} such that S0 = 0, Sn = n ∑
One-loop quantum corrections to the thermodynamics of charged black holes.

Quantum corrections are studied for a charged black hole in a two-dimensional model obtained by spherisymmetric reduction of the 4D Einstein-Maxwell theory. The classical (tree-level) thermodynamics is re-formulated in the framework of the off-shell approach, considering systems at arbitrary temperature. This implies a conical singularity at the horizon and modifies the gravitational action by terms defined on the horizon. A consistent variational procedure for the action functional is formulated. It is shown that the free energy reaches an extremum on the regular manifold with $T=T_H$. The one-loop contribution to the action in the Liouville-Polyakov form is re-examined. All the boundary terms are taken into account and the dependence on the state of the quantum field is established. The modification of the Liouville-Polyakov term for a 2D space with a conical defect is derived. The backreaction of the Hawking radiation on the geometry is studied and the quantum-corrected black hole metric is calculated perturbatively. Within the off-shell approach the one-loop thermodynamical quantities, energy and entropy, are found. They are shown to contain a part due to hot gas surrounding he black hole and a part due to the hole itself. It is noted that the contribution of the hot gas can be eliminated by appropriate choice of the (generally, non-flat) reference geometry. The deviation of the {\it `` entropy - horizon area''} relation for the quantum-corrected black hole from the classical law is discovered and possible physical consequences are discussed.
Modularity of Plant Metabolic Gene Clusters: A Trio of Linked Genes That Are Collectively Required for Acylation of Triterpenes in Oat[W][OA]

This study reports on an anthranilate N-methyltransferase, MT1, required for synthesis of antimicrobial triterpenoid defense compounds (avenacins) in oat and, through the characterization of MT1 and the products of other genes within the avenacin metabolic gene cluster, presents a model of the subcellular organization of triterpenoid biosynthesis. Operon-like gene clusters are an emerging phenomenon in the field of plant natural products. The genes encoding some of the best-characterized plant secondary metabolite biosynthetic pathways are scattered across plant genomes. However, an increasing number of gene clusters encoding the synthesis of diverse natural products have recently been reported in plant genomes. These clusters have arisen through the neo-functionalization and relocation of existing genes within the genome, and not by horizontal gene transfer from microbes. The reasons for clustering are not yet clear, although this form of gene organization is likely to facilitate co-inheritance and co-regulation. Oats (Avena spp) synthesize antimicrobial triterpenoids (avenacins) that provide protection against disease. The synthesis of these compounds is encoded by a gene cluster. Here we show that a module of three adjacent genes within the wider biosynthetic gene cluster is required for avenacin acylation. Through the characterization of these genes and their encoded proteins we present a model of the subcellular organization of triterpenoid biosynthesis.
Mechanical properties of natural fibre polymer composites

Abstract Extensive efforts have been made in the last decade for the development of natural fibre composites. This development paved the way for engineers and researchers to come up with natural fibre composites (NFCs) that exhibit better mechanical properties. The present review is based on the mechanical properties of jute, abaca, coconut, kenaf, sisal, and bamboo fibre-reinforced composites. Before selecting any NFC for a particular application, it becomes necessary to understand its compatibility for the same, which can be decided by knowing its mechanical properties such as tensile, flexural, and impact strengths. This review paper emphasises on the factors influencing the mechanical properties of NFCs like the type of matrix and fibre, interfacial adhesion, and compatibility between matrix and fibre. Efforts are also made to unveil the research gaps from the past literatures, as a result of which it is inferred that there is very limited work published in the field of vibration incorporating potential fillers such as red mud and fly ash with NFCs.
Automated digital mammogram segmentation using Dispersed Region Growing and Sliding Window Algorithm

Early diagnosis of breast cancer can improve the survival rate by detecting cancer at an early stage. Breast region segmentation is an essential step in the analysis of digital mammograms. Accurate image segmentation leads to better detection of cancer. It aims at separating out Region of Interest (ROI) from rest of the image. The procedure begins with removal of labels, annotations and tags from the mammographic image using morphological opening method. Sliding Window Algorithm (SWA) is used for removal of pectoral muscle from mammograms which is necessary as the intensity values of pectoral muscles are similar to that of ROI which makes it difficult to separate out. After removing the pectoral muscle, Dispersed Region Growing Algorithm (DRGA) is used for segmentation of mammogram which disperses seeds in different regions instead of a single bright region. To demonstrate the validity of our segmentation method, 322 mammographic images from Mammographic Image Analysis Society (MIAS) database are used. The dataset contains mediolateral oblique (MLO) view of mammograms. Experimental results on MIAS dataset show the effectiveness of our proposed method.
A k-nearest neighbor locally weighted regression method for short-term traffic flow forecasting

In this paper, a k-nearest neighbor locally weighted regression method (k-LWR) is proposed to forecast the short-term traffic flow. Inspired by k-nearest neighbor (k-NN) method, the traffic flows which have the same clock time with the current traffic flow are viewed as neighbors. The traffic flows which have the same clock time with the predicted traffic flow are viewed as the outputs of the neighbors. The neighbors most similar to the current traffic flow are viewed as nearest neighbors. It is observed that each nearest neighbor has different similarity with the current traffic flow, and the similarity is relevant to the contribution of the nearest neighbor's output to predicted traffic flow. The greater the similarity is, the greater the contribution is. These contributions of the nearest neighbors' outputs are obtained by the locally weighted regression (LWR) method. In this way, k-LWR uses less data, but uses it more effectively. We use the root mean square error (RMSE) between the actual traffic flow and the predicted traffic flow as the measurement. The proposed method is tested on the actual data from Xingye intersection and Feihu intersection in Jiangsu Province in China. The experimental results show that k-LWR has 20% and 24% improvement over the pattern recognition algorithm (PRA), 26% and 30% improvement over k-NN, for the two intersections, respectively.
Not so fast: Domain-general factors can account for selective deficits in grammatical processing

Normals display selective deficits in morphology and syntax under adverse processing conditions. Digit loads do not impair processing of passives and object relatives but do impair processing of grammatical morphemes. Perceptual degradation and temporal compression selectively impair several aspects of grammar, including passives and object relatives. Hence we replicate Caplan & Waters's specific findings but reach opposite conclusions, based on wider evidence.
Electromagnetic Field Analysis by using Parallel Processing Based on OpenMP

Recently, numerical analysis of electromagnetic field can be performed on high performance PCs. However, improvement of CPU operation frequency is becoming saturate. In order to speed up the calculation, multi-core CPU system is paid attention and it has been used in high performance PC. In this paper, a parallelization using multi-threads on SMP (symmetric multiple processor) for a finite element analysis using hexahedral edge element is investigated
First and Last Triggering Event Approaches for Replacement With Minimal Repairs

To make effective use of a running system, this paper proposes that, when replacement times could be scheduled at a planned time T of operation, and at a number N of minimal repairs, the newly proposed approach of whichever occurs last should be employed into optimizations for policy consideration. The replacement policy with the classical approach of whichever occurs first is also used to make comparison with the approach of whichever occurs last. Further, using the overtime technique, a replacement scheduled at time T in this paper is modified to be done at the first failure after T has arrived, to avoid probable interruptions for running jobs. That is, the system is replaced at failure N before time T, or at the first failure after T has arrived, whichever occurs first, and last, respectively. The policies acting on the approaches of first and last with minimal repairs are analyzed in detail, and their expected cost rates are formulated. Optimal solutions for separate and bivariate T and N are obtained and compared analytically.
Invariant target detection of MIMO radar with unknown parameters

In this paper, three target detectors Uniformly Most Powerful Invariant (UMPI), Generalized Likelihood Ratio Test (GLRT) and a Separating Function Estimation Test (SFET) based on the scale group of transformations are proposed and applied to Widely Separated Antennas Multiple-Input Multiple-Output (WSA MIMO) radars. It is shown that for this problem the UMPI test depends on the scatter to noise ratio, hence the UMPI test provides the upper performance bound for all invariant tests. To derive the asymptotically optimal SFET the Maximum Likelihood Estimation (MLE) of unknown parameters are replaced into the induced maximal invariant, which is equal to the scatter to noise ratio. The MLE of the scatter to noise ratio does not have a closed form, hence we propose an iterative estimator to calculate the SFET statistic. Similarly an iterative GLRT is also proposed for this problem. The simulation results show that the performance of SFET tends to the optimal invariant bound by increasing the scatter to noise ratio.
Secrecy Outage Analysis of Multiuser Downlink Wiretap Networks With SECps Scheduling in Nakagami- $m$ channel

In this letter, we investigate the security of multiuser downlink wiretap networks over Nakagami-m channel, where a base station (BS) serves NB legitimate users and is overheard by NE eavesdroppers. Specifically, to achieve a good tradeoff between the secrecy performance and number of user estimations, we introduce a threshold-based scheduling algorithm, termed switch-and-examine combining with post-examining selection (SECps). Moreover, we consider the practical scenario, where the channel state information (CSI) of the eavesdropper's channel is unavailable at the BS. Building on this, new exact and asymptotic closed-form expressions of the secrecy outage probability are derived for the considered network, which are valid for general systems with an arbitrary number of legitimate users, number of eavesdroppers, channel fading severity, and switching threshold. The findings suggest that with the switching threshold being carefully chosen, the considered SECps scheme achieves a comparable secrecy outage performance with regard to selection combining (SC) scheme while maintaining a lower number of user examinations.
Improved sensitivity of the rapid screen of mild traumatic brain injury

This study aimed to investigate the acute effects of mild traumatic brain injury (mTBI) in an emergency department sample. A total of 246 (186 male, 60 female) cases of mTBI and 102 (65 male and 37 female) cases of orthopedic injuries were tested within 24 hours of injury. Mild TBI patients performed more poorly on all subtests of the Rapid Screen of Concussion (RSC) and completed fewer symbols on Digit Symbol than did orthopedic controls. RSC scores predicted group membership better than chance, and Digit Symbol scores contributed significantly to predicting group membership over and above the contribution of the RSC, resulting in 70.4% sensitivity and 74% specificity for the extended protocol. The results of this study indicate that learning and memory, orientation, and speed of information processing are impaired immediately following mTBI. Furthermore, a brief battery of tests that include word recall, orientation, and the Digit Symbol Substitution Test could assess the severity of dysfunction following mTBI, and assist in clinical decision making regarding discharge, return to routine activities, and management of the effects of injury.
Ageing and yield behaviour in model soft colloidal glasses

We use multi-arm star polymers as model soft colloids with tuneable interactions and explore their behaviour in the glassy state. In particular, we perform a systematic rheological study with a well-defined protocol and address aspects of ageing and shear melting of star glasses. Ageing proceeds in two distinct steps: a fast step of O(103 s) and a slow step of O(104 s). We focus on creep and recovery tests, which reveal a rich, albeit complex response. Although the waiting time, the time between pre-shear (rejuvenation) of the glassy sample and measurement, affects the material’s response, it does not play the same role as in other soft glasses. For stresses below the yield value, the creep curve is divided into three regimes with increasing time: viscoplastic, intermediate steady flow (associated with the first ageing step) and long-time evolving elastic solid. This behaviour reflects the interplay between ageing and shear rejuvenation. The yield behaviour, as investigated with the stress-dependent recoverable strain, indicates a highly nonlinear elastic response intermediate between a low-stress Hookean solid and a high-stress viscoelastic liquid, and exemplifies the distinct characteristics of this class of hairy colloids. It appears that a phenomenological classification of different colloidal glasses based on yielding performance may be possible.
ATC Enhancement with Facts Devices using Quantum Inspired PSO

Under new de-regulated environment an open access to transmission system seems to be desired. Determination and enhancement of available transfer capability (ATC) are important issues in deregulated operation of power systems. This paper focuses on the best location and optimal allocation of FACTS devices to improve maximum available transfer capacity (ATC). ATC is computed using repeated power flow method considering voltage profile. Quantum inspired PSO is used for optimization of FACTs requirement for maximizing ATC. The suggested methodology is tested on IEEE 30-bus system.
Stochastic predictive control for lane keeping assistance systems using a linear time-varying model

This paper presents a new controller for prevention of unintended roadway departures using model predictive control (MPC). The uncertainty with the driver's behavior is taken into account as the Gaussian disturbance. Correspondingly, we impose a lower bound on the probability of the vehicle remaining within the lane. Using current information of the vehicle and predicted steering of the driver, a linear time-varying (LTV) model of the human-vehicle system is obtained on-line through a successive linearization approach. The probabilistic safety constraints are converted into tightened constraints on the states of the LTV model by computing the evolution of the disturbance. Consequently, the predictive control problem is formulated as a quadratic program. The controller corrects the driver's steering, wherever there is a risk of unintended roadway departure, to keep the vehicle within the lane. Simulations and experiments implemented on a passenger vehicle were performed. The results indicate that the proposed controller improves safety performance compared to previous works.
A Persian Treebank with Stanford Typed Dependencies

We present the Uppsala Persian Dependency Treebank (UPDT) with a syntactic annotation scheme based on Stanford Typed Dependencies. The treebank consists of 6,000 sentences and 151,671 tokens with an average sentence length of 25 words. The data is from different genres, including newspaper articles and fiction, as well as technical descriptions and texts about culture and art, taken from the open source Uppsala Persian Corpus (UPC). The syntactic annotation scheme is extended for Persian to include all syntactic relations that could not be covered by the primary scheme developed for English. In addition, we present open source tools for automatic analysis of Persian containing a text normalizer, a sentence segmenter and tokenizer, a part-of-speech tagger, and a parser. The treebank and the parser have been developed simultaneously in a bootstrapping procedure. The result of a parsing experiment shows an overall labeled attachment score of 82.05% and an unlabeled attachment score of 85.29%. The treebank is freely available as an open source resource.
A Web-based Demonstrator of a Multi-lingual Phrase-based Translation System

This paper describes a multi-lingual phrase-based Statistical Machine Translation system accessible by means of a Web page. The user can issue translation requests from Arabic, Chinese or Spanish into English. The same phrase-based statistical technology is employed to realize the three supported language-pairs. New language-pairs can be easily added to the demonstrator. The Web-based interface allows the use of the translation system to any computer connected to the Internet.
Development of TiC Based Wear Resistance Composite Coating on AISI 304 Steel by Pulsed Laser and TIG Cladding Process

TiC is a preferred coating material for the components working under the extreme tribological condition, due to its high hardness, high melting temperature, and low density. In order to improve the hardness and wear resistance properties of stainless steel surface, TiC reinforced coating has been produced on AISI 304 stainless steel using pulsed Nd:YAG laser and Tungsten Inert Gas (TIG) cladding process. Further, to enhance the efficiency of TIG cladding process as well as to amend the tribological properties of TiC based coating, Ni (for better bonding) and CaF2 (as a solid lubricant) have been incorporated in various phases of experiments. The produced composite coatings are then analyzed by using SEM, FESEM and XRD for microstructural evaluation and phase identification. Micro-hardness value of the produced TiC, TiC-Ni, and TiC-Ni-CaF2 coating has been measured by Vickers micro-indentation tester and the tribological behavior of the produced coatings have been assessed by sliding abrasive wear test through pin-on-disc wear testing machine. The experimental analysis revealed that TiC reinforced composite coating produced by TIG heat source improved the micro-hardness and abrasive wear resistance significantly. Further, with the incorporation of Ni, bonding between the substrate and TiC reinforcement enhances, and consequently augmented the wear resistance of the coating. In addition, by employing CaF2 with TiC and Ni, the coefficient of friction (COF) of the coating diminishes, which found become beneficial for the performance of the coating.
Experimental Swap of Anopheles gambiae's Assortative Mating Preferences Demonstrates Key Role of X-Chromosome Divergence Island in Incipient Sympatric Speciation

Although many theoretical models of sympatric speciation propose that genes responsible for assortative mating amongst incipient species should be associated with genomic regions protected from recombination, there are few data to support this theory. The malaria mosquito, Anopheles gambiae, is known for its sympatric cryptic species maintained by pre-mating reproductive isolation and its putative genomic islands of speciation, and is therefore an ideal model system for studying the genomic signature associated with incipient sympatric speciation. Here we selectively introgressed the island of divergence located in the pericentric region of the X chromosome of An. gambiae s.s. into its sister taxon An. coluzzii through 5 generations of backcrossing followed by two generations of crosses within the introgressed strains that resulted in An. coluzzii-like recombinant strains fixed for the M and S marker in the X chromosome island. The mating preference of recombinant strains was then tested by giving virgin recombinant individuals a choice of mates with X-islands matching and non-matching their own island type. We show through genetic analyses of transferred sperm that recombinant females consistently mated with matching island-type males thereby associating assortative mating genes with the X-island of divergence. Furthermore, full-genome sequencing confirmed that protein-coding differences between recombinant strains were limited to the experimentally swapped pericentromeric region. Finally, targeted-genome comparisons showed that a number of these unique differences were conserved in sympatric field populations, thereby revealing candidate speciation genes. The functional demonstration of a close association between speciation genes and the X-island of differentiation lends unprecedented support to island-of-speciation models of sympatric speciation facilitated by pericentric recombination suppression.