Miracle-dz/UniFAR-FTUs huggingface dataset:
Lexicon and Grammar in Probabilistic Tagging of Written English

The paper describes the development of software for automatic grammatical analysis of unrestricted, unedited English text at the Unit for Computer Research on the English Language (UCREL) at the University of Lancaster. The work is currently funded by IBM and carried out in collaboration with colleagues at IBM UK (Winchester) and IBM Yorktown Heights. The paper will focus on the lexicon component of the word tagging system, the UCREL grammar, the databanks of parsed sentences, and the tools that have been written to support development of these components. This work has applications to speech technology, spelling correction, and other areas of natural language processing. Currently, our goal is to provide a language model using transition statistics to disambiguate alternative parses for a speech recognition device.
Suux Tree Automata in State Space Search

An on{line learning algorithm for pruning state space search is described in this paper. The algorithm is based on a nite state machine which is both created and used in the search. The pruning technique is necessary when memory resources in searching huge problem spaces are restricted. A duplicate sequence is a generating path in the search tree that has a counterpart with smaller weight. The automaton provides the dictionary operations Insert and Delete for the duplicate sequences found in the search and Search for pruning the search tree. The underlying data structure is a multi suux tree. Given that the alphabet of state transitions is bounded by a constant an optimal worst case bound of O(jmj) for both insertion and deletion of a duplicate sequence m 2 is achieved. Using the structure as a nite state machine we can incrementally accept a given sequence x in time O(jxj).
CLINICALLY PRACTICAL APPLICATIONS OF PATTERN RECOGNITION FOR MYOELECTRIC PROSTHESES

The promise of pattern recognition for improved control of upper-extremity powered prostheses has existed for a long time. During the years of offline research and algorithm development, very little experience has been gained with real-time use in clinical and chronic settings. Our group, having the benefit of working with subjects who have undergone targeted muscle reinnervation (TMR) surgery, is at the forefront of real-world application of pattern recognition for upper extremity amputees. Based on our experiences, we highlight a progression of myoelectric control schemes from conventional control to enhanced pattern recognition control, stressing the application of simple pattern recognition schemes to replace more conventional control. These clinically practical pattern recognition systems incorporate a realistic number of electrodes and the ability to control available prosthetic components. Our experience suggests how the impending, and initial deployment of pattern recognition-controlled prostheses for daily use can be more approachable than what is depicted in high-dimension studies common in the literature today.
ANALYSIS OF NEAR-FIELD WIRELESS POWER TRANSMISSION FOR FRACTIONATED SPACECRAFT APPLICATIONS

The modular design of a fractionated spacecraft is intended to avoid drawbacks inherent to monolithic designs such as subsystem failure, expensive designs, underestimated costs, expensive launches and over-complex systems. Since the power systems represent one of the main mass and volume drivers of spacecraft, one of the key technologies required for truly fractionated architectures is the ability to distribute power wirelessly between spacecraft depending on the respective power needs over time. Investigations on the subsystem aspects of radiative wireless power transmission have been published, including the use of both, laser and microwave frequencies. Near-field wireless power transmission has so far been quickly discarded, mainly due to its apparent limited range. The present paper intends to contribute to this discussion by investigating a method of increasing the range near-field power transmission, which might be sufficient for its use within fractionated spacecraft applications.
Estimating the frequencies of harmonics in multiplicative and additive noise based on subspace rotational invariance

The frequency estimation of harmonics in the presence of nonzero mean multiplicative and additive noise is considered in this paper. We first define a generalized covariance of harmonics in multiplicative and additive noise, then, we construct a Toeplitz matrix using the defined generalized covariance. Finally, we estimate the frequencies form the constructed matrix via the subspace rotational invariance technique. The proposed method has high-resolution and no assumptions imposed on the color or the distribution of the noises. Simulation results demonstrate the effectiveness of the proposed method.
An Approach to Ballet Dance Training through MS Kinect and Visualization in a CAVE Virtual Reality Environment

This article proposes a novel framework for the real-time capture, assessment, and visualization of ballet dance movements as performed by a student in an instructional, virtual reality (VR) setting. The acquisition of human movement data is facilitated by skeletal joint tracking captured using the popular Microsoft (MS) Kinect camera system, while instruction and performance evaluation are provided in the form of 3D visualizations and feedback through a CAVE virtual environment, in which the student is fully immersed. The proposed framework is based on the unsupervised parsing of ballet dance movement into a structured posture space using the spherical self-organizing map (SSOM). A unique feature descriptor is proposed to more appropriately reflect the subtleties of ballet dance movements, which are represented as gesture trajectories through posture space on the SSOM. This recognition subsystem is used to identify the category of movement the student is attempting when prompted (by a virtual instructor) to perform a particular dance sequence. The dance sequence is then segmented and cross-referenced against a library of gestural components performed by the teacher. This facilitates alignment and score-based assessment of individual movements within the context of the dance sequence. An immersive interface enables the student to review his or her performance from a number of vantage points, each providing a unique perspective and spatial context suggestive of how the student might make improvements in training. An evaluation of the recognition and virtual feedback systems is presented.
New Principles in Algorithm Design for Problems of Face Recognition

This chapter is devoted to two main problems in pattern recognition. First problem concerns the methodology of classification quality and stability estimation that is also known as classification reliability estimation. We consider general problem statement in classification algorithms design, classification reliability estimation and the modern methods solution of the problem. On the other hand we propose our methods for solution of such kind of a problem. In general this could be made by using of different kind of indicators of classification (classifier) quality and stability. All this should summarize everything made before with our latest results of solution of the problem. Second part of the chapter is devoted to new approach that gives the possibility to solve the problem of classifier design that is not sensitive to the learning set but belongs to some kind of learning algorithms. Let us consider recognition process, using the next main algorithms, as some parts of the some complicated recognition system: algorithm for feature generating, algorithms for feature selection and classification algorithms realizing procedure of decision making. It is really important to have good algorithms for feature generating and selection. Methods for feature generating and selection are developed a lot for many objects to be recognized. For facial images the most popular algorithms use 3D graph models, morphological models, the selection some geometrical features using special nets, etc. From other hand very popular algorithms for feature generating and selection are those which use Principle Component Analysis (PCA) or Independent Component Analysis (ICA). PCA and ICA are good enough for a number of practical cases. However there are a lot of different deficiencies in classifier building. For classifiers using learning the most essential gap is that all such classifiers can work pretty well on learning stage and really bad for some test cases. Also they can work well enough if classes are linearly separated e.g. Support Vector Machines (SVM) in linear case. For non-linear case they have a number of disadvantages. That is why it is important to develop some approaches for algorithms building that are not sensitive for the kind of sample or complexity in classification task. All classification algorithms built for the present could be divided almost into 5 groups: algorithms built on statistical principles, algorithms, built on the basis of potential functions and non-parametrical estimation, algorithms, using similarity functions (all kinds of metrical classifiers like 1NN and kNN classifiers) algorithms, using logical principles like decision lists, trees, etc, hierarchical and combined algorithms. A lot of recognition systems use a number of algorithms or algorithm compositions. For their optimization and tuning
Support Vector Machines as Probabilistic Models

We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic models. This model class can be viewed as a reparametrization of the SVM in a similar vein to the ? -SVM reparametrizing the classical (C-)SVM. It is not discriminative, but has a non-uniform marginal. We illustrate the benefits of this new view by re-deriving and re-investigating two established SVM-related algorithms.
Traffic light based time stable geocast (T-TSG) routing for urban VANETs

Vehicular Ad Hoc Networks is a self-organizing, distributed communication network formed by highly Mobile Vehicles. This type of networks is developed as part of Intelligent Transportation Systems (ITS) to bring significant improvement to the transportation systems. One of the main goal of ITS, is to increase safety on road and reduce traffic congestion. Safety application requires messages to be sent to all nodes which belong to a particular geographical region. This message must be available to all the vehicles which enter the Geographical Region within a certain Time Period. Also, there are wide varieties of scenarios in VANETs to communicate. In urban environment, there are many streets, intersections, avenues etc. Hence, Driver has many options to reach his destination. In Highway environment, vehicles stay in the same road as there are only few entrances and exits. From a routing perspective, there are different options to forward information in an urban environment depending upon the behavior of traffic lights whereas in highway, most of the same set of vehicles may be used to forward information. In this paper, we have proposed a novel time stable geocast routing protocol nameed as traffic light based time stable geocast (T-TSG) routing protocol for informing vehicles after an accident in urban vehicular environment. T-TSG is a three phase routing approach based on traffic light behavior. It has better message delivery rate, negligible network load for life time management and lower end-to-end delay performance under simulated urban environment.
Science opportunities with the near-IR camera (NIRCam) on the James Webb Space Telescope (JWST)

The Near-Infrared Camera (NIRCam) on the James Webb Space Telescope (JWST) offers revolutionary gains in sensitivity throughout the 1-5 μm region. NIRCam will enable great advances in all areas of astrophysics, from the composition of objects in our own Kuiper Belt and the physical properties of planets orbiting nearby stars to the formation of stars and the detection of the youngest galaxies in the Universe. NIRCam also plays an important role in initial alignment of JWST and the long term maintenance of its image quality. NIRCam is presently undergoing instrument Integration and Test in preparation for delivery to the JWST project. Key near-term milestones include the completion of cryogenic testing of the entire instrument; demonstration of scientific and wavefront sensing performance requirements; testing of replacement H2RG detectors arrays; and an analysis of coronagraphic performance in light of measured telescope wavefront characteristics. This paper summarizes the performance of NIRCam, the scientific and education/outreach goals of the science team, and some results of the on-going testing program.
Looking at Joint Custody Through the Language and Attitudes of Attorneys

The workings of the judicial system influence the attitudes and actions of attorneys and, in turn, their attitudes and actions affect the courts. Through their experiences with the courts, lawyers develop perceptions toward policy embedded in law and toward the court system that implements the law. These perceptions may in turn influence the construction of new policies. This article examines the connections between the attitudes of family law attorneys toward the process of divorce and their construction of the “custody problem” in the debate over joint custody. It concludes that, because matrimonial lawyers are less likely to engage in “zealous advocacy” for their clients and more likely to seek “fair solutions” than are other types of attorneys, their framing of the “custody problem” (whether for or against joint custody) focused on the mental health of the parties and the just and fair functioning of the court system.
Characterization of avian H5N1 influenza viruses from poultry in Hong Kong.

The transmission of avian H5N1 influenza viruses to 18 humans in Hong Kong in 1997 with six deaths established that avian influenza viruses can transmit to and cause lethal infection in humans. This report characterizes the antigenic and biological properties of the H5N1 influenza viruses isolated from chickens, ducks, and geese from farms and poultry markets in Hong Kong during 1997 and compares them with those of virus isolated from the index human case. Each of the H5N1 viruses from Hong Kong poultry markets that were tested were lethal in chickens, possessed polybasic amino acids at the carboxy-terminus of HA1, and by definition were highly pathogenic in poultry. The available nonpathogenic H5 influenza viruses and the pathogenic H5N1 virus from Hong Kong were analyzed with monoclonal antibodies prepared to A/chicken/Pennsylvania/1370/83 (H5N2). The analysis revealed limited antigenic drift in 15 years and established that monoclonal antibodies are useful reagents for identification and antigenic analysis of avian strains that may transmit to humans in the future. One of the monoclonal antibodies permitted separation of the H5N1 influenza viruses from poultry into two groups that correlated with the presence or absence of a carbohydrate at residue 158 adjacent to the receptor binding site on HA. The H5N1 viruses examined replicated in geese, pigs, rats, and mice, but to only a very limited extent in ducks. It is noteworthy that all infected geese shed virus and that the H5N1 viruses caused disease signs and death in a portion (3 of 16) of the geese, with evidence of systemic spread to the brain. The tropism for geese is unusual and may provide insight into the origin of these viruses. In mice, the H5N1 virus caused lethal pneumonia and spread systemically to the brain. Mice would thus provide an ideal model system for studying immune responses and pathogenesis. Transmission experiments in chickens revealed that the H5N1 viruses are spread by fecal-oral transmission rather than by aerosol, and that the viruses are inactivated by drying of feces at ambient temperature. However, infectivity is maintained for at least 4 days in wet feces at 25 degreesC. There were differences in the morphology of the H5N1 viruses isolated from birds and humans. The perpetuation of H5N1 influenza viruses in the poultry markets in Hong Kong and the transmission of these viruses to humans emphasize the importance of these markets in the epidemiology of influenza. The poultry markets are of critical importance in the perpetuation and transmission of influenza viruses to other avian species and to mammals, including humans.
The development and application of hydraulic engineering migration risk early warning system based on data mining

This paper aims at the risk early warning system developed to solve the prevention problem of hydraulic engineering migration risk. Under the support of big data produced by the relocation and resettlement, it uses the data mining technology to develop the Hydraulic Engineering Migration Risk Early Warning System, and the basic thoughts of the system design is to select the association rule data mining technology as the core technology of the system, and builds the system using B/S structure. The purpose of this system is to predict the dangerous risks issues in the hydraulic engineering migration, and conducts the visual output through the network system, allowing decision makers to better cope with the crisis.
Position Estimation and Autonomous Travel by Mobile Robots in Natural Terrain

simplistic language, these two meanings correspond to answers to the questions “Where am I? ’ and “How do I get there? ’ Although the robotics community has devoted significant effort to unattended air and water vehicles, in this chapter we restrict attention to ground robots. One reason for this restriction is that the majority of research and development efforts have concentrated on land vehicles, so we have learned more about ground-travelling robots than about flying, gliding, swimming, or floating robots. Another reason for the restriction is that, in general, the density of obstacle fields is greater on the ground than in either air or water, and
Improving localization accuracy based on Lightweight Visual Odometry

New methods based on vision have emerged in the area of mobile vehicle localization. Such methods offer an improved alternative in terms of accuracy to traditional localization methods like wheel odometry. In this paper we propose such a method that does not compromise precision and can run in real time. Depending on environment, feature numbers are sometimes insufficient. To solve this, our algorithm allows using slower feature detectors like SURF for frame keypoints, together with Shi-Tomasi corners for increasing points number. We show how accuracy is further improved by using a Kalman filter to enhance the computation of pose to pose relative motion variation.
ITÔ CALCULUS AND DERIVATIVE PRICING WITH RISK-NEUTRAL MEASURE

This paper will develop some of the fundamental results in the theory of Stochastic Differential Equations (SDE). After a brief review of stochastic processes and the Itô Calculus, we set our sights on some of the more advanced machinery needed to work with SDE. Chief among our results are the Feynman-Kac Theorem, which establishes a link between stochastic methods and the classic PDE approach, and the Girsanov theorem, which allows us to change the drift of an Itô diffusion by switching to an equivalent martingale measure. These results are also valuable on a practical level, and we will consider some of their applications to derivative pricing calculations in mathematical finance.
Embryology of the human fetal hippocampus: MR imaging, anatomy, and histology.

PURPOSE To identify changes in the embryology of the hippocampus responsible for its adult anatomy. METHODS Ten human fetal specimens ranging from 13 to 24 weeks' gestational age were examined with MR imaging. Dissections and histologic sections of 10 different specimens of similar ages were compared with MR imaging findings. RESULTS At 13 to 14 weeks' gestation, the unfolded hippocampus, on the medial surface of the temporal lobe, surrounds a widely open hippocampal sulcus (hippocampal fissure). At 15 to 16 weeks, the dentate gyrus and cornu ammonis have started to infold. The hippocampal sulcus remains open. The parahippocampal gyrus is larger and more medially positioned. The CA1, CA2, and CA3 fields of the cornu ammonis are arranged linearly. The dentate gyrus has a narrow U shape. By 18 to 20 weeks, the hippocampus begins to resemble the adult hippocampus. The dentate gyrus and cornu ammonis have folded into the temporal lobe. The hippocampus and subiculum approximate each other across a narrow hippocampal sulcus. The CA1-3 fields form an arc and the CA4 field has increased in size within the widened arch of the dentate gyrus. CONCLUSION MR imaging of fetuses provides a developmental basis for understanding hippocampal anatomy.
Nanomedicine as an emerging approach against intracellular pathogens

Diseases such as tuberculosis, hepatitis, and HIV/AIDS are caused by intracellular pathogens and are a major burden to the global medical community. Conventional treatments for these diseases typically consist of long-term therapy with a combination of drugs, which may lead to side effects and contribute to low patient compliance. The pathogens reside within intracellular compartments of the cell, which provide additional barriers to effective treatment. Therefore, there is a need for improved and more effective therapies for such intracellular diseases. This review will summarize, for the first time, the intracellular compartments in which pathogens can reside and discuss how nanomedicine has the potential to improve intracellular disease therapy by offering properties such as targeting, sustained drug release, and drug delivery to the pathogen’s intracellular location. The characteristics of nanomedicine may prove advantageous in developing improved or alternative therapies for intracellular diseases.
A Central Neural Pathway Controlling Odor Tracking in Drosophila

Chemotaxis is important for the survival of most animals. How the brain translates sensory input into motor output beyond higher olfactory processing centers is largely unknown. We describe a group of excitatory neurons, termed Odd neurons, which are important for Drosophila larval chemotaxis. Odd neurons receive synaptic input from projection neurons in the calyx of the mushroom body and project axons to the central brain. Functional imaging shows that some of the Odd neurons respond to odor. Larvae in which Odd neurons are silenced are less efficient at odor tracking than controls and sample the odor space more frequently. Larvae in which the excitability of Odd neurons is increased are better at odor intensity discrimination and odor tracking. Thus, the Odd neurons represent a distinct pathway that regulates the sensitivity of the olfactory system to odor concentrations, demonstrating that efficient chemotaxis depends on processing of odor strength downstream of higher olfactory centers.