Miracle-dz/UniFAR-FTUs huggingface dataset:
Building the Uppsala Hindi Corpus

The aim of this presentation is to describe our on-going work on the building of a written Hindi treebank, referred to here as the Uppsala Hindi Corpus. The Uppsala Hindi Corpus is a part of our project on the construction of a HindiSwedish-English parallel treebank, financed by the Swedish Research Council and the Faculty of Languages, Uppsala University. India is making progress at a rapid pace in the global economy, increasing the need for speedy translation of material as well as a better understanding of its official language (Hindi). Hindi also provides a good testing ground for language technology tools. There are, at present, two major Hindi corpora generally available: the EMILLE corpus (Hardie et al., 2006) and the Hindi corpus at IIT Bombay. The IIT Bombay Hindi corpus is a monolingual corpus, consisting of excerpts of texts each around 2,000 words, and does not seem to have any linguistic annotation. The EMILLE corpus has both a large monolingual and a smaller parallel corpus part (Hindi-English), but this corpus, too, is not linguistically annotated. Given that our goal is to create a trilingual parallel corpus that is POStagged and dependency parsed as well as aligned at the word and sentence levels, and that can be used in linguistic research and teaching, these existing Hindi corpora are less useful for our purposes. In the remaining presentation we will focus on our work on the building of the Uppsala Hindi Corpus. The Hindi materials that, at present, are included in our corpus are:
Applicability of clustering to cyber intrusion detection

Maintaining cyber security is a complex task, utilizing many levels of network information along with an array of technology. Current practices for combating cyber attacks typically use Intrusion Detection Systems (IDSs) to passively detect and block multi-stage attacks. Because of the speed and force at which a new type of cyber attack can occur, automated detection and response is becoming an apparent necessity. Anomaly-based detection systems, such as statistical-based or clustering algorithms, attempt to address this by analyzing the relative differences in network and host activity. Signature-based IDS systems are typically more accurate for known attacks, but require time and resources for an analyst to update the signature database. This work hypothesizes that the latency from zero-day attack to signature creation can be shortened via anomaly-based algorithms. In particular, the summarizing ability of clustering is leveraged and examined in its applicability of signature creation. This work first investigates a modified density-based clustering algorithm as an IDS, with its strengths and weaknesses identified. Being able to separate malicious from normal activity, the modified algorithm is then applied in a supervised way to signature creation. Lessons learned from the supervised signature creation are then leveraged for the development of unsupervised real-time signature classification. Automating signature creation and classification via clustering turns out satisfactory but with limitations. Density supports for new signatures via clustering can be diluted and lead to misclassification.
Apache Derby SMP scalability: Investigating limitations and opportunities for improvement

This report investigates the B-Tree access method of Apache Derby. Apache Derby is an open source Java database system. The detailed focus of the report is on performance aspects of the Derby page latch implementation. Our focal point is the interaction between the B-Tree access method and page latching, and the impact of these components on the ability of Derby to scale on multiprocessor systems. Derby uses simple and  in the single-threaded case  inexpensive exclusive-only page latches. We investigate the impact on scalability of this design, and contrast it with a version of Derby modified to support both shared read-only and exclusive page access for lookups in index structures. This evaluation is made for single-threaded as well as multi-threaded scenarios on multiprocessing systems. Based on analyses of benchmark results and profiler traces, we then suggest how Derby may be able to utilize modern Java locking primitives to improve multiprocessor scalability.
Freshman Composition in the Early Middle Ages: Epistolography and Rhetoric before the Ars dictaminis

"Freshman Composition in the Early Middle Ages: Epistolography and Rhetoric before the Ars dictaminis. " Letter-writing was an acknowledged literary genre from classical times onward, and thousands of letters-but little direct evidence for epistolary theory-survive in Latin. Systematic transmission by teaching is, however, likely, long before the ars dictaminis appeared late in the 11th century. The progymnasmata, introductory exercises in rhetoric, included ethopoeia, the speech in character. Two Greek treatises, Cassiodorus, and Alberic of Monte Cassino associate ethopoeia with letter-writing. Several epistolary formulas reflect ethopoeia-theory and later appear in dictaminal treatises, and scattered evidence for classroom instruction in letter-writing appears in medieval sources. Structural changes in the classical curriculum transferred responsibility for the progymnasmata from rhetoric teachers, who aimed to produce accomplished public speakers, to the grammatici, who thus added the formal study of pr.
OBJECT-ORIENTED AND RULE-BASED MODELLING - EXPERIENCE FROM TRAFFIC SIGNAL SIMULATION

This paper discusses the advantages of object-oriented rule-based modelling in traffic simulation based on experience gained in the development of the HUTSIM traffic signal simulation system in Helsinki. The basic features of HUTSIM are object-oriented rule-based simulation of vehicle and control interactions and precise presentation of the signal control, the latter being realised by connecting a real adaptive signal controller to the micro-computer- based simulation system. Principles behind object-oriented modelling and elements of the model are discussed. Rule-based and state-based vehicle dynamics are described. The interactive role of graphics is considered. It is suggested that object-oriented programming with rule-based presentation is particularly suitable for traffic simulation. (A) For the covering abstract see IRRD 873901.
Semi-Automated Frame Transformations using FFT Analysis on 2-D Images

Cassini entered Saturn’s orbit on July 1, 2004 beginning a four-year exploration of Saturn. In 2008 the mission was extended, and Cassini continues to collect and transmit images and data collected during its mission. In order to accurately interpret images, it is necessary to know the location and orientation of the camera provided the field of view when the image was collected. While the mission managers provide initial estimates of this orientation, scientific analysis requires better estimates than the initial data provided. Navigation is a process for improving the estimation of the true camera pointing vector as determined by features identified in an image. Features such as the body of Saturn or specific rings can be utilized to approximate the correct position and orientation of Cassini. The Cassini Viewing Utility (CASVU) is a set of tools developed by the Software Engineering Research Group at the University of Texas at El Paso designed to facilitate the analysis of data returned by Cassini. In particular, the Navigation tool is provided for the correction of orientation and positioning of Cassini. CASVU uses the perspective projection approach to model a 3-D environment as seen from Cassini. The 3-D model is composed of wireframes that provide a predict view of Saturn and the rings assuming the initial estimation of camera orientation. These wireframes are superimposed on an image collected by Cassini. Features in the images are identified, and a Fast Fourier Transform based algorithm computes rotation and shift ratios between the predict wireframe and image. These ratios can then be applied to the predict wireframe to correct the pointing vector of Cassini. This thesis presents a semi-automated FFT-based navigation algorithm that can be utilized for the correction of spacecraft pointing estimates when integrated into CASVU.
Enhancing Survivability with Distributed Adaptive Coordination

Abstract : The focus of this effort was to develop distributed detection and diagnosis algorithms for use in recognizing and explaining the cause of unacceptable performance of a distributed, multi-agent system. The explanation generated by the diagnosis algorithms was to be used by other components of the agent to reorganize processing in order to improve performance given current capabilities and resources. In this way, the system would have a higher degree of survivability in the event of software errors, hardware malfunctions, or hostile attacks. The researchers view survivable systems as computational organizations that can redesign themselves in response to threats and opportunities. A central assumption of organizational design is that there exist alternative ways to accomplish tasks in terms of agents, methods and resources used. In systems of any complexity, such alternatives do exist, and systems constructed for survivability will intentionally contain them. Under these conditions, the central challenges of survivability are making effective use of the available alternatives, acquiring knowledge about those alternatives, and making inferences based on that knowledge.
Estimation and control with relative measurements: algorithms and scaling laws

In this dissertation we examine a class of estimation and control problems involving interconnected systems. These problems share the common attribute that, between two component subsystems, noisy measurements of the difference of their states alone is available. The estimation problem is relevant to sensor and actuator networks, and the control problem is relevant to coordination in multi-agent systems. Both classes of problems are defined over a graph that is used to describe the interconnections. In the first part of this dissertation, the estimation problem is examined. The variables correspond to the nodes of a graph, and the measurements of the noisy difference between pairs of variables correspond to its edges. The task is to compute estimates of the node variables with respect to a reference node. We begin by designing distributed algorithms to compute the optimal estimate, which refers to the best linear unbiased estimator (BLUE). We then examine the effect of the graph structure on the minimum achievable estimation error. Specifically, we examine how the optimal estimation error of a node variable grows with its distance from the reference node. A classification of graphs—sparse and dense in 1D, 2D, and 3D—is obtained, which determines the error growth rate: linear, logarithmic, or bounded. In the second part of this dissertation, the control of formations over arbitrary graphs is described. Specifically, we examine how the structure of the interconnection graph affects the stability and sensitivity to measurement noise of the formation. The vehicular platoon problem is investigated in detail—especially the decentralized bidirectional control architecture in which each vehicle uses front and back spacing measurements to compute its control signal. Fundamental limitations in disturbance amplification are established for the symmetric bidirectional architecture. Then we show that arbitrary small asymmetry in the front and back controller gains can lead to an order of magnitude improvement in stability margin. The underlying theme of our investigations is that of performance degradation—and possible amelioration—in interconnected systems as the number of constituent sub-systems increases.
Microstrip Antenna Design Handbook

Microstrip Radiators: Various Microstrip Antenna Configurations. Feeding Techniques and Modeling. Applications. Radiation Field. Surface Waves and Photonic Band-Gap Structures. Analytical Models for Microstrip Antennas: Transmission Line Model. Cavity Model. Generalized Cavity Model. Multi-port Network Model (MNM). Radiation Fields. Aperture Admittance. Mutual Admittance. Model for Coaxial Probe in Microstrip Antennas. Comparison of Analytical Models. Full-Wave Analysis of Microstrip Antennas: Spectral Domain Full-Wave Analysis. Mixed-Potential Integral Equation Analysis. Finite-Difference Time Domain Analysis.Rectangular Microstrip Antenna: Models for Rectangular Patch Antenna. Design Considerations for Rectangular Patch Antennas. Tolerance Analysis of Rectangular Microstrip Antennas. Mechanical Tuning of Patch Antennas. Quarter-wave Rectangular Patch Antenna. Circular Disk and Ring Antennas: Analysis of a Circular Disk Microstrip Antenna. Design Considerations for Circular Disk Antennas. Semicircular Disk and Circular Sector Microstrip Antennas. Comparison Of Rectangular And Circular Disk Microstrip Antennas. Circular Ring or Annular Ring Microstrip Antenna. Circular Sector Microstrip Ring Antenna. Microstrip Ring Antennas of Non-Circular Shapes. Dipoles and Triangular Patch Antennas: Microstrip Dipole and Center-Fed Dipoles. Triangular Microstrip Patch Antenna. Design of an Equilateral Triangular Patch Antenna. Microstrip Slot Antennas: Microstrip-Fed Rectangular Slot Antennas. CPW-Fed Slot Antennas. Annular Slot Antennas. Tapered Slot Antennas (TSA). Comparison of Slot Antennas with Microstrip Antennas. Circularly Polarized Microstrip Antennas and Techniques: Various Types of Circularly Polarized Microstrip Antennas. Singly-Fed Circularly Polarized Microstrip Antennas. Dual-Orthagonal Feed Circularly Polarized Microstrip Antennas. Circularly Polarized Traveling-Wave Microstrip-Line Arrays. Bandwidth Enhancement Techniques. Sequentially Rotated Arrays. Broad-Banding of Microstrip Antennas: Effect of Substrate Parameters on Bandwidth. Selection of Suitable Patch Shape. Selection of Suitable Feeding Technique. Multi-Moding Techniques. Other Broadbanding Techniques. Multifrequency Operation. Loaded Microstrip Antennas and Applications: Polarization Diversity Using Microstrip Antennas. Frequency Agile Microstrip Antennas. Radiation Pattern Control of Microstrip Antennas. Loading Effect of a Short. Compact Patch Antennas. Planar Inverted F Antenna. Dual-Frequency Microstrip Antennas. Dual-Frequency Compact Microstrip Antennas. Active Integrated Microstrip Antennas: Classification of Active Integrated Microstrip Antennas. Theory and Design of Active Integrated Microstrip Antenna Oscillators. Theory and Design of Active Integrated Microstrip Antenna Amplifiers. Frequency Conversion Active Integrated Microstrip Antenna Theory and Design. Design and Analysis of Microstrip Antenna Arrays: Parallel and Series Feed Systems. Mutual Coupling. Design of Linear Arrays. Design of Planar Arrays. Monolithic Integrated Phased Arrays.
Visual and spatial analysis : advances in data mining, reasoning, and problem solving

Preface, Color Plates PART 1. Visual Problem Solving and Decision Making 1. Decision process and its visual aspects, 2.Information visualization value stack model PART 2. Visual and Heterogeneous Reasoning 3. Visual reasoning and representation, 4. Representing visual decision making: a computational architecture for heterogeneous reasoning, 5. Algebraic visual symbolism for problem solving: iconic equations from Diophantus to our days, 6. Iconic reasoning architecture for analysis and decision making, 7.Toward visual reasoning and discovery: lessons from early history of mathematics PART 3. Visual Correlation 8. Visual correlation methods and models, 9.Iconic approach for data annotating, searching and correlating, 10. Bruegel iconic correlation system PART 4. Visual and Spatial Data Mining 11. Visualizing data streams, 12. SPIN! - an enterprise architecture for data mining and visual analysis of spatial data, 13. XML-based visualization and evaluation of data mining results, 14. Neural-network techniques for visual mining clinical electronencephalograms, 15. Visual data mining with simultaneous rescaling, 16. Visual data mining using monotone Boolean functions PART 5. Visual and Spatial Problem Solving in Geospatial Domains 17. Imagery integration as conflict resolution decision process: methods and approaches, 18. Multilevel analytical and visual decision framework for imagery conflation and registration, 19. Conflation of images with algebraic structures, 20. Algorithm development technology for conflation and area-based conflation algorithm, 21. Virtual experts for imagery registration and conflation
Families, Labour and Love: Family Diversity in a Changing World

Maureen Baker is Professor of Sociology at the University of Auckland, New Zealand. The idea for this book was conceived when, on moving to Auckland from McGill University, Canada, she was unable to find a recent New Zealand text on the sociology of families. Further, most analogous texts from countries with broadly similar social histories-Australia and Canada-failed to mention New Zealand, let alone each other. This book, then, is written to fill a gap. It is a scholarly textbook for academics and students in Australia, Canada and NZ (p. xi), a comparative study of these three "settler societies" that share a broadly similar history of colonisation and subjugation of Indigenous culture-but exhibit significant differences within their individual histories. The treatment of the topic is both comprehensive and thorough. An introductory chapter provides an overview of the personal and social worlds of families, identifying trends common to all three societies, including rising life expectancies, declining fertility, declining legal marriage rates, rising rates of remarriage, and greater participation of women in the paid workforce. Subsequent chapters discuss cultural variations in families; issues involved in conceptualising families; intimacy, cohabitation and the quality of marriage; childhood, reproduction and child care; families and paid/unpaid work; separation, divorce and remarriage; state regulation of family life; and the future of family life. At the end of each chapter a set of discussion questions encourages reflection on key issues and their implications. These questions are designed, presumably, as tutorial guides, but they also offer a valuable review fr.lmework for individual readers. An extensive glossary is proVided for readers unfamiliar with the language of family studies.
Modeling Intelligent Control of Distributed Cooperative Inferencing

Abstract : The ability to harness different problem-solving methods together into a cooperative system has the potential for significantly improving the performance of systems for solving NP-hard problems. The need exists for an intelligent controller that is able to effectively combine radically different problem-solving techniques with anytime and anywhere properties into a distributed cooperative environment. This controller requires models of the component algorithms in conjunction with feedback from those algorithms during run-time to manage a dynamic combination of tasks effectively. This research develops a domain-independent method for creating these models as well as a model for the controller itself. These models provide the means for the controller to select the most appropriate algorithms, both initially and during run-time. We utilize the algorithm performance knowledge contained in the algorithm models to aid in the selection process. This methodology is applicable to many NP-hard problems; applicability is only limited by the availability of anytime and anywhere algorithms for that domain. We demonstrate the capabilities of this methodology by applying it to a known NP-hard problem: uncertain inference over Bayesian Networks. Experiments using a collection of randomly generated networks and some common inference algorithms showed very promising results. Future directions for this research could involve the analysis of the impact of the accuracy of the algorithm models on the performance of the controller; the issue is whether the increased model accuracy would cause excessive system overhead, counteracting the potential increase in performance due to better algorithm selection.
Cgi How-To: The Definitive Cgi Scripting Problem-Solver

Reading data from a form request using the data passed into a CGI script reading data from an Imagemap request standard responses manipulating existing HTML files during dynamic output advanced responses to a request accessing other services connecting multiple scripts into an application testing a script installing a script security taking advantage of the server. Appendices: CGI supported environmental variables HTML forms quick reference reference list for HTML books Web resources what's on the CD.
A RESEARCH STUDY ON RECENT SKIN COLOR BASED STATISTICAL SEGMENTATION MODELING TECHNIQUES

The fundamental thought behind pixel based skin color segmentation is to detect and extract the pigment color of human's skin from the input image since it may contain other like skin color. The skin color is a perfect sign to the presence of human skin in a specific scene and a helpful indicator to minimize the search area to include the hand and face only. Skin color modeling techniques have been widely utilized for this purpose, the selection of color modeling techniques depends on the nature of the application with the suitable color model. In this paper we will discuss some recent skin color based segmentation modeling techniques applied to located and extract the hand gesture in order to prepare the segmented hand for the later gesture recognition stages.
On-demand Television combined with non-real-time Peer-to-Peer Content Delivery for Television Content Providers

With the expansion of the Internet and an increasing fraction of consumers having broadband connections, more and more content is finding its way on-line. Video content is becoming one of the most popular types of media content on the Internet. Traditional media content providers, such as television networks, are placing their content on the Internet in order to gain a broader audience. On-demand websites such as kanal5play.se allow viewers to view the multimedia content they want at the time of their choice. While this gives viewers flexibility in their viewing, it creates resource problems for content providers. Statistics from Kanal5 AB show that, even with individual viewers requesting content when they want, there are still patterns in which multiple viewers watch the same content at the same time. This means there are correlations in the demand for content. With unicast distribution this leads to spikes in requirements for bandwidth to the viewers. These peaks lead to high costs for network and server resources to deliver the requested content, but these resources have low average utilization. This thesis project investigates how a content provider can make use of each viewer’s own resources to deliver content to other users using peer-to-peer techniques. The thesis evaluates what methods can be used in order to reduce the content provider’s resource requirements during peak hours by exploiting copies of contents that have already been delivered to viewers who requested this same content earlier. A prototype was made to evaluate the suggested design using Java Remote Method Invocation (RMI), which is built on top of the Transfer Control Protocol (TCP). Experiments show that an initial delay of several seconds is reached on a network with a simulated delay of 100ms, while a minimal initial delay was observed on a network with low delay, i.e. ideal conditions. The throughput results of the prototype show that the suggested solution is adequate for delivering on-demand content supplied by Kanal5 AB. However, the relatively poor startup performance of this solution argues for tuning the application to better work with the TCP protocol or to utilize another transport protocol - especially if the round-trip delay is large as TCP’s 3-way handshake and flow control algorithm limit the performance of the prototype system.