Miracle-dz/UniFAR-FTUs huggingface dataset:
An information-theoretic unsupervised learning algorithm for neural networks

In the unsupervised learning paradigm, a network of neuron-like units is presented an ensemble of input patterns from a structured-environment, such as the visual world, and learns to represent the regularities in that input. The major goal in developing unsupervised learning algorithms is to find objective functions that characterize the quality of the network's representation without explicitly specifying the desired outputs of any of the units. Previous approaches in unsupervised learning, such as clustering, principal components analysis, and information-transmission-based methods, make minimal assumptions about the kind of structure in the environment, and they are good for preprocessing raw signal input. These methods try to model all of the structure in the environment in a single processing stage. The approach taken in this thesis is novel, in that our unsupervised learning algorithms do not try to preserve all of the information in the signal. Rather, we start by making strongly constraining assumptions about the kind of structure of interest in the environment. We then proceed to design learning algorithms which will discover precisely that structure. By constraining what kind of structure will be extracted by the network, we can force the network to discover higher level, more abstract features. Additionally, the constraining assumptions we make can provide a way of decomposing difficult learning problems into multiple simpler feature extraction stages. We propose a class of information-theoretic learning algorithms which cause a network to become tuned to spatially coherent features of visual images. Under Gaussian assumptions about the spatially coherent features in the environment, we have shown that this method works well for learning depth from random dot stereograms of curved surfaces. Using mixture models of coherence, these algorithms can be extended to deal with discontinuities, and to form multiple models of the regularities in the environment. Our simulations demonstrate the general utility of the Imax algorithms in discovering interesting, non-trivial structure (disparity and depth discontinuities) in artificial stereo images. This is the first attempt we know of to model perceptual learning beyond the earliest stages of low-level feature extraction, and to model multiple stages of unsupervised learning.
7th DisCo Conference Reader: New Media and Education

The open and distance learning (ODL) paradigm has no doubt provided tertiary education opportunity for a greater number of qualified students who would have been denied access due to limitation of time and space in conventional universities. The open and distance learning institutions pride in large number of students. It is worthy of note that innovative instructional media such as e-learning, video conferencing, virtual learning etc are being developed continuously in order to address the instructional needs of these large populations. Considering that these innovative instructional procedures are able to meet the instructional needs of large populations; can the same be said of the assessment of student learning? While one lecturer can attend to the instructional needs of about five thousand students, it is practically impossible for a single lecturer to objectively score this same number. This paper shows the various challenges that exist in student learning assessments across a large population and proffers strategic procedures that can be adopted to address these challenges for the purpose of assuring quality of the programmes and products of distance learning.
Micropipelined Cache Design Strategies for an Asynchronous Microprocessor

8 Declaration . 9 Acknowledgements . 10 About the Author . 11 Chapter
A Survey On Research Issues in Wireless Sensor Networks

Wireless Sensor Networks make a tremendous growth and becomes an emerging research area in wireless and distributed networks. Wireless sensor network (WSN) is comprised of huge number of small and cheap devices recognized as sensor nodes. The sensor nodes are capable of sensing, actuating, and controlling the collected information. The sensor nodes communicate together by many wireless strategies and these communication strategies are administered by routing protocols. Performance of sensor networks largely depends on the some factors. Keeping this in mind, we have carried out extensive survey on issues in wireless sensor networks. Finally, this paper summarized the research issues and pointed out some future directions.
Calibrating Survey Data using Iterative Proportional Fitting (Raking)

In this article, I introduce the ipfraking package, which implements weight-calibration procedures known as iterative proportional fitting, or raking, of complex survey weights. The package can handle a large number of control variables and trim the weights in various ways. It also provides diagnostic tools for the weights it creates. I provide examples of its use and a suggested workflow for creating raked replicate weights.
H.264/AVC and Transcoding for Multimedia Adaptation

The newly ratified video compression standard H.264/AVC provides tools and solutions for coding improvements of at least 2 dB, in terms of PSNR, and at least 40% in bit rate saving, as compared with the previous standards. The development of video transcoding, which is one of the critical components for multimedia adaptation and Universal Multimedia Access, can gain benefits by using the tools and solutions from the standard. In this paper, the new features of H.264/AVC are first briefly reviewed. The issues involved in video transcoding are addressed together with a general framework for video transcoding. Here we utilize an architecture of pixel domain video transcoding derived directly from H.264/AVC.
What Counts and What Should Count as Evidence

In this chapter, we present our views on the place of experimental design in evidencebased policy-making and practice. Learning where we agree should help readers identify where they can be relatively confident about method choice. Learning where we disagree may help them identify which method choice decisions remain problematic, and where maximal caution is required in evaluating claims about new knowledge for improving the outcomes from education.
A transaction manager component supporting extended transaction models

A Transaction Manager Component for Extended Transaction Models George Theodore Heineman Database management systems (DBMSs) have increasingly been used for advanced database application. Traditional database applications, such as banking and airline reservation systems, rely on the DBMS to guarantee the consistency of the data. Towards this end, most DBMSs provide a correctness model based on con ict serializability (serializability for short) that assumes no specialized knowledge of the transactions. Many researchers have argued that serializability, as a concurrency control policy, is too restrictive; advanced database applications have semantic information that should be employed when maintaining the consistency of the data. The term semantic information refers to any pertinent knowledge about a transaction, its operations, or its relationships with other transactions. Many extended transaction models (ETMs) have been developed, but since di erent applications require di erent ETMs, there will likely never be a consensus on a standard ETM. A DBMS, therefore, cannot expect to implement an ETM suitable for all applications. This dissertation aims to solve two problems: How does one specify an ETM? How to implement (or support) an ETM? We avoid solutions that require a full implementation from scratch by designing an External Concurrency Control (ECC) architecture that captures the essence of advanced database applications. We show how a transaction manager can employ semantic information from the Task Management Layer (TML) of these applications. Our mediator-based architecture allows for exible integration of a transaction manager component with advanced database applications and provides for generic extraction of semantic information from database applications. The Pern transaction manager component we implemented realizes the ECC architecture. Pern employs a declarative concurrency control language, called Cord that determines how to extend the behavior of transactions. Using Cord, an ETM is speci ed by its extensions to serializability. Pern can then support the desired ETM by applying Cord rules during transaction execution. Cord is practical since it assumes that the transaction manager already provides serializability as a correctness criterion. We show the power and exibility of Cord as we model many popular ETMs from the literature. For existing DBMSs, we show how to modify transaction managers to incorporate the Cord run-time interpreter, allowing them to provide extensible concurrency control.
Exploring Time Series Graphically

Introduction Interactive graphical tools are available in a number of packages (Data Desk, JMP, SAS Insight and to a lesser extent LispStat, S+ and others), but none provide interactive tools for working with time series. This is surprising, as graphical displays have always been considered important for time series analysis. The natural time ordering of the data makes graphs very informative and the lack of independence of the data makes simple summary statistics less useful than in other contexts.
The SC4 Short Names Registry

This paper describes a software environment recently implemented for maintaining a registry of unique short names for each of the entity data types within each of the Express schemas in the ISO TC184/SC4 standards. The new environment replaces an ine cient application and has already provided time savings for both the registry's administrator and editors of SC4 standards. It is also improving the quality of SC4 standards. The new SC4 Short Names Registry resides on a server at NIST and uses an SQL database engine in conjunction with the NIST Express Toolkit. Two applications have been developed for accessing the Short Names Registry. An application for end users that is accessible using the World Wide Web allows individuals to view SC4 part summary information and entity long names and short names in a variety of useful formats. An application for database administrators supports the insertion, deletion, and modi cation of SC4 parts.
A dynamic field approach to goal inference, error detection and anticipatory action selection in human-robot collaboration

In this chapter we present results of our ongoing research on efficient and fluent human-robot collaboration that is heavily inspired by recent experimental findings about the neurocognitive mechanisms supporting joint action in humans. The robot control architecture implements the joint coordination of actions and goals as a dynamic process that integrates contextual cues, shared task knowledge and the predicted outcome of the user’s motor behavior. The architecture is formalized as a coupled system of dynamic neural fields representing a distributed network of local but connected neural populations with specific functionalities. We validate the approach in a task in which a robot and a human user jointly construct a toy ‘vehicle’. We show that the context-dependent mapping from action observation onto appropriate complementary actions allows the robot to cope with dynamically changing joint action situations. More specifically, the results illustrate crucial cognitive capacities for efficient and successful human-robot collaboration such as goal inference, error detection and anticipatory action selection.
Argumentation and artifacts for intelligent multi-agent systems

Reasoning under uncertainty is a human capacity that in software system is necessary and often hidden. Argumentation theory and logic make explicit non-monotonic information in order to enable automatic forms of reasoning under uncertainty. In human organization Distributed Cognition and Activity Theory explain how artifacts are fundamental in all cognitive process. Then, in this thesis we search to understand the use of cognitive artifacts in an new argumentation framework for an agent-based artificial society.
TOS: a temporal object system

In many engineering applications, changes to the state and structure of an object need to be maintained over a period of time. Existing object-oriented data models allow such changes in the state (referred to as Version Management) and structure (referred to as Schema Evolution) of an object. However, when the structure changes, the old structure is replaced by the new one. We proposed a Temporal Object System (TOS) which maintains changes to both the structure and the state of an object. Objects in TOS are referred to as Temporal Objects and are allowed to evolve over time. A family is a collection of temporal objects which share a common set properties: root of family (ROF). We define an aggregation of a set of simple families as a complex family and a temporal object of the complex family is called a temporal complex object (TCO). A temporal object that can also be defined by using local knowledge of a family is referred to as an offstage object. Offstage objects and temporal objects can replace and refresh their knowledge through a process called renovation. We discuss the renovations of both temporal complex objects and offstage objects and enumerate their temporal parameters (i.e. time-span, life-span and life-sequence) after renovation. The available knowledge sharing mechanisms, inheritance and delegation, are not suitable for a temporal system, therefore, we propose a knowledge sharing mechanism Share-kno and give it a formal model. We prove that Share-kno is more knowledgeable than the inheritance and delegation models which are proposed by Stein. We also give the syntax of the data definition and data manipulation languages (DDL & DML) for TOS. A data manipulation language, temporal object-oriented query (TO$\sp2$L), is proposed which is a super-set of the relational query language SQL. It can answer temporal and non-temporal queries of a TOS from a stage level to system level. In the end, we propose two future research directions. The first direction is implementation of a TOS, and the second is to provide a mathematical background to TOS. To make TOS more formal, the mathematical tool category theory is suggested. This can give a mathematical foundation to this research.
Optimal buffering algorithms for client-server VBR video retrievals

Variable bit rate (VBR) videos refer to videos with varying frame sizes. When transmitted through networks in a client-server environment, their corresponding traffic is inherently bursty because of the embedded timing constraints in digital videos. In reservation based networks like ATM network, such traffic may result in considerable network under-utilization if the network has to accommodate the peak bit rate. Traffic smoothing is thus necessary to reduce the burstiness in the VBR video traffic and it can be very effective in the case of stored video. By introducing a playback delay and buffering video data on the client side, a smoother traffic can be transmitted by the server. In order for the client to restore the original timing information in the video, it is important to avoid buffer overflow or underflow during the video retrieval. This buffer constraint determines the "smoothest" traffic that can be sent out by the server and thus defines a set of optimization problems based on different traffic types. In this thesis, several buffering and traffic smoothing methods for VBR videos are thoroughly studied and their relationships established. Among them, minimum polyline smoothing and minimum on-off smoothing are two fundamental methods and serve as the basis for other methods. For a given video service with buffer and delay constraint, minimum polyline smoothing produces smoothed traffic with multiple rate changes while minimum on-off smoothing generates a single rate traffic with transmitting (on) and idle (off) periods. We carefully choose smoothness criterion for each method and identify optimization problems based on these criteria. Novel algorithms are then presented for these problems and their correctness and effectiveness are theoretically proved and experimentally verified. These methods not only can be applied very effectively on stored VBR videos, but can serve as benchmark algorithms for real-time video smoothing. Simulation programs based on the algorithms designed in the thesis are applied to VBR video traces to show the effectiveness of these smoothing methods.
From Propositional to First Order Logic in Machine Learning and Data Mining - Induction of first ord

An almond tree which is open, large, vigorous, and upright; foliated with medium size, acuminate, acutely pointed leaves having a crenate margin, and alternate, small, globose, green glands; blooms early and heavily with white flowers; and is a regular, very heavy bearer of early-in-harvest, well-distributed nuts; the nuts, of medium size, being ovate, plump, soft shell, and well-sealed, and the kernels, of small but uniform size, being ovate, medium thick, and attractive in appearance.
Multiuser Receivers for Coded CDMA Systems

Abstract : In this dissertation, the asynchronous direct sequence code division multiple access (CDMA) communication system is described and a number of multiuser detection approaches are proposed that improve upon the performance of the conventional base station. Both coded and uncoded systems are studied for nondispersive, additive white Gaussian noise (AWGN) channels. For the uncoded system case, the multiuser detection techniques that have already been proposed are first reviewed. Then, two decision feedback equalizers (DFE's) that have been proposed are combined to form a new hybrid DFE which outperforms the others in situations where the multiuser interference in the system is high. Next, the case where each user in the system employs a convolutional code to improve its performance is studied. First, the optimal multiuser sequence estimator is formulated, and it is shown that this receiver may be implemented using a Viterbi algorithm which operates on a time varying trellis with a number of states which is exponential in the product of the number of users in the system and the constraint length of the codes used (for the rate 1/2 code case). Because this optimal receiver has a very high complexity, a variety of suboptimum receivers are proposed which have a performance level near that of the optimal receiver's but have a more manageable complexity. All of the approaches are compared on the basis of their performance (through analysis and simulation), their complexity and their decoding delay.
Children's Inquiry: Using Language to Make Sense of the World (Language and Literacy Series)

This exploration of children's "inquiry" - what it is, how it develops, and how it contributes to children's learning - should help elementary and language teachers to understand, appreciate, and foster children's inquiry in classrooms. In this volume, the author introduces a theoretical framework for understanding children's "inquiry" language, not as linguistic forms (questions), but as communication acts in which the child brings another into the act of sense-making. By examining these "inquiry acts", the author aims to uncover new possibilities for the understanding of how children learn and how tachers can foster their learning in classrooms, class exercises, research findings, classroom episodes, and the author's own reflections.
Selecting Salient Features of Psychophysiological Measures

Abstract : Determining operator cognitive or functional state is a critical component of adaptive aiding systems. To determine cognitive state, we must decide which measured features from the human will assist in distinguishing different levels of mental activity. A battery of psychophysiological signals was collected for two levels of cognitive workload from which 43 measures were derived. Three feature-reduction methods, principal component analysis, a weight-based partial derivative method, and a weight-based signal-to-noise ratio were applied, and the results were used as inputs to an artificial neural network for training and classification. Average classification accuracies up to 89.7 percent were achieved and the number of input features required was reduced by up to 84 percent.
Microscope X dans la fenêtre de l’eau : conception, miroirs à revêtements multicouches et métrologie associée

L’observation d’echantillons biologiques a une echelle nanometrique est actuellement un theme majeur pour la biologie. En particulier, la microscopie a rayons X dans la fenetre de l’eau (entre les seuils d’absorption K-alpha de l’oxygene et du carbone, soit entre 2,4 et 4,4 nm de longueur d’onde) presente un interet remarquable car elle permet a la fois l’observation d’echantillons biologiques avec un fort contraste d’absorption naturel, mais egalement une haute resolution grâce a la courte longueur d’onde d’utilisation. Plusieurs microscopes bases sur des composants diffractifs ont d’ores et deja ete developpes et ont montre une resolution allant jusqu’a 12 nm. Dans ce contexte, nous developpons au Laboratoire Charles Fabry un microscope X plein champ a miroirs en incidence proche de la normale. Le schema optique du microscope a dans un premier temps ete etudie et optimise. Il est base sur un objectif de Schwarzschild, et dispose donc d’une longue distance de travail ce qui permettra de faciliter l’installation de l’echantillon a observer. Les miroirs doivent etre traites avec un revetement multicouche a tres faible periode a base de chrome et de scandium. Plusieurs systemes multicouches a couches sub nanometrique ont ete etudies pour maximiser la reflectivite des revetements a une longueur d’onde proche de 3,14 nm, parmi lesquels : Cr/Sc, Cr/B4C/Sc, CrN/Sc et CrN/B4C/Sc. Une reflectivite pic de plus de 23% a ete mesuree pour un revetement multicouche CrN/B4C/Sc a un angle d’incidence inferieur a 5°.
Impact of Query Correlation on Web Searching

Correlation among queries is an important factor to analyze as it may affect the results delivered by a search engine. In this paper, we analyze correlation among queries and how it affects the information retrieved from the Web. We analyze two types of queries: (i) queries with embedded semantics, and (ii) queries without any semantics. In our analysis, we consider parameters such as search latencies and search relevance. We focus on two major search portals that are mainly used by end users. Further, we discuss a unified criteria for comparison among the performance of the search engines.
Structural Optimization of Solid Components with Topology Optimizing Structural Language TopoSLang

The invention provides an apparatus for automatically moving the tongue of a seat belt into a position in which it may conveniently be grasped by an operator for insertion into a buckle. The apparatus comprises an inflatable bellows engageable with the tongue and extensible into the position by the application of pressure. The bellows may be retracted by vacuum pressure or by integral resilient means in response to the tongue having been inserted into the buckle.
The best batsmen and bowlers in one-day cricket

This project proposes a new measure for assessing the performance of batsmen and bowlers in one-day cricket. Current measures of performance all suffer from serious drawbacks, thus expressing the need for a more sensible measure. The ratio of runs scored to resources consumed (where resources are defined according to the Duckworth-Lewis method of resetting targets) provides a statistic which is developed and studied in this project. The approach used in defining the new measure is explained in detail, as well as a description of the Duckworth-Lewis method. The statistic is then calculated for a subset of batsmen and bowlers. In addition, a standard error is provided to help determine real differences in performance. Finally, comparisons are made with traditional measures of performance by looking at players’ rankings.