Miracle-dz/UniFAR-FTUs huggingface dataset:
AMPL: A Modeling Language for Mathematical Programming

Practical large-scale mathematical programming involves more than just the application of an algorithm to minimize or maximize an objective function. Before any optimizing routine can be invoked, considerable effort must be expended to formulate the underlying model and to generate the requisite computational data structures. AMPL is a new language designed to make these steps easier and less error-prone. AMPL closely resembles the symbolic algebraic notation that many modelers use to describe mathematical programs, yet it is regular and formal enough to be processed by a computer system; it is particularly notable for the generality of its syntax and for the variety of its indexing operations. We have implemented an efficient translator that takes as input a linear AMPL model and associated data, and produces output suitable for standard linear programming optimizers. Both the language and the translator admit straightforward extensions to more general mathematical programs that incorporate nonlinear expressions or discrete variables.
Digital Communications Over Fading Channels

Abstract : In this report, the probabilities of bit error for the most commonly used digital modulation techniques are analyzed. Analytic solutions are developed for the probability of bit error when the signal is affected by the most commonly encountered impairment to system performance for a wireless channel, the transmission of the signal over a fading channel. In this report, the effect of a slow, flat Ricean fading channel on communications systems performance is examined. Since channel fading significantly degrades the performance of a communication system, the performance of digital communication systems that also use forward error correction channel coding is analyzed for hard decision decoding and, where appropriate, for soft decision decoding. Diversity, another technique to mitigate the effect of fading channels on digital communication systems performance, is also discussed. Also included is a discussion of the effect of narrowband noise interference, both continuous and pulsed, on digital communication systems. We then discuss the analysis of the probability of bit error for the combination of error correction coding and diversity. Following this, we briefly discuss spread spectrum systems. Next, we examine the link budget analysis and various models for channel loss. Finally, we examine in detail the second generation digital wireless standard Global System for Mobile (GSM).
Speech recognition with continuous-parameter hidden Markov models

The acoustic-modelling problem in automatic speech recognition is examined from an information theoretic point of view. This problem is to design a speech-recognition system which can extract from the speech waveform as much information as possible about the corresponding word sequence. The information extraction process is factored into two steps: a signal-processing step which converts a speech waveform into a sequence of informative acoustic feature vectors, and a step which models such a sequence. The authors are primarily concerned with the use of hidden Markov models to model sequences of feature vectors which lie in a continuous space. They explore the trade-off between packing information into such sequences and being able to model them accurately. The difficulty of developing accurate models of continuous-parameter sequences is addressed by investigating a method of parameter estimation which is designed to cope with inaccurate modeling assumptions. <<ETX>>
Synchronization of hyperchaotic discrete-time systems: model-matching approach

In this paper, a study of synchronization problem of hyperchaotic discrete-time systems is presented. In particular, we use a model-matching approach from the nonlinear control theory. One simulation example shows that the model-matching approach is indeed suitable for synchronization of hyperchaotic systems. An application to private communications is also given using two different schemes.
Cambridge Handbook of Generative Syntax, the: Syntax and the brain

1. The role of syntactic theory in a cognitive neuroscience of syntax Marr (1982:19-29) argued that a complete description of any information processing device, including the human brain, will necessarily involve three levels of description: the computational level, the algorithmic level, and the implementational level. The computational level can best be described as an answer to the question " what problem is being solved by the device? " (and to some extent " why does the problem have the form that it does? "). The algorithmic level is a description of the specific operations necessary to solve the problem. And the implementational level is a description of how those operations are implemented in the hardware of the device itself. Although this partitioning of the problem into three neat levels of analysis can be abused (see Phillips and Lewis 2010 for discussion), it also provides a good starting point for understanding the relationship between syntactic theory, the theory of sentence processing within psycholinguistics, and the neural implementation of sentence processing within neurolinguistics. Therefore we will begin our discussion with Marr's three levels and how they map to the cognitive neuroscience of sentences. 1.1 The computational level – syntactic theory Marr famously used a cash register to illustrate the three levels, so it seems appropriate to continue the tradition. The computational theory of a cash register (i.e. the problem that a cash register must solve) is the tallying of the cost of purchasing multiple items from a store, or more abstractly, the theory of addition. The properties of addition are familiar from arithmetic: (i) the order of addition for two numbers has no effect on the final sum (commutativity), (ii) the grouping of three or more items into pairs prior to addition also has no effect on the final sum (associativity), (iii) the addition of zero to a number has no effect on the number (identity), (iv) and the addition of a number and its inverse results in zero. As Marr (1982: 22) stated, " these properties are part of the fundamental theory of addition " , which means that " they are true no matter how the numbers are written… and no matter how the addition is executed. " In many ways, syntactic theory is the computational theory of the " human sentence processor " , as syntactic theory seeks to describe the fundamental properties of the sentences that are the …
Umbra's High Level Architecture (HLA) Interface

This report describes Umbra's High Level Architecture HLA library. This library serves as an interface to the Defense Simulation and Modeling Office's (DMSO) Run Time Infrastructure Next Generation Version 1.3 (RTI NG1.3) software library and enables Umbra-based models to be federated into HLA environments. The Umbra library was built to enable the modeling of robots for military and security system concept evaluation. A first application provides component technologies that ideally fit the US Army JPSD's Joint Virtual Battlespace (JVB) simulation framework for Objective Force concept analysis. In addition to describing the Umbra HLA library, the report describes general issues of integrating Umbra with RTI code and outlines ways of building models to support particular HLA simulation frameworks like the JVB.
Adaptive fuzzy control for automatic path tracking of outdoor mobile robots. Application to Romeo 3R

This paper deals with automatic steering and velocity control of outdoor mobile robots. An adaptive fuzzy control system is used to generate the appropriate vehicle steering angle and velocity command. Two fuzzy logic identification systems are used for geometric behavior identification (goal point selector) and dynamic model identification. Determination of the dynamic order, the number of rules and the constant stepsize is optimized to improve the convergence. The paper presents the application of the proposed method to the Romeo 3R outdoor mobile robot.
VIDEO CODING AND THE APPLICATION LEVEL FRAMING PROTOCOL ARCHITECTURE

As networks and computers become faster, real time video transmission is expected to become common. Variable bit rate video coders will be used in order to take advantage of the statistical multiplexing gain and bandwidth efficiency of packet switched networks. Video streams have different service requirements from the traffic usually carried on computer networks. A new protocol architecture called Application Level Framing (ALF) has been proposed to allow efficient implementation of communications with diverse service requirements. ALF allows the application to control the way in which network errors are handled. This thesis studies the compatibility of three proposed video coding standards with an ALF protocol architecture. Each of the standards is found to be usable with varying degrees of effort. A set of design principles for video codes intended for use over an ALF protocol architecture is presented.
Finding the Right Metaphor: Restructuring, Realigning, and Repackaging Today's Research Libraries

ABSTRACT To change from collection-centric to user-centered research libraries and to survive in tough economic times, libraries face 2 major challenges: 1st, libraries need to change how they are viewed by their constituencies so they are seen as indispensable; and 2nd, libraries need to help the librarians and staff change their own mental models of their roles to remain relevant in these changing times. Metaphors are one way to help people connect terms in new ways so they develop new images of those terms. For more than 100 years, libraries have used metaphors to seek connections that will help people see libraries as something other than warehouses for books. This article will explore various metaphors being used in the library field and how these metaphors can help libraries introduce change to improve their chances of receiving the support needed to survive.
Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability

From the Publisher: From mobile communications to robotics to space technology to medical instrumentation, new technologies are demanding increasingly complex methods of digital signal processing (DSP). This book shows researchers how recurrent neural networks can be implemented to expand the range of traditional signal processing techniques. Featuring original research on stability in neural networks, the book combines rigorous mathematical analysis with application examples. Experimental evidence as well as an overview of existing approaches are also included. Market: Engineers working in signal processing, neural networks, communications, nonlinear control, and time series analysis.
Understanding and enhancing return to work after sick leave for workers with common mental disorders

Een nieuwe methode voor werknemers die verzuimen om psychische redenen, verlengt de periode om het werk volledig te hervatten. Na de gebruikelijke zorg van de bedrijfsarts wordt het werk na 153 dagen (mediaan) hervat, bij een nieuwe exposure-in vivo methode is dat 209 dagen. Dit constateert Erik Noordik in zijn onderzoek naar een betere begeleiding om mensen die verzuimen om psychische redenen weer aan de slag te krijgen. De gebruikelijke zorg van de bedrijfsarts bestaat uit een geleidelijke opbouw van het aantal werkuren. De experimentele benadering voegt daar een geleidelijk toenemende confrontatie met moeilijke, stressvolle of beangstigende taken of werksituaties aan toe. Noordik adviseert door te gaan met het begeleiden volgens de bestaande richtlijnen en geen gebruik te maken van de principes van exposure-in-vivo. Het vertrouwen van werknemers in een terugkeer naar werk hangt sterk samen met een daadwerkelijke terugkeer. Bedrijfsartsen en leidinggevenden moeten extra aandacht geven aan personeel met weinig vertrouwen in terugkeer. Deze personen hebben vaak depressieve klachten of zijn vermoeid en melden een hoge werklast. Een van de oplossingen kan zijn om de arbeidsomstandigheden te verbeteren. De bedrijfsgezondheidsdienst en leidinggevenden moeten mensen die hun werk gedeeltelijk hebben hervat, actief helpen met de laatste stappen naar volledige werkhervatting, aldus Noordik.
Temperature-Dependent Instabilities of DC characteristics in AlGaN/GaN-on-Si Heterojunction Field Effect Transistors

We have performed reverse gate bias stress tests on AlGaN/GaN-on-Si Heterostructure FETs (HFETs). The shift of threshold voltage (Vth) and the reduction of on-current were observed from the stressed devices. These changes of the device parameters were not permanent. We investigated the temporary behavior of the stressed devices by analyzing the temperature dependence of the instabilities and TCAD simulation. As the baseline temperature of the electrical stress tests increased, the changes of the Vth and the on-current were decreased. The on-current reduction was caused by the positive shift of the Vth and the increased resistance of the gate-to-source and the gate-to-drain access region. Our experimental results suggest that electron- trapping effect into the shallow traps in devices is the main cause of observed instabilities.
A Multidimensional Approach to Utterance Segmentation and Dialogue Act Classification

In this paper we present a multidimensional approach to utterance segmentation and automatic dialogue act classification. We show that the use of multiple dimensions in distinguishing and annotating units not only supports a more accurate analysis of human communication, but can also help to solve some notorious problems concerning the segmentation of dialogue into functional units. We introduce the use of per-dimension segmentation for dialogue act taxonomies that feature multi-functionality and show that better classification results are obtained when using a separate segmentation for each dimension than when using one segmentation that fits all dimensions. Three machine learning techniques are applied and compared on the task of automatic classification of multiple communicative functions of utterances. The results are encouraging and indicate that communicative functions in important dimensions are easy machinelearnable.
Full-body pose tracking under severe occlusions: the Top View Reprojection approach

Marker-less articulated human body pose recovery and tracking is a challenging problem of great importance, with strong theoretical and practical implications. The recent introduction of low-cost depth cameras triggered a number of interesting new works, pushing forward the state of the art. However, despite the remarkable progress, estimating the body pose in realistic, complex scenarios is still an open research task. In this thesis we propose and develop a markerless model-based method to recover and track the full body pose, from RGB-D sequences, in arbitrary scenarios where users can freely enter or leave the scene, move, act and interact with other users or the environment. Our research focuses mainly on the problem of handling occlusions, either across body parts belonging to the same user, or across different users. At the same time, we attempt to tackle additional important issues encountered in the problem at hand, such as dealing with the large diversity of human bodies or the unconstrained initialization of tracking. Towards this goal, we introduced the novel concept of Top View Reprojection (TVR) of cylindrical objects, which uniquely defines the pose of a cylinder based on certain quantitative appearance properties of its Top View, i.e. the view aligned with the cylinder’s main axis. Based on this, the problem of estimating the pose of a cylindrical object becomes that of estimating the corresponding Top View. Interestingly, the developed formulation of TVR remains unaffected from factors such as noisy or missing data. Capitalising on the TVR concept, we represent the human body by a cylinderbased model, consisting of 11 body parts. The body is uniformly treated within the TVR framework following a local optimization technique; body parts, represented as cylinders, are examined in a top-to-bottom sequential order, starting from the head. For each body part a set of hypotheses is generated and tracked over time by a Particle Filter (PF). To evaluate each hypothesis, we employ a novel metric that considers the virtual Top View of the corresponding body part. The latter, in conjunction with regular depth information, effectively copes with difficult and ambiguous cases, such as severe interand intra-person occlusions. For evaluation purposes, we conducted several series of experiments addressing realistic scenarios of gradually increased difficulty, involving varying number of users interacting with each other. We further compared the performance of the proposed method against that of state-of-the-art approaches using public or own-collected datasets with ground truth annotation. The presented quantitative and qualitative results attest for the effectiveness of our approach.
Moving a Robot Arm: An interesting application of the Direct method of Lyapunov

In this paper, we explore the fundamentals of an emerging technique applicable, at least, in principle, to robot navigation, or motion planning. Termed the second method of Lyapunov, it is currently a powerful mathematical technique used to study the qualitative behaviour of natural or man-made systems that could be modeled, in an approximate way, by differential equations. We review the Lyapunov method and then in a simple and direct way, we use it to propose a theoretical technique to control the motion of a planar arm in a constrained environment. The controllers are mathematical entities which are nonlinear in nature. Computer simulations are used to illustrate the effectiveness of the proposed controllers.
Derivation and Validation of the Automated Readability Index for Use with Technical Materials

The utility of technical materials is influenced to a marked extent by their reading level or readability. This article describes the derivation and validation of the Automated Readability Index (ARI) for use with technical materials. The method allows for the easy, automatic collection of data as narrative material is typed on a slightly modified electric typewriter. Data collected includes word length (a measure of word difficulty) and sentence length (a measure of sentence difficulty). Appropriate weightings of these factors in a multiple regression equation result in an index of reading difficulty. Uses of the index for evaluating and controlling the readability of large quantities of technical material are described.
A fast and low power multiplier architecture

In this paper a new multiplier architecture is proposed for low power and high speed applications. It is based on generating all partial products in one step, then summing these partial products using binary tree network. This reveals a speedup of more than 50% than the array multiplier for (32/spl times/32) bit multiplication. Computer simulation with HSPICE shows that the new proposed architecture has better speed and power performance.
A Polar Rover for Large-Scale Scientific Surveys: Design, Implementation and Field Test Results

Exploration of polar regions is of great importance to scientific research. Unfortunately, due to the harsh environment, most of the regions on the Antarctic continent are still unreachable for humankind. Therefore, in 2011, the Chinese National Antarctic Research Expedition (CHINARE) launched a project to design a rover to conduct large-scale scientific surveys on the Antarctic. The main challenges for the rover are twofold: one is the mobility, i.e., how to make a rover that could survive the harsh environment and safely move on the uneven, icy and snowy terrain; the other is the autonomy, in that the robot should be able to move at a relatively high speed with little or no human intervention so that it can explore a large region in a limit time interval under the communication constraints. In this paper, the corresponding techniques, especially the polar rover's design and autonomous navigation algorithms, are introduced in detail. Subsequently, an experimental report of the fields tests on the Antarctic is given to show some preliminary evaluation of the rover. Finally, experiences and existing challenging problems are summarized.
Detecting Static Objects in Busy Scenes

Detecting static objects in scenes containing signiicant number of moving objects has several applications in video surveillance. One example is the detection of suspicious packages which is left unattended in an airport terminal or railway station. This paper outlines an approach to automatically detect static objects from a video sequence of a busy scene. Our approach consists of two phase : foreground object extraction and object matching. In the rst phase, we nd the foreground objects in current video frame, using an image of a background as reference. In the object matching phase, we try to match the objects with objects that appears before in previous frames. Matching is done based on three parameter : shape and position, intensity and edge. Temporary occluded of objects is also handled. We built a system based on our approach. Preliminary experiments shows that our system are able to identify static objects in a busy scene in real time.
Learning Hidden Markov Models with Geometric Information

Hidden Markov models (\textsc{hmm}s) and partially observable Markov decision processes (\textsc{pomdp}s) provide a useful tool for modeling dynamical systems. They are particularly useful for representing environments such as road networks and office buildings, which are typical for robot navigation and planning. In a previous paper [Shatkay and Kaelbling 1997] we have empirically shown that by taking advantage of readily available odometric information, learning \textsc{hmm}s/\textsc{pomdp}s can be made faster and better. This paper extends our previous results in two ways. We show that our algorithm, which introduces an additional data structure and constraints to the standard \textsc{hmm} and extends the Baum-Welch algorithm to accommodate them, indeed converges to a local maximum of the likelihood function. In addition, we extend our empirical study, and show that the algorithm is robust in the face of reduction in the length of the training sequences. Thus, the use of local odometric information yields faster convergence to better solutions with less data.
Fine-grained integration of Oberon into Windows using pluggable objects

The ETH Oberon System has been implemented in two fundamentally different ways: as native operating system and as an application running on top of another operating system. The embedded versions of Oberon are typically implemented as full screen applications, which are poorly integrated in their host environment. On the on hand, this approach has the advantage of maintaining the look–and–feel of a native Oberon implementation. On the other hand, developers of Oberon software would sometimes want to reuse it or make it available on a fine–grained level as part of commercial applications. In this thesis, a generic solution to this problem using a software component approach is presented. Visual and non–visual Oberon components — ranging from simple gadgets such as buttons, to complex containers such as desktops — are subject to be plugged into foreign contexts of different kinds, e.g. web pages, spreadsheets, etc. Such pluggable objects are able to cooperate and communicate with their context and with other components using technologies like in–place activation, scripting, automation, clipboard, drag–and–drop, persistency, etc. Although the implementation described in this thesis is specific to the Windows platform, most of the fundamental ideas can easily be adopted for other platforms.