Miracle-dz/UniFAR-FTUs huggingface dataset:
NewsTalk--a speech interface to a personalized information agent

Personalized information agents have proven to be useful tools for a number of tasks. To date, these tools have required a person to use a visual display in the current situation. However, this reliance on the use of the eyes is inappropriate in common situations (e.g., while driving a car) and impossible for some people (those who are blind or visually impaired). NewsTalk, a speech-only interface to the day's news, enables a person to access personalized information without the use of the eyes. The interface creates a spoken conversation metaphor, and makes use of speech recognition, synthesis, and digitized speech to enable communication. Qualitative and quantitative studies validate the utility of the system. Thesis supervisor: Christopher M. Schmandt Title: Principal Research Scientist, MIT Media Laboratory This work was sponsored by IBM and the MIT Media Lab News in the Future Consortium.
Fisch and Spehlmann's Eeg Primer: Basic Principles of Digital and Analog Eeg

Part A: Technical background. 1. The source of the EEG. 1.1 The generator of the EEG. 1.2 Rhythmical EEG activity. 1.3 Recording of electrical potentials with scalp electrodes. 2. Recording electrodes. 2.1 Electrode shapes and application methods. 2.2 Electrical properties of recording electrodes. 2.3 Electrode placement. 2.4 Recording non-cerebral potentials. 3. Digital and analogue EEG instruments: parts and functions. Introduction. 3.1 The electrode panel. 3.2. Analog EEG instrument input selector switches. 3.3 Analogue and digital calibration. 3.4 Amplifiers. 3.5 Filters. 3.6 Analogue writing units. 3.7 Analogue to digital conversion. 3.8 The signal display. 3.9 Digital filtering. 3.10 Digital montage selection and montage reformatting. 3.11 Digital data storage and transmission. 3.12 Electrical safety. 4. Spatial analysis of the EEG. 4.1 Multichannel recordings. 4.2 Bipolar montages. 4.3 Common electrode reference montages. 4.4 Average reference montages. 4.5 Weighted average montages. 4.6 Laplacian montages. 4.7 Source localization. 4.8 Montage display and design. 4.9 Analysis of the topography of the EEG voltage field. 4.10 Summary. 5. The product of the recording: the clinical EEG record. 5.1 General technical standards. 5.2 Standards for pediatric recordings. 5.3 Standards for recordings in cases of suspected cerebral death. 5.4 Telephone transmission. 6. Artifacts. 6.1 Artifacts from the patient. 6.2 Interference. 6.3 Artifacts arising from recording electrodes and equipment. 7. Special methods of analysis and recording. 7.1 Quantitative EEG analysis. 7.2 Topographic mapping. 7.3 Automated event detection. 7.4 Intraoperative and intensive care unit monitoring. 7.5 Ambulatory EEG recording. 7.6 EEG recording with simultaneous video monitoring. Part B: The normal EEG. 8. Definition of the normal EEG, relation to brain function. 8.1 Definition of the normal EEG. 8.2 A normal EEG does not always mean normal brain function. 8.3 An abnormal EEG does not necessarily mean clinically abnormal brain function. 9. Descriptors of EEG activity. 9.1 Waveform. 9.2 Repetition. 9.3 Frequency. 9.4 Amplitude. 9.5 Distribution. 9.6. Phase relation. 9.7 Timing. 9.8 Persistence. 9.9 Reactivity. 10. The normal EEG from premature age to the age of 19 years. 10.1 Neonatal EEG. 10.2 Infants from full term to 3 months of age. 10.3 Infants from 3 months to 12 months of age. 10.4 Children and adolescents from 1 to 19 years of age. 11. The normal EEG of wakeful resting adults of 20-60 years of age. 11.1 The alpha rhythm. 11.2 Beta rhythms. 11.3 Mu rhythm. 11.4 Lambda waves. 11.5 Vertex sharp transients (V waves). 11.6 Kappa rhythm. 11.7 Normal posterior theta rhythms. 11.8 The low voltage EEG. 11.9 Major abnormalities. 12. The normal sleep EEG of adults over 20 years. 12.1 Elements of normal sleep activity. 12.2 Sleep stages. 12.3 Sleep cycles. (Part contents).
Efficient Approach for the Development of Metadata Editors by Metamodeling Strategy : A Survey

Metadata is information about the date that describes, specifies, or makes it easier to reclaim, utilizes or deals with an information resource. The latest version of the metadata standards that supports the metadata editors. To make certain correct and appropriate use and understanding of the data. We use metadata standards are requirements which are deliberate to ascertain a common indulgencing of the meaning or semantics of the data. The barrier for this invention of the metadata is the miscellany and heterogeneity. The main goal of our ongoing research is the Model Driven Architecture for the development of metadata editors for geographic information resources, in order to more focus on the generic action of metadata model than on the enlargement of the specific edition form of a reduced set of metadata standards. It could help to improve the efficiency and interoperability of any metadata editors using metamodeling development strategy. In this paper, intended to learn and evaluate various approaches of metadata modeling strategy. Keywords-Spatial Data Infrastructure, Metadata, Ontology, Eclipse Modeling Framework, Data Access Service
Optimising multiple aspects of network survivability

It is generally accepted that survivable networks tend to consist of network elements (nodes and links) where no individual element is significantly more important than any other element. Using a traffic based network survivability metric Si, which quantifies the impact of removing network element i from a network of N elements, this paper investigates the modification of link capacities to simultaneously maximise average network survivability (1/N/spl Sigma//sub i=1//sup N/S/sub i/) and minimise the variability of Si (var(Si)). For some networks there appears to be an unique optimal set of link capacities however, for others, a number of possible optima exist. For these networks a Pareto-optimal set was generated so that a decision could be made on which link enhancements should be performed. The change in optima as a consequence of changes in the budget for link enhancements and also in changes in the required network traffic load were also investigated.
Multiobjective Programming and Goal Programming: Theoretical Results and Practical Applications

This book gives the reader an insight into the state of the art in the field of multiobjective (linear, nonlinear and combinatorial) programming, goal programming and multiobjective metaheuristics. The 26 papers describe all relevant trends in this fields of research . They cover a wide range of topics ranging from theoretical investigations to algorithms, dealing with uncertainty, and applications to real world problems such as engineering design, water distribution systems and portfolio selection. The book is based on the papers of the seventh international conference on multiple objective programming and goal programming (MOPGP06).
Simulation of arbitrary transmission line networks with nonlinear terminations

The transient response of a high-speed digital circuit is determined by the interaction of a lossy distributed transmission line network and lumped nonlinear circuits. A robust and accurate method for the analysis of such a system is reported, and its implementation in an analog circuit simulator is discussed. The method uses a convolution technique and a time-domain impulse response to perform a transient simulation of a transmission line network. The time-domain impulse response is derived using a Fourier transform of modified frequency-domain scattering parameters. Implementation of the technique is verified by comparison with measured results. >
Particle filter to track multiple people for visual surveillance

A particle filter (PF) has been recently proposed to detect and track colour objects in video. This study presents an adaptation of the PF to track people in surveillance video. Detection is based on automated background modelling rather than a manually generated object colour model. Furthermore, a labelling method is proposed to create tracks of objects through the scene, rather than unconnected detections. A methodical comparison between the new PF tracking method and two other multi-object trackers is presented on the PETS 2004 benchmark data set. The PF tracker gives significantly fewer false alarms owing to explicit modelling of the object birth and death processes, while maintaining a good detection rate.
A medical image watermarking scheme based on wavelet transform

A wavelet-based multiple watermarking scheme is proposed, which addresses the problems of medical confidentiality protection and both origin and data authentication. The scheme embeds multiple watermarks serving different purposes: a robust watermark containing the doctor's digital signature for authentication, a caption watermark with patient's personal and examination related data, and a fragile watermark for the purpose of data integrity control. Thus, the proposed added-value tool offers alternatives for different issues associated with medical data management and distribution. The experimental results demonstrate the efficiency of the watermarking scheme, which fulfills the strict requirements concerning the acceptable alterations of medical images.
Neural network design

This book, by the authors of the Neural Network Toolbox for MATLAB, provides a clear and detailed coverage of fundamental neural network architectures and learning rules. In it, the authors emphasize a coherent presentation of the principal neural networks, methods for training them and their applications to practical problems. Features Extensive coverage of training methods for both feedforward networks (including multilayer and radial basis networks) and recurrent networks. In addition to conjugate gradient and Levenberg-Marquardt variations of the backpropagation algorithm, the text also covers Bayesian regularization and early stopping, which ensure the generalization ability of trained networks. Associative and competitive networks, including feature maps and learning vector quantization, are explained with simple building blocks. A chapter of practical training tips for function approximation, pattern recognition, clustering and prediction, along with five chapters presenting detailed real-world case studies. Detailed examples and numerous solved problems. Slides and comprehensive demonstration software can be downloaded from hagan.okstate. edu/nnd.html.
An amendment to final-offer arbitration

Final-offer arbitration (FOA) was proposed to settle a dispute between two disputants. Although FOA was proposed to induce two disputants to reach an agreements by themselves, FOA fails to achieve the fulfilment, when disputants have incomplete information about the arbitrator's notion of a fair settlement. This paper proposes a new arbitration procedure, which is a simple amendment to FOA that lets the arbitration settlement be determined by the loser's offer if the offers diverge. We show that the offers converge in a unique pure strategy Nash equilibrium without any additional condition. We also provide two methods to prevent an extreme arbitration result, in case the offers do not converge for some reasons.
Review Paper On Data Clustering Of Categorical Data

Data mining refers to extracting or mining knowledge from large amounts of data. Clustering is the dynamic field of research in data mining.Most of the earlier work on clustering has mainly been focused on numerical data whose inherent geometric properties can be used to naturally define distance functions between data points. Many clustering algorithms are available to group objects having similar characteristics. But these algorithms cannot be applied to categorical data. Many of the algorithms have efficiency issues. This necessitated the development of some algorithms for clustering categorical data. This paper gives an overview of different clustering techniques.
The MediaSense Framework: Ranking Sensors in a Distributed Architecture

—The evolution of mobile applications and services, largely enhanced by their ability to respond to changes in a user’s situation is key driver towards an Internet of Things . With a size expected to exceed the current Internet, solutions are required for self organisation based on relevance and importance. This, underpinning new applications and services exposed to reliable and evolving context information around a presentity. One such element is the ability to rank heterogeneous and distributed sensors in response to real time interaction between users and the digital ecosystem. In this paper, we consider one approach to calculating sensor ranking based on their general usage patterns. We present it relevant to our work in progress MediaSense framework, showing the ability for it to be implemented without the need for any centralized coordination.
Comparison of kinematic analysis methods at one demonstration mechanism

The mechanisms are systems of moving parts that perform some function. One of their main advantages is converting the input forces and movements into a desired set of output forces and movements. The mechanism movement simulation is described in this paper. The solution includes calculation of velocities, accelerations and overall performance analysis. Numerical simulation of model mechanism was performed in the software package SAM. The velocities optimal for the drive element and the initial position of mechanism were given for initial conditions. All velocities and accelerations of mechanism points in this position were calculated. Results of computer simulation were compared with the results obtained by vector method. By comparison of the results it was found that the deviations were small, therefore it was concluded that the simulation was successfully performed.
Analysis and Comparison on Image Restoration Algorithms Using MATLAB

TheImage restoration is the recovery of an image that has been degraded by blur and noise. Degradation typically involves blurring of the original image and corruption noise. The recovery of an original image from degraded observations is of paramount importance and can find its application in several scientific areas including medical and diagnostics, military surveillance,satellite and astronomical imaging, remote sensing, authentication automated industry inspection and many areas. Image restoration assures good insights of image when it is subjected to further techniques of image processing. Presentation of the results and comparisons of the restoration algorithms namely Weiner Filter, the Regularized filter and Lucy-Richardson as implemented in Matlab. This is done using an image that is degraded by motion blur with Gaussian, Salt and Pepper and Speckle noise models respectively and restoration of same image using various algorithms mentioned above. Image restoration algorithms, distinguish themselves from enhancement methods in that they are based on models for degrading process and for the ideal image. The image restoration methods in this paper fall under the class of linear spatially invariant restoration filters. Degradation typically involves blurring of the original image and corruption noise.
Improving automated lexical and discourse analysis of online chat dialog

Abstract : One of the goals of natural language processing (NLP) systems is determining the meaning of what is being transmitted. Although much work has been accomplished in traditional written and spoken language domains, little has been performed in the newer computer-mediated communication domain enabled by the Internet, to include text-based chat. This is due in part to the fact that there are no annotated chat corpora available to the broader research community. The purpose of our research is to build a chat corpus, initially tagged with lexical and discourse information. Such a corpus could be used to develop stochastic NLP applications that perform tasks such as conversation thread topic detection, author profiling, entity identification, and social network analysis. During the course of our research, we preserved 477,835 chat posts and associated user profiles in an XML format for future investigation. We privacy-masked 10,567 of those posts and part-of-speech tagged a total of 45,068 tokens. Using the Penn Treebank and annotated chat data, we achieved part-of-speech tagging accuracy of 90.8%. We also annotated each of the privacy-masked corpus's 10,567 posts with a chat dialog act. Using a neural network with 23 input features, we achieved 83.2% dialog act classification accuracy.
How Do Young Deaf Children Learn to Read? A Proposed Model of Deaf Children's Emergent Reading Behaviors. Technical Report No. 329.

An instructional model based on deaf children's early attempts at learning to read is proposed based on a nine-month longitudinal study. This model holds that reading can be initiated by giving deaf children opportunities to match their internalized manual language to printed words. The recommended procedures stress the use of joint reading-related activities involving parents, teachers and peers. Two classroom experiments and parental interviews, provide evidence to support this instructional model. A three-leveled word reading seq ence is defined for deaf children based on the subjects' e prgent reading behaviors. Finally, practical suggestions are made for teachers and parents . interested in promoting reading in yoing deaf children.
Low-complexity space-time coding for multi-antenna systems and wireless relay networks

A rapidly growing demand on transmission rates, coverage and reliability for wireless communication systems has triggered an intensive research in the field of multi-antenna communications. The use of multi-antenna systems provides significant gains by making use of independent propagation paths between the transmitter and the receiver. Space-time coding has been recently proposed to exploit the benefits of the multi-antenna channels. In space-time code design, different tradeoffs have to be taken into account. Good codes should provide a high diversity gain and achieve the highest possible multiplexing gain. At the same time, the encoding/decoding complexity should remain as low as possible to enable computationally efficient signal processing. In this thesis, we propose high-rate high-performance space-time block coding schemes that achieve a significantly reduced maximum likelihood decoding complexity in comparison to other state-of-the-art space-time codes. In particular, we propose a 2x2 full-rate space-time code with non-vanishing determinants that achieves the optimal diversity-multiplexing gain tradeoff while using a fast maximum likelihood decoder. Furthermore, by extending the proposed strategy, we develop space-time codes for 3 and 4 transmit antennas. In certain cases, the use of multi-antenna systems can become impractical due to restrictions in hardware size and cost. As an alternative to create multi-path propagation environments, half-duplex wireless relay networks have emerged. In such networks, single antenna users cooperate to provide gains similar to that of the multi-antenna channel. Considering the initial restrictions, low-complexity distributed space-time coding schemes are required for relay systems. In the second part of the thesis, we develop a novel low-rate feedback-based distributed approach for cooperative transmission in relay networks that achieves the maximum diversity offered by the relay network, enjoys low-complexity maximum likelihood decoding, avoids long decoding delays and is applicable to any number of relays. The use of second-order channel statistics to design “long-term” power control weights is considered to further improve the performance of our approach in practical scenarios with channel links of different quality. Moreover, the proposed distributed space-time coding schemes are generalized to the non-coherent receiver case using differential transmission.
Tutorial: Survival Estimation for Cox Regression Models with Time-Varying Coe?cients Using SAS and R

Survival estimates are an essential compliment to multivariable regression models for time-to-event data, both for prediction and illustration of covariate effects. They are easily obtained under the Cox proportional-hazards model. In populations defined by an initial, acute event, like myocardial infarction, or in studies with long-term followup, the proportional-hazards assumption of constant hazard ratios is frequently violated. One alternative is to fit an interaction between covariates and a prespecified function of time, implemented as a time-dependent covariate. This effectively creates a time-varying coefficient that is easily estimated in software such as SAS and R. However, the usual programming statements for survival estimation are not directly applicable. Unique data manipulation and syntax is required, but is not well documented for either software. This paper offers a tutorial in survival estimation for the time-varying coefficient model, implemented in SAS and R. We provide a macro coxtvc to facilitate estimation in SAS where the current functionality is more limited. The macro is validated in simulated data and illustrated in an application.
Decentralized Methods for Cooperative Task Execution in Multi-robot Systems

Research on multi-robot systems have received a lot of interest during recent years. In this thesis, a group of methods addressing some relevant multirobot problems are presented. The first part deals with three environmental coverage problems. Chapter 1 describes the Sensor-based Random Graph (SRG) method for cooperative robot exploration. Chapter 2 describes the distributed visibility patrolling method, which can be viewed as a recurrent version of the exploration and is aimed to find optimal trajectories for a team of robots that must periodically visit a set of viewpoints in an environment with obstacles. In Chapter 3 the visibility-based pursuit-evasion method is presented, where a team of searchers must coordinate to guarantee detection of all evaders in an unknown environment while using only local information. The second part deals with localization and control problems in presence of anonymous measures. In particular Chapters 4 and 5 address the mutual localization, i.e., the estimation of the change of coordinates among the team members, using anonymous distance-bearing measures affected by false positives and false negatives. In Chapter 6 the anonymous-measurement setting is applied to the formation control field, addressing the encircling task.
dkrMorph : A Syriac Morphological Analyzer

This thesis proposes a method for automatic morphological analysis of Syriac - an under-resourced language for which there are no natural language processing tools such as morphological analyzers readily available. The proposed method uses a data-driven approach with automatically generated and weighted regular expression rules and patterns to cater for morphological attribute tagging and root- and lexeme derivation for dictionary linkage. The method is compared against a baseline, which it outperforms on all tests, and significantly outperforms for unknown words. When trained on all available training data, the analyzer achieves an accuracy of 95.53%.
Fusing optical flow and stereo disparity for object tracking

This paper proposes a novel approach to object detection and tracking using video sensors. Two different methods are employed to retrieve depth information from images: stereopsis and depth from motion. The obtained data streams are fused yielding increased reliability and accuracy. A set of image points is tracked over time using an extended Kalman filter. The proposed algorithm clusters points of similar dynamics by analysis of the filter residuals. Experimental results are provided for synthetic as well as for natural image sequences.