Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine learning techniques in dialogue act recognition

This report addresses dialogue acts, their existing applications and techniques of automatically recognizing them, in Estonia as well as elsewhere. Three main applications are described: in dialogue systems to determine the intention of the speaker, in dialogue systems with machine translation to resolve ambiguities in the possible translation variants and in speech recognition to reduce word recognition error rate. Several recognition techniques are described on the surface level: how they work and how they are trained. A summary of the corresponding representation methods is provided for each technique. The paper also includes examples of applying the techniques to dialogue act recognition. The author comes to the conclusion that using the current evaluation metric it is impossible to compare dialogue act recognition techniques when these are applied to different dialogue act tag sets. Dialogue acts remain an open research area, with space and need for developing new recognition techniques and methods of evaluation. DOI: http://dx.doi. org/10.5128/ERYa3.08
Design and Implementation of Secure Subnet Inside of Data Sensitive Network

Sensitive data leak can cause significant loss for some organizations, especially for technology intensive companies and country security departments. Traditional mandatory access control (MAC) can only control whether the user can access the sensitive data or not, and cannot prevent the user to leak or spread the data. So even designed impeccable access control policies, we still cannot prevent inside leak. A nature solution is using physical isolation to prevent sensitive data from being leaked outside network; however inside the physical isolated network, data still can be spread from one subnet to another. We present Secure Subnet System, a BLP model base security system that can provide more strong access control, which is called mandatory action control. In our system after a user read sensitive data, system will dynamically change security policies to prevent the user to leak these data or spread the data outside to another subnet. We use a state machine model to describe our system, and use secure transfer equations to dynamically calculate the system policies for each new state. Our model can be proved to be secure by formal methods. We implemented a demon of our system. In this paper we also show the design details of the demon and evaluate the demon both from security and performance. The evaluation results show that the output of the security tests case are under expected; and the performance test case show that, for the 64KB IO chunk size, IO read loss can be improved to 6.6%, IO write loss can be improved to 1.2% after optimization.
Communications Receivers: Principles and Design

For professional-level information, this classic work has long been considered the definitive guide to both theory and design of all types of communications receivers including shortwave, military, broadcast, and direction-finding.Now the new edition builds on the reputation of its best-selling predecessor. Completely revised throughout, it features the latest advances in cellular and digital systems . basic discussions of selectivity and dynamic range . specifics on design approaches, circuitry, and components . details on the use of microprocessors and logic devices . coverage of special modes such as pulse and data . and more.
Opinion summarization of customer reviews

This paper focuses on the problem of opinion summarization of customer reviews, which has not been solved completely in how to get a summary that overlaps the most important topics of review text and to extract the opinion on these topics. With the intuition that both factual text and evaluative text should be considered in opinion summarization, this paper deals with sentiment and topics of review text simultaneously and proposes a multi-document opinion summarization approach based on Latent Dirichlet Allocation model. Experiments on product reviews show that the approach is effective.
Fast demodulation method for passive MIMO communication by using beam-forming at receiver

In this letter, we propose the demodulation method to improve the complexity of demodulation in passive MIMO (Multiple-Input MultipleOutput) scheme. This scheme uses the multiple antennas at both reader and RFID (Radio Frequency Identification) tag to increase the data-rate, but the complexity of MLD (Maximum Likelihood Detection), which is used as demodulation algorithm, increases exponentially with the number of antennas. The proposed method divides tag antennas into two groups that do not interfere each other by decoupling tag antenna groups using 180-degree hybrids at tag side and beam-forming at receiver side. Individual demodulation for each group improves the complexity of MLD significantly. Simulation results show the proposed method can reduce the complexity of MLD with degrading slight BER (Bit-Error-Rate) performance. The results reveal the proposed method is effective in reducing demodulation complexity of passive MIMO transmission even when the number of tag antennas is increased.
Hungarian: An Essential Grammar

This is a user-friendly guide to the structure of the Hungarian language. It contains jargon-free explanations and can be used by those studying independently or following a taught course. Topics covered include verbal prefixes; aspect and tense; word-formation mechanisms; linking vowels; the case system and its uses; and word order. Appendices feature the formation of irregular verbs, complete noun declensions and iregular noun patterns. With numerous language examples bringing grammar to life, this reference work should be valuable to students looking to master the patterns and irregularities of modern Hungarian.
On the Design, Analysis, and Implementation of Algorithms for Selected Problems in Graphs and Networks

On the Design, Analysis, and Implementation of Algorithms for Selected Problems in Graphs and Networks by Matthew D. Williamson Doctor of Philosophy in Computer Science West Virginia University This thesis studies three problems in network optimization, viz., the minimum spanning tree verification (MSTV) problem, the undirected negative cost cycle detection (UNCCD) problem, and the negative cost girth (NCG) problem. These problems find applications in several domains including program verification, proof theory, real-time scheduling, social networking, and operations research. The MSTV problem is defined as follows: Given an undirected graph G = (V,E) and a spanning tree T , is T a minimum spanning tree of G? We focus on the case where the number of distinct edge weights is bounded. Using a bucketed data structure to organize the edge weights, we present an efficient algorithm for the MSTV problem, which runs in O(|E|+ |V | ·K) time, where K is the number of distinct edge weights. When K is a fixed constant, this algorithm runs in linear time. We also profile our MSTV algorithm with the current fastest known MSTV implementation. Our results demonstrate the superiority of our algorithm when K ≤ 24. The UNCCD problem is defined as follows: Given an undirected graph G = (V,E) with arbitrarily weighted edges, does G contain a negative cost cycle? We discuss two polynomial time algorithms for solving the UNCCD problem: the b-matching approach and the T -join approach. We obtain new results for the case where the edge costs are integers in the range {−K · ·K}, where K is a positive constant. We also provide the first extensive empirical study that profiles the discussed UNCCD algorithms for various graph types, sizes, and experiments. The NCG problem is defined as follows: Given a directed graph G = (V,E) with arbitrarily weighted edges, find the length, or number of edges, of the negative cost cycle having the least number of edges. We discuss three strongly polynomial NCG algorithms. The first NCG algorithm is known as the matrix multiplication approach in the literature. We present two new NCG algorithms that are asymptotically and empirically superior to the matrix multiplication approach for sparse graphs. We also provide a parallel implementation of the matrix multiplication approach that runs in polylogarithmic parallel time using a polynomial number of processors. We include an implementation profile to demonstrate the efficiency of the parallel implementation as we increase the graph size and number of processors. We also present an NCG algorithm for planar graphs that is asymptotically faster than the fastest topology-oblivious algorithm when restricted to planar graphs.
Query optimization by semantic reasoning

The problem of database query optimization is to select an efficient way to process a query expressed in logical terms from among the alternative ways it can be carried out in the physical database. This thesis presents a new approach to this problem, called semantic query optimization. The goal of semantic query optimization is to produce a semantically equivalent query that is less expensive to process than the original query. Semantic query optimization actually transforms the original query into a new one by means of a process of inference. The transformations are limited to those that yield a semantically equivalent query, one that is guaranteed to produce the same answer as the original query in any permitted state of the database. This guarantee is achieved because the knowledge used to transform a query is the same knowledge used to insure the semantic integrity of the data stored in the database. Thus, semantic query optimization brings together the apparently separate research areas of query processing the database integrity. The thesis also addresses an important issue in current automatic planning research: production not just of a correct solution but of a "good" one, by means of an efficient problem solver. Semantic query optimization advances the notion of a problem reformulation step for problem-solving programs. In this step, equivalent statements of the original problem are sought, one of which may have a better solution than the original problem. This method avoids explicit and possibly costly analysis of efficiency factors during planning itself. Semantic query optimization can also be viewed as one aspect of intelligent database mediation. It applies knowledge of a problem domain and of the capabilities and limitations of the database to pose the most effective and easily processed queries to solve a user's problem. The thesis formally defines transformations that preserve semantic equivalence for queries in the relational calculus. In addition, it identifies several classes of cost-reducing query transformations for relational database queries, and provides quantitative estimates of the improvements they can produce, based upon widely accepted models of query processing. The thesis also discusses the design and implementation of a system that carries out semantic query optimization for an important class of relational database queries. The system is called QUIST, standing for QUery Improvement through Semantic Transformation. The QUIST system has analyzed a range of queries for which different transformations apply. For these queries, QUIST obtains substantial reductions in the cost of processing at a negligible cost for the analysis itself.
A controller to compensate voltage sags, unbalance and harmonic distortion using a series active filter

In this paper we present an adaptive controller for the series active filter to guarantee a sinusoidal balanced voltage on the load side despite of the presence of perturbations in the source voltage such as unbalance, harmonic distortion, sags and swells, as well as disturbances in the current load such as step changes, unbalance and distortion by higher order harmonics. To accomplish this objective, the series active filter is forced to inject the appropriate voltage to the line through a series connected transformer. This task is performed by the proposed controller in three stages (loops). First, an inner control loop forces the injected voltage to track a periodic reference. Second, an outer control loop regulates the voltage level in the capacitor (the storage element) making possible the construction of such a periodic reference. Third, the power flow between the line and the DC capacitor is handled by an outer (higher level) loop that allows the DC capacitor to deliver or absorb the necessary power to improve transients on load voltage when changes appear in the active power delivered by the source or absorbed by the load.
Online Sequential Prediction for Nonstationary Time Series with New Weight-Setting Strategy Using Extreme Learning Machine

Accurate and fast prediction of nonstationary time series is challenging and of great interest in both practical and academic areas. In this paper, an online sequential extreme learning machine with new weighted strategy is proposed for nonstationary time series prediction. First, a new leave-one-out (LOO) cross-validation error estimation for online sequential data is proposed based on inversion of block matrix. Second, a new weighted strategy based on the proposed LOO error estimation is proposed. This strategy ranks the samples’ importance by means of the LOO error of each new added sample and then assigns various weights. Performance comparisons of the proposed method with other existing algorithms are presented based on chaotic and real-world nonstationary time series data. The results show that the proposed method outperforms the classical ELM and OS-ELM in terms of generalization performance and numerical stability.
Word sense disambiguation

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Cross-words reference template for DTW-based speech recognition systems

One of the main problems in dynamic time-warping (DTW) based speech recognition systems are the preparation of reliable reference templates for the set of words to be recognised. This paper presents a simple novel technique for preparing reliable reference templates to improve the recognition rate score. The developed technique produces templates called crosswords reference templates (CWRTs). It extracts the reference template from a set of examples rather than one example. This technique can be adapted to any DTW-based speech recognition systems to improve its performance. The speaker-dependent recognition rate, as tested on the English digits, is improved from 85.3%, using the traditional technique to 99%, using the developed technique.
A GMSK modulator using a ΔΣ frequency discriminator-based synthesizer

This paper describes a new transmitter architecture suitable for wideband GMSK modulation. The technique uses direct modulation of /spl Delta//spl Sigma/ frequency discriminator (/spl Delta//spl Sigma/FD)-based synthesizer to produce the modulated RF signal without any up-conversion. Digital equalization is used to extend the modulation data rate far beyond the synthesizer closed-loop BW. A prototype 1.9-GHz GSM transmitter was constructed consisting of a /spl Delta//spl Sigma/FD-based synthesizer and a digital transmit filter. The synthesizer consists of an 0.8-/spl mu/m BiCMOS /spl Delta//spl Sigma/FD chip, a digital signal processor FPGA, and an off-chip D/A converter, filter, and VCO. Measured results, using 271-kbit/s GSM modulation, demonstrate data rates well in excess of the 30-kHz synthesizer closed-loop BW are possible with digital equalization. Without modulation, the synthesizer exhibits a -76-dBc spurious noise level and a close-in phase noise of -74 dBc/Hz.
Space vector modulated three-phase to three-phase matrix converter with input power factor correction

Analysis, design, and implementation of the space vector modulated three-phase to three-phase matrix converter with input power factor correction are presented. The majority of published research results on the matrix converter control are given an overview, and the one which employs simultaneous output-voltage and input-current space vector modulation, is systematically reviewed. The modulation algorithm is theoretically derived from the desired average transfer functions, using the indirect transfer function approach. The algorithm is verified through implementation of a 2 kVA experimental matrix converter driving a standard induction motor as a load. The switching frequency is 20 kHz. The modulator is implemented with a digital signal processor. The resultant output voltages and input currents are sinusoidal, practically without low-frequency harmonics. The input power factor is above 0.99 in the whole operating range.
Adaptation en temps réel pour une meilleure qualité d'expérience en réalité augmentée

In the framework of mobile augmented reality, a video stream is sent to the user with the help of a wireless communication link. To guarantee an efficient transmission, the video stream rate is controlled by adapting the encoding parameters such as to follow a given bandwidth. The rate can be reduced by reducing the frame rate and/or by choosing a higher compression factor for the video stream. These parameter modifications impact both the level of detail and the fluidity perceived by the user, and thus his/her subjective appreciation. The experience perceived by the user also depends on the context. During a rapid head motion, the notion of fluidity is more important than for a fixed head position. We propose an end-to-end adaptation scheme which enables the encoding of parameters such as to provide the best experience for the user regarding the dynamical context. For example, when the user moves quickly his/her head, the frame is compressed more to increase the frame rate and hence achieve a better perception of the motion. The lack of direct measurement for the subjective user experience is addressed with the design of objective metrics and a generic model to predict the user quality of experience in real time. A rate control strategy based on a systems approach is deployed to manage the multiple encoding parameters which control the stream rate. The encoder is modeled in an abstract manner as a single-variable linear system, where the content variation is taken as a perturbation. A stable and efficient controller is designed for the abstract model of the encoder. To implement the designed controller, the parameter combinations for the real encoder corresponding to the single input of the abstract model should be determined. A new one-pass algorithm determines this correspondence in real time based on a mapping method. Then, the proposed contextual adaptation enables to get the encoding parameter combination that maximizes the quality of experience using an appropriate model. Finally, the global adaptation scheme combines the rate control, the mapping method and the contextual adaptation for real-time implementation. Simulation and experiments illustrate the approach and the global adaptation scheme is validated through different scenarios.
Deploying and evaluating the effectiveness of energy eco-feedback through a low-cost NILM solution

This paper describes a low cost eco-feedback energy monitoring research platform. The prototype system developed in Java uses a netbook audio input and a single point current and voltage sensor to calculate real-time energy usage while also offering multiple visualization options and tracking human-activities. The prototype is deployed in a multidisciplinary research project to understand the long-term effects of eco-feedback and enduring behavioral changes towards practices that promote sustainability. This paper reports the efforts required to deploy the prototype system in 21 houses during a period of 9 weeks. The results enable quantitative analysis of the effectiveness of energy eco-feedback and provide a platform for further research in this domain.
Understanding the phonetics of neutralisation: a variability-field account of vowel/zero alternationsin a Hijazi dialect of Arabic

This thesis throws new light on issues debated in the experimental literature on neutralisation. They concern the extent of phonetic merger (the completeness question) and the empirical validity of the phonetic effect (the genuineness question). Regarding the completeness question, I present acoustic and perceptual analyses of vowel/zero alternations in Bedouin Hijazi Arabic (BHA) that appear to result in neutralisation. The phonology of these alternations exemplifies two neutralisation scenarios bearing on the completeness question. Until now, these scenarios have been investigated separately within small-scale studies. Here I look more closely at both, testing hypotheses involving the acoustics-perception relation and the phonetics-phonology relation. I then discuss the genuineness question from an experimental and statistical perspective. Experimentally, I devise a paradigm that manipulates important variables claimed to influence the phonetics of neutralisation. Statistically, I reanalyse neutralisation data reported in the literature from Turkish and Polish. I apply different pre-analysis procedures which, I argue, can partly explain the mixed results in the literature. My inquiry into these issues leads me to challenge some of the discipline’s accepted standards for characterising the phonetics of neutralisation. My assessment draws on insights from different research fields including statistics, cognition, neurology, and psychophysics. I suggest alternative measures that are both cognitively and phonetically more plausible. I implement these within a new model of lexical representation and phonetic processing, the Variability Field Model (VFM). According to VFM, phonetic data are examined as jnd-based intervals rather than as single data points. This allows for a deeper understanding of phonetic variability. The model combines prototypical and episodic schemes and integrates linguistic, paralinguistic, and extra-linguistic effects. The thesis also offers a VFM-based analysis of a set of neutralisation data from BHA. In striving for a better understanding of the phonetics of neutralisation, the thesis raises important issues pertaining to the way we approach phonetic questions, generate and analyse data, and interpret and evaluate findings.