Miracle-dz/UniFAR-FTUs huggingface dataset:
Lipreadable frame animation driven by speech parameters

Two different approaches are here presented for converting speech into graphic animation, suitable to lipreading. Coarticulation modeling has been taken into account by means of an original algorithm for multistep statistical processing of digital speech in the cepstrum space. Two different visualization methods have been used, the first based on key reference pictures and the second based on a parametric flexible structure. Speech is converted, in real-time, into lipreadable visual animation by associating incoming acoustic frames with correspondent consistent graphic primitives, pictures or parameters, suitably visualized. Multiple fields of application are foreseen, mainly in rehabilitation, training, education and communication among hard of hearing people. <<ETX>>
Considering Discourse References in Textual Entailment Annotation | NIST

In the 2009 Recognizing Textual Entailment challenge a Search Pilot task has been introduced, aimed at finding all the sentences in a corpus which entail a set of given hypotheses. The preparation of the data set for this task has provided an opportunity to better understand some phenomena concerning textual entailment recognition in a natural setting. This paper focuses on some problematic issues related to resolving coreferences to entities, space, time and events at the corpus level, as emerged during the annotation of the data set for the textual entailment Search Pilot.
Calibration-free Pedestrian Partial Pose Estimation Using a High-mounted Kinect

The application of human behavior analysis has undergone rapid development during the last decades from entertainment system to professional one, as Human Robot Interaction (HRI), Advanced Driver Assistance System (ADAS), Pedestrian Protection System (PPS), etc. Meanwhile, this thesis addresses the problem of recognizing pedestrians and estimating their body orientation in 3D based on the fact that estimating a person’s orientation is beneficial in determining their behavior. In this thesis, a new method is proposed for detecting and estimating the orientation, in which the result of a pedestrian detection module and a orientation estimation module are integrated sequentially. For the goal of pedestrian detection, a cascade classifier is designed to draw a bounding box around the detected pedestrian. Following this, extracted regions are given to a discrete orientation classifier to estimate pedestrian body’s orientation. This classification is based on a coarse, rasterized depth image simulating a top-view virtual camera, and uses a support vector machine classifier that was trained to distinguish 10 orientations (30 degrees increments). In order to test the performance of our approach, a new benchmark database contains 764 sets of point cloud for body-orientation classification was captured. For this benchmark, a Kinect recorded the point cloud of 30 participants and a marker-based motion capture system (Vicon) provided the ground truth on their orientation. Finally we demonstrated the improvements brought by our system, as it detected pedestrian with an accuracy of 95.29% and estimated the body orientation with an accuracy of 88.88%. We hope it can provide a new foundation for future researches.
Compact Stepped Impedance Resonator Bandpass Filter with Tunable Transmission Zeros

This paper proposes a compact microstrip bandpass filter (BPF) with tunable transmission zeros, narrow bandwidth and low insertion loss. A λ/4 stepped impedance resonator (SIR) with two additional via holes has been adopted to obtain a compact size and a pair of transmission zero (TZ). Furthermore, three techniques have been developed to create a pair of controllable transmission zeros on both side of each passband. The TZ can be controlled by adjusting either magnetic or electric coupling. The measured return losses and insertion loss is larger than 18 dB and 2.2 dB respectively. The overall size of the proposed design filter is 5.3mm x 5.5mm without considering the feeding lines.
DICTIONARY APPLICATION WITH SPEECH RECOGNITION AND SPEECH SYNTHESIS

Sanket Kamble, Ajinkya Kundur, Akash Hulbutti, Shubham Thorve, Vijayendra Gaikwad 1 2 3 4 Graduate Student, 5 Assistant Professor Department of Computer Engineering, Savitribai Phule Pune University, Pune, India ________________________________________________________________________________________________________ Abstract : In today’s environment while reading documents (online/offline) or browsing through many websites, we face many unfamiliar words, as we cannot get the meaning of those, we lack in complete understanding of the concepts or situation. So, to overcome this problem we are developing a Speech–To-Text and Text-To-Speech input and output method for our voice based dictionary system. The System is implemented using Java Sphinx-4 API for Speech Synthesis and Speech Recognition. The application or the system uses Java concepts like Swing API and JAVAFX for Graphical User Interface. The system will be deployed as the background process using Multithreading support.
An Automated System for the Assessment and Ranking of Domain Ontologies

As the number of intelligent software applications and the number of semantic web sites continue to expand, ontologies are needed to formalize shared terms. Often it is necessary to either find a previously used ontology for a particular purpose, or to develop a new one to meet a specific need. Because of the challenge involved in creating a new ontology from scratch, the latter option is often preferable. The ability of a user to select an appropriate, high-quality domain ontology from a set of available options would be most useful in knowledge engineering and in developing intelligent applications. Being able to assess an ontology’s quality and suitability is also important when an ontology is developed from the beginning. These capabilities, however, require good quality assessment mechanisms as well as automated support when there are a large number of ontologies from which to make a selection. This thesis provides an in-depth analysis of the current research in domain ontology evaluation, including the development of a taxonomy to categorize the numerous directions the research has taken. Based on the lessons learned by the literature review, an approach to automatic assessment of domain ontologies is selected and a suite of ontology quality assessment metrics grounded in semiotic theory are presented. The metrics are implemented in a Domain Ontology Rating System (DoORS), which is made available as an open source web application. An additional framework is developed that would incorporate this rating system as part of a larger system to find ontology libraries on the web, retrieve ontologies from them, and assess them to select the best ontology for a particular task. An empirical evaluation in four phases shows the usefulness of the work, including a more stringent evaluation of the metrics that assess how well an ontology fits its domain and how well an ontology is regarded within its community of users. INDEX WORDS: Domain ontology, interoperability, metrics, ontology assessment, ontology evaluation, ranking, ontology, semiotics, semiotic ladder, semiotic layers AN AUTOMATED SYSTEM FOR THE ASSESSMENT AND RANKING OF DOMAIN ONTOLOGIES
Simultaneous Transmission Opportunities for LTE-LAA Co existing with WiFi in Unlicensed Spectrum from Exploiting Spatial Domain

In this thesis, we first give an intensive review on the background of LTE-LAA technology, the research status of LTE-LAA and WiFi co-existence mechanisms and 3GPP Rel. 13 standardization on LTELAA. The existing co-existence designs focus on the time-domain, frequency-domain and power-domain to achieve fairness between two systems. Simultaneous transmissions are avoided to reduce collision probability. However, by exploiting the spatial domain, we discover the possibility of simultaneous LTE-LAA/WiFi transmission opportunities as long as the interference received at the WiFi receiver is well managed. We first show the feasibility of such simultaneous transmission opportunities considering AP/UE location diversity and various coverage overlap situations between LTE-LAA small cell and WiFi AP. Then, by utilizing multi-antenna beamforming capability, we propose a more practical co-existence scheme combing DoA estimation and null steering technologies. As the lack of direct communication link between LTE-LAA and WiFi systems, we also give our design of information exchange that requires minimal modifications on current WiFi standards and with little to none extra overhead. From the discussions and simulation results, we prove the existence of such simultaneous transmission opportunities that do not bring extra impact on WiFi networks. The channel occupancy time of LTE-LAA can be greatly improved. However, problems and challenges are also identified that require future investigations.
Estudo, definição e proposta de representação de interface web visando à atividade de teste de software

O objetivo principal da Engenharia de Software e dar subsidios para desenvolvimento de software, desde a sua especiﬁcacao ate sua implantacao e manutencao, aplicando metodos, processos e ferra-mentas, buscando uma maior qualidade no software produzido. Uma das atividades para se buscar a qualidade desejada e a atividade de teste de software. Essa atividade pode se tornar bastante complexa, dependendo das caracteristicas e dimensoes do produto de software a ser desenvolvido e, desse modo, esta sujeita a diversos tipos de problemas que acabam resultando na obtencao de um produto com defeitos, prejudicando assim a qualidade do mesmo. Apesar da complexidade e das limitacoes existentes, encontram-se na literatura diferentes tecnicas que podem ser utiliza-das para gerar dados de teste para satisfazer os diversos criterios de teste de software existentes, procurando assim reduzir o custo dos testes. Porem, a geracao de dados de teste e um problema indecidivel, devido a complexidade e o tamanho de programas. Um dos fatores que aumentam a complexidade e o uso de interfaces do usuario (UI – User Interfaces), presentes em muitas aplica-coes. Essa complexidade e resultante do elevado numero de combinacoes de entrada disponivel, tornando praticamente impossivel realizar os testes UI de forma manual. Dentre as alternativas que viabilizam a automatizacao uma das mais reconhecidas e vantajosas e o teste de UI baseado em modelos. Esta tecnica passa pela construcao de um modelo a partir da estrutura da interface da aplicacao a ser testada e os dados de teste sao gerados a partir desse modelo. Porem, um fator problematico desta abordagem reside na construcao do modelo. Este processo pode ser demorado e dispendioso e, em alguns casos, pode ser bastante complicado e nao atingir um objetivo satisfatorio por nao conseguirem representar, por meio do modelo proposto, caracteristicas reais da aplicacao. Ao estudar o estado da arte de teste UI, observou-se que existem ferramentas que permitem realizar tais testes automaticamente, mas essas ainda possuem algumas limitacoes, principalmente decorrentes do modelo de representacao da interface adotado por elas. Desse modo, a proposta dessa tese e propor um modelo de representacao de UI que traga beneficios em relacao as representacoes hoje existentes na literatura. Com a proposta deste modelo e possivel representar com o maior nivel de detalhes uma interface graﬁca para aplicacoes de software. Um estudo preliminar, comparando o modelo proposto com outros disponiveis na literatura, evidencia os beneficios alcancados.
Maturity Model for Cloud Computing Transformation: Assessing an Information System's Functional Block Maturity

— IT managers and decision makers permanently need support tools to make decision for adopting new solutions and services such as cloud computing. This paper introduces a maturity assessment model of an Information System architecture functional block in the aim of outsourcing to cloud services. This model considers the fundamental requirements arising from the literature, best practices, and standards in the domain. Thus, this model provides a new added value for the opening of enterprise architectures to new technologies.
Teacher Researchers: Utilizing Archival Primary Sources

This study analyzed the experiences of elementary teachers who engaged in archival research with primary sources, then used their new knowledge and materials to create elementary curriculum. The teachers located and identified primary source material then determined its reliability. They placed the source and its author in the correct historical context and evaluated perspectives and biases. By engaging in this process, teachers developed a greater understanding of primary sources, a key component of historical thinking, advancing their subject content and pedagogical knowledge. The teachers developed lessons centered on primary sources rather than using them in a more superficial manner. They came to view primary sources as tools to: develop historical empathy, advance the teaching of multiple perspectives, and construct meaning. Further, they developed meaningful lessons that not only motivate their students, but also enhance their students’ higher order thinking skills and ability to conduct historical research.
A Survey on Various Methodologies of Automatic Text Summarization

Conversion of text-to-text, to generate summary has been a key research area now a days. Automatic text summarization reduces human effort in generating summary from text document(s) with the help of computer program. Various approaches, methods and systems have been suggested and developed so far till date. This survey focuses on some of the existing techniques of statistical document summarization as well as summarization using semantic approaches to deal with the improvements that can be done for Extractive Text
Scalable Auditory Data Signatures for Discovery Oriented Browsing in an Expressive Context

To be useful for browsing in vast multidimensional databases, auditory representations need to accommodate different levels of depth and detail: The ideas behind Scalable Auditory Data Signatures as a sonification strategy that accommodates these demands as well as the underlying concepts of quantitative and qualitative listening are presented. The implementation of these concepts within the interdisciplinary project “ATLAS in silico” is described.
Enhancing the Capacity of the Indoor 60 GHz Band Via Modified Indoor Environments Using Ring Frequency Selective Surface Wallpapers and Path Loss Models

The 60 GHz band has been selected for short-range communication systems to meet consumers’ needs for high data rates. However, this frequency is attenuated by obstacles. This study addresses the limitations of the 60 GHz band by modifying indoor environments with ring Frequency Selective Surfaces (FSSs) wallpaper, thereby increasing its utilization. The ring FSS wallpaper response at a 61.5 GHz frequency has been analyzed using both MATLAB and Computer Simulation Technology (CST) Microwave Studio (MWS) software. ‘Wireless InSite’ is also used to demonstrate enhanced wave propagation in a building modified with ring FSSs wallpaper. The demonstration is applied to Single Input Single Output (SISO) and Multiple Input Multiple Output (MIMO) systems to verify the effectiveness of FSSs on such systems’ capacity. The effectiveness of the suggested modification over delay spread has been studied for the MIMO scenario, as well as the effect of the human body on capacity. Simulation results presented here show that modifying a building using ring FSS wallpaper is an attractive scheme for significantly improving the indoor 60 GHz wireless communications band. This paper also presents and compares two large-scale indoor propagation Path Loss Models (PLMs), the Close-In (CI) free space reference distance model and the Floating Intercept (FI) model. Data obtained from ‘Wireless InSite’ over distances ranging from 4 to 14.31 m is analyzed. Results show that the CI model provides good estimation and exhibits stable behavior over frequencies and distances, with a solid physical basis and less computational complexity when compared to the FI model.
Multi-modality image registration by maximization of mutual information

Mutual information of image intensities has been proposed as a new matching criterion for automated multi-modality image registration. In this paper the authors give experimental evidence of the power and the generality of the mutual information criterion by showing results for various applications involving CT, MR and PET images. The authors' results illustrate the large applicability of the approach and demonstrate its high suitability for routine use in clinical practice.
From Phonemes to Robot Commands with a Neural Parser

The understanding of how children acquire language [1][2], from phoneme to syntax, could be improved by computational models. In particular when they are integrated in robots [3]: e.g. by interacting with users [4] or grounding language cues [5]. Recently, speech recognition systems have greatly improved thanks to deep learning. However, for specific domain applications, like Human-Robot Interaction, using generic recognition tools such as Google API often provide words that are unknown by the robotic system when not just irrelevant [6]. Additionally, such recognition system does not provide much indications on how our brains acquire or process these phonemes, words or grammatical constructions (i.e. sentence templates). Moreover, to our knowledge they do not provide useful tools to learn from small corpora, from which a child may bootstrap from. Here, we propose a neuro-inspired approach that processes sentences word by word, or phoneme by phoneme, with no prior knowledge of the semantics of the words. Previously, we demonstrated this RNN-based model was able to generalize on grammatical constructions [7] even with unknown words (i.e. words out of the vocabulary of the training data) [8]. In this preliminary study, in order to try to overcome word misrecognition, we tested whether the same architecture is able to solve the same task directly by processing phonemes instead of grammatical constructions [9]. Applied on a small corpus, we see that the model has similar performance (even if a little weaker) when using phonemes as inputs instead of grammatical constructions. We speculate that this phoneme version could overcome the previous model when dealing with real noisy phoneme inputs, thus improving its performance in a real-time human-robot interaction.
The CNN universal machine: an analogic array computer

A new invention, the cellular neural network (CNN) universal machine and supercomputer, is presented. This is the first algorithmically programmable analog array computer having real-time and supercomputer power on a single chip. The CNN universal machine is described, emphasizing its programmability as well as global and distributed analog memory and logic, high throughput via electromagnetic waves, and complex cells that may be used also for simulating a broad class of PDEs. Its implementation, the CNN universal chip, is also described, along with its use of a multichip supercomputer. Other types of hardware implementations are also briefly discussed. Details of the algorithmic aspects of the new type of analogic (analog logic) algorithms, as well as the analogic software (language, compiler, machine code, etc.) are explained, along with a brief description of the available CNN workstation for implementing and simulating these new concepts. A broad range of applications is reviewed, including neuromorphic computing, programmable physics, programmable chemistry, and programmable bionics. >
Line recognition

The use of edge detection and localizing filters for the recognition of lines (narrow contrasting strips) in visual scenes is shown to produce systematic errors while being suboptimum with respect to noise. The authors derive optimum filters for the detection and localization of lines based on matched filtering in the line normal direction and a Wiener filter in the direction tangential to the line. The matched filters for the detection and localization of line normals in white noise have the form of the system response and its first derivative, respectively. The orthogonal least-restrictive Wiener filter is also closely approximated by the form of the system response in cased where Gaussian response and white noise dominate. Close approximations to the optimum filters for line recognition under these common conditions are readily realized. Line filters were integrated with the Boie-Cox edge detector. Results for images with mixed lines and edges show that the integrated Boie-Cox system is free of the systematic errors common to other edge recognition systems. <<ETX>>
Theoretical mathematical model of non-invasive flow quantification for future implementation in routine clinical MRI

Automated push-button medical analysis using quantitative multiparametric standard scales will offer the possibility of efficient fast medical diagnosis in a precise and accurate manner. Magnetic Resonance Imaging (MRI) offers complex geometrico-physicochemical analysis of the physio-anatomy of interest. Most imaging protocols for the quantitative multiparametric MRI have already been implemented clinically, but flow assessment still remains a problem, especially when evaluated without contrast agents. A simple method for flow quantification using MRI without contrast agents is described in this study. The proposed method has the potential of non-invasive flow quantification, produced offline from MRI images acquired in less than one minute.
Structured Control for Future European Launchers

Control of a flexible launcher during the atmospheric flight phase is a highly challenging control problem involving multiple and concurrent design requirements: stability (stabilization of unstable rigid dynamics, sloshing modes and flexible structural modes), performance (guidance tracking, structural load minimization) and robustness (physical parameter uncertainties and accommodation to multiple vehicle configurations) on a non-stationary system. This paper focuses on co-funded AG/CNES research activities on the development of an advanced modular control strategy using recent advances in structured control design. We demonstrate here that structured H∞ synthesis could give a gain scheduling solution to full timevarying flexible launcher control problems during the non-stationary ascent phase, enabling load performance improvement between complex sets of requirements, and, design cost improvements through simplification of the tuning process. We also present a generic framework for rapid control design that is now applicable both for European launcher families already in activity (with existing S/W and fixed controller structure) and for future expendable and reusable launchers.
Solving Capacitated Closed Vehicle Routing Problem with Time Windows (CCVRPTW) using BRKGA with local search

The main issue in vehicle routing problem (VRP) is finding the shortest route of product distribution from the depot to outlets to minimize total cost of distribution. Capacitated Closed Vehicle Routing Problem with Time Windows (CCVRPTW) is one of the variants of VRP that accommodates vehicle capacity and distribution period. Since the main problem of CCVRPTW is considered a non-polynomial hard (NP-hard) problem, it requires an efficient and effective algorithm to solve the problem. This study was aimed to develop Biased Random Key Genetic Algorithm (BRKGA) that is combined with local search to solve the problem of CCVRPTW. The algorithm design was then coded by MATLAB. Using numerical test, optimum algorithm parameters were set and compared with the heuristic method and Standard BRKGA to solve a case study on soft drink distribution. Results showed that BRKGA combined with local search resulted in lower total distribution cost compared with the heuristic method. Moreover, the developed algorithm was found to be successful in increasing the performance of Standard BRKGA.