Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting treatment outcomes in dysarthria through speech feature analysis.

Increasing loudness and reducing speech rate are common behavioural speech modifications used in the treatment of dysarthria. Both strategies provide a promising basis for intervention, but studies have reported considerable inter-participant variability in the intelligibility benefit gained. While neurologic aetiology and the Mayo classification system are generally used to group participants with dysarthria in treatment studies, there is little evidence that this approach provides meaningful insight into which individuals benefit from particular speech modification strategies. This thesis posited that differences in baseline speech symptoms between speakers could underlie significant disparities in treatment outcomes. Hence the overall aim, addressed in the final phase of this thesis, was to identify whether measurements of individuals’ baseline speech could be used to predict their intelligibility gains in response to cues to speak louder and reduce speech rate. To begin, the first two phases of this thesis addressed methodological issues in the assessment of speech features. The purpose of these investigations was to refine the methods of acoustic and perceptual analysis employed in the final phase, and test their application on New Zealand speakers with and without dysarthria. Phase one of this thesis focused on vowel dispersion and speech duration in healthy, older speakers of New Zealand English (NZE), as it was unknown how NZE’s unique dialect might affect commonly used metrics of vowel articulation. A group of 149 NZE speakers aged 65 to 90 years read a standard passage. Two formant measurements, from selected [i:], [ɐ:], and [o:] vowels, were used to calculate two measurements of Vowel Space Area (VSA) for each speaker. Average vowel duration was calculated from segments across the passage. Results demonstrated that measures of VSA, adapted for NZE, produced a similar range of values to those reported in previous studies of speakers from the United States. In addition, a statistically significant relationship existed between speakers’ average vowel durations and VSA measurements indicating that, on average, speakers with slower speech rates produced more acoustically distinct speech segments. As expected, increases in average vowel duration were found with advancing age. However, speakers’ formant values remained unchanged. The second phase explored the ability of different acoustic and perceptual measures to index speakers’ baseline (i.e., habitual) dysarthria severity. Sixty-one speakers (17 healthy individuals and 44 speakers with dysarthria) read a standard passage. To obtain acoustic data, different formant extraction points and frequency measures were trialled. VSA and an adapted Formant Centralization Ratio (FCR) were calculated using first and second formants of the speakers’ [ɐː], [iː] and [oː] vowels. Twenty-eight listeners completed separate ratings
Distributed Scheduling Approaches in Wireless Sensor Network

Wireless sensor network (WSN) is a resource constrained network system.Many kinds of scheduling approaches have been proposed to improve the performances of WSN.In this paper,the design principles and classification methods for distributed scheduling approaches of WSN are summarized.And the scheduling approaches are discussed and classified with respect to scheduling object.The fundamental mechanisms of some typical approaches are discussed further and the characteristics of each class are analyzed in detail.Comparison between the designed objects and the performance features of these scheduling approaches are presented.Finally,the current research situations for distributed scheduling approaches of WSN are summarized and the key aspects for further research are also suggested.
Wavelet theory and its applications

Foreword. Preface. 1. Introduction/Background 2. The Wavelet Transform. 3. Practical Resolution, Gain, and Processing Structures. 4. Wavelet Theory Extentions and Ambiguity Functions. 5. Linear Systems Modelling with Wavelet Theory. 6. Wideband Scattering and Environmental Imaging. Related Research. References. Subject Index.
Simulación y control de la velocidad y par electromagnético de un motor de inducción trifásico: Un enfoque a vehículos eléctricos

En este estudio se presentan los resultados obtenidos en simulación y control de un motor de inducción trifásico (MTI) utilizando MATLAB/Simulink. El análisis comprende el estudio de la respuesta transitoria del MTI en lazo abierto y en lazo cerrado utilizando dos tipos de controladores: Control Directo de Par (DTC) y Control Escalar. Los resultados más relevantes de este trabajo se dan al evaluar el desempeño de cada controlador, que tienen como objetivo principal seguir el perfil de velocidad deseado, atendiendo a las respuestas dinámicas de velocidad mecánica del rotor, par electromagnético, flujo magnético y corrientes de estator y rotor, así como de los voltajes de excitación. Se consideran dos escenarios de operación: en el primer caso el MTI opera sin carga mecánica y en el segundo opera como sistema de propulsión de un vehículo con parámetros mecánicos cercanos a los de un automóvil convencional. Así mismo se demostró que el DTC brinda al sistema de un comportamiento dinámico más óptimo minimizando los errores de seguimiento de velocidad y par electromagnético, minimizando el rizado en los valores de par y flujo estimado.
An Adaptive Vector Quantization Method for Image Compression

Image compression is to reduce redundancy of the image data in order to store or transmit data in an efficient form. Compression is carried out for the following reasons about reduce, the storage requirement, processing time and transmission duration. The most powerful and quantization technique used for the image compression is vector quantization (VQ). The Existing methods Linde-Buzo-Gray (LBG) and Fast Back Propagation (FBP) algorithm are presented. In existing methods, the compression ratio is decreased. The proposed method adaptive vector quantization is used to analyze for image vector quantization (VQ). The performance of proposed work is analyzed using the factors SNR, MSE, PSNR and CR. The experimental work using MatLab shows that the proposed scheme is efficient and produced expected result.
Création d'un espace conceptuel par analyse de données contextuelles

The computerized treatment of numerical information requires a system of representation. The objective of the method presented in this paper is the entirely automated generation of a valid and compact system of representation of the information contained in documents. One hopes to group words referring itself on the same subject, the same idea in order to use these “concepts” to model information rather than to use the representation of these concepts. The algorithm proposed generates a vector space of the concepts by gathering dimensions of a vector space of the terms. This regrouping is carried out by comparison of the parameters related to the context of appearance of the terms in the treated documents. The reduction of dimension of the space used will allow a faster data processing and requiring a less important memory capacity. This type of improvement being typically that required within the framework of real system, tallies of the application for which the method was developed.
Topic Modeling as an Analysis Tool to Understand the Impact of the Iraq War on the Iraqi Blogosphere

The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. Topic Modeling as an Analysis Tool to Understand the Impact of the Iraq War on the Iraqi Blogosphere Thesis directed by Professor Leysia Palen Social media provide a democratized platform for expressing one's opinion or viewpoint. The everyday discussions that people have with their families, friends and colleagues became available through blogging services. The emergence of the blogging activity made the classic ethnographic approaches more difficult to deploy. The use of these methods becomes even more problematic when the available data contain a wide variety of languages. This thesis proposes the use of topic modeling as a method for quantitatively analyzing crawled blogs that were created by Iraqi citizens and active over a period of 8 years since the beginning of the Iraq war in 2003. This document presents how data were collected, the way dominant languages were separated in different datasets, the limits of using classification and clustering techniques, the benefits of employing topic modeling, and the evaluation of this technique.
The decision exploration lab: supporting the business analyst in understanding automated decisions

A Decision Management System (DMS) provides means to model and automate enterprise decisions and they are applied in a wide range of industries, among which health care, commerce, insurance, finance and transportation. These systems make millions of decisions each day without direct human supervision, impacting the life of millions of people and impacting economies at a large scale. The multiplicative effect of decision automation provides the opportunity to fine-tune the decision system. By analyzing its global and emerging properties rather than focusing on the details of each decision, the system as a whole can be better adapted to the reality it models. Like expert systems, DMSs provide a clear separation of decision logic, information related to individual decisions and decision execution. These data spaces contain a wealth of information related to the structure and functioning of a DMS. In this thesis various ways are explored to visualize and analyze this data in order to help a business user to gain a deeper understanding of automated decisions. To address the problem of understanding the global and emerging properties of automated decision making systems, we combine interactive analysis of the decision data with analysis of the decision logic. We present a visual analytics system, the Decision Exploration Lab (DEL), which provides a verbal analysis mode and a visual decision exploration mode. In verbal mode the user can make selections on past decisions using controlled natural language. In visual de- cision exploration mode, the decision data is analyzed using Multiple Correspondence Analysis (MCA). The analysis results are visualized using interactive techniques to show the important structure of the decision data to the user. Correlated concepts can be clustered at a level of granularity that suits the needs of the business analyst. Clustered concepts can next be linked to the rules of the decision logic that are relevant for the subset of decisions which match these concepts. We evaluated our approach with two use case scenarios from the car insurance industry. Apart from the above, we propose a number of technical contributions, enhancements and extensions to information visualization methods, for multivariate categorical data. Firstly, we present a generic algorithm to generate all well-known treemap layouts as well as other rectangular space-filling layouts. Secondly, we present explanatory and interactive visualization techniques to support interpretation and usage of MCA. Thirdly, we present labeling and scale adjustment techniques in order to improve the usability of 2D-plots.
Choosing a Good Toolkit, I: Formulation, Heuristics, and Asymptotic Properties

The problem of choosing an optimal toolkit day after day, when the distribution of values of different toolkits is uncertain and can only be observed by carrying different toolkits, is a multi-armed bandit problem with non-independent arms. Accordingly, except for very simple specifications, this problem cannot (practically) be solved. Decision makers facing this problem presumably resort to “sensible” decision heuristics, employing past experience and, perhaps, what they know about the problem. In this paper, Part I of a two-part study of this situation, we provide a general formulation the problem, describe a variety of heuristics, and provide some theoretical results about how the heuristics perform asymptotically. (In the second paper, we compare the performance of these heuristics through simulations.)
Implementation of Demo Program for Visual Communication in Compliance with MPEG-21 Part 22: User Description

ISO/IEC JTC1/SC29WG11 MPEG has been standardizing UD(user description) to give a user personalized recommendation services. Besides, CD(context description), service description(SD), and recommendation description(RD) are recently being standardized by UD Adhoc Group in MPEG with an advanced UD to cope with needs of current and upcoming services such as augmented reality and social network. The descriptions was reflected to MPEG-UD WD(Working Draft) at MPEG 107th meeting and the document was finally approved as international standard by national bodies with standard number(ISO/IEC IS 21000-22 UD) at 114th MPEG meeting. In addition, reference software WD to validate conformance of UD standard was approved at 113th MPEG meeting. In this paper, we developed a demo program for visual communication according to guideline defined in reference software WD to validate the reference software as well as UD standard.
User-Oriented Redundancy Elimination Mechanism in Enterprise WLANs

The rapid spreading of mobile devices and smartphones has promoted the deployment of enterprise WLANs. This research collects read traces from over 10 000 WiFi users in one university in Shanghai. Through intensive data analysis, it finds that there exists more than 24% redundancy traffic in WLANs. By mining the patterns of data set, a user-oriented redundancy elimination strategy is proposed to allocate different cache sizes to different users adaptively. Simulation results show that user-oriented redundancy elimination
Designing Intelligent Robots

Traditionally, in robotics, artificial intelligence, and neuroscience, there has been a focus on the study of the control or the neural system itself. Recently there has been an increasing interest into the notion of embodiment in all disciplines dealing with intelligent behavior, including psychology, philosophy, and linguistics. In this paper, we explore the far-reaching and often surprising implications of this concept. While embodiment has often been used in its trivial meaning, i.e. „intelligence requires a body“, there are deeper and more important consequences, concerned with connecting brain, body, and environment, or more generally with the relation between physical and information (neural, control) processes. It turns out that, for example, robots designed by exploiting embodiment are frequently simpler, more robust and adaptive than those based on the classical control paradigm. Often, morphology and materials can take over some of the functions normally attributed to control, a phenomenon called “morphological computation”. It can be shown that through the embodied interaction with the environment, in particular through sensory-motor coordination, information structure is induced in the sensory data, thus facilitating perception and learning. A number of case studies are presented to illustrate the concept of embodiment. We conclude with some speculations about potential lessons for robotics.
Dependable systems for Sentient Computing

Dependable Systems for Sentient Computing Andrew Rice Computers and electronic devices are continuing to proliferate throughout our lives. Sentient Computing systems aim to reduce the time and effort required to interact with these devices by composing them into systems which fade into the background of the user’s perception. Failures are a significant problem in this scenario because their occurrence will pull the system into the foreground as the user attempts to discover and understand the fault. However, attempting to exist and interact with users in a real, unpredictable, physical environment rather than a wellconstrained virtual environment makes failures inevitable. This dissertation describes a study of dependability. A dependable system permits applications to discover the extent of failures and to adapt accordingly such that their continued behaviour is intuitive to users of the system. Cantag, a reliable marker-based machine-vision system, has been developed to aid the investigation of dependability. The description of Cantag includes specific contributions for marker tracking such as rotationally invariant coding schemes and reliable back-projection for circular tags. An analysis of Cantag’s theoretical performance is presented and compared to its real-world behaviour. This analysis is used to develop optimised tag designs and performance metrics. The use of validation is proposed to permit runtime calculation of observable metrics and verification of system components. Formal proof methods are combined with a logical validation framework to show the validity of performance optimisations.
Optimizing communication performance of web services using differential deserialization of soap messages

Web services have recently emerged as a de facto standard for building Grid and distributed computing infrastructures and applications. SOAP, a simple, interoperable, robust, and extensible protocol for the exchange of messages, is the most widely used communication protocol in the Web services model. SOAP's XML-based message format hinders its performance, thus making it unsuitable in many scientific applications. The deserialization of SOAP messages, which includes processing of XML data and conversion of strings to in-memory data types, is the major performance bottleneck in a SOAP message exchange. The contributions of this dissertation address SOAP's poor deserialization performance with the design and implementation of differential deserialization (DDS), an optimization technique that exploits similarities between incoming messages to reduce deserialization time. DDS is a fully SOAP compliant technique, and requires no changes to a SOAP client. A performance study demonstrates that DDS can result in performance improvements up to 226% for some Web services. When DDS is used with differential serialization (DS), its sender-side analog, the performance study demonstrates even more significant performance improvements.
A NEW MECHANISM FOR RISKLESS AUTHORIZED DEDUPLICATION IN CLOUD

Data de duplication is among important data compression approaches for getting rid of duplicate copies of repeating data, and it has been broadly utilized in cloud storage to lessen the quantity of space for storage and save bandwidth. To safeguard the confidentiality of sensitive data while supporting de duplication, the convergent file encryption method has been suggested to secure the information before outsourcing. To higher safeguard data security, this paper helps make the first make an effort to formally address the issue of approved data de duplication. Not the same as traditional de duplication systems, the differential rights of customers are further considered in duplicate check aside from the data itself. Like a evidence of concept, we implement a prototype in our suggested approved duplicate check plan and conduct test bed experiments using our prototype. We reveal that our suggested approved duplicate check plan incurs minimal overhead in comparison to normalcy procedures.
Joint Balanced Routing and Energy Harvesting Strategy for Maximizing Network Lifetime in WSNs

Nowadays, wireless sensor networks (WSNs) are becoming increasingly popular due to the wide variety of applications. The network can be utilized to collect and transmit numerous types of messages to a data sink in a many-to-one fashion. The WSNs usually contain sensors with low communication ability and limited battery power, and the battery replacement is difficult in WSNs for large amount embedded nodes, which indicates a balanced routing strategy is essential to be developed for an extensive operation lifecycle. To realize the goal, the research challenges require not only to minimize the energy consumption in each node but also to balance the whole WSNs traffic load. In this article, a Shortest Path Tree with Energy Balance Routing strategy (SPT-EBR) based on a forward awareness factor is proposed. In SPT-EBR, Two methods are presented including the power consumption and the energy harvesting schemes to select the forwarding node according to the awareness factors of link weight. First, the packet forwarding rate factor is considered in the power consumption scheme to update the link weight for the sensors with higher power consumption and mitigate the traffic load of hotspot nodes to achieve the energy balance network. With the assistance of the power consumption scheme, hotspot nodes can be transferred from the irregular location to the same intra-layer from the sink. Based on this feature, the energy harvesting scheme combines both the packet forwarding rate and the power charging rate factors together to update the link weight with a new battery charging rate factor for hotspot nodes. Finally, simulation results validate that both power consumption and energy harvesting schemes in SPT-EBR achieve better energy balance performance and save more charging power than the conventional shortest path algorithm and thus improve the overall network lifecycle.
The Applicability of Artificial Intelligence in International Law

Law reacts to the progression of scientific technology in the end. Though conservative, changes are beginning to take place due to Artificial Intelligence (AI). AI is automating conventional legal works, creating a new industry namely Legal-Tech. This paper investigates the characteristics and flow of legal-AI and computational law while focusing on the applicability of AI to international law. Mainly, the paper reviews three critical areas: dispute resolution, trial prediction, and machine translation, respectively. International law has different characteristics than the domestic law applied in each country. Unlike domestic law, international law has not been aggregated from a pandect, and it is a still daunting task to draw any meaningful insights for further analysis due mainly to limited data (i.e., trial cases and precedents). Nevertheless, AI is already penetrating the legal ecology system, and international law would eventually accept the influx of such changes exhibiting greater force.