Miracle-dz/UniFAR-FTUs huggingface dataset:
Using phonetic knowledge in tools and resources for Natural Language Processing and Pronunciation Evaluation

This thesis presents tools and resources for the development of applications in Natural Language Processing and Pronunciation Training. There are four main contributions. First, a hybrid grapheme-to-phoneme converter for Brazilian Portuguese, named Aeiouadô, which makes use of both manual transcription rules and Classification and Regression Trees (CART) to infer the phone transcription. Second, a spelling correction system based on machine learning, which uses the trascriptions produced by Aeiouadô and is capable of handling phonologically-motivated errors, as well as contextual errors. Third, a method for the extraction of phonetically-rich sentences, which is based on greedy algorithms. Fourth, a prototype system for automatic pronunciation assessment, especially designed for Brazilianaccented English. Palavras-chaves natural language processing; pronunciation training; text-to-speech; spelling correction; corpus balancing; automatic pronunciation assessment.
Improved Model Checking Techniques for State Space Analysis of Gene Regulatory Networks

A better understanding of the behavior of a cell, as a system, depends on our ability to model and understand the complex regulatory mechanisms that control gene expression. High level, qualitative models of gene regulatory networks can be used to analyze and characterize the behavior of complex systems, and to provide important insights on the behavior of these systems. In this chapter, we describe a number of additional functionalities that, when supported by a symbolic model checker, make it possible to answer important questions about the nature of the state spaces of gene regulatory networks, such as the nature and size of attractors, and the characteristics of the basins of attraction. We illustrate the type of analysis that can be performed by applying an improved model checker to two well studied gene regulatory models, the network that controls the cell cycle in the yeast S. cerevisiae, and the network that regulates formation of the dorsal-ventral boundary in D. melanogaster. The results show that the insights provided by the analysis can be used to understand and improve the models, and to formulate hypotheses that are biologically relevant and that can be confirmed experimentally. DOI: 10.4018/978-1-60566-685-3.ch016
A Behavioural Model for Consumer Reputation.

In recent years, substantial academic research has focussed on solving the problem of email spam using reputation mechanisms (e.g., [1] and [2]) while others [3] have discussed the generalised problem of any unsolicited network transaction in client-server scenarios. We propose a reputation model based on behavioural history as a solution to this problem. We use behavioural history of long-lived network identities to develop local and global reputation. This helps the provider to make decisions regarding future network transactions. The decisions are either binary (e.g., provide service or cutoff) or more fine grained where the provider can vary levels of service. A declarative specification of behaviour quality of network identities in relation to relevant terms in the service contract is being developed, which will relate network activities to discrete units of good or bad behaviour. In most cases, clients have their own identities or they are identified as members of a group (e.g., customers of a particular Internet Service Provider). In situations where the identity of the client is anonymous and cannot be associated with any group, best effort service will be provided as a fall-back option. The term score is used to denote reputation value of the consumer, while the term rank is used for the provider. We have experimented with mathematical functions to best represent the reputation response to behaviour. We are using exponential saturation, exponential decay and linear patterns with adjustable slope (change) parameters. A local reputation response (ordinate) in relation to cumulative behaviour (abscissa) is illustrated in Fig. 1. The score saturates at positive or negative saturation levels (solid curves) with good and bad behaviour respectively. Good score drops with bad behaviour, and bad score gets better with good behaviour (dotted curves). There is also a score expiring mechanism, which 'decays' good reputation to positive default and bad reputation to negative default, respectively , over time. This is represented using quadratic decay patterns. The local scores are globally aggregated for collaborative inferences. A global score can initialise a local score if no prior local score is available. The local scores are securely submitted to and stored in a score aggregation system. The global score of a consumer is calculated, at query-time, over a window of scores submitted by providers. The impact of each submission is weighed by the rank of the provider. Newer score submission from the same provider overrides the corresponding previous submission. There is time …
Karyometric Analysis of Squamous Metaplasia, Dysplasia and Squamous Cell Carcinoma of the Lung

Summary The sequence of precursor lesions for squamous cell carcinoma may be hyperplasia-metaplasia-dysplasia-carcinoma in situ. The aim of this study was to perform a karyometric analysis of squamous metaplasia, moderate dysplasia and squamous cell lung carcinoma. Bronchoscopic biopsies of normal mucosa in chronic bronchitis patients (n=10), squamous metaplasia (n=10), moderate dysplasia (n=11), squamous cell lung carcinoma (n=48), and normal appearing mucosa surrounding carcinoma (n=11) were retrieved. Three nuclear variables were estimated using an image analysis system. The mean equivalent diameter, nuclear area and volume of equivalent sphere of squamous cell lung carcinoma were significantly larger than in moderate dysplasia, squamous metaplasia and normal bronchial mucosa. Also, the values of equivalent diameter, nuclear area and volume of equivalent sphere were significantly larger in normal appearing mucosa surrounding carcinoma compared to normal mucosa in chronic bronchitis patients. Karyometric analysis may be a helpful ancillary tool in distinguishing squamous cell lung carcinoma from dysplasia, and dysplasia from squamous metaplasia in bronchoscopic biopsy specimens. Sažetak Sekvence prekursornih lezija planocelularnog karcinoma mogu biti hiperplazija-metaplazija-displazija- karcinom in situ. Cilj rada bio je da se izvrši kariometrijska analiza skvamozne metaplazije, displazije umerenog gradusa i planocelularnog karcinoma pluća. Analizirane su bronhoskopske biopsije normalne mukoze kod bolesnika sa hroničnim bronhitisom (n=10), skvamoznom metaplazijom (n=10), umerenom displazijom (n=11), planocelularnim karcinomom (n=48) i "na izgled normalnom” mukozom u okolini karcinoma (n=11). Ispitivana su tri nuklearna parametra uz pomoć sistema za analizu prikaza. Prosečni ekvivalentni nuklearni dijametar, area i volumen ekvivalentne sfere planocelularnog karcinoma bili su signifikantno veći nego kod umerene displazije, skvamozne metaplazije i normalne bronhijalne mukoze. Vrednosti ekvivalentnog dijametra, areala i volumena ekvivalentne sfere jedara bili su signifikantno veći u “na izgled normalnoj” mukozi kod bolesnika sa planocelularnim karcinomom u odnosu na normalnu mukozu kod bolesnika sa hroničnim bronhitisom. Kariometrijska analiza može biti korisna pomoćna metoda u diferenciranju planocelularnog karcinoma od displazije i displazije od skvamozne metaplazije na bronhoskopskim biopsijskim uzorcima.
Developing Web Services with Apache CXF and Axis2

If you'd like to learn how to create web services (in particular, using Apache CXF or Axis2) and make some sense of various standards like JAX-WS, JAX-RS, JAXB, SOAP, WSDL, REST, MTOM, WS-Security, WS-Policy, XML Encryption and XML Signature, then this book is for you. Why? 1) It has a tutorial style that walks you through in a step-by-step manner.2) It is concise. There is no lengthy, abstract description.3) Many diagrams are used to show the flow of processing and high level concepts so that you get a whole picture of what's happening.4) It contains working code.5) The first two chapters are freely available on http://www.agileskills2. org. You can judge it yourself.
Chronic obstructive pulmonary disease: symptoms and signs

Despite the uncertainties about the relative roles of different pathophysiological processes in chronic obstructive pulmonary disease (COPD), there is now a uniform approach to diagnosing this disorder [1–3], which emphasises the presence of both symptoms and objective evidence of relatively fixed airflow limitation. The presence of abnormal physical signs helps with the grading of severity of the abnormality, but is not necessary for the diagnosis itself. Whilst pathological changes may be present in asymptomatic individuals, clinicians meet patients when they develop symptoms. However, the relative importance of a particular symptom varies as the disease progresses, as do the coexisting physical signs. One scheme relating airflow limitation to symptoms and signs is shown in table 1. In the present chapter, the current knowledge about the processes underlying the symptoms and signs typically seen in COPD will be reviewed, and how this might affect the presentation of this common illness will be considered.
COMPARATIVE STUDY OF SHIRO ABHYANGA WITH PRAPOUNDARIKADI TAILA AND KARANJA TAILA IN THE MANAGEMENT OF DARUNAKA: A RANDOMIZED CONTROLLED TRIAL

Background: Dandruff is a common disorder affecting the scalp caused by yeast Pityrosporum. Dandruff cannot be completely eliminated but can only be managed and effectively controlled. Dandruff can be compared to Darunaka (Dandruff) based on the features explained in Ayurvedic medicine. Objectives: To evaluate and compare the effects of shiro abhyanga with Prapoundarikadi taila and Karanja taila in the management of Darunaka. Design: This was a randomized comparative clinical study. In Group A, Prapoundarikadi taila shiroabhyanga (Head massage) and in Group B, Karanja taila shiroabhyanga (Head massage) was done for thirty days, daily once in the evening. After the completion of treatment, follow up was done once in fifteen days for a period of 2 months. Results: Statistically significant results were seen in the reduction of severity in kandu, Group A (50.98%) compared to Group B (26.53), (p<0.001), keshachyuti (p<0.001), Group A (41.30%), Group B (20.45%), rookshata Group A (49.05%) compared to Group B (36.53%) (p<0.001) and twak sputana with p<0.001, Group A (48.07%) compared to Group B (20%). Conclusions: Prapoundarikadi taila shiro abhyanga showed statistically significant results in pacifying the symptoms of Darunaka (Dandruff) and marked reduction in clinical symptoms within two months duration compared to karanja taila shiroabhyanga.
Estudi en l’espai i el temps de poblacions del cranc marí Liocarcinus depurator mitjançant el gen mitrocondrial coi

Trabajo final presentado por Victor Ojeda Martin para el Master en Genetica y Genomica de la Universitat de Barcelona (UB), realizado bajo la direccion del Dr. Francesc Mestres Naval de la Universitat de Barcelona (UB) y del Dr. Pere Abello Sala del Institut de Ciencies del Mar (ICM-CSIC). -- 30 pages, 6 figures, 3 tables, supplemental material
IMAGE PROCESSING WITH CUDA

This thesis puts to the test the power of parallel computing on the GPU against the massive computations needed in image processing of large images. The GPU has long been used to accelerate 3D applications. With the advent of high level programmable interfaces, programming to the GPU is simplied and is being used to accelerate a wider class of applications. More specifically, this thesis focuses on CUDA as its parallel programming platform. This thesis explores on the possible performance gains that can be achieved by using CUDA on image processing. Two well known algorithms for image blurring and edge detection is used in the experiment. Benchmarks are done between the parallel implementation and the sequential implementation.
Evaluating the Security and Usability of Emoji-Based Authentication

With the increasing digitization of the world, there is a growing need to prove one’s identity and to restrict access to both personal and corporate data. Passwords have several drawbacks, but are still the preferred choice for this purpose. Motivated by the fact that the human brain remembers visual information better than text, graphical password schemes – such as the Android Pattern Lock – have been proposed as an alternative to traditional passwords. Emojis have become an inherent part of almost every digital text message. More than 2700 emojis are currently available, and this number is constantly increasing. The huge amount of characters can provide passwords with higher security than their text-based equivalents. Only limited research on emoji-based authentication exists, making it an interesting subject to study. In this project, a literature study on the use of emojis as an alternative to PIN entry and text passwords was conducted. By analyzing the current state of emoji-based authentication, a novel password scheme called EmojiStory was proposed. In EmojiStory passwords are created from predefined stories and emojis selected by the user. The security and usability of the system was evaluated through two online surveys, in which more than 1,700 participants took part. The results from the surveys suggest that EmojiStory offers good usability. The emoji passwords are easy to remember, password creation and login are fast, and a positive user experience is provided. The results also indicate that EmojiStory offers better security than PIN. However, certain emojis were preferred by the participants. Therefore, further research is needed to compare observed bias in the passwords with that of other authentication systems. We also advise that further studies on the memorability provided by EmojiStory should be conducted.
A Survey on Learning System Applications in Energy System Modeling and Prediction

: Learning Systems (LS) such as machine learning, statistical pattern recognition and neural networks are computer programs that can learn from sample data and develop a prediction model that makes prediction for new cases. The most important think related with a prediction model is to achieve results as closer as to real situation while making predictions. This is important because being closer to real results help to reduce the costs of feasibility studies in system installation. The performance of Learning Systems has been raised in latest years such as it sometimes exceeds the performance of humans. That’s why the applications of Learning Systems have been increased in many areas. This paper reviews the present applications of Learning Systems in energy system modeling and prediction especially in renewable energy systems such as wind and solar. The aim of this paper is to create a vision for researchers by gathering the present applications and outline their merits and limits and the prediction of their future performance on specific applications.
Deriving a Model of the Necessity to Hospitalize Nursing Home Residents

Although often important to recover from acute medical problems and exacerbations of chronic illness, hospitalizations can be traumatic for nursing home residents and costly for payers. It is important that unnecessary hospitalizations are avoided wherever possible. The authors derived and validated a diagnosis-based model to estimate the clinical necessity of hospitalizing nursing home residents with common conditions using data from an expert panel survey. Model validation involved a linked minimum data set—hospitalization claims data set. The expert panel of 12 experienced geriatricians rated the necessity of hospitalization for 1,948 clinical scenarios containing diagnoses, cognitive and functional status, age, gender, and advance directives. Primary diagnoses with the highest average necessity scores were respiratory failure, acute myocardial infarction, hip fracture, and brain injury. The secondary diagnosis-primary diagnosis interaction with the greatest impact was gastrointestinal bleed on gastroenteritis. Poor cognitive function and presence of an advance directive lowered the risk of hospitalization.
Analysing TDoA Localisation in LoRa Networks

The IoT contains billions of interconnected devices and is only growing larger by the day. These devices often need to operate for years while keeping mobile objects, such as animals or vehicles, connected to a larger system. Therefore they will be battery-powered, energy efficient and, their position will be tracked. Therefore, connecting these devices requires low-power, long-range communication that can also be used for localisation. Because of the scale of the IoT industry, manufacturing and infrastructure costs need to be considered. The low cost, long range and energy efficiency that is required exempts many wireless communication and localisation solutions such as WiFi, GPS and Bluetooth because they are not as suitable as Low-Power Wide-Area Networks (LPWAN's). LoRa is a LPWAN technology that is both Long-Range and cost effective. Therefore, the objective of this thesis is to use a LoRa network for our localisation algorithms. In this work we show that signal strength data becomes turbulent when communicating over a large, urban area. Therefore we evaluate Time Difference of Arrival (TDoA)-based localisation algorithms, including a novel area-based algorithm that we developed. We evaluate the localisation algorithms on a proprietary LoRa network which also provides a localisation service that we use as a benchmark. We evaluate the performance of the algorithms over a large, mostly urban, region of The Netherlands. Using mobile LoRa devices, we show that for 80\% of cases, our proposed algorithm has a position error less than 925m. We also show that the other localisation methods, including the proprietary localisation service, have a larger maximum position error for the same portion of cases. This work contributes a localisation algorithm that can compete against proprietary geolocation services, such as Sigfox and KPN's services, in many applications.
Book Reviews: The Syntactic Process

In this book Mark Steedman argues that the surface syntax of natural languages maps spoken and written forms directly to a compositional semantic representation that includes predicate-argument structure, quantification and information structure without constructing any intervening structural representation. His purpose is to construct a principle theory of natural grammar that is directly compatible with both expalantory linguistic accounts of a number of problematic syntactic phenomena and a straightforward computational account of the way sentences are mapped onto represenations of meaning. The radical nature of Steedman's proposal stems from his claim that much of the apparent complexity of syntax, prosody and processing follows from the lexical specification of the grammar and from the involvement of a small number of universal rule-types for combining predicates and arguments. These syntactic operations are related to the combinators of Combinatory Logic, engendering a much freer definition of derivational constituency than is traditionally assumed. This property allows Combinatory Categorical Grammar to capture elegantly the structure and interpretation of coordination and intonation contour in English as well as some well-known interactions between word order, coordination and relativization across a number of other languages. It also allows more direct compatibility with incremental semantic interpretation during parsing. The book covers topics in formal linguistics, intonational phonology, computational linguistics and experimental psycholinguistics, presenting them as an integrated theory of the language faculty in a form accessible to readers from any of those fields.
Calculating the number of direct lightning strokes to tall structures using leader progression model and particle swarm optimisation (PSO) algorithm

ABSTRACT In this paper, an approach based on a combination of leader progression model and particle swarm optimisation (PSO) algorithm is proposed to calculate the number of direct lightning strokes to tall structures. Here, beside high accuracy, computing time is reduced. This method can be applied to compare lightning vulnerability of different points on tall structures. In the proposed approach, the riskiest position and current range of lightning corresponding to vulnerable points on the structure are determined one after another. The lightning performance of three tall adjacent structures in Kuala Lumpur is evaluated as a case study, and the results were compared with those of previous studies. The simulation results confirm the merits of the proposed method.
An vertical layered space-time coding and the symbol detection

Recent results in information theory have demonstrated the enormous potential of wireless communication systems with antenna arrays at both the transmitter and receiver. To exploit this potential, vertical layered space-time codes is attractive for its relative simplicity and robust high capacity. Thus far, vertical layered space-time code assumed that perfect estimates of current channel fading conditions are available at the receiver. In certain situations, however, it may be difficult or costly to estimate the channel accurately. In this paper, by applying the subspace method, we propose a vertical layered space-time code to detect symbols without the knowledge of the channel. From Monte Carlo simulations, we show that performance can approach the detection method needed the knowledge of the channel.
The 2014 Ebola Outbreak: Preparedness in West African Countries and its Impact on the Size of the Outbreak

The recent Ebola virus outbreak in West Africa was the first that reached epidemic size resulting in more than 28,000 suspected and confirmed cases and more than 11,000 deaths. Here, we performed a meta-analysis to determine the role of preparedness in the course of the epidemic. Relevant research articles were identified using the search terms "Ebola 2014 preparedness", "Ebola 2014 treatment and diagnosis", "Ebola 2014 isolation", "Ebola 2014 culture", and "Ebola 2014 Health Care Workers" in PubMed. 21 relevant original articles in English were identified and analysed. Results revealed that a lack of preparedness substantially contributed to the scale of the Ebola epidemic in West Africa. Studies consistently reported on shortcomings in the availability and use of personal protective equipment, transportation and communication systems, surveillance, patient isolation and treatment, training of healthcare workers, and public awareness and perception in the affected West African countries. Effective surveillance and patient isolation enabled outbreak control. In conclusion, effective health care systems and procedures for early detection and containment of outbreaks, in combination with education of the population will be needed to better control future Ebola outbreaks and outbreaks of other (novel) pathogens for which no effective treatment is available.