Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentation of 3D Tubular Tree Structures in Medical Images

The segmentation of tubular tree structures like vessel systems in volumetric medical images is of vital interest for many medical applications. However, a diverse set of challenging objectives and problems is related to this task in different application domains. In this work, we develop and evaluate methods to address these issues. To accomplish the segmentation of heavily branched structures in a robust manner, we propose a generally applicable three-step approach consisting of: (i) a bottom-up identification of tubular structures followed by (ii) a grouping and linkage of these tubular structures into tree structures that are (iii) used as a prior for the actual segmentation. This approach incorporates additional prior knowledge compared to conventional approaches: the individual tubular structures have to be connected with each other and – from a biological perspective – to be supplied. In this way, we achieve a high robustness regarding the structural correctness of the segmentation results. We develop and investigate novel methods for each of these processing steps addressing the needs of different applications. In particular, we present a novel approach for detection of tubular objects using the Gradient Vector Flow to address limitations of the typically used Gaussian scale space. We propose two methods for grouping and linkage of sets of unconnected tubular structures into tubular tree structures. One enables an extraction of high quality centerlines in regions that deviate significantly from a typical tubular shape, while the other one allows for a separation of interwoven tubular tree structures as well as handling of various kinds of disturbances. To accurately segment the identified tubular structures two methods are developed. One solves the segmentation task in a globally optimal way using graph cuts, while the other one segments according to the edge closest to the centerline. Based on these methods, different applications for segmentation of blood vessel trees (liver vasculature and coronary arteries) and airway trees in CT datasets are developed. The methods are evaluated on clinical datasets and compared to results achieved with other state-of-the-art methods developed for the same task. The results successfully demonstrate
Predicting B.Tech student admission decisions by data mining algorithms

In learning calculations affiliation govern mining is the most intense capacity in information mining. The age of principles includes two stages in which the primary stage finds the arrangements of continuous components and the second stage creates the run the show. Numerous calculations are determined to discover sets of incessant components from successive examples. In our exploration work an imperative perception is made in the information digging calculations for the informational index of the designing understudies. By discovering relationship between qualities, we can discover the potential outcomes for affirmation and anticipate understudy confirmation choices. To discover solid and substantial affiliation rules, distinctive measures are thought about lift, support, cost, confidence and conviction. The gauge is come to with the utilization of the imperative as needs be amid the age of the affiliation rules. As we move towards the objective, to give an examination the affiliation runs, the understudies who pick the branch have utilized the calculations specified to demonstrate the guidelines and the aftereffects of the affiliation in light of the past database of the records of confirmation.
Career Guidance through TIC-TAC-TOE Game

Many graduates are being qualified year after year in different disciplines that do not have any kind of idea about the career that is most suitable to them. Some of the graduates are suffering due to the bad career choice that they have taken in the absence of proper career guidance system which is based on psychological assessment. The type of career suitable for a graduate student is dependent on the Psychology of a student and therefore the psychology of a graduate must be measured which can be used for determining suitable career that suits the Graduate. In this paper, the design of Tic-Toc-Toe Game that can be played by a student is presented and it is also shown how psychology of student can be measured considering Intelligence, Learning ability, perseverance, patience and Speed of solving problem etc. while the student plays the game. An expert system is also presented that helps predicting a career that is most suitable to a graduating student
The effect of herbage type prior to fasting on the rate of liveweight loss during fasting in ewe lambs

This experiment examined the hypothesis that herbage type, would affect the rate of liveweight loss of Romney lambs after a period of fasting. Lambs (n=80) were allocated to one of two treatments; grass (ryegrass and white clover) and herb-clover (chicory, plantain, red clover, white clover). Lambs grazed their respective treatments for one month prior to the start of the experiment. Lambs were weighed immediately after being removed from their herbage treatment and then at one-hour intervals for eight hours. Herbage type had a significant effect (P<0.01) on the rate of liveweight loss over the eight-hour fast. Lambs grazing herb-clover swards had a greater (P<0.05) rate of weight loss after four hours than did lambs grazing grass (0.55 vs. 0.23 kg/h, respectively). Similarly, after eight hours, lambs grazing herb-clover lost weight more rapidly (P<0.05) than did those grazing grass (0.39 vs. 0.22 kg/h, respectively). These results support the hypothesis that herbage type influenced the rate of liveweight loss during fasting and indicate that farmers need to consider the type of herbage and time off herbage in order to obtain accurate liveweight data.
La discipline budgétaire dans la zone euro : enjeux et perspectives

A l’heure ou l’Italie se voit retoquer son budget 2019 par la Commission europeenne et ou un certain nombre d’autres pays de la zone euro restent en difficultes financieres, cela relance un debat desormais recurrent sur la pertinence des mesures mises en place pour assurer la discipline budgetaire dans l’Union economique et monetaire (UEM).
Sparse Coding-Based Voice Conversion from Lip Information

A technology to recognize speech content from lip motion is called visual speech recognition (VSR). VSR is an important communication method for people who have a handicap with hearing or speaking. In this paper, we propose a sparse-coding-based voice conversion method using lip motion without text information. Lip information and voices are extracted from videos, where they are used to construct lip dictionary and voice dictionary. Input lip information is represented by a linear combination of a small number of bases in the lip dictionary. The bases are replaced to coordinate bases in the voice dictionary, and they are recomposed to voice information. In this paper, we conducted vowel conversion because vowels are able to recognize from lip information.
L G ] 2 M ar 2 01 8 Shampoo : Preconditioned Stochastic Tensor Optimization

Preconditioned gradient methods are among the most general and powerful tools in optimization. However, preconditioning requires storing and manipulating prohibitively large matrices. We describe and analyze a new structure-aware preconditioning algorithm, called Shampoo, for stochastic optimization over tensor spaces. Shampoo maintains a set of preconditioning matrices, each of which operates on a single dimension, contracting over the remaining dimensions. We establish convergence guarantees in the stochastic convex setting, the proof of which builds upon matrix trace inequalities. Our experiments with state-ofthe-art deep learning models show that Shampoo is capable of converging considerably faster than commonly used optimizers. Although it involves a more complex update rule, Shampoo’s runtime per step is comparable to that of simple gradient methods such as SGD, AdaGrad, and Adam.
Kinetic characterization and molecular modeling of trehalose-6-phosphate phosphatase from Anopheles gambiae and expressed in Pichia pastoris

Trehalose-6-phosphate phosphatase (TPP) is one of the primary enzymes involved in the synthesis of trehalose, the main sugar found in insect hemolymph. In the present study, we report for the first time heterologous expression in Pichia pastoris, characterization and homology modeling of TPP from Anopheles gambiae mosquito. Purified TPP recombinant exhibited a molecular weight of approximately 36 kDa with optimum pH of 8.0, optimum temperature of 38°C, and the KM was 3.19 ± 0.10 mM. Inhibition tests revealed that CaCl2 and Ca(NO3)2 at 5 and 25 mM, respectively, were effective inhibitors of TPP activity. Homology studies and molecular modeling indicated high similarity of the TPP tridimensional structure with TPP enzymes deposited at a data bank and these homology studies confirmed that it is a trehalose phosphatase with conserved motifs of the superfamily haloacid dehydrogenase. These results may provide support for the discovering of TPP inhibitors to be used for development of insecticides to control mosquito vectors. Key words: Trehalose, trehalose-6-phosphate phosphatase, expression, enzyme characterization, homology modeling.
Mobile interaction trajectories: a design focused approach for generative mobile interaction design research

Mobile HCI’s (Human Computer Interaction) understanding of mobility can benefit from novel theoretical perspectives that have been largely underexploited. This thesis develops and applies a novel middle range theory for mobile interaction design called mobile interaction trajectories, demonstrating the theory’s use and value in practical design settings. Mobile interaction trajectories offer a new theoretical perspective for mobile interaction design, considering people’s everyday trajectories as a baseline for mediated communication, with foci on practices and experiences of changing states of connectedness, chronologies of mediated communication, and mobile communication routines. Following a research through design methodology, probing was used as a creative research method. Two probing experiments informed the theory’s development. A new Probe resource was designed and applied, called the Hankie Probe. It was used to collect instances of mobile interaction trajectories and informed a range of design workshops. The Hankie Probe is based on a fabric-based format and expresses everyday trajectories, and mobile communication practice and experience via stitched and drawn handmade space-time diaries. Research about design analysed the design processes with the completed Probes revealing the middle range theory’s value. The theory’s distinctive characteristics have shown to inform generative design processes. The trajectory-based perspective inspired design concepts for contextually adaptive services that enable new communication experiences and alter the chronology of social interaction. The thesis contributes to knowledge by underpinning generative design work with novel mobility theories via a new Probe format for mobile interaction design research. The following additional discoveries were made: There are three basic probing functions in generative design workshops; designer’s experiences and subjective interpretation augment insights about users and contexts in design workshops, the fabric-based handmade Probes influenced design work offering a captivating authentic format that requires subjective interpretation.
Computer Programming Competencies Required by Computer Education Graduates for Sustainable Employment

This study identified the computer programming competencies required of computer education graduates for sustainable employment in Enugu metropolis, Enugu state, Nigeria. Three research questions and one null hypothesis guided the study. The study adopted descriptive survey research design. The population for the study was 95, which comprised of 74 computing lecturers, 6 IT programming instructors, and 15 programmers. A structured questionnaire was used for data collection. The instrument was face validated by three experts in computer programming. Cronbach Alpha statistic was used to determine the internal consistency of the instrument, yielding reliability co-efficient of 0.83. Mean and Standard deviation were used to answer the research questions while ANOVA statistic was used to test the hypothesis. The study found out that 25 hard competencies, 18 business competencies, and 19 soft competencies are required by computer education graduates for sustainable employment in programming jobs. These competencies identified include among others, ability to code, test and debug programs quickly and efficiently; ability to explore and evaluate application design considerations for multiple technologies, ability to analyze users’ needs and specifications then design, test, and develop software to meet those needs, ability to recommend software upgrades for clients’ existing programs and systems, proficiency in data mining, confidence in personal ideas but open to feedbacks, adapting to changes while remaining focused on project with topmost priority and good sense of judgment. It was therefore recommended that the identified competencies should be incorporated in the curriculum for training Computer Education graduates for sustainability in programming jobs.
Caracterização de eventos de exceção e de seus respectivos impactos no sistema de transporte público por ônibus da cidade de São Paulo

DIAS, Felipe Cordeiro Alves. Characterization of exception events and their respective impacts on the public transport system by bus of the city of São Paulo. 2019. 259 p. Dissertation (Master of Science) School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, 2019. The city of São Paulo is the most populous municipality in Brazil, characterized by an urban segregation responsible for numerous problems related to urban mobility. The current actions to solve the problems of urban mobility have little deepening in technological issues and improvements of existing computer systems — such as those required for the Integrated Monitoring and Transport System (in the Portuguese acronym: SIM), used for the management and monitoring of public transport by buses of the city of São Paulo. One of the possible improvements is integrating the SIM with Social Networks. With this perspective of integration, this work aims to use tweets and data from SIM in the characterization of exception events and their respective impacts on the public transport system by buses of the city of São Paulo. In order to achieve this objective, this work proposes to use tweets published by governmental institutions responsible for reporting exception events, data from SIM’ Automatic Vehicle Location (AVL) modules, responsible for the tracking and locating of urban buses and data from SPTrans’ GTFS (General Transit Feed Specification). In order to reach the proposed goal, we manually classified 60,984 tweets and trained different models through supervised machine learning algorithms to identify exception events. In addition, we propose a new methodology to extract and geolocalize the addresses of the exception events, through Natural Language Processing and Regular Expression. Using that approaches, we show that it is possible to correlate the data of these events with the historical data of the SIM and GTFS, to characterize how the public transport by bus of the city of São Paulo is impacted in these scenarios. Additionally, we propose a distributed architecture for exploration and visualization of large volumes of data related to public transport.
Entrenamiento en deportes de equipo: el entrenamiento estructurado en el FCB

espanolAunque las ciencias que estudian la actividad fisica y el deporte son relativamente jovenes, en las ultimas decadas han evolucionado notablemente, y en este sentido las metodologias que estudian el entrenamiento deportivo no son una excepcion. En este contexto parece que gran parte de las metodologias conocidas, como por ejemplo la periodizacion clasica, no dan respuesta a todas las necesidades que presentan los llamados deportes de equipo, caracterizados por competiciones que se mantienen durante largos periodos de tiempo, sometiendo al deportista a un gran estres competitivo. El entrenamiento estructurado nace con la voluntad de adaptarse a las necesidades especificas de los deportes de equipo, basandose en la especificidad, la individualizacion, el abordaje global y el aprendizaje diferencial, respetando las diferentes estructuras que conforman al ser humano deportista. Este articulo explica los fundamentos y las caracteristicas principales del entrenamiento estructurado desde un abordaje holistico. EnglishAlthough the sciences that study physical activity and sports are relatively young, they have evolved considerably in recent decades, and the methodologies that study sports training are no exception. In this context, it seems that most of the known methodologies, such as classical periodization, do not meet all the needs of team sports, which are characterised by competitions that go on for long periods of time which subject the players to extraordinary competitive stress. Structured training was devised with the aim of adapting to the specific needs of team sports based on specificity, individualisation, a global approach and differential learning, while respecting the different structures that comprise human athletes. This article explains the fundamentals and main characteristics of structured training using a holistic approach.
Machine Learning on Statistical Manifold

This senior thesis project explores and generalizes some fundamental machine learning algorithms from the Euclidean space to the statisticalmanifold, an abstract space in which each point is a probability distribution. In this thesis, we adapt the optimal separating hyperplane, the k-means clusteringmethod, and the hierarchical clustering method for classifying and clustering probability distributions. In these modifications, we use the statistical distances as a measure of the dissimilarity between objects. We describe a situation where the clustering of probability distributions is needed and useful. We presentmany interesting and promising empirical clustering results, which demonstrate the statistical-distance-based clustering algorithms often outperform the same algorithms with the Euclidean distance in many complex scenarios. In particular, we apply our statistical-distance-based hierarchical and k-means clustering algorithms to the univariate normal distributions with k 2 and k 3 clusters, the bivariate normal distributions with diagonal covariance matrix and k 3 clusters, and the discrete Poisson distributions with k 3 clusters. Finally, we prove the k-means clustering algorithm applied on the discrete distributions with the Hellinger distance converges not only to the partial optimal solution but also to the local minimum.
Development of a Traction Control System for a Parallel-Series PHEV

II VITA . IV LIST OF TABLES . IX LIST OF FIGURES . X CHAPTER 1: MOTIVATION . 1 1.1 THESIS OVERVIEW . 3 CHAPTER 2: LITERATURE REVIEW . 5 2.1 ELECTRIC AND HYBRID VEHICLES . 5 2.1.
The Semiparametric Juhn-Murphy- Pierce Decomposition of the Gender Pay Gap with an application to Spain

An originally new semiparametric decomposition of t he wage differential between men and women is proposed. The here proposed decomposition foll ws the ideas of Juhn, Murphy, and Pierce (1993) to analyze for example the gender pay gap. Among other advantages, this decomposition allows us to study the development of a (gender) wage gap over time. A semiparametric specification of the wage equation o vercomes the criticism of Heckman, Lochner, and Todd (2008) concerning misspecificatio ns f the Mincer equation. We use our method to study the gender wage gap in Spain before and after the implementation of the 3rd Plan for Equal Opportunities for Men and Women (199 7-2000) of the European Union.
A testbed for experimental evaluation of efficient multimedia delivery over lossy networks

Multimedia transmission over lossy networks has been rapidly increasing, especially with the advent of different high-speed and cost-effective Internet technologies. Despite these technology advances, however, the quality of video streaming over lossy networks is still a major challenge towards obtaining the best quality of service. In this paper, a new experimental testbed that is based on the real-time media flow protocol (RTMFP) is proposed to enable researchers to investigate and optimise the effect of changing multiple key parameters relevant to the video-streaming quality. The impact of these parameters, which include video resolution, frames per second, and compression rate on the video quality are investigated with various settings of network packet loss. The obtained results and relationships between these parameters have led to development of a new algorithm that is capable of changing the parameters under study, in real time, according to the estimated packet loss towards maximum obtainable quality. Design details and experimental setup of the proposed testbed are presented along with key practical considerations and experimental evaluation results.
Actuation system design with electrically powered actuators

This project addresses the actuation system architecture of future All-electric aircraft (AEA) with electrically powered actuators (EPA). Firstly, the information of EPAs is reviewed, and then an electro-hydrostatic actuator (EHA) and electro-mechanical actuator (EMA) are selected for further system research. The actuation system architecture of Boeing and Airbus is then presented as a conventional design where the new design concepts are also researched and the distributed architecture was proposed as another design trend. To find out which one is better, both of them are selected for further research. The easily available data makes the Flying Crane a better choice for the case study. Stall load, maximum rate and power are the main elements for electric actuator requirements and power consumption, weight, cost and safety are the most important aspects for civil aircraft actuation systems. The conventional and distributed flight actuation system design considered the redundancy of systems and actuators, and also the relationship of the power, control channel and actuator work mode. But only primary flight actuation control system specifications are calculated since this data has better precision and also the limited time has to be taken into consideration. Brief comparisons of the two system specifications demonstrate that the higher power actuator have has higher efficiency and distributed actuators could reduce the system weight through reduce the system redundancy with a power efficiency decline. The electrically powered actuation system for future aircraft design is a balance between actuator number, system weight and power consumption.
LEACH Algorithm Improvement Based on Cluster Head Selection

In order to solve the problem of LEACH Algorithm cannot guarantee the larger residual energy node absolutely were elected as cluster head , and it consumes large amounts of energy for double counting of cluster head election, at the same time, the influence of the node distance for cluster head election is not included. The improved LEACH algorithm has solved the problems very well, it makes a use of cluster heads projection to decrease the number of cluster competition by combining with the optimal cluster head selection algorithm, which can reduce the node energy consumption, then to achieve equilibrium network energy consumption and prolong the survival time of the network. And the experimental results are shown that the improved LEACH algorithm balanced the energy consumption of the entire network, significantly reduced the power consumption of the nodes in the monitoring area, delayed the first dead nodes appear on the number of rounds, and prolonged the life cycle of monitoring network. Keywords-the improvement of LEACH algorithm; optimal cluster head selection; cluster heads forecasting mechanism; time schedule