Miracle-dz/UniFAR-FTUs huggingface dataset:
Desenvolvendo Modelos de Deep Learning para Aplicações Multimídia no Tensorflow

The availability of massive quantities of data, combined with increasing computational capabilities, makes it possible to develop more precise Machine Learning algorithms. These new tools provide advances in areas such as Natural Language Processing and Computer Vision, allowing efficient processing of images, text and audio. Now, cognitive functionalities, such as learning, recognition and detection, can be used in multimedia applications to create mechanisms beyond traditional capture, streaming and presentation uses. Methods based on Deep Learning became state-of-the-art in several Multimedia challenges. This short course presents the grounds and ways to develop models using Deep Learning. It prepares the participant to: (1) understand and develop models based on Deep Neural Networks, Convolutional Neural Networks (CNN), Recurrent Neural Networks, including LSTM and GRU; (2) apply the Deep Learning models to solve problems within the multimedia domain like Image Classification, Facial Recognition, Object Detection, Video Scenes Classification. The Python programming language is shown alongside TensorFlow, a package for developing Deep Learning models.
Modulation of the startle reflex by heat pain: Does threat play a role?

Previous studies have indicated that the startle reflex is potentiated by phasic, but not by tonic, heat pain, although the latter is seen as more strongly associated with emotional responses and more similar to clinical pain. The threat value of pain might be a decisive variable, which is not influenced alone by stimulus duration.
Spectral and Spatial Variation at Leaf and Patch Scale of Invasive Wetland Weeds

The establishment of invasive weeds in wetland environments is a prominent threat in Australia with adverse impacts on native flora. Current management is hindered by the lack of information available on which to base and justify management interventions, in particular, mapping of weed distributions. Remote sensing is a possible solution to difficulties of this type as illustrated by its successful application to wetland mapping in general. This paper explores the potential of multiscale spectral reflectance to discriminate between two particularly offensive, invasive woody weeds, bitou bush (Chrysanthemoides monilifera ssp rotundata), and lantana (Lantana camara). Spectral reflectance at the leaf and patch-level scales was measured at multiple sites using a field spectrometer. Derivative analyses of spectra as well as t-tests were used to evaluate spectral separability between species across scales. Results suggest further analysis is warranted at the patch level where species are intermixed and structural factors more complex.
An Ensemble Speaker and Speaking Environment Modeling Approach to Robust Speech Recognition

We propose an ensemble speaker and speaking environment modeling (ESSEM) approach to characterizing environments in order to enhance performance robustness of automatic speech recognition systems under adverse conditions. The ESSEM process comprises two phases, the offline and the online. In the offline phase, we prepare an ensemble speaker and speaking environment space formed by a collection of super-vectors. Each super-vector consists of the entire set of means from all the Gaussian mixture components of a set of hidden Markov models that characterizes a particular environment. In the online phase, with the ensemble environment space prepared in the offline phase, we estimate the super-vector for a new testing environment based on a stochastic matching criterion. In this paper, we focus on methods for enhancing the construction and coverage of the environment space in the offline phase. We first demonstrate environment clustering and partitioning algorithms to structure the environment space well; then, we propose a minimum classification error training algorithm to enhance discrimination across environment super-vectors and therefore broaden the coverage of the ensemble environment space. We evaluate the proposed ESSEM framework on the Aurora2 connected digit recognition task. Experimental results verify that ESSEM provides clear improvement over a baseline system without environmental compensation. Moreover, the performance of ESSEM can be further enhanced by using well-structured environment spaces. Finally, we confirm that ESSEM gives the best overall performance with an environment space refined by an integration of all techniques.
Effective Transactional Memory Execution Management for Improved Concurrency

This article describes a transactional memory execution model intended to exploit maximum parallelism from sequential and multithreaded programs. A program code section is partitioned into chunks that will be mapped onto threads and executed transactionally. These transactions run concurrently and out of order, trying to exploit maximum parallelism but managed by a specific fully distributed commit control to meet data dependencies. To accomplish correct parallel execution, a partial precedence order relation is derived from the program code section and/or defined by the programmer. When a conflict between chunks is eagerly detected, the precedence order relation is used to determine the best policy to solve the conflict that preserves the precedence order while maximizing concurrency. The model defines a new transactional state called executed but not committed. This state allows exploiting concurrency on two levels: intrathread and interthread. Intrathread concurrency is improved by having pending uncommitted transactions while executing a new one in the same thread. The new state improves interthread concurrency because it permits out-of-order transaction commits regarding the precedence order. Our model has been implemented in a lightweight software transactional memory system, TinySTM, and has been evaluated on a set of benchmarks obtaining an important performance improvement over the baseline TM system.
Contact merging algorithm for efficient substrate noise analysis in large scale circuits

A methodology is proposed to efficiently estimate the substrate noise generated by large scale aggressor circuits. Small spatial voltage differences within the ground distribution network of an aggressor circuit are exploited to reduce the overall number of input ports before the substrate extraction process. Specifically, the substrate of an aggressor circuit is partitioned into voltage domains where each domain is represented by a single substrate contact. The remaining ports of the substrate within that domain are ignored to reduce the computational complexity. A linear time algorithm is developed to identify these voltage domains and generate an equivalent contact. A reduction of more than four orders of magnitude in the number of extracted substrate resistances is demonstrated while introducing 20% error in the peak-to-peak value of the substrate noise voltage.
Complex Systems Modelling and Simulation Cosmos 2014 Programme Committee Using Cosmos to Reverse Engineer a Domain Model for Aevol . . 61 Using the Cosmos Approach to Study Schelling's Bounded Neighbourhood Model

While every attempt is made to ensure that the information in this publication is correct, no liability can be accepted by the authors or publishers for loss, damage or injury caused by any errors in, or omission from, the information given. v Preface The CoSMoS workshops series has been organised to disseminate best practice in complex systems modelling and simulation, with its genesis in the similarly-named CoSMoS research project, a four year EPSRC funded research project at the Universities of York and Kent in the UK. Funding for the CoSMoS project has now completed, but we have continued to run the workshop series as a forum for research examining all aspects of the modelling and simulation of complex systems. To allow authors the space to describe their systems in depth we put no stringent page limit on the submissions. We are pleased to be running the seventh CoSMoS workshop as a satellite event at the 14th International Conference on the Synthesis and is the leading international conference on artificially constructed living systems, a highly interdisciplinary research area rich in complexity, which provides a natural complement to the issues addressed by the CoSMoS workshop. The main session of the workshop is based on four full paper and two extended abstract submissions: Afshar Dodson et al. apply the CoSMoS approach to analyse and re-engineer Schelling's Bounded Neighbourhood Model, highlighting the importance of formalising a model for clarity and reproducibility in simulation studies. Youssef and Rizk study node-heterogeneity in complex networks, proposing a new model for generating various types of complex networks by varying model parameters. Banda et al. introduce a web-based chemistry simulation framework that provides an intuitive user interface, access to a computational grid and reliable database storage. Andrews and Stepney show how the CoSMoS process and patterns can be used to reverse engineer a domain model of an existing simulation , Aevol, from the simulation code and associated research literature. Leijnen and Dormans present a case study for designing emergence in games, showing how dynamical feedback loops in game mechanics creates fun and interesting gameplay experiences. Mavelli et al. describe a computational platform for studying the role of randomness in a minimal cell model, highlighting how random fluctuations can play an important role in determining timing behaviour. vi Our thanks go to all the contributors for their hard work in getting these submissions prepared and revised. All submissions received multiple …
Experimental study on optimal motion planning of wheeled mobile robot using convex optimization and receding horizon concept

In this paper, a novel algorithm for collision-free motion planning of two wheeled mobile robots is presented. The proposed approach stands on discrete motion planning, convex optimization and model-based control. It was employed for motion planning and control of E-puck mobile robot to pass through an unknown environment both in simulation software in MATLAB and real setting. In this regard, CVX package benefited by the Gurobi solver is employed to solve the optimization problem. Obtained results show the reliability of this algorithm for safe collision avoidance. The reported results reveal this fact that by considering the maximum velocity of the E-puck, obtained computational time is less than 0.2 seconds in each stage which is fast enough for robot motion planning tasks.
Implementing Lock-Free Queues

We study practical techniques for implementingthe FIFO queue abstract data type using lock-free data structures, which synchronize the operations of concurrent processes without the use of mutual exclusion. Two new algorithms based on linked lists and arrays are presented. We also propose a new solution to the ABA problem associated with the Compare&Swap instruction. The performance of our linked list algo-rithm is compared several other lock-free queue implementations, as well as more conventional locking techniques.
Workbench for 3D target detection and recognition from airborne motion stereo and ladar imagery

3D imagery has a well-known potential for improving situational awareness and battlespace visualization by providing enhanced knowledge of uncooperative targets. This potential arises from the numerous advantages that 3D imagery has to offer over traditional 2D imagery, thereby increasing the accuracy of automatic target detection (ATD) and recognition (ATR). Despite advancements in both 3D sensing and 3D data exploitation, 3D imagery has yet to demonstrate a true operational gain, partly due to the processing burden of the massive dataloads generated by modern sensors. In this context, this paper describes the current status of a workbench designed for the study of 3D ATD/ATR. Among the project goals is the comparative assessment of algorithms and 3D sensing technologies given various scenarios. The workbench is comprised of three components: a database, a toolbox, and a simulation environment. The database stores, manages, and edits input data of various types such as point clouds, video, still imagery frames, CAD models and metadata. The toolbox features data processing modules, including range data manipulation, surface mesh generation, texture mapping, and a shape-from-motion module to extract a 3D target representation from video frames or from a sequence of still imagery. The simulation environment includes synthetic point cloud generation, 3D ATD/ATR algorithm prototyping environment and performance metrics for comparative assessment. In this paper, the workbench components are described and preliminary results are presented. Ladar, video and still imagery datasets collected during airborne trials are also detailed.
The Spectral Shift Function and the Invariance Principle

Abstract The new representation formula for the spectral shift function due to F. Gesztesy and K. A. Makarov is considered. This formula is extended to the case of relatively trace class perturbations. The proof is based on the analysis of a certain new unitary invariant for a pair of self-adjoint operators.
Dehydration and cognition: an understated relation

Water is essential for mental health. In spite of research evidence that dehydration has detrimental effects on cognitive functioning, the element of water has often been understated in the nutrition literature. The purpose of this paper is to highlight the necessity to integrate water as an essential nutrient for healthy cognitive functioning in nutrition research. ,This study is based on a general review. The first section reviews the literature on the relationship between dehydration and cognitive performance in both adult and children populations, using electronic databases for systematic reviews and meta-analyses (excluding vulnerable populations, such as infants, the elderly and people with disabilities). The second section examines the status of water, as a nutrient, in nutrition and water-related documentation by international authorities (FAO, UNICEF, World Food Program, WHO, etc.). ,Dehydration, even at mild levels, is associated with impairments in basic and higher order cognitive functions. Websites from international authoritative nutrition sources understate the role of water in healthy nutrition, and omit the discussion of the impact of dehydration on cognitive functioning. ,The relation between dehydration and cognition is under-documented and not enough elaborated in guidelines and texts of authoritative international health policy and dietary sources.
Annotation of Tribolium nuclear receptors reveals an evolutionary overacceleration of a network controlling the ecdysone cascade

The Tribolium genome contains 21 nuclear receptors, representing all of the six known subfamilies. When compared to other species, this first complete set for a Coleoptera reveals a strong conservation of the number and identity of nuclear receptors in holometabolous insects. Two novelties are observed: the atypical NR0 gene knirps is present only in brachyceran flies, while the NR2E6 gene is found only in Tribolium and in Apis. Using a quantitative analysis of the evolutionary rate, we discovered that nuclear receptors could be divided into two groups. In one group of 13 proteins, the rates follow the trend of the Mecopterida genome-wide acceleration. In a second group of five nuclear receptors, all acting together at the top of the ecdysone cascade, we observed an overacceleration of the evolutionary rate during the early divergence of Mecopterida. We thus extended our analysis to the twelve classic ecdysone transcriptional regulators and found that six of them (ECR, USP, HR3, E75, HR4 and Kr-h1) underwent an overacceleration at the base of the Mecopterida lineage. By contrast, E74, E93, BR, HR39, FTZ-F1 and E78 do not show this divergence. We suggest that coevolution occurred within a network of regulators that control the ecdysone cascade. The advent of Tribolium as a powerful model should allow a better understanding of this evolution.
The cultural preparedness model of aspiration and engagement: understanding the dynamics of integration

ABSTRACT This paper uses the cultural preparedness approach to analyse the interface between the aspirations of immigrants and their engagement with systems of the host country. It draws upon interviews with 84 immigrants from 35 developing countries living in 9 high-income countries. Based upon Edmund Husserl’s hermeneutical phenomenology, two studies are presented to understand the disturbance of equilibrium in cultural preparation status experienced by immigrants as they try to find their way in a host country. Aspiration-Engagement themes and responses to the challenges of integration are discussed. A model of aspiration and engagement based on the cultural preparedness approach is proposed as a framework that guidance and counselling workers could use to help immigrants optimise their engagement with the systems of the host country.
Connotation Frames: Typed Relations of Implied Sentiment in Predicate-Argument Structure

Through a choice of a predicate (e.g., "violate"), a writer can convey subtle sentiments and value judgements toward the arguments of a verb (e.g., projecting the agent as an "antagonist" and the theme as a "victim"). We introduce connotation frames to encode the rich dimensions of implied sentiment, value judgements, and effect evaluation as typed relations that these choices influence, and propose a factor graph formulation that captures the inter-play among different types of connotative relations at the lexicon-level. Experimental results confirm that our model is effective in predicting connotative sentiments compared to strong baselines and existing sentiment lexicons.
A Full-Distributed Architecture for PoC Application in Data Packet Voice Communication

Push-to-Talk over Cellular (PoC) is a "walkie-talkie" like voice communication service over mobile wireless networks, based on Voice over IP (VoIP) technology. The traditional PoC defined in the Open Mobile Alliance (OMA) specification is a centralized architecture. In this architecture, servers need to be deployed for the PoC service to work and be widely available, presenting a substantial cost to ISPs. Meanwhile, the problem of network congestion and one point failure existing in the centralized architecture may degrade system performance and cause the failure of an entire system. In addition, the traditional floor control based on the centralized architecture, also suffers from the drawbacks of using a centralized controller. In this article, we propose a full-distributed architecture for PoC application (FDPoC) in data packet voice communication. In the full-distributed architecture, we propose an ALM-based distributed data packet transmission mechanism and a distributed floor control (DFC) algorithm to alleviate the above issues. In terms of average end to end delay, average max end to end delay and average floor determination delay, the performance of the proposed FDPoC and DFC algorithm are investigated through our analytical model.
Multi-View Representation Based Face Sketch Synthesis

Face photos and sketches are in two different modalities and synthesizing face sketches from photos plays an important role in law enforcement and digital entertainment. Although many face sketch synthesis methods have been proposed in recent years, most of these methods choose neighbor image patches based on image intensities. However, it is not appropriate to represent the similarity of two image patches merely according to image intensities, especially under uncontrolled environments such as varying illumination conditions. In this paper, we propose a multi-view representation of image patches for face sketch synthesis. It first constructs a high dimensional multi-view feature vector through a hierarchical framework including multiple filters and multiple local features. Then an unsupervised dimensionality reduction method is used to reduce the cost of computation and model storage. Finally traditional face sketch synthesis methods can be applied based on the proposed representation. Experimental results on the Chinese University of Hong Kong (CUHK) face sketch database and celebrity photos from the Internet illustrate that the proposed strategy improves the performance of the state-of-the-arts.
Methods for diagnosis and treatment of stimulus‐correlated motion in generic brain activation studies using fMRI

Movement‐related effects in realigned fMRI timeseries can be corrected by regression on linear functions of estimated positional displacements of an individual subject's head during image acquisition. However, this entails biased (under)estimation of the experimental effect whenever subject motion is not independent of the experimental input function. Methods for diagnosing such stimulus‐correlated motion (SCM) are illustrated by application to fMRI data acquired from 5 schizophrenics and 5 normal controls during periodic performance of a verbal fluency task. The schizophrenic group data were more severely affected by SCM than the control group data. Analysis of covariance (ANCOVA) was used, with a voxelwise measure of SCM as a covariate, to estimate between‐group differences in power of periodic signal change while controlling for variability in SCM across groups. Failure to control for SCM in this way substantially exaggerated the number of voxels, apparently demonstrating a between‐group difference in task response. Hum. Brain Mapping 7:38–48, 1999. © 1999 Wiley‐Liss, Inc.
Religiosity, masculinity, and marital and life satisfaction among Balinese Hindu men

This exploratory study describes Balinese Hindu men’s definitions of masculinity or manhood. The research study involved direct and participant observation, interviewing key informants, group interviews with Balinese men, and survey research. In this sequential mixed-methods research design, the construct of masculinity was operationalized and relationships between religiosity, masculinity, and marital and life satisfaction were explored. Five areas were identified that describe Balinese masculinity: head of family, protector and provider, caring for others, strength of character, and characteristics of the self. The survey research showed that head of the family as an important masculinity experience was associated with satisfaction with one’s marriage. Multiple regression analysis indicated that caring for others was the only significant predictor of life satisfaction. Religiosity related positively to the importance of the masculinity experiences and life satisfaction, and accounted for the positive relationship between masculinity and life satisfaction. The findings are discussed within the context of Balinese religious culture.