Miracle-dz/UniFAR-FTUs huggingface dataset:
The Children's Report of Sleep Patterns (CRSP): a self-report measure of sleep for school-aged children.

STUDY OBJECTIVES (1) Present preliminary psychometrics for the Children's Report of Sleep Patterns (CRSP), a three-module measure of Sleep Patterns, Sleep Hygiene, and Sleep Disturbance; and (2) explore whether the CRSP provides information about a child's sleep above and beyond parental report. METHODS A multi-method, multi-reporter approach was used to validate the CRSP with 456 children aged 8-12 years (inclusive). Participants were recruited from pediatricians' offices, sleep clinics/laboratories, children's hospitals, schools, and the general population. Participants completed measures of sleep habits, sleep hygiene, anxiety, and sleepiness, with actigraphy and polysomnography used to provide objective measures of child sleep. RESULTS The CRSP demonstrated good reliability and validity. Differences in sleep hygiene and sleep disturbances were found for children presenting to a sleep clinic/laboratory (vs. community population); for younger children (vs. older children); and for children who slept less than 8 hours or had a sleep onset later than 22:00 on actigraphy. Further, significant associations were found between the CRSP and child-reported anxiety or sleepiness. Notably, approximately 40% of parents were not aware of child reported difficulties with sleep onset latency, night wakings, or poor sleep quality. CONCLUSIONS The three modules of the CRSP can be used together or independently, providing a reliable and valid self-report measure of sleep patterns, sleep hygiene, and sleep disturbances for children ages 8-12 years. Children not only provide valid information about their sleep, but may provide information that would not be otherwise captured in both clinical and research settings if relying solely on parental report.
BeatBank ? An MPEG-7 Compliant Query by Tapping System

A Query by Tapping System is a multi-media database containing rhythmic metadata descriptions of songs. This paper presents a Query by Tapping system called BeatBank. The system allows to formulate queries by tapping the melody line’s rhythm of a song requested on a MIDI keyboard or an e-drum. The query entered is converted into an MPEG-7 compliant representation. The actual search process takes only rhythmic aspects of the melodies into account by comparing the values of the MPEG-7 Beat Description Scheme. An efficiently computable similarity measure is presented which enables the comparison of two database entries. This system works in real-time and computes the search process online. It computes and presents a new search result list after every tap made by the user.
The NEPSAC Nonlinear Predictive Controller in a Real Life Experiment

This paper is intended to give a short overview about the NEPSAC nonlinear predictive control approach. In the first part there are presented the theoretical aspects of the control design procedure, and then in the next section are shown the results for the designed algorithm for a real life experiment. There are also compared the results with other type of controllers like the MPC or PID controller.
Multi-Level Fusion of CT and MRI Brain Images for Classifying Tumor

Medical image processing is the most stimulating and developing field in our day today life. Now a day's processing of MRI images is one of the parts of this field This paper proposes an efficient method for detection of brain tumor from CT and MRI images of brain, by applying image fusion, segmentation, feature extraction and classification. Image Fusion is the process of combining relevant information from two or more images into a single composite image. First, the CT and MRI images of brain are subjected to multilevel fusion using discrete wavelet transform. The fusion strategy uses multi-level decomposition of the images obtained using wavelet transform. By analyzing the images at multiple levels, the method is able to extract finer details from them and in turn improves the quality of the fused image. The fused image is then segmented using morphological operations. And the features are extracted. Finally the extracted image is exposed to fuzzy based classification to identify whether the tumor is benign or malignant.
The Pharmaceutical Industry in 2016. An Analysis of FDA Drug Approvals from a Perspective of the Molecule Type

This is an analysis from a chemical point of view of the 22 drugs accepted by the FDA during 2016. The different drugs from the 2016 “harvest” have been classified according to their chemical structure: antibodies; TIDES (oligonucleotides and peptides); amino acids and natural products; drug combination; and small molecules.
Directional antennas improve the link-connectivity of interference limited ad hoc networks

We study wireless ad hoc networks in the absence of any channel contention or transmit power control and ask how antenna directivity affects network connectivity in the interference limited regime. We answer this question by deriving closed-form expressions for the outage probability, capacity and mean node degree of the network using tools from stochastic geometry. These novel results provide valuable insights for the design of future ad hoc networks. Significantly, our results suggest that the more directional the interfering transmitters are, the less detrimental are the effects of interference to individual links. We validate our analytical results through computer simulations.
Detection of partial and complete acrosome reaction in human spermatozoa: which inducers and probes to use?

The acrosome reaction (AR), an essential step for achieving mammalian fertilization, was recently introduced as a means of clinical evaluation of male fertility. However, most of the available techniques for acrosomal status assessment (except those employing electron microscopy) do not define whether the measurements represent partial or complete AR. We, therefore, performed a crossover investigation of the types of inducers and probes required for detecting partial or complete AR in human spermatozoa. The acrosomal status before and after stimulation with four AR inducers was evaluated after incubation for 3 h in capacitating conditions. We used a fluorescence-activated cell sorter with fluorescein isothiocyanate-conjugated monoclonal antibody CD46 (FITC-CD46) targeting the inner acrosomal membrane for detecting a complete AR, and fluorescein isothiocyanate-Pisum sativum agglutinin (FITC-PSA) targeting the acrosomal content for detection of both partial and complete AR. Without stimulation or following stimulation with progesterone, follicular fluid (FF) or phorbol myristate ester (PMA), the AR could be detected with FITC-PSA but not with FITC-CD46. Following stimulation with the calcium ionophore A23187, the AR could be detected by both FITC-PSA and FITC-CD46. These results suggest that spontaneous AR as well as AR induced by progesterone, PMA and FF are partial. In contrast, the AR induced by A23187 is total, i.e. both partial and complete. These findings are valuable for both research and clinical purposes and are a step towards an international agreement on a standard test for human sperm AR, for which there is an urgent need.
A low complexity near-lossless image compression method and its ASIC design for wireless endoscopy system

This paper proposes a low complexity near-lossless image compression method and its ASIC design for the wireless endoscopy system. Assuring high image quality (PSNR larger than 46.37dB and every pixel error is less than 2), the proposed method can provide lower compression rate (3.5bits/pixel) and lower complexity than any conventional interpolation-first methods and other existing similar compression-first methods. In addition, the ASIC design of this compression method is also given out. The hardware design has been verified on FPGAs and implemented in 0.18mum CMOS process
Graft-vs-host disease following allogeneic hematopoietic cell transplantation.

BACKGROUND Allogeneic hematopoietic cell transplantation (HCT) is a potentially curative therapy with proven efficacy in the management of hematologic malignancies. However, it is complicated by the syndromes of acute and chronic graft-vs-host disease (GVHD). METHODS A narrative review is provided to summarize major biologic insights into the pathogenesis of these immune-mediated disorders, as well as advances in diagnosis, classification, prevention, management, and allied supportive care with the aim of providing essential understanding for clinicians with or without subspecialty experience in the field of blood and marrow transplantation. RESULTS Major scientific advances have contributed to enhanced understanding of the pathogenesis of these disorders, and clinical investigation has provided more effective preventive and therapeutic strategies for GVHD. However, since acute GVHD and chronic GVHD remain leading sources of transplantation-related morbidity and mortality, ongoing investigation is needed to develop new approaches to addressing these syndromes. CONCLUSIONS The major challenge for future investigation will be to capitalize on biologic insights in order to develop novel strategies for the prevention and therapy of acute and chronic GVHD that will address the current shortcomings in existing therapeutic approaches.
Development and potential analysis of Heuristic Evaluation for Educational Computer Game (PHEG)

Heuristic Evaluation has expended tremendously from general interface evaluation to more specific evaluation including for computer games application. Computer game plays an important leisure tool nowadays and the potential of it has been explored and being used in teaching and learning. Combination of evaluation method and computer game application that focus on educational purposes, lead to the realization of having comprehensive evaluation method that able to evaluate elements of fun and educational. As a result, Playability Heuristics Evaluation for Educational Computer Game (PHEG) was proposed because of the needs to address important elements especially fun element in educational computer games so that the produced application is fun to be used as well as it incorporates educational elements to help users during the learning process. The development process of PHEG involved five major steps; initial study, proposed heuristics, experts review, evaluation process and final heuristics. The discussions of this paper only focus on the fourth step which is evaluation process on PHEG. At the end of this paper, a potential analysis for PHEG using quantitative method is proposed.
Measurement of nondegenerate nonlinearities using a two-color Z scan.

A simple dual-wavelength (two-color) Z-scan geometry is demonstrated for measuring nonlinearities at frequency omega(p) owing to the presence of light at omega(e). This technique gives the nondegenerate two-photon absorption (2PA) coefficient beta(omega(p); omega(e)) and the nondegenerate nonlinear refractive index n(2)(omega(p); omega(e)), i.e., cross-phase modulation. We demonstrate this technique on CS(2) for n(2) and on ZnSe where 2PA and n(2) are present simultaneously.
Bayesian Interpolation and Parameter Estimation in a Dynamic Sinusoidal Model

In this paper, we propose a method for restoring the missing or corrupted observations of nonstationary sinusoidal signals which are often encountered in music and speech applications. To model nonstationary signals, we use a time-varying sinusoidal model which is obtained by extending the static sinusoidal model into a dynamic sinusoidal model. In this model, the in-phase and quadrature components of the sinusoids are modeled as first-order Gauss-Markov processes. The inference scheme for the model parameters and missing observations is formulated in a Bayesian framework and is based on a Markov chain Monte Carlo method known as Gibbs sampler. We focus on the parameter estimation in the dynamic sinusoidal model since this constitutes the core of model-based interpolation. In the simulations, we first investigate the applicability of the model and then demonstrate the inference scheme by applying it to the restoration of lost audio packets on a packet-based network. The results show that the proposed method is a reasonable inference scheme for estimating unknown signal parameters and interpolating gaps consisting of missing/corrupted signal segments.
Wind Power Prediction with Cross-Correlation Weighted Nearest Neighbors

A precise wind power prediction is important for the integration of wind energy into the power grid. Besides numerical weather models for short-term predictions, there is a trend towards the development of statistical data-driven models that can outperform the classical forecast models [1]. In this paper, we improve a statistical prediction model proposed by Kramer and Gieseke [5], by employing a cross-correlation weighted k-nearest neighbor regression model (x-kNN). We demonstrate its superior performance by the comparison with the standard u-kNN method. Even if different pre-processing steps are considered, our regression technique achieves a comparably high accuracy.
Closing seminars and lectures: The work that lecturers and students do

Based on an analysis of naturally occurring interactions between lecturers and students, this article investigates how university lectures and seminars are brought to a close through the collaborative work of lecturers and students. The analysis focuses on, first, the resources that lecturers and students have to accomplish this (which include not just speech but also embodied conduct, as well as references to clock time and lesson phases); second, the active role that students play, who may engage in closing activities in ways that attempt to preserve the classroom order (e.g. by packing up silently while continuing to demonstrably listen) or in ways that are disruptive of it (e.g. by packing up noisily); and third, the occasional subversive role that students may adopt, who may attempt to initiate closings in order to cut the lecture or seminar short (e.g. by suggesting to the lecturer that he or she is going over time or by engaging in ‘premature’ closing activities).
Energy Optimization of Memory Intensive Parallel workloads

Energy consumption is an important concern in modern multicore processors. The energy consumed during the execution of an application can be minimized by tuning the hardware state utilizing knobs such as frequency, voltage etc. The existing theoretical work on energy mini- mization using Global DVFS (Dynamic Voltage and Frequency Scaling), despite being thorough, ignores the energy consumed by the CPU on memory accesses and the dynamic energy consumed by the idle cores. This article presents an analytical model for the performance and the overall energy consumed by the CPU chip on CPU instructions as well as the memory accesses without ignoring the dynamic energy consumed by the idle cores. We present an analytical framework around our energy-performance model to predict the operating frequencies for global DVFS that minimize the overall CPU energy consumption within a performance budget. Finally, we suggest a scheduling criteria for energy aware scheduling of memory intensive parallel applications.
A Deterministic Distributed TDMA Scheduling Algorithm for Wireless Sensor Networks

Efficient scheduling of time slots in a time division multiple access scheme (TDMA) is important for low power wireless sensor networks. Existing algorithms are either centralized with poor scalability, or distributed but with high complexity. In this paper, we explain how TDMA could be more energy efficient by careful slot scheduling in wireless sensor networks. Then we propose a deterministic distributed TDMA scheduling algorithm (DD-TDMA). In DD-TDMA, each sensor node schedules its own TDMA slot based on its neighborhood information, and packet collisions are gracefully avoided during scheduling. The experimental results show that compared to other centralized and distributed scheduling algorithms, DD-TDMA achieves better performance in terms of schedule length, running time and message complexity.
A Proximal Classification Method based on Two Smallest and Supervised Hyperspheres

We propose a proximal classification method, named as the hyperspherical 2-surface proximal (H2SP) classifier, by seeking the two smallest hyperspheres for the positive class and the negative class, respectively, each containing the most samples from one class while also the least samples from the other. The proposed H2SP classifier is validated using five public benchmark datasets, including one toy dataset and four real datasets. The results are compared with those obtained by using Fisher's linear discriminant analysis (FLDA), support vector machines (SVM), and radial basis function (RBF) networks. Experimental results comparing classification error rates demonstrate the effectiveness of the proposed method.
Near-Optimal BRL using Optimistic Local Transitions ( Extended Version )

Model-based Bayesian Reinforcement Learning (BRL) allows a sound formalization of the problem of acting optimally while facing an unknown environment, i.e., avoiding the exploration-exploitation dilemma. However, algorithms explicitly addressing BRL su er from such a combinatorial explosion that a large body of work relies on heuristic algorithms. This paper introduces bolt, a simple and (almost) deterministic heuristic algorithm for BRL which is optimistic about the transition function. We analyze bolt's sample complexity, and show that under certain parameters, the algorithm is near-optimal in the Bayesian sense with high probability. Then, experimental results highlight the key di erences of this method compared to previous work. Key-words: Bayesian Reinforcement Learning, Optimistic Algorithms,PAC-MDP BRL Quasi-Optimal à l'aide de Transitions Locales Optimistes (Version Étendue) Résumé : L'apprentissage par renforcement bayésien basé modèle (BRL) permet une formalisation saine du problème consistant à agir optimalement face à un environnement inconnu, c'està-dire en évitant le dilemme exploration-exploitation. Toutefois, les algorithmes s'attaquant explicitement au BRL sou rent d'une telle explosion combinatoire qu'un grand nombre de travaux repose sur des algorithmes heuristiques. Cet article introduit bolt, un algorithme heuristique simple et (presque) déterministe pour le BRL qui est optimiste vis à vis de la fonction de transition. Nous analysons la complexité d'échantillon de bolt et montrons que, pour certains paramètres, l'algorithme est quasi-optimal au sens bayésien avec une grande probabilité. Puis, des résultats expérimentaux mettent en valeur les principales di érences entre cette méthode et des travaux antérieurs. Mots-clés : Apprentissage par renforcement bayésien, Algorithmes optimistes, PAC-MDP Bayesian Optimistic Local Transitions 3
Models Transformations for Ubiquitous System Design

Many different models and tools exist for supporting the design of ubiquitous interactive systems. Each of them deals with a different point of view. As a result designing such systems has to involve a set of models rather than just one. In this paper we first provide an overview on existing models dedicated to Mixed Interactive Systems, one form of ubiquitous systems. Then, to facilitate the elicitation of the most appropriate model, we organize them along the steps of the development process. Finally, to smoothly guide the use of these different design resources along the development process, we provide an overview of different linking mechanisms between design models for ubiquitous systems and highlight their characteristics.
Réalité Augmentée et Environnement Collaboratif : Un Tour d'Horizon

La Realite Augmentee (RA) est generalement definie comme une branche derivee de la Realite Virtuelle. D'une facon plus generale, le concept de realite augmentee regroupe une approche multidisciplinaire visant un melange entre reel et virtuel. La forte potentialite induite par cette connexion promet un cadre adequat pour l'interaction 3D ou les applications collaboratives. On presente dans cet article un tour d'horizon des principaux travaux menes a ce jour dans le cadre de l'image et de la RA et plus particulierement le cadre collaboratif.
FTV (Free-viewpoint TV)

We have developed a new type of television named FTV (Free-viewpoint TV). FTV is the ultimate 3DTV that enables us to view a 3D scene by freely changing our viewpoints. At present, FTV is available on a single PC or a mobile player. The international standardization of FTV has been conducted in MPEG. The first phase of FTV was MVC (Multi-view Video Coding) and the second phase is 3DV (3D Video). FDU (FTV Data Unit) is proposed as a data format for 3DV. FTU can compensate errors of the synthesized views caused by depth error.
Towards automatic actor pinning on multi-core architectures

The actor model is a high-level programming abstraction that attempts to ease the development of parallel applications, among others, by shielding the developer from the underlying platform. In this model the execution relies on a runtime environment (RE) to be able to efficiently use the underlying machine. Modern processors possess a hierarchical architecture of memory, thus making the performance of an application dependent on the placement of the application threads. This makes the choices of the RE much more important since the chosen actor placement will have a considerable impact on the application performance. In this paper we describe a work in progress that aims to create an on-line automatic actor placement engine. Using application profiling in association with hardware counters, it will pin and migrate actors to processing units aiming to optimize performance.
Symmetry breaking during search in constraint programming

We introduce a method for symmetry breaking during search (SBDS) in constraint programming. It has the great advantage of not interfering with heuristic choices. It guarantees to return a unique solution from each set of symmetrically equivalent ones, which is the one found rst by the variable and value ordering heuristics. We prove this claim, describe a general implementation of SBDS in ILOG Solver, and describe applications to low autocorrelation binary sequences and the n-queens problem. We discuss a version of SBDS that can be applied when there are too many symmetries to reason with individually, and give applications in graph colouring and Ramsey theory.
Implementing performance measurement systems: a literature review

Currently, there is a great interest in performance measurement, with many companies attempting to implement the balanced scorecard. However, there is also evidence that many of these implementations are not successful. This paper reviews the different performance measurement system design processes published in the literature and creates a framework for comparing alternative approaches. The paper then proceeds to review the literature on performance measurement system implementations and concludes that the performance measurement literature is at the stage of identifying difficulties and pitfalls to be avoided based on practitioner experience with few published research studies. This paper is the first of two, the second going on to consider performance measurement implementation from the point of view of the change management literature.