Miracle-dz/UniFAR-FTUs huggingface dataset:
Augmenting and Exploiting Auditory Perception for Complex Scene Analysis

We present a framework for speech enhancement and robust speech recognition that exploits the harmonic structure of speech. We achieve substantial gains in signal to noise ratio (SNR) of enhanced speech as well as considerable gains in accuracy of automatic speech recognition in very noisy conditions. The method exploits the harmonic structure of speech by employing a high frequency resolution speech model in the log-spectrum domain and reconstructs the signal from the estimated posteriors of the clean signal and the phases from the original noisy signal. We achieve a gain in signal to noise ratio of 8.38 dB for enhancement of speech at 0 dB. We also present recognition results on the Aurora 2 data-set. At 0 dB SNR, we achieve a reduction of relative word error rate of 43.75% over the baseline, and 15.90% over the equivalent low-re olution algorithm.
Elevated Serum Levels of Stromal-Derived Factor-1α Are Associated with Increased Osteoclast Activity and Osteolytic Bone Disease in Multiple Myeloma Patients

Multiple myeloma (MM) is an incurable plasma cell (PC) malignancy able to mediate massive destruction of the axial and craniofacial skeleton. The aim of this study was to investigate the role of the potent chemokine, stromal-derived factor-1α (SDF-1α) in the recruitment of osteoclast precursors to the bone marrow. Our studies show that MM PC produce significant levels of SDF-1α protein and exhibit elevated plasma levels of SDF-1α when compared with normal, age-matched subjects. The level of SDF-1α positively correlated with the presence of multiple radiological bone lesions in individuals with MM, suggesting a potential role for SDF-1α in osteoclast precursor recruitment and activation. To examine this further, peripheral blood–derived CD14+ osteoclast precursors were cultured in an in vitro osteoclast-potentiating culture system in the presence of recombinant human SDF-1α. Although failing to stimulate an increase in TRAP+, multinucleated osteoclast formation, our studies show that SDF-1α mediated a dramatic increase in both the number and the size of the resorption lacunae formed. The increased osteoclast motility and activation in response to SDF-1α was associated with an increase in the expression of a number of osteoclast activation–related genes, including RANKL, RANK, TRAP, MMP-9, CA-II, and Cathepsin K. Importantly, the small-molecule CXCR4-specific inhibitor, 4F-Benzoyl-TE14011 (T140), effectively blocked osteoclast formation stimulated by the myeloma cell line, RPMI-8226. Based on these findings, we believe that the synthesis of high levels of SDF-1α by MM PC may serve to recruit osteoclast precursors to local sites within the bone marrow and enhance their motility and bone-resorbing activity. Therefore, we propose that inhibition of the CXCR4-SDF-1α axis may provide an effective means of treatment for MM-induced osteolysis.
Record Formatting: MARC AMC.

La facon dont les archivistes utilisent le format MARC AMC (Machine Readable Cataloging for Archival and Manuscripts Control) pour echanger des donnees en description des archives est discutee. Le format MARC est decrit ainsi que les changements induits par MARC AMC. Des exemples d'enregistrements en trois formats sont donnes: US MARC AMC generique, RLIN AMC et OCLC AMC. L'impact de l'unification des formats et les changements causes par MARC AMC dans la profession d'archiviste sont discutes
Utilizando redes neurais artificiais para modelar a confiabilidade de software

9 1 Introdução 10 1.1 Motivação . 14 1.2 Objetivos do Trabalho . 14 1.3 Organização do Trabalho . 15 2 Redes Neurais Artificiais 16 2.1 Estrutura e Funcionamento . 16 2.2 Topologias de Redes Neurais Artificiais . 19 2.3 Considerações Finais . 20 3 Fundamentação Básica 21 3.1 Garantia da Qualidade . 21 3.2 Terminologia . 21 3.3 Atividades de Teste . 22 3.3.1 Técnicas de Teste de Software . 23 3.4 Métricas de Software . 25 3.5 Considerações Finais . 26 4 Modelos de Confiabilidade de Software 27 4.1 Modelos Baseados no Domı́nio do Tempo . 28 4.1.1 Modelo de Jelinski–Moranda . 28 4.1.2 Modelo Geométrico . 29 4.1.3 Outros Modelos . 30 Modelo de Goel–Okumoto (G–O) . 30 Modelo de Musa . 31 O Modelo NHPP Melhorado (ENHPP) . 31 Modelos Bayesianos . 32 4.2 Modelos Baseados em Cobertura . 33 4.2.1 Modelos Baseados em Cobertura de Crespo . 34 4.2.2 Modelo Binomial Baseado em Cobertura – MBBC . 34 4.3 Modelos Neurais . 35 4.4 Considerações Finais . 36 5 Experimentos Realizados 37 5.1 Modelo Neural Baseado no Domı́nio do Tempo – MNT . 37 5.1.1 Base de Dados . 38 5.1.2 Adequação dos Dados . 38 5.1.3 Avaliação dos Modelos . 39 5.1. 4 Configuração das Redes Neurais . 41 5.1. 5 Treinamento das Redes Neurais Artificiais . 42 5.1. 6 Análise dos Resultados . 42 5.2 Modelo Neural Baseado na Cobertura de Critérios de Teste – MNC . 44 5.2.1 Bases de Dados . 45 5.2.2 Medida de Avaliação . 45 5.2.3 Configuração das Redes Neurais . 46 5.2. 4 Análise dos Resultados . 46 5.3 Considerações Finais . 48 6 Conclusões e Trabalho Futuros 50
Sepsis induces an early impairment of cerebral metabolism in a model of traumatic brain injury (TBI): a morpho-functional study with micro-PET in rat: 7AP5-4

Background and Goal of Study: The development of sepsis in patient suf fering from TBI represents a frequent complication that has been associated with worsened global and neurological outcome. In order to bet ter characterize the influence of sepsis following TBI, we developed an in vivo model of combined TBI and sepsis in the rat. In this model we observed a worsening of post-injury mortality and weight loss, a significant exacerbation of post-injury motor deficit and cognitive impairments, and an exacerbation of neuronal cell death [1]. The aim of this study was to evaluate the in vivo alterations induced by sepsis on the evolution of post-traumatic damage by using microimaging techniques: Computerized Tomography (CT) and Positron Emission Tomography (PET). Materials and Methods: TBI was induced by Controlled Cortical Impact (CCI, n=3), sepsis was induced by Cecal Ligation and Puncture (CCI+CLP, n=3), control animals (CTRL, n=3) underwent craniotomy and laparotomy only. At 24, 48 and 72 hours af ter surgery, neuroimaging was performed by CT, in order to evaluate cerebral morphological changes, and by PET using FDG as tracer, in order to evaluate variations in cerebral metabolism. Af ter the last imaging (72h), animals were sacrificed and brains collected for histological assessment of lesion volume. Results and Discussion: No CT dif ferences were found between CCI and CCI+CLP at 24, 48 and 72 hours af ter surgery; similarly, no dif ference was observed for the lesion volume. On the contrary, FDG-PET documented a dramatic decrease in cerebral metabolism in the perilesional area in CCI+CLP rats as compared to CCI animals at all the experimental time points. Conclusion(s): FDG-PET, but not CT and histology, was able to discover early dif ference between uncomplicated CCI and CCI complicated by sepsis. The major impairment in cerebral metabolism in perilesional area in rat affected by TBI and sepsis might contribute to explain the worse neurological and global outcome observed in rats undergoing the combined injury. References: 1. Venturi L, Miranda M, Selmi V et al. J Neurotrauma. 2009;26:1547-56.
Big Data in een vrije en veilige samenleving

Big Data-toepassingen bieden vele kansen voor opsporing en surveillance. Ze maken snelle en precieze reconstructies van misdaden mogelijk, evenals gerichte inspecties en het realtime volgen van ontwikkelingen bij crisissituaties. Tegelijkertijd ontstaan er nieuwe risico’s voor burgers, op het gebied van privacy, discriminatie en de vrije meningsuiting. Aan de horizon dreigt (semi-)automatische besluitvorming, waarbij de uitkomsten van data-analyses sturend zijn voor het handelen van veiligheidsorganisaties. De WRR analyseert in dit rapport hoe de Nederlandse overheid Big Data kan gebruiken en richt zich daarbij specifiek op het veiligheidsdomein. Big Data kan volgens de raad uitsluitend vruchten afwerpen als de huidige wet-en regelgeving wordt versterkt om fundamentele rechten en vrijheden te waarborgen. Hiertoe moet de aandacht worden verlegd van het reguleren van het verzamelen van data - het zwaartepunt in de huidige juridische kaders - naar de regulering van en het toezicht op de fases van de analyse en het gebruik van Big Data. Voor de vrijheid en de veiligheid van de burgers doen zich in deze twee fasen van Big Data-processen de grootste kansen en de grootste risico’s voor.
A Natural Adaptive Control Law for Robot Manipulators

Existing adaptive robot control laws typically require an engineering choice of a constant adaptation gain matrix, which often involves repeated and time-consuming trial and error. Moreover, physical consistency of the estimated inertial parameters or the uniform positive definiteness of the estimated robot mass matrix cannot in general be guaranteed without nonsmooth corrections, e.g., projection to the boundary of the feasible parameter set. In this paper we present a natural adaptive control law that mitigates many of these difficulties, by exploiting the coordinate-invariant differential geometric structure of the space of physically consistent inertial parameters. Our approach provides a more generalizable and physically consistent adaptation law for the robot parameters without significant additional computations compared to existing methods. Simulation results showing markedly improved tracking error convergence over existing adaptive control laws are provided as validation.
Real-Time Motion Planning in Changing Environments Using Topology-Based Encoding of Past Knowledge

Trajectory planning and replanning in complex environments often reuses very little information from the previous solutions. This is particularly evident when the motion is repeated multiple times with only a limited amount of variation between each run. To address this issue, we propose the DRM-connect algorithm, a combination of dynamic reachability maps (DRM) with lazy collision checking and a fallback strategy based on the RRT-connect algorithm which is used to repair the roadmap through further exploration. This fallback allows us to use much sparser roadmaps. Furthermore, we investigate using an approximate Reeb graph to capture the topology-persistent features of the past solutions of the problem utilising this sparsity. We evaluate DRM-connect with a Reeb graph on reaching tasks, and we compare it to state-of-the-art methods. We show that the proposed method outperforms both RRT-connect and BKPIECE algorithms in the number of collision checks required and we show that our method has the potential to scale to systems with higher number degrees of freedom.
Stability Control of Mobile Inverted Pendulum Through an Added Movable Mechanism

Mobile inverted pendulums (MIP) are good alternatives for three or four wheels vehicles used in industries or services such as robotic wheelchairs. However, they are statically unstable and controllers are applied to keep their stability. Most controllers developed so far are torque based, that is, they rely on the torques applied to MIPs wheels. In this paper a new control method is proposed in which a movable mechanism is in a form of pendulum is added to the MIP and its position can be varied by a computed torque controller to stabilize system. The controller is developed from the equation of motion of the system derived from the Newtonian method. Simulation results show that it has a better performance than the conventional wheel torque based controller, while the input torque to actuate the movable pendulum remains low.
Learning to Pour using Deep Deterministic Policy Gradients

Pouring is a fundamental skill for robots in both domestic and industrial environments. Ideally, a robot should be able to pour with high accuracy to specific, pre-defined heights and without spilling. However, due to the complex dynamics of liquids, it is difficult to learn how to pour to achieve these goals. In this paper we present an approach to learn a policy for pouring using Deep Deterministic Policy Gradients (DDPG). We remove the need for collecting training experiences on a real robot, by using a state-of-the-art liquid simulator, which allows for learning the liquid dynamics. We show through our experiments, performed with a PR2 robot, that it is possible to successfully transfer the learned policy to a real robot and even apply it to different liquids.
Concept for Controlled Business Critical Information Sharing Using Smart Contracts

Trust management has been a topic of keen interest in recent years. There has been a lot of discussion as to what new opportunities it can bring to markets, what benefits it can offer, and what system development possibilities it enables for software development. In this paper we discuss trust management and business critical information sharing in a definite group of stakeholders called Circle of Trust. We examine the key features of the Circle of Trust in military environments. We address the most essential problems and obstacles to be considered before the benefits of Circle of Trust can be fully enabled therein. As a solution to problems with the information transfer management, we propose a novel conceptual approach which ensures the privacy of the data source and transparency of information sharing utilizing the blockchain technology and modern cryptographic solutions. In addition, the concept presented enables the quantitative information trade and objective control mechanism for contractual liabilities within the consortium. The discussion and views presented in this paper can be adopted in any organization with doubts concerning the sensitive and classified contents of supply chain management or current ICT systems.
Impedance Based Force Control for Aerial Robot Peg-in-Hole Insertion Tasks

This paper demonstrates the experimental validation of canonical peg-in-hole manipulation task using an aerial robot. The robot consists of a multirotor platform equipped with a dual arm multi degree of freedom manipulator. The paper discusses the introduced kinematic constraints which make sure the robot holds a bolt with both arms. We build our peg-in-hole approach using impedance control which is the foundation of compliant interaction with the environment. We utilize a finite state automaton to plan a multi stage strategy which relies on tactile perception in order to pin point the target. Finally, the whole body locomotion is considered, meaning both the degrees of freedom of multirotor base and the dual arm manipulator are considered.
A Review on Neurocomputing Based wind Turbines Fault Diagnosis and Prognosis

Renewable energy, especially wind power energy, has gone through fast growth in the last decade According to the Global Wind Energy Council (GWEC), the worldwide global installed wind power capacity has reached 486.8 GW in 2016 and may reach 817 GW by 2021. Commonly, wind turbines (WTs) are located in remote areas with limited access and their maintenance and repairing operations often require the use of expensive equipment such as cranes and lifting machinery, increasing significantly the operation and maintenance (O&M) costs that may far exceed the cost of the failed component itself. Moreover, one of the main sources for the O&M costs is the unscheduled maintenance due to unexpected failures. Therefore, fault diagnosis and prognosis are critical to help reducing O&M costs and keeping wind power a competitive energy source. The main contribution of this paper is an updated, unbiased and repeatable search, review and analysis (summary and classification) of the main approaches, e.g. methods and techniques, for WTs fault diagnosis and prognosis. A systematic review of neurocomputing based approaches is presented, including innovative comprehensive lists of references grouped by the studied WT components. The paper concludes with a discussion on some promising future research directions.
3-Dimensional Channel-Shuffling Single-mode Polymer Waveguides: Design and Fabrication

This paper introduces 3-dimensional channel-shuffling single-mode circular core polymer optical waveguides for optical printed circuit boards (OPCBs) using the unique fabrication technique, named the Mosquito method. In this waveguide, the fabricated cores are horizontally and vertically bent to have crossover structures, where a height gap between two core layers is added in order to obtain higher wiring density.
Smart ECG Holter Monitoring System Using Smartphone

The Prevention of cardiovascular disease requires continuous monitoring of cross-clock ECG signals along with the activity status. Traditional ECG Holter has numerous electrodes connected to the chest, which is heavy, so it is very difficult to carry by the patient, so ECG monitoring usually requires the patient to stay in the hospital for a long time. This paper presented a small ECG Holter device that was developed to detect arrhythmias in real-time based on Android mobile application. The ECG signals are obtained directly through ECG’s three-electrode sensor then transmitted through a Bluetooth module to Android smartphone. Prepossessing ECG signal algorithm is implemented on Arduino Device. Android mobile application analysis and classify patient’s ECG data to detect abnormal signs. Data used in testing and training was 303 cases acquired from El-Monofia University, 162 cases were normal, and 141 cases were abnormally divided into 57 cases were Coronary Artery Disease, 36 cases were Old Anterior Myocardial Infarction, and 48 cases were Sinus tachycardia. The experimental results show that the presented system’s performance has been improved in the accuracy of diagnosis of arrhythmias and the identification of the most widely recognized anomalies in various activities.
Theoretical Analysis on Affecting Factors of Power Line Harmonic Radiation

Power line harmonic radiation (PLHR) is an artificial electromagnetic pollution source in the near-earth space environment. Up until now, there has been little quantitative research on its formation mechanism. This paper details a model and solver for electromagnetic waves propagation in a stratified anisotropic ionosphere. In our model, these electromagnetic waves are generated by an arbitrary electric dipole source above a nonideal conductive ground. The matrix-exponent method and a full-wave method are combined to analyze the model, avoiding the problem of numerical overflow and swamping in numerical calculations. The computing results obtained from the proposed method and the observed electric field data by using DEMETER satellite are compared and found to be in good agreement. Furthermore, this paper considers the effects on PLHR propagation in the ionosphere due to dipole source frequency, earth’s conductivity, electron density, geographic latitude, and geomagnetic field orientation. Results show that when the frequency increases, the strength of PLHR penetrating into the ionosphere has an increasing tendency. If the harmonic current remains constant, lower ground conductivity and electron density of the ionosphere result in higher radiation power. PLHR propagates along the direction of the geomagnetic field in the ionosphere, and its strength decreases with the increasing geomagnetic inclination at the same height. In addition, the radiation power of less than 1 W may trigger PLHR.
Sustainability Simulation and Assessment of Bicycle Network Design and Maintenance Environment

Humans are an integral part of the nature and to avoid imbalance, the impact of technology on the surrounding environment should be limited. Therefore, green technologies are becoming an important part of economy, politics and science. One of the largest sources of pollution are motorized vehicles, that account for around 14 % of the global greenhouse gas emissions [1]. Use of green transportation within the integrated multimodal transport system is important to minimize carbon emissions [2]. One of these means of transportation is cycling. For cycling to become a fully integrated element within a multimodal transport system and not just a type of tourism, an appropriate infrastructure is necessary – cycling routes, lighting, bike rental, parking, repair services, as well as alignment with other types of transport. Cyclists need route planning tools, information about road surface quality, relief, and usage patterns during different weather conditions and over different days of the week. Infrastructure development projects demand significant financial resources and therefore municipalities need sustainable tools for services design and management. In this article the authors discuss acceptance and sustainability assessment methodology IASAM use to validate the VeloRouter - cycling network designing technology.
Development of a Smart Rotameter with Intelligent Temperature Compensation

Rotameter is a particular kind of flow meter, based on variable area principle. In this paper, an intelligent inductive pickup type flow transducer using rotameter is developed with temperature compensation. The float of rotameter is attached with a ferromagnetic wire and with the movement of float the self-inductance of inductive pickup changes. The self-inductance is changed into a voltage with the modified Maxwell bridge network. The density of the fluid flowing through the rotameter get changed with the change in temperature, and it disturbs the calibration of rotameter. In this paper, different ANN (Artifical neural network) algorithm scheme is used for compensating the temperature influence in the modified rotameter.
A Review of Sparse Recovery Algorithms

Nowadays, a large amount of information has to be transmitted or processed. This implies high-power processing, large memory density, and increased energy consumption. In several applications, such as imaging, radar, speech recognition, and data acquisition, the signals involved can be considered sparse or compressive in some domain. The compressive sensing theory could be a proper candidate to deal with these constraints. It can be used to recover sparse or compressive signals with fewer measurements than the traditional methods. Two problems must be addressed by compressive sensing theory: design of the measurement matrix and development of an efficient sparse recovery algorithm. These algorithms are usually classified into three categories: convex relaxation, non-convex optimization techniques, and greedy algorithms. This paper intends to supply a comprehensive study and a state-of-the-art review of these algorithms to researchers who wish to develop and use them. Moreover, a wide range of compressive sensing theory applications is summarized and some open research challenges are presented.
Dynamic Modelling and Control of Self-Balancing One-Legged Robot

One-legged robot is a class of underactuated legged robots that has been a challenging system to develop and control. There are limitless possible configurations of such system, each with its own specific advantages and limitations. This paper presents the dynamic modelling of a single contact point one-legged robot based on Euler-Lagrange formulation. The obtained equations of motion are then used as basis to develop an experimental prototype and its balancing control system. The mechanical configuration used in the prototype allows the decoupling of the control systems on the coronal and sagittal planes. The experimental results are presented.