Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time Blind Source Separation Of Acoustic Signals With A Recursive Approach

We propose an approach for real-time blind source separation (BSS), in which the observations are linear convolutive mixtures of statistically independent acoustic sources. A recursive least square (RLS)-like strategy is devised for real-time BSS processing. A normal equation is further introduced as an expression between the separation matrix and the correlation matrix of observations. We recursively estimate the correlation matrix and explicitly, rather than stochastically, solve the normal equation to obtain the separation matrix. As an example of application, the approach has been applied to a BSS problem where the separation criterion is based on the second-order statistics and the non-stationarity of signals in the frequency domain. In this way, we realise a novel BSS algorithm, called exponentially weighted recursive BSS algorithm. The simulation and experimental results showed an improved separation and a superior convergence rate of the proposed algorithm over that of the gradient algorithm. Moreover, this algorithm can converge to a much lower cost value than that of the gradient algorithm.
Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images

Diagnosis of breast carcinomas has so far been limited to the morphological interpretation of epithelial cells and the assessment of epithelial tissue architecture. Consequently, most of the automated systems have focused on characterizing the epithelial regions of the breast to detect cancer. In this paper, we propose a system for classification of hematoxylin and eosin (H&E) stained breast specimens based on convolutional neural networks that primarily targets the assessment of tumor-associated stroma to diagnose breast cancer patients. We evaluate the performance of our proposed system using a large cohort containing 646 breast tissue biopsies. Our evaluations show that the proposed system achieves an area under ROC of 0.92, demonstrating the discriminative power of previously neglected tumor associated stroma as a diagnostic biomarker.
Designing Safe Smart Home Systems for Vulnerable People

Designing assistive technological solutions for people with disabilities and older people is fraught with problems due to the number of agencies involved. These problems are compounded by the lack of understanding that can exist between the engineers and the health staff. This lack of understanding can develop into extreme delays in installing the technology and the needs of the person with disabilities being subsumed in preference to ease of design and installation. Clearly, these potential misunderstandings could be ameliorated by improved communication between the widely different disciplines each with their own culture, ethos, knowledge and jargon. The CUSTODIAN smart house simulation software provides a focus for discussion on CUSTODIAN’s development in relation to reliability and safety of systems design.
In Vitro Evaluation of Major In Vivo Drug Metabolic Pathways Using Primary Human Hepatocytes and HepaRG Cells in Suspension and a Dynamic Three-Dimensional Bioreactor System

Major human specific metabolites, not detected during in vivo and in vitro preclinical studies, may cause unexpected drug interactions and toxicity in human and delays in clinical programs. Thus, reliable preclinical tools for the detection of major human metabolites are of high importance. The aim of this study was to compare major drug metabolic pathways in HepaRG cells, a human hepatoma cell line, to fresh human hepatocytes, cryopreserved human hepatocytes, and human in vivo data. Furthermore, the maintenance of cytochrome P450 (P450) and UDP-glucuronosyltransferase (UGT) activities in a dynamic three-dimensional (3D) bioreactor were evaluated over time by using HepaRG cells and human hepatocytes. 14C-diclofenac and a candidate from AstraZeneca's drug development program, 14C-AZD6610, which are metabolized by P450 and UGT in vivo, were used as model substrates. The proportion of relevant biotransformation pathways of the investigated drug was clearly different in the various cell systems. The hydroxylation route was favored in primary human hepatocytes, whereas the glucuronidation route was favored in HepaRG cells. The human in vivo metabolite profile of AZD6610 was best represented by human hepatocytes, whereas all major diclofenac metabolites were detected in HepaRG cells. Moreover, the metabolite profiles in cryopreserved and fresh human hepatocytes were essentially the same. The liver bioreactor using both fresh human hepatocytes and HepaRG cells retained biotransformation capacity over 1 week. Thus, the incubation time can be increased from a few hours in suspension to several days in 3D cultures, which opens up for detection of metabolites from slowly metabolized drugs.
Support vector machine based conformal predictors for risk of complications following a coronary Drug Eluting Stent procedure

Drug Eluting Stents (DES) have distinct advantages over other Percutaneous Coronary Intervention procedures, but have been associated with the development of serious complications after the procedure. There is a growing need for understanding the risk of these complications, which has led to the development of statistical risk evaluation models. Conformal Predictors are a recently developed set of machine learning algorithms that allow not just risk classification on new patients, but add valid measures of confidence in predictions for individual patients. In this work, we have applied a novel Support Vector Machine (SVM) based conformal prediction framework to predict the risk of complications following a coronary DES procedure. This predictive model helps to risk stratify a patient for post-DES complications, and the valid measures of confidence can be used by the physician to make an informed, evidence-based decision to manage the patient appropriately.
Who, how, and why? Enhancing privacy awareness in Ubiquitous Computing

The combination and integration of sensing and interaction capabilities with almost ubiquitous inter-connectivity are basic requirements for context-aware systems to unobtrusively and invisibly support users in their daily activities. However, the invisible nature of such systems also threatens users' privacy. Users often lack awareness about a system's capabilities to gather data or to intervene in user activities, or even the system's presence. We propose a model to enhance user-centric privacy awareness by consistently modeling observations and disturbances of users. The model allows to capture who is affecting a user's privacy, how privacy is affected, and why it is affected. We further discuss how this model can be instantiated with discovery of channel policies.
Une approche distribuée pour l'extraction de connaissances: application à l'enrichissement de l'aspect factuel des BDG

Résumé. Les systèmes d’informations géographiques (SIG) sont utilisés pour améliorer l’efficacité des entreprises et des services publics, en associant méthodes d’optimisation et prise en compte de la dimension géographique. Cependant, les bases de données géographiques (BDG) stockées dans les SIG sont restreintes à l’application pour laquelle elles ont été conçues. Souvent, les utilisateurs demeurent contraints de l’existant et se trouvent dans le besoin de données complémentaires pour une prise de décision adéquate. D’où, l’idée de l’enrichissement de l’aspect descriptif des BDG existantes. Pour atteindre cet objectif, nous proposons une approche qui consiste à intégrer un module de fouille de données textuelles au SIG lui même. Il s’agit de proposer une méthode distribuée de résumé de documents multiples à partir de corpus enligne. L’idée est de faire coopérer un ensemble d’agents s’entraidant afin d’aboutir à un résumé optimal.
Finite-element modelling reveals force modulation of jaw adductors in stag beetles

Male stag beetles carry large and heavy mandibles that arose through sexual selection over mating rights. Although the mandibles of Cyclommatus metallifer males are used in pugnacious fights, they are surprisingly slender. Our bite force measurements show a muscle force reduction of 18% for tip biting when compared with bites with the teeth located halfway along the mandibles. This suggests a behavioural adaptation to prevent failure. We confirmed this by constructing finite-element (FE) models that mimic both natural bite situations as well as the hypothetical situation of tip biting without muscle force modulation. These models, based on micro-CT images, investigate the material stresses in the mandibles for different combinations of bite location and muscle force. Young's modulus of the cuticle was experimentally determined to be 5.1 GPa with the double indentation method, and the model was validated by digital image correlation on living beetles. FE analysis proves to be a valuable tool in the investigation of the trade-offs of (animal) weapon morphology and usage. Furthermore, the demonstrated bite force modulation in male stag beetles suggests the presence of mechanosensors inside the armature.
Stable Bilateral Control of Teleoperators Under Time-varying Communication Delay: Time Domain Passivity Approach

In this paper, modified two-port time-domain passivity approach is proposed for stable bilateral control of teleoperators under time-varying communication delay. We separate input and output energy at each port of a bilateral controller, and propose a sufficient condition for satisfying the passivity of the bilateral controller including time-delay. Output energy at the master port should be less than the transmitted input energy from the slave port with time-delay, and output energy at the slave port should be less than the transmitted input energy from the master port with time-delay. For satisfying above two conditions, two passivity controllers are attached at each port of the bilateral controller. Teleoperation experiment with about 120 (msec) of time-delay each way is performed. Stable teleoperation is achieved in free motion and hard contact as well.
Characterization of Hog Cholera Virus I. Determination of Buoyant Density

Horzinek, Marian (Tierärztliche Hochschule, Hannover, West Germany). Characterization of hog cholera virus. I. Determination of buoyant density. J. Bacteriol. 92:1723–1726. 1966. —Hog cholera virus was subjected to cesium chloride density gradient centrifugation. Most of the infectious activity was detected in fractions with densities between 1.15 and 1.20 g/ml, with a peak at 1.16 g/ml. Infectivity was assayed by use of either the exaltation of Newcastle disease virus method or the hemagglutination exaltation and inhibition of cytopathic effect method.
Replicability of Dynamically Provisioned Scientific Experiments

The ability to repeat an experiment, known as replicability, is a basic concept of scientific research and also an important aspect in the field of eScience. The principles of Service Oriented Computing (SOC) and Cloud Computing, both based on high runtime dynamicity, are more and more adopted in the eScience domain. Simulation experiments exploiting these principles introduce significant challenges with respect to replicability. Current research activities mainly focus on how to exploit SOC and Cloud for eScience, while the aspect of replicability for such experiments is still an open issue. In this paper we define a general method to identify points of dynamicity in simulation experiments and to handle them in order to enable replicability. We systematically examine different types of service binding strategies, the main source of dynamicity, and derive a method and corresponding architecture to handle this dynamicity with respect to replicability. Our work enables scientists to perform simulation experiments that exploit the dynamicity and flexibility of SOC and Cloud Computing but still are repeatable.
Quality of service support for recording and playback of MBone sessions in heterogeneous IP/ATM networks

Many video and audio sessions are transmitted via the Multicast Backbone (MBone) medium day by day. The Integrated Services architecture of the Internet will make it now possible to transmit and receive these sessions in a 'guaranteed' quality of service. To allow this in heterogeneous networks, consisting of, e.g. Ethernet and ATM, an interaction between the QoS architectures of the Internet and ATM is necessary. However, they are very different, so mapping them is a difficult task. In this paper, the implementation of an interaction approach for the QoS architectures developed for the Internet and for ATM, and the extension of the MBone VCR for recording and playing back MBone sessions in a higher quality, is described. This system allows the QoS supported recording and off-line playback of MBone session in heterogeneous IP/ATM networks.
Linear prediction and discrete wavelet transform to identify pathology in voice signals

This work describes an algorithm to help in the identification of pathologically affected voices. Based on inverse linear prediction filter (LPC) and discrete wavelet transform (DWT), this method can be used in conjunction with other classifiers in order to improve them, by the addition of the new parameter we propose, DWT-RMS. Using no association with other methods, DWT-RMS gives quantitative evaluation of voice signals from male and female subjects of different ages and leads to an adequate larynx pathology classifier with 85.94% of classification accuracy, 0% of false negatives and 14.06% of false positives, to identify nodules in vocal folds.
Tasks , Games and Domain Knowledge in Dialogue Management

The inexorably rising cost of healthcare provision is a major problem worldwide. A cost-effective way of improving quality of care while containing costs is to manage clinical decision-making and workflow by means of computerized care pathways. These pathways are increasingly represented using machine-readable formalisms, and this creates important opportunities for developing flexible natural language interfaces for capturing clinical data (e.g. taking clinical histories) and giving advice (e.g. recommending clinical actions). Natural language interaction could also offer patients more control of their own care, by allowing them to obtain advice whenever and as often as they need it. Voice interaction seems a particularly suitable approach as speech is a natural way for people to communicate and does not require the patient to use any technology other than a telephone. Spoken dialogue systems have great potential for delivery of healthcare services. However medical applications that provide advice to patients or to practitioners pose particular problems relative to standard information seeking dialogues such as flight booking or banking. In most current commercial dialogue systems, the dialogue designer specifies the exact interactions which can take place. Manual-coding allows precise control of what can occur within a dialogue, but is an expensive process, especially for complex dialogues. In the medical domain, the knowledge structures are particularly complex, and the system requires complex reasoning and decision-making to respond to the user. It therefore seems necessary to integrate technologies such as medical guidelines and advice systems directly with the dialogue system so that dialogues can be generated automatically to reflect user behaviour and changes in clinical context. 2 Solution
Thwarting Adversaries with Unpredictability: Massive-scale Game-Theoretic Algorithms for Real-world Security Deployments

Protecting critical infrastructure and targets such as airports, transportation networks, power generation facilities as well as critical natural resources and endangered species is an important task for police and security agencies worldwide. Securing such potential targets using limited resources against intelligent adversaries in the presence of the uncertainty and complexities of the real-world is a major challenge. My research uses a game-theoretic framework to model the strategic interaction between a defender (or security forces) and an attacker (or terrorist adversary) in security domains. Game theory provides a sound mathematical approach for deploying limited security resources to maximize their effectiveness. While game theory has always been popular in the arena of security, unfortunately, the state of the art algorithms either fail to scale or to provide a correct solution for large problems with arbitrary scheduling constraints. For example, US carriers fly over 27,000 domestic and 2,000 international flights daily, presenting a massive scheduling challenge for Federal Air Marshal Service (FAMS). My thesis contributes to a very new area that solves game-theoretic problems using insights from large-scale optimization literature towards addressing the computational challenge posed by real-world domains. I have developed new models and algorithms that compute optimal strategies for scheduling defender resources is large real-world domains. My thesis makes the following
The CyberWalk Platform: Human-Machine Interaction Enabling Unconstrained Walking through VR

In recent years, Virtual Reality (VR) has become increasingly realistic and immersive. Both the visual and auditory rendering of virtual environments have been improved significantly, thanks to developments in both hardware and software. In contrast, the possibilities for physical navigation through virtual environments (VE) are still relatively rudimentary. Most commonly, users can ‘move’ through highfidelity virtual environments using a mouse or a joystick. Of course, the most natural way to navigate through VR would be to walk. For small scale virtual environments one can simply walk within a confined space. The VE can be presented by a cave-like projection system, or by means of a head-mounted display combined with head-tracking. For larger VEs, however, this quickly becomes impractical or even impossible. Different locomotion interfaces already exist that allow walking in virtual environments (see, e.g., the surveys in [1] and [2]). However, they usually constrain the feet, the body, or the legs of the user. Moreover, locomotion is either restricted to a 1D motion on a linear treadmill, like in the Treadport platform [3] with possible slope effects [4], or is limited in space and speed, like in the case of the moving tiles of the CirculaFloor [5]. In the CyberWalk European research project [6], we set out to develop an omnidirectional treadmill system that allows for unconstrained walking in all directions through large scale virtual environments. To this end, a novel motion concept for unconstrained walking on a plane has been developed: the “omni-directional” CyberWalk platform (Figs. 1–2). The platform consists of an array of synchronous linear belts C1, C2, . , CN that can be displaced with a common velocity vcx in the (blue) direction, which is orthogonal to the (yellow) velocity vcy of each independent belt. Thus, a velocity with any (green) direction in the plane can be obtained as a combination of the two linear motions. This concept is similar, although with different implementations of the mechanical, actuation, and control parts, to the Omnidirectional Treadmill proposed in [7], which uses two perpendicular belts and a large number of rollers, and to the Torus Treadmill [8], having a torusshaped belt arrangement but of quite small dimensions. On the CyberWalk platform, the walker can experience
Sliding mode observer for nonlinear uncertain systems

A new sliding mode observer for a class of nonlinear uncertain systems is proposed in this article. The proposed sliding mode observer works under much less conservative conditions than previous nonlinear unknown input observers. Also, a functional version of the observer is proposed in certain cases where it may not be possible to design an observer capable of estimating the entire state of the system.
Variability aware cell library optimization for reliable sub-threshold operation

Standard cell libraries are designed focusing on the best performance-area trade-off for a technology at nominal supply. Scaling supply voltages emphasizes the effects of systematic or random variation. We revisit existing approaches and present two new design points in standard CMOS that target variability hardened standard cells integrated into the digital design flow. They are optimized for dynamic and stand-by power, respectively. A speed-up from 1.4 to more than 3x is achieved on cell level. These gains are preserved in the example of an FIR filter while even improving in energy efficiency. The analysis and design has been performed in a low-power 40nm CMOS technology.
A systematic selection of an alternative parameterisation for predictive control

Alternative parameterisations have been shown to improve the feasible region for a predictive control law when the number of degrees of freedom is limited. One question yet to be resolved is: which alternative parameterisation is best for a particular problem and what choice of parameter(s) within each parameterisation will lead to an improved feasible region with good performance? This paper tackles this question and demonstrates two systematic approaches to select the best alternative parameterisations. These approaches are based on multiobjective optimisation and a pragmatic selection. Numerical examples demonstrate the efficacy of both methods.
Analysis and Visualization for Hot Spot Based Route Recommendation Using Short-Dated Taxi GPS Traces

Taxi GPS traces, which contain a great deal of valuable information as regards to human mobility and city traffic, can be extracted to improve the quality of our lives. Since the method of visualized analysis is believed to be an effective way to present information vividly, we develop our analysis and visualization method based on a city’s short-dated taxi GPS traces, which can provide recommendation to help cruising taxi drivers to find potential passengers with optimal routes. With our approach, hot spots for loading and unloading passenger(s) are extracted using an improved DBSCAN algorithm after data preprocessing including cleaning and filtering. Then, this paper describes the start-end point-based similar trajectory method to get coarse-level trajectories clusters, together with the density-based e distance trajectory clustering algorithm to identify recommended potential routes. A weighted tree is defined including such factors as driving time, velocity, distance and endpoint attractiveness for optimal route evaluation from vacant to occupied hot spots. An example is presented to show the effectiveness of our visualization method.
A real-time model-based human motion analysis system

This paper introduces a real time model-based human motion analysis system using two orthogonal views. The goal of the system is to analyze the motion of the human object without using any markers on the object. The system will generate the corresponding body definition parameters (BDPs) and body animation parameters (BAPs) defined by MPEG-4. With the BDPs and a sequence of BAPs, a real-time virtual actor can be synthesized on various platforms.