Miracle-dz/UniFAR-FTUs huggingface dataset:
Rescue robotics — a crucial milestone on the road to autonomous systems

Rescue robotics is an important steppingstone in the scientific challenge to create autonomous systems. There is a significant market for rescue robots, which have unique features that allow a fruitful combination of application-oriented developments and basic research. Unlike other markets for advanced robotics systems like service robots, the rescue robotics domain benefits from the fact that there is a human in the loop, which allows a stepwise transition from dumb teleoperated devices to truly autonomous systems. Current teleoperated devices are already very useful in this domain and they benefit from any bit of autonomy added. Human rescue workers are a scarce resource at disaster scenarios. A single operator should, hence, ideally supervise a multitude of robots. We present results from the rescue robots at the International University Bremen in a core area supporting autonomy, i.e., mapping.
A Terminological Logic with Defaults: A Definition and an Application

In this paper we present a terminological language which includes defaults, and a definition of default subsumption based on the notion of skeptical in­ heritance in default reasoning. Except for the in­ clusion of defaults the language is limited when compared to most terminological logics. However defaults are a necessary construct in many applica­ tions and we suggest that the language presented here is a useful tradeoff between different types of expressivity We present an algorithm for classify­ ing new concepts into the default hierarchy repre­ senting the taxonomy, and in addition an algorithm for what we call default classification, suitable for interactive reasoning about individuals. We de­ scribe a diagnosis application which has been im­ plemented using this language and reasoning mech­ anisms. We present an evaluation of the diagnosis application on the basis of comparison with 63 pa­ tient protocols. We conclude that the language pre­ sented is in fact adequate for the application pre­ sented here and hypothesize that it i . s interesting for a significant group of applications. 1 Introduction Taxononiic representations and reasoning have been popular in A.l. for a long time, largely because they provide an efficient way of representing knowledge and organising it for reasoning purposes. The two main kinds of taxononiic reasoning to be found in the litera­ ture are classification (e.g. [Brachinan ei al., 1991]) and default inheritance reasoning (e.g. [Horty et a/., 1987; Fahhnan, 1979]). Classification in systems with strict inheritance hierarchies has been used in a number of ap­ plications. However the kind of classification systems used here have also been criticised for not having the • necessary expressivity of defaults [Doyle and Patil, 1991]. Default reasoning on the other hand has been used very little in real applications since the early work with NETL [Fahlman, 1979]. Recently there has been increased interest in incorpo­ rating defaults and principled default reasoning reason­ ing into classification systems. Some problems have been identified [Padgham and Nebel, 1993] and some theories for integrating default reasoning in terminological logics 1 have been developed [ In this work we define a language which is relatively sim­ ple compared to most terminologic logics (e.g. [Patel-Schneider et al., 1990]), but which also contains impor­ tant constructs not (usually) found in other languages of this type-namely defaults and features with predicate values. (The latter is however not the concern of this paper). In the search for computationally …
Texture mapping for view-dependent rendering

View-dependent multiresolution meshes allow smooth interactive animation and optionally time-critical rendering of huge geometric data-sets and are therefore an important tool for large-model visualization. So far most viewd-ependent rendering frameworks are restricted to models with a topologically simple texture mapping. Our approach overcomes this restriction with a new texturing technique, which allows texture mapping during the runtime simplification process. In fact, novel algorithm generates a graph of textures in a preprocess automatically. This texture graph is furthermore integrated into a view-dependent rendering approach. Particularly we perform a texture validation step for the whole vertex tree, which is the basic data structure in the framework. At runtime the vertex tree is traversed and we introduce a texture proxy map to assure correct texture mapping during view-dependent rendering. Additionally the new technique allows us to guarantee a constant frame rate. Finally the results of our method enhancing visual detail of geometric models are shown.
Vadim Cherezov Coupled Receptor −-Adrenergic G Protein 2 β High-Resolution Crystal Structure of an Engineered Human

clicking here. colleagues, clients, or customers by , you can order high-quality copies for your If you wish to distribute this article to others here. following the guidelines can be obtained by Permission to republish or repurpose articles or portions of articles ): June 28, 2012 www.sciencemag. org (this information is current as of The following resources related to this article are available online at http://www.sciencemag.org/content/318/5854/1258.full.html version of this article at: including high-resolution figures, can be found in the online Updated information and services, http://www.sciencemag.org/content/suppl/2007/10/26/1150577.DC1.html http://www.sciencemag.org/content/suppl/2007/11/21/318.5854.1258.DC2.html can be found at: Supporting Online Material http://www.sciencemag.org/content/318/5854/1258.full.html#related found at: can be related to this article A list of selected additional articles on the Science Web sites http://www.sciencemag.org/content/318/5854/1258.full.html#ref-list-1 , 1 of which can be accessed free: cites 2 articles This article 663 article(s) on the ISI Web of Science cited by This article has been http://www.sciencemag. org/content/318/5854/1258.full. html#related-urls 100 articles hosted by HighWire Press; see: cited by This article has been http://www.sciencemag. org/cgi/collection/biochem Biochemistry subject collections: This article appears in the following
Ventricular arrhythmias in competitive athletes: risk stratification with T-wave alternans

Introduction: Aim of our study is to evaluate the role of TWA to stratify the risk of sudden cardiac death in athletes (Ath) with complex ventricular arrhythmias (VA), and to document a possible correlation between TWA and electrophysiological testing (EES) results. Methods: We studied 43 Ath with VA (31 M, mean age 34 ± 12 years). In all cases a cardiological evaluation was performed, including TWA and EES. The patients were evaluated during a follow-up of 25 ± 22 months. The end-point was the occurrence of sudden death or malignant ventricular tachyarrhythmias (VT). Results: TWA was negative in 28 Ath (65%), positive in 8 (19%) and indeterminate in 7 (16%). All subjects with negative TWA did not show induction of VT at EES, with significant correlation between negative TWA and negative EES (p<0.001). All Ath with positive TWA also had VT induced by a EES, but without significant correlation between positive TWA and positive EES. In 2 Ath with undetermined TWA (29%) VT were induced at EES. Our data did not show significant correlation between indeterminate TWA and positive or negative EES. However, logistic regression analysis showed significant correlation between abnormal TWA test (positive or indeterminate) and inducibility of VT at EES (p<0.001). During follow-up we observed a significant difference in end-point occurrence between Ath with negative or positive TWA and between Ath with negative or positive EES. Conclusion: TWA confirm its role as a simple and non-invasive test, and it seems useful for prognostic stratification of Ath with VA.
Science Autonomy in the Atacama

We have recently embarked on a three-year project, funded by the NASA ASTEP program, to develop robotic astrobiology in the process of learning the limits of life in the Atacama desert of Chile. We see this as an opportunity to develop a more science-aware rover: one that, on encountering a new area, can select interesting features, perform initial experiments, and selectively return relevant data, all before receiving feedback from the science team. Several components of the proposed science autonomy system can make use of classifiers (is this the kind of rock we are looking for? ) and clustering algorithms (is this rock like anything we have already sampled? ). The unknown character of unexplored areas motivates use of on-line learning techniques.
A Study on Remaining Useful Life Prediction for Prognostic Applications

We consider the prediction algorithm and performance evaluation for prognostics and health management (PHM) problems, especially the prediction of remaining useful life (RUL) for the milling machine cutter and lithium‐ion battery. We modeled battery as a voltage source and internal resisters. By analyzing voltage change trend during discharge, we made the prediction of battery remain discharge time in one discharge cycle. By analyzing internal resistance change trend during multiple cycles, we were able to predict the battery remaining useful time during its life time. We showed that the battery rest profile is correlated with the RUL. Numerical results using the realistic battery aging data from NASA prognostics data repository yielded satisfactory performance for battery prognosis as measured by certain performance metrics. We built a battery test platform and simulated more usage pattern and verified the prediction algorithm. Prognostic performance metrics were used to compare different algorithms. Prognostics and Health Management, Remaining Useful Life, Lithium‐ion Battery, Linear Regression
Hardware-oriented stereo vision algorithm based on 1-D guided filtering and its FPGA implementation

This paper presents a novel hardware-oriented stereo vision system based on 1-D cost aggregation. Many researchers have implemented hardware efficient stereo matching to realize real-time systems. However, such methods require a large amount of memory. We proposed a system that is based on a hardware-software hybrid architecture for memory reduction. It consisted of grayscale 1-D cost aggregation HW and 2-D disparity refinement SW. The 1-D processing reduced the size of RAM in our HW to 266 kb with an input image size of 1024×768. We achieved the average error rate for the Middlebury datasets as 6.24%. The processing time was 56.6 ms for the 1024×768 images and an average of 8.6 ms for the Middlebury datasets which have an average size of 400×380. Using the resolution of Middlebury datasets, our system can perform real-time depth-aided image processing.
Localized shrinkage covariance estimation of hyperspectral image classification

Many existing pattern recognition techniques require the estimation of the covariance matrix. When the number of available samples is sufficient large relative to the dimension the features, a maximum likelihood estimator or a related unbiased covariance matrix estimator can be applied. In the classification task of the hyperspectral image, however, the number of available observations is very limited or even smaller than the number of bands due to the access of the ground truth samples is costly and valuable. In this case, the performance of the maximum likelihood related estimators will be poor. Thus, the classification accuracy of the corresponding classification methods is unsatisfied. Based on the idea of combining several different structures in an estimator, a new covariance matrix estimator called localized shrinkage covariance estimator (LSCE) is proposed in this study. The performance of LSCE is evaluated via the classification accuracy of the linear discriminant classifier (LDC) using LSCE as the estimator of its covariance matrix. The results of the simulation studies show that LSCE is an ideal covariance estimator and the classical method LDC can be a very competitive classifier comparing to other popular techniques in hyperspectral data classification.
Employing Rapid Prototyping biomedical model to assist the surgical planning of defect mandibular reconstruction

Mandibular defects need customized titanium plates for reconstruction. The conventional design process of titanium plate is prior to surgical interventions. The efficiency and accuracy of the conventional method is mainly dependent on experiences and skills of the designer. In order to decrease the dependence on design experience and enhance the participation of surgeons in the design process, designing and fabricating a customized titanium plate implant according to Rapid Prototyping (RP) biomedical model could be employed. RP biomedical model is greatly convenient to diagnosis and treatment planning. It could decrease the operation time and the risk of misinterpretation of the medical problem. In these cases, the operation time was reduced by 1.5–2.5 hours. A physical biomedical model also facilitates surgery planning and makes the rehearsal and simulation of the operation possibly. The customized titanium plate shape conforms to the patient's mandible anatomy and is thick enough to provide the strength and stiffness needed to fix the mandible until the bone grafts and soft tissues heal. At the same time it is thin enough to avoid extensive intrusion into soft tissues and to avoid weighing too much for the patient's jaw.
Clustering Technology of a Data Engine for Analytical Computing

Contemporary scientific studies frequently rely on data-intensive analytical computing. While the main goal of this emerging form of computing is to facilitate hypothesis formulation or to test the validity of a postulated model, its primary method is usually that of data clustering. Since typical analytical tasks operate on very large volumes of potentially highdimensional data, scientific studies also face enormous problems of scale. This paper describes the clustering technology of a new engine for data-intense analytical computing. The technology is designed to operate in high-dimensional feature spaces without requiring dimensionality reduction. This enables the data engine to achieve high degrees of scalability and high interoperability between the analytical tasks. Most processes supported by the engine operate on a shared aggregate representation of data in the original feature space.
Linear feedback communication systems with Markov sources: optimal system design and performance evaluation

The optimal analog discrete-time feedback communication system is designed for the transmission of a Markov process, such as that generated by a combined source/channel encoder. The forward channel is affected by an additive white Gaussian noise, while the feedback channel is causal and noiseless; no repetition of the transmitted sample is assumed. On the basis of the minimum mean square error (MMSE) criterion, the optimal transmitter and receiver are derived under the constraint of a maximum power level for the transmission over the forward channel. The resulting optimized system is adaptive and fully exploits the available power, thus maximizing the information rate transferred by the system itself. For comparison purposes, the optimal MMSE communication system without feedback link is also designed. The MSE performance of both systems, with and without feedback link, is evaluated by means of closed-form expressions and their convergence rate to the steady state is also computed. Using the feedback link gives significant performance improvements when the input-encoded process is moderately or highly correlated; in this case, the advantages offered by the combined source-channel coding techniques are fully exploited by the proposed optimized feedback communication systems.
Integrating InfoVis and GeoVis Components

We introduce our generic "GeoAnalytics" visualization (GAV) component toolkit, based on the principles behind visual analytics (VA), for dynamically exploring time-varying, geographically referenced and multivariate attribute data. GAV includes components that supports a mixture of technologies from the three visualization fields; information visualization, geovisualization and scientific visualization. Our research concentrates on improving visual user interfaces (VUI) methods and extends existing visual representation techniques. In this paper, we demonstrate the synergy of integrating a wide range of different methods using multiple-linked views with a rich variety of possible coordination exploration ideas and allowing the user to view the information from different perspectives and try out different scenarios. The effectiveness of our proposed framework is demonstrated in a tailor-made case study assembled from GAV components and explores the supply and use of energy data for controlling the emission of carbon dioxide among 290 Swedish municipality regions during 1990-2004.
Articulatory Manner Features Recognition with Linear and Polynomial Kernels

A typical speech recognition system uses acoustic features to represent speech for its processing. Recently, articulatory features were introduced to serve the same purpose. They are motivated by linguistic knowledge and may therefore provide better or complementary representation of speech signal. We present research on recognition of such articulatory features by Support Vector Machines with three types of kernels—a linear kernel and two polynomial kernels. As input for recognizers we use standard set of Mel-frequency cepstral coefficients extended with values of formants and pitch of the speech signal. Performance is compared to recent results for the task based on other methods of machine learning. We conclude that for most of the articulatory features SVMs with a polynomial kernel give superior performance. Razpoznavanje značilk artikulatornega načina z linearnimi in polinomskimi jedri Tipičen sistem razpoznavanja govora uporablja pri procesiranju za predstavitev govora akustične značilke. V zadnjem času so se z istim namenom začele uporabljati tudi artikulatorne značilke. Uporabo leteh je motiviralo jezikoslovno znanje, zato lahko morda omogočajo boljšo ali komplementarno predstavitev govornega signala. V prispevku predstavljamo raziskavo o tem, kako z metodo podpornih vektorjev (MPV) razpoznavamo artikulatorne značilke s tremi vrstami jeder z linearnim jedrom in z dvema polinomskima jedroma. Kot vhodne podatke za razpoznavalnike uporabljamo standardno množico melodičnih frekvennih kepstralnih koeficientov, razširjenih z vrednostmi formantov in osnovnih period govornega signala. Kakovost izvedbe primerjamo z nedavnimi rezultati za isto nalogo na podlagi drugih metod strojnega učenja. Sklenemo z ugotovitvijo, da dajo za večino artikulatornih značilk polinomske MPV najboljše rezultate.
An Exploratory Study of the Perceived Utility and Effectiveness of State

ii Acknowledgements iv List of Tables and Graphs xiii List of Illustrations xiv List of Abbreviations xv Chapter 1: Introduction 1 Identifying Our Weakness 2 Problem Statement 7 The Structure of this Dissertation 10 Chapter 2: Law Enforcement, Terrorism & Intelligence 13 Introduction 13 The Convergence of Crime and Terrorism 14 Shared Characteristics between Crime and Terrorism 16 The Realities of Post-9/11 Policing: Changes and Challenges 21 Changes in State and Local Police Agencies 24 Challenges 30 Conceptual Obstacles 31 Structural Obstacles 33 Organizational Obstacles 34 Cultural Obstacles 36 Technological Obstacles 38 Legal Obstacles 39 Partnership Obstacles 41 What is Intelligence? 42
Evolutionary Dynamics of Small RNAs in 27 Escherichia coli and Shigella Genomes

Small RNAs (sRNAs) are widespread in bacteria and play critical roles in regulating physiological processes. They are best characterized in Escherichia coli K-12 MG1655, where 83 sRNAs constitute nearly 2% of the gene complement. Most sRNAs act by base pairing with a target mRNA, modulating its translation and/or stability; many of these RNAs share only limited complementarity to their mRNA target, and require the chaperone Hfq to facilitate base pairing. Little is known about the evolutionary dynamics of bacterial sRNAs. Here, we apply phylogenetic and network analyses to investigate the evolutionary processes and principles that govern sRNA gene distribution in 27 E. coli and Shigella genomes. We identify core (encoded in all 27 genomes) and variable sRNAs; more than two-thirds of the E. coli K-12 MG1655 sRNAs are core, whereas the others show patterns of presence and absence that are principally due to genetic loss, not duplication or lateral genetic transfer. We present evidence that variable sRNAs are less tightly integrated into cellular genetic regulatory networks than are the core sRNAs, and that Hfq facilitates posttranscriptional cross talk between the E. coli–Shigella core and variable genomes. Finally, we present evidence that more than 80% of genes targeted by Hfq-associated core sRNAs have been transferred within the E. coli–Shigella clade, and that most of these genes have been transferred intact. These results suggest that Hfq and sRNAs help integrate laterally acquired genes into established regulatory networks.
WhatsUp: News, From, For, Through, Everyone

WhatsUp (WUP) is a new form of electronic news. It is personalized and decentralized. Users receive news and have the ability to express their interest in it. This opinion, in turn, is used as an implicit and dynamic subscription scheme to filter and personalize future information. The system is peer-to-peer: no big brother company controls the news, and no central server makes it vulnerable to failures, censorship or attacks. At the heart of WUP lies the idea of collaborative filtering applied to the dissemination of news: people who liked the same news in the past might as well like the same news in the future: irrelevant news disappear by themselves. The idea is put to work through Beep: a biased epidemic dissemination (gossip) protocol that delivers news to interested users in a timely manner, despite jamming and churn. Beep is dynamically parameterized on a per- user, per-news, and per-dissemination-hop basis. When compared to a classical epidemic dissemination protocol, Beep has two key characteristics: orientation and amplification. Every user forwards the news of interest to a randomly selected set of users largely constituted by those who have similar interests (orientation). Moreover, the size of this set of users depends on the level of interest in the news itself (amplification).
AGN and starbursts at high redshift: High resolution EVN radio observations of the Hubble Deep Field

We present deep, wide-field European VLBI Network (EVN) 1.6 GHz observations of the Hubble Deep Field (HDF) region with a resolution of 0.025 arcseconds. Above the 210 μ Jy/beam ($5\sigma$) detection level, the EVN clearly detects two radio sources in a field that encompasses the HDF and part of the Hubble Flanking Fields (HFF). The sources detected are: VLA J123644+621133 (a $z=1.013$, low-luminosity FR-I radio source located within the HDF itself) and VLA J123642+621331 (a dust enshrouded, optically faint, $z=4.424$ starburst system). A third radio source, VLA J123646+621404, is detected at the $4\sigma$ level. The VLBI detections of all three sources suggest that most of the radio emission of these particular sources (including the dusty starburst) is generated by an embedded AGN.