Miracle-dz/UniFAR-FTUs huggingface dataset:
A Simple k NN Search Protocol using Data Broadcasting in Wireless Mobile Environments

Data broadcasting is an effective way to disseminate information to a large amount of mobile clients in wireless mobile environments. Many information services can use such a technique to serve the clients, including location-based service. The k nearest neighbor (kNN) search is one of the important locationbased services. With such a search, the clients can get the points of interests around them. In this paper, we propose a kNN search protocol using data broadcasting. We consider how the server generates the broadcast schedule and how the client can efficiently execute the query process in terms of latency (time interval from issuing and terminating a query) and tuning time (time spent on listening to the broadcast). Without using an index in the broadcast, the proposed protocol uses some addition information for each broadcast data instead in order to save the tuning time and latency. The effectiveness of the proposed protocol will be verified by proofs.
Coordination Issues in an Agent-Based Approach for Territorial Emergence Management

This paper presents a new architectural approach for managing healthcare emergences and large scale disasters using agent-based applications. Such scenarios require a support that must be distributed, context-aware, reactive and autonomous. In the following, we will show how agent’s behaviour best fits to these requirements and how the agent technology can be efficiently applied to problems where the main challenge is coordination and collaboration between components. We propose a FIPA compliant Multi-Agent System based on the BDI and PIM technologies.
OPTIMIZING THE FINAL COST IN

The sizing of pipelines in distribution networks is a well known problem in industrial engineering. This is a diicult problem due, mainly, to the complex calculi required and the presence of some restrictions throughout the network. In this paper we approach the problem considering soft restrictions, instead of hard restrictions, with a view to obtaining more economic solutions when these restrictions are slightly violated.
Enhanced Figure-Ground Classification With Background Prior Propagation

We present an adaptive figure-ground segmentation algorithm that is capable of extracting foreground objects in a generic environment. Starting from an interactively assigned background mask, an initial background prior is defined and multiple soft-label partitions are generated from different foreground priors by progressive patch merging. These partitions are fused to produce a foreground probability map. The probability map is then binarized via threshold sweeping to create multiple hard-label candidates. A set of segmentation hypotheses is formed using different evaluation scores. From this set, the hypothesis with maximal local stability is propagated as the new background prior, and the segmentation process is repeated until convergence. Similarity voting is used to select a winner set, and the corresponding hypotheses are fused to yield the final segmentation result. Experiments indicate that our method performs at or above the current state-of-the-art on several data sets, with particular success on challenging scenes that contain irregular or multiple-connected foregrounds.
Meeting the Demands of the Digital Home with High-Speed Multi-Hop Wireless Networks

In the near future, homes will be equipped with wireless networks that bridge data and consumer electronics networks, interconnecting desktop PCs, mobile laptops and handhelds, High-Definition TVs (HDTVs), DVD players, camcorders, and other multimedia devices. This environment introduces new wireless network requirements, including high and dependable bandwidth, low latency, and coverage throughout the home. Multihop wireless technology offers unique benefits for creating a high-speed, robust home wireless network. However, to support these demanding usage models, significant wireless networking innovations are required across the physical, MAC, and routing layers, and solutions need to be found for higher level issues such as Quality of Service (QoS) guarantees, device discovery, and security. In addition, user acceptance of multi-hop wireless networks will require ease of installation. Intel R&D is currently researching self-organizing multi-hop wireless networks for home environments. This paper introduces the technologies and tradeoffs needed to create a multi-hop wireless home network, identifying benefits and limitations. In particular, we describe usage scenarios and assumptions that drive the requirements. Finally, we provide an outline of the key technology problems that must be solved and recommend the necessary next steps to make this vision a reality.
NONCOMMUTATIVE HYPERGEOMETRIC AND BASIC HYPERGEOMETRIC EQUATIONS

Recently, J. A. Tirao [Proc. Nat. Acad. Sci. 100(14) (2003) 8138–8141] considered a matrix-valued analogue of the 2F1 Gauß hypergeometric function and showed that it is the unique solution of a matrix-valued hypergeometric equation analytic at z = 0 with value I, the identity matrix, at z = 0. We give an independent proof of Tirao's result, extended to the more general setting of hypergeometric functions over an abstract unital Banach algebra. We provide a similar (but more complicated-looking) result for a second type of noncommutative 2F1 Gauß hypergeometric function. We further give q-analogues for both types of noncommutative hypergeometric equations.
Intrinsic Absorption in the Spectrum of Markarian 279: Simultaneous Chandra, FUSE, and STIS Observations

We present a study of the intrinsic X-ray and far-ultraviolet absorption in the Seyfert 1.5 galaxy Markarian 279 using simultaneous observations from the Chandra X-ray Observatory, the Space Telescope Imaging Spectrograph aboard the Hubble Space Telescope, and the Far Ultraviolet Spectroscopic Explorer (FUSE). We also present FUSE observations made at three additional epochs. We detect the Fe Kα emission line in the Chandra spectrum, and its flux is consistent with the low X-ray continuum flux level of Mrk 279 at the time of the observation. Because of low signal-to-noise ratios (S/N) in the Chandra spectrum, no O VII or O VIII absorption features are observable in the Chandra data, but the UV spectra reveal strong and complex absorption from H I and high-ionization species such as O VI, N V, and C IV, as well as from low-ionization species such as C III, N III, C II, and N II in some velocity components. The far-UV spectral coverage of the FUSE data provides information on high-order Lyman series absorption, which we use to calculate the optical depths and line and continuum covering fractions in the intrinsic H I absorbing gas in a self-consistent fashion. The UV continuum flux of Mrk 279 decreases by a factor of ∼7.5 over the time spanning these observations and we discuss the implications of the response of the absorption features to this change. From arguments based on the velocities, profile shapes, covering fractions and variability of the UV absorption, we conclude that some of the absorption components, particularly those showing prominent low-ionization lines, are likely associated with the host galaxy of Mrk 279, and possibly with its interaction with a close companion galaxy, while the remainder arises in a nuclear outflow.
Power Control and Network Design in Mobile Sensor Networks

We consider the problem of designing a wireless mobile sensor network to collect information from demands whose time of arrival and locations are stochastic. We study a simple scheme that partitions the target area into subregions monitored by a mobile node, which then communicates the data collected from its region via multihop wireless communication to a single base station. We find the unique joint power control and area partitioning strategy that maximizes the lifetime of the wireless mobile sensor network. We explicitly characterize this strategy and propose an efficient algorithm to find it. Finally, we study the sensitivity of the optimal strategy on the parameters of the problem via simulations.
TIRA: Configuring, Executing, and Disseminating Information Retrieval Experiments

With its close ties to the Web, the information retrieval community is destined to leverage the dissemination and collaboration capabilities that the Web provides today. Especially with the advent of the software as a service principle, an information retrieval community is conceivable that publishes executable experiments by anyone over the Web. A review of recent SIGIR papers shows that we are far away from this vision of collaboration. The benefits of publishing information retrieval experiments as a service are striking for the community as a whole, including potential to boost research profiles and reputation. However, the additional work must be kept to a minimum and sensitive data must be kept private for this paradigm to become an accepted practice. In order to foster experiments as a service in information retrieval, we present the TIRA (Testbed for Information Retrieval Algorithms) web framework that addresses the outlined challenges and possesses a unique set of compelling features in comparison to existing web-based solutions. To describe TIRA in a practical setting, we explain how it is currently used as an official evaluation platform for the well-established PAN international plagiarism detection competition. We also describe how it can be used in future scenarios for search result clustering of non-static collections of web query results, as well as within a simulation data mining setting to support interactive structural design in civil engineering.
Diagnostic Accuracy and Applicability of a PCR System for the Detection of Schistosoma mansoni DNA in Human Urine Samples from an Endemic Area

Schistosomiasis caused by Schistosoma mansoni, one of the most neglected human parasitoses in Latin America and Africa, is routinely confirmed by microscopic visualization of eggs in stool. The main limitation of this diagnostic approach is its lack of sensitivity in detecting individual low worm burdens and consequently data on infection rates in low transmission settings are little reliable. According to the scientific literature, PCR assays are characterized by high sensitivity and specificity in detecting parasite DNA in biological samples. A simple and cost effective extraction method for DNA of Schistosoma mansoni from urine samples in combination with a conventional PCR assay was developed and applied in an endemic area. This urine based PCR system was tested for diagnostic accuracy among a population of a small village in an endemic area, comparing it to a reference test composed of three different parasitological techniques. The diagnostic parameters revealed a sensitivity of 100%, a specificity of 91.20%, positive and negative predictive values of 86.25% and 100%, respectively, and a test accuracy of 94.33%. Further statistical analysis showed a k index of 0.8806, indicating an excellent agreement between the reference test and the PCR system. Data obtained from the mouse model indicate the infection can be detected one week after cercariae penetration, opening a new perspective for early detection and patient management during this stage of the disease. The data indicate that this innovative PCR system provides a simple to handle and robust diagnostic tool for the detection of S. mansoni DNA from urine samples and a promising approach to overcome the diagnostic obstacles in low transmission settings. Furthermore the principals of this molecular technique, based on the examination of human urine samples may be useful for the diagnosis of other neglected tropical diseases that can be detected by trans-renal DNA.
4 The Adele Conﬁguration Manager

This article proposes an overview of the Adele system and also discusses other approaches and other systems. While most of our work on Configuration Management is covered, we have deliberately chosen to discuss in greater depth the Work Space aspect and the relationship between the Repository Space and the WSs. A Software Conﬁguration Management (SCM) system results from harmonious collaboration between a Repository Space (RS) and Work Spaces (WSs). The WS controls the dynamic aspect of SCM, i.e., the place where activities are performed; the RS is the place wherein software objects are modelled, stored and manipulated. It is argued here that an SCM system must satisfy conﬂicting requirements. These are the need for a powerful and dedicated OMS with high modelling power (and thus complexity), and the need for ﬁles and directories which are simple concepts, but with low modelling power. We show how different systems have met these requirements. This article shows how different aspects of the Adele system contribute to meeting these requirements and how this provides a highly customizable and extensible system with services for complex data management, tool integration, inter-tool cooperation, process support and conﬁguration management.
Wait-Free Algorithms for Heaps

This paper examines algorithms to implement heaps on shared memory multiprocessors. A natural model for these machines is an asynchronous parallel machine, in which the processors are subject to arbitrary delays. On such machines, it is desirable for algorithms to be wait-free, meaning that each thread makes progress independent of the other threads executing on the machine. We present a waitfree algorithm to implement heaps. The algorithms are similar to the general approach given in [4], with optimizations that allow many threads to work on the heap simultaneously, while still guaranteeing a strong serializability property.
Overtaking & receding vehicle detection for driver assistance and naturalistic driving studies

Although on-road vehicle detection is a well-researched area, overtaking and receding vehicle detection with respect to (w.r.t) the ego-vehicle is less addressed. In this paper, we present a novel appearance-based method for detecting both overtaking and receding vehicles w.r. t the ego-vehicle. The proposed method is based on Haar-like features that are classified using Adaboost-cascaded classifiers, which result in detection windows that are tracked in two directions temporally to detect overtaking and receding vehicles. A detailed and novel evaluation method is presented with 51 overtaking and receding events occurring in 27000 video frames. Additionally, an analysis of the detected events is presented, specifically for naturalistic driving studies (NDS) to characterize the overtaking and receding events during a drive. To the best knowledge a of the authors, this automated analysis of overtaking/receding events for NDS is a first of its kind in literature.
Program Development for Extreme-Scale Computing Dagstuhl Seminar

From May 2 to May 7, 2010, the Dagstuhl Seminar 10181 Program Development for Extreme-Scale Computing was held in Schloss Dagstuhl Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. Links to extended abstracts or full papers are provided, if available.
Robust NLS sensor localization using MDS initialization

Before a sensor network can be used for target localization, the locations of the sensors need to be determined. We approach this calibration step by moving a source to distinct positions around the network. At each position, the range to each sensor is measured, and from these range measurements the sensor locations can be estimated by solving a nonlinear least squares (NLS) problem. Here we formulate the NLS problem and describe how to robustly initialize it by the use of multidimensional scaling. The method is evaluated on both simulations and real data from an acoustic sensor network. With as few as six source positions, a robust calibration is demonstrated that gives a position error about the same size as the range error. In the acoustic example this RMSE is less than 40 cm.
A semi-parametric multiple imputation data augmentation procedure

Multiple imputation procedures (MI) are a useful tool to adjust for item non-response but are often based on fully parametric assumptions, such as multivariate normality. For many applications such assumptions may not hold in practice, for example if the data are skewed and affected by rounding and truncation effects. Hot deck imputation methods, however, make less or no assumptions about underlying distributions and may be more appropriate to use in such circumstances. The basic idea is to combine multiple imputation and hot deck approaches with the aim of preserving advantageous properties of MI and at the same time relaxing distributional assumptions. This paper develops a semi-parametric data augmentation method to generate MI under the missing at random assumption and a nonignorable missing data mechanism. The use of predictive mean matching as a form of hot deck imputation is considered as part of the data augmentation procedure to improve the robustness of the multiple imputation method.
Towards Deep Developmental Learning

Deep learning techniques are having an undeniable impact on general pattern recognition issues. In this paper, from a developmental robotics perspective, we scrutinize deep learning techniques under the light of their capability to construct a hierarchy of meaningful multimodal representations from the raw sensors of robots. These investigations reveal the differences between the methodological constraints of pattern recognition and those of developmental robotics. In particular, we outline the necessity to rely on unsupervised rather than supervised learning methods and we highlight the need for progress towards the implementation of hierarchical predictive processing capabilities. Based on these new tools, we outline the emergence of a new domain that we call deep developmental learning.
Novel materials and fabrication technologies for SIW components for the Internet of Things

This paper presents an overview of the recent achievements in the development of novel microwave components and antennas for the future Internet of Things (IoT), based on the use of innovative materials and manufacturing technologies. In particular, the development of substrate integrated waveguide (SIW) structures is discussed, based on the use of paper substrates for eco-friendly wireless systems, textile materials for wearable applications, and 3D-printed substrates for the implementation of fully-3D and cost-effective components. A number of prototypes, based on the different materials, are reported and discussed, to show the variety of structures and potentials of integrated microwave systems in future wireless devices for IoT applications.
Comparison of State-Machine and Deferred-Update Replication

Distributed replication can improve service or database availability and reliability by moving data closer to users and by processing many requests (or transactions) in parallel on different machines which can crash independently. In the paper, we analytically and experimentally compare two popular transactional replication schemes relying on atomic broadcast: state machine replication (SMR) and deferred update replication (DUR). In the best/worst case analysis, we calculate lower/upper bounds on the running time of SMR and DUR algorithms, considering a parallel architecture with multi-core processors and various optimizations, such as processing of read-only requests differently. In the worst case analysis of DUR, we consider conflict patterns. We then analyze the scalability of SMR and DUR systems. It reflects the capacity of SMR and DUR systems to effectively utilize an increasing number of processing cores. Next, we compare SMR and DUR experimentally under different levels of contention, using several benchmarks. We show throughput and abort rate (in DUR) with the increasing number of processor cores. The key result of our work is that neither system is superior in all cases. We therefore propose to combine both replication schemes and gain the best of both worlds. Index Terms—state machine replication; deferred update replication; distributed transactional memory !
On-Mote Compressive Sampling in Wireless Seismic Sensor Networks

Implementing a wireless sensor network capable of near real-time, continuous (e.g., 500 Hz sampling rate), geophysical sensing requires a better approach than a simplistic sense, store, send methodology. Transmitting all sensor data is very power intensive, as the radio consumes much more power than other wireless mote components (e.g., CPU, ADC) [1]. To address the need for a lightweight data reduction algorithm, we investigate the viability of on-mote compressive sampling (CS), both in simulation on seismic data and in real hardware.
It ’ s the context stupid : Considering technical , social and organizational contexts in the design systems to support teacher learning

This paper presents the results of a field trial of the Living Curriculum (an on-line professional development resource for teachers) examining use, utility and usability. Results show limited use of the system, but high utility for the teachers that did use it. Usability results suggest some design improvements but by and large show that teachers were readily able to use the system. Limited use is attributed to a failure to account for the context of use. Future research in this area should attend realistically to the constraints of the school environment both in terms of the technical and social infrastructure.
The Horticultural Trade and Ornamental Plant Invasions in Britain

Abstract: Ornamental horticulture has been recognized as the main pathway for plant invasions worldwide. We examined the link between propagule pressure created by the presence of ornamental plants in the market and their ability to escape from cultivation and establish in the wild. A random sample of 534 non‐native ornamental species on sale in nineteenth century Britain showed that 27% of these species were recorded growing outside cultivation and 30% of those were established. Species that had escaped from cultivation were more frequently on sale both in the nineteenth century and today than nonescaping species. We used logit regression models to identify biological and socioeconomic variables that affect species' abilities to escape cultivation and become established. Frequencies in the market in the nineteenth century and today were good explanatory variables that distinguished escaping from nonescaping species, whereas for the transition from casual to established status these two socioeconomic variables were either absent or only of weak significance. Biological characteristics that increased the probability that a species would escape from cultivation were species height, a European native range, and being an annual. Climbing plants and species intolerant of low temperatures were less likely to escape. In contrast, the establishment probability was greater if the species belonged to a genus native to Britain and increased as the number of continents in a plant's native range increased. Annual plants had a reduced probability of establishment. Market presence, prices, and the date of introduction are among the socioeconomic factors that have had important effects on the observed course of invasions.
Commutativity up to a factor of bounded operators in complex Hilbert space

We explore commutativity up to a factor, AB = λBA, for bounded operators in a complex Hilbert space. Conditions on the possible values of the factor λ are formulated and shown to depend on spectral properties of the operators involved. Commutativity up to a unitary factor is considered for pairs of self–adjoint operators. Examples of non–trivial realizations of such commutation relations are given.