Miracle-dz/UniFAR-FTUs huggingface dataset:
Randomized Consensus in Expected O(n log² n) Operations Per Processor

This paper presents a new randomized algorithm for achieving consensus among asynchronous processors that communicate by reading and writing shared registers. The fastest previously known algorithm requires a processor to perform an expected $O(n^2 \log n)$ read and write operations in the worst case. In our algorithm, each processor executes at most an expected $O(n \log^2 n)$ read and write operations, which is close to the trivial lower bound of $\Omega(n)$. All previously known polynomial-time consensus algorithms were structured around a shared-coin protocol [J. Algorithms, 11 (1990), pp. 441--446] in which each processor repeatedly adds random $\pm 1$ votes to a common pool. Consequently, in all of these protocols, the worst-case expected bound on the number of read and write operations done by a single processor is asymptotically no better than the bound on the total number of read and write operations done by all of the processors together. We succeed in breaking this tradition by allowing the processors to cast votes of increasing weights. This grants the adversary greater control since he can choose from up to $n$ different weights (one for each processor) when determining the weight of the next vote to be cast. We prove that our shared-coin protocol is nevertheless correct using martingale arguments.
Invited Paper Special Section on Analog Circuits and Related Soc Integration Technologies Extremely Low Power Digital and Analog Circuits

SUMMARY Extremely low voltage operation near or below threshold voltage is a key circuit technology to improve the energy efficiency of information systems and to realize ultra-low power sensor nodes. However, it is difficult to operate conventional analog circuits based on amplifier at low voltage. Furthermore, PVT (Process, Voltage and Temperature) variation and random V th variation degrade the minimum operation voltage and the energy efficiency in both digital and analog circuits. In this paper, extremely low power analog circuits based on comparator and switched ca-pacitor as well as extremely low power digital circuits are presented. Many kinds of circuit technologies are applied to cope with the variation problem. Finally, image processing SoC that integrates digital and analog circuits is presented, where improvement of total performance by a cooperation of analog circuits and digital circuits is demonstrated. key words: sub-threshold, near-threshold, energy efficiency, extremely low voltage, extremely low power
The Behavioral Implications of a Multi-Individual Bonebed of a Small Theropod Dinosaur

Background Central Patagonia, Argentina, preserves an abundant and rich fossil record. Among vertebrate fossils from the Upper Cretaceous Bajo Barreal Formation of Patagonia, five individuals of the small, non-avian theropod dinosaur Aniksosaurus darwini were recovered. Group behavior is an important aspect of dinosaur paleoecology, but it is not well-documented and is poorly understood among non-avian Theropoda. Methods/Principal Findings The taphonomic association of individuals from the Bajo Barreal Formation and aspects of their bone histology suggest gregarious behavior for Aniksosaurus, during at least a portion of the life history of this species. Histology indicates that the specimens were juvenile to sub-adult individuals. In addition, morphological differences between individuals, particularly proportions of the appendicular bones, are probably related to body-size dimorphism rather than ontogenetic stage. Conclusions/Significance Gregarious behaviour may have conferred a selective advantage on Aniksosaurus individuals, contributing to their successful exploitation of the Cretaceous paleoenvironment preserved in the Bajo Barreal Formation. The monospecific assemblage of Aniksosaurus specimens constitutes only the second body fossil association of small, coelurosaurian theropods in South America and adds valuable information about the paleoecologies of non-avian theropod dinosaurs, particularly in the early Late Cretaceous of Patagonia.
Fast Approximation of Maximum Flow using Electrical Flows

We look at a variety of topics relating to better understanding the fast approximate maximum flow algorithm presented in ‘Electrical Flow, Laplacian Systems, and Faster Approximation of Maximum Flow in Undirected Graphs’ (Christiano, Kelner, Madry, and Spielman 2010). The algorithm constructs an approximate maximum flow from a series of intermediate electrical flows over an iteratively updated resistor network. We explore the relationship between electrical flows and maximum flow and discuss a number of topics relevant to the goal of proving that the intermediate electrical flows calculated in the algorithm directly converge to a maximum flow (rather than converge as an averaged set). We present a proof that the algorithm can be run without the binary search technique described in the original paper, and discuss how the slightly modified algorithm may help better understand the overall behavior of the technique. Finally, we look at some interesting results that arise when we consider continuous time analogs of the discrete iterative algorithm. We discuss how the maximum flow on a graph can arise as a steady state flow of a related thermistor network and how this phenomena could possibly be used to design future maximum flow algorithms.
A comparative case study of Reserve Deputies in a Florida sheriff’s office and Special Constables in an English police force

Volunteers operating as ‘sworn’ police personnel with full policing powers are a common feature of policing organizations in many countries, including Special Constables in the UK and Reserve and Auxiliary police officers and deputy sheriffs in many law enforcement agencies in the USA. There has been only limited research into the experience of serving as a volunteer in such policing roles in either the US or UK settings, together with very little comparative research into volunteer officer experience across different international settings. This article presents a small-scale, comparative qualitative case study based upon interviews with volunteers from a Reserve Unit in a sheriff’s office in Florida and with volunteer Special Constables from an English police force, exploring their perspectives and experiences of volunteering in their respective policing organizations. The research identifies key differences between the settings in respect of past experience and volunteer pathways, models of training and confidence of operational capability, development and management of roles, the opportunities to develop specialization for volunteers, and leadership. The article points to the value of comparative research in police voluntarism and calls for more research in this area.
A new scattering formulation for broad leaves

Scattering from thin dielectric objects is a classic research topic in electromagnetics. A traditional approach is to model thin dielectrics with resistive sheets, and for several canonical geometries of resistive sheet bodies. However, for many important geometries such as disks, exact solutions are not known and only approximate solutions can be applicable to limited cases of interest. In this paper a new approximate solution is formulated based on a volumetric integral equation using Fourier transform, and it is shown that the solution is uniformly valid from low to high frequencies at all incidence angles including edge-on incidence. Validity of the solution is demonstrated through a series of comparisons with known exact solutions and a numerical solution. Method of Moment, for canonical objects such as an infinite dielectric half-plane, strip, and a circular disk for 2-D and 3-D dielectric scatterers, respectively
OPTIMIZATION OF PARAMETERS TO IMPROVE SVM ACCURACY USING HARMONY SEACRH ALGORITHM

This paper discusses the problem of classification of data by using the Support Vector Machine (SVM) classification method. For classification of datawith SVM required parameters capable of producing optimal performance for a classification model so as to obtain better accuracy. For selection of parameter valuesthat can produce good SVM performance. The proposed algorithm for parameter optimization in this paper is Harmony Search Algorithm (HSA).
Adapting Fuzzy Formal Concept Analysis for Fuzzy Description Logics

Fuzzy Logics have been applied successfully within both For- mal Concept Analysis and Description Logics. Especially in the latter field, Fuzzy Logics have been gaining significant momentum during the last two years. Unfortunately, the research on fuzzy logics within the two communities has been conducted independently from each other, lead- ing to dierent approaches being pursued. We show that if we look at a restricted variant of fuzzy formal concept analysis, then the dierences between the two approaches can be reconciled. Moreover, an implica- tional base can be computed even when the identity hedge is used.
Automatic segmentation of clinical structures for RTP: Evaluation of a morphological approach

This paper describes a morphological segmentation technique developed to assist clinicians and radiologists in conformal RTP. The system uses a watershed transformation to give an initial over-segmentation of a 2D CT; this is then refined by homotopy modification with markers identified automatically from the image histogram and the final segmentation is represented by a region adjacency graph which may be interactively edited by the user. To evaluate the system, 77 CT images from 11 patients have been segmented and the results compared against those produced by 5 clinical experts. The approach has enabled the quality of the automatic segmentation to be assessed in terms of the overall expert intra/inter variability. It has been proved good agreement between computer generated and expert manual delineations.
Comparing brain-computer interaction and eye tracking as input modalities: An exploratory study

Brain computer interfaces have become one of the growing areas for human computer interaction research. Various research studies were conducted to control graphical user interfaces using brain computer interface methods. Furthermore, eye tracking was another input modality that has been examined for controlling interactive systems. In this paper we investigate object selection using P300 brain signals and eye tracking across consistently design graphical user interface. We conducted several experiments on each approach on able-bodied subjects. The aim of these experiments was to evaluate and compare the accuracy and time to complete the task for both approaches. Experimental results indicated that the accuracy of eye tracking as an input modality was 92.5% on average, with 80% of participants reaching 100% accuracy. In contrast, P300 was found to produce low accuracy and efficiency results compared to eye tracking with average accuracy 32% among 20 participants.
Procedural Control in ATC Selection Tests to Predict Situational Awareness

At LVNL we have developed a new selection system, called DATCOSS, which should contribute to a higher output of qualified controllers from training. Two job sample tests are part of this selection system, specifically designed to measure the candidate’s potential for Situational Awareness by using simplified procedural control tasks. Grading takes half a day while AAPRO is a selective training module of five weeks. We examined the psychometric quality of both tests and the predictive validity of Grading for AAPRO. We may conclude that SA is sufficiently measured in the two job samples and that Grading results are rather predictive for performance in AAPRO. We made a start with analyzing predictive validity in relation to training success; this will be further examined in the near future
Advances in voxel-based 6-DOF haptic rendering

An approach is presented for realizing an order-of-magnitude improvement in spatial accuracy for voxel-based 6-DOF haptics. It trades constant-time performance for greater spatial accuracy. This helps to make 6-DOF haptics applicable to extraordinarily complex real-world task simulations, which often admit no other known solution short of physical mockup. A reduction of haptic fidelity is tactically incurred but simultaneously mitigated by augmenting standard voxel-sampling methodology with distance fields, temporal coherence, and culling of redundant polyhedral surface interactions. This is applied to large-scale haptic scenarios involving multiple moving objects and to collaborative virtual environments.
Probabilistic graph formalisms for meaning representations

In recent years, many datasets have become available that represent natural language semantics as graphs. To use these datasets in natural language processing (NLP), we require probabilistic models of graphs. Finite-state models have been very successful for NLP tasks on strings and trees because they are probabilistic and composable. Are there equivalent models for graphs? In this thesis, we survey several graph formalisms, focusing on whether they are probabilistic and composable, and we contribute several new results. In particular, we study the directed acyclic graph automata languages (DAGAL), the monadic second-order graph languages (MSOGL), and the hyperedge replacement languages (HRL). We prove that DAGAL cannot be made probabilistic, we explain why MSOGL also most likely cannot be made probabilistic, and we review the fact that HRL are not composable. We then review a subfamily of HRL and MSOGL: the regular graph languages (RGL; Courcelle 1991), which have not been widely studied, and particularly have not been studied in an NLP context. Although Courcelle (1991) only sketches a proof, we present a full, more NLP-accessible proof that RGL are a subfamily of MSOGL. We prove that RGL are probabilistic and composable, and we provide a novel Earley-style parsing algorithm for them that runs in time linear in the size of the input graph. We compare RGL to two other new formalisms: the restricted DAG languages (RDL; Björklund et al. 2016) and the tree-like languages (TLL; Matheja et al. 2015). We show that RGL and RDL are incomparable; TLL and RDL are incomparable; and either RGL are incomparable to TLL, or RGL are contained within TLL. This thesis provides a clearer picture of this field from an NLP perspective, and suggests new theoretical and empirical research directions.
Temporal texture modeling

Temporal textures are textures with motion. Examples include wavy water, rising steam and fire. We model image sequences of temporal textures using the spatio-temporal autoregressive model (STAR). This model expresses each pixel as a linear combination of surrounding pixels lagged both in space and in time. The model provides a base for both recognition and synthesis. We show how the least squares method can accurately estimate model parameters for large, causal neighborhoods with more than 1000 parameters. Synthesis results show that the model can adequately capture the spatial and temporal characteristics of many temporal textures. A 95% recognition rate is achieved for a 135 element database with 15 texture classes.
Bandpass sigma-delta analog-to-digital conversion

The traditional low-pass sigma-delta ( Sigma Delta ) analog-to-digital converter is extended to the bandpass case. For input signals with small relative bandwidths, bandpass Sigma Delta converters offer high signal-to-noise ratios at significantly lower sampling rates than are required for low-pass Sigma Delta converters. A sixth-order single-ended switched-capacitor circuit, clocked at 3 MHz, is designed to convert bandpass signals centered at 455 kHz with 20-kHz bandwidth. Time-domain circuit simulations show that this modulator realizes a 94-dB signal-to-noise ratio for a half-scale input, giving roughly 16-b performance. >
Bare-metal performance for virtual machines with exitless interrupts

Direct device assignment enhances the performance of guest virtual machines by allowing them to communicate with I/O devices without host involvement. But even with device assignment, guests are still unable to approach bare-metal performance, because the host intercepts all interrupts, including those generated by assigned devices to signal to guests the completion of their I/O requests. The host involvement induces multiple unwarranted guest/host context switches, which significantly hamper the performance of I/O intensive workloads. To solve this problem, we pres-ent ExitLess Interrupts (ELI), a software-only approach for handling interrupts within guest virtual machines directly and securely . By removing the host from the interrupt handling path, ELI improves the throughput and latency of unmodified, untrusted guests by 1.3×–1.6×, allowing them to reach 97–100% of bare-metal performance even for the most demanding I/O-intensive workloads.
Beltrami Representation and its applications to texture map and video compression

Surface parameterizations and registrations are important in computer graphics and imaging, where 1-1 correspondences between meshes are computed. In practice, surface maps are usually represented and stored as 3D coordinates each vertex is mapped to, which often requires lots of storage memory. This causes inconvenience in data transmission and data storage. To tackle this problem, we propose an effective algorithm for compressing surface homeomorphisms using Fourier approximation of the Beltrami representation. The Beltrami representation is a complex-valued function defined on triangular faces of the surface mesh with supreme norm strictly less than 1. Under suitable normalization, there is a 1-1 correspondence between the set of surface homeomorphisms and the set of Beltrami representations. Hence, every bijective surface map is associated with a unique Beltrami representation. Conversely, given a Beltrami representation, the corresponding bijective surface map can be exactly reconstructed using the Linear Beltrami Solver introduced in this paper. Using the Beltrami representation, the surface homeomorphism can be easily compressed by Fourier approximation, without distorting the bijectivity of the map. The storage memory can be effectively reduced, which is useful for many practical problems in computer graphics and imaging. In this paper, we proposed to apply the algorithm to texture map compression and video compression. With our proposed algorithm, the storage requirement for the texture properties of a textured surface can be significantly reduced. Our algorithm can further be applied to compressing motion vector fields for video compression, which effectively improve the compression ratio.
Faster SAT-Based Analysis of OO-Programs by Separation of Mutant and Non Mutant Objects

In this article we present an optimization to the analysis of DynAlloy programs based on the distinction between mutant objects (those whose state is modified by the program) and non mutant objects. This allows us to consider smaller scopes and therefore to reduce the analysis time. The theoretical observation that the technique reduces the state space exponentially is supported by examples where a striking analysis time reduction can be observed.
Methods for Constructing Lexicon-Grammar Resources: The Example of Measure Expressions

We construct, in the framework of the lexicon-grammar theory, a set of grammars dealing with measure expressions. First, we manually represent compounds with graphs: determiners such as ten pounds of and prepositions such as 34 miles from. Then, by the means of lexicon-grammar matrices, graphs and a semi-automatic process, we build a set of grammars of kernel sentences e.g. the door is 2-meter high. Finally, we evaluate our methods and grammars according to three points: production, maintenance and concrete application.
Characterization of ISP Traffic: Trends, User Habits, and Access Technology Impact

In the recent years, the research community has increased its focus on network monitoring which is seen as a key tool to understand the Internet and the Internet users. Several studies have presented a deep characterization of a particular application, or a particular network, considering the point of view of either the ISP, or the Internet user. In this paper, we take a different perspective. We focus on three European countries where we have been collecting traffic for more than a year and a half through 5 vantage points with different access technologies. This humongous amount of information allows us not only to provide precise, multiple, and quantitative measurements of "What the user do with the Internet" in each country but also to identify common/uncommon patterns and habits across different countries and nations. Considering different time scales, we start presenting the trend of application popularity; then we focus our attention to a one-month long period, and further drill into a typical daily characterization of users activity. Results depict an evolving scenario due to the consolidation of new services as Video Streaming and File Hosting and to the adoption of new P2P technologies. Despite the heterogeneity of the users, some common tendencies emerge that can be leveraged by the ISPs to improve their service.
Sparkwave: continuous schema-enhanced pattern matching over RDF data streams

Data streams, often seen as sources of events, have appeared on the Web. Stream processing on the Web needs however to cope with the typical openness and heterogeneity of the Web environment. Semantic Web technologies, meant to facilitate data integration in an open environment, can help to address heterogeneities across multiple streams. In this paper we present Sparkwave, an approach for continuous pattern matching over RDF data streams. Sparkwave is based on the Rete algorithm, which allows efficient and truly continuous processing of data streams. Sparkwave is able to leverage RDF schema information associated to data streams to compute entailments, so that implicit knowledge is taken into account for pattern matching. In addition, it further extends Rete to support time-based sliding windows and static data instances, to cope with the streaming nature of processed data and real-world use cases.
Dynamic investment strategies of hedge funds s

In this paper we study the investment dynamics employed by hedge fund managers. Using daily data for nine investable hedge fund strategies, we use a rolling-over regression technique, which allows us to capture the time-variability present in the different strategies of hedge fund managers. The results indicate that the inclusion of time-variability is important as the risk exposures change significantly over time. Our results show no evidence of traditional alpha out-performance within a multifactor framework. Given this inability to generate consistent alpha returns, we also analyze the performance data relative to the factor specific beta risk. To this end, we replicate static hedge fund returns and compare them to the actual hedge fund returns. We conclude that most hedge fund returns beat the replicated static trading strategy. This suggests that particular hedge funds add alpha return through the skill of timing alternative beta risk.
Image Matching for Workpiece Based on Genetic Algorithm

Traditional image matching algorithms are always global search method, but they are time-consuming. In order to meet the real-time requirements of recognition system based on matching edge of the workpiece, a new image matching algorithm which combines improved adaptive genetic algorithm based on information of population generation and improved Hausdorff distance algorithm is proposed here. The use of genetic algorithm search mechanism of the non-ergodicity makes it rapidly converge to the global optimal solution and increases the speed to searching for matching. The experimental results show that the algorithm not only speeds up the matching process, improves the anti-noise performance, but also effectively solves the problem of image matching and recognition in the case of translation, rotation and partial occlusion.