Miracle-dz/UniFAR-FTUs huggingface dataset:
Fault-tolerant cluster-wise clock synchronization for wireless sensor networks

Wireless sensor networks have received a lot of attention recently due to their wide applications, such as target tracking, environment monitoring, and scientific exploration in dangerous environments. It is usually necessary to have a cluster of sensor nodes share a common view of a local clock time, so that all these nodes can coordinate in some important applications, such as time slotted MAC protocols, power-saving protocols with sleep/listen modes, etc. However, all the clock synchronization techniques proposed for sensor networks assume benign environments; they cannot survive malicious attacks in hostile environments. Fault-tolerant clock synchronization techniques are potential candidates to address this problem. However, existing approaches are all resource consuming and suffer from message collisions in most of cases. This paper presents a novel fault-tolerant clock synchronization scheme for clusters of nodes in sensor networks, where the nodes in each cluster can communicate through broadcast. The proposed scheme guarantees an upper bound of clock difference between any nonfaulty nodes in a cluster, provided that the malicious nodes are no more than one third of the cluster. Unlike the traditional fault-tolerant clock synchronization approaches, the proposed technique does not introduce collisions between synchronization messages, nor does it require costly digital signatures.
Visualizing Time-Varying Topics Via Images and Texts for Inter-Media Analysis

This paper proposes a system for analyzing societal behaviors by visualizing time-varying topics in multiple media. Various types of content such as text, images, and videos have spread throughout multiple media, such as TV and the Web, that have complementary information and influence one another. It is important to compare how these media react to real world events to understand recent societal behaviors and how each medium reacts to other media. Our system visualizes flows of content in multiple media in 3D space enabling us to simultaneously explore them. We present two example applications using our system. The first involves the visualization of inter-media events comparing the exposure of topics in TV news and the activities of bloggers. The second example application is a system for visualizing visual trends on social media that chronologically displays extracted clusters of images on blogs. The proposed systems enable users to visually monitor changes in thought, activities, and interests of people, and differences between media through interactively exploring flows of texts and images extracted from the media.
Adding Virtual Machine Abstractions Into SimGrid: A First Step Toward the Simulation of Infrastructure-as-a-Service Concerns

As real systems become larger and more complex, the use of simulator frameworks grows in our research community. By leveraging them, users can focus on the major aspects of their algorithm, run in-siclo experiments (i.e., simulations), and thoroughly analyze results, even for a large-scale environment without facing the complexity of conducting in-vivo studies (i.e., on real test beds). Since nowadays the virtual machine (VM) technology has become a fundamental building block of distributed computing environments, in particular in cloud infrastructures, our community needs a full-fledged simulation framework that enables us to investigate large-scale virtualized environments through accurate simulations. To be adopted, such a framework should provides easy-to-use APIs, close to the real ones and preferably fully compatible with those of an existing popular simulation framework. In this paper, we present the current implementation status of a highly-scalable and versatile simulation framework supporting VM environments, extending a widely-used, open-source framework, SimGrid. Our simulation framework allows users to launch hundreds of thousands of VMs on their simulation programs and control VMs in the same manner as in the real world (e.g., suspend/resume and migrate). Users can execute computation and communication tasks on physical machines (PMs) and VMs through the same SimGrid API, which will provide a seamless migration path to IaaS simulations for thousands of SimGrid users. Preliminary validations showed that the resource sharing mechanism of the VM support worked correctly.
Illegitimacy and illegitimates in English history

'The bastard, like the prostitute, thief and beggar, belongs to that motley crowd of disreputable social types which society has generally resented, always endured. He is a living symbol of social irregularity. '(1) Thus commences one of the classic sociological analyses of the types of illegitimacy, and it immediately poses three problems for the anthropologist and the historian concerned with this topic in Britain. What was the rate of illegitimacy in our country before civil registration began? What was the attitude to those who bore and begat bastards? What was the attitude to the bastards themselves?
Crypto Topics and Applications I

In this chapter we continue the exposition of crypto topics that was begun in the previous chapter. This chapter covers secret sharing, threshold cryptography, signature schemes, and finally quantum key distribution and quantum cryptography. As in the previous chapter, we have focused only on the essentials of each topic. We have selected in the bibliography a list of representative items, which can be consulted for further details. First we give a synopsis of the topics that are discussed in this chapter. Secret sharing is concerned with the problem of how to distribute a secret among a group of participating individuals, or entities, so that only predesignated collections of individuals are able to recreate the secret by collectively combining the parts of the secret that were allocated to them. There are numerous applications of secret-sharing schemes in practice. One example of secret sharing occurs in banking. For instance, the combination to a vault may be distributed in such a way that only specified collections of employees can open the vault by pooling their portions of the combination. In this way the authority to initiate an action, e.g., the opening of a bank vault, is divided for the purposes of providing security and for added functionality, such as auditing, if required. Threshold cryptography is a relatively recently studied area of cryptography. It deals with situations where the authority to initiate or perform cryptographic operations is distributed among a group of individuals. Many of the standard operations of single-user cryptography have counterparts in threshold cryptography. Signature schemes deal with the problem of generating and verifying electronic) signatures for documents.Asubclass of signature schemes is concerned with the shared-generation and the sharedverification of signatures, where a collaborating group of individuals are required to perform these actions. A new paradigm of security has recently been introduced into cryptography with the emergence of the ideas of quantum key distribution and quantum cryptography. While classical cryptography employs various mathematical techniques to restrict eavesdroppers from learning the contents of encrypted messages, in quantum cryptography the information is protected by the laws of physics.
ON COMPLETE TOPOLOGICAL SUBGRAPHS OF CERTAIN GRAPHS

Let G he a graph . We say that G contains a complete k-gon if there are ! c vertices of G any two of which are connected by an edge, we say that it contains a complete topological k-gon if it contains k vertices any two of which are connected by paths no two of which have a common vertex (except endpoints) . Following G . DIRAC we will denote complete k-gons by -k = and complete topological k-gons by G(k, 1) denotes a graph of k vertices and 1 edges
Threshold resummation for high-transverse-momentum Higgs production at the LHC

We study the resummation of large logarithmic QCD corrections for the process pp ? H + X when the Higgs boson H is produced at high transverse momentum. The corrections arise near the threshold for partonic reaction and originate from soft gluon emission. We perform the all-order resummation at next-to-leading logarithmic accuracy and match the resummed result with the next-to-leading order perturbative predictions. The effect of resummation on the Higgs transverse momentum distribution at the LHC is discussed.
DBSCAN data clustering algorithm for video stabilizing system

This paper proposed a method based on DBSCAN data clustering algorithm to stabilize the jitter of digital video with moving objects in it. In order to distinguish the corners on moving objects with those on background, after extracting the corners of each frame, DBSCAN algorithm was used to cluster all the corners by clustering their motion vectors' lengths and directions. Then we compared the dispersion of each cluster to confirm whether the corners in each cluster were belonged to moving objects or background. Simulation experimental results showed that the proposed method had good stabilization effects to stabilize jitter in video sequence with moving objects in it.
Laplacian Mixture Modeling for Overcomplete Mixture Matrix Estimation in Wavelet Packet Domain by Adaptive EM-type Algorithm

Speech process has benefited a great deal from the wavelet transforms. Wavelet packets decompose signals in to broader components using linear spectral bisecting. In this paper, mixtures of speech signals are decomposed using wavelet packets, the phase difference between the two mixtures are investigated in wavelet domain. In our method Laplacian mixture model (LMM) is defined. An expectation maximization (EM) algorithm is used for training of the model and calculation of model parameters which is the mixture matrix. Therefore individual speech components of speech mixtures are separated
Density of newly synthesized plasma membrane proteins in intracellular membranes. I. Stereological studies

As the spike proteins of Semliki Forest virus (SFV) pass from their site of synthesis in the endoplasmic reticulum (ER) to the cell surface, they must be concentrated and freed from endogenous proteins. To determine the magnitude of this sorting process we have measured the density of spike proteins in membranes of the intracellular transport pathway. In this first paper, using stereological procedures, we have estimated the surface areas of the ER, Golgi complex, and plasma membrane of infected and mock-infected baby hamster kidney cells. First, we estimated the mean cell volume in absolute units. This was done using a novel in situ method which is described in detail. Infection by SFV was found to have no effect on any of the parameters measured. In the accompanying paper ( Quinn , P., G. Griffiths, and G. Warren, 1984, J. Cell Biol., 2142-2147) these stereological estimates were combined with biochemical estimates of the amount of spike proteins in ER, Golgi complex, and plasma membrane to determine the density in the membranes of these compartments.
Aliveness Detection of Fingerprints using Multiple Static Features

Fake finger submission attack is a major problem in fingerprint recognition systems. In this paper, we introduce an aliveness detection method based on multiple static features, which derived from a single fingerprint image. The static features are comprised of individual pore spacing, residual noise and several first order statistics. Specifically, correlation filter is adopted to address individual pore spacing. The multiple static features are useful to reflect the physiological and statistical characteristics of live and fake fingerprint. The classification can be made by calculating the liveness scores from each feature and fusing the scores through a classifier. In our dataset, we compare nine classifiers and the best classification rate at 85% is attained by using a Reduced Multivariate Polynomial classifier. Our approach is faster and more convenient for aliveness check for field applications.
Case-control study of periconceptional folic acid supplementation and oral clefts.

There is consistent evidence that the risk of neural tube defects is decreased by periconceptional supplementation with folic acid. A similar protective effect has been postulated for oral clefts. A case-control study was conducted in greater metropolitan Boston; Massachusetts; Philadelphia, Pennsylvania; and southeastern Ontario, Canada, from 1988 through 1991 to test the hypothesis that folic acid supplementation during the periconceptional period reduces the risk of oral clefts. Crude and multivariate-adjusted relative risks were calculated for all oral clefts (n = 303), cleft palate (n = 108), and cleft lip with or without cleft palate (n = 195). Controls (n = 1,167) were liveborn or stillborn infants less than age 6 months who had various congenital anomalies other than oral clefts, neural tube defects, or other "midline defects. " Adjusted relative risks and 95 percent confidence intervals for daily folic acid supplementation during the periconceptional period were: oral clefts, 1.1 (95% confidence interval (CI) 0.8-1.7), cleft palate, 0.9 (95% CI 0.5-1.6), and cleft lip with or without cleft palate, 1.3 (95% CI 0.8-2.1). These findings do not support a protective association between the periconceptional use of folic acid supplements and the risk of oral clefts.
Modularity in BDI-Based Multi-agent Programming Languages

This paper proposes a module-based vision for designing BDI-based multi-agent programming languages. The introduced concept of modules enables common programming techniques such as encapsulation and information hiding for BDI-based programs, and facilitates the implementation of agent roles and profiles. This vision is applied to a BDI-based agent programming language to which specific programming constructs are added to allow the implementation of modules. The syntax and intuitive semantics of module based programming constructs are explained. An example is presented to illustrate how modules can be used to implement BDI-based multi-agent systems.
Role of BLE in proximity based automation of IoT: A practical approach

In this paper, we successfully demonstrate the role of Bluetooth Low Energy (BLE) in automating the Proximity based solutions for Internet of Things (IoT) by considering a real world use case scenario. Devices in IoT must be low powered in order to extend their lifetime. BLE compatible AltBeacon is aptly suited for this purpose. We have developed an application to show how various disparate technologies are integrated together to form IoT paradigm. We use a fixed AltBeacon node which allows an application running on a smart phone to determine its proximity with respect to the AltBeacon node. Once the application finds that it is within the proximity of the AltBeacon node then we can control various IP enabled devices through RESTful Service. We have proposed a software framework which can be used to automate IoT based on the proximity. This framework can be extended to control any of the IP enabled devices for Home Automation and Industrial Systems. From our experiments we determined that 1.5m is an optimum range for proximity.
Role of cannabis in motor vehicle crashes.

The use of cannabis is widespread throughout the world, and in many countries is increasing (1). After alcohol, the most frequently found psychoactive substance in the blood of motorists involved in traffic crashes is cannabis. The very high costs, in human and financial terms, of road traffic crashes underscores the need for a clear understanding of the contribution of cannabis use to the incidence of such crashes. If cannabis were demonstrated to be an independent risk factor for such crashes, then efforts to prevent driving after recent cannabis use could be justified. Evidence accumulated over the last half-century or more has clearly demonstrated the relation between blood alcohol concentration (BAC) and the risk of a serious road traffic crash. Significant impairment of driving skills begins at a BAC of about 50 mg/100 ml blood and increases exponentially with increasing BAC (2). This has led to various jurisdictions imposing maximum blood alcohol concentrations for legal driving. However, the relations between driving impairment and blood concentrations of other drugs, including cannabis, have not been so well established, and the legal responses have varied. The World Health Organization recently convened an Expert Working Group on Health Effects of Cannabis Use. This committee's report states: "There is sufficient consistency and coherence in the evidence from experimental studies and studies of cannabinoid levels among crash victims to conclude that there is an increased risk of motor vehicle crashes among persons who drive when intoxicated with cannabis" (1, p. 15). However, the references cited in support of this statement were for experimental studies and descriptive
A New Version Of GENETIC ALGORITHMS For Controlling Time Intensive Processes

The Genetic Algorithm (GA) has the superiority over classical optimization algorithms in finding the optimal (global) solution in multi-parameter search space. Because it simultaneously evaluates many points in the parameters space, it is more likely to converge toward the global solution. It need not assume that the search space differentiable or continuous and can also iterate several times on each datum received. This chapter proposes two genetic-based Takagi-Sugeno-Kang Recurrent Fuzzy Neural Network (TSK-RFNN) schemes; one is TSK-RFNN-G and the other is TSK-RFNN-GMRC. The former employs the well-known GA while the latter introduces the ModelReference Control (MRC) to the former. The proposed algorithm uses real data instead of binary data to represent a chromosome. Unlike the TSK-RFNN-G, the TSK-RFNN-GMRC selects the controller’s parameters online (at each time step). For comparison reasons, both the proposed schemes were tested for controlling time intensive processes e. g. the oxygen (O2) uptake system.
Deep Learning Regularized Fisher Mappings

For classification tasks, it is always desirable to extract features that are most effective for preserving class separability. In this brief, we propose a new feature extraction method called regularized deep Fisher mapping (RDFM), which learns an explicit mapping from the sample space to the feature space using a deep neural network to enhance the separability of features according to the Fisher criterion. Compared to kernel methods, the deep neural network is a deep and nonlocal learning architecture, and therefore exhibits more powerful ability to learn the nature of highly variable datasets from fewer samples. To eliminate the side effects of overfitting brought about by the large capacity of powerful learners, regularizers are applied in the learning procedure of RDFM. RDFM is evaluated in various types of datasets, and the results reveal that it is necessary to apply unsupervised regularization in the fine-tuning phase of deep learning. Thus, for very flexible models, the optimal Fisher feature extractor may be a balance between discriminative ability and descriptive ability.
Circadian adaptations to meal timing: neuroendocrine mechanisms

Circadian rhythms of behavior and physiology are generated by central and peripheral circadian oscillators entrained by periodic environmental or physiological stimuli. A master circadian pacemaker in the hypothalamic suprachiasmatic nucleus (SCN) is directly entrained by daily light-dark (LD) cycles, and coordinates the timing of other oscillators by direct and indirect neural, hormonal and behavioral outputs. The daily rhythm of food intake provides stimuli that entrain most peripheral and central oscillators, some of which can drive a daily rhythm of food anticipatory activity if food is restricted to one daily mealtime. The location of food-entrainable oscillators (FEOs) that drive food anticipatory rhythms, and the food-related stimuli that entrain these oscillators, remain to be clarified. Here, we critically examine the role of peripheral metabolic hormones as potential internal entrainment stimuli or outputs for FEOs controlling food anticipatory rhythms in rats and mice. Hormones for which data are available include corticosterone, ghrelin, leptin, insulin, glucagon, and glucagon-like peptide 1. All of these hormones exhibit daily rhythms of synthesis and secretion that are synchronized by meal timing. There is some evidence that ghrelin and leptin modulate the expression of food anticipatory rhythms, but none of the hormones examined so far are necessary for entrainment. Ghrelin and leptin likely modulate food-entrained rhythms by actions in hypothalamic circuits utilizing melanocortin and orexin signaling, although again food-entrained behavioral rhythms can persist in lesion and gene knockout models in which these systems are disabled. Actions of these hormones on circadian oscillators in central reward circuits remain to be evaluated. Food-entrained activity rhythms are likely mediated by a distributed system of circadian oscillators sensitive to multiple feeding related inputs. Metabolic hormones appear to play a modulatory role within this system.
Note on tautological classes of moduli of K3 surfaces

In this note we prove some cycle class relations on moduli of K3 surfaces. This note deals with a few properties of tautological classes on moduli spaces of K3 surfaces. Let M2d denote a moduli stack of K3 surfaces over an algebraically closed field with a polarization of degree 2d prime to the characteristic of the field. The Chern classes of the relative cotangent bundle 1 /M of the universal K3 surface X2d = X define classes t1 and t2 in the Chow groups CH i(X2d) of the universal K3 surface over M2d. The class t1 is the pull back from M2d of the first Chern class v = c1(V ) of the Hodge line bundle V = �∗( 2 /M ). We use Grothendieck-Riemann-Roch to determine the push forwards of the powers of t2. These are powers of v. We then prove that v 18 = 0 in the Chow group with rational coefficients ofM2d We show that this implies that a complete subvariety of M2d has dimension at most 17 and that this bound is sharp. These results are in line with those for moduli of abelian varieties. There the top Chern classg of the Hodge bundle vanishes in the Chow group with rational coefficients. The idea is that if the boundary of the Baily-Borel compactification has co-dimension r then some tautological class of co-dimension r vanishes. Our result means that v 18 is a torsion class. It would be very interesting to determine the order of this class as well as explicit representations of this class as a cycle on the boundary, cf., (2, 3). 2. The Moduli Space M2d Let k be an algebraically closed field. We consider the moduli space M2d of polarized K3 surfaces over k with a primitive polarization of degree 2d. This is a 19-dimensional algebraic space. Over the complex numbers we can describe it as an orbifold quotient 2d\2d, where 2d is a bounded symmetric domain and 2d an arithmetic subgroup of SO(3,19) obtained as follows. Consider the lattice U 3 ⊕E 2 8 , where U denotes a hyperbolic plane and E8 the usual rank 8 lattice. Let h be an element of this lattice with h h,hi = 2d. Then L2d = h ⊥ ∼ U 2 ⊥E 2 8 ⊥Zu with h u,ui = −2d is a lattice of signature (2,19) and we put
On convergence rates of Gibbs samplers for uniform distributions

We consider a Gibbs sampler applied to the uniform distribution on a bounded region R ⊆ R. We show that the convergence properties of the Gibbs sampler depend greatly on the smoothness of the boundary of R. Indeed, for sufficiently smooth boundaries the sampler is uniformly ergodic, while for jagged boundaries the sampler could fail to even be geometrically ergodic.