Miracle-dz/UniFAR-FTUs huggingface dataset:
A Tractable Pseudo-Likelihood Function for Bayes Nets Applied to Relational Data

Bayes nets (BNs) for relational databases are a major research topic in machine learning and artificial intelligence. When the database exhibits cyclic probabilistic dependencies, measuring the fit of a BN model to relational data with a likelihood function is a challenge [5, 36, 28, 9]. A common approach to difficulties in defining a likelihood function is to employ a pseudo-likelihood; a prominent example is the pseudo likelihood defined for Markov Logic Networks (MLNs). This paper proposes a new pseudo likelihood P ∗ for Parametrized Bayes Nets (PBNs) [32] and other relational versions of Bayes nets. The pseudo log-likelihood L∗ = ln(P ∗) is similar to the single-table BN log-likelihood, where row counts in the data table are replaced by frequencies in the database. We introduce a new type of semantics based on the concept of random instantiations (groundings) from classic AI research [12, 1]: The measure L∗ is the expected log-likelihood of a random instantiation of the 1st-order variables in the PBN. The standard moralization method for converting a PBN to an MLN provides another interpretation of L∗: the measure is closely related to the loglikelihood and to the pseudo log-likelihood of the moralized PBN. For parameter learning, the L∗-maximizing estimates are the empirical conditional frequencies in the databases. For structure learning, we show that the state of the art learn-and-join method of Khosravi et al. [18] implicitly maximizes the L∗ measure. The measure provides a theoretical foundation for this algorithm, while the algorithm’s empirical success provides experimental validation for its useful-
Anonymity of Bitcoin Transactions An Analysis of Mixing Services

Bitcoin, a distributed, cryptographic, digital currency, gained a lot of media attention for being an anonymous e-cash system. But as all transactions in the network are stored publicly in the blockchain, allowing anyone to inspect and analyze them, the system does not provide real anonymity but pseudonymity. There have already been studies showing the possibility to deanonymize bitcoin users based on the transaction graph and publicly available data. Furthermore, users could be tracked by bitcoin exchanges or shops, where they have to provide personal information that can then be linked to their bitcoin addresses. Special bitcoin mixing services claim to obfuscate the origin of transactions and thereby increase the anonymity of its users. In this paper we evaluate three of these services – Bitcoin Fog, BitLaun-dry, and the Send Shared functionality of Blockchain.info – by analyzing the transaction graph. While Bitcoin Fog and Blockchain.info successfully mix our transaction, we are able to ﬁnd a direct relation between the input and output transactions in the graph of BitLaundry.
Power system small-signal oscillation stability as affected by large-scale PV penetration

This paper investigates the impact of a large photovoltaic (PV) penetration on power system small signal oscillation stability. A comprehensive model of a single-machine infinite-bus power system integrated with a PV power generation power plant is established. Numerical computation of damping torque contribution from the PV power plant is carried out, which is confirmed by the results of calculation of system oscillation model and non-linear simulation. Those results indicate that power system oscillation stability can be affected either positively or negatively. There exists an operational limit of the PV power plant as far as system oscillation stability is concerned. Beyond the operational limit, the PV generation supplies negative damping torque, thus damaging system oscillation stability. Hence for the safe penetration of PV generation into power systems, the operational limit of oscillation stability of the PV power plant must be considered.
Selective Reduction of AMPA Currents onto Hippocampal Interneurons Impairs Network Oscillatory Activity

Reduction of excitatory currents onto GABAergic interneurons in the forebrain results in impaired spatial working memory and altered oscillatory network patterns in the hippocampus. Whether this phenotype is caused by an alteration in hippocampal interneurons is not known because most studies employed genetic manipulations affecting several brain regions. Here we performed viral injections in genetically modified mice to ablate the GluA4 subunit of the AMPA receptor in the hippocampus (GluA4HC−/− mice), thereby selectively reducing AMPA receptor-mediated currents onto a subgroup of hippocampal interneurons expressing GluA4. This regionally selective manipulation led to a strong spatial working memory deficit while leaving reference memory unaffected. Ripples (125–250 Hz) in the CA1 region of GluA4HC−/− mice had larger amplitude, slower frequency and reduced rate of occurrence. These changes were associated with an increased firing rate of pyramidal cells during ripples. The spatial selectivity of hippocampal pyramidal cells was comparable to that of controls in many respects when assessed during open field exploration and zigzag maze running. However, GluA4 ablation caused altered modulation of firing rate by theta oscillations in both interneurons and pyramidal cells. Moreover, the correlation between the theta firing phase of pyramidal cells and position was weaker in GluA4HC−/− mice. These results establish the involvement of AMPA receptor-mediated currents onto hippocampal interneurons for ripples and theta oscillations, and highlight potential cellular and network alterations that could account for the altered working memory performance.
Information Flow in Systems with Schedulers

The focus of work on information flow security has primarily been on definitions of security in asynchronous systems models. This paper considers systems with schedulers, which require synchronous variants of these definitions. In particular, it studies the dependence of these variant definitions of security on implementation details of the scheduler. Such independence is shown to hold for synchronous variants of trace-based definitions, but not for bisimulation-based definitions. Stronger versions of the bisimulation-based definitions are proposed that recover implementation-independence.
Unsupervised classification via decision trees: an information-theoretic perspective

Integrated sensing and processing decision trees (ISPDT) (Priebe et al. (2004)) were introduced as a tool for supervised classification of high-dimensional data. In this paper, we consider the problem of unsupervised classification, through a recursive construction of ISPDT, where at each internal node the data (i) are split into clusters, and (ii) are transformed independently of other clusters, guided by some optimization objective. We show that the maximization of information-theoretic quantities such as mutual information and /spl alpha/-divergences is theoretically justified for growing ISPDT, assuming that each data point is generated by a finite-memory random process given the class label. Furthermore, we present heuristics that perform the maximization in a greedy manner, and we demonstrate their effectiveness with empirical results from multispectral imaging.
An Intelligent Interactive System Based on Hand Gesture Recognition Algorithm and Kinect

In this paper, gesture recognition algorithm with kinect sensor is proposed. the depth cue is used to locate the hand area. Based on the histograms of oriented gradient (HOG) and adaboost learning methods, the static hand algorithm is designed to recognize the predefine gesture in the hand Area. by tracking the hand trajectory by kinect, hmms is used to train and classify dynamic gesture. an intelligent interactive system based on hand gesture recognition algorithm above is presented to choose and control different programs. Experimental results demonstrate that our gesture recognition algorithm is robust and effective, and the built interactive system with more intelligence improves the convenience and nature between human-computer interaction.
Fabrication and Performance of 0.25-$\mu$m Gate Length Depletion-Mode GaAs-Channel MOSFETs With Self-Aligned InAlP Native Oxide Gate Dielectric

The fabrication and performance of 0.25- mum gate length GaAs-channel MOSFETs using the wet thermal native oxide of InAlP as the gate dielectric are reported. A fabrication process that self-aligns the gate oxidation to the gate recess and metallization to reduce the source access resistance is demonstrated for the first time. The fabricated devices exhibit a peak extrinsic transconductance of 144 mS/mm, an on-resistance of 3.46 Omega-mm, and a threshold voltage of -1.8 V for typical 0.25 -mum gate devices. A record cutoff frequency of 31 GHz for a GaAs-channel MOSFET and a maximum frequency of oscillation fmax of 47 GHz have also been measured.
Heat, fire and temperature: the industrial revolution and HCI

HCI has many challenges and internal debates (for example, where is our theory? What is the role of design in HCI? What is the relationship between research and practice? How do we make an impact? ) that recur at the CHI conference and that students either ask themselves or find they are asked by others. This paper takes a historical look at this issue and describes some of the discoveries made during the industrial revolution about heat, fire and temperature (the development of thermodynamics) and how these discoveries were made. The parallels to human-computer interaction today are explored with two primary intentions: - to show how important it is that we continue to debate and investigate the precise nature of concepts we take for granted (e.g. usability, user interfaces, user experience), and to illustrate how practice contributes to the development of theoretical concepts.
Pedestrian Detection on a Moving Vehicle: an Investigation about Near Infra-Red Images

The aim of this paper is to investigate the employment of a NIR (near infra-red) camera on a moving vehicle for pedestrian detection, considering the NIR radiation as a suitable waveband for a single sensor device. In particular, we studied a system with special attention to cost, in order to make it affordable for all vehicles. We used as equipment an analog NIR CCD camera and examined the system behaviour in three different lighting conditions: daytime, nighttime using dipped-beam headlights and nighttime using full-beam headlights. Subsequently we chose the lighting situation which proved, in the long run, to be the most suitable for pedestrian detection. The algorithm proved to be efficient in common exurban scenarios
Hedgehog labeling: View management techniques for external labels in 3D space

Annotations of objects in 3D environments are commonly controlled using view management techniques. State-of-the-art view management strategies for external labels operate in 2D image space. This creates problems, because the 2D view of a 3D scene changes over time, and temporal behavior of elements in a 3D scene is not obvious in 2D image space. We propose managing the placement of external labels in 3D object space instead. We use 3D geometric constraints to achieve label placement that fulfills the desired objectives (e.g., avoiding overlapping labels), but also behaves consistently over time as the viewpoint changes. We propose two geometric constraints: a 3D pole constraint, where labels move along a 3D pole sticking out from the annotated object, and a plane constraint, where labels move in a dominant plane in the world. This formulation is compatible with standard optimization approaches for labeling, but overcomes the lack of temporal coherence.
Nonlinearity estimation in Hammerstein systems based on ordered observations

The nonlinear subsystem of a Hammerstein system is identified, i.e., its characteristic is recovered from input output ohservations of the whole system. The input and disturbance are white stochastic processes. The identified characteristic satisfies a piecewise Lipschitz condition only. Algorithms presented in the paper are calculated from ordered input-output observations, i.e., from pairs of observations arranged in a sequence in which input measurements increase in value. The mean integrated square error converges to zero as the number of observations tends to infinity. Convergence rates are insensitive to the shape of the probability density of the input signal. Results of numerical simulation are also shown.
Fixed Priority Scheduling Theory for Hard Real-time Systems. in Foundations of Real-time Computing — Scheduling and Resource Management. Kluwer Academic Symbolic Model Checking for Event-driven Real-time Systems

In this work we propose a verification methodology consisting of selective quantitative analysis and interval model checking. Our methods can aid not only in determining if a system works correctly, but also in understanding how well the system works. The selective quantitative algorithms compute minimum and maximum delays over a selected subset of system executions. We use a formula of the linear-time temporal logic LTL in order to select either infinite paths or finite intervals over which the computation is performed. We therefore define two semantics for LTL – over infinite paths and over finite intervals. We show how tableaux for LTL formulas can be used for selecting either paths or intervals and can also be used for model checking formulas interpreted over paths or intervals. We have implemented a tool based on our techniques. To demonstrate the usefulness of our methods we verified a complex distributed real-time system. Several features of this example make it an interesting target for our techniques. It is a system of realistic complexity, its components are existing systems and protocols executing a mixture of multimedia, traditional real-time and non-real time tasks. Also, the distributed nature of the system makes the interaction among its various components much richer. This also makes its analysis more difficult. Out tool were able to analyze the system and verify that the deadlines are met by the design. Moreover, we have been able to identify inefficiencies that caused the response time to increase significantly (about 50%). After changing the design we not only verified that the response time was lower, but were also able to determine the causes for the poor performance of the original model using interval model checking. Address: School of Computer Science, Pittsburgh, PA 15213, USA. Email: Sergio.Campos@cs.cmu. edu yAddress: School of Computer Science, Pittsburgh, PA 15213, USA. Email: Edmund.Clarke@cs.cmu. edu zAddress: Department of Computer Science, Haifa 32000, Israel. Email: orna@cs.technion. ac.il
Generating Representative Synthetic Workloads: An Unsolved Problem

Synthetic disk request traces are convenient and popular workloads for performance evaluation of storage subsystem designs and implementations. This paper develops an approach for validating synthetic disk request generators. Using this approach, commonly-used simplifying assumptions about workload characteristics (e.g., uniformly-distributed starting addresses and Poisson arrivals) are shown to be inappropriate, often leading to inaccurate performance predictions. Also, workload characteristics that require additional study are identi ed.
Market-based dynamic task allocation in mobile surveillance systems

Mobile surveillance systems include a vast array of mobile sensing nodes with varying sensing modalities that can sense continuously the volume of interest. These distributed nodes are capable of sensing, processing, mobilization and communication with other nodes. One of the fundamental problems of mobile surveillance systems is how to assign a set of tasks to a set of mobile sensors and how to coordinate the behavior of these mobile sensing nodes in order to perform cooperative tasks efficiently. This problem is known as multi-robot task allocation (MRTA). This paper presents centralized and hierarchical dynamic and fixed tree task allocation approaches to solve the MRTA problem. The objective comparison results show that hierarchical dynamic tree task allocation outperforms all the other techniques especially in complex surveillance operations where large number of robots is used to scan large number of areas.
An alternating sheared AA pair and elements of stability for a single sheared purine-purine pair flanked by sheared GA pairs in RNA.

A previous NMR structure of the duplex 5'GGU GGA GGCU/PCCG AAG CCG5' revealed an unusually stable RNA internal loop with three consecutive sheared GA pairs. Here, we report NMR studies of two duplexes, 5'GGU GGA GGCU/PCCA AAG CCG5' (replacing the UG pair with a UA closing pair) and 5'GGU GAA GGCU/PCCG AAG CCG5' (replacing the middle GA pair with an AA pair). An unusually stable loop with three consecutive sheared GA pairs forms in the duplex 5'GGU GGA GGCU/PCCA AAG CCG5'. The structure contrasts with that reported for this loop in the crystal structure of the large ribosomal subunit of Deinococcus radiodurans [Harms, J., Schluenzen, F. , Zarivach, R. , Bashan, A. , Gat, S. , Agmon, I. , Bartels, H. , Franceschi, F. , and Yonath, A. (2001) Cell 107, 679-688]. The middle AA pair in the duplex 5'GGU GAA GGCU/PCCG AAG CCG5' rapidly exchanges orientations, resulting in alternative base stacking and pseudosymmetry with exclusively sheared pairs. The U GAA G/G AAG C internal loop is 2.1 kcal/mol less stable than the U GGA G/G AAG C internal loop at 37 degrees C. Structural, energetic, and dynamic consequences upon functional group substitutions within related 3 x 3 and 3 x 6 internal loops are also reported.
Detection of pYV+ Yersinia enterocolitica isolates by P1 slide agglutination

Rabbit polyclonal antisera were raised against the pYV-encoded outer membrane protein P1 of five Yersinia enterocolitica strains belonging to serogroups O:3, O:5,27, O:8, and O:9. Analysis of these strains with the sera showed that P1 presented at least six different antigenic factors. Two of the serum specimens were chosen to test the P1 agglutinability of 797 strains isolated from various sources. This technique appeared to be more reliable than autoagglutination and Ca2+ dependency to monitor the presence of the pYV plasmid. Hence, we propose this P1-mediated agglutination as a new and easy virulence test.
Binary Reweighted l1-Norm Minimization for One-Bit Compressed Sensing

The compressed sensing (CS) can acquire and reconstruct a sparse signal from relatively fewer measurements than the classical Nyquist sampling. Practical ADCs not only sample but also quantize each measurement to a finite number of bits; moreover, there is an inverse relationship between the achievable sampling rate and the bit depth. The quantized CS has been studied recently and it has been demonstrated that accurate and stable signal acquisition is still possible even when each measurement is quantized to just a single bit. Many algorithms have been proposed for 1-bit CS however, most of them require that the prior knowledge of the sparsity level (number of the nonzero elements) should be known. In this paper, we explored the reweighted l1-norm minimization method in recovering signals from 1-bit measurements. It is a nonconvex penalty and gives different weights according to the order of the absolute value of each element. Simulation results show that our method has much better performance than the state-of-art method (BIHT) when the sparsity level is unknown. Even when the sparsity level is known, our method can get a comparable performance with the BIHT method. Besides,we validate our methods in an ECG signal recovery problem.
A model for tetrapyrrole synthesis as the primary mechanism for plastid-to-nucleus signaling during chloroplast biogenesis

Chloroplast biogenesis involves the co-ordinated expression of the chloroplast and nuclear genomes, requiring information to be sent from the developing chloroplasts to the nucleus. This is achieved through retrograde signaling pathways and can be demonstrated experimentally using the photobleaching herbicide, norflurazon, which in seedlings results in chloroplast damage and the reduced expression of many photosynthesis-related, nuclear genes. Genetic analysis of this pathway points to a major role for tetrapyrrole synthesis in retrograde signaling, as well as a strong interaction with light signaling pathways. Currently, the best model to explain the genetic data is that a specific heme pool generated by flux through ferrochelatase-1 functions as a positive signal to promote the expression of genes required for chloroplast development. We propose that this heme-related signal is the primary positive signal during chloroplast biogenesis, and that treatments and mutations affecting chloroplast transcription, RNA editing, translation, or protein import all impact on the synthesis and/or processing of this signal. A positive signal is consistent with the need to provide information on chloroplast status at all times. We further propose that GUN1 normally serves to restrict the production of the heme signal. In addition to a positive signal re-enforcing chloroplast development under normal conditions, aberrant chloroplast development may produce a negative signal due to accumulation of unbound chlorophyll biosynthesis intermediates, such as Mg-porphyrins. Under these conditions a rapid shut-down of tetrapyrrole synthesis is required. We propose that accumulation of these intermediates results in a rapid light-dependent inhibition of nuclear gene expression that is most likely mediated via singlet oxygen generated by photo-excitation of Mg-porphyrins. Thus, the tetrapyrrole pathway may provide both positive and inhibitory signals to control expression of nuclear genes.
Experimental identification of stress concentrations in piezoresistive nanocomposites via electrical impedance tomography

Piezoresistive nanocomposites hold incredible potential for structural health monitoring (SHM). The electrical conductivity of these materials is influenced by strain, making them self-sensing. Electrical impedance tomography (EIT) is a low-cost, non-invasive method of imaging the internal conductivity distribution of a domain. To date, EIT has most often been used to detect damage. However, localizing incipient damage for failure prediction may situationally be a more useful capability from a SHM perspective. Herein, we explore the potential of EIT to identify stress concentration-induced conductivity changes in piezoresistive nanocomposites. First, a nanocomposite specimen with a circular hole is manufactured. Next, displacements are applied in small increments and boundary voltage data is collected after each increment of displacement such that conductivity images can be produced as the stress concentration intensifies. These results demonstrate that the proposed approach allows for accurate spatial localization of stress concentrations in deformed nanocomposites via EIT-imaged conductivity changes and therefore has potential to enable greatly advanced failure prediction capabilities.