Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Aspects of a Probabilistic Resource Location Algorithm

Abstract. Resource location is a fundamental problem for large-scale distributed applications. In order to deal with this problem we have developed PSEARCH, a probabilistic protocol for large-scale networks. PSEARCH is an epidemic algorithm that uses basic concepts of Bayesian statistical inference to execute probabilistic queries. A probabilistic query has a predicate as parameter and returns a set of sites where the predicate is believed to hold. The query is probabilistic because there are some chances that the predicate does not hold in all, or even in any, of the sites returned. To evaluate the performance of PSEARCH, we have developed a simulation model and a prototype of the algorithm. This paper discusses the performance of PSEARCH and presents results based on a comparison with a flooding algorithm.
Optimal Control of a Class of Non-Linear Discrete-Continuous Hybrid Systems

This work is derived for solving a non-linear discrete-continuous systems optimal control problem by iterating on a sequence of simplified problems in linear quadratic form. A mixed approach with a discrete performance index and continuous state variable system description is used as the basis of the design, and it is shown how the global problem can be decomposed into local sub-system problems and a coordinator within a hierarchical framework, so the problem become simple. The correct optimal solution of a real system in which model-reality difference exists can be obtained from system model by interconnected co-state prediction iterative solution. An analysis of the optimality and convergence properties of the algorithm is presented and the efficiency of the technique is demonstrated
Leveraging primary feedback and spectrum sensing for cognitive access

We consider a time-slotted primary system where both the primary channel and primary activity are modeled as two independent two-state Markov chains. The primary transmitter can be idle or busy, whereas the channel can be in erasure or not. Moreover, the sensing channel between the primary transmitter and secondary transmitter is modeled as a two-state Markov chain to represent two levels of sensing reliability. At the beginning of each time slot, the secondary transmitter may remain idle, transmit directly, or probe the channel and access the channel only if it is sensed to be free. At the end of the slot the secondary transmitter overhears the ARQ feedback from the primary receiver, which is used to update its belief regarding primary activity, primary channel state, and sensing channel state. We devise optimal transmission strategies for the cognitive radio so as to maximize secondary throughput with the primary throughput guaranteed to be above a certain specified value. The optimization accounts for the instantaneous reward and also the expected future reward given secondary action.
Selfish Routing in the Presence of Network Uncertainty

We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modeled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of [14] and the congestion games with user-specific functions of [22]. We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms (w.r.t. our model's parameters) for computing some special cases of pure Nash equilibria and we show that negative results of [22], for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we show that when they exist, they are unique. Finally, we prove that the fully mixed Nash equilibrium is the worst equilibrium.
A 60-dB image rejection filter using Δ-Σ modulation and frequency shifting

We propose a novel image rejection scheme for a low-IF (low intermediate frequency) receiver. A Δ-Σ modulator converts I/Q signals to digital values, and then they are digitally processed. The Δ-Σ modulator is a second-order complex band-pass type; the proposed architecture is suitable for various multi-channel communications and/or cognitive radio. As the first step in the digital signal processing, a spectrum is shifted so that the desired signal band is centered at 0 Hz. Next, by LPFs (low-pass filters), an image signal and the quantization noise of the Δ-Σ modulator are removed. These LPFs also function as a decimation filter; thus a dedicated decimation filter is not needed, and an extra area and power for it are saved. The test chip occupies 0.75 mm2 in a 180-nm mixed-signal process. The power is 6.0 mW at 1.8 V. The IRR (image rejection ratio) achieves 60 dB.
Automatic Acquisition of Lexical-Functional Grammar Resources from a Japanese Dependency Corpus

This paper describes a method for automatic acquisition of wide-coverage treebank-based deep linguistic resources for Japanese, as part of a project on treebankbased induction of multilingual resources in the framework of Lexical-Functional Grammar (LFG). We automatically annotate LFG f-structure functional equations (i.e. labelled dependencies) to the Kyoto Text Corpus version 4.0 (KTC4) (Kurohashi and Nagao 1997) and the output of of Kurohashi-Nagao Parser (KNP) (Kurohashi and Nagao 1998), a dependency parser for Japanese. The original KTC4 and KNP provide unlabelled dependencies. Our method also includes zero pronoun identification. The performance of the f-structure annotation algorithm with zero-pronoun identification for KTC4 is evaluated against a manually-corrected Gold Standard of 500 sentences randomly chosen from KTC4 and results in a pred-only dependency f-score of 94.72%. The parsing experiments on KNP output yield a pred-only dependency f-score of 82.08%.
Index finger rehabilitation/assistive device

In this paper, a novel exoskeleton for the index finger is introduced. Such a device is intended to be used for the rehabilitation of post-stroke patients. The target of the design is to produce a device with low weight and reduced space occupation, so that it can be worn without interfering with everyday use of the hand. The actuation is provided using low-cost lightweight miniature DC motors, and position feedback is obtained trough potentiometers. A working prototype has been built and tested. A closed-loop position control with friction compensation has been implemented and experimental results are presented and discussed.
HuRIC: a Human Robot Interaction Corpus

Recent years show the development of large scale resources (e.g. FrameNet for the Frame Semantics) that supported the definition of several state-of-the-art approaches in Natural Language Processing. However, the reuse of existing resources in heterogeneous domains such as Human Robot Interaction is not straightforward. The generalization offered by many data driven methods is strongly biased by the employed data, whose performance in out-of-domain conditions exhibit large drops. In this paper, we present the Human Robot Interaction Corpus (HuRIC). It is made of audio files paired with their transcriptions referring to commands for a robot, e.g. in a home environment. The recorded sentences are annotated with different kinds of linguistic information, ranging from morphological and syntactic information to rich semantic information, according to the Frame Semantics, to characterize robot actions, and Spatial Semantics, to capture the robot environment. All texts are represented through the Abstract Meaning Representation, to adopt a simple but expressive representation of commands, that can be easily translated into the internal representation of the robot.
Fusing Data and Optimizing Queries for Intelligent Search

A progressive application of evolutionary computing to optimize Boolean search queries in crisp and fuzzy information retrieval systems was investigated, evaluated in laboratory environment and presented. Additionally, WebFusion - novel meta- search engine contributing to the effectiveness of web search has been presented. The system learns the expertness of every particular underlying standalone search engine in a certain category based on the users ' preferences estimated according to an analysis of the click-through behavior. An intelligent re-ranking based on ordered weighted averaging is used for fusing the results' scores obtained from the underlying search engines. In this paper, the two promising web search improvement techniques are merged on the way towards intelligent search application.
Boosting GSHADE Capabilities: New Applications and Security in Malicious Setting

The secure two-party computation (S2PC) protocols SHADE and GSHADE have been introduced by Bringer et al. in the last two years. The protocol GSHADE permits to compute different distances (Hamming, Euclidean, Mahalanobis) quite efficiently and is one of the most efficient compared to other S2PC methods. Thus this protocol can be used to efficiently compute one-to-many identification for several biometrics data (iris, face, fingerprint). In this paper, we introduce two extensions of GSHADE. The first one enables us to evaluate new multiplicative functions. This way, we show how to apply GSHADE to a classical machine learning algorithm. The second one is a new proposal to secure GSHADE against malicious adversaries following the recent dual execution and cut-and-choose strategies. The additional cost is very small. By preserving the GSHADE's structure, our extensions are very efficient compared to other S2PC methods.
Contributions of phytoplankton and other particles to inherent optical properties in New England continental shelf waters

Variability in upper ocean optical properties is often driven by changes in the particle pool. We investigated the effects of such changes by characterizing individual particles. For particles in natural assemblages, we used a combination of Mie theory and flow cytometry to determine diameter (D), complex refractive index (n + in'), and optical cross‐sections at 488 nm. Particles were grouped into categories of eukaryotic pico/nanophytoplankton, Synechococcus, heterotrophic prokaryotes, detritus, and minerals to interpret variability in concurrently measured bulk inherent optical properties (IOPs) in New England continental shelf waters during two seasons. The summed contributions of individual particles to phytoplankton absorption and particle scattering were close to values for these properties measured independently using bulk methods (87% and 107%, respectively). In surface waters during both seasons, eukaryotic phytoplankton were responsible for the majority of both total particle absorption and total particle scattering. Mineral particles contributed the most to backscattering (bb) in the spring, whereas in the summer both mineral and detrital particles were important. Synechococcus and heterotrophic prokaryotes never contributed more than 14% to IOPs. Our findings emphasize that the measurement of nonliving particles, including detritus and minerals, is necessary for understanding variability in bb in the ocean, an important quantity in the interpretation of satellite ocean color.
Operator placement with QoS constraints for distributed stream processing

Distributed stream processing relies on in-network operator placement to achieve an optimal resource allocation which can use the pool of machines and network resource efficiently. Due to the QoS (Quality of Service) constraints imposed by the application, operator placement is usually treated as an optimization problem with constraints. Trying to get a global optimization is challenging since it's a NP-hard problem. In this paper, we formalize the operator placement problem with network usage as the optimization objective and use two resource allocation related QoS metrics: throughput and end-to-end delay. We propose a concept of Optimization Power to describe the host's capacity to reach a global optimal solution as soon as possible. We also propose a corresponding Optimization Power-based heuristic algorithm for operator placement. Experiment results show that our approach can achieve a better performance in terms of reducing network usage and end-top-end delay, improving success ratio, and decreasing resource discovery frequency, compared to some other placement algorithms.
Breaking Microsoft ’ s CAPTCHA

In this work we analyze the weaknesses of the CAPTCHA scheme used by Microsoft in their registration website. Furthermore, we propose some alternatives to mitigate the weaknesses found. In the first part of this project we built a CAPTCHA data set and used two different methods to automatically predict the CAPTCHA content, achieving a 57% success rate by using state-of-the-art techniques in computer vision. Finally, we propose some methods to overcome the vulnerabilities found. After a review on existing methods, we propose two alternatives: visual question-answer challenges and motion-based CAPTCHAs.
Chaotifying continuous-time TS fuzzy systems via discretization

An approach is proposed for making a given stable continuous-time Takagi-Sugeno (TS) fuzzy-system chaotic, by first discretizing it and then using state feedback control of arbitrarily small magnitude. The feedback controller chosen among several candidates is a simple sinusoidal function of the system states, which can lead to uniformly bounded state vectors of the controlled system with positive Lyapunov exponents, and satisfy the chaotic mechanisms of stretching and folding, thereby yielding chaotic dynamics. This approach is mathematically proven for rigorous generation of chaos from a stable continuous-time TS fuzzy system, where the generated chaos is in the sense of Li and Yorke (1975). A numerical example is included to visualize the theoretical analysis and the controller design.
Dual Role of the Tyrosine Kinase Syk in Regulation of Toll-Like Receptor Signaling in Plasmacytoid Dendritic Cells

Crosslinking of regulatory immunoreceptors (RR), such as BDCA-2 (CD303) or ILT7 (CD85g), of plasmacytoid dendritic cells (pDCs) efficiently suppresses production of type-I interferon (IFN)-α/β and other cytokines in response to Toll-like receptor (TLR) 7/9 ligands. This cytokine-inhibitory pathway is mediated by spleen tyrosine kinase (Syk) associated with the ITAM-containing adapter of RR. Here we demonstrate by pharmacological targeting of Syk that in addition to the negative regulation of TLR7/9 signaling via RR, Syk also positively regulates the TLR7/9 pathway in human pDCs. Novel highly specific Syk inhibitor AB8779 suppressed IFN-α, TNF-α and IL-6 production induced by TLR7/9 agonists in primary pDCs and in the pDC cell line GEN2.2. Triggering of TLR9 or RR signaling induced a differential kinetics of phosphorylation at Y352 and Y525/526 of Syk and a differential sensitivity to AB8779. Consistent with the different roles of Syk in TLR7/9 and RR signaling, a concentration of AB8779 insufficient to block TLR7/9 signaling still released the block of IFN-α production triggered via the RR pathway, including that induced by hepatitis B and C viruses. Thus, pharmacological targeting of Syk partially restored the main pDC function—IFN-α production. Opposing roles of Syk in TLR7/9 and RR pathways may regulate the innate immune response to weaken inflammation reaction.
OSBP-Related Protein 8 (ORP8) Regulates Plasma and Liver Tissue Lipid Levels and Interacts with the Nucleoporin Nup62

We earlier identified OSBP-related protein 8 (ORP8) as an endoplasmic reticulum oxysterol-binding protein implicated in cellular lipid homeostasis. We now investigated its action in hepatic cells in vivo and in vitro. Adenoviral overexpression of ORP8 in mouse liver induced a decrease of cholesterol, phospholipids, and triglycerides in serum (−34%, −26%, −37%, respectively) and liver tissue (−40%, −12%, −24%), coinciding with reduction of nuclear (n)SREBP-1 and -2 and mRNA levels of their target genes. Consistently, excess ORP8 reduced nSREBPs in HuH7 cells, and ORP8 overexpression or silencing by RNA interference moderately suppressed or induced the expression of SREBP-1 and SREBP-2 target genes, respectively. In accordance, cholesterol biosynthesis was reduced by ORP8 overexpression and enhanced by ORP8 silencing in [3H]acetate pulse-labeling experiments. ORP8, previously shown to bind 25-hydroxycholesterol, was now shown to bind also cholesterol in vitro. Yeast two-hybrid, bimolecular fluorescence complementation (BiFC), and co-immunoprecipitation analyses revealed the nuclear pore component Nup62 as an interaction partner of ORP8. Co-localization of ORP8 and Nup62 at the nuclear envelope was demonstrated by BiFC and confocal immunofluorescence microscopy. Furthermore, the impact of overexpressed ORP8 on nSREBPs and their target mRNAs was inhibited in cells depleted of Nup62. Our results reveal that ORP8 has the capacity to modulate lipid homeostasis and SREBP activity, probably through an indirect mechanism, and provide clues of an entirely new mode of ORP action.
NFAs with tagged transitions, their conversion to deterministic automata and application to regular expressions

A conservative extension to traditional nondeterministic finite automata (NFAs) is proposed to keep track of the positions in the input string for the last uses of selected transitions, by adding "tags" to transitions. The resulting automata are reminiscent of nondeterministic Mealy machines. A formal semantics of automata with tagged transitions is given. An algorithm is given to convert these augmented automata to the corresponding deterministic automata, which can be used to process strings efficiently. The application to regular expressions is discussed, explaining how the algorithms can be used to implement, for example, substring addressing and a lookahead operator, and an informal comparison to other widely-used algorithms is made.
A Software-Implemented Configurable Control Flow Checking Method

In space radiation environment, a large number of cosmic ray often results in transient faults on on-board computer. These transient faults lead to data flow errors or control flow errors during program running. For the control flow errors caused by transient faults, this paper proposes a control flow checking method based on classifying basic blocks CFCCB. CFCCB firstly classifies the basic blocks based on the control flow graph that has been inserted the abstract blocks. CFCCB then designs formatted signatures for the basic blocks and inserts the instructions for comparing and update signatures into every basic block for the purpose of checking the control flow errors that are inter-blocks, intra-blocks or inter-procedures. Compared to existing algorithms, CFCCB not only has high label express ability, but also can be configured flexibly. The fault injection experiment results of CFCCB and other similar algorithms have shown that, the average fail rate of programs with CFCCB has decreased to 19.9% at the cost of increasing the executing time by 34% and increasing the memory overhead by 41.5% in average. CFCCB has lower performance and memory overhead, and has highest reliability among the similar algorithms.
Who is not reassured following benign diagnosis of breast symptoms?

Many women fail to be reassured about their breast symptom following benign diagnosis. Identification of the factors contributing to this continued anxiety is important in order that appropriate intervention can be incorporated into the care of women undergoing diagnosis. In this study, we measured levels of anxiety, depression, stress, perceived personal risk of breast cancer, fear of breast cancer treatment and general health anxiety along with clinical and demographic variables in women undergoing investigation of breast symptoms. We then assessed if these factors were associated with reassurance about the breast symptom immediately following benign diagnosis.
20 Associative Effects : Competition , Social Interactions

These findings . support the writer's view that competitive ability should be accepted as it stands as a genetic character, simple or aggregate, a view of great importance in the discussion to follow. This chapter weaves together several seemingly unrelated, but nevertheless important, topics: competition; altruism and other social behaviors; traits defined by group, rather than individual, behavior; maternal effects; group and kin selection. The connection between all of these topics is the notion that the genotype (and hence phenotype) of one individual may influence the trait value of another. In this sense, the " environmental " component of the phenotype of a focal individual may itself have some heritable component (based on the contribution from some other individual), allowing some part of the environmental component to evolve along with the focal trait. In such settings, the phenotype of a focal individual consists of two components: direct effects from the focal individual and associative (or associate) effects contributed from other individuals within the group. A critical implication of this distinction is that the breeding value of an individual contains a component for direct effects that appear in its phenotype (and hence can be influenced by individual selection) and a component for associative effects that only appear in the phenotypes of other group members. For selection to effectively access the associative contribution generally requires either that (i) interactions occur among kin (kin selection), or (ii) selection is based on some combination of both individual and group values (multilevel selection). In the extreme, group selection occurs when all of the weight is placed on between-group differences. Note that multilevel selection is a generalization of the family selection index (Chapter 17) to more general groups. The framework for dealing with these issues has was laid out in a series of classic, but largely ignored, papers by, who introduced associative effects. There are also roots extending to classic work on maternal effects based on trait phenotype (Falconer 1965) or on an unmeasured material value (Willham 1963), as well as to the foundations of the study of social evolution (Hamilton 1963, 1964a,b). There are two modeling approaches for dealing with associative effects: trait-based and variance-component based. Trait-based approaches (Moore et al. 1997) have their roots in univariate (Falconer 1965) and multivariate (Kirkpatrick and Lande 1989, Lande and Kirk-patrick 1990) models of response under maternal effects. As their name implies, trait-based approaches assume that we know …