Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic Query Answering with Time-Series Graphs

Statistical graphs are ubiquitous mechanisms for data visualization such that most, if not all, enterprises communicate information through them. However, many graphs are stored as unstructured images or proprietary binary objects, making them difficult to work with beyond the reports in which they are embedded. While graphs can be mapped to more common XML representations, these lack expressive semantics to discover new knowledge about them or to answer queries at various levels of granularity. This paper describes an OWL ontology that facilitates the representation, exchange, reasoning and query answering of statistical graph data. We illustrate the advantages of using an ontological approach to discover and query about time-series statistical graphs.
Runtime verification of cryptographic protocols 5

There has been a significant amount of work devoted to the static verification of security protocol designs. Virtually all of these results, when applied to an actual implementation of a security protocol, rely on certain implicit assumptions on the implementation (for example, that the cryptographic checks that according to the design have to be performed by the protocol participants are carried out correctly). So far there seems to be no approach that would enforce these implicit assumptions for a given implementation of a security protocol (in particular regarding legacy implementations which have not been developed with formal verification in mind). In this paper, we use a code assurance technique called ‘‘runtime verification’’ to solve this open problem. Runtime verification determines whether or not the behaviour observed during the execution of a system matches a given formal specification of a ‘‘reference behaviour’’. By applying runtime verification to an implementation of any of the participants of a security protocol, we can make sure during the execution of that implementation that the implicit assumptions that had to be made to ensure the security of the overall protocol will be fulfilled. The overall assurance process then proceeds in two steps: First, a design model of the security protocol in UML is verified against security properties such as secrecy of data. Second, the implicit assumptions on the protocol participants are derived from the design model, formalised in linear-time temporal logic, and the validity of these formulae at runtime is monitored using runtime verification. The aim is to increase one’s confidence that statically verified properties are satisfied not only by a model of the system, but also by the actual running system itself. We demonstrate the approach at the hand of the open source implementation Jessie of the de-facto Internet security protocol standard SSL. We also briefly explain how to transfer the results to the SSL-implementation within the Java Secure Sockets Extension (JSSE) recently made open source by Sun Microsystems.
Analysing user motivation in an art folksonomy

The perception of art is a subjective affair - being influenced by our feelings, education and cultural background. Contrary, the study of art history uses formal methods to classify artworks. This discrepancy often poses a risk of being insurmountable -- especially for users without prior knowledge of art history. The concept of social tagging provides the possibility to merge art historical information with the subjective perception of users. For our art Web platform explorARTorium, social tags augment exiting art historical information. In order to better understand how social tagging is best applied, it is necessary to examine the user's motivation to assign tags. We adopt the differentiation between users who are motivated by categorizing, and users who are motivated by describing resources. By evaluating our folksonomy according to this paradigm, we show that the preference for certain artworks has an effect on the user's tagging motivation, whereas the presentation of an artwork does not. While measures exist that are able to identify the user's motivation for annotating artworks, we propose an heuristic that aims to classify categorizing, respectively descriptive, tags. After evaluating this proposed heuristic, we show that it is indeed possible to identify categorizing and descriptive tags, even though the results are somewhat biased by the content of the resources and the individual tagging behaviour of the users.
IMPROVED BICLUSTERING ALGORITHM FOR GENE EXPRESSION DATA

Biclustering algorithms simultaneously cluster both rows and columns. These types of algorithms are ap plied to gene expression data analysis to find a subset o f genes that exhibit similar expression pattern und er a subset of conditions. Cheng and Church introduced t he mean squared residue measure to capture the coherence of a subset of genes over a subset of con ditions. They provided a set of heuristic algorithm s based primarily on node deletion to find one bicluster or a set of biclusters after masking discovered biclu sters with random values. The mean squared residue is a popular measure of bicluster quality. One drawback however is that it is biased toward flat biclusters with lo w row variance. In this paper, we introduce an impr oved bicluster score that removes this bias and promotes the discovery the most significant biclusters in t he dataset. We employ this score within a new bicluste ring approach based on the bottom up search strateg y. We believe that the bottom-up search approach bette r models the underlying functional modules of the g ene expression dataset.
The validity and reliability of the EValuation of INtervention Scale: preliminary report

Pain management is a priority for infants receiving neonatal care as they undergo many necessary painful and stressful interventions, which are associated with negative short‐ or long‐term consequences. This study aims to validate the content, and test the reliability, of the EValuation of INtervention Scale (EVIN), which is designed to evaluate the use of widely recommended nonpharmacological strategies to reduce neonatal pain and stress during procedures.
HTTP/2-Based Adaptive Streaming of HEVC Video Over 4G/LTE Networks

In HTTP Adaptive Streaming, video content is temporally divided into multiple segments, each encoded at several quality levels. The client can adapt the requested video quality to network changes, generally resulting in a smoother playback. Unfortunately, live streaming solutions still often suffer from playout freezes and a large end-to-end delay. By reducing the segment duration, the client can use a smaller temporal buffer and respond even faster to network changes. However, since segments are requested subsequently, this approach is susceptible to high round-trip times. In this letter, we discuss the merits of an HTTP/2 push-based approach. We present the details of a measurement study on the available bandwidth in real 4G/LTE networks, and analyze the induced bit-rate overhead for HEVC-encoded video segments with a sub-second duration. Through an extensive evaluation with the generated video content, we show that the proposed approach results in a higher video quality (+7.5%) and a lower freeze time (-50.4%), and allows to reduce the live delay compared with traditional solutions over HTTP/1.1.
Analysis on the Effect of System Parameter on Double Cantilevers Vibro-Impact System Response

The dynamic response of double cantilever vibro-impact system such as the stability of periodic motion, bifurcation etc., is an extremely important research content. However, the system dynamic characteristics are often influenced by the system parameters. Therefore, the theoretical modal of a double cantilevers vibro-impact system was established in this work, and the influence of clearance, damping and cubic nonlinear item on the dynamic characteristics of double cantilever vibro-impact system is detailedly analyzed through the numerical method . The results is helpful to analyze the practical engineering and to explore the nonlinear phenomena and the instability mechanism of the vibro-impact system such as milling process.
Edinburgh Research Explorer Dependency Tree Automata

We introduce a new kind of tree automaton, a dependency tree automaton, that is suitable for deciding properties of classes of terms with binding. Two kinds of such automaton are deﬁned, nondeterministic and alternating. We show that the nondeterministic automata have a decidable nonemptiness problem and leave as an open question whether this is true for the alternating version. The families of trees that both kinds recognise are closed under intersection and union. To illustrate the utility of the automata, we apply them to terms of simply typed lambda calculus and provide an automata-theoretic characterisation of solutions to the higher-order matching problem.
Disorder-Specific Predictive Classification of Adolescents with Attention Deficit Hyperactivity Disorder (ADHD) Relative to Autism Using Structural Magnetic Resonance Imaging

Objective Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder, but diagnosed by subjective clinical and rating measures. The study’s aim was to apply Gaussian process classification (GPC) to grey matter (GM) volumetric data, to assess whether individual ADHD adolescents can be accurately differentiated from healthy controls based on objective, brain structure measures and whether this is disorder-specific relative to autism spectrum disorder (ASD). Method Twenty-nine adolescent ADHD boys and 29 age-matched healthy and 19 boys with ASD were scanned. GPC was applied to make disorder-specific predictions of ADHD diagnostic status based on individual brain structure patterns. In addition, voxel-based morphometry (VBM) analysis tested for traditional univariate group level differences in GM. Results The pattern of GM correctly classified 75.9% of patients and 82.8% of controls, achieving an overall classification accuracy of 79.3%. Furthermore, classification was disorder-specific relative to ASD. The discriminating GM patterns showed higher classification weights for ADHD in earlier developing ventrolateral/premotor fronto-temporo-limbic and stronger classification weights for healthy controls in later developing dorsolateral fronto-striato-parieto-cerebellar networks. Several regions were also decreased in GM in ADHD relative to healthy controls in the univariate VBM analysis, suggesting they are GM deficit areas. Conclusions The study provides evidence that pattern recognition analysis can provide significant individual diagnostic classification of ADHD patients and healthy controls based on distributed GM patterns with 79.3% accuracy and that this is disorder-specific relative to ASD. Findings are a promising first step towards finding an objective differential diagnostic tool based on brain imaging measures to aid with the subjective clinical diagnosis of ADHD.
The unconscious thought advantage: Further replication failures from a search for confirmatory evidence

According to the deliberation without attention (DWA) hypothesis, people facing a difficult choice will make a better decision after a period of distraction than after an equally long period of conscious deliberation, an effect referred to as the unconscious thought advantage (UTA). The status of the DWA hypothesis is controversial, as many studies have tried but failed to replicate the UTA. Here, we report a series of experiments that sought to identify the conditions under which the UTA can be replicated. Our starting point was a recent meta-analysis that identified the conditions under which the UTA was strongest in previous studies. Using a within-subjects design and a task that met each of these conditions, we failed to replicate the UTA. Based on closer inspection of previous methods and findings, we then examined some additional factors that could be important for replicating the UTA, including mental fatigue and choice complexity. This was to no avail, as the results revealed only a significant conscious thought advantage, when choice complexity was increased relative to the first experiment. We subsequently conducted exploratory analyses on the data across experiments and found that male subjects showed a significant conscious thought advantage while female subjects showed a trend towards an UTA. Taken together, our results suggest that replication of the UTA may depend more on characteristics of the sample than on the characteristics of the task, and they suggest that gender could be a source of variance in the outcomes of previous studies using a between-subjects design.
Interpolation-based Q-learning

We consider a variant of Q-learning in continuous state spaces under the total expected discounted cost criterion combined with local function approximation methods. Provided that the function approximator satisfies certain interpolation properties, the resulting algorithm is shown to converge with probability one. The limit function is shown to satisfy a fixed point equation of the Bellman type, where the fixed point operator depends on the stationary distribution of the exploration policy and the function approximation method. The basic algorithm is extended in several ways. In particular, a variant of the algorithm is obtained that is shown to converge in probability to the optimal Q function. Preliminary computer simulations are presented that confirm the validity of the approach.
A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds

Three dimensional city models are necessary for supporting numerous management applications. For the determination of city models for visualization purposes, several standardized workflows do exist. They are either based on photogrammetry or on LiDAR or on a combination of both data acquisition techniques. However, the automated determination of reliable and highly accurate city models is still a challenging task, requiring a workflow comprising several processing steps. The most relevant are building detection, building outline generation, building modeling, and finally, building quality analysis. Commercial software tools for building modeling require, generally, a high degree of human interaction and most automated approaches described in literature stress the steps of such a workflow individually. In this article, we propose a comprehensive approach for automated determination of 3D city models from airborne acquired point cloud data. It is based on the assumption that individual buildings can be modeled properly by a composition of a set of planar faces. Hence, it is based on a reliable 3D segmentation algorithm, detecting planar faces in a point cloud. This segmentation is of crucial importance for the outline detection and for the modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, and the modeling approach, and we present and discuss several actual projects.
Simple mathematical modeling of efficient path selection for QoS routing in load balancing

We develop a very simple mathematical model to investigate the upper bound of the size of limited choices in our proposed QoS path selection algorithm called the largest widest shortest path among limited choices (LWSP-LC) for engineering design. The LWSP-LC can achieve load balancing effectively and reduce path searching complexity significantly. However, its performance is highly related to many factors, including the network environment and traffic condition. Our simulation results show that the size of limited choices is highly dependent on both the network size and network connectivity. By considering a fully connected network, we derive a simple mathematical model on the upper bound of the size of limited choices based on the network size only.
Widespread activation of immunity and pro‐inflammatory programs in peripheral blood leukocytes of HIV‐infected patients with impaired lung gas exchange

HIV infection is associated with impaired lung gas transfer as indicated by a low diffusing capacity (DLCO), but the mechanisms are not well understood. We hypothesized that HIV‐associated gas exchange impairment is indicative of system‐wide perturbations that could be reflected by alterations in peripheral blood leukocyte (PBL) gene expression. Forty HIV‐infected (HIV+) and uninfected (HIV–) men with preserved versus low DLCO were enrolled. All subjects were current smokers and those with acute illness, lung diseases other than COPD or asthma were excluded. Total RNA was extracted from PBLs and hybridized to whole‐genome microarrays. Gene set enrichment analysis (GSEA) was performed between HIV+ versus HIV– subjects with preserved DLCO and those with low DLCO to identify differentially activated pathways. Using pathway‐based analyses, we found that in subjects with preserved DLCO, HIV infection is associated with activation of processes involved in immunity, cell cycle, and apoptosis. Applying a similar analysis to subjects with low DLCO, we identified a much broader repertoire of pro‐inflammatory and immune‐related pathways in HIV+ patients relative to HIV– subjects, with up‐regulation of multiple interleukin pathways, interferon signaling, and toll‐like receptor signaling. We confirmed elevated circulating levels of IL‐6 in HIV+ patients with low DLCO relative to the other groups. Our findings reveal that PBLs of subjects with HIV infection and low DLCO are distinguished by widespread enrichment of immuno‐inflammatory programs. Activation of these pathways may alter the biology of circulating leukocytes and play a role in the pathogenesis of HIV‐associated gas exchange impairment.
How to Disembed a Program ?

This paper presents the theoretical blueprint of a new secure token called the Externalized Microprocessor (XμP). Unlike a smart-card, the XμP contains no ROM at all. While exporting all the device’s executable code to potentially untrustworthy terminals poses formidable security problems, the advantages of ROM-less secure tokens are numerous: chip masking time disappears, bug patching becomes a mere terminal update and hence does not imply any roll-out of cards in the field. Most importantly, code size ceases to be a limiting factor. This is particularly significant given the steady increase in on-board software complexity. After describing the machine’s instruction-set we will introduce two XμP variants. The first design is a public-key oriented architecture which relies on a new RSA screening scheme and features a relatively low communication overhead at the cost of computational complexity, whereas the second variant is secret-key oriented and relies on simple MACs and hash functions but requires more communication. For each of these two designs, we propose two protocols that execute and dynamically authenticate arbitrary programs. We also provide a strong security model for these protocols and prove their security under appropriate complexity assumptions.
Massless fields in scalar-tensor cosmologies.

We derive exact Friedmann--Robertson--Walker cosmological solutions in general scalar--tensor gravity theories, including Brans--Dicke gravity, for stiff matter or radiation. These correspond to the long or short wavelength modes respectively of massless scalar fields. If present, the long wavelength modes of such fields would be expected to dominate the energy density of the universe at early times and thus these models provide an insight into the classical behaviour of these scalar--tensor cosmologies near an initial singularity, or bounce. The particularly simple exact solutions also provide a useful example of the possible evolution of the Brans--Dicke (or dilaton) field, $\phi$, and the Brans--Dicke parameter, $\omega(\phi)$, at late times in spatially curved as well as flat universes. We also discuss the corresponding solutions in the conformally related Einstein metric.
WCET overapproximation for software in the context of a Cyber-Physical System

We propose an approach for overapproximating the Worst-Case Execution Time (WCET) of embedded control software using formal methods. Model checking is iteratively applied to compute the WCET from the machine code of the software considering a platform and an environment model. We implemented the approach and present first experiments for a thermal controller application executed on a LEON3 processor under different environment constraints.
Shallow syntax analysis in Sanskrit guided by semantic nets constraints

We present the state of the art of a computational platform for the analysis of classical Sanskrit. The platform comprises modules for phonology, morphology, segmentation and shallow syntax analysis, organized around a structured lexical database. It relies on the Zen toolkit for finite state automata and transducers, which provides data structures and algorithms for the modular construction and execution of finite state machines, in a functional framework. Some of the layers proceed in bottom-up synthesis mode - for instance, noun and verb morphological modules generate all inflected forms from stems and roots listed in the lexicon. Morphemes are assembled through internal sandhi, and the inflected forms are stored with morphological tags in dictionaries usable for lemmatizing. These dictionaries are then compiled into transducers, implementing the analysis of external sandhi, the phonological process which merges words together by euphony. This provides a tagging segmenter, which analyses a sentence presented as a stream of phonemes and produces a stream of tagged lexical entries, hyperlinked to the lexicon. The next layer is a syntax analyser, guided by semantic nets constraints expressing dependencies between the word forms. Finite verb forms demand semantic roles, according to valency patterns depending on the voice (active, passive) of the form and the governance (transitive, etc) of the root. Conversely, noun/adjective forms provide actors which may fill those roles, provided agreement constraints are satisfied. Tool words are mapped to transducers operating on tagged streams, allowing the modeling of linguistic phenomena such as coordination by abstract interpretation of actor streams. The parser ranks the various interpretations (matching actors with roles) with penalties, and returns to the user the minimum penalty analyses, for final validation of ambiguities. The whole platform is organized as a Web service, allowing the piecewise tagging of a Sanskrit text.
Biochemical Constituents and Antioxidant Potential of Endophytic Fungi isolated from the Leaves of Azadirachta indica A. Juss (Neem) from Chennai, India

Four endophytic fungi identified from the leaves of Azadirachta indica A. Juss. (Meliaceae) were studied for their antioxidant potential. Biochemical constituents of endophytic fungal extracts were evaluated for their antioxidant activity by reducing power assay and nitric oxide radical inhibition by GriessIllosvoy reaction. The ascorbic acid content in Chaetomium sp. , Curvularia sp. , Colletotrichum sp. and Trichoderma sp. were 2.38, 1.21, 1.11, and 0.83 mg of quercetin equivalents/g respectively. The content of phenolic compounds followed the same pattern with values 28.5, 10.63, 9.82 and 7.51 mg of gallic acid equivalents/g, for Chaetomium sp. , Colletotrichum sp. , Curvularia sp. and Trichoderma sp. respectively. Apart from these, β-Carotene, tannin and total flavonoid content were also studied quantitatively. The antioxidant activities of fungal extracts increase with increasing amount of extracts (0.2-1 mg/mL). The variation in the content of phenolic components and ascorbic acid levels reflected the antioxidant activity of the organisms studied. The antioxidant activity of the extract of Chaetomium sp. is the highest followed by Curvularia sp. , Colletotrichum sp. and Trichoderma sp. The methanolic extracts of these endophytic fungi showed promising antioxidant potential for bioprospecting.