Miracle-dz/UniFAR-FTUs huggingface dataset:
Scalable long-term preservation of relational data through SPARQL queries

This Thesis addresses how Semantic Web representations, in particular RDF, can enable flexible and scalable preservation, recreation, and querying of databases.An approach has been developed for selective scalable long-term archival of relational databases (RDBs) as RDF, implemented in the SAQ (Semantic Archive and Query) system. The archival of user-specified parts of an RDB is specified using an extension of SPARQL, A-SPARQL. SAQ automatically generates an RDF view of the RDB, the RD-view. The result of an archival query is RDF triples stored in: i) a data archive file containing the preserved RDB content, and ii) a schema archive file containing sufficient meta-data to reconstruct the archived database. To achieve scalable data preservation and recreation, SAQ uses special query rewriting optimizations for the archival queries. It was experimentally shown that they improve query execution and archival time compared with naive processing. The performance of SAQ was compared with that of other systems supporting SPARQL queries to views of existing RDBs.When an archived RDB is to be recreated, the reloader module of SAQ first reads the schema archive file and executes a schema reconstruction algorithm to automatically construct the RDB schema. The thus created RDB is populated by reading the data archive and converting the read data into relational attribute values. For scalable recreation of RDF archived data we have developed the Triple Bulk Load (TBL) approach where the relational data is reconstructed by using the bulk load facility of the RDBMS. Our experiments show that the TBL approach is substantially faster than the naive Insert Attribute Value (IAV) approach, despite the added sorting and post-processing.To view and query semi-structured Topic Maps data as RDF the prototype system TM-Viewer was implemented. A declarative RDF view of Topic Maps, the TM-view, is automatically generated by the TM-viewer using a developed conceptual schema for the Topic Maps data model. To achieve efficient query processing of SPARQL queries to the TM-view query rewrite transformations were developed and evaluated. It was shown that they significantly improve the query execution time.
Axisymmetric oscillations of magnetic neutron stars

We calculate axisymmetric oscillations of rotating neutron stars composed of the surface fluid ocean, solid crust and fluid core, taking account of a dipole magnetic field as strong as B s ∼ 10 15 G at the surface. The adiabatic oscillation equations for the solid crust threaded by a dipole magnetic field are derived in Newtonian dynamics, on the assumption that the axis of rotation is aligned with the magnetic axis so that perturbations on the equilibrium can be represented by series expansions in terms of spherical harmonic functions Y m (θ, (Φ) with different degrees l for a given azimuthal wave number m around the magnetic axis. Although the three component models can support a rich variety of oscillation modes, axisymmetric (m = 0) toroidal t n and spheroidal l s n shear waves propagating in the solid crust are our main concerns, where l and n denote the harmonic degree and the radial order of the modes, respectively. In the absence of rotation, axisymmetric spheroidal and toroidal modes are completely decoupled, and we consider the effects of rotation on the oscillation modes only in the limit of slow rotation. We find that the oscillation frequencies of the fundamental toroidal torsional modes lt n in the crust are hardly affected by the magnetic field as strong as B s ∼ 10 15 G at the surface. As the radial order n of the shear modes in the crust becomes higher, however, both spheroidal and toroidal modes become susceptible to the magnetic field, and their frequencies in general get higher with increasing B s . We also find that the surface g modes and the crust/ocean interfacial modes are suppressed by a strong magnetic field, and that there appear magnetic modes in the presence of a strong magnetic field.
Interesting patterns using goal programming

Data mining leads to the discovery of large number of patterns, all of these patterns can not be of interest to user. So mining of interesting patterns from the set of mined patterns is an issue. According to the user's interest at particular time, set of interesting patterns can be mined; the interest of user can vary with the time. In this paper we proposed that using goal programming we can find the interesting patterns according to the user's requirement at particular time. In order to control the priority of interesting patterns we can attach the deviational variables. Set of interesting patterns can be mined according to the user's will at particular time.
Miniaturization, calibration & accuracy evaluation of a hybrid self-tracker

We have previously presented a prototype of a novel vision/inertial hybrid self-tracker intended for AR, wearable computing and mobile robotics applications. In this paper we describe a new prototype of the system which has been greatly reduced in size, weight, power consumption and cost, while simultaneously improved in performance through careful calibration. We describe the calibration approach in detail and present results to show the high accuracy levels achieved for the camera calibration and for the integrated tracking system.
Towards a Framework for Differential Unit Testing of Object-Oriented Programs

Software developers often face the task of determining how the behaviors of one version of a program unit differ from (or are the same as) the behaviors of a (slightly) different version of the same program unit. In such situations, developers would like to generate tests that exhibit the behavioral differences between the two versions, if any differences exist. We call this type of testing differential unit testing. Some examples of differential unit testing include regression testing, N-version testing, and mutation testing. We propose a framework, called Diffut, that enables differential unit testing of object-oriented programs. Diffut enables "simultaneous" execution of the pairs of corresponding methods from the two versions: methods can receive the same inputs (consisting of the object graph reachable from the receiver and method arguments), and Diffut compares their outputs (consisting of the object graph reachable from the receiver and method return values). Given two versions of a Java class, Diffut automatically synthesizes annotations (in the form of preconditions and postconditions) in the Java Modeling Language (JML) and inserts them into the unit under test to allow the simultaneous execution of the corresponding methods.
A similarity-based method for retrieving documents from the SCI/SSCI database

As more and more documents become electronically available, finding documents in large databases that fit users' needs is becoming increasingly important. In the past, the document search problem was dealt with using the database query approach or the text-based search approach. In this paper, we investigate this problem, focusing on the SCI/SSCI databases from ISI. Specifically, we design our search methodology based on the four fields commonly seen in a scientific research document: abstract, title, keywords, and reference list. Of these four, only the abstract field can be viewed as a normal text, while the other three have their own characteristics to differentiate them from texts. Therefore, we first develop a method to compute the similarity value for each field. Our next problem is combining the four similarity values into a final value. One approach is to assign weights to each and compute the weighted sum. We have not adopted this simple weighting method, however, because it is difficult to determine appropriate weights. Instead, we use the back propagation neural network to combine them. Finally, extensive experiments have been carried out using real documents drawn from TKDE journal, and the results indicate that in all situations our method has a much higher accuracy than the traditional text-based search approach.
Soil Nematodes and Their Prokaryotic Prey Along an Elevation Gradient in The Mojave Desert (Death Valley National Park, California, USA)

We characterized soil communities in the Mojave Desert across an elevation gradient. Our goal was to test the hypothesis that as soil quality improved with increasing elevation (due to increased productivity), the diversity of soil prokaryotes and nematodes would also increase. Soil organic matter and soil moisture content increased with elevation as predicted. Soil salinity did not correlate to elevation, but was highest at a mid-gradient, alluvial site. Soil nematode density, community trophic structure, and diversity did not show patterns related to elevation. Similar results were obtained for diversity of bacteria and archaea. Relationships between soil properties, nematode communities, and prokaryotic diversity were site-specific. For example, at the lowest elevation site, nematode communities contained a high proportion of fungal-feeding species and diversity of bacteria was lowest. At a high-salinity site, nematode density was highest, and overall, nematode density showed an unexpected, positive correlation to salinity. At the highest elevation site, nematode density and species richness were attenuated, despite relatively high moisture and organic matter content for the soils. Our results support emerging evidence for the lack of a relationship between productivity and the diversity of soil nematodes and prokaryotes.
Evolving and validating annotations in web-based collaborative environments through ontology matching

The research presented in this paper describes an automated approach for extracting concepts from annotated shared contents within a collaborative web environment, and matching them with domain ontologies. Feedback on the domain ontology suitability for the environment purposes is provided as a result of the automatic matching between the domain ontology and the free tags that users of the system employ. This approach will enable annotations and domain ontologies to evolve coherently with the real use of any social web environment. Experiments carried out on the Knowledge Practice Environment of the EU-funded project KP-Lab demonstrate the feasibility of our approach.
Of Smiles and Smirks: A Term Structure Perspective

Abstract An extensive empirical literature in finance has documented not only the presence of anomalies in the Black-Scholes model, but also the term structures of these anomalies (for instance, the behavior of the volatility smile or of unconditional returns at different maturities). Theoretical efforts in the literature at addressing these anomalies have largely focused on two extensions of the Black-Scholes model: introducing jumps into the return process, and allowing volatility to be stochastic. We employ commonly used versions of these two classes of models to examine the extent to which the models are theoretically capable of resolving the observed anomalies. We find that each model exhibits some term structure patterns that are fundamentally inconsistent with those observed in the data. As a consequence, neither class of models constitutes an adequate explanation of the empirical evidence, although stochastic volatility models fare somewhat better than jumps.
An extensible semantic catalogue for geospatial web services

Searching for web services is a challenging task due to the diversity of existing discovery tools. Varying standards for service descriptions require different tools to query their content. These standards exist for good reasons. Web services are used in different application environments and special solutions are required for their integration. We suggest an architecture for web service catalogues, which takes this diversity of standards into account. Its extensibility allows for a complete separation between service discovery and service description. Using ontologies for the storage of service descriptions enables the support of different description standards without loosing their specific advantages. The discussion and implementation focuses on geospatial web services. Due to the heterogeneity of spatially referenced data, different specifications exist for them, making the problem of different standards for service discovery and service description most evident here.
Content-aware Ranking for visual search

The ranking models of existing image/video search engines are generally based on associated text while the visual content is actually neglected. Imperfect search results frequently appear due to the mismatch between the textual features and the actual visual content. Visual reranking, in which visual information is applied to refine text based search results, has been proven to be effective. However, the improvement brought by visual reranking is limited, and the main reason is that the errors in the text-based results will propagate to the refinement stage. In this paper, we propose a Content-Aware Ranking model based on “learning to rank” framework, in which textual and visual information are simultaneously leveraged in the ranking learning process. We formulate the Content-Aware Ranking based on large margin structured output learning, by modeling the visual information into a regularization term. The direct optimization of the learning problem is nearly infeasible since the number of constraints is huge. The efficient cutting plane algorithm is adopted to learn the model by iteratively adding the most violated constraints. Extensive experimental results on a large-scale dataset collected from a commercial Web image search engine, as well as the TRECVID 2007 video search dataset, demonstrate that the proposed ranking model significantly outperforms the state-of-the-art ranking and reranking methods.
VizEval: An Experimental System for the Study of Program Visualization Quality

The VizEval Suite is an environment designed to support experimentation with and evaluation of program visualization attributes that affect the user's ability to grasp essential concepts. In this paper, we describe the VizEval Suite and an initial experiment conducted both as a test-bed of the VizEval Suite and to study how perceptual/cognitive characteristics of the visualization affect the users' understanding of the program visualization. VizEval is designed to simplify the creation and analysis of such studies. Our experimental results show that some perceptual/cognitive characteristics that help one task (e.g., detection of critical information) may harm another (e.g., localization of critical items), and vice versa. The VizEval software is available for download at http://www.cs. uga.edu/~eileen/VizEval/
MobiCom Poster Abstract : Interference-aware Fast Path Adaptation in Wireless Mesh Networks

Existing multihop wireless routing protocols are incapable of reacting quickly to transient degradation of link quality rendering them unsuitable for supporting real-time applications such as streaming/interactive voice and video. This limitation in the sensitivity of the routing protocols to link quality is difficult to overcome due to the following reasons. All link quality metrics used in routing, such as ETX [1, 2] require active probing. Too frequent probing results in high overhead and can interfere with the actual traffic. Further, a time window of 5 to 10 seconds is required to gather enough probe samples to allow reasonable confidence in the statistics and avoid load sensitivity. Additional latency is also incurred in propagating routing updates. We designed Deflect, a lightweight and opportunistic mechanism that works underneath the routing layer. Deflect enables fast local adaptation of end-toend routes in response to sudden drops in link delivery ratio or node failures. The design of Deflect achieves the following goals: a) zero message overhead mechanism for monitoring link quality at very short time scale; b) fast switching of traffic through a node in neighborhood of the poor link; c) transparency to endto-end routing protocol. We show that Deflect can react to link quality degradation within a few hundred milliseconds, compared to tens of seconds for an endto-end routing protocol.
Spatial phase behavior in SAR images

It is well known that a SAR image is composed of two types of information: amplitude and phase. Nevertheless, the information contained in the phase is hardly exploited on its own. Indeed, the number of processes at work and the scale difference between the image resolution and the wavelength induce, with regard to the phase, a quasi-random spatial behavior. However, our recent work shows that the phase of one image can be spatially correlated. First, we define an estimator for the spatial correlation of the phase, and study its behavior with real data. We assess the phase correlation according to the resolution and the type of surface. Then, we set down the theoretical bases of a statistical model of this behavior. We highlight the conditions required with regard to the resolution, the sampling rate, and the impulse response. We therefore identify the best kinds of surfaces, so that the phenomenon occurs. Hence, we simulate the phase correlation for different cases according to the phase model defined. We choose suitable parameters to the conditions of the real data and compare measurements and simulations. Finally, we propose possible applications related to the use of this new source of information.
Formation of overlapping coalitions for precedence-ordered task-execution among autonomous agents *

(;ell-satisfaction in multi-agent environments via coalition formation may be beneficial in cases where agents cannot perform goals by themselves or they do so inefficiently. Agent coalition forn|alkm typically requires that each agent must be a member of only Olle coalition. This may lead to wasted resources alld capabilities. Therefore, we. present algorithms that lead agents to the formation of overlapping t:oMition~, where each coalition is assigned a goal. The algorithms we present arc. appropriate for agents working as a Distributed l)rolflem Solving system in non-superadditive environments. Th(. y arc: any-time distributed Mgorithms with a low computational complexity and low ratio-bound.
A probabilistic analysis of a fixed partition policy for the inventory‐routing problem

We consider the Inventory‐Routing Problem (IRP) where n geographically dispersed retailers must be supplied by a central facility. The retailers experience demand for the product at a deterministic rate, and incur holding costs for keeping inventory. Distribution is performed by a fleet of capacitated vehicles. The objective is to minimize the average transportation and inventory costs per unit time over the infinite horizon. We focus on the set of Fixed Partition Policies (FPP). In an FPP, the retailers are partitioned into disjoint and collectively exhaustive sets. Each set of retailers is served independently of the others and at its optimal replenishment rate. Previous research has measured the effectiveness of an FPP solution relative to a lower bound over all policies. We propose an additional measure that is relative to the optimal FPP. In this paper we construct a polynomial‐time partitioning scheme that is shown to yield an FPP whose cost is asymptotically within 1.5% + ϵ of the cost of an optimal FPP, for arbitrary ϵ > 0. In addition, in some cases, our polynomial‐time scheme yields an FPP whose cost is asymptotically within 1.5% + ϵ of the minimal policy's cost (over all feasible policies). © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004
Evaluation of basic object manipulation modes for low-cost immersive Virtual Reality

Object manipulation is a fundamental task in several applications of 3D and Virtual Reality (VR) interactive applications, like scientific or medical visualization tools, simulators and games and the development of effective metaphors and tools for its practical implementation is extremely important for their success. In this paper we present the result of a usability test performed to compare different paradigms and implementations for atomic gesture effects (rotation and translation) in an immersive Virtual Reality (VR) setup. The setup is based on low cost devices, e.g. the Oculus DK2 for scene display and a Leap Motion controller for gesture interaction. Four different manipulation modalities using different combinations of the translation and rotation paradigms have been compared both in terms of task completion efficiency and user acceptance. Experimental results can be used to derive useful suggestions for effective interaction design for VR applications based on similar low cost hardware devices.
Cognitive self-consciousness–a predictor of increased anxiety following first-time diagnosis of age-related hearing loss

This study tested prospective models of anxiety and depression following a first time diagnosis of age-related hearing loss, also known as presbycusis, which is one of the most common and disabling health problems in the world. The predictor of interest was cognitive self-consciousness (CSC; Cartwright-Hatton & Wells (1997). Beliefs about worry and intrusions: The Meta-Cognitions Questionnaire and its correlates. Journal of Anxiety Disorders, 11, 276–279. ), or the tendency to closely attend to and monitor the content and process of one's own thoughts. Sixty-seven older adults were assessed at a university-based audiology clinic at three timepoints: at the time of diagnosis (T1), six (T2), and 12 months later (T3). Measures of anxiety, depression, and CSC were collected. It was hypothesized that a subset of older adults with hearing loss would report increased CSC at T2. Additionally, the interaction of CSC and anxiety and depression symptoms at T2 was expected to predict significant variance in measures of anxiety and depression at T3, even after baseline levels of distress were controlled in regression models. Finally, it was hypothesized that consistent use of a hearing aid by T3 would act as a palliative to reduce distress in response to hearing loss at T3. Results were partially consistent with hypotheses and point to a new direction in preventing anxiety and depression following a first time diagnosis of presbycusis.
Performance evaluation of a generalized energy efficient time based protocol under different applications

Many Wireless Sensor Network (WSN) protocols show different performance under different applications. Therefore, a WSN protocol designer must be aware of the intended applications. In this paper, we study the effect of the inter arrival time between events on the performance of some WSN routing protocols. We observe that the investigated protocols show different performance under different applications. We compare the performance of the investigated protocols in terms of delay, network lifetime, throughput and percentage of detected events.
Clustering Subtrajectories of Moving Objects Based on a Distance Metric with Multi-dimensional Weights

Mining spatio-temporal data has recently gained great interest due to the integration of wireless communications and positioning technologies. Although clustering spatio-temporal data as a popular mining task has been well studied, the problem properly defining the distance between the objects to make the clustering results suit the application needs still remain largely unsolved. In this paper, for the purpose for trajectory data processing, we propose an improved trajectory segmentation algorithm and a new object distance metric that considers multiple dimensions on the characteristics of moving object's subtrajectories. Then, we use the new distance metric in a varient of the existing fuzzy clustering algorithm to improve the quality of clustering results. The experimental evaluation over real world trajectory data record with GPS demonstrates the efficiency and effectiveness of our approach.