Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational Distinguishability between Quantum States: Random Coset States vs. Maximally Mixed States over the Symmetric Groups

We introduce a new underlying problem for computational cryptographic schemes secure against quantum adversaries. The problem is a distinction problem between quantum states which is a natural generalization of distinction problems between probability distributions, which are commonly used in computational cryptography. Specifically speaking, our problem QSCDff is defined as a quantum state computational distinguishability problem between random coset states with a hidden permutation and a maximally mixed state (uniform distribution) over the symmetric group. A similar problem to ours appears in the context of the hidden subgroup problem on the symmetric group in the research of quantum computation and is regarded as a hard problem. In this paper, we show that (i) QSCDff has the trapdoor property; (ii) the average-case complexity of QSCDff completely coincides with its worst-case complexity; (iii) the computational complexity of QSCDff is lower-bounded by the worst-case hardness of the graph automorphism problem. These properties enable us to construct cryptographic systems. Actually, we show a cryptographic application based on the hardness of QSCDff .
Noise removal from electrocardiogram signal employing an artificial neural network in wavelet domain

Electrocardiogram (ECG) signal involves significant information about heart state and is one of the common tools for cardiologist in diagnosis of heart failures. Using adaptive filters for filtering this signal, which inherently has nonstationary features, is used as one of the known methods. In this paper, the wavelet transform and also a neural network (NN) based on adaptive filters are used for removal of undesirable noise from the ECG signal. In this context, in training stage, network weights related to each wavelet sub band is obtained by using the steepest descent algorithm, and filter coefficients for removal of noise from ECG signal are calculated. Results obtained from employing this algorithm on the MIT-BIH database and simulated ECG signal are indicative of improved performance of noise removal in comparison with other methods.
Mobile positioning for traffic state acquisition

The topics presented in this article are related to the project ‘Data Optimisation for integrated Telematics’ (Do-iT) granted by the German Ministry of Economics and Technology. Within this project the current traffic state will be derived by use of network-based data from numerous mobile phones of anonymous drivers. With respect to traditional methods such as local loop data and GPS-based floating car data (FCD), this method (floating phone data, FPD) will take advantage of area-wide availability without additional infrastructure and costs. The timing advance (TA) value and signal strength measurements to the serving antenna are available in the GSM network, as well as signal strength measurements to up to six neighbouring antennas. The TA value is used to determine the distance from the serving antenna to the mobile phone. From this a search area is generated. The position of the mobile phone is determined by use of the signal strengths, which are matched to a signal strength map. These positions are referenced to the digital road network. Positioning is used to enable a reliable traffic prediction as a base for modern traffic control and management. Within this article a brief overview of the project is given, with the main focus being on the positioning methods. Different approaches based on least squares adjustment and Kalman filtering are presented and first results from data measured in the vicinity of the city of Stuttgart are presented.
Studying Multi-threaded Behavior with TSViz

Modern high-performing systems make extensive use of multiple CPU cores. These multi-threaded systems are complex to design, build, and understand. Debugging performance of these multi-threaded systems is especially challenging. This requires the developer to understand the relative execution of dozens of threads and their inter-dependencies, including data-sharing and synchronization behaviors. We describe TSViz, a visualization tool to help developers study and understand the activity of complex multi-threaded systems. TSviz depicts the partial order of concurrent events in a time-space diagram, and simultaneously scales this diagram according to the physical clock timestamps that tag each event. A developer can then interact with the visualization in several ways, for example by searching for events of interest, studying the distribution of critical sections across threads and zooming the diagram in and out. We overview TSviz design and describe our experience with using it to study a high-performance multi-threaded key-value store based on MongoDB. A video demo of TSViz is online: https://youtu.be/LpuiOZ3PJCk.
Effect of rest interval length on the volume completed during upper body resistance exercise.

The purpose of the current study was to compare the workout volume (sets x resistance x repetitions per set) completed during two upper body resistance exercise sessions that incorporated 1 minute versus 3 minute rest intervals between sets and exercises. Twelve trained men completed two experimental sessions that consisted of 5 upper body exercises (i.e. barbell bench press, incline barbell bench press, pec deck flye, barbell lying triceps extension, triceps pushdown) performed for three sets with an 8-RM load. The two experimental sessions differed only in the length of the rest interval between sets and exercises; one session with a 1-minute and the other session with a 3-minute rest interval. The results demonstrated that for each exercise, significantly greater workout volume was completed when resting 3 minutes between sets and exercises (p < 0.05). These results indicate that during a resistance exercise session, if sufficient time is available, resting 3 minutes between sets and exercises allows greater workout volume for the upper body exercises examined. Key pointsThe length of the rest interval between sets is an important variable when designing a resistance exercise program and may vary depending on the characteristic being emphasized (i.e. maximal strength, hypertrophy, localized muscular endurance, power). Although acknowledged, this variable is rarely monitored precisely in field settings.Previous studies that examined rest interval lengths from 1 to 5 minutes between sets for single exercises demonstrated significant differences in repetition performance and the exercise volume completed.There is a need for further research to compare the workout volume (sets x resistance x repetitions per set) completed over an entire resistance exercise session with different rest intervals between sets.The results of the current study indicate that during a resistance exercise session, if sufficient time is available, resting 3 minutes between sets and exercises allows greater workout volume for the upper body exercises examined.
Resultant Based Methods Computing the Greatest Common Divisor of Several Polynomials

In this paper we develop two resultant based methods for the computation of the greatest common divisor (GCD) of many polynomials. Let S be the resultant Sylvester's matrix of the polynomials. The application of classical LU and QR factorization to S for the computation of its GCD has an inappropriate complexity of order O(n4). We modified matrix S to S* such that the rows with non-zero elements under the main diagonal, at every column, are gathered together. We constructed modified versions of the LU and QR procedures which lead to the computation of the GCD of S* in O(n3) floating point operations. Both methods are tested for several sets of polynomials and tables summarizing all the achieved results are given
VW Hyi: optical spectroscopy and Doppler tomography

We present high-quality optical spectroscopy of the SU UMa-subtype dwarf nova, VW Hyi taken while the system was in quiescence. An S-wave is executed by the emission cores of the hydrogen Balmer lines and by the emission lines of He i, Ca ii, Fe ii and He ii. Using Doppler tomography, we show it originates in the accretion stream–disc impact region. The He ii emission is strongly phase-dependent, suggesting it originates exclusively within a hot cavity at the initial impact. We map the ionization structure of the stream–disc interaction region. One possible interpretation of this is that the Balmer hotspot lies downstream of the He ii hotspot in the outer accretion disc, with the He i and Ca ii hotspots at intermediate locations between the two. This suggests that Balmer emission is suppressed until material has cooled somewhat downstream of the impact site and is able to recombine. We favour a phase offset of 0.15 ± 0.04 between the photometric ephemeris and inferior conjunction of the mass donor. The white dwarf contributes significantly to the optical continuum, with broad Balmer absorption and narrow Mg ii λ4481 absorption clearly apparent. This latter feature yields the gravitational redshift: vgrav = 38 ± 21 km s −1, so M1 = 0.71+0.18−0.26 M. This implies M2 = 0.11 ± 0.03 M and hence the donor is not a brown dwarf. A prominent Balmer jump is also observed. We note that the previously accepted system parameters for both VW Hyi and WX Hyi incorporate an algebraic error, and we provide a recalculated M1(q) plane for WX Hyi.
Trust-aware resource allocation in a cognitive radio system

Cognitive radio (CR) is a concept which can be used to improve the utilization of scarce radio spectrum resources. A reliable strategy for the detection of unused spectrum bands is essential in a practical implementation of CR systems. It is widely accepted that in a real-world environment, cooperative spectrum sensing involving many secondary users (SUs) scattered over a wide geographical area can greatly improve sensing accuracy. However, some SUs may misbehave, i.e. provide false sensing information, in an attempt to maximize their own utility gains. Such selfish behaviour, if unchecked, can severely impact the operation of the CR system. In this paper, we propose a novel trust-aware resource allocation scheme in a centralized cognitive radio network with a system-level trust model in which trustworthiness is used as social capital to gain system resources. The scheme can detect misbehaving SUs and filter out the malicious attacks while attempting to maximize the total bit rate of SUs. Computer simulations are used to illustrate the efficiency and robustness of the proposed scheme under various attack scenarios.
Learning to associate relevant photos to georeferenced textual documents

The association of illustrative photos to textual contents is a challenging cross-media retrieval problem with many practical applications. We have, for instance, that the association of photos to specific parts of travelogues, i.e. textual descriptions for travel experiences, may lead to a better usage of these documents. Despite the huge number of high quality photos in websites like Flickr, these photos are currently not being properly explored in cross-media retrieval tasks.
Life-Cycle Dynamics in Industrial Sectors. The Role of Banking Market Structure

This paper analyzes the role of bank competition on the life-cycle dynamics of non-financial industries. Using multi-dimensional data sets, which contain information on job creation and destruction for establishments in U.S. manufacturing sectors operating in different geographical regions and over time, I find evidence that bank competition accelerates the expansion of start-ups and helps them to thrive while young. Once these establishments are mature, however, less competitive banking markets are more propitious. Specifically, mature establishments expand at higher rates and exit the industry at a slower pace in less competitive banking markets.
A depth optimization method for 2D-to-3D conversion based on RGB-D images

2D-to-3D conversion is one of the key technologies in stereoscopic video. Its visual qualities depend on the qualities of depth image estimation and virtual viewpoint image rendering. Although there are many methods to get depth information, the depth information still has some errors because of calculation errors and noises, which influences the visual qualities of the generated virtual viewpoint image. This paper proposes a depth image optimization method to improve the qualities of virtual viewpoint image. It utilizes the surface normal information to segment objects and obtain the smooth factor of depth image. The experimental results demonstrate that our method can denoise and smooth the original depth map effectively.
A path selection algorithm for timing analysis

Existing algorithms for timing analysis have difficulties when dealing with large designs. A novel algorithm for timing analysis is proposed that enumerates all the paths with delay greater than a given threshold. The execution time of the proposed algorithm is proportional to the number of paths generated, so it is suitable for large designs. <<ETX>>
The design of employment information recommendation system

With the increase of the number of college graduates, the country needs to do much in promoting their employment. Meanwhile as the rapid development of Internet lead to explosive growth of information, the real value needs to be effectively and immediately selected to benefit both employers and employees. This paper aims to propose two content based algorithms, one starting with cold boot and the other combining with collaborative filtering, to process the employment information for graduates through analyzing the features of concerned information and build a linkage to help them find the matches more efficiently. The paper also devises an employment information recommendation system in which the users register, log in and have access to the jobs and talents database and recommendation system. The function, reliability, operating efficiency and compatibility, all included will be tested by the third party. In addition, some particular functions can be extended to update the database automatically. Users can also add, modify, delete and search the data manually to meet the users' need.
Genetics of Bark Beetles and Associated Microorganisms : Third Workshop

To enable the resolution of deep phylogenetic divergence in Scolytinae and closely related weevils, several new molecular markers were screened for their phylogenetic potential. The nuclear protein encoding genes, CAD and Arginine Kinase, were particularly promising and will be added to future phylogenetic studies in combination with 28S, COI, and Elongation Factor 1α. The combined analysis of multiple molecular markers and wide taxon sampling is expected to resolve many previously unresolved nodes in scolytine phylogeny, but a completely resolved topology seems dependent on the inclusion of a large number of morphological characters. A well founded phylogeny will provide a powerful framework for testing evolutionary hypotheses on habitat selection and reproductive biology.
Coexistence in neutral theories: interplay of criticality and mild local preferences

Neutral theories have played a crucial and revolutionary role in fields such as population genetics and biogeography. These theories are critical by definition, in the sense that the overall growth rate of each single allele/species/type vanishes. Thus each species in a neutral model sits at the edge between invasion and extinction, allowing for the coexistence of symmetric/neutral types. However, in finite systems, mono-dominated states are ineluctably reached in relatively short times owing to demographic fluctuations, thus leaving us with an unsatisfactory framework to rationalize empirically-observed long-term coexistence. Here, we scrutinize the effect of heterogeneity in quasi-neutral theories, in which there can be a local mild preference for some of the competing species at some sites, even if the overall species symmetry is maintained. As we show here, mild biases at a small fraction of locations suffice to induce overall robust and durable species coexistence, even in regions arbitrarily far apart from the biased locations. This result stems from the long-range nature of the underlying critical bulk dynamics and has a number of implications, for example, in conservation ecology as it suggests that constructing local specific ‘sanctuaries’ for different competing species can result in global enhancement of biodiversity, even in regions arbitrarily distant from the protected refuges.
A fast pipeline for textured object recognition in clutter using an RGB-D sensor

This paper presents a modular algorithm pipeline for recognizing textured household objects in cluttered environment and estimating 6 DOF poses using an RGB-D sensor. The method draws from recent advances in this area and introduces a number of innovations that enable improved performances and faster operational speed in comparison with the state-of-the-art. The pipeline consists of (i) support plane subtraction (ii) SIFT feature extraction and approximate nearest neighbour based matching (iii) feature clustering using 3D Eculidean distances (iv) SVD based pose estimation in combination with a outlier rejection strategy named SORSAC (Spatially ORdered RAndom Consensus) and (v) a pose combination and refinement step to combine overlapping identical instances and to refine the pose estimation result by removing incorrect hypothesis. Quantitative comparisons with the MOPED [1] system on self-constructed dataset are presented to demonstrate the effectiveness of the pipeline.
Cross-lingual document similarity

In this paper we investigated how to compute similarities between documents written in different languages based on a weekly aligned multi-lingual collection of documents. Computing the cross-lingual similarities is based on an aligned set of basis vectors obtained by either latent semantic indexing or the k-means algorithm on an aligned multi-lingual corpus. We evaluated the methods on two data sets: Wikipedia and European Parliament Proceedings Parallel Corpus.
Cache Accurate Time Skewing in Iterative Stencil Computations

We present a time skewing algorithm that breaks the memory wall for certain iterative stencil computations. A stencil computation, even with constant weights, is a completely memory-bound algorithm. For example, for a large 3D domain of $500^3$ doubles and 100 iterations on a quad-core Xeon X5482 3.2GHz system, a hand-vectorized and parallelized naive 7-point stencil implementation achieves only 1.4 GFLOPS because the system memory bandwidth limits the performance. Although many efforts have been undertaken to improve the performance of such nested loops, for large data sets they still lag far behind synthetic benchmark performance. The state-of-art automatic locality optimizer PluTo achieves 3.7 GFLOPS for the above stencil, whereas a parallel benchmark executing the inner stencil computation directly on registers performs at 25.1 GFLOPS. In comparison, our algorithm achieves 13.0 GFLOPS (52\% of the stencil peak benchmark). We present results for 2D and 3D domains in double precision including problems with gigabyte large data sets. The results are compared against hand-optimized naive schemes, PluTo, the stencil peak benchmark and results from literature. For constant stencils of slope one we break the dependence on the low system bandwidth and achieve at least 50\% of the stencil peak, thus performing within a factor two of an ideal system with infinite bandwidth (the benchmark runs on registers without memory access). For large stencils and banded matrices the additional data transfers let the limitations of the system bandwidth come into play again, however, our algorithm still gains a large improvement over the other schemes.
Interleaving ontology-based reasoning and Natural Language Processing for character identification in folktales

We propose a system for identifying literary characters from folktales. The process of extracting characters from free texts is guided by an ontology that encodes the knowledge of the folktale domain. We present how the ontology works with Natural Language Processing in GATE to increase the accuracy of character recognition. We validated the solution against various folktales.
Using pattern construction and analysis in an exploratory learning environment for understanding mathematical generalisation: The potential for intelligent support

Few systems exist that support learners explicitly in the pro- cess of learning mathematical generalisation. This paper presents the eX- presser, part of a new system that seeks to address this issue by providing the user with a microworld for the construction and analysis of general patterns. The design includes the provision of sophisticated intelligent support that assists learners and teachers throughout their various in- teractions with the system. Given the open and exploratory nature of the environment and the resultant freedom it affords, integrating such intelligent support poses a significant research challenge. This paper de- scribes the system in detail and discusses a variety of ways in which we intend to meet our research goals for providing intelligent support.
Derived classes as a basis for views in UML/OCL data models

UML is the de facto standard language for analysis and design in object-oriented frameworks. Information systems, and in particular information systems based on databases and their applications, rely heavily on sound principles of analysis and design. Many present-day database applications employ object-oriented principles in the phases of analysis and design due to the advantages of expressiveness and clarity of such languages as UML. Database specifications often involve specifications of constraints, and the Object Constraint Language (OCL) - as part of UML - can aid in the unambiguous modelling of database constraints. One of the central notions in database modelling and in constraint specifications is the notion of a database view. A database view closely corresponds to the notion of derived class in UML. This paper will show how the notion of a derived class in UML can be given a precise semantics in terms of OCL. We will then demonstrate that the notion of a relational database view can be correctly expressed as a derived class in UML/OCL. A central part of our investigation concerns the generality of our manner of representing relational views in OCL. An important problem that we address in this respect is the representation of product spaces and relational joins. Joins are often essential in view definitions, and we shall demonstrate how we can express Cartesian products and joins within the current framework of UML/OCL language by employing the notions of derived class. As a consequence, OCL will be shown to be equipped with the full expressive power of the relational algebra, offering support for the claim that OCL can be useful as a general query language within the framework of the UML/OCL data model.
Detection of Action Potentials In Vitro by Changes in Refractive Index

The detection of individual action potentials in nerve cells via intrinsic optical signals could open a new modality for the analysis of cellular properties in spatially extended cells and emergent properties in networks of neurons. Here we review the experimental evidence for the detection of changes in intrinsic optical properties, i.e., changes in optical refractive index, that covary with changes in the transmembrane voltage.