Miracle-dz/UniFAR-FTUs huggingface dataset:
A method to determine the parameters of black holes in AGNs and galactic X-ray sources with periodic modulation of variability

We propose a simple and unambiguous way to deduce the parameters of black holes which may reside in AGNs and some types of X-ray binaries. The black-hole mass and angular momentum are determined in physical units. The method is applicable to the sources with periodic components of variability, provided one can assume the following: (i) Variability is due to a star or a stellar-mass compact object orbiting the central black hole and passing periodically through an equatorial accretion disk (variability time-scale is given by the orbital period). (ii) The star orbits almost freely, deviation of its trajectory due to passages through the disk being very weak (secular); the effect of the star on the disk, on the other hand, is strong enough to yield observable photometric and spectroscopic features. (iii) The gravitational field within the nucleus is that of the (Kerr) black hole, the star and the disk contribute negligibly.
The Essence of AspectJ [ Functional Pearl ]

In the construction of a large software system, it is inevitable that some aspects of program behavior will cut across the structure of the code. The changes that are needed to support a new feature, for example, may be spread across several different points in the original program, making them harder to maintain and harder to reuse. The designers of “aspect-oriented” programming languages aim to tackle these problems by introducing new language mechanisms to capture cross-cutting concerns. Their hope is that this will allow different aspects of a program to be captured as independent entities that can be woven together automatically to produce a complete program. In this paper, we focus on AspectJ, an aspect-oriented extension of Java that has been designed and implemented by a team at Xerox PARC to support an empirical assessment of aspect-oriented programming. The development of AspectJ has been driven largely by pragmatic concerns. Here, we provide a complimentary perspective by using interpreters, written in Haskell, to present a formal semantics for a simple aspect-oriented programming language, and so to distill the essence of AspectJ. This paper provides a firm semantic foundation for the design of aspect-oriented programming languages. It illustrates the flexibility that can be obtained by writing interpreters in a monadic style, but also challenges us to contemplate how the ideas of aspect-oriented programming might be applied to the design of future functional languages.
Tractable model for heterogeneous cellular networks with directional antennas

Heterogeneous cellular networks consisting of microcell, picocell, femtocell, distributed antennas and relays codeployed in space and frequency with carefully planned tower-mounted base stations, increase the complexity of the cellular network structure, which makes a tractable analysis model difficult to obtain. In this paper, we extend the original tractable model for downlink heterogeneous cellular network to the scenario with directional antennas, from which the coverage probability (or equivalently outage probability) for a randomly located mobile user in this network can be derived. By using this tractable model, the impact of implementing directional antenna for certain heterogeneous tiers can be demonstrated and utilized as a deployment guideline.
Geometric properties of Julia sets of the composition of polynomials of the form z2 + cn

For a sequence (cn) of complex numbers we consider the quadratic polynomials fcn(z) := z 2 + cn and the sequence (Fn) of iterates Fn := fcn ◦ · · · ◦ fc1 . The Fatou set F(cn) is by definition the set of all z ∈ Ĉ such that (Fn) is normal in some neighbourhood of z, while the complement of F(cn) is called the Julia set J(cn). The aim of this article is to study geometric properties, Lebesgue measure and Hausdorff dimension of the Julia set J(cn) provided that the sequence (cn) is bounded.
Matching Contours of Folded Garments to Unfolded Templates using Robust Shape Analysis Techniques

This work presents a novel approach to shape matching of folded garments to unfolded templates, aiming to facilitate unfolding by robotic manipulators. The proposed method incorporates robust shape analysis techniques, estimating point correspondences between contours of folded garments and unfolded templates. The analysis results are also used for estimating the location of the folding axis on the templates and discriminating between different types of garments. The method has been experimentally evaluated using both synthetic and real datasets of folded garments and the produced results indicate the usefulness of the proposed approach.
Experimental assessment of manual versus tool-based maintenance of GUI-directed test scripts

Since manual black-box testing of GUI-based APplications (GAPs) is tedious and laborious, test engineers create test scripts to automate the testing process. These test scripts interact with GAPs by performing actions on their GUI objects. As GAPs evolve, testers should fix their corresponding test scripts so that they can reuse them to test successive releases of GAPs. Currently, there are two main modes of maintaining test scripts: tool-based and manual. In practice, there is no consensus what approach testers should use to maintain test scripts. Test managers make their decisions ad hoc, based on their personal experience and perceived benefits of the tool-based approach versus the manual. In this paper we describe a case study with forty five professional programmers and test engineers to experimentally assess the tool-based approach for maintaining GUI-directed test scripts versus the manual approach. Based on the results of our case study and considering the high cost of the programmers' time and the lower cost of the time of test engineers, and considering that programmers often modify GAP objects in the process of developing software we recommend organizations to supply programmers with testing tools that enable them to fix test scripts faster so that these scripts can unit test software. The other side of our recommendation is that experienced test engineers are likely to be as productive with the manual approach as with the tool-based approach, and we consequently recommend that organizations do not need to provide each tester with an expensive tool license to fix test scripts.
Evolving Neural Network with Dynamic Time Warping and Piecewise Linear Representation System for Stock Trading Decision Making

Stock turning points detection is a very interesting subject arising in numerous financial and economic planning problems. In this paper, Evolving Neural Network model with Dynamic Time warping Piecewise Linear Representation system for stock turning points detection is presented. The piecewise linear representation method is able to generate numerous stocks turning points from the historic data base, then Evolving Neural Network model will be applied to train the pattern and retrieve similar stock price patterns from historic data for training the system. These turning points represent short-term trading signals for selling or buying stocks from the market. it is applied to forecast the future turning points from the set of test data. Experimental results demonstrate that the hybrid system integrating DPLR and evolving neural networks can make a significant and constant amount of profit when compared with other approaches using stock data.
Verifying Simulink diagrams via a Hybrid Hoare Logic Prover

Simulink is an industrial de-facto standard for building executable models of embedded systems and their environments, facilitating validation by simulation. Due to the inherent incompleteness of this form of system validation, complementing simulation by formal verification would be desirable. A prerequisite for such an approach is a formal semantics of Simulink's graphical models. In this paper, we show how to encode Simulink diagrams into Hybrid CSP (HCSP), a formal modelling language encoding hybrid system dynamics by means of an extension of CSP. The translation from Simulink to HCSP is fully automatic. We furthermore discuss how to utilize a Hybrid Hoare Logic Prover to verify the translated HCSP models. We demonstrate our approach on a combined scenario originating from the Chinese High-speed Train Control System at Level 3 (CTCS-3).
DESIGNING THE HOUSE OF SECURITY : STAKEHOLDER PERCEPTIONS OF SECURITY ASSESSMENT AND IMPORTANCE EXECUTIVE SUMMARY

In this paper we introduce a methodology for analyzing differences regarding security perceptions within and between stakeholders, and the elements which affect these perceptions. Following a comprehensive discussion of theories pertaining to security, we design the “House of Security”, a security assessment model that provides the basic framework for considering eight different constructs of security: Vulnerability, Accessibility, Confidentiality, Technology Resources for Security, Financial Resources for Security, Business Strategy for Security, Security Policy and Procedures, and Security Culture. We designed and performed a survey to perform a gap analysis to uncover differences (1) between the different constructs and aspects of security, (2) between different enterprise stakeholder roles, and (3) between different organizations. This paper describes the development of the security constructs, the testing of the survey instruments for construct reliability and validity, and details some of the preliminary findings. Specific focus is on the evaluation of the quality of the survey instrument by measuring the statistically significance of the questions and the constructs, the reliability of the constructs (by computing Cronbach Alphas) and the content, convergent and discriminant validity of the constructs.
Non-verbal communications in mobile text chat: emotion-enhanced mobile chat

Great part of human communication is carried out non-verbally. All this information is lost in mobile text messaging. This work describes an attempt to augment text chatting in mobile phones by adding automatically detected facial expression reactions, to conversations. These expressions are detected using known image processing techniques. Known related work, concerning the investigation of non-verbal communication through text messaging are considered and distinguished from the present solution. The conception and implementation of a mobile phone application with the debated feature is described and user studies are narrated. Finally, context of application, conclusions and future work are also discussed.
Interval type-2 fuzzy logic gravitational search algorithm for the optimization of modular neural networks in echocardiogram recognition

Research in echocardiogram imaging it's very important because it allows assessing both anatomy and cardiac function, help diagnose various diseases. In this paper to find the optimal architecture of a MNN, where means finding the number of layers and nodes. In this case the Type-2 fuzzy logic gravitational search algorithm is used for optimizing the MNN for pattern recognition in echocardiogram imaging.
On the power and limits of evolutionary conservation—unraveling bacterial gene regulatory networks

The National Center for Biotechnology Information (NCBI) recently announced ‘1000 prokaryotic genomes are now completed and available in the Genome database’. The increasing trend will provide us with thousands of sequenced microbial organisms over the next years. However, this is only the first step in understanding how cells survive, reproduce and adapt their behavior while being exposed to changing environmental conditions. One major control mechanism is transcriptional gene regulation. Here, striking is the direct juxtaposition of the handful of bacterial model organisms to the 1000 prokaryotic genomes. Next-generation sequencing technologies will further widen this gap drastically. However, several computational approaches have proven to be helpful. The main idea is to use the known transcriptional regulatory network of reference organisms as template in order to unravel evolutionarily conserved gene regulations in newly sequenced species. This transfer essentially depends on the reliable identification of several types of conserved DNA sequences. We decompose this problem into three computational processes, review the state of the art and illustrate future perspectives.
The Risk-Need-Responsivity Model Revisited: Using Biosocial Criminology to Enhance Offender Rehabilitation

During the past four decades, researchers and practitioners working in corrections have shifted from a “nothing works” to a “what works” orientation. Emphasizing the importance of adopting evidence-based interventions, Andrews and Bonta have argued that efforts to rehabilitate offenders should adhere to a number of specified principles of effective intervention, three of which—risk, need, and responsivity—are considered the most critical. These principles were derived from Andrews and Bonta’s theory of the psychology of criminal conduct, which underscores the necessity to link correctional practice to empirically defensible theories of offending. The vast majority of research has provided evidence of the effectiveness of the risk-need-responsivity model; however, far less attention has been given to expanding its theoretical foundation. Given the wealth of evidence supporting biosocial explanations of criminal behavior, we consider potential avenues for enhancing the risk-need-responsivity model through the integration of key findings from biosocial research.
A capacity-based codebook design method for sparse code multiple access systems

Sparse code multiple access (SCMA) is a novel non-orthogonal multiple access scheme, which exploits a multidimensional constellation based on the non-orthogonal spreading technique. The SCMA multi-user codebook design is the bottleneck of system performance and there is no design guideline from the perspective of capacity. In this paper, a novel SCMA codebook design scheme is proposed to maximize the sum rate, where we transfer the design of multi-dimensional constellation sets to the optimizing of series of 1-dimensional complex codewords. Specifically, a basic M-order pulse-amplitude modulation (PAM) is optimized and then the angles of rotation between the input 1-dimensional constellation and the basic M-PAM constellation can be obtained within a feasible calculation complexity to improve the sum-rate. Finally, the series of 1-dimensional complex codewords are combined to construct multi-dimensional codebooks based on Latin square criterion. Numerical results illustrate that the proposed codebook outperforms the existing codebook by 1.3 dB over AWGN channel and 1.1 dB over Rayleigh channel in terms of bit error rate (BER) performance.
Prediction interval estimation for wind farm power generation forecasts using support vector machines

Accurate forecasting of wind power generation is quite an important as well as challenging task for the system operators and market participants due to its high uncertainty. It is essential to quantify uncertainties associated with wind power generation forecasts for their efficient application in optimal management of wind farms and integration into power systems. Prediction intervals (PIs) are well known statistical tools which are used to quantify the uncertainty related to forecasts by estimating the ranges of the future target variables. This paper investigates the application of a novel support vector machine based methodology to directly estimate the lower and upper bounds of the PIs without expensive computational burden and inaccurate assumptions about the distribution of the data. The efficiency of the method for uncertainty quantification is examined using monthly data from a wind farm in Australia. PIs for short term application are generated with a confidence level of 90%. Experimental results confirm the ability of the method in constructing reliable PIs without resorting to complex computational methods.
Single Source -- All Sinks Max Flows in Planar Digraphs

Let G = (V, E) be a planar n-vertex digraph. Consider the problem of computing max st-flow values in G from a fixed source s to all sinks t ϵ V \ {s}. We show how to solve this problem in near-linear O(n log3 n) time. Previously, nothing better was known than running a single-source singlesink max How algorithm n-1 times, giving a total time bound of O(n2 log n) with the algorithm of Borradaile and Klein. An important implication is that all-pairs max st-How values in G can be computed in near-quadratic time. This is close to optimal as the output size is 8(n2). We give a quadratic lower bound on the number of distinct max How values and an Ω(n3) lower bound for the total size of all min cut-sets. This distinguishes the problem from the undirected case where the number of distinct max How values is O(n). Previous to our result, no algorithm which could solve the all-pairs max How values problem faster than the time of 8(n2) max-How computations for every planar digraph was known. This result is accompanied with a data structure that reports min cut-sets. For fixed s and all t, after O(n1.5 log2 n) preprocessing time, it can report the set of arcs C crossing a min st-cut in O(|C|) time.
Truthful germs are contagious: a local to global characterization of truthfulness

We study the question of how to easily recognize whether a social choice function f from an abstract type space to a set of outcomes is truthful, i.e. implementable by a truthful mechanism. In particular, if the restriction of f to every "simple" subset of the type space is truthful, does it imply that f is truthful? Saks and Yu proved one such theorem: when the set of outcomes is finite and the type space is convex, a function f is truthful if its restriction to every 2-element subset of the type space is truthful, a condition called weak monotonicity. This characterization fails for infinite outcome sets. We provide a local-to-global characterization theorem for any set of outcomes (including infinite sets) and any convex space of types (including infinite-dimensional ones): a function f is truthful if its restriction to every sufficiently small 2-D neighborhood about each point is truthful. More precisely, f is truthful if and only if it satisfies local weak monotonicity and is vortex-free, meaning that the loop integral of f over every sufficiently small triangle vanishes. Our results apply equally well to multiple solution concepts, including dominant strategies, Nash and Bayes-Nash equilibrium, and to both deterministic and randomized mechanisms. When the type space is not convex, we show that f is truthful if and only if it extends to a truthful function on the convex hull of the original type space. We use our characterization theorem to give a simple alternate derivation of the Saks-Yu theorem. Generalizing this, we give a sufficient condition for constructing a truthful function by "stitching together" truthful subfunctions on different subsets of the domain.
Models of Quantum Algorithms in Sets and Relations

We construct abstract models of blackbox quantum algorithms using a model of quantum computation in sets and relations, a setting that is usually considered for nondeterministic classical computation. This alternative model of quantum computation (QCRel), though unphysical, nevertheless faithfully models its computational structure. Our main results are models of the Deutsch-Jozsa, single-shot Grovers, and GroupHomID algorithms in QCRel. These results provide new tools to analyze the semantics of quantum computation and improve our understanding of the relationship between computational speedups and the structure of physical theories. They also exemplify a method of extending physical/computational intuition into new mathematical settings.
Variable density compressed image sampling

Compressed sensing (CS) provides an efficient way to acquire and reconstruct natural images from a reduced number of linear projection measurements at sub-Nyquist sampling rates. A key to the success of CS is the design of the measurement ensemble. This paper addresses the design of a novel variable density sampling strategy, where the “a priori” information about the statistical distributions that natural images exhibit in the wavelet domain is exploited. Compared to the current sampling schemes for compressed image sampling, the proposed variable density sampling has the following advantages: 1) The number of necessary measurements for image reconstruction is reduced; 2) The proposed sampling approach can be applied to several transform domains leading to simple implementations. In particular, the proposed method is applied to the compressed sampling in the 2D ordered discrete Hadamard transform (DHT) domain for spatial domain imaging. Furthermore, to evaluate the incoherence of different sampling schemes, a new metric that incorporates the “a priori” information is also introduced. Extensive simulations show the effectiveness of the proposed sampling methods.
The Impact of Social Websites over Jordanian Students’ Intentions of Active political Participation: An Application of Theory of Planned Behavior

Appreciating the massive popularity and application of social websites worldwide, the purpose of this paper was to explore the impact of such websites over young Jordanians’ intentions of active political participation. To that end, the paper developed a model based on Ajzen’s (1991) Theory of Planned Behavior. Further, quantitative data was collected through a survey of 461 BA students at one Jordanian university. Empirical findings underlined that respondents’ use of social websites had a direct impact over their exposure to online political content. Further, exposure to such content had a direct impact over respondents’ both “attitudes towards active political participation” and “perceived behavioral control”. While “subjective norms” had also a strong significant impact over respondents’ “attitudes towards active political participation” and “perceived behavioral control”, both constructs had a direct impact over respondents’ “intentions of active political participation”. Upon its findings, the paper draws some conclusions, introduces certain recommendations, and suggests further avenues for future research.
Improved Automatic Keyphrase Extraction by Using Semantic Information

Keyphrases provide semantic metadata producing an overview of the content of a document, they are used in many text-mining applications. This paper proposes a new method that improves automatic keyphrase extraction by using semantic information of candidate keyphrases. Our method is realized in two stages. In selecting candidates stage, after extraction of all phrases from document, a word sense disambiguation method is used to get senses of phrases, then term conflation is performed by using case folding, stemming, and semantic relatedness between candidates. In filtering stage, four features are used to compute for each candidate: the TFxIDF measure describing the specificity of a phrase, first occurrence of a phrase in the document, length of a phrase, and coherence score which measure the semantic relatedness between the phrase and other candidates. A Naive Bayes scheme builds a prediction model training data with known keyphrases, and then uses the model to calculate the overall probability for each candidate. We evaluate semantically improved method against the well known Kea system by using a more effective semantically enhanced evaluation method. The inter-domain experiment shows that quality of keyphrases extraction can be improved significantly when semantic information is exploited. The intra-domain experiment shows our method is competitive with Kea++ algorithm, and not domain-specific.