Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects, Asynchrony, and Choice in Arrowized Functional Reactive Programming

Effects, Asynchrony, and Choice in Arrowized Functional Reactive Programming Daniel Winograd-Cort 2015 Functional reactive programming facilitates programming with time-varying data that can be perceived as streams flowing through time. Thus, one can think of FRP as an inversion of flow control from the structure of the program to the structure of the data itself. In a typical (say, imperative) program, the structure of the program governs how the program will behave over time; as time moves forward, the program sequentially executes its statements, and at any line of code, one can make a clear distinction between code that has already been run (the past) and code that has yet to be run (the future). However, in FRP, the program acts as a signal function, and, as such, we are allowed to assume that the program executes continuously on its time-varying inputs—essentially, it behaves as if it is running infinitely fast and infinitely often. We consider this to be the core principle of the design and call it the fundamental abstraction of FRP. Design and Performance This work is specifically rooted in Arrowized FRP, where these signal functions remain static as they process the dynamic signals they act upon. However, in practice, it is often valuable to be able to dynamically alter the way that a signal function behaves over time. Typically, this is achieved with “switching” or other monadic features, but this significantly reduces the usefulness of the arrows. We develop an extension to arrows to allow “predictably dynamic” behavior along with a notion of settability, which together recover the desired dynamic power. We further demonstrate that optimizations designed specifically for arrowized FRP and which do not apply to monadic FRP, such as those for Causal Commutative Arrows, are applicable to the system. Thus, it can be powerfully optimized.
Learning quality-aware filters for no-reference image quality assessment

With the rapid development of the usage of digital imaging and communication technologies, there appears to be a great demand for fast and practical approaches for image quality assessment (IQA) algorithms that can match human judgements. In this paper, we propose a novel general-purpose no-reference IQA (NR-IQA) framework by means of learning quality-aware filters (QAF). Using these filters for image encoding, we can obtain effective image representations for quality estimation. Additionally, random forest is used to learn the mapping from feature space to human subjective scores. Extensive experiments conducted on LIVE and CSIQ databases demonstrate that the proposed NR-IQA metric QAF can achieve better prediction performance than all the other state-of-the-art NR-IQA approaches in terms of both prediction accuracy and generalization capabilities.
Dynamic Scene Reconstruction for Efficient Remote Surveillance

In this paper a system is presented able to reproduce the actions of multiple moving objects into a 3D model. A multi-camera surveillance system is used for automatically detect, track and classify the objects. Data fusion from multiple sensors allows to get a more precise estimation of the position of detected moving objects and to solve occlusions problem. These data are then used to automatically place and animate objects avatars in a 3D virtual model of the scene, thus allowing a human operator to remotely visualize the dynamic 3D reconstruction by selecting a arbitrary point of view.
Evaluation of a Java Processor

In this paper, we will present the evaluation results for a Java processor, with respect to size and performance. The Java Optimized Processor (JOP) is an implementation of the Java virtual machine (JVM) in a low-cost FPGA. JOP is the smallest hardware realization of the JVM available to date. Due to the efficient implementation of the stack architecture, JOP is also smaller than a comparable RISC processor in an FPGA. Although JOP is intended as a processor for embedded realtime systems, whereas accurate worst case execution time analys is is more important than average case performance, its general performance is still important. We will see that a real-time processor architecture does not need to be slow.
The intra- and interrater reliability of the action research arm test: a practical test of upper extremity function in patients with stroke.

OBJECTIVES To determine the intra- and interrater reliability of the Action Research Arm (ARA) test, to assess its ability to detect a minimal clinically important difference (MCID) of 5.7 points, and to identify less reliable test items. DESIGN Intrarater reliability of the sum scores and of individual items was assessed by comparing (1) the ratings of the laboratory measurements of 20 patients with the ratings of the same measurements recorded on videotape by the original rater, and (2) the repeated ratings of videotaped measurements by the same rater. Interrater reliability was assessed by comparing the ratings of the videotaped measurements of 2 raters. The resulting limits of agreement were compared with the MCID. PATIENTS Stratified sample, based on the intake ARA score, of 20 chronic stroke patients (median age, 62yr; median time since stroke onset, 3.6yr; mean intake ARA score, 29.2). MAIN OUTCOME MEASURES Spearman's rank-order correlation coefficient (Spearman's rho); intraclass correlation coefficient (ICC); mean difference and limits of agreement, based on ARA sum scores; and weighted kappa, based on individual items. RESULTS All intra- and interrater Spearman's rho and ICC values were higher than . 98. The mean difference between ratings was highest for the interrater pair (.75; 95% confidence interval, .02-1.48), suggesting a small systematic difference between raters. Intrarater limits of agreement were -1.66 to 2.26; interrater limits of agreement were -2.35 to 3.85. Median weighted kappas exceeded . 92. CONCLUSION The high intra- and interrater reliability of the ARA test was confirmed, as was its ability to detect a clinically relevant difference of 5.7 points.
Improving the Discrimination of Benign and Malignant Breast MRI Lesions Using the Apparent Diffusion Coefficient

This paper presents an investigation of the apparent diffusion coefficient (ADC) for improving the discrimination of benign and malignant lesions in breast magnetic resonance imaging (MRI). In particular a method is presented for automatically selecting hyper intense tumour voxels in dynamic contrast enhanced (DCE) MRI data and evaluating their average ADC in the corresponding diffusion-weighted (DW) MRI data. The method was applied to ten breast MRI datasets obtained from routine clinical practice. The results demonstrate that the combination of the relative signal increase (DCE-MRI) with the apparent diffusion coefficient (DW-MRI) leads to better discrimination than with either feature alone. The results also suggest that it is important to acquire the DWMRI data in a consistent fashion, i.e. either before or after the acquisition of the DCE-MRI data.
Tape Mbo'e (TME): A Service-Oriented Method

In many developing countries, legacy systems of government are normally isolate affecting the quality of services provided to citizens. This situation affects the data trustfulness, and transparency. For this reason, various governments have been striving interoperate their legacy systems using service oriented paradigm. To achieve this ambitious goal many aspects have to be considered such as the economy conditions that have an influence on the decision of adopting software development method. The method has to produce fast deliveries, maintains the costs low, and considers from the beginning aspects related to long-term sustainability of the IT solutions. Trying to comply with such requirements, Tape Mbo'e Process (TME) has been proposed. TME focuses on building, and maintaining sustainable services-based applications. TME has been used in five case studies, which embraced both academia and public organizations in Paraguay. It is important to remark that it was the first application of this type of evaluation in the public sector in Paraguay. The initial results of the different case studies indicate the feasibility and simplicity of TME when it is applied in this context.
Towards a Model for Creating Comparable Intellectual Capital Reports

Since the beginning 1990s various concepts of intellectual capital reports have been elaborated and their descriptions can be found in both scientific and management literature. Their major task is the attempt to cover intangible assets within an organisation or firm and to illustrate the immense resources, which may be used to attain competitive advantages. A major drawback of all presented intellectual capital reports is their non-comparability due to the diversity of conceptions. Thus, it is not possible to compare and evaluate the results of different firms within an industry using diverse concepts of intellectual capital reports. This paper presents an approach, which allows the creation of comparable intellectual capital reports based on so called meta-indicators (or benchmarks). By using the meta-modelling approach the intellectual capital reporting (ICR) benchmark framework and a top-down procedure model (the intellectual capital reporting (ICR) step model) are outlined and discussed in detail.
A Short, Nonplanetary, Microlensing Anomaly: Observations and Light-Curve Analysis of MACHO 99-BLG-47

We analyze PLANET and MACHO observations of MACHO 99-BLG-47, the first nearly normal microlensing event for which high signal-to-noise ratio data reveal a well-covered, short-duration anomaly. This anomaly occurs near the peak of the event. Short-duration anomalies near the peak of otherwise normal events are expected to arise both from extreme-separation (either very close or very wide), roughly equal-mass binary lenses and from planetary systems. We show that the lens of MACHO 99-BLG-47 is in fact an extreme-separation binary, not a planetary system, thus demonstrating for the first time that these two important classes of events can be distinguished in practice. However, we find that the wide-binary and close-binary lens solutions fit the data equally well and cannot be distinguished even at Δχ2 = 1. This degeneracy is qualitatively much more severe than the one identified for MACHO 98-SMC-1 because the present degeneracy spans two rather than one dimension in the magnification field and does not require significantly different blending fractions. In the Appendix, we explore this result and show that it is related to the symmetry in the lens equation.
Path Planning Methods for Autonomous Underwater Vehicles by Konuralp Yigit

From naval operations to ocean science missions, the importance of autonomous vehicles is increasing with the advances in underwater robotics technology. Due to the dynamic and intermittent underwater environment and the physical limitations of autonomous underwater vehicles, feasible and optimal path planning is crucial for autonomous underwater operations. The objective of this thesis is to develop and demonstrate an efficient underwater path planning algorithm based on the level set method. Specifically, the goal is to compute the paths of autonomous vehicles which minimize travel time in the presence of ocean currents. The approach is to either utilize or avoid any type of ocean flows, while allowing for currents that are much larger than the nominal vehicle speed and for three-dimensional currents which vary with time. Existing path planning methods for the fields of ocean science and robotics are first reviewed, and the advantages and disadvantages of each are discussed. The underpinnings of the level set and fast marching methods are then reviewed, including their new extension and application to underwater path planning. Finally, a new feasible and optimal time-dependent underwater path planning algorithm is derived and presented. In order to demonstrate the capabilities of the algorithm, a set of idealized test-cases of increasing complexity are first presented and discussed. A real three-dimensional path planning example, involving strong current conditions, is also illustrated. This example utilizes four-dimensional ocean flows from a realistic ocean prediction system which simulate the ocean response to the passage of a tropical storm in the Middle Atlantic Bight region. Thesis Supervisor: Pierre F.J. Lermusiaux Title: Associate Professor
Multi-view Clustering via Concept Factorization with Local Manifold Regularization

Real-world datasets often have representations in multiple views or come from multiple sources. Exploiting consistent or complementary information from multi-view data, multi-view clustering aims to get better clustering quality rather than relying on the individual view. In this paper, we propose a novel multi-view clustering method called multi-view concept clustering based on concept factorization with local manifold regularization, which drives a common consensus representation for multiple views. The local manifold regularization is incorporated into concept factorization to preserve the locally geometrical structure of the data space. Moreover, the weight of each view is learnt automatically and a co-normalized approach is designed to make fusion meaningful in terms of driving the common consensus representation. An iterative optimization algorithm based on the multiplicative rules is developed to minimize the objective function. Experimental results on nine reality datasets involving different fields demonstrate that the proposed method performs better than several state-of-the-art multi-view clustering methods.
Data layout management for energy-saving key-value storage using a write off-loading technique

The objective of our research has been to achieve energy-saving key-value store system. We introduce architecture of our distributed key value store and control framework for energy saving. To reduce power consumption, the control framework should reduce the time required before node power-down. Since this time depends heavily on the amount of data migration, we employ an approach which reduce that amount. We describe and evaluate three control strategies that can be executed on this control framework, each consisting of a data allocation algorithm and data control layout algorithm for use when nodes are to be powered down. With a prototype system developed for evaluation purposes, the time required before node power down is reduced by use of our proposed data allocation algorithm, by means of its taking into account the possible presence of Write off-loading nodes.
Encyclopedia of Database Technologies and Applications Knowledge Discovery from Databases

As databases are pervading every parcel of reality, they record what happens in and around organizations all over the world. Databases store the detailed history of organizations, institutions, governments and individuals. An efficient and agile analysis of the data recorded in a database can no longer be done manually. Knowledge Discovery from Databases (KDD) is a collection of technologies which aim at extracting nontrivial, implicit, previously unknown, and potentially useful information (Fayyad, Piatetsky-Shapiro, Smyth & Uthurusamy, 1996) from raw data stored in databases. The extracted patterns, models or trends can be used to better understand the data, and hence the context of an organization, and to predict future behaviors in this context that could improve decision making. KDD can be used to answer questions such as: Is there a group of customers buying a special kind of products? Which sequence of financial products improves the chance of contracting a mortgage? Which telephone call patterns suggest a future churn? Are there relevant associations between risk factors in coronary diseases? How can I assess my e-mail messages more or less likely to be spam (junk mail)? The previous questions cannot be answered by other tools usually associated to database technology such as OLAP tools, decision support systems, executive information systems, etc. The key difference is that KDD does not convert information into (more aggregated or interwoven) information, but generates inductive models (under the form of rules, equations or other kind of knowledge) that could be sufficiently consistent with the data. In other words, KDD is not a deductive process but an inductive one.
Bayesian Estimation of a Dsge Model and Convergence Dynamics Analysis for Central Europe Transition Economies

This paper studies a dynamic stochastic general equilibrium model for a small open economy with two types of consumption goods (home produced goods and imported goods) and two types of production goods (home goods and export goods). The objective is to analyze the convergence issues, with respect to the EU-15, of the Central Europe countries: Czech Republic, Hungary, Poland, Slovakia and Slovenia. The model exhibits features of market imperfections and nominal rigidities. Then, the model is estimated using Bayesian methods. The estimation results illustrate some di¤erences from the Euro area results in structural parameters. However, the results exhibit some similarities across countries, notably in some shocks volatilities and high habit formation of consumption. The results illustrate also an important degree of rigidity of imported goods prices, which implies a low pass-through of the exchange rate ‡uctuations. Finally, we study the Ramsey optimal allocation, in a timeless perspective, of the estimated model for each country in order to analyze the convergence criteria of entrance in the european exchange rate mechanism. I would like to thank …rst my supervisor Ferhat Mihoubi for all the useful comments and the helpful supervision to achieve this paper. I thank also Douglas Laxton, Paolo Pesenti and Dirk Muir for their feedback and suggestions.
Acupuncture for chronic diarrhea in adults

Background: As 2 major common types of chronic diarrhea, functional diarrhea (FD) and diarrhea-predominant irritable bowel syndrome (IBS-D) affect 1.54% to 1.72% of people in China. Acupuncture is commonly used in clinical practice for patients with chronic diarrhea. Here, we present a protocol of systematic review aimed at systematically review all the clinical evidence on the effectiveness of acupuncture for treating FD and IBS-D in adults. Methods: The review will be performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. We will search the following databases from their inception to January 2017: Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, China Biology Medicine disc, Wan-Fang Data, China National Knowledge Infrastructure, Citation Information by National Institute of Informatics, Oriental Medicine Advanced Searching Integrated System by Korea Institute of Oriental Medicine, and Japan Science and Technology Information Aggregator (J-stage). Clinical trial registrations will also be searched. Primary outcome measures are the change of bowel movements. The secondary outcomes include stool consistency, quality of life scales, other standardized rating scales, patient satisfaction, and acupuncture-related adverse effects assessment. Ethics and dissemination: This review does not require ethical approval and will be disseminated electronically or in print. PROSPERO registration number: CRD42015017574.
Teenage girls negotiating femininity in the context of sexually explicit materials

ABSTRACT In this paper, we draw from elements of a study that sought to examine how teenage South African girls, both white and black African, articulate their relationship with online sexually explicit materials (SEM). The study contributes to the literature by resisting the dominant discursive practices underlined by the construction of sexuality as an exclusive realm of danger for teenage girls. Challenging this static version of femininity, we focus on the ways in which teenage girls, aged between 13 and 18 years old in two elite private schools, use online SEM to expand their sexual knowledge and engage in pleasurable forms of sexuality. By drawing on individual interviews, focus group discussions and open-ended visual elicitation research methods, we show how girls embrace online SEM in ways that expand the definition of femininity beyond fearing sexuality whilst demonstrating the entanglement with gender inequalities. Girls’ relationship with online SEM, whilst tenuous, disrupts normative assumptions around femininity. However, an ambiguous relationship with online SEM is evident as their challenges to dominant femininity are mediated by concerns about respect and innocence, as well as by persistent evidence of male power within online SEM. Implications for school-based sexuality education concludes the paper.
Sexual Violence Victimization, Mental Health, and University-Based Health Service Use among College Females.

SEXUAL VIOLENCE VICTIMIZATION, MENTAL HEALTH, AND UNIVERSITYBASED HEALTH SERVICE USE AMONG COLLEGE FEMALES Julie Emery Stoner Old Dominion University, 2018 Chair: Dr. Robert J. Cramer Females between the ages of 18 and 24 consistently experience higher rates of sexual violence compared to females in any other age group (Sinozich & Langton, 2014). Approximately one in five college women experience sexual violence victimization (SVV; Krebs, Lindquist, Berzofsky, Shook-Sa & Peterson, 2016) during the academic year. Among undergraduate female students, 23.1% are victims of sexual violence due to physical force, violence or incapacitation (Cantor et al., 2015). Sexual victimization has been associated with several shortand long-term psychological health consequences, accounting for enhanced symptoms of depression, anxiety, PTSD, and suicide risk (Basile, Smith, Breiding, Black & Mahendra, 2014). Compared with the general population, college women are consistently less likely to disclose an experience of sexual assault (Fisher, Cullen & Turner, 2000). Despite the high rates of sexual violence against college females, only 11% of rapes are reported to college authorities, making sexual victimization the most underreported violent crime among this population (Kilpatrick, Resnick, Ruggiero, Conoscenti & McCauley, 2007). College students are 13% less likely to report an incident of sexual assault to police versus nonstudents in the same age group (Sinozich & Langton, 2014) and one-third of female students never tell anyone about the victimization (Fisher et al., 2000)
System-level approach to the design of collaborative distributed systems based on wireless sensor and actuator networks

Wireless sensor and actuator networks (WSAN) have become pervasive and are found in many embedded and intelligent systems. However, the complexity of applications based on WSANs is limited due to the lack of programming tools for this type of networks. In this paper, we show how a concurrent programming language, SystemJ, is used to develop a middleware-free distributed system that consists of a combination of stationary and mobile WSAN nodes. A distributed Ambient Intelligence (AmI) monitoring and control scenario that consists of collaborating stationary and mobile WSAN nodes with high degree of reactivity is presented. The system is designed and implemented using SystemJ to demonstrate the proposed system-level design approach. SystemJ is designed specifically to handle reactive and concurrent behaviors while providing modular and scalable methodology for distributed system composition. In addition, SystemJ removes the need for a middleware and allows system designers to focus on implementing system functionality rather than to deal with the low level programming details.