Miracle-dz/UniFAR-FTUs huggingface dataset:
A new classifier simulator for evaluating parallel combination methods

The use of artificial outputs generated by a classifier simulator has recently emerged as a new trend to provide an underlying evaluation of classifier combination methods. In this paper, we propose a new method for the artificial generation of classifier outputs based on additional parameters which provide sufficient diversity to simulate, for a problem of any number of classes and any type of output, any classifier performance. This is achieved through a two-step algorithm which first builds a confusion matrix according to desired behaviour and secondly generates, from this confusion matrix, outputs of any specified type. We provide the detailed algorithms and constraints to respect for the construction of the matrix and the generation of outputs. We illustrate on a small example the usefulness of the classifier simulator.
Availability-Consistency Trade-Offs in a Fault-Tolerant Stream Processing System

This paper presents an approach to fault-tolerant stream processing. In contrast to previous techniques that handle node failures, our approach also tolerates network failures and network partitions. The approach is based on a principled trade-off between consistency and availability in the face of failure, that (1) ensures that all data on an input stream is processed within a specified time threshold, but (2) reduces the impact of failures by limiting if possible the number of results produced based on partially available input data, and (3) corrects these results when failures heal. Our approach is well-suited for applications such as environment monitoring, where high availability and “real-time” response is preferable to perfect answers. Our approach uses replication and guarantees that all processing replicas achieve state consistency, both in the absence of failures and after a failure heals. We achieve consistency in the former case by defining a data-serializing operator that ensures that the order of tuples to a downstream operator is the same at all the replicas. To achieve consistency after a failure heals, we develop approaches based on checkpoint/redo and undo/redo techniques. We have implemented these schemes in a prototype distributed stream processing system, and present experimental results that show that the system meets the desired availability-consistency trade-offs.
Enhancing feature interfaces for supporting software product line maintenance

Software product line (SPL) is a technology aimed at speeding up the development process. Although SPLs are widely used, their maintenance is a challenging task. In particular, when maintaining a SPL feature, developers need to know which parts of other dependent features might be affected by this maintenance. Otherwise, further maintenance problems can be introduced in the SPL implementation. However, the identification and understanding of the so-called feature dependencies in the source code are an exhaustive and error-prone task. In fact, developers often ignore unconsciously feature dependencies while reasoning about SPL maintenance. To overcome this problem, this PhD research aims at understanding the properties of feature dependencies in the source code that exert impact on SPL maintenance. Furthermore, we propose a way to structure and segregate feature interfaces in order to help developers to identify and understand feature dependencies, thus reducing the effort and avoiding undesirable side effects in SPL maintenance.
Feedback linearized strategies for collaborative nonholonomic robots

Collaborative wheeled mobile robots are not stable around a point by continuous time-invariant feedback. Therefore, linear control is ineffective and innovative design techniques such as feedback linearization are required. This paper presents feedback linearized control strategies for collaborative nonholonomic robots using leader-follower formation. A framework for collaborative robots is developed based on their kinematics. The development framework relies on robots having communication capabilities instead of visual capabilities. The collaborative robot system is modeled using Simulink. From the simulation results, the full state linearized via dynamic feedback strategy for the leader robot globally stabilizes the system. Furthermore, the full state linearized via dynamic feedback strategy achieves postures stabilization for the leader-follower formation. For the follower robots, the input-output via static feedback linearized control strategies minimize the error between the desired and actual formation. Furthermore, the input-output linearized control strategies allow dynamical change of the formation at run-time. Thus, for a given feasible trajectory, the full state feedback linearized strategy for the leader robot and input-output feedback linearized strategies for the follower robots are found to be more efficient in stabilizing the system.
Effects of Resistance Training Intensity to Momentary Concentric Failure on Muscular Strength, Body Composition, and Affective Responses in Untrained Females

by Taylor K. Dinyer The purpose of this study was to examine strength, body composition, and affective responses from resistance training to failure at 30% 1-RM (30-fail) or 80% 1-RM (80-fail) in previously untrained females. Fourteen subjects completed this study. Subjects completed 10 weeks of RT to failure on four exercise machines. Strength and lean body mass were assessed at baseline and post-intervention. Strength increased significantly in the 30-fail and 80-fail groups (39.15 ± 22.00 kg and 35.15 ± 11.66 kg, respectively). Lean body mass increased significantly in the 30fail group (1.45 ± 1.70 kg). The 30-fail group reported significantly increase in pleasure immediately post to 60 minutes post exercise (0.25 ± 1.98 to 2.13 ± 1.36, respectively). The 30fail group reported lower perceived exertion than the 80-fail group (17.88 ± 1.36 and 18.67 ± 1.51, respectively). Training to momentary concentric failure can result in significant increases strength, LBM, and affective responses in untrained females. EFFECTS OF RESISTANCE TRAINING INTENSITY TO MOMENTARY CONCENTRIC FAILULRE ON MUSCULAR STRENGTH, BODY COMPOSITION, AND AFFECTIVE RESPONSES IN UNTRAINED FEMALES by Taylor K. Dinyer A Thesis Presented in partial fulfillment of the requirements for the degree of Master of Science in the Department of Nutrition and Kinesiology University of Central Missouri May, 2017
Measuring interestingness of continuous game problems

This paper investigates the relationship between the difficulty and the interestingness of individual problem candidates from within a class of related problems, using Lunar Lander as a case study. In this class of problems, a 2D spaceship must be controlled by a simple set of macro-actions, including both linear and angular impulses, such that it fulfils a set of weighted criteria relating to landing on a jagged landscape with flat landing pads. It is demonstrated that a very simple measure based on standard deviations of improvement can be used to guide evolution to develop interesting problems in this class of problems, which in turn can be solved using evolution strategies to get a high level of improvement based on initial random performance. We examine the impact of the measure used on the evolution of the problems, and also what aspects of this problem class affect the difficulty and interestingness the most.
A CNN-inspired mixed signal processor based on tunnel transistors

Novel devices are under investigation to extend the performance scaling trends that have long been associated with Moore's Law-based device scaling. Among the emerging devices being studied, tunnel FETs (or TFETs) are particularly attractive, especially when targeting low power systems. This paper studies the potential of analog/mixed-signal information processing using TFETs. The design of a highly-parallel processor - inspired by cellular neural networks - is presented. Signal processing is performed partially in the time-domain to better leverage the unique properties of TFETs, i.e., (i) steep slopes (high gm/IDS) in the subthreshold region, and (ii) high output resistance in the saturation region. Assuming an InAs TFET with feature sizes comparable to the 14 nm technology node, a power efficiency of 10,000 GOPS/W is projected. By comparison, state-of-the-art hardware assuming CMOS technology promises a power efficiency only close to 1,000 GOPS/W.
Centre de Referència en Economia Analítica Barcelona Economics Working Paper Series Working Paper n o 276 The Informational Value of Incumbency

This paper proposes an argument that explains incumbency advantage without recurring to the collective irresponsibility of legislatures. For that purpose, we exploit the informational value of incumbency: incumbency confers voters information about governing politicians not available from challengers. Because there are many reasons for high reelection rates di¤erent from incumbency status, we propose a measure of incumbency advantage that improves the use of pure reelection success. We also study the relationship between incumbency advantage and ideological and selection biases. An important implication of our analysis is that the literature linking incumbency and legislature irresponsibility most likely provides an overestimation of the latter. Key words: Incumbency, information, candidate quality, selection bias, ideology. JEL Classi cation Number(s): D72, D78. We thank Enriqueta Aragonés, Luis Corchón, and Paula González for helpful comments and suggestions. This research has been supported by Barcelona Economics program (CREA). Carmen Beviá acknowledges nancial support from grants SEJ200501581/ECONFEDER, and 2005SGR-00454. Humberto Llavador acknowledges nancial support from grant BEC2003-00412 and the European Commission (contract n. HPSE-CT-199000007) yDepartament dEconomia i dHistòria Econòmica and CODE. carmen.bevia@uab.es zDepartament dEconomia i Empresa. humberto.llavador@upf.edu Barcelona Economics WP no 276
Fuzzy logic-based outlier detection for bio-medical data

Many bio-medical databases such cohort study data suffer from potential errors involved with human factors like mistyping, overlooking some fields. It is crucial to detect such errors at the data entry stage using some techniques like outlier detection. Because such data lie in high-dimensional space and contain many null values, i.e., missing values, most conventional outlier detections are not a good choice for error detection. This paper proposes a fuzzy logic-based outlier detection technique designed to handle data inconsistency at the entry stage for bio-medical databases. The method takes care of the problems in the perspective of the horizontal and vertical consistencies. The method was implemented for a data entry assisting module of a cohort data collection system. In the pilot study, it was observed that the proposed method could detect potential errors at the data entry time.
Model Reference Adaptive Controller using MOPSO for a Non-Linear Boiler-Turbine

Biologically inspired algorithms are attracting lot of researchers in recent decades. Particle swarm optimization is a recent algorithm based on the movement and intelligence of swarms. This paper proposes an application of Multi Objective Particle Swarm Optimization (MOPSO) for tuning the Model Reference Adaptive Controller (MRAC) for a non-linear BoilerTurbine system. The Boiler-turbine system is a Multi Input Multi Output (MIMO) system which is non-linear in nature and hence MOPSO is used to obtain the solution. This paper proposes a new approach combining a priority based lexicography method and the overall error for tuning the parameters of swarm in order to get the best optimal solution. The model was developed using MATLAB simulink tool and the results were compared.
Machine learning techniques to diagnose breast cancer

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. As a result, machine learning is frequently used in cancer diagnosis and detection. In this paper, support vector machines, K-nearest neighbours and probabilistic neural networks classifiers are combined with signal-to-noise ratio feature ranking, sequential forward selection-based feature selection and principal component analysis feature extraction to distinguish between the benign and malignant tumours of breast. The best overall accuracy for breast cancer diagnosis is achieved equal to 98.80% and 96.33% respectively using support vector machines classifier models against two widely used breast cancer benchmark datasets.
Hybrid Titanium/Biodegradable Polymer Implants with an Hierarchical Pore Structure as a Means to Control Selective Cell Movement

In order to improve implant success rate, it is important to enhance their responsiveness to the prevailing conditions following implantation. Uncontrolled movement of inflammatory cells and fibroblasts is one of these in vivo problems and the porosity properties of the implant have a strong effect on these. Here, we describe a hybrid system composed of a macroporous titanium structure filled with a microporous biodegradable polymer. This polymer matrix has a distinct porosity gradient to accommodate different cell types (fibroblasts and epithelial cells). The main clinical application of this system will be the prevention of restenosis due to excessive fibroblast migration and proliferation in the case of tracheal implants. Methodology/Principal Findings A microbead-based titanium template was filled with a porous Poly (L-lactic acid) (PLLA) body by freeze-extraction method. A distinct porosity difference was obtained between the inner and outer surfaces of the implant as characterized by image analysis and Mercury porosimetry (9.8±2.2 µm vs. 36.7±11.4 µm, p≤0.05). On top, a thin PLLA film was added to optimize the growth of epithelial cells, which was confirmed by using human respiratory epithelial cells. To check the control of fibroblast movement, PKH26 labeled fibroblasts were seeded onto Titanium and Titanium/PLLA implants. The cell movement was quantified by confocal microscopy: in one week cells moved deeper in Ti samples compared to Ti/PLLA. Conclusions In vitro experiments showed that this new implant is effective for guiding different kind of cells it will contact upon implantation. Overall, this system would enable spatial and temporal control over cell migration by a gradient ranging from macroporosity to nanoporosity within a tracheal implant. Moreover, mechanical properties will be dependent mainly on the titanium frame. This will make it possible to create a polymeric environment which is suitable for cells without the need to meet mechanical requirements with the polymeric structure.
Modelling Credit Spreads evolution using the Cox Process within the HJM framework

In this paper a simulation approach for defaultable yield curve is developed within the Heath et al. (1992) framework. The default event is modelled using the Cox process when the stochastic intensity repre sents the credit spread. The forward credit spread volatility function is affected by the entire credit spread term structure. Cox process properties and the Monte Carlo simulations technique are used for pricing defaultable bonds.
Exploiting dynamic proxies in middleware for distributed, parallel, and mobile Java applications

Babylon v2.0 is a collection of tools and services that provide a 100% Java compatible environment for developing, running and managing parallel, distributed and mobile Java applications. It incorporates features like object migration, asynchronous method invocation and remote class loading while providing an easy-to-use interface. The implementation of Babylon v2.0 exploits dynamic proxies, a feature added to Java 1.3 that allows runtime creation of proxy objects. This paper shows how Babylon v2.0 exploits dynamic proxies to implement several key features without the need for special language or virtual machine extensions, preprocessors, or compilers. The resulting Babylon programs are portable across all Java virtual machines, and the development process is simplified by removing the extra steps needed to invoke external stub compilers and incorporate the generated code into an application. This simplification also allows remote objects to be created for any class that supports an interface to its methods, even if source code is not available
Trade-offs in execution signature compression for reliable processor systems

As semiconductor processes scale, making transistors more vulnerable to transient upset, a wide variety of microarchitectural and system-level strategies are emerging to perform efficient error detection and correction computer systems. While these approaches often target various application domains and address error detection and correction at different granularities and with different overheads, an emerging trend is the use of state compression, e.g., cyclic redundancy check (CRC), to reduce the cost of redundancy checking. Prior work in the literature has shown that Fletcher's checksum (FC), while less effective where error detection probability is concerned, is less computationally complex when implemented in software than the more-effective CRC. In this paper, we reexamine the suitability of CRC and FC as compression algorithms when implemented in hardware for embedded safety-critical systems. We have developed and evaluated parameterizable implementations of CRC and FC in FPGA, and we observe that what was true for software implementations does not hold in hardware: CRC is more efficient than FC across a wide variety of target input bandwidths and compression strengths.
High levels of maternally transferred mercury do not affect reproductive output or embryonic survival of northern watersnakes (Nerodia sipedon)

Maternal transfer is an important exposure pathway for contaminants because it can directly influence offspring development. Few studies have examined maternal transfer of contaminants, such as mercury (Hg), in snakes, despite their abundance and high trophic position in many ecosystems where Hg is prevalent. The objectives of the present study were to determine if Hg is maternally transferred in northern watersnakes (Nerodia sipedon) and to evaluate the effects of maternal Hg on reproduction. The authors captured gravid female watersnakes (n = 31) along the South River in Waynesboro, Virginia, USA, where an extensive Hg‐contamination gradient exists. The authors measured maternal tissue and litter Hg concentrations and, following birth, assessed (1) reproductive parameters (i.e., litter size and mass, neonate mass); (2) rates of infertility, death during development, stillbirths, malformations, and runts; and (3) the overall viability of offspring. Mercury concentrations in females were strongly and positively correlated with concentrations in litters, suggesting that N. sipedon maternally transfer Hg in proportion to their tissue residues. Maternal transfer resulted in high concentrations (up to 10.10 mg/kg dry wt total Hg) of Hg in offspring. The authors found little evidence of adverse effects of Hg on these measures of reproductive output and embryonic survival, suggesting that N. sipedon may be more tolerant of Hg than other vertebrate species. Given that this is the first study to examine the effects of maternally transferred contaminants in snakes and that the authors did not measure all reproductive endpoints, further research is needed to better understand factors that influence maternal transfer and associated sublethal effects on offspring. Environ. Toxicol. Chem. 2013;32:619–626. © 2012 SETAC
Jumper’s Knee or Lander’s Knee? A Systematic Review of the Relation between Jump Biomechanics and Patellar Tendinopathy

Abstract Patellar tendinopathy (jumper’s knee) is a common injury in sports that comprise jump actions. This article systematically reviews the literature examining the relation between patellar tendinopathy and take-off and landing kinematics in order to uncover risk factors and potential prevention strategies. A systematic search of the Pubmed, Embase and Amed databases was performed to identify studies that reported kinematics of sport specific jumps in relation to patellar tendinopathy. A quantitative analysis was performed on 4 indentified studies. Differences were found only between controls and asymptomatic subjects with patellar tendon abnormalities. Most differences were found during horizontal landing after forward acceleration. A synthesis of the literature suggests that horizontal landing poses the greatest threat for developing patellar tendinopathy. A stiff movement pattern with a small post-touchdown range of motion and short landing time is associated with the onset of patellar tendinopathy. Accordingly, employing a flexible landing pattern seems to be an expedient strategy for reducing the risk for (re-) developing patellar tendinopathy. Together, these findings indicate that improving kinetic chain functioning, performing eccentric exercises and changing landing patterns are potential tools for preventive and/or therapeutic purposes.
LANGUAGE ATTITUDE AND CHOICE BY MINANGKABAU COMMUNITY:A SOCIOLINGUISTIC STUDY IN MEDAN

The objective of the research is to observe language attitude and choice of Minangkabau community residing in Medan to find out whether the people in the community have a positive or negative attitude toward Minangkabau language, and whether their language choice shows a preference toward Bahasa Indonesia, Minangkabau language, or other languages. This research was conducted in two subdistricts covering four villages in Medan. The data of this research were 400 copies of questionnaire whichcontained the respondents’ answers to 11 questions on language attitude and 18 questions on language choice. The data obtained were analyzed using Likert Scale for language attitude and domain analysis for language choice. It was found that the result of the language attitude was positive but in the language choice, respondents tended to use Bahasa Indonesia in the family, friendship, place, and media domains Permalink/DOI: dx.doi. org/10.17977/um015v45i12017p076
ALCOHOL AND REMEMBERING SEXUAL ASSAULT 1 Alcohol and remembering a hypothetical sexual assault : Can people who were under the influence of alcohol during the event provide accurate testimony ?

We examined the influence of alcohol on remembering an interactive hypothetical sexual assault scenario in the laboratory using a balanced placebo design. Female participants completed a memory test 24 hours and 4 months later. Participants reported less information (i.e., responded ‘don’t know’ more often to questions) if they were under the influence of alcohol during scenario encoding. The accuracy of the information intoxicated participants reported did not differ compared to sober participants, however, suggesting intoxicated participants were effectively monitoring the accuracy of their memory at test. Additionally, peripheral details were remembered less accurately than central details, regardless of intoxication level; and memory accuracy for peripheral details decreased by a larger amount compared to central details across the retention interval. Finally, participants were more accurate if they were told they were drinking alcohol rather than a placebo. We discuss theoretical implications for alcohol myopia and memory regulation, together with applied implications for interviewing intoxicated witnesses.