Miracle-dz/UniFAR-FTUs huggingface dataset:
Strider: Runtime Support for Optimizing Strided Data Accesses on Multi-Cores with Explicitly Managed Memories

Multi-core processors with explicitly-managed local memories provide advanced capabilities to optimize data caching and prefetching in software. Unfortunately, these capabilities are neither easily accessible to programmers, nor exploited to their maximum potential by current language, compiler, or runtime frameworks. We present Strider, a runtime framework for optimizing compilers on multi-core processors with software- managed memories. Strider transparently optimizes grouping, decomposition, and scheduling of explicit software-managed accesses to multi-dimensional arrays in nested loops, given a high- level specification of loops and their data access patterns. In particular, Strider contributes new methods to improve temporal locality, optimize the critical path of scheduling data transfers for multi-stride accesses in regular nested parallel loops, and distribute accesses between cores. The prototype of Strider on the IBM Cell processor performs competitively to hand-optimized code and better than contemporary language frameworks, in both non-trivial parallel applications and important application kernels.
State Policies on Tuition and Fees for Public Higher Education.

has been considerable attention focused on the issue of tuition and fees in colleges and universities recently. College and university governing boards, state coordinating boards, regional educational groups like the Southern Regional Education Board (SREB) and the Western Interstate Commission on Higher Education (WICHE), state legislators, students, and others have expressed interest in and concern over rapidly rising tuition and fee costs. The issue is of particular import in 1982 as the federal government considers proposals that would reduce available student aid that helps pay for the tuition and mandatory charges. At most colleges and universities in the United States, there are many different tuition and fee charges that vary in amount from institution to institution. These charges can be classified into two components: tuition and mandatory fees. Tuition is the basic charge for education and may vary by residency, fullor part-time status, and level of the student. For example, full-time resident tuition would be charged to students who meet the residency requirements of the college and who carry a specified credit hour load each semester or term. The credit hour load for full-time status varies from institution to institution; however, some colleges charge tuition only by credit hours. In at least two states, colleges charge tuition that varies by the type and level of class. For example, a student enrolling in a senior level physics class would be charged more than a student enrolling in a freshman level English class. Mandatory fees are all those charges that are not tuition and that must be paid by a particular group of students. Generally, fees are charged for registration, student activities, bonded indebtedness, athletics, health, and other items peculiar to an institution. Some colleges include fees in the tuition charge while others charge no, or very low, tuition but a large dollar amount of fees. Some states have established tuition and fee policies that relate
Annular Mode Variability of the Atmospheric Meridional Energy Transport and Circulation

AbstractMonth-to-month variability in the meridional atmospheric energy transport is analyzed in the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis for 1979–2012. The meridional transport of moist static energy (MSE) is composited onto the high and low phases of the northern and southern annular modes (NAM and SAM). While the high phase of the NAM and SAM is known to involve a poleward shift in the midlatitude storm track and jet, it is shown here that the distribution of poleward MSE transport shifts equatorward. This change is explained by examining the variability of the underlying meridional circulation. In particular, changes in the mass transport averaged on dry and moist static energy levels are considered. These circulations have an advantage over the conventional Eulerian circulation for explaining the total energy transport. They are computed using the statistical transformed Eulerian-mean (STEM) formulation, which provides a decomposition of the circulation i.
Optimal Investment and Consumption Decisions when Time-Horizon is Uncertain

Many investors do not know with certainty when their portfolio will be liquidated. Should their portfolio selection be in‡uenced by the uncertainty of exit time? In order to answer that question, we consider a suitable extension of the familiar optimal investment problem of Merton (1971), where we allow the conditional distribution function of an agent’s time-horizon to be stochastic and correlated to returns on risky securities. In contrast to existing literature, which has focused on an independent time-horizon, we
A COTS architectural component specification stencil for selection and reasoning

Reusing commercial-off-the-shelf (COTS) components may reduce cost and time-to-market. It may significantly improve software productivity. However, the selection and assessment of COTS components are still a challenge task. It is hard to find the right components that exactly fit into the requirements. The selection processes are in general ad-hoc. Wrong choice of COTS components may compromise the benefits from reusing these components since the chosen component may mismatch with other components and the environment. In this position paper, we advocate a more detailed architectural specification stencil which may help on the component selection and mismatch detection. The architectural specification of a COTS component is encoded in XML so that searching components can be automated. In addition, inconsistencies and mismatches among components can be detected.
Improving Web accessibility through an enhanced open-source browser

The accessibilityWorks project provides software enhancements to the MozillaTM, Web browser and allows users to control their browsing environment. Although Web accessibility standards specify markup that must be incorporated for Web pages to be accessible, these standards do not ensure a good experience for all Web users. This paper discusses user controls that facilitate a number of adaptations that can greatly increase the usability of Web pages for a diverse population of users. In addition to transformations that change page presentation, innovations are discussed that enable mouse and keyboard input correction as well as vision-based control for users unable to use their hands for computer input.
Prediction of magnetic remanence of NdFeB magnets by using novel machine learning intelligence approach — Support vector regression

A novel model using support vector regression (SVR) combined with particle swarm optimization (PSO) integrating leave-one-out cross validation (LOOCV) was employed to construct mathematical model for prediction of the magnetic remanence of the NdFeB magnets. The leave-one-out cross validation of SVR model test results show that the mean absolute error doesnot exceed 0.0036, the mean absolute percentage error is only 0.53%, and the correlation coefficient (R2) is as high as 0.839. This investigation suggests that the SVR-LOOCV is not only an effective and practical method to simulate the remanence of NdFeB, but also a powerful tool to optimize designing or controlling the experimental process.
CNeT: competitive neural trees for pattern classification

This paper introduces competitive neural trees (CNeT) for pattern classification. The CNeT performs hierarchical classification and employs competitive unsupervised learning at the node level. The generalization ability of the CNeT is guaranteed by forward pruning, which is an inherent part of the learning process. Different search methods are introduced for the CNeT and used for both training and recall. The influence of different search methods on the performance of the CNeT is experimentally evaluated.
Smooth versus Textured Surfaces: Feature-Based Category Selectivity in Human Visual Cortex

Abstract In fMRI studies, human lateral occipital (LO) cortex is thought to respond selectively to images of objects, compared with nonobjects. However, it remains unresolved whether all objects evoke equivalent levels of activity in LO, and, if not, which image features produce stronger activation. Here, we used an unbiased parametric texture model to predict preferred versus nonpreferred stimuli in LO. Observation and psychophysical results showed that predicted preferred stimuli (both objects and nonobjects) had smooth (rather than textured) surfaces. These predictions were confirmed using fMRI, for objects and nonobjects. Similar preferences were also found in the fusiform face area (FFA). Consistent with this: (1) FFA and LO responded more strongly to nonfreckled (smooth) faces, compared with otherwise identical freckled (textured) faces; and (2) strong functional connections were found between LO and FFA. Thus, LO and FFA may be part of an information-processing stream distinguished by feature-based category selectivity (smooth > textured).
Coding of Temporally Varying Signals in Networks of Spiking Neurons with Global Delayed Feedback

Oscillatory and synchronized neural activities are commonly found in the brain, and evidence suggests that many of them are caused by global feedback. Their mechanisms and roles in information processing have been discussed often using purely feedforward networks or recurrent networks with constant inputs. On the other hand, real recurrent neural networks are abundant and continually receive information-rich inputs from the outside environment or other parts of the brain. We examine how feedforward networks of spiking neurons with delayed global feedback process information about temporally changing inputs. We show that the network behavior is more synchronous as well as more correlated with and phase-locked to the stimulus when the stimulus frequency is resonant with the inherent frequency of the neuron or that of the network oscillation generated by the feedback architecture. The two eigenmodes have distinct dynamical characteristics, which are supported by numerical simulations and by analytical arguments based on frequency response and bifurcation theory. This distinction is similar to the class I versus class II classification of single neurons according to the bifurcation from quiescence to periodic firing, and the two modes depend differently on system parameters. These two mechanisms may be associated with different types of information processing.
Analysis of Scaling behavior of Heart Rate Variability based on Global and Local Exponents derived from DFA and Wavelet Transforms

—Scaling behavior of heart rate fluctuations has been analyzed using wavelet transform based Hurst exponent estimation. Global Hurst exponent is extracted using filter coefficients obtained by discrete wavelet transforms. A short term scaling exponent is also obtained based on detrended fluctuation analysis method. As the Hurst exponents obtained using these methods do not give any idea about the local singularities, a Wavelet Transform Modulus Maxima method (WTMM) to compute local Holder exponents is used. The complete singularity spectrum of younger and elderly subjects from MIT/BIH Fantasia database is obtained. It is observed that there is a decrease in long range anti-correlated behavior with age. Young subjects show multifractal behavior in HRV as compared to monofractality in aged subjects.
Of Coordinators and Dictators: A Public Goods Experiment

We experimentally investigate whether human subjects are willing to give up individual freedom in return for the benefits of improved coordination. We conduct a modified iterated public goods game in which subjects in each period first decide which of two groups to join. One group employs a voluntary contribution mechanism, the other group an allocator contribution mechanism. The setup of the allocator mechanism differs between two treatments. In the coordinator treatment, the randomly selected allocator can set a uniform contribution for all group members, including herself. In the dictator treatment, the allocator can choose different contributions for herself and all other group members. We find that subjects willingly submit to authority in both treatments, even when competing with a voluntary contribution mechanism. The allocator groups achieve high contribution levels in both treatments.
Interactions Between Intrinsic and Extrinsic Motivation

In this paper we will discribe a system that motivates robots with a combination of intrinsic and extrinsic sources of motivation. The system is based on reinforcement learning, and uses neural networks to predict the eects of the robot’s actions on the environment and rewarding it for improvement in predictions, while also granting other extrinsic rewards for specic actions. We then test the system in a simulated environment to see whether the combination of dierent sources of motivation can allow a robot to learn about its environment while also avoiding potentially dangerous actions and keeping its battery charged. We nd that robots with extrinsic motivation are able to avoid harm and keep their battery charged successfully, even when intrinsic motivation is also present. However, intrinsically motivated robots are only slightly better at learning about the environment than extrinsically motivated ones, and robots with a combination of both types of motivation do not do any better than those with only extrinsic motivation. Furthermore, robots that choose actions randomly learn about the environment better than those with either intrinsic or extrinsic motivation. From these results, we conclude that the addition of intrinsic motivation does not stop a robot from achieving extrinsic goals, but that aws in either our system or environment prevent intrinsic motivation from yielding any benets in the tests performed.
Effectiveness of Stakeholder Identification Methods in Requirements Elicitation: Experimental Results Derived from a Methodical Review

One of the key challenges to producing high-quality software is identifying and understanding software requirements. In requirements acquisition, one of the crucial parts is stakeholder identification. This paper reports a methodical review of empirical studies concerning the effectiveness of stakeholder identification methods in requirements software, and the subsequent experimental evidence gathered from those studies. The following are the most considerable results: 1) studies which limit themselves to only proposing a list of possible stakeholders, 2) methods which not only indicate who the stakeholders can be but also studies their interactions and, 3) approaches dealing with studies that include an assessment of stakeholders. It should be noted that the studies from which these results were obtained have not been validated, and therefore the above-mentioned claims cannot be regarded as foolproof. However, these findings can be used by researchers as items of knowledge to be further investigated, and by practitioners in development software projects.
eft-corner Unification-base

In this paper, we present an efficient algorithm for parsing natural language using unification grammars. The algorithm is an extension of left-corner parsing, a bottom-up algorithm which utilizes top-down expectations. The extension exploits unification grammar’s uniform representation of syntactic, semantic, and domain knowledge, by incorporating all types of grammatical knowledge into parser expectations. In particular, we extend the notion of the reochcsbility table, which provides information as to whether or not a top-down expectation can be realized by a potential subconstituent, by including all types of grammatical information in table entries, rather than just phrase structure information. While our algorithm’s worstcase computational complexity is no better than that of many other algorithms, we present empirical testing in which average-case linear time performance is achieved. Our testing indicates this to be much improved average-case performance over previous left-
Context and Linguistic Knowledge in Natural Language Processing

Tllis paper investigates the prospect of dividing linguistic knowledge into modules, which could be used, a few at a time, in understanding a sequence of natur31 language utterances. This approach leads to the need to keep track of the modules which are currently relevant at successive parts of a sequence of natural language utterances. Factors in determining the current context set include recent context history, themes announced explicitly at the start of a natural language passage, knowledge associated with words in the current clause or phrase, or in nearby clauses or phrases, and a bias towards semantic continuity. Benefits include a reduction in the problem of word-sense ambiguity.
An Study on Personalized Recommendation Model Based on Search Behaviors and Resource Properties

This paper presents an personalized recommend-ation model to recommend potentially interesting resources to users based on the users' search behaviors and resource properties. This model builds on the user-based collaborative filtering technology and the top-N resource recommending algorithm, which consists of three parts: users' preference description, similar users' calculation and the resource recommending model. Firstly, our model generates users' preference to resources by calculating relevance score between query string and resource, the score of resource owner, the score of resource category and the score of browse sequence. Then it attains similar users by given user through calculated preferences before. Finally, it recommends filtered and sorted resources to users based top-N resource recommendation model. Our recommendation model is proved more accurate than the model purely based on users' search behaviors by the experiments of our paper.
Review in thermal effects on the performance of electric motors

Thermal effects play an important role on the performance of electric motors for the applications in traction/propulsion systems. In these type of applications, there is a feedback loop as well as transients are involved. The torque speed characteristics of the electric motors are dependent upon the motor parameters such as armature/rotor resistance, stator resistance etc. The parameters are significantly affected by the temperature because change in temperature is very high in propulsion systems. As a result, the performance of electric motors used in propulsion systems is degraded. In this paper, the thermal effects on electric motors are combined at one place which is not done before. This will be quite helpful for the researchers of this area to study the thermal effects on the performance of electric motors collectively.
TLR–CD40 Cross-Talk in Anti-Leishmanial Immune Response

Toll-like receptors (TLRs) recognize pathogen-associated molecular patterns (PAMPs) and activate innate immune cells to induce cytokines and co-stimulatory molecules such as CD40 and to enhance antigen presentation to T cells (1) that, upon activation, can either eliminate or support the pathogen (2). Herein, we propose that this duality in TLR functions results from their cross-talk with CD40. While all TLRs enhance CD40 expression, CD40 augments the expression of only TLR9 (3). As both CD40 and TLR9 induce expression of IL-12, a cytokine that induces the IFN-γ secreting Th1 cell differentiation (4), the CD40–TLR9 cross-regulation implies a positive feedback loop. By contrast, TLR1–TLR2 heterodimer down-regulates TLR9 expression (5) and antagonizes the development of Th1 response but favors the differentiation of regulatory T (T-reg) cells (Pandey et al., unpublished observation). Low CD40 expression levels in dendritic cells also promote T-reg cell differentiation (6). This duality can emerge from the sharing of signaling molecules. CD40 induces TRAF6-mediated, ERK-1/2-dependent IL-10 (7), which can inhibit the TLR-induced p38-MAPK activation and IL-12 production, antagonizing Th1 development. CD40-induced TRAF3-dependent p38-MAPK activation (7) can synergize with the TLR-activated p38-MAPK-dependent IL-12 production and Th1 differentiation. Using Leishmania infection, we show that the TLR–CD40 cross-talk can induce contrasting anti-leishmanial immune responses. Leishmania, a protozoan parasite, lives in macrophages. Leishmania expresses lipophosphoglycan (LPG), proteoglycans, flagellin, and profilin for possible recognition by the host cell-expressed TLRs. Recognition of the Leishmania-expressed PAMPs results in differential immune responses, which can either reduce or exacerbate Leishmania infection. As TLRs modulate the expression of CD40, a co-stimulatory molecule whose expression levels modulate anti-leishmanial T cell responses, we propose that TLR–CD40 cross-talk significantly regulate the outcome of an anti-leishmanial immune response.
Interactive Learning Objects in Mobile E-Learning

Cooperation and interaction between learners are important aspects especially for mobile E-Learning scenarios. The requirement of mobility raises the need for innovative CSCL applications as it increases the complexity of the architecture of such systems. Current solutions, commonly web-based, do not satisfy all needs of mobile E-Learning. Motivated by practical approaches and focused on interactive learning-objects we will present an architecture for an ELearning system that fits the needs of mobile E-Learning environments.
Analysis of genetic population structure in Acacia caven (Leguminosae, Mimosoideae), comparing one exploratory and two Bayesian-model-based methods

Bayesian clustering as implemented in STRUCTURE or GENELAND software is widely used to form genetic groups of populations or individuals. On the other hand, in order to satisfy the need for less computer-intensive approaches, multivariate analyses are specifically devoted to extracting information from large datasets. In this paper, we report the use of a dataset of AFLP markers belonging to 15 sampling sites of Acacia caven for studying the genetic structure and comparing the consistency of three methods: STRUCTURE, GENELAND and DAPC. Of these methods, DAPC was the fastest one and showed accuracy in inferring the K number of populations (K = 12 using the find.clusters option and K = 15 with a priori information of populations). GENELAND in turn, provides information on the area of membership probabilities for individuals or populations in the space, when coordinates are specified (K = 12). STRUCTURE also inferred the number of K populations and the membership probabilities of individuals based on ancestry, presenting the result K = 11 without prior information of populations and K = 15 using the LOCPRIOR option. Finally, in this work all three methods showed high consistency in estimating the population structure, inferring similar numbers of populations and the membership probabilities of individuals to each group, with a high correlation between each other.