Miracle-dz/UniFAR-FTUs huggingface dataset:
Defeating the Homogeneity Assumption

The statistical NLP and IR literatures tend to make a “homogeneity assumption” about the distribution of terms, either by adopting a “bag of words” model, or in their treatment of function words. In this paper we develop a notion of homogeneity detection to a level of statistical significance, and conduct a series of experiments on different datasets, to show that the homogeneity assumption does not generally hold. We show that it also does not hold for function words. Importantly, datasets and document collections are found not to be neutral with respect to the property of homogeneity, even for function words. The homogeneity assumption is defeated substantially even for collections known to contain similar documents, and more drastically for diverse collections. We conclude that it is statistically unreasonable to assume that word distribution within a corpus is homogeneous. Because homogeneity findings differ substantially between different collections, we argue for the use of homogeneity measures as a means of profiling datasets.
A Degree of Practical Wisdom: The Ratio of Educational Debt to Income as a Basic Measurement of Law School Graduates’ Economic Viability

This article evaluates the economic viability of a student’s decision to borrow money in order to attend law school. For individuals, firms, and entire nations, the ratio of debt to income serves as a measure of economic stability. The ease with which a student can carry and retire educational debt after graduation may be the simplest measure of educational return on investment.Mortgage lenders evaluate prospective borrowers' debt-to-income ratios. The spread between the front-end and back-end ratios in mortgage lending provides a basis for extrapolating the maximum amount of educational debt that a student should incur. Any student whose debt service exceeds the maximum permissible spread between mortgage lenders' front-end and back-end ratios will not be able to buy a house on credit.These measures of affordability suggest that the maximum educational back-end ratio (EBER) should fall in a range between 8 and 12 percent of monthly gross income. Four percent would be even better. Other metrics of economic viability in servicing educational debt suggest that the ratio of total educational debt to annual income (EDAI) should range from an ideal 0.5 to a marginal 1.5. EBER and EDAI are mathematically related ways of measuring the same thing: a student's ability to discharge educational debt through enhanced earnings. This article offers guidance on the use of these debt-to-income ratios to assess the economic viability of students who borrow money in order to attend law school.
Accent identification

Foreign accent identification is a new challenging problem closely related to other relatively recent fields of the multilingual area such as dialect identification and language identification. The paper describes an automatic identification system for English accents from 6 different European countries. The approach is based on a parallel set of ergodic nets with context independent HMM units. The ergodic topology was also substituted by pronunciation transcription constraints in order to integrate accent specific automatic word recognisers. Considering the complexity of the task, the results can be considered encouraging for further research.
An Optimal Approach to Fault Tolerant Software Systems Design

A systematic method of providing software system fault recovery with maximal fault coverage subject to resource constraints of overall recovery cost and additional fault rate is presented. This method is based on a model for software systems which provides a measure of the fault coverage properties of the system in the presence of computer hardware faults. Techniques for system parameter measurements are given. An optimization problem results which is a doubly-constrained 0,1 Knapsack problem. Quantitative results are presented demonstrating the effectiveness of the approach.
A 0.65V embedded SDRAM with smart boosting and power management in a 45nm CMOS technology

In this paper, an embedded SDRAM (eSDRAM) with smart boosting and power management (SB-PM) scheme for low power operation has been designed. SB-PM scheme decreases 40.3% of dynamic power and 69.1% of standby power consumption with ECC compared with the conventional scheme. A 266-Mb eSDRAM with SB-PM scheme is designed in a 45-nm CMOS technology showing 51.2-mW dynamic power and 2.05mW standby power consumption at VDD=0.65V and 85°C.
Measuring Cerebral Blood Flow Using Magnetic Resonance Imaging Techniques

Accepted February 9, 1999. Supported by the Wellcome Trust. Address correspondence and reprint requests to Dr. Robert Turner, Wellcome Department of Cognitive Neurology. Institute of Neurology, University College London, 12 Queen Square. London WCIN 3BG, United Kingdom. Abbreviations used: ACZ, acetazolamide; ADC, apparent diffusion coefficient; AIF. arterial input function; ASL, arterial spin labeling; BASE. basis selective inversion; B AT, bolus arrival time; BBB, blood­ brain barrier; B OLD. blood oxygenation level-dependent; CASL. con­ tinuous arterial spin labeling; CBV. cerebral blood volume; OSC. dy­ namic susceptibility contrast; OWl. diffusion-weighted imaging; EPI, echo planar imaging; EPISTAR. echo planar imaging and signal tar­ geting with alternating radiofrequency; fMRI. functional magnetic resonance imaging; FAIR, flow-sensitive alternating inversion recov­ ery; FAIRER, flow-sensitive alternating inversion recovery excluding radiation damping; GE. gradient-echo; rCA. internal carotid artery; MCA, middle cerebral artery; MCAO, middle cerebral artery occlu­ sion; MP, maximum peak; MR, magnetic resonance; MRI. magnetic resonance imaging; MT, magnetization transfer; MTT. mean transit time; PARIS, perfusion assessment by repetitive inversion of spins; PASL. pulsed arterial spin labeling; PET, positron emission tomogra­ phy; QUIPSS. quantitative imaging of perfusion using a single sub­ traction; RF. radiofrequency; rCBF. regional cerebral blood flow; rel­ CBF. relative cerebral blood flow; reICBV. relative cerebral blood volume; ROI, region of interest; rt-PA, recombinant tissue plasminogen activator; SE, spin-echo; SMART, simultaneous multislice acquisition with arterial flow tagging; S NR. signal-to-noise ratio; SPECT, single photon emission computed tomography; STAR-HASTE. signal target­ ing alternating radiofrequency-half fourier single shot turbo spin echo; TE. echo time; TILT. magnetization transfer insensitive labeling tech­ nique; TTP. time to peak; VOl. volume of interest.
Spoken dialog strategy based on understanding graph search

We regarded information retrieval as a graph search problem and proposed several novel dialog strategies that can recover from misrecognition through a spoken dialog that traverses the graph. To recover from misrecognition without seeking confirmation, our system kept multiple understanding hypotheses at each turn and searched for a globally optimal hypothesis in the graph whose nodes express understanding states across user utterances in a whole dialog. As for a dialog strategy, we introduced a new criterion based on efficiency in information retrieval and consistency with understanding hypotheses to select an appropriate system response. Using such criterion, the system removes the ambiguity so that users do not feel that a response that conflicts with the actual user intent is unnatural. We developed a spoken dialog system using these techniques and showed dialog examples in which misrecognition was naturally corrected. We also showed that our strategy was efficient in terms of the number of turns.
High-dynamic-range infrared image enhancement and hardware design

A new technique for the display of high-dynamic-range infrared images is presented in this paper, which reduces the dynamic range while preserving details. It is based on a two-scale decomposition of the image into a base layer and a detail layer . The base layer is obtained using an edge-preserving filter called the bilateral filter. We discuss the different characteristics between Gaussian filter and bilateral filter in filtering noise and edges. Then we present the technique of histogram projection based on the information of histogram. The proposed design is a combination of bilateral filter and histogram projection. And that is suitable for FPGA to map the 14-bit infrared image data to 8-bit values for display. This kind of technique has considered infrared image characteristic and vision characteristic of the human eye synthetically, and guarantees real-time character of image process, at the same time, also give consideration to the advantage of the FPGA design.
Neural Networks With Real Weights: Analog Computational Complexity

We pursue a particular approach to analog computation, based on dynamical systems of the type used in neural networks research. Our systems have a xed structure, invariant in time, corresponding to an unchanging number of \neurons". If allowed exponential time for computation, they turn out to have unbounded power. However, under polynomial-time constraints there are limits on their capabilities, though being more powerful than Turing Machines. (A similar but more restricted model was shown to be polynomial-time equivalent to classical digital computation in the previous work 17].) Moreover, there is a precise correspondence between nets and standard non-uniform circuits with equivalent resources, and as a consequence one has lower bound constraints on what they can compute. This relationship is perhaps surprising since our analog devices do not change in any manner with input size. We note that these networks are not likely to solve polynomially NP-hard problems, as the equality \p = np " in our model implies the almost complete collapse of the standard polynomial hierarchy. In contrast to classical computational models, the models studied here exhibit at least some robustness with respect to noise and implementation errors. ABSTRACT We pursue a particular approach to analog computation, based on dynamical systems of the type used in neural networks research. Our systems have a xed structure, invariant in time, corresponding to an unchanging number of \neurons". If allowed exponential time for computation, they turn out to have unbounded power. However, under polynomial-time constraints there are limits on their capabilities, though being more powerful than Turing Machines. (A similar but more restricted model was shown to be polynomial-time equivalent to classical digital computation in the previous work 17].) Moreover, there is a precise correspondence between nets and standard non-uniform circuits with equivalent resources, and as a consequence one has lower bound constraints on what they can compute. This relationship is perhaps surprising since our analog devices do not change in any manner with input size. We note that these networks are not likely to solve polynomially NP-hard problems, as the equality \p = np " in our model implies the almost complete collapse of the standard polynomial hierarchy. In contrast to classical computational models, the models studied here exhibit at least some robustness with respect to noise and implementation errors.
Low dimensional discriminant loci and scrolls

Smooth complex polarized varieties $(X,L)$ with a vector subspace $V \subseteq H^0(X,L)$ spanning $L$ are classified under the assumption that the locus ${\Cal D}(X,V)$ of singular elements of $|V|$ has codimension equal to $\dim(X)-i$, $i=3,4,5$, the last case under the additional assumption that $X$ has Picard number one. In fact it is proven that this codimension cannot be $\dim(X)-4$ while it is $\dim(X)-3$ if and only if $(X,L)$ is a scroll over a smooth curve. When the codimension is $\dim(X)-5$ and the Picard number is one only the Pl\"ucker embedding of the Grassmannian of lines in $\Bbb P^4$ or one of its hyperplane sections appear. One of the main ingredients is the computation of the top Chern class of the first jet bundle of scrolls and hyperquadric fibrations. Further consequences of these computations are also provided.
Evolution of a robotic soccer player

Robotic soccer is a complex domain where, rather than hand-coding computer programs to control the players, it is possible to create them through evolutionary methods. This has been successfully done before by using genetic programming with high-level genes. Such an approach is, however, limiting. This work attempts to reduce that limit by evolving control programs using genetic programming with low-level nodes.
CHANGING AMERICA: THE IMPACT OF IMMIGRATION ON WELFARE ATTITUDES AND WELFARE REFORM

OF DISSERTATION CHANGING AMERICA: THE IMPACT OF IMMIGRATION ON WELFARE ATTITUDES AND WELFARE REFORM The purpose of my dissertation is to further our understanding of why some states restricted immigrant access to welfare in the 1990s while other states granted immigrants access to social programs. With the passage of the Personal Responsibility Work Opportunity Reconciliation Act (PRWORA), many states diverged from equal access to welfare programs, such as Temporary Assistance to Needy Families (TANF), for immigrants arriving after 1996. Very little scholarly work examines the variance in immigrants’ access to welfare programs. Current research studying welfare attitudes and policy has largely failed to investigate whether and how the influx of immigrants over the last three to four decades has decreased public support for welfare programs and resulted in policies that both decrease benefit levels and restrict access to programs based on citizenship. This is a serious shortcoming because immigration since the 1970s represents the largest population shift since the early 20 century, a change that has increased the size of the underclass and transformed the cultural and racial makeup of the United States. Accordingly, in my dissertation, I will examine how changes to the American political environment, immigration levels and the increasing number of immigration media stories, trigger authoritarian attitudes that in turn form a breeding ground supporting restrictive welfare programs. The results from the individual-level analysis provide strong evidence that authoritarians prefer less welfare spending, fewer immigrants, and a waiting period before immigrants can access welfare programs. In addition, authoritarians view immigrants as a threat due to their perceived failure to socially conform to American society. Building on these individual-level results, I find that states with large authoritarian populations are more likely to adopt restrictive welfare policies. Jason E. Kehrberg March 30, 2013
New Genetic Operator (Jump Crossover) for the Traveling Salesman Problem

Inspired by nature, genetic algorithms (GA) are among the greatest meta-heuristics optimization methods that have proved their effectiveness to conventional NP-hard problems, especially the traveling salesman problem (TSP) which is one of the most studied supply chain management problems. This paper proposes a new crossover operator called Jump Crossover (JMPX) for solving the travelling salesmen problem using a genetic algorithm (GA) for near-optimal solutions, to conclude on its efficiency compared to solutions quality given by other conventional operators to the same problem, namely, Partially matched crossover (PMX), Edge recombination Crossover (ERX) and r-opt heuristic with consideration of computational overload. The authors adopt a low mutation rate to isolate the search space exploration ability of each crossover. The experimental results show that in most cases JMPX can remarkably improve the solution quality of the GA compared to the two existing classic crossover approaches and the r-opt heuristic.
Robust, parameter insensitive position sensorless field orientation control of the induction machine

A physical approach is employed to estimate the rotor flux for a position sensorless induction machine drive system. This approach is based on the fundamental operating characteristics of the induction machine. The estimator structure calculates the rotor flux accurately at low speeds, and is largely insensitive to parameter variations. System structure, theoretical analysis, simulation, and laboratory results are presented. <<ETX>>
Paper stitching using maximum tolerant seam under local distortions

Paper stitching technology can reconstruct a whole paper page from two sub-images separately scanned from a camera with limited vision field. Traditional technology usually chooses a global optimal seam, and the two sub-images are stitched along it. These methods perform well on the rigid object, but when distortion exists caused by the uneven placement of paper, local contents of two sub-images may be upside-down and their positions are misaligned. Although some methods choose two matching seams on each sub-image, they use either the local patch similarity or the global consistent constraint to get two matching seams. However, only the local matching may lead to stitching failure when wrong matching occurs at the local patch, while only the global constraint usually suffers from inaccuracy of the stitching result. After the two seams are obtained, the traditional methods usually construct the whole image through global transformation along the seams, and image deformation usually occurs in this stage. In this paper, we proposed a robust estimation algorithm to get the matched seams in the sub-images, and stitched the sub-images with a maximum tolerance to conquer the image deformation. Finally a whole image with a smooth stitching seam and the minimum deformation is generated. Experimental results show that this new paper stitching method can produce better results than state-of-arts methods even under challenging scenarios such as large distortion and large contrast difference.
Pulsewidth Modulation Technique for BLDCM Drives to Reduce Commutation Torque Ripple Without Calculation of Commutation Time

This paper presents a three-phase pulsewidth modulation (PWM) technique for brushless dc motor (BLDCM) drives to reduce the commutation torque ripple. As compared to previous approaches, the presented technique does not require any torque observer and calculation of commutation time which may be sensitive to motor parameters and may require more calculation time. The commutation time for the presented technique is determined by a detection circuit which consists of simple comparator circuit. The experimental results derived from a field programmable gate array based controlled BLDCM drive show that the commutation current ripple can be significantly reduced by the presented PWM technique.
DISTRIBUTED FAULT-TOLERANT ROUTING IN A HYPERCUBE

A ABSTRACT connected hypercube containing faulty nodes/links is called an injured hypercube, f whereas a hypercube without faulty components is called a healthy hypercube. To allow non-aulty nodes in an injured hypercube to communicate with one another, each hypercube node has to be equipped with enough information so as to make correct routing decisions, and 1 y c update the information whenever the network condition changes. Obviously, it will be ver ostly for each node to keep and update complete information of the entire hypercube, i although, in that case, routing decisions will always be correct. Instead, we would like to ncorporate only minimal information into each node that is necessary for correct routing decisions. We propose two fault-tolerant routing schemes for hypercube computers, each of which f i differs in the amount of information kept in each node. The tradeoff between the amount o nformation kept in each node and the routing efficiency are analyzed. The region in which all c nodes must be informed about a component failure in order to route messages successfully is alled the influence zone of the failure. We show that the influence zone of a failure depends z on the network condition in the vicinity of the failed component, and the size of the influence one is usually fairly small relative to the size of the entire hypercube. Thus, each node needs f m to be equipped with only a small amount of global information for the successful routing o essages. Any opinions, findings, and conclusions or recom endations expressed in this publication are those of the authors and do not necessarily reflect the view of the ONR. A routing decision by a node is said to be correct if it allows each message to be delivered successfully from the node to any other node.
Context-aware autonomic systems in real-time applications: Performance evaluation

Nowadays one can observe rapid development of various technologies supporting autonomie features and context-awareness of pervasive systems. And this is perfectly understandable as these features effectively increase the systems autonomicity. However, in the case of safety-critical realtime systems it becomes crucial to determine how the entire system performance is affected by the growth in complexity of its autonomie / dynamic decision making engine which is processing the context information for control purposes. In this paper we consider policy-based computing as a candidate technology to support selected autonomie features and context-awareness in safety-critical systems. We conduct performance analysis in a generic policy-supervised system in order to determine the relation between policy complexity (reflecting decision making system complexity) and the decision evaluation time (affecting the entire system performance). We present a coherent characteristic polynomial method as a means of pre-estimation of policy evaluation time depending on its complexity. The results we present can be potentially used for pre-evaluation of whether a policy of a certain complexity level is of any applicability in a safety critical system that has to meet fixed real-time deadlines.
A study of virtualized server usage to support collaborative learning

Virtualized servers are attracting considerable attention in the field of information technology because of the reduction of business costs and number of servers associated with their implementation. However, the types of business applications suitable for virtualization are still unclear. In addition, information systems issues should be considered to be essential for task performance and achieving good business results, besides operating cost efficiency. This paper explores the advantages and disadvantages of the application of server virtualization and service delivery management for the collaborative learning environment. It also describes the use of the web console in the virtual server system in the collaborative learning environment and the management of the information exchange in group learning, conducting to collective knowledge rationalized the capture and delivery of acquired knowledge according to the context of the collaborative learning.