Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel architecture and algorithm for web page change detection

Internet is used for exchange of information; subsequently people upload and update web pages and information on constant basis. Due to rapid changes in the content of the web pages it has become very necessary to develop a system which can detect recurrent changes in the minimum browsing time. This paper has devised algorithm for structural changes and defines a text code formula to detect the content changes and also represents Architecture for web page change detection system. Analysis and comparison of various web page change detection algorithms based on various parameters to find out strengths and weaknesses for detecting the changes of web pages is also one of the important features highlighted through this paper.
Research Statement Rational Secret Sharing

My primary interest is in the applicability of probabilistic methods and ideas to a wide range of problems in theoretical computer science. My main research focus until 2008 was in the areas of Learning Theory and Online Optimization, and the major part of my work in these areas was the basis of my Ph.D. thesis. I have also, in the past, done some work in the areas of Fair Division algorithms and understanding Information Markets, (the latter as an summer intern at Yahoo! Research Labs) both areas which I still find interesting, but in which I am not currently active. After receiving my Ph.D. I took a two year long break from academic research to spend time with my daughter, who was born in Fall 2008. Although I tried to keep abreast, by attending seminars and talks whenever possible, I did not participate in any research activities during this time. Starting in Fall 2010, I have once again started to actively think about research problems. In particular, in addition to revisiting my interest in Learning Theory, I have also become interested in a couple of new areas, and have some ongoing collaborations on questions in these fields. The first of these is Rational Secret Sharing, which a problem in distributed computing in a game theoretic setting, on which I have some recent results with Prof. Jared Saia and a couple of his students at the University of New Mexico. The other area that I have recently taken an interest in is phase transitions for random instances of combinatorial problems. Here too, I have some recent results in collaboration with Prof. Cris Moore. In the following sections I will describe my work in these different areas in some detail, and I will also mention some ongoing work and ideas for future projects.
Twelve years of repeated wild hog activity promotes population maintenance of an invasive clonal plant in a coastal dune ecosystem

Abstract Invasive animals can facilitate the success of invasive plant populations through disturbance. We examined the relationship between the repeated foraging disturbance of an invasive animal and the population maintenance of an invasive plant in a coastal dune ecosystem. We hypothesized that feral wild hog (Sus scrofa) populations repeatedly utilized tubers of the clonal perennial, yellow nutsedge (Cyperus esculentus) as a food source and evaluated whether hog activity promoted the long‐term maintenance of yellow nutsedge populations on St. Catherine's Island, Georgia, United States. Using generalized linear mixed models, we tested the effect of wild hog disturbance on permanent sites for yellow nutsedge culm density, tuber density, and percent cover of native plant species over a 12‐year period. We found that disturbance plots had a higher number of culms and tubers and a lower percentage of native live plant cover than undisturbed control plots. Wild hogs redisturbed the disturbed plots approximately every 5 years. Our research provides demographic evidence that repeated foraging disturbances by an invasive animal promote the long‐term population maintenance of an invasive clonal plant. Opportunistic facultative interactions such as we demonstrate in this study are likely to become more commonplace as greater numbers of introduced species are integrated into ecological communities around the world.
Metric-based evaluation of graphical user interfaces: model, method, and software support

Many factors contribute to ensuring User eXperience (UX) of Graphical User Interfaces, such as, but not limited to: usability, fun, engagement, subjective satisfaction. Aesthetics is a potential element that could also significantly contribute to this user experience. Although aesthetics have been extensively discussed, there is a need to rely on a sound, empirically validated methodology in order to properly evaluate how aesthetics could be measured, namely through metrics. Two main issues need to be addressed: the representativeness and the relevance of aesthetics metrics. In order to address these challenges, this paper introduces a methodology for metric-based evaluation of a graphical user interface of any type. This methodology is based on an underlying model that captures aesthetics aspects and related metrics, a method for computing them based on the underlying model, and software that supports enacting this method on any type of graphical user interface.
A STATISTICAL ANALYSIS OF PRODUCTION SCHEDULING SYSTEMS

This paper is concerned with the scheduling of a number of jobs to be processed on various machines. Due to its combinatorial nature, economical solutions to most scheduling problems have not yet been attained, even though computational abilities are increasing concomitantly with the development of more powerful and faster computers. A statis­ tical analysis in which the original problem is decomposed into a series of smaller subproblems, has been carried out. Each of these problems is solved, and their solutions are combined together to form a decom­ position solution of the original problem. Considerable experimentation has been conducted to study the statistical effects of decomposition solutions. The hypotheses which have been tested are: (1) the distribu­ tion of the schedule times shifts toward the optimal as the number of jobs in each subproblem, K, increases; (2) the decomposition solution is improved as K increases; and (3) the computation time required to obtain a decomposition solution decreases as K increases. These hypotheses are verified using a statistical test.
Combining Microarray‐based Genomic Selection (MGS) with the Illumina Genome Analyzer Platform to Sequence Diploid Target Regions

Novel methods of targeted sequencing of unique regions from complex eukaryotic genomes have generated a great deal of excitement, but critical demonstrations of these methods efficacy with respect to diploid genotype calling and experimental variation are lacking. To address this issue, we optimized microarray‐based genomic selection (MGS) for use with the Illumina Genome Analyzer (IGA). A set of 202 fragments (304 kb total) contained within a 1.7 Mb genomic region on human chromosome X were MGS/IGA sequenced in ten female HapMap samples generating a total of 2.4 GB of DNA sequence. At a minimum coverage threshold of 5X, 93.9% of all bases and 94.9% of segregating sites were called, while 57.7% of bases (57.4% of segregating sites) were called at a 50X threshold. Data accuracy at known segregating sites was 98.9% at 5X coverage, rising to 99.6% at 50X coverage. Accuracy at homozygous sites was 98.7% at 5X sequence coverage and 99.5% at 50X coverage. Although accuracy at heterozygous sites was modestly lower, it was still over 92% at 5X coverage and increased to nearly 97% at 50X coverage. These data provide the first demonstration that MGS/IGA sequencing can generate the very high quality sequence data necessary for human genetics research.
Yet another bidirectional algorithm for shortest paths

For finding a shortest path in a network the bidirectional~A* algorithm is a widely known algorithm. An A* instance requires a heuristic estimate, a real-valued function on the set of nodes. %This algorithm distinguishes between the main phase and the postprocessing phase. %As long as the search processes of the two sides do not meet, we are in the main phase. %As soon as a meeting point is obtained, the post-phase is in progress. \\\\ The version of bidirectional~A* that is considered the most appropriate in literature hitherto, uses so-called balanced heuristic estimates. This means that the two estimates of the two directions are in balance, i.e., their sum is a constant value. In this paper, we do not restrict ourselves any longer to balanced heuristics. A generalized version of bidirectional A* is proposed, where the heuristic estimate does not need to be balanced. This new version turns out to be faster than the one with the balanced heuristic.
Notice of RetractionAn optimal routing strategy based on random-walk betweenness

A new routing strategy is proposed to improve the transportation efficiency. Instead of using the routing strategy for shortest path and efficient path, we give a generalized routing algorithm to find the so-called optimal path, which considers the modified betweenness measure based on random-walk. It can effectively balance the traffic loads between central nodes and other noncentral nodes. Simulation results indicate that compared with the classic routing strategy, the new strategy can improve the network capability in processing traffic several times while does not increase path length too much.
Functional magnetic resonance imaging investigation of the amphetamine sensitization model of schizophrenia in healthy male volunteers.

CONTEXT Recent work suggests that the amphetamine sensitization model of schizophrenia can safely be induced in healthy volunteers and is associated both with behavioral and dopaminergic hypersensitivity to amphetamine. However, the effects of a sensitization on brain function remain unclear. OBJECTIVE To assess the impact of a sensitizing dosage regimen of dextroamphetamine on human cortical functioning and cognition. DESIGN Randomized, double-blind, parallel-groups design using pharmacological functional magnetic resonance imaging. SETTING The neuroimaging research unit at the Institute of Psychiatry, King's College London, London, England. PARTICIPANTS Healthy male volunteers (n = 22). INTERVENTIONS Dextroamphetamine (20 mg) or placebo administration at 4 testing sessions, using a dosage regimen shown to induce sensitization (ie, 3 doses administered with a 48-hour interdose interval and a final dose after a 2-week washout period). MAIN OUTCOME MEASURES Sensitization was characterized by enhanced subjective response to the drug, changes in behavioral performance (reaction time and accuracy), and functional magnetic resonance imaging measurements of brain activity during an N-back working memory task. RESULTS Sensitization was associated with more rapid responding during the performance of an intermediate-load working memory challenge. During a high-load cognitive challenge, sensitization did not produce performance deficits, but functional magnetic resonance imaging showed hyperactivity of the dorsolateral prefrontal cortex and aberrant recruitment of the superior temporal gyrus, caudate nucleus, and thalamus. Furthermore, the change in striatal activity was negatively correlated with the enhanced subjective effects of the drug, whereas prefrontal hyperactivity was positively correlated with sensitized measures of alertness. CONCLUSIONS These transient load-dependent abnormalities of frontal and temporal activity induced by amphetamine sensitization support neuroimaging findings in schizophrenic patients, implying that amphetamine sensitization may help to bridge pathophysiological theories of schizophrenia that focus on pharmacological (dopaminergic) and cognitive mechanisms, respectively.
HTB based packet scheduler for cloud computing

Cloud computing is Internet - connected mode of supercomputing. In cloud computing all the resources are provided as service that causes high traffic on cloud. So an efficient traffic management mechanism is required for cloud environment. Hierarchical link sharing algorithms like HTB (Hierarchical Token Bucket) are suitable for cloud traffic management, because each class in HTB can borrow bandwidth from its parent. But the sequential HTB can afford only low speeds (0.5Gbps). For better performance, HTB can be parallelized to reduce concurrency in HTB key structure access. This parallel HTB could not only increase the processing rate, but also keep a well performance on stability. In this paper, we propose an adaptive bandwidth management mechanism based on parallelized version of HTB. This packet scheduler uses inference mechanism to identify the bandwidth requirement and allocate bandwidth dynamically. Finally, we evaluate the effectiveness of the proposed scheme through extensive simulation studies.
Fast, accurate, and robust self-localization in polygonal environments

Self-localization is important in almost all robotic tasks. For playing an aesthetic and effective game of robotic soccer, self-localization is a necessary prerequisite. When we designed our robotic soccer team for RoboCup'98, it turned out that all existing approaches did not meet our requirements of being fast, accurate, and robust. For this reason, we developed a new method, which is presented and analyzed in the paper We additionally present experimental evidence that our method outperforms other methods in the RoboCup environment.
Separability of a Random Graph and Applications

‘Separator’ based divide and conquer algorithms have been used to solve many computational problems successfully ([10],[13], etc.) These algorithms perform very well when the ‘separator size’ is small. An interesting question is: ‘How well do these algorithms function on arbitrary instances of the problem (for which we may have no knowledge about the separability of the underlying graphs)? ’ This paper provides answers to this question. In particular, we give tight bounds for the ‘separability’ of a random graph. We then use these bounds to analyze the expected behavior of separator based algorithms for three different problems namely 1) Combinatorial Optimization, 2) Matrix Inversion and related problems, and 3) Satisfiability. There are two popular models of a random graph and the one we employ in this paper assumes that each possible edge in the graph occurs independently with a specified probability, say p. A member in this model is denoted as Gp. We derive optimal bounds for the separability of Gp. In particular we prove that almost all Gps with n nodes are n − θ(1/p) separable. We apply these separability results to analyze the expected performance of the best known algorithms for three important computational problems. The ‘separability’ bounds we derive in this paper are of independent interest and have the potential of finding other applications. The first problem we consider is combinatorial optimization. Simulated Annealing is a family of randomized algorithms used to solve many combinatorial optimization problems. In practice they have been applied to solve some presumably hard (e.g., NPcomplete) problems. The level of performance obtained has been promising [6, 2, 7, 17]. The success of this heuristic technique has motivated analysis of this algorithm from a theoretical point of view. In particular, people have looked at the convergence of this algorithm. They have shown (see e.g., [12]) that this algorithm converges in the limit to a globally optimal solution with probability 1. However few of these convergence results specify a time limit within which the algorithm is guaranteed to converge (with some high probability, say). Also, these proofs hold for only certain restricted classes of ‘annealing schedules’. We present a simple analysis of SA that will provide a time bound for convergence with overwhelming probability. The analysis will hold no matter what annealing schedule is used. Convergence of Simulated Annealing in the limit will follow as a corollary to our time convergence proof. In this paper we also look at optimization problems for which the cost function has some special properties. In a pioneering work, Rajasekaran and Reif [15] presented ‘Nested Annealing’, a heuristic algorithm similar to Simulated Annealing, which prov-
Growth, Inequality, and Social Welfare: Cross-Country Evidence

Social welfare functions that assign weights to individuals based on their income levels can be used to document the relative importance of growth and inequality changes for changes in social welfare. In a large panel of industrial and developing countries over the past 40 years, most of the cross-country and over-time variation in changes in social welfare is due to changes in average incomes. In contrast, the changes in inequality observed during this period are on average much smaller than changes in average incomes, are uncorrelated with changes in average incomes, and have contributed relatively little to changes in social welfare.
Representing the UMLS as an OODB: Modeling Issues and Advantages

Objective: The Uniied Medical Language System (UMLS) designed by NLM combines many well established authoritative medical informatics terminologies in one knowledge representation system. Such a resource is very valuable to the healthcare community and industry. However, the UMLS is very large and complex and poses serious comprehension problems for users and maintenance personnel. We present a representation to support the comprehension and navigation of the UMLS. components of the UMLS, the Metathesaurus and the Semantic Network, as a uniied system. The semantic types of the Semantic Network are modeled as semantic type classes. Intersection classes are deened to model concepts of multiple semantic types which are removed from the semantic type classes. Results: We present examples of how the intersection classes help expose omissions of concepts , highlight errors of semantic type classiication, and uncover ambiguities of concepts in the UMLS. The resulting UMLS OODB schema is deeper and more reened than the Semantic Network since intersection classes are introduced. The Metathesaurus is classiied into a larger number of mutually exclusive, uniform sets of concepts. The schema improves the comprehension and navigation of the Metathesaurus. Conclusions: The UMLS OODB schema supports the comprehension and navigation of the Metathesaurus. It also supports exposing and resolving modeling problems in the UMLS.
A Novel Approach for Detection of Fingerprint by Constructing Relational Graph using Singular Points

Fingerprint is the dominant trait between different biometrics like iris, retina, and face. A fingerprint is the pattern of ridges and valleys on the surface on a fingertip. Now days itself this method is very powerful because of their immutability and uniqueness of patterns . immutability means the patterns by ridges and valleys are permanent and unchanged. Many techniques have been proposed for pattern recognition in fingerprint, most of them being based on minutiae and singular point. In the singular points method we are extracting the core, delta, arch and whorl points. In human fingerprint, it may contain more than one core point or delta point by . By using these points we can construct a graphical shape that is used for fingerprint identification. So the whole image storing in database is replaced by some shape or values. According to the position of each point the graphical shape for each person is different from others, so comparing with this shape can identify each person.
Good Cell , Bad Cell : Classification of Segmented Images for Suitable Quantification and Analysis

While open-source tools exist to automatically segment and track cells in time-lapse microscopy experiments, the resulting output must be inspected to detect and remove spurious artifacts. In addition, data not exhibiting proper experimental controls must be discarded before performing downstream analysis. Currently, the data set is manually examined to accomplish these tasks. Here we present machine learning approaches for classifying the suitability of data traces for downstream processing and analysis. We integrate the most successful approaches into the experimental workflow.
Freedom in geoinformation science and software development : A GRASS GIS contribution

Over the past decade geoinformation field has evolved from a highly specialized niche to a technology with broad impact on society and its interaction with nature. Geographic Information Systems (GIS) applications now range from simple navigation to critical and extremely complex tasks, such as prediction and management of natural disasters. Due to the increased use of GPS, faster access to georeferenced data, expanding field of remote sensing and real-time monitoring, GIS technology is entering many new disciplines and industries and GIS is becoming a part of general computational infrastructure. It is therefore natural that geospatial tools are being developed also within the Open Source and Free Software community [60]. Several important trends can be identified in the current development of geospatial technology:
An unsupervised method for learning to track tongue position from an acoustic signal.

A procedure for learning to recover the relative positions of the articulators from speech signals is demonstrated. The algorithm learns without supervision, that is, it does not require information about which articulator configurations created the acoustic signals in the training set. The procedure consists of vector quantizing short time windows of a speech signal, then using multidimensional scaling to represent quantization codes that were temporally close in the encoded speech signal by nearby points in a continuity map. Since temporally close sounds must have been produced by similar articulator configurations, sounds which were produced by similar articulator positions should be represented close to each other in the continuity map. Using an articulatory speech synthesizer to produce acoustic signals from known articulator positions, relative articulator positions were estimated from synthesized acoustic signals and compared to the synthesizer’s actual articulator positions. High rank‐order correl.
A discriminant analysis of social and psychological factors influencing fishing participation

Lake Ontario, one of North America? s Great Lakes, provides coastal residents of New York State with a sportfishery integral to both local traditions and the economy. Recent and projected declines in the number of state residents fishing Lake Ontario have generated concerns among fishery managers and business owners. In order to identify management and marketing strategies that can be used to increase fishing participation, an understanding of the influence of social and psychological factors on participation during childhood, adolescence, and adulthood is needed. Examination of both existing angler market groups (e.g., males) and market groups with growth potential (e.g., females) could provide further insight into increasing participation. This study identifies the social and psychological factors that influenced fishing participation for a sample of 1,050 Lake Ontario anglers (i.e., 525 males and 525 females). A mail survey, based on the elements included in a wildlife recreation involvement model by Decker et al. (1987), was conducted in 2001. Discriminant analysis was used to quantify the influence of these elements on fishing participation for males and females during childhood, adolescence, and adulthood. Elements identified as strongly influencing fishing participation for both males and females were opportunity, perceived ability, and fishing-related customs during childhood; affiliation, opportunity, and commitment during adolescence; and affiliation and commitment during adulthood. Based on study results, management and marketing strategies for increasing fishing participation were developed.