Miracle-dz/UniFAR-FTUs huggingface dataset:
Large-time asymptotics, vanishing viscosity and numerics for 1-D scalar conservation laws

In this paper we analyze the large time asymptotic behavior of the discrete solutions of numerical approximation schemes for scalar hyperbolic conservation laws. We consider three monotone conservative schemes that are consistent with the one-sided Lipschitz condition (OSLC): Lax-Friedrichs, Engquist-Osher and Godunov. We mainly focus on the inviscid Burgers equation, for which we know that the large time behavior is of self-similar nature, described by a two-parameter family of N-waves. We prove that, at the numerical level, the large time dynamics depends on the amount of numerical viscosity introduced by the scheme: while Engquist-Osher and Godunov yield the same N-wave asymptotic behavior, the Lax-Friedrichs scheme leads to viscous self-similar profiles, corresponding to the asymptotic behavior of the solutions of the continuous viscous Burgers equation. The same problem is analyzed in the context of self-similar variables that lead to a better numerical performance but to the same dichotomy on the asymptotic behavior: N-waves versus viscous ones. We also give some hints to extend the results to more general fluxes. Some numerical experiments illustrating the accuracy of the results of the paper are also presented.
Resonant states for the static Klein–Gordon–Maxwell–Proca system

We prove the existence of resonant states for the critical static Klein-Gordon-Maxwell-Proca system in the case of closed manifolds. Standing waves solutions with arbitarilly large multi-spikes amplitudes and unstable phases are constructed. We investigate in this paper the existence of resonant states for the electrostatic Klein-Gordon-Maxwell-Proca system in closed manifolds, a massive version of the more traditional electrostatic Klein-Gordon-Maxwell system. The system provides a dualistic model for the description of the interaction between a charged relativistic matter scalar field and the electromagnetic field that it generates. The external vector field (ϕ, A) in the system inherits a mass and is governed by the Proca action which generalizes that of Maxwell. Let (M, g) be a closed three-dimensional Riemannian manifold. Writing the matter scalar field in polar form as ψ(x, t )= u(x, t)e iS(x,t) ,t he
Relational browser + + : An interface for exploring and searching large information collection

The size and breadth of digital government information published on the web (such as the huge amount of statistics data generated by wide range of government agencies) makes it difficult for people to quickly grasp what data is and is not available. Consequently, people usually need an overview of the published information to help them decide if it is worthwhile to look further. As they do look further, it is helpful for their searching and browsing to get an idea of what is in the web site and how many items are available. We believe that users of digital government information will be well-served by highly interactive user interfaces that support alternative views of the information partitions/collections/results sets. The Relation Browser (RB) is such a highly interactive interface for people to explore and search useful information. It has been undergoing development and revision for several years and this paper described the functionality and design process for the most recent version, named RB++. The RB++ provides several interface features to facilitate this process, among which are: 1. global overview of the collection and various partitions within it. 2. highly interactive interface for exploring the collection and items within it. 3. highly interactive and flexible searching utility. 4. Tightly coupling these searching and browsing capabilities.
Finding Repeating Patterns in Acoustic Musical Signals : Applications for Audio Thumbnailing

Finding structure and repetitions in a musical signal is crucial to enable interactive browsing into large databases of music files. Notably, it is useful to produce short summaries of musical pieces, or ”audio thumbnails”. In this paper, we propose an algorithm to find repeating patterns in an acoustic musical signal. We first segment the signal into a meaningful succession of timbres. This gives a reduced string representation of the music, the texture score, which doesn’t encode any pitch information. We then look for patterns in this representation, using two techniques from image processing: Kernel Convolution and Hough Transform. The resulting patterns are relevant to musical structure, which shows that pitch is not the only useful representation for the structural analysis of polyphonic music.
An automatic detection method of mura defects for liquid crystal display using real Gabor filters

Mura is one types of defects on liquid crystal display (LCD), it is difficult to be detected with regular image processing method. As the existing of respective textural background, the texture analysis approach is helpful. In this paper, the real Gabor filer method and its principles of parameters selecting are studied for the Mura detection. First, in the preprocessing, threshold segmentation, geometric operations and gray interpolation are carried out to pick-up the target normal direction of LCD areas. Then, the real Gabor filters are designed through selecting appropriate filtering scale and orientation, detection results show that the structurally textural backgrounds are removed. Finally, experiments show that the performances of Gabor filters are influenced by its parameters such as central frequencies and mask size. Furthermore, by using real Gabor filters instead of complex, large computational load is saved.
Homogeneous region merging approach for image segmentation preserving semantic object contours

Morphological image segmentation is an essential tool for various image analysis tasks. In this paper, we propose two successive region-merging algorithms that mainly aim to represent homogeneous objects simply and clearly. First, we define a marker cluster and extract markers having similar intensity values from each marker cluster. After initial segmentation using the markers, perceptually insignificant small regions are removed to reduce the number of regions based on some heuristics. Then, we classify all regions into three classes according to their homogeneity. Finally, gradient-based region merging is performed for all regions except inhomogeneous regions. Experimental results show that the proposed regionmerging scheme can represent homogeneous objects with few regions while preserving most of the semantic object shapes. Hence, the proposed method can be a useful tool for semantic object segmentation.
Gain Scheduling Control for a Class of Variable Stiffness Actuators Based on Lever Mechanisms

This paper is concerned with the design of a control strategy for variable stiffness actuators in series configuration, exploiting the lever concept to adjust the stiffness at the transmission. A control strategy based on gain scheduling is proposed, which is able to regulate both stiffness and position at output link. The gain scheduling is designed based on a set of linear quadratic regulators (LQRs), because LQR's inherent robustness properties can accommodate significant variation in the actuation plant parameters. The link positioning relies on continuous adjustment of the control effort based on the current transmission stiffness; the stiffness perceived at the output link is regulated through combined action of the transmission stiffness and the positioning gains of the scheduling strategy. The effectiveness of the controller is verified in simulation and experiments on the actuator with adjustable stiffness. The overall strategy has been proven to be locally stable.
Resource allocation issues and challenges in cloud computing

Resource management is the primary issue as the demand grows for provisioning resources and computation in cloud systems. This article presents various research issues pertaining to the management of cloud resources while a comparison is made between existing resource allocation systems. The issues and challenges discussed in this paper are resource provisioning, job scheduling, load balancing, scalability, pricing, energy management and availability.
TelStem : An Unsupervised Telugu Stemmer with Heuristic Improvements and Normalized Signatures

Stemming is a technique for reducing variant forms of a word to their roots (or stems) by enabling extraction of common suffixes. Stem need not correspond to the linguistic root of a word. Stemming is predominantly used in IR system to enrich retrieval effectiveness and to reduce the size of index for information retrieval task. This paper presents a systematic way of algorithm and implementation to develop an unsupervised Telugu stemmer using Take-All-Splits heuristic and improved paradigms. The performance of this stemmer is evaluated by taking two sets of 500 randomly extracted words. The trained Telugu corpus is taken from large set of documents containing 129066 words from CIIL Mysore. The accuracy is found to be 85.40% after applying normalization heuristic. The F-score is 92.94%, the recall is 91.97% and the precision is 96.91%. As the algorithm does not require any language specific information, it can be applied to other languages that are morphologically rich. The percentage reduction in index size for Telugu information retrieval task is also evaluated before and after normalization heuristic.
Nuclear and Chloroplast DNA Variation Provides Insights into Population Structure and Multiple Origin of Native Aromatic Rices of Odisha, India

A large number of short grain aromatic rice suited to the agro-climatic conditions and local preferences are grown in niche areas of different parts of India and their diversity is evolved over centuries as a result of selection by traditional farmers. Systematic characterization of these specialty rices has not been attempted. An effort was made to characterize 126 aromatic short grain rice landraces, collected from 19 different districts in the State of Odisha, from eastern India. High level of variation for grain quality and agronomic traits among these aromatic rices was observed and genotypes having desirable phenotypic traits like erect flag leaf, thick culm, compact and dense panicles, short plant stature, early duration, superior yield and grain quality traits were identified. A total of 24 SSR markers corresponding to the hyper variable regions of rice chromosomes were used to understand the genetic diversity and to establish the genetic relationship among the aromatic short grain rice landraces at nuclear genome level. SSR analysis of 126 genotypes from Odisha and 10 genotypes from other states revealed 110 alleles with an average of 4.583 and the Nei’s genetic diversity value (He) was in the range of 0.034–0.880 revealing two sub-populations SP 1 (membership percentage-27.1%) and SP 2 (72.9%). At the organelle genomic level for the C/A repeats in PS1D sequence of chloroplasts, eight different plastid sub types and 33 haplotypes were detected. The japonica (Nipponbare) subtype (6C7A) was detected in 100 genotypes followed by O. rufipogon (KF428978) subtype (6C6A) in 13 genotypes while indica (93–11) sub type (8C8A) was seen in 14 genotypes. The tree constructed based on haplotypes suggests that short grain aromatic landraces might have independent origin of these plastid subtypes. Notably a wide range of diversity was observed among these landraces cultivated in different parts confined to the State of Odisha.
Determining Mixing Parameters From Multispeaker Data Using Speech-Specific Information

In this paper, we propose an approach for processing multispeaker speech signals collected simultaneously using a pair of spatially separated microphones in a real room environment. Spatial separation of microphones results in a fixed time-delay of arrival of speech signals from a given speaker at the pair of microphones. These time-delays are estimated by exploiting the impulse-like characteristic of excitation during speech production. The differences in the time-delays for different speakers are used to determine the number of speakers from the mixed multispeaker speech signals. There is difference in the signal levels due to differences in the distances between the speaker and each of the microphones. The differences in the signal levels dictate the values of the mixing parameters. Knowledge of speech production, especially the excitation source characteristics, is used to derive an approximate weight function for locating the regions specific to a given speaker. The scatter plots of the weighted and delay-compensated mixed speech signals are used to estimate the mixing parameters. The proposed method is applied on the data collected in actual laboratory environment for an underdetermined case, where the number of speakers is more than the number of microphones. Enhancement of speech due to a speaker is also examined using the information of the time-delays and the mixing parameters, and is evaluated using objective measures proposed in the literature.
Data Selection for Semi-Supervised Learning

The real challenge in pattern recognition task and machine learning process is to train a discriminator using labeled data and use it to distinguish between future data as accurate as possible. However, most of the problems in the real world have numerous data, which labeling them is a cumbersome or even an impossible matter. Semi-supervised learning is one approach to overcome these types of problems. It uses only a small set of labeled with the company of huge remain and unlabeled data to train the discriminator. In semi-supervised learning, it is very essential that which data is labeled and depend on position of data it effectiveness changes. In this paper, we proposed an evolutionary approach called Artificial Immune System (AIS) to determine which data is better to be labeled to get the high quality data. The experimental results represent the effectiveness of this algorithm in finding these data points.
Single Objective Guided Multiobjective Optimization Algorithm

Most of multiobjective optimization algorithms consider multiple objectives as a whole when solving multiobjective optimization problems (MOPs). However, in MOPs, different objective functions may possess different properties. Hence, it can be beneficial to build objective-wise optimization strategy for each objective separately. This paper presents a single objective guided multiobjective optimization (SOGMO) framework to solve continuous MOPs. In SOGMO framework, a solution is first selected from archive, and then objective-wise learning strategy is developed for each objective separately. Finally, all the objectives of the considered solution can be simultaneously optimized in parallel by the cooperation of objective-wise learning process. An instantiation of SOGMO, called SOGMO-NFO, is designed by introducing a neighborhood field optimization (NFO), as objective-wise learning strategy. Simulation results show that SOGMO-NFO outperforms current state-of-the-art multiobjective evolutionary algorithms.
Study of power consumption for high-performance reconfigurable computing architectures

ii ACKNOWLEDGEMENTS I would like to express my sincere gratitude and respect for my committee chairman, Dr. John K. Antonio for his guidance, expertise, and encouragement throughout this research effort and for giving me the opportunity to work with him in the High Performance Computing Laboratory at Texas Tech University. He is a wonderful mentor and friend. I thank Dr. Noe Lopez-Benitez for being on my committee and supporting my efforts throughout my educational career here at Texas Tech University. The work represented in this thesis is largely in part due to the tireless work of my colleagues in the High Performance Computing Laboratory. I wish to thank Tim Osmulski for the amazing work he did with the probabilistic power simulator, Nikhil Gupta and Jeff Muehring for the work they did on the Wild-One and VHDL, and Jack West for the support he has given to the whole lab. Weight, and Power, " contract number F30602-97-2-0297. Without the loving support and caring of my parents, James H. Veale and Carolyn S. Veale, I would have never made it this far in my educational career. They have been there every moment along the way when I needed them the most. I thank them for the countless hours of support and years of growth they have given me. I would also like to thank my brother Jonathan H. Veale who has been a true friend throughout my life.
Critical Reflection and Human Centred Design – the Case of BreastScreen Tasmania

Critically reflecting on qualitative human centred design approaches reveals concerns about the process of translation that occurs between the rich user insights generated in the wild to the systems that are finally built. Implicit techno-centrism inherent within most IS design processes tend to relegate these insights to be mere adjuncts of conventional usability testing and to marginalise opportunities to open up dialogue on new ways of thinking and designing (Gasson, 2003). Drawing on theoretical insights from distributed cognition, user-centred design, customer trajectories and communities of practice this paper presents a research approach adopted to investigate BreastScreen Tasmania in an effort to address these human centred design challenges. Through critical reflection on insights from these multiple perspectives the paper demonstrates the possibility of generating contributions to IS knowledge at substantive, methodological and theoretical levels. Significantly, the paper highlights the need for IS researchers to be more sensitive to the implicit assumption that technology will always be the end-point of their activities and the tendency for judgments about criteria for successful designs to be technologically and/or economically over-determined.
Long-Term Memorarity Analysis of Stock Chaos and Volatility

The stock prices are affected by historical information to a certain extent. The fluctuation volatility can be measured by the Hurst index. With modified rescale range/ standard deviation (R/S) model, this paper presents an analysis of CSI 300 index, coal and oil industry index, and other six individual stocks in different industries for their fluctuation features.
Impact of Obesity on the Expression Profile of Natriuretic Peptide System in a Rat Experimental Model

Natriuretic peptides (NPs) play an important role in obesity and aim of this study was to evaluate, in cardiac tissue of obese Zucker rats (O, n = 29) their transcriptomic profile compared to controls (CO, n = 24) by Real-Time PCR study; CNP protein expression was evaluated by immunostaining and immunometric tests. Myocardial histology was performed, confirming no alteration of organ structure. While ANP and BNP are cardiac peptides, CNP is mainly an endothelial hormone; thus its expression, as well as that of NPR-B and NPR-C, was also evaluated in kidney and lung of an animal subgroup (n = 20). In heart, lower BNP mRNA levels in O vs CO (p = 0.02) as well as ANP and CNP (p = ns), were detected. NPR-B/NPR-A mRNA was similar in O and CO, while NPR-C was numerically lower (p = ns) in O than in CO. In kidney, CNP/NPR-B/NPR-C mRNA was similar in O and CO, while in lung CNP/NPR-C expression decreased and NPR-B increased (p = ns) in O vs CO. Subdividing into fasting and hyperglycemic rats, the pattern of mRNA expression for each gene analyzed remained unchanged. The trend observed in heart, kidney and lung for CNP protein concentrations and immunohistochemistry reflected the mRNA expression. TNF-α and IL-6 mRNA were measured in each tissue and no significant genotype effect was detected in any tissue. The main NP variations were observed at the cardiac level, suggesting a reduced release by cardiac cells. The understanding of mechanisms involved in the modulation of the NP system in obesity could be a useful starting point for future clinical study devoted to identifying new obesity treatment strategies.
Observations on the geometric distribution of micro-structural features in cortical bone

Abstract—This paper reports on observations of the distribution of micro-structural features in a sample of cortical bone (mid-diaphysis femur from bovine). Such features include lacunae, Haversian canals, and canaliculi clusters and are considered, upon bone treatment, to be porosities. Initially, image segmentation was utilized to quantify feature geometric attributes such as area A (μm), perimeter P(μm), elliptical ratio min/maj axis length, and compactness. A center point of the bone cross section was determined from which a polar coordinate system was constructed related to which was a grid containing 25 regions of roughly 500x500 μm in size. Distributions of these features were plotted vs. distal radius and vs. angular positions as measured from the center of the bone. Analyses of the linear trends reveals that all porosity attributes and for all feature types (Haversian canals, and canaliculi clusters) appear to decrease fairly linearly with increasing radius from bone center (p< 0.05%) as the outer perimeter is reached. Also, these features tend to become more round (p< 0.05%) as they get closer to the outer shell. In contrast, the geometric attributes appear to be indifferent vs. the angle.
How early phonological development might set the stage for phoneme awareness.

A recent chapter by Treiman and Zukowski (in press) provides evidence that pre-readers are aware of sublexical units intermediate between the syllable and the phoneme. Whereas four-year old preschoolers can note commonalities in sound only when a full syllable is shared (e.g., entreat/retreat), five-year old kindergartners also demonstrate an ability to group words on the basis of a shared onset or a shared rime (e.g., treat/trick, sack/black). In their study, the ability to group words on the basis of a single shared segment (e.g., break/block) does not appear before the first grade. These findings support Treiman's view, expressed in other papers (Treiman, 1985, Treiman & Danis, 1988), that syllables, onsets, and rimes constitute units of linguistic processing that are more accessible than the phoneme. In demonstrating the developmental priority of onsets and rimes, Treiman and Zukowski suggest that this initial cut may serve as a guide in focussing explicit attention on the internal structure of the syllable. In my discussion, I would like to explore the possibility that the developmental progression observed by Treiman and Zukowski over the preschool years may extend beyond phonological awareness to reflect more fundamental changes in phonological representation, in particular to how lexical items are stored for recognition and retrieval. That is, the child's early vocabulary may
A Multi-hop ARQ Protocol for Underwater Acoustic Networks

Underwater acoustic networks are envisaged to be the enabling technology for oceanographic data collection, pollution monitoring, offshore exploration and tactical surveillance applications. Unique characteristics of underwater acoustic channels such as large propagation delays and high bit error rates pose a challenge to designing reliable and efficient communication protocols. In this paper, we propose an opportunistic acknowledgement scheme suited for Stop and Wait ARQ protocols and demonstrate using simulations that it achieves better latency and energy efficiency than traditional non-opportunistic schemes for both one and two-dimensional multi-hop acoustic channels.