Miracle-dz/UniFAR-FTUs huggingface dataset:
A lossless coding scheme for maps using binary wavelet transform

ABSTRACT The maps and images of geographical information system (GIS) are used for finding locations, accessing rail, bus routes, and for educational purposes such as study on vegetation, landscapes, population, and so on and so forth. Remote sensing is the process of acquiring data about Earth by using satellites or satellite-borne or airborne sensors. The images acquired through remote sensing systems are integrated within GIS to store, analyze, and manipulate geographical information of the Earth. The huge size of the digital raster maps makes compression inevitable in particular to reduce the transmission time and display them on the Internet as well as other networks. In this paper, a lossless coding approach that performs encoding on the decomposed binary layers by taking the advantage of binary wavelet transform that produces sparse matrix for row column reduction and Huffman coding is presented. The results obtained on raster maps are compared with those of other existing techniques.
Modelling of the ultrasonic propagation in polycrystalline materials

In some polycrystalline materials, ultrasonic non destructive testing is affected by structural noise and attenuation. Those phenomena can cause significant loss in detection performances. Thus, the presence of a microstructure is a limiting factor of ultrasonic inspection capabilities and it must be accounted for when designing new NDE methods. Modelling work has been underway at CEA-LIST in the software CIVA to describe attenuation, structural noise and beam distortions appearing when a wave propagates in a heterogeneous medium such as a polycrystalline material. The objective is to develop new simulation tools based on metallurgical data input. To achieve this goal, a theoretical model relating ultrasonic scattering to properties of the microstructure and its integration to existing algorithms, allowing us to compute structural noise and attenuation from material properties is proposed. Further numerical study and comparisons with experimental results have been performed to study the influence of the type of structure (simple or duplex), the shape (equiaxed or elongated) and the size of grains.
C V ] 11 F eb 2 01 6 Generating Discriminative Object Proposals via Submodular Ranking

A multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale by using a diversity ranking algorithm. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a singlescale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the singlescale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentatio n and detection and outperform the state-of-art performance .
Methods for detecting multi-locus genotype-phenotype association

Methods for detecting multi-locus genotype-phenotype association by Jeffrey R. Kilpatrick Solutions to the genotype-phenotype problem seek to identify the set of genetic mutations and interactions between them which modify risk for and severity of a trait of interest. I propose association graph reduction (AGR), a novel algorithm to detect such genetic lesions in genome-wide data, particularly in the presence of high-order interactions. I describe several existing methods and evaluate their performance in terms of computational cost and power to detect associations. An objective comparison of the results shows that AGR successfully combines high power with computational efficiency, while providing a detailed account of interactions present in the data. No other known method combines these three properties. When applied to real data, AGR can be used to discover genetic causes of common diseases such as arthritis, hypertension, diabetes, asthma, and many others, which will facilitate the discovery of novel diagnostic tools and treatment protocols.
Hamiltonian-Like System Model Structure : Failure-Free Case

As the scale of engineered systems such as electric power grids, communication networks, and the Internet expands and as society’s dependence upon reliable operation of these networks increases, it is vital that system engineers seek a better understanding of how small-scale failures of individual elements may propagate to produce global, system-wide failures. Within this general class of problems, importance sampling methods have improved the efficiency of search techniques for identifying rare failures in probabilistic models for communication networks [1], [2]; similar progress has been made in characterizing the role of graph interconnection structure in propagation of failures in electric power networks [3], [4]. The work here is motivated largely by the electric power systems application. Efforts to date on these problems for power networks have focused primarily on Markov chain-like representations, in which the state of the system is represented as discrete and the engineering constraints impacting failure transitions are those of the steady state. Our goal here will be somewhat different in flavor. In a deterministic model, we seek to capture the role of transient dynamic response following a specified initiating disturbance and examine subsequent (“cascading”) element failures that are induced when operating thresholds for individual elements are exceeded along the state trajectory. In the formulation to be presented here, the potentially probabilistic nature of initiating events is not treated. To allow tractable analysis of continuous dynamics in state-space models of high dimension, we will restrict attention to a specialized class of system representation, one in which energy storage associated with individual elements is
Molecular Fingerprinting and RNA-Based Pyrosequencing and Mycorrhizal Fungal Communities via DNA-Cry 1 Ab Endotoxin ( Bt Maize ) on Expressing the Bacillus thuringiensis Testing Potential Effects of Maize

Published Ahead of Print 10 August 2012. 10.1128/AEM.01372-12. 2012, 78(20):7384. DOI: Appl. Environ. Microbiol. Kowalchuk and Marcel G. A. van der Heijden de Hollander, E. Toby Kiers, Wilfred F. M. Röling, George A. Erik Verbruggen, Eiko E. Kuramae, Remy Hillekens, Mattias Molecular Fingerprinting and RNA-Based Pyrosequencing and Mycorrhizal Fungal Communities via DNACry1Ab Endotoxin (Bt Maize) on Expressing the Bacillus thuringiensis Testing Potential Effects of Maize
Simulation of alternative temperature control structures of a biogas reactor in a wastewater treatment plant

INTRODUCTION The temperature of Anaerobic Digestion (AD) has significant effects on methane production as well as on sludge hygienisation. The temperature stability has been found by several studies to be one of the most important parameters (Leitao, Haandel, Zeeman, & Lettinga, 2006), (Chae, Jang, Yim, & Kim, 2008). Since the methane forming bacteria is sensitive to temperature changes, accurate temperature control is essential. The consensus is that temperature changes greater than 1°C/d affect process performance, thus temperature variations of less than 1°C/d are recommended (Metcalf & Eddy, 2003)
ABOUT THE ZETA FUNCTION AND THE RIEMANN HYPOTHESIS

Abstract. The present essay aims at investigating whether and how far an algebraic analysis of the Zeta Function Z(s) and of the RIEMANN Hypothesis can be carried out. Of course the well-established properties of the Zeta Function, explored in depth in over 150 years of world-wide study, are taken for granted. The chosen approach starts from the recognized necessity of formulating an extension of the Zeta Function which is defined for Re(s) = X < 1. The extension chosen substitutes a part of the RIEMANN series with an integral, see e.g. the work of GRAM and BACKLUND. The rest of the series is then replaced by two corrective terms. The zero-condition on Z(s) implies that a sum of three different types of terms should be nil. This zero-condition hypothetically satisfied in an outlying (X 6= 1 2 ) complex-conjugate (c.c.) zero-pair implies the existence of another zero-pair, mirror-image of the first with respect to the Critical Line X = 1 2 (C.L.). The term derived from the EULER-McLAURIN integration is endowed with a high degree of symmetry with respect to the C.L. It follows that the other two terms of the zero-condition should possess the same type of symmetry, but this is shown to be possible only in the degenerate case when the two specular c.c. pairs collapse onto a single pair located on the C.L.
On Quality Assurance of 3 D Bust Reconstructions

In this paper a non-reference method for quality assurance in 3D bust reconstruction is presented. The proposed approach is part of an automatic parametrization concept for 3D reconstruction applications with no ground-truth data available. It is based on a novel concept of pair-wise view comparisons, which is new in this field. Evaluation on a dataset of human bust scans shows perfect prediction of human votes.
CHAPTER 3 GESTURE ’ S ROLE IN LEARNING ARITHMETIC

Mathematical concepts are traditionally viewed as abstract and formal. However, recent research suggests that there is an embodied component to these concepts––that notions like infinity, continuity, and number are metaphorical and grounded in our experience of the world (Lakoff & Núñez, 2000). The evidence for this view has largely come from analyses of mathematical language. But the spontaneous gestures that speakers produce when they talk about math have also been used to argue that mathematical concepts are metaphorical and embodied (Núñez, 2008). For example, gesture can reveal that a speaker construes a problem dynamically even when the speaker’s words focus exclusively on the problem’s static notation (e.g., Marghetis & Núñez, 2010).
Mechanical Strength Evaluation of Superconducting Magnet Structures by HIP Bonding Method

MTC proposed that production of the International Thermonuclear Experimental Reactor (ITER) toroidal magnetic field coils support structure "Radial Plate (RP)" using the HIP diffusion bonding. HIP allows production cost reductions in materials and machining time. However, insufficient strength of the HIP diffusion bonded sections was an issue. In this study, changes in bonding strength and base material strength were investigated using HIP treatment temperatures as parameters. Mechanical property tests and microstructure observation of the cross sections at the bonded areas after HIP treatment were conducted and as a result it was found that the bonding strength equivalent to the mechanical strength of the base metal can be obtained at 1300[°C]. However, the yield strength at room temperature of the base material after HIP treatment decreased by 24%. Since crystal grain coarsening occurs due to heat input by HIP, design considerations are required to guarantee the specified strength. Furthermore, a full-size mock-up of RP segments was fabricated by HIP. It was confirmed that the yield strength and fracture toughness at 4 [K] at the bonded sections of the mock-up satisfied the specified values required for the RP and uniform quality was obtained. From this study, it was proven that HIP diffusion bonding can be applied to the fabrication of RP segments.
Small-World Network Analysis of Cortical Connectivity in Chronic Fatigue Syndrome using EEG

The primary aim of this thesis was to explore the relationship between electroencephalography (qEEG) and brain system dysregulation in people with Chronic Fatigue Syndrome (CFS). EEG recordings were taken from an archival dataset of 30 subjects, 15 people with CFS and 15 healthy controls (HCs), evaluated during an eye-closed resting state condition. Exact low resolution electromagnetic tomography (eLORETA) was applied to the qEEG data to estimate cortical sources and perform functional connectivity analysis assessing the strength of time-varying signals between all pairwise cortical regions of interest. To obtain a comprehensive view of local and global processing, eLORETA lagged coherence was computed on 84 regions of interest representing 42 Brodmann areas for the left and right hemispheres of the cortex, for the delta (1-3 Hz) and alpha-1 (8-10 Hz) and alpha-2 (10-12 Hz) frequency bands. Graph theory analysis of eLORETA coherence matrices for each participant was conducted to derive the “small-worldness” index, a measure of the optimal balance between the functional integration (global) and segregation (local) properties known to be present in brain networks. The data were also associated with the cognitive impairment composite score on the DePaul Symptom Questionnaire (DSQ), a patient-reported symptom outcome measure of frequency and severity of cognitive symptoms. Results showed that small-worldness for the delta band was significantly lower for patients with CFS compared to HCs. Smallworldness for delta, alpha-1, and alpha-2 were associated with higher cognitive composite scores on the DSQ. Finally, small-worldness in all 3 frequency bands correctly distinguished those with CFS from HCS with a classification rate of
Loadable Real-Time Extension for CPU / GPU Resource Coordination

Graphics processing units (GPUs) facilitate high-performance computing. However, GPU runtime environments target to best-effort oriented applications, and do not consider real-time applications. Previous work have contributed to real-time GPU, depends on the kernel. Dependence on the kernel and device driver gives incurs burden to developers and users. We present Linux-RTXG, a method that uses a loadable kernel module approach without kernel modification to coordinate CPU and GPU resources for a real-time scheduling framework. Linux-RTXG employs a CPU realtime scheduler, a GPU real-time scheduler, and GPU reservation mechanisms. To achieve the proposed framework without kernel modification, we present interrupt intercept mechanisms and independent interrupt mechanisms and to solved currently Linux kernel real-time scheduling problem. Experimental results indicate that the proposed kernel modification free Linux-RTXG framework achieves, GPU scheduling overhead and quality of service management performance comparable to existing kernel-dependent approaches.
Foreign Accent Conversion by Synthesizing Speech from Phonetic Posteriorgrams

Methods for foreign accent conversion (FAC) aim to generate speech that sounds similar to a given non-native speaker but with the accent of a native speaker. Conventional FAC methods borrow excitation information (F0 and aperiodicity; produced by a conventional vocoder) from a reference (i.e., native) utterance during synthesis time. As such, the generated speech retains some aspects of the voice quality of the native speaker. We present a framework for FAC that eliminates the need for conventional vocoders (e.g., STRAIGHT, World) and therefore the need to use the native speaker’s excitation. Our approach uses an acoustic model trained on a native speech corpus to extract speaker-independent phonetic posteriorgrams (PPGs), and then train a speech synthesizer to map PPGs from the non-native speaker into the corresponding spectral features, which in turn are converted into the audio waveform using a high-quality neural vocoder. At runtime, we drive the synthesizer with the PPG extracted from a native reference utterance. Listening tests show that the proposed system produces speech that sounds more clear, natural, and similar to the non-native speaker compared with a baseline system, while significantly reducing the perceived foreign accent of nonnative utterances.
Influence of functional adaptation on the torque-angle relation

* Exercise Research Laboratory, Federal University of Rio Grande do Sul (UFRGS), Brazil o Physical Therapy Faculty, Lutheran University of Brazil (ULBRA), Brazil Introduction Functional demand has been proposed as one of the responsible factors for adaptation of skeletal muscle (Caplan et al., 1988; Herzog, 1996). Muscle fibers increase their structural and functional capacity in response to overload. Different types of overload should determine different types of structural and functional adaptations in skeletal muscle. Classical ballet dancers and volleyball players, for example, show different demands for the ankle plantar-flexor (PF) muscles, where classical ballet dancers use the PF muscles in a shortened position, while the volleyball players use the same muscles in a lengthened position. The functional adaptation due to these different types of training may be responsible for changing the force production capacity, and, consequently, for modifying the force-length (or torqueangle) relationship of these two groups. Therefore, the purpose of this study was to compare the torqueangle (TA) relation and the electromyographic (EMG) activity of the PF muscles in these two groups.
Low Phase Noise Digital Division by 2 and by 3 of a 30 GHz Coupled Optoelectronic Oscillator

A frequency synthesis technique based on the division of a coupled optoelectronic oscillator (COEO) reference is presented. This technique overcomes one of the main issues of the most common frequency synthesis technique, namely the phase locked loop (PLL): the inherent phase noise degradation of frequency multiplication. In order to keep the benefits of the frequency division technique, residual phase noise of the dividers has to be reduced as much as possible. This article discusses the results of two digital dividers, a divider by 2 and a divider by 3, both with a 30 GHz COEO reference.
Securitized Banking and the Run on Repo

The Panic of 2007-2008 was a run on the sale and repurchase market (the “repo” market), which is a very large, short-term market that provides financing for a wide range of securitization activities and financial institutions. Repo transactions are collateralized, frequently with securitized bonds. We refer to the combination of securitization plus repo finance as “securitized banking”, and argue that these activities were at the nexus of the crisis. We use a novel data set that includes credit spreads for hundreds of securitized bonds to trace the path of crisis from subprime-housing related assets into markets that had no connection to housing. We find that changes in the “LIB-OIS” spread, a proxy for counterparty risk, was strongly correlated with changes in credit spreads and repo rates for securitized bonds. These changes implied higher uncertainty about bank solvency and lower values for repo collateral. Concerns about the liquidity of markets for the bonds used as collateral led to increases in repo “haircuts”: the amount of collateral required for any given transaction. With declining asset values and increasing haircuts, the U.S. banking system was effectively insolvent for the first time since the Great Depression.
The role of third party assurance of sustainability reports

Background: Companies responsibilities regarding sustainability issues has drawn significant attention globally recent years due to catastrophes such as pollution and destruction of ozone layer. Out of this, a demand for companies to account for their sustainability performance has dawn, together with an almost concomitant growth in sustainability assurance. Some companies are truly committed to sustainability issues whilst other use sustainability reporting as manipulation and so called “greenwashing”. The role of sustainability assurance of these reports is unclear. Does it function as a legitimizer, a managerial tool and/or a corrector? Purpose: The purpose of this thesis is to investigate what role of third party assurance of sustainability information play, by identifying incentives and challenges. The thesis is written from a Swedish perspective. Method: It is a qualitative research and the data is collected through semi-structured interviews. Interviews was performed with assurance providers, companies with assured sustainability information and companies without sustainability information. Conclusion: The result shows that sustainability assurance is mainly functioning as a managerial tool that aims to improve internal processes, communication and control environment. However, it is associated with difficulties. Moreover, it does not necessarily imply that accountability increases and that the quality and credibility of the report is improved, since the role as corrector is unprioritized and associated with difficulties. A main concern is lack of standardization and laws, and lack of stakeholder inclusiveness in the reporting process and assurance process, referring to a wide range of stakeholders. Instead an important role of sustainability assurance is to legitimize the company as well as the assurer. Lastly, if the company acts sustainable or not is up to the company to decide. One should not expect auditors to prevent scandals or contribute significantly to a more sustainable world.
BEST PRACTICES IN REDUCING BUREAUCRACY AND CORRUPTION QUERY

23 July 2012 SUMMARY Excessive bureaucracy or red tape – as it is often referred to – is a “derisive term for excessive regulation or rigid conformity to formal rules that is considered redundant or bureaucratic and hinders or prevents action or decision-making” (Anti-Corruption Business Portal, Corruption Vocabulary). As a result, red tape imposes a disproportionate bureaucratic burden on firms and citizens. It can manifest itself through excessive or overly rigid administrative procedures, requirements for unnecessary licences, protracted decision-making processes involving multiple people or committees and a myriad of specific rules that slow down business operations. There is a broad consensus that unnecessary and excessive administrative requirements for complying with regulations create both incentives and opportunities for bribery and corruption.
Modeling assumptions and evaluation schemes: On the assessment of deep latent variable models

Recent findings indicate that deep generative models can assign unreasonably high likelihoods to out-of-distribution data points. Especially in applications such as autonomous driving, medicine and robotics, these overconfident ratings can have detrimental effects. In this work, we argue that two points contribute to these findings: 1) modeling assumptions such as the choice of the likelihood, and 2) the evaluation under local posterior distributions vs global prior distributions. We demonstrate experimentally how these mechanisms can bias the likelihood estimates of variational autoencoders.