Miracle-dz/UniFAR-FTUs huggingface dataset:
Lagrangian decomposition approach to active power congestion management across interconnected regions

In the paper an augmented Lagrangian relaxation based algorithm for regional decomposition optimal power flow (OPF) is presented to address congestion management across interconnected regions. An OPF problem is decomposed into regional sub-problems through Lagrangian relaxation. Unlike other existing methods, no dummy generators or loads are added into the original network model. Applying this algorithm with the real-time balancing mechanism, the problem of active power congestion management across interconnected regions is separated into quadratic regional sub-problems, which can be solved either sequentially or in parallel. With this approach, regional ISOs can relieve network congestion co-ordinately without knowing any other regions' network information but the corresponding Lagrangian multipliers of coupling constraints between regions. The IEEE RTS-96 with three interconnected regions is studied to illustrate the proposed approach.
Determination of Deformation Modulus for Lower Sands in Nakdong River Delta

The deformation modulus of sands below 30 m in the Nakdong River Delta was estimated by using various in-situ tests, such as the piezocone penetrometer (CPT), seismic dilatometer (SDMT), and pressuremeter tests (PMT). Disturbed sand samples retrieved at several depths of two boreholes were reconstituted to simulate the in-situ deposited condition using a slurry method. Thereafter, the drained triaxial compression (TX) and the resonant column (RC) tests were also conducted. The elastic modulus obtained through the application of the TX and PMT results to conventional methods led to the underestimation of the in-situ values, because the inherent characteristics of the natural sands were not considered. Thus, the non-linear modulus degradation curves were constructed using the modulus degradation from the TX, RC, PMT, and the in-situ maximum shear modulus from SDMT. Thereafter, the modulus at 25% failure stress strength was re-evaluated. The re-evaluated values from the TX were in good agreement with those from the PMT, using the unloading curves and with the existing empirical equation based on the seismic CPT. Finally, a CPT-compatible empirical formula for the deformation modulus at 25% failure strength was proposed.
Model-Driven Risk Analysis: The CORAS Approach

The term risk is known from many fields, and we are used to references to contractual risk, economic risk, operational risk, legal risk, security risk, and so forth. We conduct risk analysis, using either offensive or defensive approaches to identify and assess risk. Offensive approaches are concerned with balancing potential gain against risk of investment loss, while defensive approaches are concerned with protecting assets that already exist.In this book, Lund, Solhaug and Stlen focus on defensive risk analysis, and more explicitly on a particular approach called CORAS. CORAS is a model-driven method for defensive risk analysis featuring a tool-supported modelling language specially designed to model risks. Their book serves as an introduction to risk analysis in general, including the central concepts and notions in risk analysis and their relations. The authors aim is to support risk analysts in conducting structured and stepwise risk analysis. To this end, the book is divided into three main parts. Part I of the book introduces and demonstrates the central concepts and notation used in CORAS, and is largely example-driven. Part II gives a thorough description of the CORAS method and modelling language. After having completed this part of the book, the reader should know enough to use the method in practice. Finally, Part III addresses issues that require special attention and treatment, but still are often encountered in real-life risk analysis and for which CORAS offers helpful advice and assistance. This part also includes a short presentation of the CORAS tool support.The main target groups of the book are IT practitioners and students at graduate or undergraduate level. They will appreciate a concise introduction into the emerging field of risk analysis, supported by a sound methodology, and completed with numerous examples and detailed guidelines.
Data Processing Algorithms for Generating Textured 3 D Building Façade Meshes From Laser Scans and Camera Images

processing steps are needed to cope with imperfections and non-idealities inherent in laser scanning systems such as occlusions and reflections from glass surfaces. The driven path iscutintoeasy-to-handlequasi-linearsegmentswith approximately straight driving direction. The vertical scans in each segment are recorded in a sequential topological order, andaretransformedintoadepthimage;ifavailable, additional 3D data from other modalities such as stereo vision is also taken into consideration. Dominant building structures are detected in the depth images, and points are classified into foregroundandbackgroundlayers.Largeholesinthe background layer, caused by occlusion from foreground layer objects, are filled in by planar or horizontal interpolation. The depth image is further processed by removing isolated points and filling remaining small holes, to obtain a textured surface mesh. We apply the above steps to a large set of data with several million 3D points, and show photorealistic texture mapped 3D models. I.INTRODUCTION Three-dimensionalmodelsofurbanenvironmentsare useful in a variety of applications such as urban planning, training and simulation for urban terrorism scenarios, and virtualreality.Currently,thestandardtechniquefor creating large scale city models in an automated or semi-automated way, is to use stereo vision approaches on aerial or satellite images [5, 9, 14]. In recent years, advances in resolution and accuracy of airborne laser scanners have also rendered them suitable for the generation of reasonable models [8, 10]. Both approaches have the disadvantage that their resolution is only in the range of 1 to 2 feet, and more importantly, they can only capture the roofs of the buildings but not the facades. This essential disadvantage prohibits theiruseinphotorealisticwalkordrive-through applications. There have been various attempts to acquire the complementary ground-level data necessary to complete existing airborne models, either using stereo vision [3] or 3D laser scanners [11]. But as data has to be acquired in a slow stop-and-go fashion, these approaches do not scale to more than few buildings. In previous work, we have developed a method capable of rapidly acquiring 3D geometry and texture data for an entire city at the ground level by using fast 2D laser scanners and a digital camera [6, 7]. The data acquisition system is mounted on a truck, moving at normal speeds on public roads, collecting data to be processed offline. This approach has the advantage that data can be acquired continuously, rather than in a stop-and-go fashion, and is therefore extremely fast. Relative position changes are computed with centimeter accuracy by matching successive horizontal laser scans against each other; global position is determined by additional …
Base-Complexity Classifications of Qcb0-Spaces

We define and study new classifications of qcb0-spaces based on the idea to measure the complexity of their bases. The new classifications complement those given by recently introduced hierarchies of qcb0-spaces and provide new tools to investigate non-countably based qcb0-spaces. As a by-product, we show that there is no universal qcb0-space and establish several new properties of the Kleene-Kreisel continuous functionals of countable types.
Automated quantification of epicardial adipose tissue in cardiac magnetic resonance imaging

Cardiovascular disease is one of the leading causes of death worldwide. Epicardial adipose tissue (EAT) has emerged as an independent predictor of high cardiometabolic risk. Cardiovascular MRI has proven to be a feasible and reproducible method to assess EAT quantitatively. We present a novel approach for the automated quantification of EAT using “a priori” anatomical information. We extracted a region of interest (ROI) in the end-diastolic heart phase followed by a GVF-snake algorithm to smooth it. For the EAT and endocardial boundary detection, a Law's texture filter is applied. Left and right ventricle are localized using spatial prior information. Then, thresholding is applied to quantify the cardiac muscle. For the EAT, it is differentiated from the paracardial fat by K-cosine curvature analysis. Results for 10 morbidly obese patients show no significant differences between manual and automatic quantification with a remarkable time and effort saving between them.
An intelligent FLC method for tracking the maximum power of photovoltaic systems

Maximum power point trackers are so important in photovoltaic systems since they become an efficient solution to improve the overall system efficiency. This paper presents a photovoltaic system with maximum power point tracking facility. An intelligent fuzzy logic controller method is proposed in this paper to achieve the maximum power point tracking of PV modules. The system consists of a photovoltaic solar module connected to a DC-DC Buck-boost converter. The proposed input variables are the change in the voltage and the change in the power of the PV module which the output variable is the reference voltage which is then accumulated every certain time. The system is modeled using MATLAB/SIMULINK. The system has been experienced under disturbance in the photovoltaic temperature and irradiation levels. The simulation results show that the proposed maximum power tracker tracks the maximum power accurately and successfully in all condition tested. Comparison of different performance parameters such as: tracking efficiency and response time of the system shows that the proposed method gives higher efficiency and better performance than the conventional perturbation and observation method.
Image-Based Visual Hulls

This thesis addresses the problem of acquisition and rendering of dynamic real-world scenes. It describes an efficient image-based approach to computing and shading the scene geometry described by visual hulls shapes obtained from silhouette image data. The novel algorithms take advantage of epipolar geometry and incremental computation to achieve a constant rendering cost per rendered pixel. They do not suffer from the computation complexity, limited resolution, or quantization artifacts of previous volumetric approaches. The use of these algorithms is demonstrated in a real-time virtualized reality application running off a small number of video streams. Thesis Supervisor: Leonard McMillan Title: Assistant Professor
outputs Automatically structuring domain knowledge from text : a review of current research

This paper presents an overview of automatic methods for building domain knowledge structures (domain models) from text collections. Applications of domain models have a long history within knowledge engineering and artificial intelligence. In the last couple of decades they have surfaced noticeably as a useful tool within natural language processing, information retrieval and semantic web technology. Inspired by the ubiquitous propagation of domain model structures that are emerging in several research disciplines, we give an overview of the current research landscape and some techniques and approaches. We will also discuss trade-offs between different approaches and point to some recent trends.
Learning Discriminative MspLBP Features Based on Ada-LDA for Multi-Class Pattern Classification

This paper presents a novel approach for multi-class pattern classification – face detection and facial expression recognition, which is based on discriminative multi-scale and multi-position Local Binary Pattern (MspLBP) features selected by a boosting technique called the AdaBoost+LDA (Ada-LDA) method. From a large pool of MspLBP features within a face image, the most discriminative MspLBP features trained by two alternative LDA methods depending on the singularity of the within-class scatter matrix, are selected under the framework of AdaBoost. To verify the feasibility of our approach, we performed two extensive experiments on the famous face databases in terms of face detection and facial expression recognition. First, face detection, a typical example of two-class pattern classification, was carried out on the MIT-CBCL and MIT+CMU face test sets. Second, facial expression recognition, a typical problem of multi-class pattern classification, was performed on the JAFFE face database. Given the same number of features, the proposed face detector shows over 25% higher detection rate than the well-known Viola’s detector at a given false positive rate of 10%. It can also provide real-time operation with over 10 frames per second rate. For facial expression recognition, our approach also shows a better performance over at least 21% recognition rates than other linear subspace-based methods such as PCA, DCV, and PCA+LDA. Our proposed approach provides a considerable performance improvement with only a small number of discriminative MspLBP features in the multi-class pattern classification problem.
Optimal Approximation of Elliptic Problems by Linear and Nonlinear Mappings IV : Errors in L 2 and Other Norms

We study the optimal approximation of the solution of an operator equation A(u) = f by linear and different types of nonlinear mappings. In our earlier papers we only considered the error with respect to a certain Hs-norm where s was given by the operator since we assumed that A : Hs 0(Ω) → H−s(Ω) is an isomorphism. The most typical case here is s = 1. It is well known that for certain regular problems the order of convergence is improved if one takes the L2-norm. In this paper we study error bounds with respect to such a weaker norm, i.e., we assume that Hs 0(Ω) is continuously embedded into a space X and we measure the error in the norm of X. A major example is X = L2(Ω) or X = Hr(Ω) with r < s. We prove this better rate of convergence also for non-regular problems. AMS subject classification: 41A25, 41A46, 41A65, 42C40, 46E35, 65C99
Multilevel Preconditioning for Adaptive Sparse Optimization

We are concerned with the efficient numerical solution of minimization problems in Hilbert spaces involving sparsity constraints. These optimizations arise, e.g., in the context of inverse problems. In this work we analyze a very efficient variant of the well-known iterative soft-shrinkage algorithm for large or even infinite dimensional problems. This algorithm is modified in the following way. Instead of prescribing a fixed thresholding parameter, we use a decreasing thresholding strategy. Moreover, we use suitable variants of the adaptive schemes derived by Cohen, Dahmen and DeVore [11, 12] for the approximation of the infinite matrix-vector products. We derive a block multiscale preconditioning technique which allows for local wellconditioning of the underlying matrices and for extending the concept of restricted isometry property to infinitely labelled matrices. The careful combination of these ingredients gives rise to a numerical scheme that is guaranteed to converge with exponential rate, and which allows for a controlled inflation of the support size of the iterations. We also present numerical experiments that confirm the applicability of our approach which extends concepts from compressed sensing to large scale simulation. AMS subject classification: 41A25, 65F35, 65F50, 65N12, 65T60.
JPred: a consensus secondary structure prediction server

UNLABELLED An interactive protein secondary structure prediction Internet server is presented. The server allows a single sequence or multiple alignment to be submitted, and returns predictions from six secondary structure prediction algorithms that exploit evolutionary information from multiple sequences. A consensus prediction is also returned which improves the average Q3 accuracy of prediction by 1% to 72.9%. The server simplifies the use of current prediction algorithms and allows conservation patterns important to structure and function to be identified. AVAILABILITY http://barton.ebi.ac.uk/servers/jpred.h tml CONTACT geoff@ebi.ac.uk
Connecting Abstract Description Systems

Combining knowledge representation and reasoning formalisms like description logics (DLs), temporal logics, and logics of space, is worthwhile but diicult. It is worthwhile because usually application domains comprise various aspects of the world, thus requiring suitable combinations of formalisms modeling each of the aspects. It is diicult because the computational behavior of the resulting hybrids is often much worth than the behavior of it components. In this paper we propose a combination method which is robust in the computational sense and still allows for interactions between the combined systems. The combination method{called E-connection{will be deened and investigated for so-called abstract description systems (ADS) which subsume all standard description logics, various logics of time and space, modal logics, and epistemic logics. The main theoretical result is that the E-connection of any nite set of decidable ADSs is decidable as well. Four instances of E-connections of ADSs will be discussed: (1) The E-connection of DLs with the logic MS for quantitative reasoning about space, (2) the E-connection of DLs with the logic S4 u (containing RCC-8) for qualitative reasoning about space, (3) the E-connection of two DLs (ALCO and SHIQ), and (4) the E-connection of DLs with propositional temporal logic PTL and S4 u .
Paleotempestite Distribution across an Isolated Carbonate Platform, San Salvador Island, Bahamas

ABSTRACT Mattheus, C.R. and Fowler, J.K. , 2015. Paleotempestite distribution across an isolated carbonate platform, San Salvador Island, Bahamas. Sediment cores were collected from coastal ponds across San Salvador Island, an isolated Bahamian carbonate platform, and integrated with aerial photographs and field-survey data to provide insight into how spatially variable storm records are at the island scale and what drives this variance. A better understanding of local tempestite generation and preservation potential is crucial for correlating events across more regional scales. Sandy storm layers, products of beach overwash and/or high-energy aeolian transport from the shore into coastal ponds, are easily distinguished from flocculated carbonate muds, microbial mats, and other organics that ordinarily sequester in the stagnant, low-energy coastal water bodies. Interpreted paleotempestites do not correlate well between studied ponds using a strictly stratigraphic approach, although all sites investigated are situated within 150 m of a sandy beach, are similar in size and morphology, and coastal terrains across the small island are comparable. While wrack lines show that individual storms produce surges that vary in height along the island's 60 km-long coastline, differences in the spatial distribution of storm deposits cannot be explained solely as a function of variable surge heights, storm trajectories, and shore aspect; they also reflect intrinsic, biogeomorphic variables such as pond-fringing vegetation characteristics and coastal geomorphic configuration. A complete storm chronology for the island is not generated in any single pond location, and diagenetic processes compound this variance, producing a high degree of spatial heterogeneity of storm records. Nonetheless, the Caribbean-wide Hurricane Hyperactivity Period is distinguished in core from the modern period of relative inactivity by an up-core transition from sandy, stratified pond deposits containing storm layers to heavily bioturbated sediments indicative of low-E deposition. This facies transition, recognized across the island, provides a regional correlation tool for evaluating the distribution of paleotempestites within context of major climate regimes.
On computable numbers with an application to the Entscheidungsproblem Universal Turing Machine

Many cyberneticists would agree that, had it not been for consistent hashing, the simulation of checksums might never have occurred. After years of essential research into replication, we prove the analysis of online algorithms, wh ich embodies the confirmed principles of robotics. Our focus in our research is not on whether digital-to-analog converter s and evolutionary programming can agree to accomplish this mission, but rather on constructing a novel framework for th e construction of scatter/gather I/O (HOLLEE). while such a hypothesis is usually an intuitive objective, it is derived from known results.
Effects of Groundwater‐Flow Paths On Nitrate Concentrations Across Two Riparian Forest Corridors 1

Speiran, Gary K. , 2010. Effects of Groundwater‐Flow Paths on Nitrate Concentrations Across Two Riparian Forest Corridors. Journal of the American Water Resources Association (JAWRA) 46(2):246‐260. DOI: 10.1111/j.1752‐1688.2010. 00427.x
Spontaneous Colonization and Forest Fragmentation in the Central Amazon Basin

This article addresses the emergence of road networks and forest fragmentation in Central Amazônia, which has been impacted by both spontaneous and planned settlement. The first objective of the article is to broaden the discussion of fragmentation by addressing social processes that generate it through the construction of roads. Roads impact land cover change worldwide, and their role in Amazonian deforestation is known. The article also seeks to extend the literature on roads to address the social processes and individual behaviors that create the road network architecture. The second objective is to open a discussion about the biodiversity implications of different patterns of forest fragmentation. Our specific focus is the geometry of settlement associated with urban nodes, referred to here as radial fragmentation. The article pursues its objectives by implementing a conceptual framework that extends the pattern-to-process paradigm of landscape ecology by adding a (social) process-to-pattern component. This is accomplished through a mixed-method approach including (1) field-based narratives of the social processes that gave rise to radial fragmentation in the hinterland of the town of Itaituba, an important settlement in the middle Tapajós valley; (2) remote sensing of the evolution of road networks, which we then link to deforestation in a temporal analysis of emergent fragmentation patterns; and (3) computational applications to compare the biodiversity implications of radial and fishbone landscape fragmentation.
Simulation and dSPACE hardware implementation of the MPPT techniques using buck boost converter

Maximum power point trackers are so important in photovoltaic systems to increase their efficiency. This paper presents a photovoltaic system with maximum power point tracking facility. The system consists of a photovoltaic solar module connected to a DC-DC buck boost converter and load. The system is modeled using MATLAB/SIMULINK. Maximum power point tracking is achieved using perturbation and observation method and incremental conductance method. The MPPT system is simulated and experimentally implemented. The implementation of the MPPT hardware setup is done using dSPACE real time control. Data acquisition and the control system is implemented using dSPACE 1104. The simulation and the practical results show that the proposed system tracked the maximum power accurately and successfully under different conditions tested.