Miracle-dz/UniFAR-FTUs huggingface dataset:
MARKOV CHAIN MODEL AND PSO TECHNIQUE FOR DYNAMIC HEURISTIC RESOURCE SCHEDULING FOR SYSTEM LEVEL OPTIMIZATION OF CLOUD RESOURCES

Cloud computing options a versatile computing infrastructure for large scale processing needs effective load equalization and migration of the cloud resources for rising the energy potency and resource utilization. The instructed resource allocation technique considers numerous parameters like migration time, waiting time, QoS, resource utilization etc. for effective and economical virtualized resource management and allocation. This paper aims at dispatching the computation load to any or all process nodes within the cloud computing atmosphere by considering the physical employment on every node therefore on stop bias during arranging computation resources and therefore improve the general computing performance in a heterogeneous cloud atmosphere.
Incorporating water table dynamics in climate modeling: 1. Water table observations and equilibrium water table simulations

[1] Soil moisture is a key participant in land-atmosphere interactions and an important determinant of terrestrial climate. In regions where the water table is shallow, soil moisture is coupled to the water table. This paper is the first of a two-part study to quantify this coupling and explore its implications in the context of climate modeling. We examine the observed water table depth in the lower 48 states of the United States in search of salient spatial and temporal features that are relevant to climate dynamics. As a means to interpolate and synthesize the scattered observations, we use a simple two-dimensional groundwater flow model to construct an equilibrium water table as a result of long-term climatic and geologic forcing. Model simulations suggest that the water table depth exhibits spatial organization at watershed, regional, and continental scales, which may have implications for the spatial organization of soil moisture at similar scales. The observations suggest that water table depth varies at diurnal, event, seasonal, and interannual scales, which may have implications for soil moisture memory at these scales.
3D SURFACE GENERATION FROM AERIAL THERMAL IMAGERY

Aerial thermal imagery has been recently applied to quantitative analysis of several scenes. For the mapping purpose based on aerial thermal imagery, high accuracy photogrammetric process is necessary. However, due to low geometric resolution and low contrast of thermal imaging sensors, there are some challenges in precise 3D measurement of objects. In this paper the potential of thermal video in 3D surface generation is evaluated. In the pre-processing step, thermal camera is geometrically calibrated using a calibration grid based on emissivity differences between the background and the targets. Then, Digital Surface Model (DSM) generation from thermal video imagery is performed in four steps. Initially, frames are extracted from video, then tie points are generated by Scale-Invariant Feature Transform (SIFT) algorithm. Bundle adjustment is then applied and the camera position and orientation parameters are determined. Finally, multi-resolution dense image matching algorithm is used to create 3D point cloud of the scene. Potential of the proposed method is evaluated based on thermal imaging cover an industrial area. The thermal camera has 640×480 Uncooled Focal Plane Array (UFPA) sensor, equipped with a 25 mm lens which mounted in the Unmanned Aerial Vehicle (UAV). The obtained results show the comparable accuracy of 3D model generated based on thermal images with respect to DSM generated from visible images, however thermal based DSM is somehow smoother with lower level of texture. Comparing the generated DSM with the 9 measured GCPs in the area shows the Root Mean Square Error (RMSE) value is smaller than 5 decimetres in both X and Y directions and 1.6 meters for the Z direction.
Reflectance and Transmittance Spectroscopy Applied to Detecting Fumonisin in Single Corn Kernels Infected with Fusarium verticillioides

ABSTRACT Reflectance and transmittance visible and near-infrared spectroscopy were used to detect fumonisin in single corn kernels infected with Fusarium verticillioides. Kernels with >100 ppm and <10 ppm could be classed accurately as fumonisin positive or negative, respectively. Classification results were generally better for oriented kernels than for kernels that were randomly placed in the spectrometer viewing area. Generally, models based on reflectance spectra have higher correct classification than models based on transmittance spectra. Statistical analyses indicated that including near-infrared wavelengths in calibrations improved classifications, and some calibrations were improved by including visible wavelengths. Thus, the color and chemical constituents of the infected kernel contribute to classification models. These results show that this technology can be used to rapidly and nondestructively screen single corn kernels for the presence of fumonisin, and may be adaptable to on-line detection.
Fractional-order control for a novel chaotic system without equilibrium

The control problem is discussed for a chaotic system without equilibrium in this paper. On the basis of the linear mathematical model of the two-wheeled self-balancing robot, a novel chaotic system which has no equilibrium is proposed. The basic dynamical properties of this new system are studied via Lyapunov exponents and Poincare map. To further demonstrate the physical realizability of the presented novel chaotic system, a chaotic circuit is designed. By using fractional-order operators, a controller is designed based on the state-feedback method. According to the Gronwall inequality, Laplace transform and Mittag-Leffler function, a new control scheme is explored for the whole closed-loop system. Under the developed control scheme,the state variables of the closed-loop system are controlled to stabilize them to zero. Finally, the numerical simulation results of the chaotic system with equilibrium and without equilibrium illustrate the effectiveness of the proposed control scheme.
Mini-cours (orateurs invités)

Nicolas Bonichon Quelques résultats sur les spanners géométriques Un graphe géométrique est un graphe défini à partir d’un nuage de points (par exemple dans le plan). L’étirement d’un graphe géométrique est le pire rapport entre la distance dans le graphe et la distance Euclidienne, pour toute paire de points du graphe. Un t-spanner est un graphe (ou une famille de graphes) dont l’tirement est born par t. Dans cet exposé je présenterai quelques résultats relatifs à certains spanners: triangulations de Delaunay, Θ-graphs, spanners de degré borné, routage dans les triangulations de Delaunay.
Comparison of Estimated Continuous Cardiac Output and Transoesophageal Echocardiography Cardiac Output for Noninvasively Measuring Cardiac Output inPaediatric Patients Undergoing Kidney Transplant Surgery: A Pilot Study

Comparison of Estimated Continuous Cardiac Output and Transoesophageal Echocardiography Cardiac Output for Noninvasively Measuring Cardiac Output in Paediatric Patients Undergoing Kidney Transplant Surgery: A Pilot Study Objective: Estimated continuous cardiac output (esCCO), a noninvasive technique for continuously measuring cardiac output, is based on modified pulse wave transit time (m-PWTT), which in turn is determined by pulse oximetry and electrocardiography (ECG). However, its trending ability has never been evaluated in paediatric patients. Therefore, this study examined esCCO’s ability to detect the exact changes in cardiac output (CO), compared with transoesophageal echocardiography, in patients undergoing kidney transplantation. Methods and Results: The cardiac index was determined simultaneously using both the estimated continuous cardiac output and transoesophageal echocardiography in 11 paediatric kidney transplant patients. After the initial calibration measurement, cardiac index was measured using transoesophageal echocardiography before and after volume loading, and before surgery completion. The cardiac index determined using transoesophageal echocardiography increased significantly between the pre- and post-volume loading measurements (P 15% from before volume loading to after volume loading or between volume loading and the completion of surgery was 16 points; this lead to a change of >15% in the cardiac index determined using continuous cardiac output, in the same direction, in 100% cases. The sensitivity and specificity for cardiac index determination, using estimated continuous cardiac output compared to transoesophageal echocardiography, were 87.5% and 100%, respectively. Conclusions: Although there was poor agreement between the cardiac indexes determined by estimated continuous cardiac output and transoesophageal echocardiography, the trends determined by both methods were in good agreement. This method may be sufficient for trend monitoring.
Teacher Evaluations: Use or Misuse?.

This manuscript examines value added measures used in teacher evaluations. The evaluations are often based on limited observations and use student growth as measured by standardized tests. These measures typically do not use multiple measures or consider other factors in the teaching and learning process. This manuscript identifies some of the factors usually not taken into account in teacher evaluations and suggests ways to improve the teacher evaluation process. This manuscript advocates use of multiple measures in the both formative and summative evaluation of teachers and suggests the inclusion of specific student characteristics and a collegial process that needs to make the teacher evaluation process fair and more meaningful.
PREFERENCE-BASED MULTI-OBJECTIVE DISTINCT CANDIDATES OPTIMIZATION

Traditional evolutionary multi-objective optimization (EMO) algorithms typically return several hundred non-dominated candidate solutions. From a practical point-of-view, a small set of 5-10 distinct candidates is often preferred because post-processing of several hundred solutions may be too costly, too time-consuming, too difficult to compare design differences, or similar solutions may turn out to be statistically equal in prototyping and manufacturing. Interestingly, these limitations apply to most if not all real-world problems. In this paper we introduce a novel approach to incorporating preferences in order to make an EMO algorithm return a small set of clearly different solutions with respect to performance and design. Here, we distinguish between generalized and domain-specific preferences, where generalized preferences address the aforementioned limitations and the domain-specific preferences cover the whishes of the decisison maker. We further suggest the General Cluster-Forming Differential Evolution (GCFDE) algorithm complying to the approach of returning a small, diverse result set. The algorithm is tested on five well-known mechanical engineering problems and a real-world many-objective problem from electrical engineering. On all test problems, GCFDE located distinct optimal solutions, which shows that this is a promising approach for handling preferences in both multiand many-objective settings.
RAPID TWO-STEP BLOOD SAMPLE PREPARATION WITH ACOUSTIC MICROFLUIDIC CHIPS

Analysis of proteins in blood such as detecting antibodies in serology tests necessitates that the blood samples be stripped of their cellular components and diluted. The standard method of sample preparation requires a centrifuge and careful pipetting techniques to transfer the sample to the analysis tool. Here we present a microfluidic device that can rapidly perform two-step blood sample preparation using air-liquid cavity acoustic transducers (ALCATs). ALCATs are trapped microbubbles that generate cavitation microstreaming when activated with ultrasound. Using ALCATs, plasma separation from a blood sample followed by plasma dilution is performed wholly on chip in approximately one minute.
12 Intelligent Object Exploration

Tool use is considered to be the hallmark of higher cognitive abilities (compare e.g. Blaisdell, 2008). It is therefore the target of an extensive body of work in psychology. The mechanisms that enable the discovery of affordances in humans and animals are still not fully understood. Tool use has been observed predominantly in primates but also in other animals such as crows. Weir and Kacelnik (2007), for instance, report on a New Caledonian Crow modifying aluminum strips in order to retrieve food. The crow correctly chooses between bending and unbending aluminum strips, depending on the specific type of jar it is presented with. Studies on tool use suggest that the potential application of objects to achieve manipulation objectives can be discovered through exploration. When an affordance of an object is discovered, it becomes a tool.
Computational biomes: The ecometrics of large mammal teeth

As organisms are adapted to their environments, assemblages of taxa can be used to describe environments in the present and in the past. Here, we use a data mining method, namely redescription mining, to discover and analyze patterns of association between large herbivorous mammals and their environments via their functional traits. We focus on functional properties of animal teeth, characterized using a recently developed dental trait scoring scheme. The teeth of herbivorous mammals serve as an interface to obtain energy from food, and are therefore expected to match the types of plant food available in their environment. Hence, dental traits are expected to carry a signal of environmental conditions. We analyze a global compilation of occurrences of large herbivorous mammals and of bioclimatic conditions. We identify common patterns of association between dental traits distributions and bioclimatic conditions and discuss their implications. Each pattern can be considered as a computational biome. Our analysis distinguishes three global zones, which we refer to as the boreal-temperate moist zone, the tropical moist zone and the tropical-subtropical dry zone. The boreal-temperate moist zone is mainly characterized by seasonal cold temperatures, a lack of hypsodonty and a high share of species with obtuse lophs. The tropical moist zone is mainly characterized by high temperatures, high isothermality, abundant precipitation and a high share of species with acute rather than obtuse lophs. Finally, the tropical dry zone is mainly characterized by a high seasonality of temperatures and precipitation, as well as high hypsodonty and horizodonty. We find that the dental traits signature of African rain forests is quite different from the signature of climatically similar sites in North America and Asia, where hypsodont species and species with obtuse lophs are mostly absent. In terms of climate and dental signatures, the African seasonal tropics share many similarities with Central-South Asian sites. Interestingly, the Tibetan plateau is covered both by redescriptions from the tropical-subtropical dry group and by redescriptions from the boreal-temperate moist group, suggesting a combination of features from both zones in its dental traits and climate.
Applications of Adaptive Filtering: Recent Advancements in Active Noise Control

ACTIVENOISE CONTROL (ANC) is based on the simple principle of destructive interference of propagating acoustic waves, (Elliot, 2001). The basic idea was proposed in 1936 (Lueg, 1936), however, real applications were quite limited till recently. Thanks to advancement in the algorithms for adaptive signal processing and their implementation using digital signal processors (DSPs); many successful applications of ANC have been reported, themost famous being noise reduction headsets (Gan & Kuo, 2002; Kuo et al., 2006). The most popular adaptive algorithm used for ANC applications is the filtered-x least mean square (FxLMS) algorithm (Kuo & Morgan, 1996) which is a modified version of the LMS algorithm (Widrow & Stearns, 1985). The FxLMS algorithm is computationally simple, but its convergence speed is slow. Different ANC algorithms, with improved convergence properties, have been proposed, viz., 1) lattice-ANC systems (Park & Sommerfeldt, 1996); 2) infinite impulse response (IIR) filter-based LMS algorithms called filtered-u recursive LMS (FuRLMS) (Eriksson et al., 1987), and filtered-v algorithms (Crawford & Stewart, 1997); 3) recursive least squares (RLS) based algorithms called filtered-x RLS (FxRLS) (Kuo & Morgan, 1996) and filtered-x fast-transversal-filter (FxFTF) (Bouchard & Quednau, 2000); and 4) frequency-domain-ANC systems (see (Kuo & Tahernezhadi, 1997) and references there in). There are the following problemswith these approaches: 1) IIR-based structures have inherent stability problems; 2) other approaches mentioned above increase the computational burden substantially; and 3) RLS-based ANC systems have numerical instability problems. These reasons make FxLMS still a good choice for ANC applications, and hence, in this chapter we describe various concepts and methods using FxLMS algorithm. The main objective of this chapter is to provide a comprehensive review of adaptive filtering algorithms developed and employed for ANC systems. We also provide some recent results for two challenging problems: ANC of impulsive-like noise sources, and mitigating effect of the uncorrelated disturbances for which a correlated reference signal is not available. We see that simple modifications and extensions of the existing algorithms and methods improve robustness of the ANC systems. The outline of the chapter is as follows. Section 2 details FxLMS algorithm for feedforward and feedback type ANC systems. It also highlights signal processing issues and open problems for further research. Section 3 describes development of various adaptive algorithm for ANC for Impulsive Noise Sources, and Section 4 addresses issue of Mitigating 2
Applied Hydrological Modeling with the Use of Geoinformatics: Theory and Practice

Water resource management and catchment analysis are crucial aspects of the twentyfirst century in hydrological and environmental sciences. Linked directly with studies and research about climate change effects in global resources (e.g., diminution of rainfall dynamic), as well as continuously growing extreme natural phenomena with catastroph‐ ic results (e.g., floods and erosion), hydrological modeling has become a key priority in modern academic research goals. On a national or lower administrative level, the need for coping with natural disasters—affecting mainly human life, property, local econo‐ my, infrastructure, etc.—and the need to design management plans and projects for sustainable exploitation of natural resources set hydrological modeling in high demand by government organizations and local authorities. Thus, hazard assessment and risk evaluation modeling have become a strategic aim and an extremely useful tool for stakeholders, decision-makers, and scientific community.
Enhancement of mechanical effects of single photons in modulated two-mode optomechanics

We propose an approach to enhance the mechanical effects of single photons in a two-mode optomechanical system. This is achieved by introducing a resonance-frequency modulation to the cavity fields. When the modulation frequency and amplitude satisfy certain conditions, the mechanical displacement induced by single photons could be larger than the quantum zero-point fluctuation of the oscillating resonator. This method can be used to create distinct mechanical superposition states.
Comparison of α-synuclein gene methylation in peripheral blood mononuclear cells of Uighur and Han patients with sporadic Parkinson's disease

This study aims to investigate the correlations between the methylation level of the Parkinson's Disease (PD)-susceptibility α-synuclein gene (SNCA) intron region 1 and the PD incidences in Uighur and Han ethnic groups. The Peripheral Blood Mononuclear Cells (PBMCs) of 40 patients (19 Uighur and 21 Han) with Early-Onset Parkinson's Disease (EOPD) and 40 normal people (19 Uighur and 21 Han, ≤ 50 y old) were isolated by density gradient centrifugation, and the methylation level of SNCA gene intron region 1 was then detected using the bisulfite Polymerase Chain Reaction (PCR) sequencing method. The comparisons between the EOPD group and the ≤ 50 y old control group, between the Han-EOPD group and the Han-control group, between the Uygur-EOPD group and the Uygur-control group, between the male EOPD group and the male control group, between the female PD group and the female control group, and between the male EOPD group and the female EOPD group all showed no significant difference in the average methylation level of the SNCA gene intron region 1 (P>0.05). The methylation level of the SNCA gene intron region 1 might not be associated with the EOPD incidence in Uighur and Han patients.
Real Time Monitoring System for Surface Reconstruction Using Delaunay Algorithm

Delaunay triangulation algorithm plays an important role due to its guaranteed quality of mesh generation. It proposes optimization of mesh reconstruction system from 3D cloud point. The process monitoring is emerging as a valuable tool and realtime monitoring systems are being used to enhance operational efficiency. It is possible to develop real-time applications by generating the mesh from 3d point cloud which actually enables to describe the details of surface reconstruction and determines the surface reconstruction progress. In this paper Delaunay Algorithm simulates the mesh generation criteria. It monitors the various parameters of mesh generation and evaluates the performance of Delaunay surface reconstruction algorithm. Keywords-3d point cloud; mesh reconstruction; performance evaluation.
Circular law for sparse random regular digraphs

Fix a constant $C\geq 1$ and let $d=d(n)$ satisfy $d\leq \ln^{C} n$ for every large integer $n$. Denote by $A_n$ the adjacency matrix of a uniform random directed $d$-regular graph on $n$ vertices. We show that, as long as $d\to\infty$ with $n$, the empirical spectral distribution of appropriately rescaled matrix $A_n$ converges weakly in probability to the circular law. This result, together with an earlier work of Cook, completely settles the problem of weak convergence of the empirical distribution in directed $d$-regular setting with the degree tending to infinity. As a crucial element of our proof, we develop a technique of bounding intermediate singular values of $A_n$ based on studying random normals to rowspaces and on constructing a product structure to deal with the lack of independence between the matrix entries.