Miracle-dz/UniFAR-FTUs huggingface dataset:
Variability in the Northern North Atlantic and Arctic Oceans Across the Last Two Millennia: A Review

The climate of the last two millennia was characterized by decadal to multicentennial variations, which were recorded in terrestrial records and had important societal impacts. The cause of these climatic events is still under debate, but changes in the North Atlantic circulation have often been proposed to play an important role. In this review we compile available high‐resolution paleoceanographic data sets from the northern North Atlantic and Nordic Seas. The records are grouped into regions related to modern ocean conditions, and their variability is discussed. We additionally discuss our current knowledge from modeling studies, with a specific focus on the dynamical changes that are not well inferred from the proxy records. An illustration is provided through the analysis of two climate model ensembles and an individual simulation of the last millennium. This review thereby provides an up‐to‐date paleoperspective on the North Atlantic multidecadal to multicentennial ocean variability across the last two millennia.
Accuracy Evaluation and Consistency Analysis of Four Global Land Cover Products in the Arctic Region

Land cover is a fundamental component of crucial importance in the earth sciences. To date, many excellent international teams have created a variety of land cover products covering the entire globe. To provide a reference for researchers studying the Arctic, this paper evaluates four commonly used land cover products. First, we compare and analyze the four land cover products from the perspectives of land cover type, distribution and spatial heterogeneity. Second, we evaluate the accuracy of such products by using two sets of sample points collected from the Arctic region. Finally, we obtain the spatial consistency distribution of the products by means of superposition analysis. The results show the following: (a) among the four land cover products, Climate Change Initiative Land Cover (CCI-LC) has the highest overall accuracy (63.5%) in the Arctic region, GlobeLand30 has an overall accuracy of 62.2% and the overall accuracy of the Global Land Cover by the National Mapping Organization (GLCNMO) is only 48.8%. When applied in the Arctic region, the overall accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) is only 29.5% due to significant variances. Therefore, MODIS and GLCNMO are not recommended in Arctic-related research as their use may lead to major errors. (b) An evaluation of the consistency of the four products indicates that the classification of the large-scale homogeneous regions in the Arctic yields satisfactory results, whereas the classification results in the forest–tundra ecotone are unsatisfactory. The results serve as a reference for future research. (c) Among the four products, GlobeLand30 is the best choice for analyzing finely divided and unevenly distributed surface features such as waters, urban areas and cropland. Climate Change Initiative Land Cover (CCI-LC) has the highest overall accuracy, and its classification accuracy is relatively higher for forests, shrubs, sparse vegetation, snow/ice and water. GlobeLand30 and CCI-LC do not vary much from each other in terms of overall accuracy. They differ the most in the classification accuracy of shrub-covered land; CCI-LC performed better than GlobeLand30 in the classification of shrub-covered land, whereas the latter obtained higher accuracy than that of the former in the classification of urban areas and cropland.
Resolution limits of fluid overpressures from mineralogy, porosity, and sonic velocity variations in North Sea mudrocks

Pore pressure identification in mudrocks largely relies on indirect methods, including analyses of sonic velocity data. The magnitude of pore pressure changes that can be resolved from such data depends on the impact of fluid pressures on well log responses and on the velocity responses to lithological variations that could be mistaken for indications of pore pressure changes. Analysis of relationships between sonic velocity, mineralogy, and porosity from 11 North Sea wells demonstrated porosity variations of up to 5% from the mean value in mudrocks at any given depth between 1 and 3.5 km (3300–11,500 ft). Comparisons of these wells with seven wells from the Norwegian Sea demonstrated that the sonic velocity and density variations are influenced by the content of silica with a biogenic origin, but that they can otherwise not, in general, be related to mineralogy and pore pressure variations. The sonic velocity deviations from the mean value are of the same magnitude as those that would be caused by porosity changes of ±8% in mudrocks of uniform lithology. Furthermore, the deviations are not significantly reduced when the velocity data are compensated for changes in density (porosity). Detection limits for mechanically compacting mudrocks that are at their maximum effective stress are equivalent to static mud density changes of 0.1–0.15 g/cm3. These numbers apply to mudrocks with similar lithological variability to those analyzed in our data set but should be much higher when significant amounts of silica with a biogenic origin are present. The impact of effective stress changes on the sonic velocities of chemically compacting as well as of mechanically unloading rocks is much less because small or no porosity changes follow from the effective stress changes in such cases. The velocity responses for mechanically unloading and stress-insensitive chemical compaction can only be identified from four-dimensional (time-lapse) seismic data unless the rocks are close to the fracturing limit. These observations imply that reasonably accurate velocity-based pore pressure identification in North Sea mudrocks requires a knowledge of local mudrock heterogeneity and compaction that cannot easily be obtained. As a result, sonic velocity data should be treated with considerable caution in pore pressure evaluation.
Centralized Air Pollution Detection and Monitoring: A Review

Air pollution has become a major concern over the last quarter century and therefore mitigation of poor air quality for health and environmental reasons has been a primary focus for local governments. Industrialization and increasing number of vehicles are the primary source of pollution. There is ever rising need for continuous monitoring of air quality. A lot of technologies have introduced for measuring the air pollution. This paper presents a comparative study of the available technologies. Comparisons have been done based on measured pollutants, sensitivity, range, implementation cost, level of complexity etc., which are provided in tabular form for easy comparison. Paper also includes a proposed model which is an idea to implement the same as a real time project for air pollution detection and monitoring using microcontroller and Wi-Fi module.
Towards Building Efficient Malware Detection Engines Using Hybrid CPU/GPU-Accelerated Approaches

This chapter presents an outline of the challenges involved in constructing efficient malware detection engines using hybrid CPU/GPU-accelerated architectures and discusses how one can overcome such challenges. Starting with a general problem description for malware detection and moving on to the algorithmic background involved for solving it, the authors present a review of the existing approaches for detecting malware and discuss how such approaches may be improved through GPU-accelerated processing. They describe and discuss several hybrid hardware architectures built for detecting malicious software and outline the particular characteristics of each, separately, followed by a debate on their performance and most suitable application in real-world environments. Finally, the authors tackle the problem of performing real-time malware detection and present the most important aspects that need to be taken into account in intrusion detection systems. Ciprian Pungila West University of Timişoara, Romania Viorel Negru West University of Timişoara, Romania
Classification and Prediction Model using Hybrid Technique for Medical Datasets

For processing of large amount of data numerous techniques are used. Data Mining is one of the technique that is used most often. To process these data, Data mining combines traditional data analysis with sophisticated algorithms. Medical data mining is an important area of Data Mining and considered as one of the important research field due to its application in healthcare domain. Classification and prediction of medical datasets poses real challenges in Medical Data Mining. To cope with these challenges Logistic Regression (LR) and Artificial Neural Network (ANN) are commonly used. LR enables us to investigate the relationship between a categorical outcome and a set of explanatory variables. LR explains that there can be one or more independent variables that can determine the problem outcome. ANN resembles the human brain and here the information is processed by simple elements called neurons and signals are transmitted between the neurons. Feature subset selection selects subsets of features that are enough to explain the target concept. In this paper feature selection methods like forward selection and backward elimination using mean evaluation are used on the medical datasets. LR and ANN are applied on feature selection methods using Cross Validation Sample (CVS) and Percentage Split as test options. From the experimental results it is identified that for SPECTF dataset LR using percentage split prediction accuracy of 83.95% is achieved, for Diabetes Dataset LR using percentage split prediction accuracy of 80.46% is achieved, and for Liver Disorder dataset NN using percentage split prediction accuracy of 74.75% is achieved.
An analysis of digital transmission techniques for the local network

On evalue la capacite de transmission maximum limitee par la diaphonie comme fonction de la largeur du routage. La performance des systemes pratiques est analysee en termes de bruit de systeme, bruit impulsif, diaphonie et interferences intersymboles
Development of environmental tracers for sediments and phosphorus

Tracing eroded sediments can aid in minimising the impacts of soil erosion by improving the understanding of transport processes. A large range of sediment tracers exists; however, to date there has been no combined use of tracers which represent the full particle size range of sediments transported in overland flow. This is relevant because particles of different sizes show differing transport behaviour, but are all capable of transporting sediment bound contaminants such as phosphorus. The aim of this project was to develop a dual tracing method for both sediments and colloids in order to better represent the transport of phosphorus. The link between soil erosion and eutrophication resulting from phosphorus transport was demonstrated. A range of sediment and colloid tracers were reviewed to select the two most appropriate tracers for this project (rare earth oxides (REOs) and fluorescent microspheres). Published methodologies relating to these tracers were investigated. The tracers were then applied to soil boxes receiving simulated rainfall, as well as a field plot, to compare their transport to the relevant phase of phosphorus. The results showed comparable behaviour between REOs and particulate phosphorus. Fluorescent microspheres had low recoveries in surface runoff due to infiltration into the soil profile which limited their ability to trace colloid bound phosphorus. However, REOs were shown to be a useful tracer due to their ability to identify the sources and transport pathways of particulate phosphorus. Furthermore, the results gained from methodological development are useful for the future development of both tracing methods. Therefore, the results of this thesis provide significant steps towards improved understanding of phosphorus transport from arable land which can lead to reductions in nutrient loss and eutrophication.
A new approach for quantitative damage assessment of in-situ rock mass by acoustic emission

The purpose of this study was to propose a new approach for quantifying in situ rock mass damage, which would include a degree-of-damage and the degraded strength of a rock mass, along with its prediction based on real-time Acoustic Emission (AE) observations. The basic approach for quantifying in-situ rock mass damage is to derive the normalized value of measured AE energy with the maximum AE energy, called the degree-of-damage in this study. With regard to estimation of the AE energy, an AE crack source location algorithm of the Wigner-Ville Distribution combined with Biot\'s wave dispersion model, was applied for more reliable AE crack source localization in a rock mass. In situ AE wave attenuation was also taken into account for AE energy correction in accordance with the propagation distance of an AE wave. To infer the maximum AE energy, fractal theory was used for scale-independent AE energy estimation. In addition, the Weibull model was also applied to determine statistically the AE crack size under a jointed rock mass. Subsequently, the proposed methodology was calibrated using an in situ test carried out in the Underground Research Tunnel at the Korea Atomic Energy Research Institute. This was done under a condition of controlled incremental cyclic loading, which had been performed as part of a preceding study. It was found that the inferred degree-of-damage agreed quite well with the results from the in situ test. The methodology proposed in this study can be regarded as a reasonable approach for quantifying rock mass damage.
Secure Call and Return Instructions for Mimicry Attack Detection

There are many methods to detect buffer overflow using host-based intrusion detection systems or compiler extensions. Some attacks, however, can avoid these defense systems. 'Mimicry Attacks' is one of such attacks. In this paper, we propose a novel method to detect Mimicry Attacks. Our proposed method is able to detect invalid control data (frame pointer and return address on the call stack) overwritten by Mimicry Attacks. To achieve this detection, we extend call and return instructions with our original saving and checking processes respectively. The saving process, which is invoked before called function starts, saves the control data to the invulnerable area. The checking process, which is invoked after called function finishes, compares the saved and real control data. We have implemented our proposed method as software simulation and evaluated its time overhead. The percentage of the processing time for proposed method in each total execution time of gzip, Apache HTTP Server and we are 2.53%, 71.10% and 94.83% respectively.
Robustly Modeling The World From Photos

A camera is a device for compressing rich information about the visual appearance of the three-dimensional world into a two-dimensional image. This process is inherently lossy: given an image, we can make educated guesses about the world's shape and appearance, but there is not enough information for our guesses to be certain. However, if we take several pictures from different viewpoints we can reason more confidently. This thesis focuses on shape: How can we determine the geometry of the world from a collection of photos? This problem is classically called Structure from Motion. We find the structure (shape of the world) from camera motion (different viewpoints). Internet photo collections are an especially interesting source of data. With simple searches we can collect the raw information to reconstruct 3D models of famous world landmarks or entire cities. However, the photos we download are disorganized and noisy, and will not have been collected with 3D reconstruction in mind. While some impressive demonstrations of Structure from Motion systems exist, the next generation of solvers will need to be far more robust to the many types of difficulties encountered in the wild. To this end, many recent solvers pose the problem in a new way, using relative relationships between images to infer first the orientations, and then the positions of every camera in a scene. This framework promises faster runtime and greater robustness. I contribute a theoretical analysis of the difficulty of finding camera orien-tations, giving a way to decide which problems are tractable and which ones might be too hard and should be reformulated. I also propose a new solver with an accompanying outlier filter for finding camera positions. However, some of the hardest scenes are those which contain ambiguous structures: objects that look the same but are not. These induce self-consistent errors which are often too confusing for solvers to resolve correctly. I describe a scalable system which uses a graph-topological cue from a visibility graph to detect and remove these sources of error. Together these improvements work towards a robust solution to the Structure from Motion problem, so that we can reliably build 3D models of the world, even from noisy and confusing internet photo collections. graduating first in his class from Dublin Coffman High School. Kyle attended college at Rose-Hulman Institute of Technology, where he completed bachelors degrees in math and mechanical engineering. Intervarsity Christian Fellowship was particularly formative to …
Wireless multi-hop network scenario emulation by controlling maximal error

A fundamental issue for ad-hoc network emulation is how to emulate a wireless multi-hop network scenario in a fixed testbed, but the existing RF-control wireless network emulators did not deeply discuss this issue. Wireless multi-hop scenario emulation problem was formulated based on RF-control, the maximal error was taken controlling as the solution mentality, and an algorithm called matching exact-solution condition algorithm was presented. Experiment results show that the algorithm can solve the wireless multi-hop network scenario emulation problem and the maximal error can be achieved.
Development of accurate well models for numerical reservoir simulation

Peaceman well model is widely used in numerical reservoir simulation. With the help of the defined equivalent radius, the bottom-hole inflow or outflow flux can be calculated and is proportional to the difference of the bottom-hole pressure and the well grid pressure. It is shown in this article, though the bottom-hole flux is calculated accurately in Peaceman well model, there are some significant errors of pressure near the well for the large value of the length-to-width ratio of the mesh. Two alternative methods, the source term compensation method and the pattern competition method, which are both based on the analytic solution induced by the source term, are proposed for homogeneous medium. In the source term compensation method, auxiliary pressure, which satisfies the Laplace equation strictly, is defined and solved instead of the original pressure variable, which actually satisfies the Poisson equation. In the pattern competition method, different flow patterns including the linear flow pattern and radial flow pattern are considered. Each flow pattern corresponds to a transmissibility of the adjacent two grids and all the transmissibilities are calculated respectively. The smallest transmissibility will outcompete, and be used for solving the discrete pressure equations. Numerical results show that for the two proposed methods, not only the bottom-hole flux but also the pressure fields can be calculated accurately. Cited as : Zhang, S. , Liu, Z. , Shi, A. , Wang, X. Development of accurate well models for numerical reservoir simulation. Advances in Geo-Energy Research, 2019, 3(3): 250-257, doi: 10.26804/ager.2019. 03.03
Assessing DOC export from a Sphagnum‐dominated peatland using δ13C and δ18O–H2O stable isotopes

Dissolved organic carbon (DOC) originating in peatlands can be mineralized to carbon dioxide (CO2) and methane (CH4), two potent greenhouse gases. Knowledge of the dynamics of DOC export via run‐off is needed for a more robust quantification of C cycling in peatland ecosystems, a prerequisite for realistic predictions of future climate change. We studied dispersion pathways of DOC in a mountain‐top peat bog in the Czech Republic (Central Europe), using a dual isotope approach. Although δ13CDOC values made it possible to link exported DOC with its within‐bog source, δ18OH2O values of precipitation and run‐off helped to understand run‐off generation. Our 2‐year DOC–H2O isotope monitoring was complemented by a laboratory peat incubation study generating an experimental time series of δ13CDOC values. DOC concentrations in run‐off during high‐flow periods were 20–30 mg L−1. The top 2 cm of the peat profile, composed of decaying green moss, contained isotopically lighter C than deeper peat, and this isotopically light C was present in run‐off in high‐flow periods. In contrast, baseflow contained only 2–10 mg DOC L−1, and its more variable C isotope composition intermittently fingerprinted deeper peat. DOC in run‐off occasionally contained isotopically extremely light C whose source in solid peat substrate was not identified. Pre‐event water made up on average 60% of the water run‐off flux, whereas direct precipitation contributed 40%. Run‐off response to precipitation was relatively fast. A highly leached horizon was identified in shallow catotelm. This peat layer was likely affected by a lateral influx of precipitation. Within 36 days of laboratory incubation, isotopically heavy DOC that had been initially released from the peat was replaced by isotopically lighter DOC, whose δ13C values converged to the solid substrate and natural run‐off. We suggest that δ13C systematics can be useful in identification of vertically stratified within‐bog DOC sources for peatland run‐off.
Speech And Audio Processing In Adverse Environments

Thank you very much for downloading speech and audio processing in adverse environments. As you may know, people have look numerous times for their chosen books like this speech and audio processing in adverse environments, but end up in harmful downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they cope with some infectious bugs inside their desktop computer.
Effect of seeding time on the formation of gold nanoplates

Metallic nanostructures, such as gold, is very sensitive to the dielectric environment of the materials due to strong dependency of plasmon on shapes and sizes. Thus, its unique properties are very good and can be used as sensing material in plasmonic sensor. This paper reports a study on the surface density on the formation of gold nanoplates with variation of seeding time. The gold nanoplates have been grown on a quartz substrate using seed mediated growth method. In this study, the seeding time was varied from one to three hours and labelled as MP1, MP2 and MP3. The XRD analysis shows two peaks of the diffraction angle occurs at the plane (111) in position ~ 38.2o and plane (200) at ~ 44.20o. Through variation of the seeding time, the optimum surface density is 61.8 % with a total of 43.7 % of the nanoplates shape from sample MP2. The optical absorption spectrum of the sample shows two resonance peaks, ~ 550 nm and 660 nm, which are corresponding to the transverse surface plasmon resonance (t-SPR) and the longitudinal surface plasmon resonance (l-SPR) respectively. Thus, in this study, it is found that the seeding time affected the growth of the gold nanostructures with optimum seeding time of two hours. Longer seeding time caused the growth of stacking nanogold and it is not suitable to be used in sensing application because of its broad and wider optical spectrum.