Miracle-dz/UniFAR-FTUs huggingface dataset:
360° Surface Regression with a Hyper-Sphere Loss

Omnidirectional vision is becoming increasingly relevant as more efficient 360° image acquisition is now possible. However, the lack of annotated 360° datasets has hindered the application of deep learning techniques on spherical content. This is further exaggerated on tasks where ground truth acquisition is difficult, such as monocular surface estimation. While recent research approaches on the 2D domain overcome this challenge by relying on generating normals from depth cues using RGB-D sensors, this is very difficult to apply on the spherical domain. In this work, we address the unavailability of sufficient 360° ground truth normal data, by leveraging existing 3D datasets and remodelling them via rendering. We present a dataset of 360° images of indoor spaces with their corresponding ground truth surface normal, and train a deep convolutional neural network (CNN) on the task of monocular 360° surface estimation. We achieve this by minimizing a novel angular loss function defined on the hyper-sphere using simple quaternion algebra. We put an effort to appropriately compare with other state of the art methods trained on planar datasets and finally, present the practical applicability of our trained model on a spherical image re-lighting task using completely unseen data by qualitatively showing the promising generalization ability of our dataset and model.
Source of coesite inclusions within inherited magmatic zircon from Sulu UHP rocks, eastern China, and their bearing for fluid–rock interaction and SHRIMP dating

The 5‐km deep Chinese Continental Scientific Drilling Main Hole penetrated a sequence of ultrahigh pressure (UHP)‐metamorphic rocks consisting mainly of eclogite, gneiss and garnet‐peridotite with minor schist and quartzite. Zircon separates taken from thin layers of schist and gneiss within eclogite were investigated. Cathodoluminescence images of zircon grains show that they have oscillatory zoned magmatic cores and unzoned to patchy zoned metamorphic rims. Zircon rims contain rare coesite and calcite inclusions whereas cores contain inclusions of both low‐P minerals (e.g. feldspar, biotite and quartz) and coesite and other eclogite‐facies minerals such as phengite and jadeite. The zircon cores give highly variable 206Pb/238U ages ranging from 760 to 431 Ma for schist and from 698 to 285 Ma for gneiss, and relatively high but variable Th/U ratios (0.16–1.91). We suggest that the coesite and other eclogite facies mineral inclusions in zircon cores were not magmatic but formed through metasomatic processes caused by fluids during UHP metamorphism, and that the fluids contain components of SiO2, Al2O3, K2O, FeO, MgO, Na2O and H2O. Metasomatism of the Sulu UHP rocks during continental subduction to mantle depths has partly altered magmatic zircon cores and reset isotopic systems. This study provides key evidence that mineral inclusions within magmatic zircon domains are not unequivocal indicators of the formation conditions of the respective domain. This finding leads us to conclude that the routine procedure for dating of metamorphic events solely based on the occurrence of mineral inclusions in zoned zircon could be misleading and the data should be treated with caution.
Phishing counter measures and their effectiveness - literature review

– Phishing is essentially a social engineering crime on the Web, whose rampant occurrences and technique advancements are posing big challenges for researchers in both academia and the industry. The purpose of this study is to examine the available phishing literatures and phishing countermeasures, to determine how research has evolved and advanced in terms of quantity, content and publication outlets. In addition to that, this paper aims to identify the important trends in phishing and its countermeasures and provides a view of the research gap that is still prevailing in this field of study. , – This paper is a comprehensive literature review prepared after analysing 16 doctoral theses and 358 papers in this field of research. The papers were analyzed based on their research focus, empirical basis on phishing and proposed countermeasures. , – The findings reveal that the current anti‐phishing approaches that have seen significant deployments over the internet can be classified into eight categories. Also, the different approaches proposed so far are all preventive in nature. A Phisher will mainly target the innocent consumers who happen to be the weakest link in the security chain and it was found through various usability studies that neither server‐side security indicators nor client‐side toolbars and warnings are successful in preventing vulnerable users from being deceived. , – Educating the internet users about phishing, as well as the implementation and proper application of anti‐phishing measures, are critical steps in protecting the identities of online consumers against phishing attacks. Further research is required to evaluate the effectiveness of the available countermeasures against fresh phishing attacks. Also there is the need to find out the factors which influence internet user's ability to correctly identify phishing websites.
Erosão marginal e sedimentação no rio Paraguai no município de Cáceres (MT)

The High Paraguay River Basin has been intensively occupied since the 1970 years and its channel dynamic has been changing. The dynamics of the fluvial corridor's margins was studied, tends as objective evaluating the erosion for a period of nineteen years, using the crossing of images of satellite TM Landsat 5 of the year of 1984 and ETM Landsat 7 de 2003. Considering the bank erosion, the channel showed a relatively high mobility in both segments (2, 3 m/y).
RSLIS at INEX 2012: Social Book Search Track

In this paper, we describe our participation in the INEX 2012 So- cial Book Search track. We investigate the contribution of different types of document metadata, both social and controlled, and examine the effective- ness of re-ranking retrieval results using different social features, such as user ratings, tags, and authorship information. We find that the best results are obtained using all available document fields and topic representations. Re- ranking retrieval results works better on shorter topic representations, where there is less information for the retrieval algorithm to work with; longer topic representations do not benefit from our social re-ranking approaches.
A note on a two dimensional knapsack problem with unloading constraints

In this paper we address the two-dimensional knapsack problem with unloading constraints: we have a bin B , and a list L of n rectangular items, each item with a class value in {1,. ,C }. The problem is to pack a subset of L into B , maximizing the total profit of packed items, where the packing must satisfy the unloading constraint: while removing one item a , items with higher class values can not block a . We present a (4 + ϵ )-approximation algorithm when the bin is a square. We also present (3 + ϵ )-approximation algorithms for two special cases of this problem.
Compiling with Continuations

This book shows how continuation-passing style is used as an intermediate representation to perform optimizations and program transformations. Continuations can be used to compile most programming languages. The method is illustrated in a compiler for the programming language Standard ML. Prior knowledge of ML, however, is not necessary, as the author carefully explains each concept as it arises. This is the first book to show how concepts from the theory of programming languages can be applied to the production of practical optimizing compilers for modern languages like ML. All the details of compiling are covered, including the interface to a runtime system and garbage collector.
A Report on a Biotite‐Calcic Hornblende Geothermometer

Abstract This paper presents a biotite‐calcic hornblende geothermometer which was empirically calibrated based on the garnet‐biotite geothermometer and the garnet‐plagioclase‐hornblende‐quartz geobarometer, in the ranges of 560–800°C (T) and 0.26–1.4 GPa (P) using the data of metadolerite, amphibolite, metagabbro, and metapelite collected from the literature. Biotite was treated as symmetric Fe‐Mg‐AlVI‐Ti quaternary solid solution, and calcic hornblende was simplified as symmetric Fe‐Mg binary solid solution. The resulting thermometer may rebuild the input garnet‐biotite temperatures well within an uncertainty of ±50°C. Errors of ±0.2 GPa for input pressure, along with analytical errors of ±5% for the relevant mineral compositions, may lead to a random error of ±16°C for this thermometer, so that the thermometer is almost independent of pressure estimates. The thermometer may clearly discriminate different rocks of lower amphibolite, upper amphibolite and granulite facies on a high confidence level. It is assumed that there is a ferric iron content of 11.6% in biotite, and that the iron content in calcic hornblende may be calculated according to the method of Dale et al. (2000). This thermometer can be used for medium‐ to high‐grade metabasites and metapelites.
Using Eddy Covariance, Soil Water Balance, and Photosynthetically Active Radiation Methods for Corn Evapotranspiration Measurements in the Red River Valley

Abstract. Evapotranspiration (ET) is an important component for determining water balance and water transfer. Water management practices (WMP) that utilize soil water balance algorithms to determine the best irrigation schedules tend to rely heavily on measured or estimated ET values. However, ET values can be difficult and expensive to obtain. In this study, three different methods were used to estimate ET: eddy covariance (EC), soil water balance (SWB), and photosynthetically active radiation (PAR). The EC method is considered as one of the most accurate methods, but the EC system is relatively expensive and requires trained personnel to conduct the calculations. The real-time ET estimates using the PAR method and wireless data access have provided simple and cheap ways to estimate ET. The SWB method has been traditionally used to estimate ET, but when a shallow water table is present and upward flux is not considered, its accuracy is questionable. In 2012, these three methods were used to estimate ET for two corn varieties in four production fields located in Clay County, Minnesota. The four adjacent fields each had a different water management system; undrained (UD), subsurface drained (SD), controlled drained (CD), and CD plus subirrigated (CD + SI). At the CD + SI site, EC, SWB, and PAR were used to measure ET, while for the other three fields, only one method, either SWB or PAR, was used. It was found that PAR ET agreed relatively well with ET by EC method with a coefficient of determination (R 2 ) of 0.94 and root mean square error of 0.02 mm/30 min. However, the SWB estimates were highly variable and showed little to no correlation with EC ET data. This paper will present comparisons across the three ET methods, four water management practices, and two corn varieties.
Climatology of potential vorticity streamers and associated isentropic transport pathways across PV gradient barriers

The European Centre for Medium‐Range Weather Forecasts reanalysis product ERA‐Interim from 1979 to 2011 is used to investigate potential vorticity (PV) streamers as indicators of Rossby wave breaking (RWB) and the exchange of air masses between the tropics and the extratropics on isentropes between 350 and 500 K. The concept of the strongest isentropic gradients of PV and wind is applied to mark a dynamically relevant PV boundary on every isentrope. An Eulerian algorithm is then used to identify streamers of this PV contour and a trajectory‐based technique to study the exchange across this contour. The climatology of PV streamers reveals a seasonal cycle with a higher frequency in summer than in winter in both hemispheres on all isentropes. During winter, PV streamers are suppressed above 400 K in line with the occurrence of polar vortices. Globally, the highest frequency of PV streamers is found between 380 and 420 K over the eastern North Pacific in summer. Exchange trajectories associated with these PV streamers constitute important atmospheric transport pathways between the tropics and extratropics. In both hemispheres, PV streamers and their associated air mass exchange are controlled by the presence of monsoon anticyclones in summer and by RWB in the vicinity of jet splittings in winter. Cross‐hemispheric transport is observed between 380 and 400 K in the westerly ducts over the Pacific and Atlantic. Equatorward PV streamers are connected with a more frequent exchange than poleward PV streamers, indicating a more reversible poleward and irreversible equatorward RWB. The latter is often connected with a frequent breaking into PV cutoffs.
Man-in-the-Middle Attack against Object Detection Systems

—Is deep learning secure for robots? As embedded systems have access to more powerful CPUs and GPUs, deep-learning-enabled object detection systems become pervasive in robotic applications. Meanwhile, prior research unveils that deep learning models are vulnerable to adversarial attacks. Does this put real-world robots at threat? Our research borrows the idea of the Main-in-the-Middle attack from Cryptography to attack an object detection system. Our experimental results prove that we can generate a strong Universal Adversarial Perturbation (UAP) within one minute and then use the perturbation to attack a detection system via the Man-in-the-Middle attack. Our ﬁndings raise a serious concern over the applications of deep learning models in safety-critical systems such as autonomous driving.
Origin of saline fluids in sedimentary basins

Abstract Subsurface saline waters in sedimentary basins can be divided into three groups based on their anionic composition and salinity: (1) Waters with anions other than Cl dominant. These include Na-HCO3 and Na-acetate waters. Most such waters have salinities of less than 10 000 mg 1−1; (2) Cl-dominated, halite-undersaturated waters having salinities between 10 000 and 250 000–300 000 mg l−1. These include Na-Cl waters and, at higher salinities, Na-Ca-Cl waters; (3) Cl-dominated, halite-saturated waters with salinities typically in excess of 300 000 mg 1−1. Ca and K become increasingly dominant and Na decreases with increasing salinity. Subaerial evaporation of marine and continental waters and the subsurface dissolution of evaporites both have the potential for producing the range of salinities and dissolved chloride concentrations observed for most subsurface brines, but not their major cation compositions. The broad systematic increase in dissolved Na, K, Mg, Ca, and Sr and decrease in pH and alkalinity with increasing salinity support the hypothesis that the approach toward thermodynamic buffering by silicate-carbonate ± (halide) mineral assemblages is a first-order control on subsurface fluid compositions, even at temperatures well below 100°C. The chemical potential of chloride or, alternatively, the aqueous concentration of anionic charge, is a master variable which ranks in importance with such other variables as pressure and temperature in driving fluid-rock exchange and controlling bulk fluid compositions. This variable is in turn controlled largely by physical processes of fluid advection and dispersion. Dissolved organic acid anions are associated primarily with low salinity waters, but dissolved metals, such as Cu, Pb, and Zn are preferentially found in brines having salinities in excess of 200 g 1−1. The high chloride concentration and low pH of these saline waters may enhance solubilization of metals through chloride complexing.
This Reprint May Differ from the Original in Pagination and Typographic Detail. Support Vector Machine Integrated with Game-theoretic Approach and Genetic Algorithm for the Detection and Classification of Malware Support Vector Machine Integrated with Game-theoretic Approach and Genetic Algorithm fo

All material supplied via JYX is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the repository collections is not permitted, except that material may be duplicated by you for your research use or educational purposes in electronic or print form. You must obtain permission for any other use. Electronic or print copies may not be offered, whether for sale or otherwise to anyone who is not an authorised user. (2013). Support Vector Machine Integrated with game-theoretic approach and genetic algorithm for the detection and classification of malware. Abstract—In the modern world, a rapid growth of malicious software production has become one of the most significant threats to the network security. Unfortunately, widespread signature-based anti-malware strategies can not help to detect malware unseen previously nor deal with code obfuscation techniques employed by malware designers. In our study, the problem of malware detection and classification is solved by applying a data-mining-based approach that relies on supervised machine-learning. Executable files are presented in the form of byte and opcode sequences and n-gram models are employed to extract essential features from these sequences. Feature vectors obtained are classified with the help of support vector classifiers integrated with a genetic algorithm used to select the most essential features, and a game-theory approach is applied to combine the classifiers together. The proposed algorithm, ZSGSVM, is tested by using a set of byte and opcode sequences obtained from a set containing executable files of benign software and malware. As a result, almost all malicious files are detected while the number of false alarms remains very low.
Massively Parallel Algorithms for Trace-Driven Cache Simulations

Considers the use of massively parallel architectures to execute a trace-driven simulation of a single cache set. A method is presented for the least-recently-used (LRU) policy, which, regardless of the set size C, runs in time O(log N) using N processors on the EREW (exclusive read, exclusive write) parallel model. A simpler LRU simulation algorithm is given that runs in O(C log N) time using N/log N processors. We present timings of this algorithm's implementation on the MasPar MP-1, a machine with 16384 processors. A broad class of reference-based line replacement policies are considered, which includes LRU as well as the least-frequently-used (LFU) and random replacement policies. A simulation method is presented for any such policy that, on any trace of length N directed to a C line set, runs in O(C log N) time with high probability using N processors on the EREW model. The algorithms are simple, have very little space overhead, and are well suited for SIMD implementation. >
Long‐term summer (AD751–2008) temperature fluctuation in the French Alps based on tree‐ring data

Corona, C. , Edouard, J.‐L. , Guibal, F. , Guiot, J., Bernard, S. , Thomas, A. & Denelle, N. 2010: Long‐term summer (AD751–2008) temperature fluctuation in the French Alps based on tree‐ring data. Boreas, 10.1111/j.1502‐3885.2010. 00185.x. ISSN 0300‐9843.
A Bio-Inspired Chaos Sensor Based on the Perceptron Neural Network: Concept and Application for Computational Neuro-science

: The study presents a bio-inspired chaos sensor based on the perceptron neural network. After training, the sensor on perceptron, having 50 neurons in the hidden layer and 1 neuron at the output, approximates the fuzzy entropy of short time series with high accuracy with a determination coefficient R 2 ~ 0.9. The Hindmarsh-Rose spike model was used to generate time series of spike intervals, and datasets for training and testing the perceptron. The selection of the hyperparameters of the perceptron model and the estimation of the sensor accuracy were performed using the K-block cross-validation method. Even for a hidden layer with 1 neuron, the model approximates the fuzzy entropy with good results and the metric R 2 ~0.5 – 0.8. In a simplified model with 1 neuron and equal weights in the first layer, the principle of approximation is based on the linear transformation of the average value of the time series into the entropy value. The bio-inspired chaos sensor model based on an ensemble of neurons is able to dynamically track the chaotic behavior of a spiked biosystem and transmit this information to other parts of the biosystem for further processing. The study will be useful for specialists in the field of computational neuroscience.
Distribución espacial de la radiación fotosintéticamente activa en Argentina

Solar radiation is information often required for studying energy balance or the growth of a specific culture. Although in general it is able to dispose of measured or estimated global irradiation data, information of photosynthetically active radiation (PAR) is not always available. Taking into account an empirical relationship established between daily totals of PAR and global solar radiation (0.47), and the existence of charts with the distribution of monthly mean values of daily global irradiation in Argentina, PAR monthly charts are presented in this work.
The integrated cutting and packing heterogeneous precast beams multiperiod production planning problem

We introduce a novel variant of cutting production planning problems named Integrated Cutting and Packing Heterogeneous Precast Beams Multiperiod Production Planning (ICP-HPBMPP). We propose an integer linear programming model for the ICP-HPBMPP, as well as a lower bound for its optimal objective function value, which is empirically shown to be closer to the optimal solution value than the bound obtained from the linear relaxation of the model. We also propose a genetic algorithm approach for the ICP-HPBMPP as an alternative solution method. We discuss computational experiments and propose a parameterization for the genetic algorithm using D-optimal experimental design. We observe good performance of the exact approach when solving small-sized instances, although there are difficulties in finding optimal solutions for medium and large-sized problems, or even in finding feasible solutions for large instances. On the other hand, the genetic algorithm is shown to typically find good-quality solutions for large-sized instances within short computing times.
What can one chromosome tell us about human biogeographical ancestry?

We study the problem of predicting human biogeographical ancestry using genomic data. While continental level ancestry is relatively simple using genomic information, distinguishing between individuals from closely associated subpopulations (e.g., from the same continent) is still a difficult challenge. In particular, we focus on the case where the analysis is constrained to using single nucleotide polymorphisms (SNPs) from just one chromosome. We thus propose methods to construct such ancestry informative SNP panels, and assess the performance of such SNP panels from just one chromosome, for both continental-level and sub-population level ancestry prediction. We present results on the performance of the proposed methods, including a comparison with other related methods.