Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial Estimation of Classification Accuracy Using Indicator Kriging with an Image-Derived Ambiguity Index

Traditional classification accuracy assessments based on summary statistics from a confusion matrix furnish a global (location invariant) view of classification accuracy. To estimate the spatial distribution of classification accuracy, a geostatistical integration approach is presented in this paper. Indicator kriging with local means is combined with logistic regression to integrate an image-derived ambiguity index with classification accuracy values at reference data locations. As for the ambiguity measure, a novel discrimination capability index (DCI) is defined from per class posteriori probabilities and then calibrated via logistic regression to derive soft probabilities. Integration of indicator-coded reference data with soft probabilities is finally carried out for mapping classification accuracy. It is demonstrated via a case study involving classification of multi-temporal and multi-sensor SAR datasets, that the proposed approach can provide a map of locally-varying accuracy values, while respecting the overall accuracy derived from the confusion matrix. It can also highlight areas where the benefit of data fusion was significant. It is expected that the indicator approach presented in this paper could be a useful methodology for assessing the spatial quality of classification results in a probabilistic way.
Energy-Efficiency Based Resource Allocation for D2D Communication and Cellular Networks

In this paper, we present an energy efficiency based resource allocation scheme for a heterogeneous integrated network consisting of device-to-device (D2D) communication system and a cellular communication system. We study the power allocation and network mode selection scheme for users' coexistence of both systems in terms of energy efficiency maximization of the heterogeneous network (Het Net). The formulated optimization problem is a fractional non-convex problem, the standard convex optimization techniques cannot be applied directly. With the use of fractional programming and dual problem formulation, we are able to solve the non-convex problem, taking into consideration the minimum data rate required, the minimum received power and the maximum device dependent radiated power constraints. Results show that the optimal solution can be achieved with a relatively small number of iterations. Also results show that the increase in both the number of users and system data rate does not necessarily lead to an increase in the energy efficiency of the network.
Assumptions in relational database theory

Many results in relational database theory on the structure of dependencies, query languages, and databases in general have now been established. However, neither (a) the reliance of these results on various assumptions, nor (b) the desirability or reasonableness of these assumptions themselves have been closely examined. These assumptions are nontrivial: examples include the universal relation assumption and the lossless join assumption.The purpose of the present paper is to clarify many of the existing assumptions, and point out weaknesses. This is desirable both to harden the statements of previous results, and to evaluate recent suggestions that certain assumptions (such as the acyclic JD assumption) may be useful for modeling "real world" databases. Specifically, studies are made of assumptions made for (1) universal relations, (2) functional dependency inference, and (3) decomposition theory. We show that:• Some assumptions (such as uniqueness of relationships among attributes) can be more powerful than they appear;• common treatment of FDs is sometimes inappropriate, and for example FD inferences such as {A → B, B → C} |= A → C can be incorrect;• the 'decomposition' approach to design may be hard to justify in real terms; and• Acyclic JDs may have drawbacks in eliminating ambiguity in queries and in modeling real enterprises.It is hoped that this exposition will help clarify some confusing issues in this field, and will lead to a better understanding of which assumptions are reasonable and useful in modeling the "real world".
Assessment of human exposure to chemicals from Superfund sites.

Assessing human exposure to chemicals from Superfund sites requires knowledge of basic physical, chemical, and biological processes occurring in the environment and specific information about the local environment and population in the vicinity of sites of interest. Although progress is being made in both areas, there is still a tremendous amount to be done. Participants at this meeting have identified several of the areas in need of greater understanding, and they are listed below. Movement of dissolved and volatile organics, especially NAPLs, in the subsurface environment. This includes study of the partitioning of compounds between NAPLs, air, water, and soil. Partitioning of volatilized chemicals between gaseous and aerosol components of the atmosphere. This includes understanding how these components influence both wet and dry deposition. Long-term movement from sediments into biota and how these affect chronic toxicity to sediment biota. Broad validation of PBPK models describing partitioning of compounds from sediment and water into fish. Reactions of chemicals sorbed to atmospheric particles. This includes application of laboratory models to real and varied atmospheric conditions. Interactions between biotic and abiotic transformations in soil and sediment. Applicability of physiological pharmacokinetic models developed in laboratory studies of experimental animals and clinical investigations of humans to environmental chemicals, concentrations, and routes of exposure in humans. Use of human and wildlife behavioral and biomonitoring information to estimate exposure. This includes better understanding of human variability and the applicability of information gathered from particular wildlife species. To successfully address these gaps in our knowledge, much more analytical data must be collected. (ABSTRACT TRUNCATED AT 250 WORDS)
Phase velocities of elastic waves in a porous stratum saturated by gas and water

A plane homogeneous porous layer saturated by gas and water is considered. A mathematical model describing distributions of the saturants' pressure and mass density along the transversal coordinate depending of the amount of the gas accumulated in the layer is developed. On this basis, with the use of the know Gassmann model, effective elasticity moduli and phase velocities of longitudinal and transversal elastic waves are calculated.
The Complexity of the A B C Problem

We present a deterministic polynomial-time algorithm for the A B C problem, which is the membership problem for 2-generated commutative linear semigroups over an algebraic number field. We also obtain a polynomial-time algorithm for the (easier) membership problem for 2-generated abelian linear groups. Furthermore, we provide a polynomial-sized encoding for the set of all solutions.
A Secured Joint Encrypted Watermarking InMedical Image Using Block Cipher Algorithm

At present year, most of the hospitals and diagnostic centre have exchanging the biomedical information through wireless media. reliability of the information can be verified by adding ownership data as the watermarking and encryption in the original information. In our proposed work, a joint encryption/watermarking system for the purpose of protecting medical image. This system based on approach which combines a substitutive watermarking algorithm with an encryption algorithm, advanced encryption standard (AES) in counter mode. If the watermarking and encryption are conducted jointly at the protection stage, watermark extraction and decryption can be applied independently. The capability of our system to securely make available security attributes in encrypted domains while minimizing the elapsed time. Furthermore, by making use of the AES algorithm in counter (CTR) mode make our compliant with the DICOM (Digital Imaging and Communications in Medicine) standard.
Analytical model of the nonlinear dynamics of cantilever tip-sample surface interactions for various acoustic atomic force microscopies

An analytical model is developed of the interaction of the cantilever tip of an atomic force microscope with the sample surface that treats the cantilever and sample as independent systems coupled by a nonlinear force acting between the cantilever tip and a volume element of the sample surface. To maintain equilibrium, the volume element is subjected to a restoring force from the remainder of the sample. The model accounts for the positions on the cantilever of the cantilever tip, laser probe, and excitation force (if any). The model leads to a pair of coupled nonlinear differential equations that are solved analytically using a matrix iteration procedure. Solutions are obtained for the phase and amplitude signals generated by various acoustic atomic force microscope (A-AFM) techniques including force modulation microscopy, atomic force acoustic microscopy, ultrasonic force microscopy, heterodyne force microscopy, resonant difference-frequency atomic force ultrasonic microscopy (RDF-AFUM), and amplitude modulation\char21{}atomic force microscopy (AM-AFM) (intermittent contact mode). The solutions are used to obtain a quantitative measure of A-AFM image contrast resulting from variations in the Young modulus of the sample. Applications of the model to measurements of LaRC™-CP2 polyimide film using RDF-AFUM and AM-AFM images predict maximum variations in the Young modulus of 24% and 18%, respectively, over a common scan area. Both predictions are in good agreement with the value of 21% obtained from independent mechanical stretching measurements of the polyimide sheet material.
Travelling light: white sharks (Carcharodon carcharias) rely on body lipid stores to power ocean-basin scale migration

Many species undertake long-distance annual migrations between foraging and reproductive areas. Such migrants depend on the efficient packaging, storage and utilization of energy to succeed. A diverse assemblage of organisms accomplishes this through the use of lipid reserves; yet, it remains unclear whether the migrations of elasmobranchs, which include the largest gill breathers on Earth, depend on such a mechanism. We examine depth records from pop-up satellite archival tags to discern changes in buoyancy as a proxy for energy storage in Eastern Pacific white sharks, and assess whether lipid depletion fuels long-distance (approx. 4000 km) migrations. We develop new algorithms to assess body condition, buoyancy and drift rate during drift dives and validate the techniques using a captive white shark. In the wild, we document a consistent increase in drift rate over the course of all migrations, indicating a decrease in buoyancy caused by the depletion of lipid reserves. These results comprise, to our knowledge, the first assessment of energy storage and budgeting in migrating sharks. The methods provide a basis for further insights into using electronic tags to reveal the energetic strategies of a wide range of elasmobranchs.
Scale space for central catadioptric systems: Towards a generic camera feature extractor

In this paper we propose a new approach to compute the scale space of any omnidirectional image acquired with a central catadioptric system. When these cameras are central they are explained using the sphere camera model, which unifies in a single model, conventional, paracatadioptric and hypercatadioptric systems. Scale space is essential in the detection and matching of interest points, in particular scale invariant points based on Laplacian of Gaussians, like the well known SIFT. We combine the sphere camera model and the partial differential equations framework on manifolds, to compute the Laplace-Beltrami (LB) operator which is a second order differential operator required to perform the Gaussian smoothing on catadioptric images. We perform experiments with synthetic and real images to validate the generalization of our approach to any central catadioptric system.
Algorithms of Optimization of a Two-Stage Procedure for Objects Detection and Recognition

This paper is about the optimization of the procedure for recognition of local objects in an image with the assumption, that the process of data processing is parted into two stages: preliminary detection and recognition. It seems to be perspective to use such approach to the real-time object recognition. In work the approach permitting to reduce the optimization task of the two-stage procedure to iterative algorithm of serial tuning of qualifiers of the first and second stages is offered. Within this framework the iterative optimization algorithm is developed. The examples of optimization of the two-stage procedure and outcomes of its work are given for the task of the objects recognition in an images.
Recognizing Emotions in the Singing Voice

Although the human ability to recognize emotions in vocal speech utterances with reasonable accuracy has been well documented in numerous studies, little research has been reported on emotion recognition from emotional expression in the singing voice. This paper is the first to examine this issue by asking internationally known professional opera singers to portray 9 major emotions by singing sequences of nonsense syllables on the standard musical scale. We then asked more than 500 hundred listener/judges from different cultures with a wide range of musical preferences and degree of musical knowledge to recognize the intended emotions from the voice recordings. The data show that listeners are indeed able to recognize emotions expressed in singing with better-than-chance accuracy. In addition, we find some evidence that there seem to be only minor effects of culture or language on the ability to recognize the emotional interpretations. Some emotions are more easily recognized than others are. Overall, recognition ability from the singing voice compares well to accuracy rates in studies using speaking. Judges clearly use the differential acoustic patterns of sound generated by the singers in their performance to infer the emotion expressed, as demonstrated by comparing the recognition rates for different emotions to results of statistical classification based on acoustic parameters. We also attempt to explore the nature of the inference process by examining, using path models, the major acoustic variables involved and the inference from subjectively perceived configurations of voice quality.
Performance of keystroke biometrics authentication system using artificial neural network (ANN) and distance classifier method

Having a secure information system depends on successful authentication of legitimate users so as to prevent attacks from fraudulent persons. Traditional information security systems use a password or personal identification number (PIN). This means they can be easily accessed by unauthorized persons without access being noticed. This paper addresses the issue of enhancing such systems using keystroke biometrics as a translucent level of user authentication. The paper focuses on using the time interval (key down-down) between keystrokes as a feature of individuals' typing patterns to recognize authentic users and reject imposters. A Multilayer Perceptron (MLP) neural network with a Back Propagation (BP) learning algorithm is used to train and validate the features. The results are compared with a Radial Basis Function (RBF) neural network and several distance classifier method used in literature based on Equal Error Rate (EER).
Merger Rate of Equal-Mass Spherical Galaxies

We present cross sections and reaction rates for merging to occur during encounters of equal-mass spherical galaxies. As an application, we determine the rate of galaxy merging in clusters of galaxies. We present results for two types of Plummer models (a full and a truncated one), two King models, and the Hernquist model. Cross sections are determined on the basis of a large number (~500) of simulations of galaxy encounters, using the 10 Gigaflops GRAPE-3A special purpose computer. We characterize the overall merger rate of galaxies in a galaxy cluster by a single number, derived from our cross sections by an integration over galaxy encounter velocities in the limit of a constant density in velocity space. For small clusters, where the cluster velocity dispersion may not significantly exceed the internal velocity dispersion of the individual galaxies, this constant-density approximation may not be valid. For those cases, we present separate results, based on integrations of our cross sections over Maxwellian velocity distributions. Finally, tidal effects from the cluster potential, as well as from neighboring galaxies, may prevent a barely bound galaxy pair from spiraling in after their first encounter. We give a quantitative estimate of the resulting reduction in the actual merger rate that is due to these tidal interactions.
ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data

RNA-binding proteins (RBPs) play important roles in RNA post-transcriptional regulation and recognize target RNAs via sequence-structure motifs. To which extent RNA structure influences protein binding in the presence or absence of a sequence motif is still poorly understood. Existing RNA motif finders which produce informative motifs and simultaneously capture the relationship between primary sequence and different RNA secondary structures are missing. We developed ssHMM, an RNA motif finder that combines a hidden Markov model (HMM) with Gibbs sampling to learn the joint sequence and structure binding preferences of RBPs from high-throughput data, such as CLIP-Seq sequences, and visualizes them as a graph. Evaluations on synthetic data showed that ssHMM reliably recovers fuzzy sequence motifs in 80 to 100% of the cases. It produces motifs with higher information content than existing tools and is faster than other methods on large datasets. Examples of new sequence-structure motifs identified by ssHMM for uncharacterized RBPs are also discussed. ssHMM is freely available on Github at https://github.molgen. mpg.de/heller/ssHMM.
Modeling Reaction Time in Car-Following Behaviour Based on Human Factors

This paper develops driver reaction-time models for car-following analysis based on human factors. The reaction time was classified as brake-reaction time (BRT) and acceleration/deceleration reaction time (ADRT). The BRT occurs when the lead vehicle is barking and its brake light is on, while the ADRT occurs when the driver reacts to adjust his/her speed using the gas pedal only. The study evaluates the effect of driver characteristics and traffic kinematic conditions on the driver reaction time in a car-following environment. The kinematic conditions introduced urgency and expectancy based on the braking behaviour of the lead vehicle at different speeds and spacing. The kinematic conditions were used for evaluating the BRT and are classified as normal, surprised, and stationary. Data were collected on a driving simulator integrated into a real car and included the BRT and ADRT (as dependent variables) and driver's age, gender, driving experience, driving intensity (driving hours per week), vehicle speed, and spacing (as independent variables). The results showed that there was a significant difference in the BRT at normal, surprised, and stationary scenarios and supported the hypothesis that both urgency and expectancy had significant effects on BRT. Driver's age, gender, speed, and spacing were found to be significant variables for the BRT in all scenarios. The results also showed that driver's age and gender were significant variables for the ADRT. The research presented in this paper is part of a larger project to develop a driver- sensitive in-vehicle rear-end collision warning system. Keywords—Brake reaction time, car-following, human factors, modeling.
Optimization and self-organized criticality in a magnetic system

We propose a kind of Bak–Sneppen dynamics as a general optimization technique to treat magnetic systems. The resulting dynamics shows self-organized criticality with power-law scaling of the spatial and temporal correlations. An alternative method of the extremal optimization (EO) is also analyzed here. We provided a numerical confirmation that, for any possible value of its free parameter τ, the EO dynamics exhibits a non-critical behavior with an infinite spatial range and exponential decay of the avalanches. Using the chiral clock model as our test system, we compare the efficiency of the two dynamics with regard to their abilities to find the system's ground state.
Decentralised PID control tuning for a multivariable glass furnace by genetic algorithm

In this paper, standard genetic algorithms (SGAs) are presented to optimise the decentralised discrete PID parameters by three tuning approaches for a multivariable glass furnace with single loop interaction. At initial state, with the aid of control oriented model, the individual tuning approach without loop interaction is considered to categories the genetic operators, personalised cost functions and improved searching boundaries to attain the performance criterions. The second tuning approach is considered in PID parameters optimisation with loop interaction with optimum cost function. While, the third tuning approach is considered by modifying the optimum cost function by including the total effect of glass temperature and excess oxygen of both variables. The modified cost function exhibits better control robustness and disturbance rejection under loop-interaction.
Ministering in Honor-Shame Cultures: Biblical Foundations and Practical Essentials

In the early days of learning the Chinese language, my teacher introduced the word for sin, zui . As an evangelical Christian with experience relating to foreign missionaries, she felt it was necessary to explain that Chinese differ from Westerners in their understanding of the concept. Zui is more akin to a crime, something for which one is liable only in the event of being caught. For us Western missionaries, this would certainly pose a problem, for we had been taught to present a gospel that requires all individuals to recognize their guilt before a holy Creator. How could people who have no conscious realization of internal guilt possibly receive the gospel? Was some change required in their worldview before they could understand and receive the message of Christ’s death and resurrection? Or, conversely, did this Western missionary need to gain a fresh understanding of the gospel so that he could communicate in a way that made sense to people from a collectivist culture? In their book, Ministering in Honor-Shame Cultures , Georges and Baker attempt to help (evangelical) Christians who possess a Western, individualistic worldview better understand the collectivist mindset of the majority world, specifically those who live according to the moral code of honor-shame. The subtitle for this book – Biblical Foundations and Practical Essentials – describes the authors’ methodological approach. Both with extensive experience in cross-cultural ministry among honor-shame cultures, as well as significant training and experience in theological education, their goal is to offer practical help to those from guilt-innocence cultures engage with people who see the world through t he lens of shame-honor. The ultimate goal is to strengthen the church in its mission, particularly from the West to the rest. The authors underscore their discussions of biblical theology and cultural-anthropological insights with stories of individuals and groups, providing readers from guilt-innocence cultures with an easy grasp of the issues. Normal 0 false false false EN-US ZH-TW X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:. 0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri",sans-serif; mso-bidi-font-family:"Times New Roman";}