Miracle-dz/UniFAR-FTUs huggingface dataset:
A Drowsiness and Point of Attention Monitoring System for Driver Vigilance

This paper presents a framework that combines a robust facial features location with an elliptical face modelling to measure driver's vigilance level. The proposed solution deals with the computation of eyelid movement parameters and head (face) point of attention. The most important facial feature points are automatically detected using a statistically anthropometric face model. After observing the structural symmetry of the human face and performing some anthropometric measurements, the system is able to build a model that can be used in isolating the most important facial feature areas: mouth, eyes and eyebrows. Combination of different image processing techniques are applied within the selected regions for detecting the most important facial feature points. A model based approach is used to estimate the 3D orientation of the human face. The shape of the face is modelled as an ellipse assuming that the human face aspect ratio (ratio of the major to minor axes of the 3D face ellipse) is known. The elliptical fitting of the face at the image level is constrained by the location of the eyes which considerable increase the performance of the system. The system is fully automatic and classifies rotation in all-view direction, detects eye blinking and eye closure and recovers the principal facial features points over a wide range of human head rotations. Experimental results using real images sequences demonstrates the accuracy and robustness of the proposed solution.
Noise reduction in 3D images using morphological amoebas

This article presents the use of morphological amoebas for the enhancement of 3D medical images. Morphological amoebas are kernels adapting their shape in such a way that they do not cross the contours of the image. They can be used in morphological operations in quite a similar way as classical kernel and are well-fitted for noise-reduction in 3D medical images.
A framework for the design of new line parameterizations

Based on four criteria, namely uniqueness, boundedness, uniformness and recursiveness, a framework for the design of new line parameterizations is introduced. It is shown that there does not exist a line parameterization which could satisfy all the above four criteria, and that the line parameterization, formulated as c=ax+(a/sub 0/-|a|)y a/spl isin/~-a/sub 0/,a/sub 0/) where a/sub 0/ is an arbitrary positive number, can not only satisfy the uniqueness, boundedness, and recursiveness conditions, but it can also achieve the best goodness to the uniformness one.
A Tracking System Exploiting Interaction Between a Detector With Localization Capabilities and the KF

In the present paper, we focus on the design of a Kalman-based algorithm to track a single target in range. The proposed approach exploits spillover of target energy between consecutive matched filter samples; to this end, at the kth scan, a GLRT-based detector is fed by the predicted target position (computed by the tracker using measurements up to the (k-1)th scan) and returns to the tracker an estimate of the current target position (measurement) obtained by taking into account target strength over consecutive samples. We assume that the target echo is known up to a complex deterministic parameter; moreover, we suppose that the target is embedded in white Gaussian noise with unknown power. The performance analysis is conducted in comparison to a more conventional Kalman-based tracker that interpolates consecutive samples to take advantage of the spillover. Remarkably, the proposed estimation scheme can provide accurate estimates of the target position within the cell under test.
Pseudorandom Number Generation by Inversive Methods

The classical linear congruential method for generating uniform pseudorandom numbers has some deficiencies that can render them useless for some simulation problems. This fact motivated the design and analysis of nonlinear congruential methods for the generation of pseudorandom numbers. Inversive methods are an interesting and very promising approach to produce uniform pseudorandom numbers. We present a critical analysis of the recent developments on the topic. Our exposition concentrates on recursive inversive congruential generators and digital inversive congruential generators.
Wormhole attack prevention mechanism for RPL based LLN network

Smart metering application has received a lot of attention from the research community lately. Usually, LLN based network runs on RPL protocol which constructs a DAG structure for its normal operation. In this paper, we devise a wormhole attack scenario in such a network. Furthermore, we propose a Merkle tree based authentication protocol which runs on the notion of constructing a tree of hashed security information. We evaluated the approach by formulating the wormhole problem as graph theoretic problem and have shown the effectiveness of the proposed Merkle tree based approach for authenticating communications. Furthermore, we perform simulations in NS 2 to observe the network performance by adopting Merkle tree based to prevent from disrupting the links and observed boost in throughput, reduction in jitter and end to end delay. In the end, we have taken the step towards optimizing the performance of the algorithm by proposing an effective tree traversal algorithm which works on the notion of electing nodes as root in a large scale network from where a Merkle tree will be originated this will assist in managing the authentication in a huge sized network broken down into many trees avoiding wormhole attacks in the network.
A MRI compatible robot for breast intervention

According to the requirements of MRI (Magnetic Resonance Imaging) surgical navigation robot, a MRI-compatible breast intervention robot is designed. Due to the available space in MRI scanner is limited, a seven DOF (Degree of Freedom) robot is designed with rectangular coordinate system. The metallic materials in nuclear magnetic environment will influence the imaging and reduce the accuracy of surgery. Resolve the MR-compatible problem by using non-magnetic stainless steels and other non-magnetic materials. Put motors out of the nuclear magnetic environment, and use a long-distance transmission way to deliver the power. Utilize MATLAB/Simulink to do working space analysis. According to the analysis results, it is testified that the robot working space can cover the whole breasts of patient. Utilize ANSYS / Workbench to do statics analysis about crucial parts of the robot. By the force simulation, the deformed patterns and stress patterns are obtained to prove that the structure of robot is reasonableness. This design lies the foundation of further study.
Survey on mining techniques for breast cancer related data

In the paper we are showing a comparative study of some of the classification and the clustering algorithms so that we can find the alternatives for the datasets depending upon the requirement. These prediction systems can be used for the medical diagnosis as various algorithms in this paper have been categorized and simulation results shown. Prevalence informs the total case load at a given time. Incidence yields a pointer to extent of attention required and choice of measures. Different classification algorithms are trained on the result set to build the final classifier model based on K-fold cross validation method. The best accuracy for the given dataset is achieved in rotation forest algorithm compared to other classifiers. The proposed approach will help sort out the. This methodology is evaluated using 286 raw breast cancer data obtained from a city hospital. The best accuracy for the given dataset is achieved in bagging algorithm compared to other classifiers. The proposed approach helps doctors in their diagnosis decisions and also in their treatment planning procedures for different categories.
Efficient prime-field arithmetic for elliptic curve cryptography on wireless sensor nodes

Public-Key Cryptography (PKC) is essential to ensure the authenticity and confidentiality of communication in open computer networks such as the Internet. While RSA is still the most widely used public-key cryptosystem today, it can be expected that Elliptic Curve Cryptography (ECC) will continue to gain importance and become the de-facto standard for PKC in the emerging “Internet of Things. ” ECC is particularly attractive for use in resource-restricted devices (e.g. wireless sensor nodes, RFID tags) due to its high level of security per bit, which allows for shorter keys compared to RSA. The performance of elliptic curve cryptosystems is primarily determined by the efficiency of certain arithmetic operations (especially multiplication and squaring) in the underlying finite field. In the present paper, we introduce a high-speed implementation of arithmetic in Optimal Prime Fields (OPFs) for the ATmega128, an 8-bit processor used in a number of sensor nodes including the MICAz mote. An OPF is defined by a prime of the form p = u · 2k +v, whereby u and v are small compared to 2k; in our implementation u is a 16-bit integer and v = 1. A special property of these primes is their low Hamming weight since only a few bits near the MSB and LSB are one. We describe an optimized variant of Montgomery multiplication, based on Gura et al's hybrid technique, that takes the low weight of such primes into account to minimize execution time. Our implementation for the ATmega128 is able to perform a multiplication in a 160-bit OPF in 3,532 clock cycles, which represents a new speed record for 160-bit modular multiplication on an 8-bit processor.
Improved data minimization technique in reducing memory space complexity for DNA local alignment accelerator application

Improved data minimization technique to optimize the length of DNA sequence and alignment result characters representation is presented in this paper. The primary objective is to improve and optimize data representation for DNA sequences alignment and result character. The proposed design change in algorithm and architecture is presented in this paper. Algorithm design based on binary equivalent method is used to obtain the optimal size of characters representation. The code is written, compiled and simulated using Altera Quartus II Version 9.0 EDA tools. Verilog Hardware Description Language (HDL) and Altera Cyclone II EP2C35 FPGA are used as coding language and target device respectively. In addition, the structural modelling technique is used to reduce the design complexity. Simulation result showed that the improved data minimization technique takes 50% more memory compared to previous work, but it covers 6 DNA sequences and alignment result characters.
Period-Dependent Initial Values for Exact Schedulability Test of Rate Monotonic Systems

Real-time systems using rate monotonic fixed priority scheduling can be checked for schedulability either by pessimistic schedulability conditions or exact testing. Exact testing provides a more precise result but cannot always be performed in polynomial time. Audsley et al. proposed one of the earliest methods by iteratively deriving the job response times. Other researchers have improved the efficiency of their exact test method by using different initial values. All currently proposed initial values do not use the relationship between task periods. In this paper we define initial values using the largest and the second largest periods in a system. We show that the new initial values can significantly improve the exact test.
User-calibration-free remote eye-gaze tracking system with extended tracking range

A novel general method to extend the tracking range of user-calibration-free remote eye-gaze tracking (REGT) systems that are based on the analysis of stereo-images from multiple cameras is presented. The method consists of two distinct phases. In the brief initial phase, estimates of the center of the pupil and corneal reflections in pairs of stereo-images are used to estimate automatically a set of subject-specific eye parameters. In the second phase, these subject — specific eye parameters are used with estimates of the center of the pupil and corneal reflections in images from any one of the systems' cameras to compute the Point-of-Gaze (PoG). Experiments with a system that includes two cameras show that the tracking range for horizontal gaze directions can be extended from ±23.2° when the two cameras are used as a stereo pair to ±35.5° when the two cameras are used independently to estimate the POG.
A Novel Approach for Dynamic Polarity Mining from Customer Reviews

The dynamic opinion words usually have different polarity directions when they are in combination with different features. Determining the polarity direction of these dynamic opinion words is one of the difficult problems in opinion mining. Although the opinion words with dynamic polarity are usually less than those with static polarity, these opinion words can be matched with most features, can appear very frequently in customer reviews. So the impact on the overall feature-opinion extraction accuracy and the calculation of comprehensive consumer word of mouth cannot be ignored. In this paper, we address this issue of judging the polarity direction of dynamic opinion words in different feature contexts by means of customer review mining and voting strategy. Our approach is based on this hypothesis: when the corpus scale is big enough, the word of mouth of product features are relatively stable. The experimental results verified the effectiveness of our method. Although the test is performed in mobile phone review areas, the approach can be easily applied to other areas.
The generation of nonaxisymmetric magnetic fields in the giant planets

Abstract We consider mean-field dynamo models in uniformly rotating spheres and spherical shells, with anisotropic alpha and magnetic diffusivity tensors which are functions of the inverse Rossby number, Ω∗. When we include an a-quenching nonlinearity we show that, for all values of Ω∗ considered, nonaxisymmetric magnetic fields are stable to axisymmetric perturbations. However the stability of nonaxisymmetric magnetic fields is weakened for large values of Ω∗, which would make the generation of axisymmetric magnetic fields more probable. When a small amount of differential rotation is introduced, only axisymmetric dipole-like solutions are stable. We draw attention to the possibility that the nonaxisymmetric magnetic fields of Uranus and Neptune could be the result of anisotropic alpha and magnetic diffusi vity tensors. The more nearly axisymmetric magnetic fields of Jupiter and Saturn could result from their more rapid rotation, or possibly because of internal differential rotation.
Facilitating participatory evaluation as a learning process

This article presents the experience of conducting an evaluation of participatory learning, within an action research project conducted in South Sulawesi, Indonesia. An alternative approach to evaluation was taken by focusing on learning, and creating dialogue with the community as a main strategy. We classified this project evaluation in terms of: the outcomes of the research project, but equally importantly by the learning that occurred for all groups of participants. In this connection, we discuss the basic differences between traditional and constructivist research paradigms. We conclude that strategies and methods employed in the evaluation itself are key elements to enable participants to clarify and articulate their norms and values, decide on action, and illuminate their learning and eventual empowerment and a sense of liberation.
Combining analytic models with neural networks

In this paper, an ensemble of models is introduced which combines a linear parametric model and a nonlinear non-parametric model such as artificial neural network (ANN). This model aims to embody the desirable characteristics of linear parametric model such as stable generalization capability while retaining the data-based learning and prediction capacity of ANNs. The proposed model is applied for short term time series prediction and the results show that the proposed model achieves good generalization (prediction) performance utilizing the nonparametric ANN model component while achieving much improved stability utilizing the linear model component. The experiment compares the proposed model to other ANN models and linear models for generalization.
A Gaussian input is not too bad

We consider the problem of choosing a robust input for communicating over an input constrained additive-noise channel where the noise distribution is arbitrary. We show that the mutual information rate achievable using a white Gaussian input never incurs a loss of more than half a bit per sample with respect to the power constrained capacity. For comparison, for the family of colored Gaussian noise channels a white Gaussian input loses at most log(e)/2e/spl ap/0.265 bit per sample with respect to the optimum water-pouring solution. For general input constraints, we derive a formula for choosing the best input in the min-max capacity loss (bound) sense. The bound on the capacity loss is tight for pulse position modulation (PPM) in the presence of a bursty jammer.
Structural brain alterations can be detected early in HIV infection

Objective: Brain changes occurring early in HIV infection are not well characterized. The Chicago Early HIV Infection Study aimed to evaluate the presence and extent of structural brain alterations using quantitative MRI. Methods: Forty-three HIV and 21 control subjects were enrolled. Mean length of infection was estimated as less than 1 year based on assay results. High-resolution neuroanatomical images were acquired. Automated image analysis was used to derive measurements for total brain, ventricular volume, and for tissue classes (total and cortical gray matter, white matter, and CSF). A separate image analysis algorithm was used to calculate measurements for individual brain regions. Cognitive function was assessed by neuropsychological evaluation. Results: Reductions were quantified in total (p = 0.0547) and cortical (p = 0.0109) gray matter in the HIV group. Analysis of individual brain regions with a separate image analysis algorithm revealed consistent findings of reductions in cerebral cortex (p = 0.042) and expansion of third ventricle (p = 0.046). The early HIV group also demonstrated weaker performance on several neuropsychological tests, with the most pronounced difference in psychomotor speed (p = 0.001). Conclusions: This cross-sectional brain volumetric study indicates structural alterations early in HIV infection. The findings challenge the prevailing assumption that the brain is spared in this period. Revisiting the question of the brain's vulnerability to processes unfolding in the initial virus-host interaction and the early natural history may yield new insights into neurologic injury in HIV infection and inform neuroprotection strategies.
On the geometric ergodicity of hybrid samplers

In this paper, we consider the random-scan symmetric random walk Metropolis algorithm (RSM) on ℝ d . This algorithm performs a Metropolis step on just one coordinate at a time (as opposed to the full-dimensional symmetric random walk Metropolis algorithm, which proposes a transition on all coordinates at once). We present various sufficient conditions implying V-uniform ergodicity of the RSM when the target density decreases either subexponentially or exponentially in the tails.
The Economics of International Trade and the Environment

Introduction and Overview of the Economics of International Trade and the Environment, A. Batabyal and H. Beladi The Impact of Selected Abatement Strategies on Transnational Pollution, the Terms of Trade, and Factor Rewards: A General Equilibrium Approach, J.D. Merrifield International Trade in Waste Products in the Presence of Illegal Disposal, B.R. Copeland Environmental Policy When Market Structure and Plant Locations are Endogenous, J.R. Markusen, E.R. Morey, and N.D. Olewiler On Ecological Dumping, M. Rauscher Strategic Environmental Policy and International Trade, S. Barrett North-South Trade and the Global Environment, G. Chichilnisky Trade and Transboundary Pollution, B.R. Copeland and M.S, Taylor Environmental Policy and International Trade When Governments and Producers Act Strategically, A. Ulph Wildlife, Biodiversity, and Trade, E.B. Barbier and C-E. Schulz Game Governments Play: An Analysis of National Environmental Policy in an Open Economy, A. Batabyal Industrial Pollution Abatement: The Impact on the Balance of Trade, H.D. Robison The Effects of Domestic Environmental Policies on Patterns of World Trade: An Empirical Test, J. Tobey Unilateral CO2 Reductions and Carbon Leakage: The Consequences of International Trade in Oil and Basic Materials, S. Felder and T.F. Rutherford International Trade and Environmental Quality: How Important are the Linkages? C. Perroni and R.M. Wigle Environmental and Trade Policies: Some Methodological Lessons, V.K. Smith and J.A. Espinosa Carbon Taxes With Exemptions in an Open Economy: A General Equilibrium Analysis of the German Tax Initiative, C. Bohringer and T.F. Rutherford The Environment and Welfare Implications of Trade and Tax Policy, H. Lee and D. Roland-Holst The Impact of NAFTA on Mexico's Environmental Policy, B.W. Husted and J.M. Logsdon The Empirical Relationship Between Trade, Growth, and the Environment, L.R. Gale and J.A. Mendez
Paraphrase Detection for Short Answer Scoring

We describe a system that grades learner answers in reading comprehension tests in the context of foreign language learning. This task, also known as short answer scoring, essentially requires determining whether a semantic entailment relationship holds between an individual learner answer and a target answer; thus semantic information is a necessary part of any automatic short answer scoring system. At the same time the method must be robust to the particularities of learner language. We propose using paraphrase detection, a method that meets both requirements. The basis for our specific paraphrasing method is word alignment learned from parallel corpora which we create from the available data in the CREG corpus (Corpus for Reading Comprehension Exercises for German). We show the usefulness of this kind of information for the task of short answer scoring. Combining our results with existing approaches we obtain an improvement tendency.
QoI-aware energy management for wireless sensor networks

In this paper, we propose an efficient energy-management framework in wireless sensor networks (WSNs) to address the fundamental research challenge imposed by both the maintenance of the energy supply and the support of the quality-of-information (QoI) requirements. By quantifying the QoI benefit the tasks receive in relation to the level of QoI they request as the QoI satisfaction index), we propose a QoI-aware energy-management scheme to distributedly decide the participating state of each sensor. Specifically, by using the mathematical framework of the Gur Game, we propose a novel pay-off structure taking into account the QoI and the energy consumption. We finally evaluate the proposed scheme under an event occurrence detection scenario, where the proposed scheme successfully guarantees less than 7% QoI outage, saves 80% of the energy reserve if compared with the lower bound solution, and achieves the suboptimum with only 4% gap if compared with optimal solution.