Miracle-dz/UniFAR-FTUs huggingface dataset:
Throughput analysis for multimedia transmission in mobile AdHoc networks using AMC

Wireless channel condition varies due to factors like fading, path loss, noise and other channel impairments. Due to these the channel throughput, packet delivery ratio also varies. In order to achieve higher transmission rates, various modulation schemes are in use. Adapting suitable modulation scheme to match the transmission rates to time varying channel conditions can increase the throughput of mobile adhoc networks. The simulation experiment carried in this paper dynamically adapts BPSK, QPSK, 16-QAM or 64-QAM for a single UDP traffic between a sender and receiver. Modulation schemes are varied by varying packet drop rates and distance of receiver from sender for a video traffic in OFDM channel using AODV as the routing protocol. The performance is measured in terms of PDR, throughput, PSNR and routing overhead for this adaptive modulation and coding technique.
Asynchrony induces polarization in attraction-based models of collective motion

Animal groups frequently move in a highly organized manner, as represented by flocks of birds and schools of fish. Despite being an everyday occurrence, we do not fully understand how this works. In particular, what social interactions between animals give rise to the flock structures we observe? This question is often investigated using self-propelled particle models where particles represent the individual animals. These models differ in the social interactions used, individual particle properties, and various technical assumptions. One particular technical assumption relates to whether all particles update their headings and positions at exactly the same time (synchronous update) or not (asynchronous update). Here, we investigate the causal effects of this assumption in an attraction-only model and find that it has a dramatic impact. Polarized groups do not form when synchronous update is used, but are produced with asynchronous update, and this phenomenon is robust with respect to variation in particle displacements and inclusion of noise. Given that many important models have been implemented with synchronous update only, we speculate that our understanding of the social interactions on which they are based may be incomplete. Perhaps previously unobserved phenomena will emerge if other potentially more realistic update schemes are used.
An Objective Out-of-Focus Blur Measurement

This paper presents a new method for objective measurement of out-of-focus blur images. The essential idea is to derive the point spread function (PSF) of an out-of-focus blur image from the line spread function (LSF). In this method, it is assumed that at least one sharp edge could be detected. Then, the LSF can be constructed from the edge(s). This approach has fast speed as it works in spatial domain without complex Fourier transform or iterative computation. Moreover, a generic criterion for out-of-focus blur measurement is proposed and it can be applied to all images without depending on image contents. The experimental results validate the accuracy and efficiency of the proposed method
Uroplakins Do Not Restrict CO2 Transport through Urothelium*

Background: The tightness of various membrane barriers to CO2 is of unknown molecular origin. Results: The bladder tissue lacks carbonic anhydrase. The resulting low intra-epithelial CO2 concentration gives rise to the apparent CO2 impermeability. Conclusion: Uroplakins do not act to decrease transepithelial CO2 flux. Significance: Enzymatic regulation of CO2 abundance rules out that aquaporins significantly contribute to the maintenance of acid base homeostasis. Lipid bilayers and biological membranes are freely permeable to CO2, and yet partial CO2 pressure in the urine is 3–4-fold higher than in blood. We hypothesized that the responsible permeability barrier to CO2 resides in the umbrella cell apical membrane of the bladder with its dense array of uroplakin complexes. We found that disrupting the uroplakin layer of the urothelium resulted in water and urea permeabilities (P) that were 7- to 8-fold higher than in wild type mice with intact urothelium. However, these interventions had no impact on bladder PCO2 (∼1.6 × 10−4 cm/s). To test whether the observed permeability barrier to CO2 was due to an unstirred layer effect or due to kinetics of CO2 hydration, we first measured the carbonic anhydrase (CA) activity of the bladder epithelium. Finding none, we reduced the experimental system to an epithelial monolayer, Madin-Darby canine kidney cells. With CA present inside and outside the cells, we showed that PCO2 was unstirred layer limited (∼7 × 10−3 cm/s). However, in the total absence of CA activity PCO2 decreased 14-fold (∼ 5.1 × 10−4 cm/s), indicating that now CO2 transport is limited by the kinetics of CO2 hydration. Expression of aquaporin-1 did not alter PCO2 (and thus the limiting transport step), which confirmed the conclusion that in the urinary bladder, low PCO2 is due to the lack of CA. The observed dependence of PCO2 on CA activity suggests that the tightness of biological membranes to CO2 may uniquely be regulated via CA expression.
Investigating the Nuclear Obscuration in Two Types of Seyfert 2 Galaxies

We build a large sample of Seyfert 2 galaxies (Sy2s) with both optical spectropolarimetric and X-ray data available, in which 29 of the Sy2s have a detection of polarized broad emission lines (PBLs) and 25 do not. We find that for luminous Sy2s with L[O III] > 1041 ergs s-1, sources with PBLs have smaller X-ray absorption column densities in comparison to those without PBLs (at a 92.3% confidence level): most of the Sy2s with NH < 1023.8 cm-2 show PBLs (86%; 12 out of 14), while the fraction is much smaller for sources with heavier obscuration (54%; 15 out of 28). The confidence level of the difference in absorption bounces up to 99.1% when using the thickness ("T") ratio (F2-10 keV/F[O III]) as an indicator. We rule out observation or selection bias as the origin for the difference. Our results, for the first time with high statistical confidence, show that, in additional to the activity of the nuclei, the nuclear obscuration also plays an important role in the visibility of PBLs in Sy2s. These results can be interpreted in the framework of the unified model. We can reach these results in the unified model if (1) the absorption column density is higher at large inclinations and (2) the scattering region is obscured at large inclinations.
A nonlinear learning control approach for a cement milling process

In this paper, a novel parameter tuning strategy for a class of controllers is discussed. The mathematical background of the algorithm is based on variable structure systems theory, which is well known with its robustness to systems having uncertainties and imprecision in the representative model. Since the course of modeling is concerned primarily with the dominant behavior, the nonlinearities existing in the system dynamics, external disturbances and plant-model mismatches require the control engineers to design controllers, which adapt the design parameters to alleviate the stated difficulties. The method introduced in this study is applicable to controller structures, whose outputs are linear in the adjustable parameters. In order to demonstrate the performance of the proposed technique, control of a cement milling circuit is studied with time-varying set values, time-varying plant parameters and a considerable amount of observation noise.
Influences of Random Surface Waves on the Estimates of Wind Energy Input to the Ekman Layer in the Antarctic Circumpolar Current Region

Sea surface waves significantly affect the wind energy input to the Ekman layer in the upper ocean. In the study, we first incorporated the wave‐induced Coriolis‐Stokes forcing, the reduction of wind stress caused by wave generation, and wave dissipation into the classical Ekman model to investigate the kinetic energy balance in the wave‐affected Ekman layer. Then, both the theoretical steady state solution for the idealized condition and the nonsteady state solution for the realistic ocean were derived. Total energy input to the wave‐affected Ekman layer includes the wind stress energy input and the wave‐induced energy input. Based on the WAVEWATCH III model, the wave spectrum was simulated to represent realistic random directional wave conditions. The wind stress energy input and the wave‐induced energy input to the wave‐affected Ekman layer in the Antarctic Circumpolar Current in the period from 1988 to 2010 were then calculated. The annual mean total energy input in the Antarctic Circumpolar Current region was 402.5 GW and the proportions of the wind stress energy input and the wave‐induced energy input were, respectively, 85% and 15%. Particularly, total energy input in the Antarctic Circumpolar Current in the wave‐affected Ekman layer model was 59.8% lower than that in the classical Ekman model. We conclude that surface waves play a significant role in the wind energy input to the Ekman layer. Plain Language Summary The wind energy input to the Ekman layer is one major source to balance the dissipation of mechanical energy in the ocean. Sea surface waves significantly influence the wind energy input to the Ekman layer. Previous studies only considered the Stokes drift induced by surface waves based on a simple monochromatic assumption. This study derived a realistic nonsteady state solution by incorporating three surface wave‐related processes: wave‐induced Coriolis‐Stokes forcing, the reduction of wind stress caused by wave generation, and wave dissipation into the classical Ekmanmodel. A numerical model was employed to simulate the wave spectra representing the realistic random surface waves. The total energy input in the Antarctic Circumpolar Current region from 1988 to 2010 was estimated. The estimated total energy input was 59.8% lower than that in the classical Ekman model, indicating that surface waves significantly affected the wind energy input in the Ekman layer.
A novel fuzzy background subtraction method based on cellular automata for urban traffic applications

Computational structure of cellular automata has attracted researchers and vastly been used in various fields of science. They are especially suitable for modeling natural systems that can be described as massive collections of simple objects interacting locally with each other, such as motion detection in image processing. On the other hand, extraction of moving objects from an image sequence is a fundamental problem in dynamic image analysis. Nowadays background modeling and subtraction algorithms are commonly used in real-time urban traffic applications for detecting and tracking vehicles and monitoring streets. In this paper by the use of cellular automata, a novel fuzzy approach for background subtraction with a particular interest to the problem of vehicle detection is presented. Our experimental results demonstrate that fuzzy-cellular system is much more efficient, robust and accurate than classical approaches.
Space Complexity in Polynomial Calculus ( Extended Abstract )

During the last decade, an active line of research in proof complexity has been to study space complexity and timespace trade-offs for proofs. Besides being a natural complexity measure of intrinsic interest, space is also an important issue in SAT solving. For the polynomial calculus proof system, the only previously known space lower bound is for CNF formulas of unbounded width in [Alekhnovich et al. ’02], where the lower bound is smaller than the initial width of the clauses in the formulas. Thus, in particular, it has been consistent with current knowledge that polynomial calculus could refute any k-CNF formula in constant space. We prove several new results on space in polynomial calculus (PC) and in the extended proof system polynomial calculus resolution (PCR) studied in [Alekhnovich et al. ’02]. 1) For PCR, we prove an Ω(n) space lower bound for a bitwise encoding of the functional pigeonhole principle with m pigeons and n holes. These formulas have width O(log n), and hence this is an exponential improvement over [Alekhnovich et al. ’02] measured in the width of the formulas. 2) We then present another encoding of the pigeonhole principle that has constant width, and prove an Ω(n) space lower bound in PCR for these formulas as well. 3) We prove an Ω(n) space lower bound in PC for the canonical 3-CNF version of the pigeonhole principle formulas PHPn with m pigeons and n holes, and show that this is tight. 4) We prove that any k-CNF formula can be refuted in PC in simultaneous exponential size and linear space (which holds for resolution and thus for PCR, but was not known to be the case for PC). We also characterize a natural class of CNF formulas for which the space complexity in resolution and PCR does not change when the formula is transformed into 3-CNF in the canonical way. Keywords-proof complexity; polynomial calculus; PCR; resolution; space; k-CNF
Analysis of Frequency Channel Division Strategy for CSMA/CA with RTS/CTS Mechanism

Abstract In this work we study the collision probability, saturation throughput and statistical delay for the carrier sense multiple access collision avoidance (CSMA/CA) protocol with request to send and clear to send (RTS/CTS) mechanism in the case of frequency channel division. We propose in this paper a modified version of CSMA/CA-RTS/CTS to be compatible with the channel repartition technique and we prove that an important gain is introduced in terms of system performance especially for loaded networks. Simulations highlight that dividing the channel into independent sub-channels reduces drastically the RTS collision probability. Moreover, a gain in terms of saturation throughput and delay is shown especially in dense networks.
A Framework for Proactive Machine Vision

As passive non-contact sensing technology that enables covering a relatively large area by a single sensor, machine vision is an attractive approach for building proactive systems. A practical system is likely to consist of several camera based sensors that each add a new view or a viewing angle. Our vision is that autonomous camera based sensor modules should be capable of rudimentary scene and event analysis, while information fusion is carried out at higher level. We intend to demonstrate the ideas in the context of an intelligent room currently under development.
THE FRECKLED INSTANTONS

We study instanton-corrected renormalization group flow in the two dimensional sigma models and four dimensional gauge theory. In two dimensions we do that by replacing the non-linear supersymmetric CP N −1 model by the gauged linear sigma model which is in the same universality class. We compare the moduli spaces of the instantons in the non-linear model and that of BPS field configurations in the linear model. We reduce the problem of matching of the parameters of the two systems to the intersection theory on the compact moduli space of the latter model. In four dimensions we find that the analogue of the linear sigma model is the gauge theory on the non-commutative space-time. Its BPS moduli space is the space of torsion free sheaves. Both cases (2d and 4d) are unified by the notion of the freckled instantons. We also put an end to the discussion of the nature of the superpotentials W ∼ σlogσ in 2d and 4d and discover the surprising disconnectnessness of the effective target space.
BERNOULLI'S LAW OF LARGE NUMBERS

Abstract This year we celebrate the 300th anniversary of Jakob Bernoulli's path-breaking work Ars conjectandi, which appeared in 1713, eight years after his death. In Part IV of his masterpiece, Bernoulli proves the law of large numbers which is one of the fundamental theorems in probability theory, statistics and actuarial science. We review and comment on his original proof.
Content based Image Retrievals for Brain Related Diseases

paper is attributed to develop a methodology for assisting the radiologists in proper identification of the diseases. In this paper we have considered the brain related disease archive from University of Rennes1 database to assist in finding the similar relevance images to the radiologists thereby helping them in drawing conclusions in their clinical practices. The methodology is implemented by considering the Generalized Gamma Distribution wherein the features extracted from the images using Discrete Cosine Transformation. Kullback- Leibler (KL) divergence methodology is used for finding the most similar images. The query image is processed and relevant images are retrieved. The final estimates of the parameters of Generalized Gamma Distribution are derived and the retrieved accuracy is identified using metrics. KeywordsGamma Distribution, image retrieval, KL divergence, Discrete Cosine Transformation, performance metrics
Modeling of power converters for debugging digital controllers through FPGA emulation

Debugging a digital controller for power converters can be a lengthy process due to the long time required in mixed-signal simulations. This paper focuses on the design of a power converter model for debugging digital controllers in closed loop. The testing may be performed by means of simulation or emulation. This paper shows the results of simulating and emulating the power converter using different data representations. Experiments will show that through a good selection of data and emulation, testing can be speeded up over 28,000 times.
Robust Automatic Speech Recognition system based on using adaptive time-frequency masking

The Automatic Speech Recognition (ASR) systems suffer from many types of noises in different environments. Nowadays, developing robust ASR system is an attractive research topic due to the high demands in many commercial applications. In this paper, the Mel-Frequency Cepstral Coefficients (MFCC) is modified to robust the noise, where the spectrogram is used as time-frequency analysis tool. The proposed system is designed to remove the energy, which is affected by the noise. It uses an adaptive filtering technique to robust the noise without loss of performance in case of undistorted speech data. The proposed system is evaluated in a noisy environment. The experimental results demonstrated that the proposed MFCC method provides significant improvements in recognition accuracy at low Signal to Noise Ratio (SNR). The average recognition accuracy is improved by 11% and 12.56% compared to standard MFCC and RASTA-PLP, respectively.
Power allocation for distortion minimization in distributed estimation with security constraints

In this paper we explore the distortion performance of distributed estimation schemes in wireless sensor networks (WSNs) in the presence of an eavesdropper. The sensors use an uncoded amplify and forward scheme to transmit their observations to the fusion center (FC), which at the same time can be overheard by the eavesdropper. Both the FC and the eavesdropper reconstruct a minimum mean squared error (MMSE) estimate of the physical quantity observed. In this paper, we address the problem of transmit power allocation for system performance optimization subject to a total average power constraint on the sensors and a security constraint on the eavesdropper. In the case of full channel state information (CSI) the proposed scheme allows the sensors to adapt their transmission strategy based on the instantaneous channel gains of both the FC and the eavesdropper. In the partial CSI case, transmit power is allocated only according to the FC instantaneous channel gains and statistical channel gains of the eavesdropper. Numerical results illustrate the performance of the power allocation algorithms.
Body Size at Birth Is Associated with Food and Nutrient Intake in Adulthood

Background Small body size at birth is associated with an increased risk of cardiovascular disease and type 2 diabetes. Dietary habits are tightly linked with these disorders, but the association between body size at birth and adult diet has been little studied. We examined the association between body size at birth and intake of foods and macronutrients in adulthood. Methodology/Principal Findings We studied 1797 participants, aged 56 to 70, of the Helsinki Birth Cohort Study, whose birth weight and length were recorded. Preterm births were excluded. During a clinical study, diet was assessed with a validated food-frequency questionnaire. A linear regression model adjusted for potential confounders was used to assess the associations. Intake of fruits and berries was 13.26 g (95% confidence interval [CI]: 0.56, 25.96) higher per 1 kg/m3 increase in ponderal index (PI) at birth, and 83.16 g (95% CI: 17.76, 148.56) higher per 1 kg higher birth weight. One unit higher PI at birth was associated with 0.14% of energy (E%) lower intake of fat (95% CI: -0.26, -0.03) and 0.18 E% higher intake of carbohydrates (95% CI: 0.04, 0.32) as well as 0.08 E% higher sucrose (95% CI: 0.00, 0.15), 0.05 E% higher fructose (95% CI: 0.01, 0.09), and 0.18 g higher fiber (95% CI: 0.02, 0.34) intake in adulthood. Similar associations were observed between birth weight and macronutrient intake. Conclusions Prenatal growth may modify later life food and macronutrient intake. Altered dietary habits could potentially explain an increased risk of chronic disease in individuals born with small body size.
Dynamic Display of BRDFs

This paper deals with the challenge of physically displaying reflectance, i.e., the appearance of a surface and its variation with the observer position and the illuminating environment. This is commonly described by the bidirectional reflectance distribution function (BRDF). We provide a catalogue of criteria for the display of BRDFs, and sketch a few orthogonal approaches to solving the problem in an optically passive way. Our specific implementation is based on a liquid surface, on which we excite waves in order to achieve a varying degree of anisotropic roughness. The resulting probability density function of the surface normal is shown to follow a Gaussian distribution similar to most established BRDF models.
Nonlinear and neural network-based control of a small four-rotor aerial robot

Small four-rotor aerial robots, so called quadrotor UAVs, have an enormous potential for all kind of near-area surveillance and exploration in military and commercial applications. In addition, they offer the possibility to fly either in-or outdoor. However, stabilizing control and guidance of these vehicles is a difficult task because of the nonlinear dynamic behavior. This paper describes the development of a nonlinear vehicle control system based on a combination of state-dependent Riccati equations (SDRE) and neural networks. Some first simulation results underline the performance of this new control approach for the current realization.
Voronoi coverage of non-convex environments with a group of networked robots

This paper presents a solution to decentralized Voronoi coverage in non-convex polygonal environments. We show that complications arise when existing approaches to Voronoi coverage are applied for deploying a group of robots in non-convex environments. We present an algorithm that is guaranteed to converge to a local optimum. Our algorithm combines classical Voronoi coverage with the Lloyd algorithm and the local path planning algorithm TangentBug to compute the motion of the robots around obstacles and corners. We present the algorithm and prove convergence and optimality. We also discuss experimental results from an implementation with five robots.