Miracle-dz/UniFAR-FTUs huggingface dataset:
Anti-Aliased Low Discrepancy Samplers for Monte Carlo Estimators in Physically Based Rendering. (Échantillonneurs basse discrepance anti aliassés pour du rendu réaliste avec estimateurs de Monte Carlo)

When you display a 3D object on a computer screen, we transform this 3D scene into a 2D image, which is a set of organized colored pixels. We call Rendering all the process that aims at finding the correct color to give those pixels. This is done by integrating all the light rays coming for every directions that the object's surface reflects back to the pixel, the whole being ponderated by a visibility function. Unfortunately, a computer can not compute an integrand. We therefore have two possibilities to solve this issue: We find an analytical expression to remove the integrand (statistic based strategy). Numerically approximate the equation by taking random samples in the integration domain and approximating the integrand value using Monte Carlo methods. Here we focused on numerical integration and sampling theory. Sampling is a fundamental part of numerical integration. A good sampler should generate points that cover the domain uniformly to prevent bias in the integration and, when used in Computer Graphics, the point set should not present any visible structure, otherwise this structure will appear as artifacts in the resulting image. Furthermore, a stochastic sampler should minimize the variance in integration to converge to a correct approximation using as few samples as possible. There exists many different samplers that we will regroup into two families: Blue Noise samplers, that have a low integration variance while generating unstructured point sets. The issue with those samplers is that they are often slow to generate a pointset. Low Discrepancy samplers, that minimize the variance in integration and are able to generate and enrich a point set very quickly. However, they present a lot of structural artifacts when used in Rendering. Our work aimed at developing hybriod samplers, that are both Blue Noise and Low Discrepancy
Scalable recommender system based on MapReduce framework

The data collection of items and its users are growing day by day over the internet. Recommender Systems (RSs) help the user to find the items of their choices. It is a big challenge for RSs to identify the right choice of the items for a user from the ocean of large data set. Therefore, the scalability of RSs is an important demand for today's application. MapReduce framework provides a solution for such demand of scalability. Hadoop is an open source tool, that helps to build such applications. The performance analysis of scalable RSs needs to be verified. In the paper, a content based RS is implemented using the MapReduce framework based on Hadoop. The scalability of RS is verified in terms of parallel computation of each task of MapReduce framework and their data distribution. The resource consumption and the execution time of the algorithm are observed in the experiment. The outcome of the experiment shows the good trend for the demand of scalability of RSs.
Speech recognition based chess system for visually challanged

To overcome the obstacle of visual chess simulators, a system is proposed in which visually impaired individuals can practice by using only voice commands. In addition, this system will be powered using machine learning algorithms with the help of a publicly available repository of over five million games. This will make the user feel like he/she is playing against another human and not a machine. The existing chess systems use a variety of algorithms in order to choose its move. Most of these use tree traversals and the most common one is the min-max algorithm with alpha-beta pruning. Min-max algorithm finds the best move, and alpha-beta pruning prevents it from going into branches of the game tree that cannot yield a better result than previously traversed branches. Since the tree generated in a chess game is very deep and have a lot nodes, these algorithms examine the depth only to a certain amount. Generally, these algorithms are accompanied by an opening repository which bolsters the algorithm's efficiency. Since these algorithms are too strong for a visually impaired individual, a new approach is suggested to choose the computer's move. A publicly available repository of over five million chess games played by humans will be used to train the machine, initially. When the user makes his/her move, it will be converted into text and given as input to both the Minimax and the k-NN algorithms. The moves given as output by both these algorithms are compared using an evaluation function. The move with a higher score is chosen. The game continues till a decisive result is obtained.
Designing and Modeling Collective Co-located Interactions for Art Installations. (Concevoir et modéliser des interactions collectives co-localisées pour les installations d'art numérique)

With works such as Kinoautomat by Raduz Cincera, SAM - Sound Activated Mobile by Edward Ihnatowicz, and Glowflow by Myron Krueger, artists have deployed, as early as the 1960s, art installations engaging novel situations of collective co-located interaction, i.e involving multiple or even many spectators interacting in the same place via and with a digital apparatus. The number of those works has continued to increase since the beginning of the 21st century, taking advantage of the new opportunities offered by advances in real-time computer vision technologies and the advent of ubiquitous computing marked by the multiplication and interoperability of mobile computing devices. While experiences in this area are more and more frequent, they have not yet been the subject of structured analysis and, even less, of proposals for dedicated tools and design methods. How can we, nowadays, conceive such interactive art installations whose intrinsic complexity involves questions of the technical, social, cognitive and aesthetic order? This dissertation draws on previous work in the fields of human-computer interaction (HCI), computer-supported cooperative work (CSCW), and interactive arts research with the aim of increasing our knowledge of the challenges faced both by art practitioners and participants in such collective interactive installations, and, beyond, the designers of apparatus in a promising future. A set of tools and guidelines are proposed when designing collective co-located interactions for digital art installations. First a classification system is developed centered on the most decisive aspects that allow the emergence of a collective experience. Two distinct approaches are then explored to find the bases of a graphical modeling language for the design and analysis of such apparatus. Build on top of Petri nets, the second approach supports modeling the spatial and material resources of an installation, as well as the human-machine, human-human and human-machine-human interactions. The investigations conducted for this research have required laying particular emphasis on the conditions - whether spatial, material, or human - which affect the ability for participants to co-construct a common aesthetic experience in the absence of orchestration or a preannounced goal to be achieved. While this singular approach primarily concerns interactive arts, it may be relevant to a wide range of research communities, including, and foremost, that of HCI, as well as CSCW, New Interfaces for Musical Expression (NIME), interaction design, and even culture, museography in particular.
LSRC: Lexicon star rating system over cloud

In the age of Internet, it is essential to go for the reviews before taking any service like to go for a movie or buying any product. Sentiment analysis plays a vital role to determine people's opinion or reviews of any entity, i.e., products, movies or comments etc. Sentiment analysis is an opinion mining technique which uses the concept of NLP (Natural Language Processing) and provide us the behavior of consumer about the product. Reviews are mainly classified as positive, negative or neutral. In this paper we used the concept of lexicon-based approach to give star rating to the reviews. Instead of classifying reviews as positive, negative or neutral, we have categorized them into five subcategories, i.e., Excellent, Good, Neutral, Bad and Worst using star-scale method. We got the results in reasonable time by using the concept of VM (Virtual Machines).
Optimization of Aggregate Capacity of PEVs for Frequency Regulation Service in Day-Ahead Market

An aggregator can coordinate plug-in electric vehicles (PEVs) to provide frequency regulation service to an independent system operator (ISO). The aggregator can participate in the electricity markets of ISOs which provide economic incentives for PEV frequency regulation service. While the ISOs typically use forward market [e.g., day-ahead market (DAM)] to trade frequency regulation service, the available regulation capacity of an aggregator is subject to the random arrival and departure of the PEVs. In the DAM, the aggregator submits a bid to indicate its available capacity on the next day. This motivates us to study the problem of how an aggregator determines its bid in the DAM, given the uncertainty of the available regulation capacity of the PEVs. The DAM is used to trade the frequency regulation capacity in California ISO (CAISO) and New York ISO (NYISO). We consider two types of DAMs based on the market rules of CAISO and NYISO. For the first type, the exact amount of regulation capacity submitted in the DAM needs to be fulfilled on the next day. For the second type, a market participant can settle a shortage of capacity by paying a penalty to the ISO. In both cases, the aggregator can participate in the real-time market to sell extra capacity on the next day. We formulate the problem for determining the bid using stochastic programming. As PEVs have uncertain arrival and departure times, our problem formulation incorporates risk management using the conditional value at risk. Efficient algorithms are proposed for solving the formulated problem. PEV charging data collected in Vancouver, BC, Canada, is used in our simulations. We compare the profit of the aggregator when it participates in the markets of CAISO and NYISO. Our simulation results show that the uncertainty of the PEVs’ available capacity has less effect on the profit and financial risk as the number of PEVs increases.
Experimental study on frequency modulation of an injection-locked magnetron based on full wave voltage doubler

In this study, we show that a 2.45 GHz magnetron can follow the frequency modulation of the injection signal, working as an amplifier. A full-wave voltage doubler was improved from the power source of a microwave oven and used as the power source of the injection-locked magnetron. By injecting a frequency modulation signal to this CW magnetron, the frequency of the magnetron was locked with the injection signal. 2 Mbps data transmission by frequency-shift keying was achieved at an anode voltage ripple rate of 4.16%.
Effect of tildrakizumab (MK‐3222), a high affinity, selective anti‐IL23p19 monoclonal antibody, on cytochrome P450 metabolism in subjects with moderate to severe psoriasis

Tildrakizumab, an interleukin (IL)‐23 inhibitor, is indicated for the treatment of moderate to severe chronic plaque psoriasis. Although tildrakizumab is not metabolized by, and does not alter, cytochrome P450 (CYP) expression in vitro, clinically significant pharmacokinetic effects through changes in systemic inflammation, which alters CYP metabolism, have been well documented. At the time of study conduct, the effect of modulation of inflammation/cytokines, including IL‐23 inhibition with tildrakizumab, on CYP metabolism, and therefore the potential for disease–drug interactions, in psoriasis patients was unknown. We therefore assessed whether tildrakizumab alters CYP metabolism in subjects with moderate to severe psoriasis.
The Corporate Reputation of Islamic Banks: A Measurement Scale

During the last few years, the concept of corporate reputation has received considerable attention from marketing academics and practitioners alike. This is not surprising in view of the concept enormous practical implications. Suffice it to say, that the market value of a modern company lies mainly in its intangibles assets. Corporate reputation embodies all of the intangible capital that a company may have. The current study describes an attempt to develop and validate a scale to measure the corporate reputation of Islamic banks. The operational definition of the construct draws mainly on its attitudinal and perceptual nature. To tap into the different dimensions of the target domain, an initial item pool of 42 statements was developed following a comprehensive review of related literature. Successive stages of revision, editing, rewriting and face and content validity reduced the initial item pool to 29 statements. These were put to a convenient sample of 150 bank customers in the Kingdom of Bahrain. The resultant data set was factor analyzed. A Principal Component Analysis extraction method suggested a two factor solution. Between them,the two factors explained 55% of the total variance in the factor model. Items that loaded poorly on any of the two components were eliminated from the analysis. 17 items made up the final version of the scale. The Cronbach alpha coefficients revealed that the two subscales and the overall scale were reliable. The inter-item correlation coefficients, the variance extracted, the factor communalities, and the Cronbach alpha coefficients do all point to the validity of the construct: that all the items in the scale seem to measure an underlying theme, in this case the corporate reputation of Islamic banks.
Development and Initial Psychometric Validation of the Brief-Caffeine Expectancy Questionnaire (B-CaffEQ)

Caffeine is the most widely available and consumed psychoactive substance in the United States. Extant work indicates that across substances, use expectancies play a marked role in the development and maintenance of consumption patterns. Despite a burgeoning line of etiological and intervention-oriented research focused on expectancies (e.g., alcohol), there is a limited literature regarding caffeine use effect expectancies, specifically. To facilitate this work, the Caffeine Expectancy Questionnaire (CaffEQ) was developed and psychometrically validated; however, the length of the CaffEQ (i.e., 47 items) may hinder widespread adoption of this tool. As such, the current study provides an initial psychometric validation of a brief, 20-item version—the Brief-Caffeine Expectancy Questionnaire (B-CaffEQ)—in a multiethnic sample of undergraduate students (N = 975). Results showed that the B-CaffEQ replicated the 7-factor structure of the original CaffEQ using both constrained (confirmatory factor analysis) and less constrained (exploratory structural equation modeling) structural models and evidenced good internal consistency across subscales. The B-CaffEQ also demonstrated concurrent validity with caffeine use frequency indices, replicated and extended convergent validity between caffeine expectancy subscales and related behavioral and psychological constructs, and demonstrated discriminant validity with other related, but notably distinct, stimulant use metrics (e.g., cocaine, Ritalin). Lastly, the B-CaffEQ appears to provide an invariant measure of expectancies across types of caffeine users. These findings indicate that the B-CaffEQ is a reliable assessment of caffeine use effect expectancies, with acceptable-to-good psychometric properties—comparable in length to other substance use expectancies measures—that may be more readily incorporated into research and clinical settings.
An integrated approach with redispatch and UPFC for voltage stability enhancement in deregulated power systems

In this paper, an effort has been made to enhance static voltage stability using Unified Power Flow Controller (UPFC) and redispatch as an integrated approach. The redispatch using Interior Point — Optimal Power Flow (IP-OPF) can ensure all operating constraints of system within satisfactory range. Using this operating state, the Continuous Power Flow (CPF) is used to compute Critical Loading Margin (CLM) as a measure for voltage instability margin. The case studies are repeated by using Decoupled Power Injection Modeling (DPIM) of UPFC on IEEE 14-bus test system. The outcome is validating the proposed approach to enhance voltage stability margin significantly even under (N-1) line contingency.
A low cost system for real time water quality monitoring and controlling using IoT

Water is a prerequisite element required for humans and therefore there must be mechanisms put in place to vigorously test the quality of drinking water in real time. This paper proposes a low cost system for real time water quality monitoring and controlling using IoT. The system consist of physiochemical sensors which can measures the physical and chemical parameters of the water such as Temperature, Turbidity, Conductivity, pH and Flow. By these sensors, water contaminants are detected. The sensor values processed by Raspberry pi and send to the cloud. Finally the sensed data is visible on the cloud using cloud computing and the flow of the water in the pipeline is controlled through IoT.
Composable and versatile privacy via truncated CDP

We propose truncated concentrated differential privacy (tCDP), a refinement of differential privacy and of concentrated differential privacy. This new definition provides robust and efficient composition guarantees, supports powerful algorithmic techniques such as privacy amplification via sub-sampling, and enables more accurate statistical analyses. In particular, we show a central task for which the new definition enables exponential accuracy improvement.
Origin and significance of cosmogenic signatures in vesicles of lunar basalt 15016

Lunar basalt 15016 (~3.3 Ga) is among the most vesicular (50% by volume) basalts recovered by the Apollo missions. We investigated the possible occurrence of indigenous lunar nitrogen and noble gases trapped in vesicles within basalt 15016, by crushing several cm‐sized chips. Matrix/mineral gases were also extracted from crush residues by fusion with a CO2 laser. No magmatic/primordial component could be identified; all isotope compositions, including those of vesicles, pointed to a cosmogenic origin. We found that vesicles contained ~0.2%, ~0.02%, ~0.002%, and ~0.02% of the total amount of cosmogenic 21Ne, 38Ar, 83Kr, and 126Xe, respectively, produced over the basalt's 300 Myr of exposure. Diffusion/recoil of cosmogenic isotopes from the basaltic matrix/minerals to intergrain joints and vesicles is discussed. The enhanced proportion of cosmogenic Xe isotopes relative to Kr detected in vesicles could be the result of kinetic fractionation, through which preferential retention of Xe isotopes over Kr within vesicles might have occurred during diffusion from the vesicle volume to the outer space through microleaks. This study suggests that cosmogenic loss, known to be significant for 3He and 21Ne, and to a lesser extent for 36Ar (Signer et al. ), also occurs to a negligible extent for the heaviest noble gases Kr and Xe.
Avian thermoregulation in the heat: metabolism, evaporative cooling and gular flutter in two small owls

ABSTRACT The thermoregulatory responses of owls to heat stress have been the subject of few studies. Although nocturnality buffers desert-dwelling owls from significant heat stress during activity, roost sites in tree and cactus cavities or in deep shade provide only limited refuge from high environmental temperatures during the day. We measured thermoregulatory responses to acute heat stress in two species of small owls, the elf owl (Micrathene whitneyi) and the western screech-owl (Megascops kennicottii), which occupy the Sonoran Desert of southwestern North America, an area of extreme heat and aridity. We exposed wild-caught birds to progressively increasing air temperatures (Ta) and measured resting metabolic rate (RMR), evaporative water loss (EWL), body temperature (Tb) and heat tolerance limits (HTL; the maximum Ta reached). Comparatively low RMR values were observed in both species, Tb approximated Ta at 40°C and mild hyperthermia occurred as Ta was increased toward the HTL. Elf owls and screech-owls reached HTLs of 48 and 52°C, respectively, and RMR increased to 1.5 and 1.9 times thermoneutral values. Rates of EWL at the HTL allowed for the dissipation of 167–198% of metabolic heat production (MHP). Gular flutter was used as the primary means of evaporative heat dissipation and produced large increases in evaporative heat loss (44–100%), accompanied by only small increases (<5%) in RMR. These small, cavity-nesting owls have thermoregulatory capacities that are intermediate between those of the open-ground nesting nightjars and the passerines that occupy the same ecosystem. Summary: Small desert owls demonstrate heat tolerance intermediate between that of very heat-tolerant nightjars and less heat-tolerant passerines. The gular flutter mechanism contributes significantly to cooling efficiency.
Coating-free, air-stable silver nanowires for high-performance transparent conductive film

Silver nanowire (Ag NW) based films are considered as a promising alternative for traditional indium tin oxide but still suffer from some limitations, including insufficient conductivity, transparency and environmental instability. We here report a novel etching synthesis strategy to improve the performance of Ag NW films. Different from the traditional methods to synthesize high aspect ratios of NWs or employ electrically conductive coatings, we find it effective to reduce the high-reactivity defects of NWs for optimizing the comprehensive performance of Ag NW films. In this strategy etching can suppress the generation of high-reactivity defects and meanwhile the etching growth of NWs can be accomplished in an uneven ligand distribution environment. The resulting Ag NWs are uniformly straight with a sharp-edged structure. The transparent conductive film obtained exhibits simultaneous improvements in electrical conductivity, transparency and air stability. Even after exposure in air for 200 days and no protective coatings, the film can still meet the highest requirement of practical applications, with a figure of merit 361 (i.e., FoM > 350). These results not only demonstrate the importance of defect control in the synthesis of Ag NWs, but also pave a way for further optimizing the performance of Ag NW-based films.
Motion deblurring based on time-evolution of simultaneous nonlinear reaction-diffusion

Previously we have presented a method for selective image sharpness enhancement. Our method is based on the simultaneous nonlinear reaction-diffusion time-evolution equipped with a nonlinear diffusion term, a reaction term and an isotropic peaking term, and it can sharpen only degraded edges blurred by several causes without increasing the visibility of nuisance factors such as random noise. This paper applies our simultaneous nonlinear reaction-diffusion method to removal of image blurs due to image motion. The motion blur is not only shift-variant but also anisotropic. To adapt our simultaneous nonlinear reaction-diffusion method for motion de-blurring, we replace the isotropic Laplacian operator, included in the isotropic peaking term of our prototypal method, with the anisotropic operator considering the direction of the estimated image motion. Preliminarily experiments using artificially generated test images show that our method achieves excellent motion de-blurring.