Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-driven Multiple Importance Sampling for Monte Carlo Rendering

Monte Carlo (MC) rendering is the most common method in Computer Graphics to generate photo-realistic images. To enhance it efficiently, a variety of methods related to sampling has been developed, one of the simple and efficient way is Multiple Importance Sampling (MIS). This technique is a powerful technique for combining several sampling strategies. However, choosing an optimal weight in combining several sampling strategies remains a challenge. To address this problem, we propose a data-driven weight computation for reducing the variance of MIS. The point of our method is to utilize the scene information. We use precomputation for utilizing scene information, and it allows for computing an optimal weight depending on a scene. Specifically, optimal weight varies on each portion of the scene. Our method applies an optimal weight to an image locally. We observed meaningful results over prior methods in different scenes.
SAXS Analysis of Magnetic Field Influence on Magnetic Nanoparticle Clusters

In this work, we investigated the local colloidal structure of ferrofluid, in the presence of the external magnetic field. The nanoparticles studied here are of the core-shell type, with the core formed by manganese ferrite and maghemite shell, and were synthesized by the coprecipitation method in alkaline medium. Measures of Small Angle X-ray Scattering (SAXS) performed in the Brazilian Synchrotron Light Laboratory (LNLS) were used for the study of the local colloidal structure of ferrofluid, so it was possible to study two levels of structure, cluster and isolated particles, in the regimes with and without applied magnetic field. In the methodology used here there is a combination of the information obtained in the system with and without magnetic field application. In this way, it is possible to undertake a better investigation of the colloidal dispersion. The theoretical formalism used: (i) the unification equation proposed by Beaucage G. ; (ii) the analysis of the radial distribution function p ( r ) and (iii) theoretical calculation of the radius of gyration as a function of the moment of inertia of the spherical of n-nanoparticles.
DEVELOPMENTAL CHANGES OF ANTIPIT CELL ULTRASTRUCTURE IN THE SOYBEAN SEED COAT DURING SEED MATURATION

The fine structure of the antipit cells of soybean {Glycine max (L.) Merr. } endosperm were analyzed by transmission electron microscopy (TEM) during the rapid seed fill period. The antipit, which apposes the pit on the abaxial surface of the cotyledon, was composed of filamentous cells whose wall porosity appeared to increase during seed development. The filamentous cells were interconnected to each other and the subtending aleurone cells by plasmodesmata. During seed fill, the filamentous cells contained numerous Golgi cisternae derived vesicles that appeared to accumulate in the cytoplasm at the end of seed fill. The Golgi cisternae were well developed; rough endoplasmic reticulum (RER), which was abundant, consisted of large stacked cisternae. The Golgi cisternae were completely fenestrated and had fewer associated secretory vesicles at the end of seed fill. The stacked lamellae of RER, were progressively replaced by short tubular cisternae and small vesicles. At the end of seed fill, the filamentous cells contained numerous lipid bodies, protein bodies and amyloplasts with large starch grains. These observations suggest that the antipit consists of physiologically active tissue that may be involved in symplastic transport of nutrients to the embryo.
DIFFERENT TYPE OF LOG FILE USING HADOOP MAPREDUCE TECHNOLOGY

There are various applications which have a huge amount of database in different format. All databases maintain log files that keep records of database changes in a system formation. This can include tracking various user events and activity. Apache Hadoop can be used for log processing at scale of a system. Log files have become a standard part of large applications and large scale industry , computer networks and distributed systems. Log files are often the only way to identify and locate an error in software as well as system, because log file analysis is not affected by any time-based issues known as probe effect or a system effect. This is opposite to analysis of a running program, when the analytical process can interfere with timecritical or resource critical conditions within the analyzed program in a system. Log files are often very large and can have complex structure of database. Although the process of generating log files is quite simple and straightforward, log file analysis could be a tremendous task that requires enormous computational resources, long time and sophisticated procedures and time consuming . This often leads to a common situation, when log files are continuously generated and occupy valuable space on storage devices, but nobody uses them and utilizes enclosed information. The overall goal of this project is to design a generic log analyzer using hadoop map-reduce framework. This generic log analyzer can analyze different kinds of log files such asEmail logs, Web logs, Firewall logs Server logs, or System produces.
Fracture Toughness Testing and Prediction for Ceramic Materials Using in Large-Flow-Rate Emulsion Pumps

Fracture toughness (KIC) tests have been carried out on single edge precracked beam specimens with dimensions in accordance with ISO15732 requirements for two types of zirconia and one type of alumina, i.e. ZrO2 -1, ZrO2 -2 and Al2O3. Experimental determinations of KIC for the two zirconia and one alumina materials are 12.18 MPa•m1/2, 16.35 MPa•m1/2 and 4.99 MPa•m1/2, respectively. The median rank method is used to calculate the probability of fracture, F(KIC) of the three cermaic materials for representing the experimental results. The SEM analysis on fracture surfaces of ZrO2-1 materials is carried out, which indicates the fracture in ZrO2 -1 material occurred at the interior of the grain associated with interior stress distribution with principal components of ZrO2 and SiO2. Th extended finite element method (XFEM), based on the linear elastic fracture mechanics in conjuciton with a bilinear traction-separation damage law, is used to simulate the progressive crack growth process in the SEPB specimens. The XFEM predicted KIC results are compared with the corresponding experimental data. The XFEM approach overpredicts the KIC values, from 10.4% to 25.6%, for the three ceramic materials. The possible reasons, in the aspect of loading conditions and contact assumptions, for the difference between the predicted and tested results are also discussed.
FINE-GRAINED EMOTION DETECTION IN MICROBLOG TEXT

Automatic emotion detection in text is concerned with using natural language processing techniques to recognize emotions expressed in written discourse. Endowing computers with the ability to recognize emotions in a particular kind of text, microblogs, has important applications in sentiment analysis and affective computing. In order to build computational models that can recognize the emotions represented in tweets we need to identify a set of suitable emotion categories. Prior work has mainly focused on building computational models for only a small set of six basic emotions (happiness, sadness, fear, anger, disgust, and surprise). This thesis describes a taxonomy of 28 emotion categories, an expansion of these six basic emotions, developed inductively from data. This set of 28 emotion categories represents a set of finegrained emotion categories that are representative of the range of emotions expressed in tweets, microblog posts on Twitter. The ability of humans to recognize these fine-grained emotion categories is characterized using inter-annotator reliability measures based on annotations provided by expert and novice annotators. A set of 15,553 human-annotated tweets form a gold standard corpus, EmoTweet-28. For each emotion category, we have extracted a set of linguistic cues (i.e., punctuation marks, emoticons, emojis, abbreviated forms, interjections, lemmas, hashtags and collocations) that can serve as salient indicators for that emotion category. We evaluated the performance of automatic classification techniques on the set of 28 emotion categories through a series of experiments using several classifier and feature combinations. Our results shows that it is feasible to extend machine learning classification to fine-grained emotion detection in tweets (i.e., as many as 28 emotion categories) with results that are comparable to state-of-the-art classifiers that detect six to eight basic emotions in text. Classifiers using features extracted from the linguistic cues associated with each category equal or better the performance of conventional corpus-based and lexicon-based features for finegrained emotion classification. This thesis makes an important theoretical contribution in the development of a taxonomy of emotion in text. In addition, this research also makes several practical contributions, particularly in the creation of language resources (i.e., corpus and lexicon) and machine learning models for fine-grained emotion detection in text. FINE-GRAINED EMOTION DETECTION IN MICROBLOG TEXT
Accurate Direct Visual-Laser Odometry with Explicit Occlusion Handling and Plane Detection

In this paper, we address the problem of combining 3D laser scanner and camera information to estimate the motion of a mobile platform. We propose a direct laser-visual odometry approach building upon photometric image alignment. Our approach is designed to maximize the information usage of both, the image and the laser scan, to compute an accurate frame-to-frame motion estimate. To deal with the sparsity of the range measurements, our approach identifies planar point sets within individual point clouds and subsequently extract their corresponding pixel patches from the camera image. The extracted planar image patches are used together with the non-planar pixels to estimate the frame-to-frame motion using a homography formulation capable of incorporating both types of pixel alignments. To achieve high estimation accuracy, we explicitly predict possible occlusions caused by observations taken from different locations. We evaluate our proposed approach using the KITTI dataset as well as data recorded with a Clearpath Husky platform. The experiments suggest that our approach can achieve competitive estimation accuracy and produce consistently registered, colored point clouds.
Impact of Capital Structure on the Performance : An Empirical Analysis of Indian Banking Sector

The determination of capital structure is one of the critical issue confronting banks in India and any inappropriate decision concerning it may prove havoc for the liquidity, solvency and profitability of the banks. Keeping the same into consideration an attempt is made in the present study to determine the impact of capital structure on the performance of banks in India. Although a significant numbers of banks are currently operating in India, yet broadly these can be classified into Private Banks, Nationalized Banks, SBI & its Associates and Foreign Banks. This four pillar broad classification is taken into consideration for the purpose of present study and covers a period of 6 years from 2009-2014. The sources of data comprise of annual reports of the sampled banks and statistics released by RBI form time to time. The data is collected for numbers of variables comprise of dependent and independent variables and the analysis of collected data is carried out using alternative research methodologies which include both static and dynamic panel regression. The results of the study provided that explanatory variables have statistical and significant influence on the explained variable. It is therefore recommended that the banks should always consider their position with respect to determinants of capital structure before embarking on financing decision.
Positioning of Thermal Via Regions for Reducing Hotspot Temperature in 3D ICs

3D stacking of integrated circuits seems to be a main trend for increasing the processor performance. However, It results in power density increase inducing additional thermal issues that have to be overcome. In this paper we analyze the thermal behaviour of eight-core processor based on Intel Haswell architecture implemented as a 2D chip and as a 3D architecture with two layers. We implement special via regions in 3D structure in various configurations and we compare results to that obtained for 2D structure. We show that the peak temperature can be significantly reduced and locations of via regions notably affects temperature distribution inside the chip.
PV based Thirteen Level Multilevel Inverter for Photovoltaic Systems

This paper approaches the appearing and modernization of S-Type PV based 13-level multilevel inverter with less quantity of switch. The current S-Type Multi level inverter contains more number of switches and voltage sources. Multilevel level inverter is a be understandable among the most gainful power converters for high power application and present day applications with reduced switches. The fundamental good arrangement of the 13-level multilevel inverter is to get ventured voltage from a couple of levels of DC voltages. The controller gives actual way day and age to switches through driver circuit using PWM methodology. The execution assessment of proposed multilevel inverter is checked using MATLAB/Simulink. This is the outstanding among other technique appeared differently in relation to all other existing system. 1 International Journal of Pure and Applied Mathematics Volume 118 No. 17 2018, 549-560 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu
Breaker evaluation and formation damage remediation of re-crosslinkable preformed particle gel (RPPG)

Re-crosslinkable preformed particle gel (RPPG) is a newly developed preformed particle gel for improving sweep efficiency and oil recovery by blocking or reducing the conductivity of fractures and fracture-like channels or conduits. However, RPPG has the potential to plug the facilities or damage the formation if a treatment is not properly conducted. This work presents the performance of selected oxidizing breakers on the degradation of RPPG. The influence of a few factors on the degradation process was investigated, including breaker type, breaker concentration, temperature, gel concentration, gel aging time, and gel size. Results indicate that breaker type, concentration, and temperature have the most significant effects on RPPG degradation. Na2S2O8 activated by NaOH provided the best degradation performance on RPPG compared with other breakers. RPPG degradation degree increased with breaker concentration and temperature. More generally, lowering the RPPG concentration can result in a better degradation degree. Moreover, the aging time of RPPG had negligible effect on the degradation of RPPG. Besides the static evaluations of RPPG degradation, several core flooding tests were carried out to analyze the RPPG damage remediation by breakers. The results show that breakers could result in the restoration of the cores’ permeability. The lower RPPG injection pressure resulted in a better permeability restoration, and low permeability cores can also result in a better permeability restoration compared higher permeability cores.
Discharge coefficient of an orifice jet in cross flow: influence of inlet conditions and optimum velocity ratio

The present work aims to characterize the discharge performance of aircraft door vent flaps. For this purpose, three different configurations with increasing complexity are studied with a RANS and a LES solver. The first configuration consists of an orifice plate in a duct for which experimental pressure loss data are available in the literature. This configuration is used as a reference for the validation of the RANS and LES setups. The duct placed downstream of the orifice is then removed to produce an unconfined geometry in which the orifice jet discharges either into an open atmosphere or a transverse flow. Finally, a classic jet in cross flow is also studied. The main objective is to analyze the discharge coefficient variations depending on three key parameters: (i) the jet Reynolds number, (ii) the inlet velocity profile, and (iii) the velocity ratio between the jet and the cross flow. Results show that for cases without cross flow, the jet Reynolds number has no influence on the discharge performance whereas a steady decrease of the orifice pressure loss is observed as the duct inlet velocity profile is deformed from that of a flat profile. The Poiseuille profile is found to minimize the pressure loss. In addition, numerical data of the reference configuration compare well with experimental values when such a profile is prescribed. Finally, simulations with a cross flow evidence an optimal velocity ratio for which the discharge coefficient is maximum and exceeds the freejet value.
Study of active vision technology in precision measurement

In this paper,precise detection technology based on the(machinery) active vision has been discussed deeply.First,Canny edge monitor is used for the rough edge position,and then the sub-pixel description of the components edge is achieved by the second surface fitting of the edge,then the precise edge is obtained.Second,the model of automatic edge tracing based on array image is established.Automatic edge date join is achieved.It resolves the contradiction between high precise measurement and small field.Because of telecentric lens,the measurement error which caused by processing error of the components,positioning error and moving error of the camera is reduced,it is a successful application of active vision in precise detection.
Presynaptic Gαo (GOA-1) signaling depresses command neuron excitability to allow for stretch-dependent modulation of egg-laying behavior in C. elegans

Caenorhabditis elegans egg laying is a two-state behavior modulated by sensory input. Feedback of egg accumulation in the uterus drives activity of the serotonergic HSN command neurons to promote the active state, but how aversive sensory stimuli signal to inhibit egg laying is not well understood. We find the Pertussis Toxin-sensitive G protein, Gαo, signals in HSN to inhibit circuit activity and prolong the inactive behavior state. Gαo signaling hyperpolarizes HSN, reducing Ca2+ activity and input into the postsynaptic vulval muscles. Loss of inhibitory Gαo signaling uncouples presynaptic HSN activity from a postsynaptic, stretch-dependent homeostat, causing precocious entry into the egg-laying active state. NLP-7 neuropeptides signal to reduce egg laying both by inhibiting HSN and by activating Gαo in cells other than HSN. Thus, Gαo integrates diverse signals to maintain a bi-stable state of electrical excitability that dynamically controls circuit activity and behavior output in response to a changing environment.
Noise reduction in near infrared-based glucose concentration measurement sensor

This paper describes the method of measuring glucose concentrations in solution using near infrared light (NIR) and photodiode sensor. A sensitive and accurate non invasive blood glucose level sensor is our main concern in designing this device. The sensor consists of a transimpedance amplifier, a notch filter and a low pass filter to reduce high frequency noise and 50 Hertz noise from the power line induction. Light Emitting Diode (LED) with 1450 nm wavelength is used as a light source and a photodiode is used as a sensor to sense this wavelength. The NIR light received by the photodiode after passing glucose solution is converted to voltage signal and filtered to determine the output voltage. The measurement results show that the filters reduced the AC voltage or noise signal under 100 mV and the DC voltage tended to decrease as glucose concentration increase until 700 mg/dL.
Risk Contours Map for Risk Bounded Motion Planning under Perception Uncertainties

—In this paper, we introduce ” risk contours map ” that contains the risk information of different regions in uncertain environments. Risk is deﬁned as the probability of collision of robots with obstacles in presence of probabilistic uncertainties in location, size, and geometry of obstacles. We use risk contours to obtain safe paths for robots with guaranteed bounded risk. We formulate the problem of obtaining risk contours as a chance constrained optimization. We leverage the theory of moments and nonnegative polynomials to provide a convex optimization in the form of sum of squares optimization. Provided approach deals with nonconvex obstacles and probabilistic bounded and unbounded uncertainties. We demonstrate the performance of the provided approach by solving risk bounded motion planning problems.
Structured ZnO and Al2O3/Ag Surfaces: Antibacteriality, Photocatalytic Activity and Durability

Functional coatings, i.e. coatings that possess a property that adds a desirable function onto a surface, offer great potential in numerous situations when specific requirements of a material must be fulfilled. Self-cleaning and antibacterial properties are useful in many cases, for instance in factories to reduce costs caused by washing processes or in hospitals to prevent bacterial infections. The self-cleaning property can be obtained with superhydrophobic, in other words highly water repellent, coatings. Besides the superhydrophobic surface, a photocatalytic surface also possesses self-cleaning capability. Photocatalysis is a phenomenon induced by light that can lead to oxidation and reduction reactions and further decomposition of organic pollutants. Photocatalytic surfaces exhibit antibacterial properties. There are also numerous metals that possess antibacterial properties, especially in the form of nanoparticles. In fact, silver is one of the most studied and used metal in antibacterial applications. In this study, we have prepared, analyzed, and investigated the properties of two selfcleaning, antibacterial surfaces: a superhydrophobic silver-containing coating and a photocatalytic ZnO film. ZnO is a photocatalyst with an additional antibacterial property that is attributed to its semiconductor properties, in addition to the toxicity of zinc ions against bacteria. In this work, we have demonstrated a route for preparing superhydrophobic silver-containing coatings and studied their antibacterial efficiency. We have also studied the effect of synthesis parameters on the structure of ZnO films. The influence of the structure of the ZnO film on functional properties, photocatalytic, and antibacterial activity has also been investigated. Moreover, we have demonstrated the functionality of silvercontaining superhydrophobic surfaces as effective antibacterial coatings. The approach of using two functional mechanisms, superhydrophobicity and antibacterial silver, offers great potential for self-cleaning applications. In addition, this study shows the antibacterial effectiveness of ZnO in dark conditions as well as the relatively high photocatalytic activity of structured ZnO films, on the basis of which we can anticipate enhanced antibacterial activity under irradiation. The chemical stability of the surfaces has been investigated in order to estimate the usability of the surfaces in varying environments. Based on the knowledge obtained in this study, the prospects of using superhydrophobic silvercontaining coatings and ZnO films in applications requiring antibacterial and self-cleaning properties are discussed.