Miracle-dz/UniFAR-FTUs huggingface dataset:
MANUFACTURING DEFECT DETECTION IN TEXTILE INDUSTRY USING NEURAL NETWORK

Quality scrutiny is an important aspect of contemporary industrial manufacturing. In textile industry production, automate fabric inspection is important for maintain the fabric quality. For a long time the fabric defects inspection process is still carried out with human visual inspection, and thus, insufficient and costly. The augmentation of fully computerizedtrap inspection system requires stout and capable fabric defect detection algorithms. The detection of local fabric defects is one of the most intriguing problems in computer vision. Texture scrutiny plays an important role in the automated visual examination of texture images to detect their defects. With the increasing customer demand on fabric variety in fashion market, fabric texture becomes much more diverse, which brings great challenges to accurate fabric detect detection. Therefore, an image processing method for automatically detecting minute scratches in fabrics without human help is introduced to reduce the cost and time waste caused by defects. In this a fabric inspection model, consisting of image preprocessing, image segmentation and image classification, is developed to address the fabric defect detection problem in the apparel industry, especially for fabric with complex texture and tiny defects. The information gathered in classification step is serially sent to microcontroller. If any defects are detected then LCD will be displayed indicating defect send alerting SMS, calls to the authority person and buzzer will be alarmed.
CHARACTERIZATION OF THE B CELLS IN LUPUS-PRONE AND RESISTANT MOUSE MODELS

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy CHARACTERIZATION OF THE B CELLS IN LUPUS-PRONE AND RESISTANT MOUSE MODELS By Biyan Duan May 2006 Chair: Laurence Morel Major Department: Pathology, Immunology and Laboratory Medicine The general hypothesis is that in the models of lupus-prone and resistant mice, B cells function differently and contribute to the phenotypes and pathogenesis. Thus, the studies of B-lymphocytes in these models may help to understand the role of B-cells and to identify involved genes.Defect splenic marginal zone (MZ) has been found in the lupus-prone NZM2410 and B6.Sle1/2/3 (TC), but not in the lupus resistant NZM.TAN (TAN) mice. I hypothesize that this defect is due to the abnormal functions of marginal zone B cells and contributes to the pathogenesis. Immuno-fluorescence study revealed that lupus MZ B cells were trans-located inside the follicle. MZ macrophages (MZM) were also found defect only in the lupus mice. Reciprocal bone marrow transfer indicated that the lack of MZM was not the reason of MZB translocation, and MZB miss-location was determined by both bone marrow and stroma-derived factors. Functional studies revealed that MZ B cells in TC and TAN mice were abnormal. The second goal of the research was to study the phenotypes and functions of the peritoneal cavity (PerC) B cells in these strains. Both lupus-prone and resistant mouse models have increased PerC B cells, especially B1 cells. Studies showed TAN PerC B1
Areal sizes of high, intermediate, low and total suitable habitats are correlated to the global extinction risk for mammals

The relationships between areal sizes of high, intermediate, low, and total sum of habitats with low, intermedi- ate and high suitability habitat ranges, and the International Union for Conservation of Nature (IUCN) threatened status of global terrestrial mammals were studied. Polyserial correlation analysis showed that all types of areal size closely and positively correlated with IUCN categories of threatened species. The results indicate that area-based extinction risk as- sessment is feasible and reliable in species' conservation prioritization. Furthermore, the partial polyserial correlation test indicates that significant correlations between the IUCN threatened status of species and range sizes of high, intermediate and low suitability habitats are not influenced by the polyserial correlation between IUCN threatened status and total suit- ability habitat range size. Thus, the prediction of species' extinction risks can be accurately fulfilled by evaluating the areal size of any one of total, high, intermediate or low suitability ranges. The present study implies that if the area size informa- tion of a totally suitable range is not available for species' extinction risk assessment, the usage of areal sizes from any parts of suitable habitats (high, intermediate or low) are effective surrogates.
Advanced Cusp Field Thruster with a 3D-printed discharge channel-Performance with Iodine and Xenon

Small satellite constellations require efficient electric propulsion subsystems to enable the required raising and de-orbiting capabilities. A possible thruster candidate for future constellations is the Advanced Cusp Field Thruster (ACFT) that has been developed over the last years by Airbus in Friedrichshafen. The ACFT has a wide operation range featuring specific impulse (Isp) up to 2000 s, power-to-thrust-ratio (PTTR) between 15W/mN and 35W/mN and thrust levels up to 14mN. The performance of an ACFT with conventionally manufactured boron-nitride (BN) discharge chamber will be discussed comparing iodine and xenon. An additive-manufactured (AM) discharge chamber constructed from alumina (Al2O3)has been tested with xenon and the results are compared to those using a BN discharge chamber. Furthermore, we have analysed the electric performance of the ACFT with xenon, monitoring the anode current using a high frequency current probe during ignition and normal operation at various points of operation. ∗PhD student, Laboratory for Enabling Technologies / JLU Giessen, max.vaupel@airbus.com. †Technical Lead, Laboratory for Enabling Technologies, franz.hey@airbus.com. 1 The 36th International Electric Propulsion Conference, University of Vienna, Austria September 15-20, 2019
Using dual quaternions for Control Cluster Method

Realistic character mesh deformation has been one of the key issues in different applications of 3D computer graphics as video games or crowd simulation. Geometric techniques such as skinning are considered an intuitive way to achieve visually plausible animation of the human-like characters despite of having certain shortcomings. Control cluster method is an alternative to tackle those drawbacks of the traditional techniques. In this paper a modification of control cluster method using dual quaternions and Bezier patch meshes is presented. Control cluster method tends to split all the vertices of the polygonal model mesh into two groups: cluster and free vertices. Free vertices position is calculated based on cluster vertices position in a non-linear fashion. Dual quaternion skinning application to cluster vertices calculation is discussed.
Fattyacidcompositionofbrain,retina, and erythrocytes in

Breast-fed infants score better on visual and developmental tests than do formula-fed infants and this has been related to higher concentrations of erythrocyte docosahexaenoic acid (DHA, 22:6w3). This prompted an investigation into the relationship between brain, retina, and erythrocyte fatty acids and diet in infancy. Total lipids of erythrocytes, retina, and brain cor- tex from 35 term infants were analyzed by capillary gas chro- matography. Breast-fed infants had a greater proportion of DHA in their erythrocytes and brain cortex relative to those fed formula (P < 0.005) but differences were not observed in retina. Cortex DHA increased in breast-fed (but not formula-fed) infants with age (r2 = 0.72, P < 0.01, n = 15), largely an effect of length of feeding (r2 = 0.62, P < 0.01, n = 35). There was an association between age at death and erythrocyte DHA with cortex DHA (r2 = 0.50, P < 0.01 ). In contrast, accretion of cortex arachidonic acid was dependent on age but not diet. The higher concentration of DHA in brains of breast-fed infants may explain the improved neurodevelopment reported in breast-fed compared with for- mula-fed infants. Am J Clin Nutr l994;60:l89-94.
Influence of seed size and soil strength on emergence and early seedling establishment in a soil with hardsetting behavior

The study was conducted to compare the influence of seed size and soil strength on germination and emergence of cereal and legume seedlings in a hardsetting soil. The seed weights (g 100 -1 seeds) of the plant species were 45.5 (maize), 4.5 (wheat), 2.5 (sorghum), 3.1 (oats), 0.54 (millet), 46.95 (bambaranut), 19.82 (cowpea), 3.13 (peas) and 45.14 (groundnut). Seedlings of each of the crop species were exposed to soil strengths of 1.2 and 2.4 kg /cm 2 . This was achieved by sowing seeds at depths of 2.5 and 5.0 cm for 1.2 and 2.4 kg/cm 2 respectively. Emergence of seedlings was generally high in cereals (96%) than in legumes (56%). The emergence was in the order: sorghum (99.2%) > oats (96.7%) > millet (96.7%) > wheat (95.8%) > maize (87.5%) > cowpea (56.7%) > bambaranut (54.0%) > groundnut (34.2%) > pea (20.0%). The mean emergence percentage for the two soil strength levels were 88.0% and 52.5% for soil strengths of 1.2 kg/cm 2 and 2.4 kg/cm 2 respectively. Generally, cereal crops had higher emergence (87.6%) percentages than legumes (76.8%) in both soil strength levels. There was a significant negative correlation (r=-0.88, p<0.05) between soil strength and seedling emergence suggesting that poor emergence was caused by the high soil strength. It is suggested that the hypocotyl shape of the emerging cereal seedlings could have been able to exert much force in order to emerge from the strong soil. The study concluded that both seed weight and sowing depth should be considered when sowing seeds in a hardsetting soil if optimum germination and seedling establishment are to be achieved. (S.A. Materechera. Influence of seed size and soil strength on emergence and early seedling establishment in a soil with hardsetting behavior.Life Science Journal. 2011;8(S2):40-46) (ISSN: 1097 - 8135). http://www.lifesciencesite. com.
Comparison of Techniques for Diabetes Detection in females using Machine Learning

---------------------------------------------------------------------- Abstract - Diabetes is a cause of immense concern these days. Everybody adjusts their diets in such a way so as to avoid diabetes completely. This paper discusses the different factors present in the human body and how they indicate the presence of diabetes in women. It discusses the different machine learning techniques that have been employed in this project to predict whether the patient has diabetes or not. This paper also highlights the advantages of each of the algorithms used and how they are better suited for this problem.
Annotating and Recognising Visually Descriptive Language

We propose recognising “visually descriptive language” (VDL) as an interesting and potentially useful task for researchers working in the ﬁeld of Vision & Language integration. Adopting the deﬁ-nition of VDL proposed by Gaizauskas et al. (2015), that VDL is language that asserts propositions whose truth can be conﬁrmed through visual sense alone, we investigate the speciﬁc task of classifying sentences as wholly, partially or not at all visually descriptive. We discuss the annotation of VDL on several texts, and report results on automatic classiﬁers trained on the annotation, showing that the task can be performed at around 79% accuracy, suggesting that this is a potentially fruitful avenue for further research.
FAST DELTA COMPUTATIONS IN THE SWAP MARKET MODEL

We develop an efficient algorithm to implement the adjoint method that computes sensitivities of an interest rate derivative (IRD) with respect to different underlying rates in the co-terminal swap market model. The order of computation per step of the new method is shown to be proportional to the number of rates times the number of factors, which is the same as the order in the LIBOR market model.
Research report Opiate-like effects of sugar on gene expression in reward areas of the rat brain

Drugs abused by humans are thought to activate areas in the ventral striatum of the brain that engage the organism in important adaptive behaviors, such as eating. In support of this, we report here that striatal regions of sugar-dependent rats show alterations in dopamine and opioid mRNA levels similar to morphine-dependent rats. Specifically, after a chronic schedule of intermittent bingeing on a sucrose solution, mRNA levels fortheD2dopaminereceptor,andthepreproenkephalin andpreprotachykiningenesweredecreased indopamine-receptive regions ofthe forebrain, while D3 dopamine receptor mRNA was increased. While morphine affects gene expression across the entire dopamine-receptive striatum, significant differences were detected in the effects of sugar on the nucleus accumbens and adjacent caudate-putamen. The effects of sugar on mRNA levels were of greater magnitude in the nucleus accumbens than in the caudate-putamen. These areas also showed clear differencesin the interactions among the genes, especially between D3R and the othergenes. This was revealed by a novelmultivariate analysis method that identified cooperative interactions among genes, specifically in the nucleus accumbens but not the caudate-putamen. Finally, a role for these cooperative interactions in a load-sharing response to perturbations caused by sugar was supported by the finding of a different pattern of correlations between the genes in the two striatal regions. These findings support a major role for the nucleus accumbens in mediating the effectsofnaturallyrewardingsubstancesandextendananimalmodelforstudyingthecommonsubstratesofdrugaddictionandeatingdisorders.
Neural Networks: Proposed Methodology for Applications Development

A review of published business neural network applications research is conducted to determine what parts of development methodologies were used or could have been used in designing, constructing, and deploying the networks. This review is limited to articles describing either the development of a prototype or an actual neural network application. Based upon this review and upon accepted development processes for creating NNs, a methodology for the complete development of neural network applications is proposed. The methodology provides a systematic view of the steps involved in the development of a successful NN business application which will allow for (1) better analysis of existing NN applications, (2) identification and development of new applications that can benefit from NN technology, and (3) development of improved NN applications.
SINGLE SWITCH HIGH GAIN ISOLATED DC-DC CONVERTER WITH ACTIVE CLAMP

— In this paper, an isolated high gain single switch dc-dc converter is proposed. In the proposed converter, high step-up voltage is obtained by single power switching technique that operates appropriate duty cycle with isolated transformer inductors, switched capacitor and power diodes. It alleviates the conventional converters high duty ratio and high voltage stress on power devices. The proposed converter eliminates the switching losses by the method of series resonance soft switching with an active clamp. To achieve high output voltage gain, the isolated transformer primary and secondary terminals are connected in series during switching operation. The proposed scheme experimented with solar cell characteristic. PSIM software has been used for simulation. The operation is verified by simulation and validated by implementing in the hardware model at 40Vdc/400Vdc, 100kHz, 500Watts.
DYNAMIC PERFORMANCE IMPROVEMENT OF A TWO-AREA POWER SYSTEM BY PSS AND SERIES FACTS BASED DAMPING CONTROLLERS USING ANFIS TECHNOLOGY

The most common control action to enhance damping of the power system oscillations is provided by the use of Power System Stabilizers (PSSs). The function of this device is to extend stability limits by modulating generator excitation to provide damping to the electromechanical oscillations. Nowadays, due to the technological stage of high power electronic devices, other effective solution such as the use of FACTS (Flexible AC Transmission System) controllers to damp low frequency electromechanical oscillations is being considered. Here, the series FACTS based damping controller such as Static Synchronous Series Compensator (SSSC) is employed. In this paper, an adaptive damping controller using ANFIS (Adaptive Neuro-Fuzzy Inference System) approach has been proposed to provide a robust and flexible power oscillation damping performance for both PSS and SSSC devices applied in a two-area power system. The efficiency of the proposed approach is validated through simulation, carried out in Matlab/Simulink environment. The digital simulation results have shown that even though initial overshoot may be slightly high, there is a significant reduction in settling time for the system with neuro-fuzzy based SSSC controller when subjected to small-signal perturbations, as compared with neuro-fuzzy based PSS control scheme.
PERFORMANCE COMPARISON OF HARD AND SOFT SWITCHED POWER CONVERTERS IN SUPPRESSING HARMONICS USING CHAOS MODULATION

Switched mode power supplies are significant generator of harmonics and electromagnetic noise . This has always been a serious concern, as it adversely affects the operation of the system. In this paper, the effectiveness of soft switching in reducing harmonic noise is first investigated. Then external chaos is added to the soft switching and the combined effect in suppressing the harmonic noise and EMI is investigated. DC-DC buck converter is taken as case study and the comparative evaluation has been made using spectral analysis. Simulations are carried out for hard switching and soft switching techniques, with external chaos generator included, using Matlab. Results confirm that, compared with the conventional hard switching method with chaos modulation, the soft switching technique with chaos modulation substantially reduces the EMI in the power converter. The simulated results are compared with the experimental counterparts to verify the validity of the approach.
Treatment Effects and the Measurement of Skills in a Prototypical Home Visiting Program

This paper evaluates the causal impacts of an early childhood home visiting program for which treatment is randomly assigned. We estimate multivariate latent skill profiles for individual children and compare treatments and controls. We identify average treatment effects of skills on performance in a variety of tasks. The program substantially improves child language and cognitive, fine motor, and social-emotional skills development. Impacts are especially strong in the most disadvantaged communities. We go beyond reporting treatment effects as unweighted sums of item scores. Instead, we examine how the program affects the latent skills generating item scores and how the program affects the mapping between skills and item scores. We find that enhancements in latent skills explain at least 90% of conventional unweighted treatment effects on language and cognitive tasks. The program enhances some components of the function mapping latent skills into item scores. This can be interpreted as a measure of enhanced productivity in using given bundles of skills to perform tasks. This source explains at most 10% of the average estimated treatment effects.
BRAINSTORMING: A REVIEW OF RESEARCHES

Brainstorming activity is one of the most important methods for developing creative thinking in the students as well as resolving the problems in the field of education, social and economic growth, political issues etc. it is particularly helpful when one need to break out stales, established patterns of thinking so that they can develop quick new ways of looking at things. The purpose of this review paper is to analyze the previous studies and provide suggestions for further research. In this paper, a review of some studies has done from 1975 to 2015. Many studies have conducted regarding the effectiveness of brainstorming for ideas generation in different areas but there is not satisfactory status of researches on brainstorming used as a teaching method for improving novel ideas generation and developing creative thinking in the teaching-learning process. Therefore, it is need to focus on its implication in the classroom situation and give attention on further research for finding out better results of brainstorming. This paper will provide a better view about process and importance of brainstorming and further insight about knowledge gaps, i.e. study of brainstormingwith other new concepts asaesthetic creativity, mathematical creativity, intelligence, scientific attitude and other demographic variables.
miRNAs-Based Molecular Signature for KRAS Mutated and Wild Type Colorectal Cancer: An Explorative Study

microRNAs (miRNAs) have been proposed as promising molecular biomarkers for diagnosis, prognosis, and responsive therapeutic targets in different types of cancer, including colorectal cancer (CRC). In this study, we evaluated the expression levels of 84 cancer-associated miRNAs in a cohort of 39 human samples comprising 13 peritumoral and 26 tumoral tissues from surgical specimens of CRC patients. KRAS mutations were detected in 11 tumoral samples. In a first analysis, we found 5 miRNAs (miR-215-5p, miR-9-5p, miR-138-5p, miR378a-3p, and miR-150-5p) that were significantly downregulated and one upregulated (miR-135b-5p) in tumoral tissues compared with the peritumoral tissues. Furthermore, by comparing miRNA profile between KRAS mutated CRC tissues respect to wild type CRC tissues, we found 7 miRNA (miR-27b-3p, miR-191-5p, miR-let7d-5p, miR-15b-5p, miR-98-5p, miR-10a-5p, and miR-149-5p) downregulated in KRAS mutated condition. In conclusion, we have identified a panel of miRNAs that specifically distinguish CRC tissues from peritumoral tissue and a different set of miRNAs specific for CRC with KRAS mutations. These findings may contribute to the discovering of new molecular biomarkers with clinic relevance and might shed light on novel molecular aspects of CRC.
Economic Policy Uncertainty and the Great Recession

I use Bayesian time-varying parameters structural VARs with stochastic volatility, and two alternative identification schemes, to explore the role played by policy uncertainty shocks within the context of the Great Recession in the United States, the Euro area, the United Kingdom, and Canada. Shocks identified as being orthogonal to the state of the economy (except stock prices) within the month played a uniformly marginal role in either country. An alternative identification strategy in the spirit of Uhlig (2003, 2004) points instead towards a non-negligible role, with, e.g., (i) the fraction of 1-year ahead forecast error variance of U.S. industrial production growth explained by these shocks being around 20-30 per cent over the entire sample period; and (ii) the trough in median counterfactual industrial production growth in the aftermath of the collapse of Lehman Brothers being equal to -8.5 per cent, as opposed to the actual value of -16.3 per cent. In either country, the period following the collapse of Lehman Brothers has been characterized by an increase in both the volatility of policy uncertainty shocks, and the fraction of draws from the posterior distribution for which they are estimated to have been positive (i.e., contractionary). Impulse-response functions, on the other hand, did not exhibit any peculiar pattern, during the Great Recession, compared to previous years.