Miracle-dz/UniFAR-FTUs huggingface dataset:
Graph-Based Locality-Sensitive Circuit Sketch Recognizer

The understanding of circuit diagram is very important for the study of electrical engineering. Existing circuit diagram simulation tools are mostly based on GUI interface and rely on users to click or drag icons with mouse, which requires them to be familiar with the software and distracts a great deal of their attention from the circuit diagram itself. Although a lot of previous works have devoted to designing algorithmic solution to recognize hand-drawn circuit diagrams automatically, there still exists strict constraints on users’ drawing habits and stroke orders. In order to address these inconveniences, this paper proposes a novel sketch recognition algorithm named <inline-formula> <tex-math notation="LaTeX">$LS^{4}D$ </tex-math></inline-formula>. It uses graph to model the input strokes and their relationships, and leverages cycles by local strokes to detect some circuit components. Theoretical derivations have demonstrated that <inline-formula> <tex-math notation="LaTeX">$LS^{4}D$ </tex-math></inline-formula> can efficiently recognize diagrams with different drawing styles and arbitrary stroke orders. To furthermore illustrate the practical value of the proposed approach, we construct a prototype of pen-based circuit diagram system based on <inline-formula> <tex-math notation="LaTeX">$LS^{4}D$ </tex-math></inline-formula>, which enables users to draw circuit diagrams directly on the digital screen without any other restriction. An experiment of 158 samples collected from 17 users is conducted on the designed platform. Our approach has achieved 93.04% recognition accuracy and overall 4.53 from a 5-scale user satisfaction rating, which outperforms previous state-of-the-art methods numerically. It is shown that the same approach can also be generalized to many other sketch recognition applications with minor modifications. To facilitate future researches and applications, we publish our source code, model, and training data at <uri>https://github.com/Huage001/</uri> Graph-Based-Circuit-Painter.
Image Segmentation and Object Detection of Lunar Landscape

This project aims to ﬁnd a solution to semantically segment lunar landscape images and detect some of their objects. There is already some realization of the method posted online. We used YOLOv2 to realize the object detection and use FCN-8s and DeepLabv3+ to do the semantic segmentation. From the result, FCN-8s and DeepLabv3+ can achieve a better result than posted models online.
Chest X-Rays Pathology Detection Using Augmented Datasets with GAN and Radiology Reports

X-Rays are the most common and best available medical imaging technique used to diagnose lungs, heart and chest related diseases. The number of radiologists is decreasing in the U.S. [1], which is even worse in the underdeveloped countries. This motivated us to develop an AI solution by building a hybrid deep Neural Network architecture using augmented datasets with GAN and Radiology Reports to detect and recognize cardiopulmonary diseases to help radiologists to maximize their effort in diagnosing the problems.
Multi-Agent Deep Reinforcement Learning in Imperfect Information Games

Reinforcement Learning has recently made big headlines with the success of AlphaGo and AlphaZero [7]. The fact that a computer can learn to play Go, Chess or Shogi better than any human player by playing itself, only knowing the rules of the game (i.e. tabula rasa), has many people interested in this fascinating topic (myself included of course! ). Also, the fact that experts believe that AlphaZero is developing new strategies in Chess is also quite impressive [4]. For my nal project, I developed a Deep Reinforcement Learning algorithm to play the card game Pedreaux (or Pedro [8]). As a kid growing up, we played a version of Pedro called Pitch with Fives or Catch Five [3], which is the version of this game we will consider for this project. Why is this interesting/hard? First, it is a game with four players, in two teams of two. So we will have four agents playing the game, and two will be cooperating with each other. Second, there are two distinct phases of the game: the bidding phase, then the playing phase. To become pro cient at playing the game, the agents need to learn to bidbased on their initial hands, and learn how to play the cards after the bidding phase. In addition, it is complex. There are ( 52 9 ) > 3×10 initial hands to consider per agent, coupled with a complicated action space, and bidding decisions, which makes the state space too large for tabular methods and one well suited for Deep Reinforcement Learning methods such as those presented in [2, 6].
A Literature Review of Employee Motivation

---With the development of globalization, there are many companies meet new challenges, employee work inefficiency, high turnover rate, which result in whole organization fall down. Motivation is very important factors that make employee work efficiency. So learn how to motivate employee is becoming more and more important. This article mainly talk about the importance of motivate employee. According to literature review and related theory, make a contribution for company how to motivate employee and conclude better suggestion, give some critical comments in order to support some advise to some companies.
Changing In-Group Boundaries: The Effect of Immigration on Race Relations in the Us

How do social group boundaries evolve? Does the appearance of a new outgroup change the ingroup&apos;s perceptions of other outgroups? We introduce a conceptual framework of context-dependent categorization, in which exposure to one minority leads to recategorization of other minorities as in- or outgroups depending on perceived distances across groups. We test this framework by studying how Mexican immigration to the US affected White Americans&apos; attitudes and behaviors towards Black Americans. We combine survey and crime data with a difference-in-differences design and an instrumental variables strategy. Consistent with the theory, Mexican immigration improves Whites&apos; racial attitudes, increases support for pro-Black government policies and lowers anti-Black hate crimes, while simultaneously increasing prejudice against Hispanics. Results generalize beyond Hispanics and Blacks and a survey experiment provides direct evidence for recategorization. Our findings imply that changes in the size of one group can affect the entire web of inter-group relations in diverse societies.
Abstractive Summarization for structured conversational text

ive summarization is the task of generating a summary comprising of a few sentences that meaningfully captures the important context from given text input. It is one of the known challenging problems in NLP since summarization doesn’t involve selecting existing sentences from the input, instead paraphrasing the main contents of the document using vocabulary previously unseen.
Rubeus-GAN: Attacking class imbalance via conditioned generation. A medical imaging perspective.

Exploiting learning algorithms under scarce data regimes is a limitation and a reality of the medical imaging ﬁeld. In an attempt to mitigate the problem, we propose a data augmentation protocol based on generative adversarial networks. The networks are conditioned at a pixel-level (segmentation mask) and at a global-level information (acquisition environment or lesion type). Such conditioning provides immediate access to the image-label pairs while controlling global class speciﬁc appearance of the synthesized images. To stimulate synthesis of the features relevant for the segmentation task, an additional passive player in a form of segmentor is introduced into the the adversarial game. We validate the approach on two medical datasets: BraTS, ISIC. By controlling the class distribution through injection of synthetic images into the training set we achieve control over the accuracy levels of the datasets’ classes.
Investigating the performance of single-and multichannel wireless receivers in generic-K fading channels

: By using versatile generic-K statistical model, a performance analysis of wireless system has been carried out through the composite fading channel scenarios. The composite fading model used here is flexible enough to represent all forms of mixed shadowed-fading channel conditions. With the aid of moment generating function (MGF) approach and Padé approximation (PA) technique, different performance measures such as outage probability and average bit error rate (ABER) have been evaluated for a variety of digital modulation formats. In contrast to previously obtained relatively complicated expressions in terms of MeijerG & Whittaker special functions, the PA technique has been used here to find tractable rational expressions for the MGF of output SNR. Using these simple rational expressions, the performance evaluations have been done for both single-and multichannel receivers under different shadowed-fading channel conditions. The numerical results are also validated through computer simulations, which show a perfect match .
Assessment of Corporal Punishmentamong Laboring Childrenat Nominated Regions of Egypt

Nahed Abd-Elazeem Abd-Elsalam*,Jihan Mahmoud Farrag**, Hanaa Mohamed Ibrahim Nassar*** *Lecturer in Family and Community Health Nursing Department, Faculty of Nursing, Port Said University, Egypt, **Lecturer inPediatric Nursing Department, Faculty of Nursing, Port Said University, Egypt. ***Lecturer inPediatric Nursing Department, Faculty of Nursing, Port Said University, Egypt. Corresponding Author: Nahed Abd-Elazeem Abd-Elsalam*
An investigation of emerin and nuclear lamins: : Interactions, distribution, and role in cell cycle regulation, in cells derived from EDMD patients.

Emery Dreifuss muscular dystrophy (EDMD) is caused by mutations either in the gene encoding emerin or in the gene encoding A-type lamins (lamins A and C). Several roles for emerin and A-type lamins have been proposed, including their involvement in nuclear structure, gene expression, cell cycle progression, and DNA replication. However, their functions are poorly understood and thus the mechanisms by which mutations cause different inherited diseases are not clear. In this project, the endogenous and exogenous distribution of emerin, and A- and B-type lamins in lymphoblasts and fibroblasts carrying mutations in emerin and A-type lamins have been investigated. For this purpose, anybodies against emerin, and A- and B-type lamins as well as GFP-, and DsRed- tagged fusion proteins (GFP-emerin, GFP-lamin A, and DsRed-lamin C) were used. From the immunofluorescence microscopy results of lymphoblasts, it is suggested that the distribution of emerin and lamins is possibly affected in these cells in EDMD. However, in fibroblasts there was no evidence of structural abnormality for the proteins investigated. The effects of emerin and A-type lamins mutations on growth and progression of cells through the cell cycle have also been investigated in fibroblasts of EDMD patients, using flow cytometry. The results obtained here suggest that emerin and lamin mutations may cause a cell cycle arrest at the G0 phase of the cycle.
Clinical and Optical Coherence Tomography Profile of Diabetic Maculopathy in Patients with and without Diabetic Nephropathy

Purpose: To compare the clinical profile and morphological pattern of Diabetic maculopathy using Optical Coherence Tomography (OCT) in Diabetes mellitus patients with and without Diabetic Nephropathy. Design: Comparative cross sectional study. Materials and Methods: 150 patients were enrolled, their clinical profile and diabetic retinopathy status were assessed. Quantitative analysis and morphological pattern of macular edema was compared between the patient having diabetic nephropathy and without nephropathy. Diabetic nephropathy was determined by patient having microalbuminuria, detected by doing spot urine albumin creatinine ratio. Results: Out of 150 patients 66.7% patients with Diabetic Nephropathy and 33.3% without microalbuminuria. 50% had moderate NPDR, 22.7% with severe NPDR, 22.7% with PDR, 4.7% with mild NPDR changes. Statistical significant difference was seen in better visual acuity (6/6 to 6/18) in patient with (28%) and without diabetic nephropathy group (46%). No significant difference was observed in maculopathy status between two groups. Duration of diabetes and hypertension showed no significant difference with the maculopathy severity. OCT pattern in macular edema between two groups showed no significant differences. Mean central foveal thickness in diabetic nephropathy group was 312.62 85.915 and without diabetic nephropathy was 289 73.748, No significant difference was observed. Conclusion: Patient without diabetic nephropathy had good vision. Early stage of diabetic nephropathy in the form of microalbuminuria showed no increase in the central foveal thickness. Diabetic nephropathy did not influence the morphological pattern of macular edema.
Test-based inference of polynomial loop-bound functions

This paper presents an interpolation-based method of inferring arbitrary degree loop-bound functions for Java programs. Given a loop, by its "loop-bound function" we mean a function with the numeric program variables as its parameters, that is used to bound the number of loop-iterations. Using our analysis, loop-bound functions that are polynomials with natural, rational or real coefficients can be found. Analysis of loop bounds is important in several different areas, including worst-case execution time (WCET) and heap consumption analysis, optimising compilers and termination-analysis. While several other methods exist to infer numerical loop bounds, we know of no other research on the inference of non-linear loop-bound functions. Additionally, the inferred bounds are provable using external tools, e.g. KeY. To infer a loop-bound function for a given loop it is instrumented with a counter and executed on a well-chosen set of values of the numerical program variables. By well-chosen we mean that using these test values and the corresponding values of the counter, one can construct a unique interpolating polynomial. The uniqueness and the existence of the interpolating polynomial is guaranteed if the input values are in the so-called NCA-configuration, known from multivariate-polynomial interpolation theory. The constructed interpolating polynomial presumably bounds the dependency of the number of loop iterations on arbitrary values of the program variables. This hypothesis is verified by a third-party proof assistant. A prototype tool has been developed which implements this method. This prototype can infer piecewise polynomial loop-bound functions for a large class of loops in Java programs. Applicability of the prototype has been tested on a series of safety-critical case studies. For most of the loops in the case studies, loop-bound functions could be inferred (and verified using a proof assistant).
Caractérisation des profils de traitements pour accident vasculaire cérébral et événements cliniques associés

Background: Stroke is a leading cause of disability and death, and secondary stroke prevention has been understudied in Canada. We examined, in the real-world clinical practice setting, treatment patterns for secondary prevention of acute ischemic stroke (AIS) according to patient sub-populations, and determined the risk of death or AIS recurrence over a one-year period.
Numerical Solution of Biomagnetic Fluid Flow in Parallel Plate Channel

This paper examines the numerical solution of bio-magnetic fluid flow in a parallel plate channel when both the plates are shrinking and the lower plate is porous. A magnetic field is applied perpendicular to the plane of the channel. The convective heat transfer with viscous dissipation is also analyzed. Numerical computations have been made for several values of the physical parameters namely magnetic parameter 2 M , suction parameterλ , Reynolds’ number R, Prandtl number Pr, Eckert number
Multilevel near optimal thresholding applied to watershed grouping

The major drawback of watershed transformation is over-segmentation. It also has a significant advantage: very good edge extraction. Thresholding methods usually utilize only global information such as an image histogram; however, they have the ability to group pixels into clusters by their value. The method presented in this paper combines the advantages of watershed segmentation and multilevel thresholding. This was achieved by modifying selected optimal thresholding methods so that they treat watersheds as a whole and using those methods in a multilevel thresholding algorithm for grouping watersheds. Otsu's, Kapur's, maximum entropy and step function approximation thresholding methods have been tested. The obtained results are presented and discussed.
Everyone could be artist: sketch to style-speciﬁed artwork

Sketch-to-image translation is meaningful in real world which provides a powerful tool for people to explore their potential in expressing themselves. Mapping from sketchs to real cat images and Van Gogh paintings separately for content and style is challenging. Therefore, we present a novel approach to learn the translation from a cat sketch to a target image combining cat content and Van Gogh style which is not existed in the real world. Finally, AMT perceptual studies are included to evaluate our generated images
A Novel Approach for Invoice Text Detection and Recognition

— Text detection has often been a major field of research in computer vision. Previous approaches by the academics have achieved promising results with regard to scene text detection, but these systems usually lack in detecting text that is present in a document format. Traditional OCR engines generally fail when the text in the image doesn’t follow a linear format. The proposed system specializes in providing a fast, and accurate text detection system for images that contain systematic and spatial data which is challenging when processed through traditional OCR engines. Our methodical improvements result in efficient text detection through a system that is reliable, fast, and intuitive. It performs well on text that is non-linear in nature and is segmented throughout the image. In comparison to other text detection algorithms such as EAST text detection, our implementation easily outperforms the state-of-the-art text detection techniques. Our proposed system would be highly beneficial for businesses and corporations in handling their financial data.
Surfactant-Modified Wheat Straw: Preparation, Characterization and its Application for Methylene Blue Adsorption from Aqueous Solution

Copyright: © 2015 Azadeh EP, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Abstract This work reports on the development of organo-modified wheat straw (WS) adsorbent prepared by using sodium dodecyl sulfate (SDS) for removing methylene blue (MB), a model cationic dye, from aqueous solution. The samples were characterized by scanning electron microscope (SEM), nitrogen physisorption and Fourier transforms infrared spectroscopy (FT-IR). Batch adsorption experiments were carried out to remove MB from its aqueous solutions using SDS modified WS (SMWS). Analysis of adsorption results showed that the adsorption pattern on the SMWS can be described perfectly with Langmuir isotherm model compared with Freundlich isotherm model, and the Langmuir adsorption capacity, Qmax was found to be 126.60 mg g-1 for SMWS and 55 mg g-1 for WS at 303K respectively. The adsorption kinetic followed the pseudo-second order kinetic model. Desorption studies suggest that MB adsorption onto the SMWS should be mainly controlled by the hydrophobic interaction mechanism, along with a considerable contribution of the cationic exchange mechanism.
ColorArt: Suggesting Colorizations For Graphic Arts Using Optimal Color-Graph Matching

Colorization is a complex task of selecting a combination of colors and arriving at an appropriate spatial arrangement of the colors in an image. In this paper, we propose a novel approach for automatic colorization of graphic arts like graphic patterns, info-graphics and cartoons. Our approach uses the artist’s colored graphics as a reference to color a template image. We also propose a retrieval system for selecting a relevant reference image corresponding to the given template from a dataset of reference images colored by different artists. Finally, we formulate the problem of colorization as a optimal graph matching problem over color groups in the reference and the template image. We demonstrate results on a variety of coloring tasks and evaluate our model through multiple perceptual studies. The studies show that the results generated through our model are significantly preferred by the participants over other automatic colorization methods.
Incidence of hepatocellular carcinoma and consequent lessons for its management in Northeastern Hungary

Bevezetés: A hepatocellularis carcinoma gyakori, nehezen kezelhető daganat. Célkitűzés: A szerzők áttekintették a májsejtrákkal kapcsolatos ismereteket és értékelték a kezelési eredményeket az északkelet-magyarországi régióban. Módszer: A szerzők intézményében 5 év alatt májsejtrák diagnózissal kezelt betegek adatait retrospektív módon elemezték. Eredmények: Ismert májcirrhosisa 187 beteg közül 71-nek (38%) volt, 52 betegnél (28%) a májcirrhosisra a daganat felismerésekor derült fény. Nem volt májzsugora 15 betegnek (8%), míg erre vonatkozóan 49 betegnél (26%) nem találtak adatot. Etiológiai faktorok az alkoholfogyasztás (52%), a vírushepatitis (41%) és a metabolikus szindróma (valószínűleg nem alkoholos zsírmáj) (44%) voltak. Cirrhosis nélkül kialakult májsejtrák hátterében leggyakrabban nem alkoholos zsírmáj állt. A daganat felismerése 83%-ban előrehaladott stádiumban történt. A túlélést a Barcelona stádium (A vs. B/C vs. D stádium: 829 vs. 387 vs. 137 nap, p<0,001) jelentősen befolyásolta, az etiológia nem (vírus 282, metabolikus szindróma 335 és alkohol 423 nap, p = 0,65). Következtetések: A hepatocellularis carcinoma rossz kimenetelének oka a késői felismerés. A májzsugoros betegek szűrése mellett a májcirrhosis korábbi felismerése szükséges. A metabolikus szindrómások ultrahangos szűrése megfontolandó. A krónikus májbetegség terápiája a túlélést lényegesen befolyásolja. Orv. Hetil. , 2016, 157(45), 1793–1801.
Diabète et Ramadan. Conséquences du jeûne et aspects pratiques de la prise en charge

Rev Med Liege 2017; 72 : 1 : xx-xx Résumé : Beaucoup de patients Musulmans diabétiques choisissent de jeûner durant le Ramadan, en dépit de recommandations qui conseillent à certains patients de s’abstenir en fonction de facteurs de risque établis. Le jeûne expose, en effet, le sujet diabétique à des complications aiguës majeures, dont l’acidocétose diabétique et les hypoglycémies sévères. Les patients diabétiques devraient, dès lors, bénéficier d’une prise en charge individualisée dès avant le Ramadan comprenant, entre autres éléments, une évaluation du risque et une éducation spécifique. Il convient, en particulier, d’adapter le traitement pharmacologique en vue de limiter la survenue de ces complications aiguës. mots-clés : Education Traitement Hypoglycémie Acidocétose Ramadan Diabetes anD RamaDan : consequences of fasting
Bayesian modelling of sensorimotor systems: Application to handwriting

This paper concerns Bayesian modeling of a sensorimotor system. We present a preliminary model of handwriting, in which the representation of letter is abstract, and is a pivot between motor and sensor models. We show how our model allows to solve a variety of tasks, like letter reading, recognizing the writer, and letter writing.