nils-herrmann/clean_scirepeval huggingface dataset:
Computer Aided System For Early Detection Of Nuclear Cataract Using Circle Hough Transform
Venue: 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)
Year: 2019

Survey done by world health organization for probing causes of blindness indicates that cataract is major cause of blindness. Even age related cataract is most commonly observed, it is serious cause to think because of its appearance in minors and children for both eyes. Detecting cataract at earlier stage is challenge as it has less affecting vision. The three most general types of cataract are nuclear cataract, cortical cataract and post subcapsular cataract. Slit lamp observation with lens opacity classification system (LOCS III) is used for detection and medical diagnosis by ophthalmologists. Lens replacement surgery is most common treatment suggested on cataract for correcting vision. Literature survey indicates towards the success and correctness of computer added detection and grading is function of correctness of lens localization from cataract eye image. The work presented in this paper uses slit lamp images from ophthalmologist at eye hospital with computer aided image processing to detect cataract at earlier stage. The challenge of detection of cataract at earlier stage is attended in steps like lens detection, lens segmentation, feature extraction and categorization. The overall accuracy is enhanced by use of Hough circle detection transform for lens detection and support vector machine for categorization. The detection and categorization is performed using statistical feature extraction with prior trained support vector machine.
Conditional Density Estimation of Tweet Location: A Feature Dependent Approach
Venue: MedInfo
Year: 2017

Twitter based public health surveillance systems have achieved many successes. Underlying this success, much useful information has been associated with tweets such as temporal and spatial information. For fine grained investigation of disease propagation, this information is attributed a more important role. Unlike temporal information that is always available, spatial information is less available because of privacy concerns. To extend the availability of spatial information, many geographic identification systems have been developed. However, almost no origin of the user location can be identified, even if a human reads the tweet contents. This study estimates the geographic origin of tweets with reliability using a density estimation approach. Our method reveals how the model interprets the origin of user location according to the spread of estimated density.
Sub 10 nm structures on silicon by thermal dewetting of platinum.
Venue: Nanotechnology
Year: 2010

A study of the dewetting behavior of platinum thin films on silicon was carried out to determine how variation of dewetting parameters affects the evolution of film morphology and to pinpoint which parameters yielded the smallest, most circular features. Platinum film thickness as well as dewetting time and temperature were varied and the film morphology characterized by means of scanning electron microscopy (SEM) analysis. Two different pathways of dewetting predicted in the literature (Vrij 1966 Discuss.   Mater. 2 59 63) were observed. Depending on the initial criteria, restructuring of the film occurred via hole or droplet formation. With increased annealing time, a transition from an intermediate network structure to separated islands occurred. In addition, the formation of multilayered films, silicide crystals and nanowires occurred for certain parameters. Nevertheless, the dewetting behavior witnessed could be related to physical processes. Droplets with a mean diameter of 9 nm were formed by using a 1.5 nm thick platinum film annealed at 800 degC for 30 s. To demonstrate the suitability of the annealed films for further processing, we then used the dewetted films as masks for reactive ion etching to transfer the pattern into the silicon substrate, forming tapered nanopillars.
Material Flow Cost Accounting System for Decision Making: The Case of Taiwan SME in the Metal Processing Industry
Year: 2015

The purpose of this paper is to examine the implementation of a Material Flow Cost Accounting system (MFCA) and to provide meaningful results for managers to make decision. A case study and the depth interview were employed for small and medium size enterprises in the metal processing industry to collect the information for further analysis. The result shows that the implementation of the Material Flow Cost Accounting system can mitigate the probability of dysfunctional decision making, particularly for investment decisions, assist managers in directly filtering out energy or material waste, and enhance the accuracy of product cost evaluations. This paper concludes that the Material Flow Cost Accounting system is not only a management tool, which helps managers achieve cost reductions, but also a mechanism, which realize corporate social responsibility. The results of this investigation support the proposition that implementation of environmental collaboration and monitoring practices by supply chain partners are both environmentally necessary and good business. The paper provides manufacturing managers with a structured approach to improving both environmental and organizational performance through environmental collaboration and monitoring with customers and suppliers
What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture?
Year: 2018

Remote sensing from unmanned aircraft systems (UAS) was expected to be an important new technology to assist farmers with precision agriculture, especially crop nutrient management. There are three advantages using UAS platforms compared to manned aircraft platforms with the same sensor for precision agriculture: (1) smaller ground sample distances, (2) incident light sensors for image calibration, and (3) canopy height models created from structure from motion point clouds. These developments hold promise for future data products. In order to better match vendor capabilities with farmer requirements, we classify applications into three general niches: (1) scouting for problems, (2) monitoring to prevent yield losses, and (3) planning crop management operations. The three different niches have different requirements for sensor calibration and have different costs of operation. Planning crop management operations may have the most environmental and economic benefits. However, a USDA Economic Research Report showed that only about 20% of farmers in the USA have adopted variable rate applicators; so, most farmers in the USA may not have the technology to benefit from management plans. In the near term, monitoring to prevent yield losses from weeds, insects, and diseases may provide the most economic and environmental benefits, but the costs for data acquisition need to be reduced.
Medical Image Fusion With Parameter Adaptive Pulse Coupled Neural Network in Nonsubsampled Shearlet Transform Domain
Venue: IEEE Transactions on Instrumentation and Measurement
Year: 2019

As an effective way to integrate the information contained in multiple medical images with different modalities, medical image fusion has emerged as a powerful technique in various clinical applications such as disease diagnosis and treatment planning. In this paper, a new multimodal medical image fusion method in nonsubsampled shearlet transform (NSST) domain is proposed. In the proposed method, the NSST decomposition is first performed on the source images to obtain their multiscale and multidirection representations. The high frequency bands are fused by a parameter adaptive pulse coupled neural network (PA PCNN) model, in which all the PCNN parameters can be adaptively estimated by the input band. The low frequency bands are merged by a novel strategy that simultaneously addresses two crucial issues in medical image fusion, namely, energy preservation and detail extraction. Finally, the fused image is reconstructed by performing inverse NSST on the fused high frequency and low frequency bands. The effectiveness of the proposed method is verified by four different categories of medical image fusion problems [computed tomography (CT) and magnetic resonance (MR) MR T1 and MR T2, MR and positron emission tomography, and MR and single photon emission CT] with more than 80 pairs of source images in total. Experimental results demonstrate that the proposed method can obtain more competitive performance in comparison to nine representative medical image fusion methods, leading to state of the art results on both visual quality and objective assessment.
Missing value imputation using unsupervised machine learning techniques
Venue: Soft Comput.
Year: 2020

In data mining, preprocessing is one of the essential processes which involves data normalization, noise removal, handling missing values, etc. This paper focuses on handling missing values using unsupervised machine learning techniques. Soft computation approaches are combined with the clustering techniques to form a novel method to handle the missing values, which help us to overcome the problems of inconsistency. Rough K means centroid based imputation method is proposed and compared with K means centroid based imputation method, fuzzy C means centroid based imputation method, K means parameter based imputation method, fuzzy C means parameter based imputation method, and rough K means parameter based imputation methods. The experimental analysis is carried out on four benchmark datasets, viz. Dermatology, Pima, Wisconsin, and Yeast datasets, which have taken from UCI data repository. The proposed method proves the efficacy of different datasets, and the results are also promising one.
The Effectiveness of Positive Thinking Skills on Academic Procrastination of High School Female Students Kermanshah City
Year: 2017

Positive psychology interventions with focus on strengths of individual, is one of the new approaches in helping people due to develop their ability and emits .the aim of this study was to determine the effectiveness of positive thinking skills on academic procrastination of high school female students.  Research type was semi experimental, pretest posttest design with control group. Population was all female high school students in 3 section education organization Kermanshah city, 2014 2015. The research sample included 120 female from 22 Bahman high school students who were selected through multistage random cluster sampling method and then based on entrance and existence criteria assigned into two groups (experimental and control) randomly. The instruments used were academic procrastination Scale (validity 0.65 reliability 0.83) The positive thinking skills intervention included 8 sessions, each 90 minutes, twice in week for experimental group. Because of effectiveness these interventions sessions were applied for control groups after posttest. Data analyzed with analysis of covariance using spss 21.  The results showed that positive thinking skills is effective on academic procrastination of high school female students (P 0.001) Conclusions Regarding the divergences between two groups' positive skills training scan be effective in reducing procrastination. Findings indicated the necessity of applying positive thinking program training in schools due to reducing academic procrastination and increasing success and progress of their academic performance in students.
Permutation Entropy and Irreversibility in Gait Kinematic Time Series from Patients with Mild Cognitive Decline and Early Alzheimer's Dementia
Venue: Entropy
Year: 2019

Gait is a basic cognitive purposeful action that has been shown to be altered in late stages of neurodegenerative dementias. Nevertheless, alterations are less clear in mild forms of dementia, and the potential use of gait analysis as a biomarker of initial cognitive decline has hitherto mostly been neglected. Herein, we report the results of a study of gait kinematic time series for two groups of patients (mild cognitive impairment and mild Alzheimer's disease) and a group of matched control subjects. Two metrics based on permutation patterns are considered, respectively measuring the complexity and irreversibility of the time series. Results indicate that kinematic disorganisation is present in early phases of cognitive impairment; in addition, they depict a rich scenario, in which some joint movements display an increased complexity and irreversibility, while others a marked decrease. Beyond their potential use as biomarkers, complexity and irreversibility metrics can open a new door to the understanding of the role of the nervous system in gait, as well as its adaptation and compensatory mechanisms.
La mise en oeuvre des resolutions du Conseil de Securite des Nations Unies par l' Union Europeenne
Year: 2011

L'Union europeenne n'est pas en tant que telle membre des Nations Unies. Afin de traiter la maniere dont elle met en oeuvre les resolutions du Conseil de securite des Nations Unies, il convient de s'interesser au rapport que le droit international entretient avec le droit communautaire. L'analyse porte notamment sur la personnalite juridique internationale de l'Union europeenne, l'engagement de sa responsabilite internationale et sur l'implication de la structure en piliers de l'Union europeenne. A travers les particularites du pilier PESC et du pilier relatif a la cooperation policiere et judiciaire en matiere penale (CPJP) il convient d'identifier les apports des differents traites jusqu'a l'adoption du traite de Lisbonne. Les consequences liees a une articulation sur trois niveaux de la relation UE/ONU sont egalement mises en avant. Il s'agit ainsi d'evoquer les effets d'une mise en oeuvre s'operant au niveau de l'ONU, ou sont decidees les mesures a mettre en place, au niveau communautaire, ou certaines initiatives sont entreprises des l'origine de la construction europeenne, et au niveau des Etats membres de l'Union, destinataires directs des decisions prises par le Conseil de securite. L'essor de la lutte contre le terrorisme et l'emergence de mesures relatives a la gestion des crises (dans ses composantes civile et militaire) permettent de delimiter les contours de la relation entre l'Union europeenne et l'organisation internationale, dont l'etude necessite une mise en perspective sous le prisme des droits fondamentaux, au regard de la jurisprudence de la CJUE et de la CEDH notamment.
The predictive role of nursing students' individual characteristics and psychological resilience in psychological distress.
Venue: Perspectives in psychiatric care
Year: 2021

This study aims to determine the predictive role of nursing students' individual characteristics and psychological resilience in psychological distress.  This study is a descriptive cross sectional study. The study sample included 652 nursing students. Binary logistic regression analysis was used for analysis.  It has been determined that 65.3% of nursing students have psychological distress. Having a chronic disease, being a woman, poor academic success, choosing the profession so as not to be unemployed, being single and low psychological resilience are factors that affect psychological distress.  It is recommended to screen nursing students for psychological distress to increase interventions that improve the psychological resilience of risky students.
Afforestation in China cools local land surface temperature
Venue: Proceedings of the National Academy of Sciences
Year: 2014

China has the largest afforested area in the world. Afforestation not only contributes to increased carbon storage but also alters local albedo and turbulent energy fluxes, which offers feedback on the local and regional climate. This study presents previously unidentified observational evidence of the effect of large scale afforestation on land surface temperature (LST) in China. Afforestation decreases daytime LST, because of enhanced evapotranspiration, and increases nighttime LST. This nighttime warming tends to offset daytime cooling in dry regions. These results suggest it is necessary to carefully consider where to plant trees to achieve potential climatic benefits in future afforestation projects. China has the largest afforested area in the world ~62 million hectares in 2008) and these forests are carbon sinks. The climatic effect of these new forests depends on how radiant and turbulent energy fluxes over these plantations modify surface temperature. For instance, a lower albedo may cause warming, which negates the climatic benefits of carbon sequestration. Here, we used satellite measurements of land surface temperature (LST) from planted forests and adjacent grasslands or croplands in China to understand how afforestation affects LST. Afforestation is found to decrease daytime LST by about 1.1 0.5 degC (mean 1 SD) and to increase nighttime LST by about 0.2 0.5 degC, on average. The observed daytime cooling is a result of increased evapotranspiration. The nighttime warming is found to increase with latitude and decrease with average rainfall. Afforestation in dry regions therefore leads to net warming, as daytime cooling is offset by nighttime warming. Thus, it is necessary to carefully consider where to plant trees to realize potential climatic benefits in future afforestation projects.
NIILISMO EM COME AND GO: DA PECA TEATRAL DE BECKETT A ADAPTACAO FILMICA DE JOHN CROWLEYIS
Year: 2014

John Crowleyis (1969) e diretor de televisao, teatro e cinema irlandes e fez parte do projeto intitulado Beckett on film, que consistiu na transposicao de todas as dezenove pecas teatrais do aclamado dramaturgo, novelista, poeta e diretor Samuel Beckett (1906 1989) para um outro sistema de signos, o do cinema. Diversos diretores foram convidados e, no ano de 2000, a adaptacao da peca teatral Come and go (1965) ficou por conta de Crowleyis. Trata se de tres mulheres de idades nao especificadas que se encontram e recordam sobre seu tempo de escola. O habito, o silencio e o nada, assim como em outras obras de Beckett, preenchem o tempo mais que as palavras das tres mulheres. A rotina e o tedio em que as tres se encontram podem ser interpretados como uma especie de alegoria do curto periodo de vida e do ritual de morte constante nas relacoes humanas (nascer, reproduzir e morrer) Para Beckett, o primeiro e o ultimo ponto sao os que mais importam (nascer e morrer) de modo que ser alguem bem sucedido ou um grande fracassado no percurso da vida pouco interessa, ja que todo ser humano tem o mesmo fim a morte. Tais aspectos estao presentes no cenario, no figurino das personagens e, inclusive, em suas falas ou na falta destas. Este trabalho tem o intuito de investigar, de forma introdutoria, como o conceito de Niilismo se configura na traducao interartes de Come and go (2000) Como embasamento teorico serao utilizadas, principalmente, as ideias do niilismo nietzschiano e as consideracoes de John Calder em seu livro The Philosophy of Samuel Beckett (2002)
Bare Naked Ladies (and Gentlemen) Analyzing Protection of Nude Protesting under the First Amendment and State Constitutions
Year: 2014

"The main hang up in the world today is hypocrisy and insecurity. If people can't face up to the fact of other people being naked or smoking pot, or whatever they want to do, then we're never going to get anywhere. People have got to become aware that it's none of their business and that being nude is not obscene. Being ourselves is what's important. If everyone practiced being themselves instead of pretending to be what they aren't, there would be peace."
The Application of Machine Learning Models in Company Bankruptcy Prediction
Venue: ICSEB 2019
Year: 2019

With the economy increasing, the number of enterprises increases gradually, and it is accompanied by the growth in quantity of bankruptcies.Therefore, predict bankruptcy is becoming more andmore important. It could not only help make the correct decision, but also reduce losses. There are several traditional methods are commonly used to predict the corporate bankruptcy conditions. But the traditional methods for bankruptcy prediction are mainly based on human subjective judgment and lack quantitative analysis. So it is for traditional methods to compete with the new and advanced Machine learning algorithms. Machine learning algorithms explore patterns based on objective data analysis, which develop rapidly and have strong learning ability. So we're going to apply machine learning to the prediction of corporate bankruptcy. We use data on the bankruptcy situation of Polish companies in 2007 2013 and construct a model by SVM and random forest algorithm separately. And then, we further use weighted methods to solve the problem of sample imbalance. According to the research, Random forest performs better than SVM in company bankruptcy prediction with accuracy higher than 70% in different years.
Robust Question Answering System
Year: 2021

Pretrained models like BERT achieves good performance when we fine tune it to resourceful QA tasks like SQuAD. However, when we apply the model to out ofdomain QA tasks with different question and passage sources, the performance degraded badly. We discovered that the domain change in passage source is the main contributor to worse performance. We investigated ways to improve robustness of pretrained QA systems by experimenting on different optimizers, freezing and re initializing model layers during training. We found that AdamW is the best optimizer for training on out of domain QA datasets, and freezing just the embedding block of DistilBERT improves model performance the most. 1 Key Information to include External collaborators (if you have any) NA External mentor (if you have any) NA Sharing project: NA
Structural and Functional Changes in the Coupling of Fascial Tissue, Skeletal Muscle, and Nerves During Aging
Venue: Frontiers in Physiology
Year: 2020

Aging is a one way process associated with profound structural and functional changes in the organism. Indeed, the neuromuscular system undergoes a wide remodeling, which involves muscles, fascia, and the central and peripheral nervous systems. As a result, intrinsic features of tissues, as well as their functional and structural coupling, are affected and a decline in overall physical performance occurs. Evidence from the scientific literature demonstrates that senescence is associated with increased stiffness and reduced elasticity of fascia, as well as loss of skeletal muscle mass, strength, and regenerative potential. The interaction between muscular and fascial structures is also weakened. As for the nervous system, aging leads to motor cortex atrophy, reduced motor cortical excitability, and plasticity, thus leading to accumulation of denervated muscle fibers. As a result, the magnitude of force generated by the neuromuscular apparatus, its transmission along the myofascial chain, joint mobility, and movement coordination are impaired. In this review, we summarize the evidence about the deleterious effect of aging on skeletal muscle, fascial tissue, and the nervous system. In particular, we address the structural and functional changes occurring within and between these tissues and discuss the effect of inflammation in aging. From the clinical perspective, this article outlines promising approaches for analyzing the composition and the viscoelastic properties of skeletal muscle, such as ultrasonography and elastography, which could be applied for a better understanding of musculoskeletal modifications occurring with aging. Moreover, we describe the use of tissue manipulation techniques, such as massage, traction, mobilization as well as acupuncture, dry needling, and nerve block, to enhance fascial repair.