nils-herrmann/clean_scirepeval huggingface dataset:
SRDANet: An Efficient Deep Learning Algorithm for Face Analysis
Venue: ICIRA
Year: 2015

In this work, we take advantage of the superiority of Spectral Graph Theory in classification application and propose a novel deep learning framework for face analysis which is called Spectral Regression Discriminant Analysis Network SRDANet. Our SRDANet model shares the same basic architecture of Convolutional Neural Network CNN, which comprises three basic components: convolutional filter layer, nonlinear processing layer and feature pooling layer. While it is different from traditional deep learning network that in our convolutional layer, we extract the leading eigenvectors from patches in facial image which are used as filter kernels instead of randomly initializing kernels and update them by stochastic gradient descent SGD. And the output of all cascaded convolutional filter layers is used as the input of nonlinear processing layer. In the following nonlinear processing layer, we use hashing method for nonlinear processing. In feature pooling layer, the block based histograms are employed to pooling output features instead of max pooling technique. At last, the output of feature pooling layer is considered as one final feature output of our model. Different from the previous single task research for face analysis, our proposed approach demonstrates an excellent performance in face recognition and expression recognition with 2D/3D facial images simultaneously. Extensive experiments conducted on many different face analysis databases demonstrate the efficiency of our proposed SRDANet model. Databases such as Extended Yale B, PIE, ORL are used for 2D face recognition, FRGC v2 is used for 3D face recognition and BU 3DFE is used for 3D expression recognition.
Progression of erectile function in men with chronic obstructive pulmonary disease: a cohort study
Venue: BMC Pulmonary Medicine
Year: 2019

Although sexual function is a quality of life aspect that is markedly affected in males with chronic obstructive pulmonary disease (COPD) this topic has not attracted much attention and research on this matter is lacking. In this study, we investigated longitudinal changes in the erectile function of men with COPD in order to identify latent groups and influencing factors. A total of 185 men with COPD from the Korean Obstructive Lung Disease study, which was conducted from 2005 to 2013, were analyzed in this study. Data on their erectile function, based on the International Index of Erectile Function 5, were collected over a period of 4 years. Growth mixture modeling and logistic regression analysis were used to determine the factors predicting distinct erectile function changes over time. Overall, subjects' erectile function slightly improved in the first year and then gradually worsened over time. Using growth mixture modeling, we identified four distinct latent groups, which we labeled as follows: "consistently maintained normal erectile function" (9.7% "rapidly worsened and then rapidly improved" (9.2% "gradually improved in the early stage and then gradually worsened" (36.8% and "consistently maintained poor erectile function" (44.3% Progression of erectile function was significantly associated with age, economic status, and self rated health status. This suggests that comprehensive patient care involving the management of COPD as well as erectile dysfunction in patients with chronic respiratory disease is important from a prophylactic perspective and should be developed in accordance with the characteristics of the disease process.
A Survey of Transfer Learning for Convolutional Neural Networks
Venue: 2019 32nd SIBGRAPI Conference on Graphics, Patterns and Images Tutorials (SIBGRAPI T)
Year: 2019

Transfer learning is an emerging topic that may drive the success of machine learning in research and industry. The lack of data on specific tasks is one of the main reasons to use it, since collecting and labeling data can be very expensive and can take time, and recent concerns with privacy make difficult to use real data from users. The use of transfer learning helps to fast prototype new machine learning models using pre trained models from a source task since training on millions of images can take time and requires expensive GPUs. In this survey, we review the concepts and definitions related to transfer learning and we list the different terms used in the literature. We bring the point of view from different authors of prior surveys, adding some more recent findings in order to give a clear vision of directions for future work in this field of research.
Impedance Control in the Rehabilitation Robotics
Year: 2017

Physical interactions between patients and therapists during rehabilitation have served as motivation for the design of rehabilitation robots, yet there is a lack in fundamental understanding of the principles governing such human human interactions. Review of the literature posed important open questions regarding sensorimotor interaction during human human interactions that could facilitate the design of human robot interactions and haptic interfaces for rehabilitation. The goal is to use the leading principles of the human human interaction in order to define a way in which people could be in contact with robots in a more intuitive and biologically inspired way. The proposed hybrid impedance control solves the robot environment contact problem and offers a possible solution for the rehabilitation robot interaction problem.
Um estudo sobre o uso de praticas e cenarios aplicados na formacao do Engenheiro de Producao
Year: 2017

Trata se de estudo sobre a importancia de atividades praticas para o desenvolvimento de competencias e habilidades de alunos do curso de Engenharia da Producao. Foi motivado pela experiencia de alunas que tiveram a iniciativa de buscarem essa pratica e perceberam sua importancia. O objetivo do artigo e investigar em que medida a pratica no mercado de trabalho, durante a graduacao, contribui para o desenvolvimento de habilidades e competencias do Engenheiro de Producao e a percepcao de estudantes e egressos sobre isso. Neste sentido, apresenta o perfil do curso em estudo e o resultado de pesquisa de campo junto a graduandos e egressos que ja atuam no mercado, atraves de levantamento por inquerito, com aplicacao de questionarios e entrevistas. A pesquisa foi embasada por abordagem quantitativa e qualitativa. Constata se que a maioria dos estudantes entrevistados considera a vivencia no mercado essencial para embasar a sua formacao e capacidade de apropriacao e producao do conhecimento. Conclui se que a vivencia e fundamental para a construcao de um curriculo mais coerente com a realidade do mercado de trabalho, o que deve ser propiciado pela instituicao de ensino, mas que o aluno deve ter proatividade e iniciativa para as acoes necessarias ao seu processo de aprendizagem.  as novas tecnologias produtivas: industria 4.0, manufatura aditiva e outras abordagens avancadas de producao"
Identification of Functional Elements and Regulatory Circuits by Drosophila modENCODE
Venue: Science
Year: 2010

From Genome to Regulatory Networks For biologists, having a genome in hand is only the beginning much more investigation is still needed to characterize how the genome is used to help to produce a functional organism (see the Perspective by Blaxter) In this vein, Gerstein et al. (p. 1775) summarize for the Caenorhabditis elegans genome, and The modENCODE Consortium (p. 1787) summarize for the Drosophila melanogaster genome, full transcriptome analyses over developmental stages, genome wide identification of transcription factor binding sites, and high resolution maps of chromatin organization. Both studies identified regions of the nematode and fly genomes that show highly occupied targets (or HOT) regions where DNA was bound by more than 15 of the transcription factors analyzed and the expression of related genes were characterized. Overall, the studies provide insights into the organization, structure, and function of the two genomes and provide basic information needed to guide and correlate both focused and genome wide studies. The Drosophila modENCODE project demonstrates the functional regulatory network of flies. To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage and tissue specific regulators, and enables gene expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.
Mobile banking adoption: A literature review
Venue: Telematics Informatics
Year: 2015

Electronic commerce (e commerce) continues to have a profound impact on the global business environment, but technologies and applications also have begun to focus more on mobile computing, the wireless Web, and mobile commerce. Against this backdrop, mobile banking (m banking) has emerged as an important distribution channel, with considerable research devoted to its adoption. However, this research stream has lacked a clear roadmap or agenda. Therefore, the present article analyzes and synthesizes existing studies of m banking adoption and maps the major theories that researchers have used to predict consumer intentions to adopt it. The findings indicate that the m banking adoption literature is fragmented, though it commonly relies on the technology acceptance model and its modifications, revealing that compatibility (with lifestyle and device) perceived usefulness, and attitude are the most significant drivers of intentions to adopt m banking services in developed and developing countries. Moreover, the extant literature appears limited by its narrow focus on SMS banking in developing countries; virtually no studies address the use of m banking applications via smartphones or tablets or consider the consequences of such usage. This study makes several recommendations for continued research in the area of mobile banking.
Emission reduction effect and carbon market efficiency of carbon emissions trading policy in China
Year: 2020

China has implemented its carbon emission trading system (ETS) in seven pilots since 2013. Many methods have been used to evaluate the effect and efficiency of the ETS in reducing carbon emissions. Evaluating the carbon ETS to determine whether it has co benefited the economy and environment in the seven pilots is crucial for the development of China. Moreover, different methods of measurement reveal different results on how efficient the seven carbon emission trading markets (ETMs) are. We use the difference in differences (DID) method to evaluate the impact of carbon emissions and economic growth following ETS implementation. Based on the data of industrial carbon emissions in 30 provinces of China from 2008 to 2016, the impact of ETS on the carbon emission reduction and economic growth of enterprises is empirically tested. Data envelopment analysis (DEA) evaluates the operating efficiency of the carbon ETMs. Based on the seven carbon emission trading pilots conducted in China in 2014 2016, the carbon ETMs differentiation system in the pilot area is taken as the input index and the ETS implementation effect is used as the output index to construct the full DEA evaluation model for gauging the operation efficiency of the carbon ETMs. The results show that the implementation of the carbon trading policy increases the economic dividend (13.6% generated by the gross industrial output value, but significantly reduces the emission (24.2% of industrial CO2 in all seven carbon emission trading pilots. The average DEA efficiency of the seven carbon ETMs operations in China have increased annually.
Waste bread recycling as a baking ingredient by tailored lactic acid fermentation.
Venue: International journal of food microbiology
Year: 2020

Food grade waste and side streams should be strictly kept in food use in order to achieve sustainable food systems. At present, the baking industry creates food grade waste as excess and deformed products that are mainly utilized for non food uses, such as bioethanol production. The purpose of this study was therefore to explore the potential of waste wheat bread recycling for fresh wheat bread production. Waste bread recycling was assessed without further processing or after tailored fermentation with lactic acid bacteria producing either dextran or b glucan exopolysaccharides. When non treated waste bread slurry was added to new bread dough, bread quality (specific volume and softness) decreased with increasing content of waste bread addition. In situ EPS production (dextran and microbial b glucan) significantly increased waste bread slurry viscosity and yielded residual fructose or glucose that could effectively replace the sugar added for yeast leavening. Furthermore, fermentation acidified waste bread matrix, thus improving the hygienic safety of the process. Bread containing dextran synthesized in situ by Weissella confusa A16 showed good technological quality. The produced dextran compensated the adverse effect of recycled bread on new bread quality attributes by 12% increase in bread specific volume and 37% decrease in crumb hardness. In this study, a positive technological outcome of the bread containing microbial b glucan was not detected. The waste bread fermented by W. confusa A16 containing dextran appears to enable safe bread recycling with low acidity and minimal quality loss.
An Efficient Method for Brain Tumor Detection Using Texture Features and SVM Classifier in MR Images
Venue: Asian Pacific journal of cancer prevention APJCP
Year: 2018

Detection and classification of abnormalities in Magnetic Resonance (MR) brain images in medical field is very much needed. The proposed brain tumor classification system composed of denoising, feature extraction and classification. Noise is one of the major problems in the medical image and due to that retrieval of useful information from the image is difficult. The proposed method for denoising an image is PURE LET transform.  This method preserves the diagnostic property of the images. In feature extraction, combination of Modified Multi Texton Histogram (MMTH) and Multi Texton Microstructure Descriptor (MTMD) is used and then Gray Level Co occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRLM)are used to extract the feature from the image to compare performance. In classification, classifiers like Support Vector Machine (SVM) K Nearest Neighbors (KNN) and Extreme Learning Machine (ELM)are trained by the extracted features and are used to classify the images.  The performance of feature extraction methods with three different classifiers are compared in terms of the performance metrics like sensitivity, specificity, and accuracy.  The result shows that the combination of MMTH and MTMD with SVM shows the highest accuracy of 95%
Variante rs628031 en el gen SLC22A1 y su asociacion con sindrome metabolico en mujeres guerrerenses
Venue: Revista de Ciencias de la Salud
Year: 2019

The metabolic syndrome (MS) is a set of metabolic abnormalities increasing the risk of developing diabetes and caridaca coronary disease. The SLC22A1 gene among different population groups, related to carnitine metabolism and acylcarnitine plasma levels associated with metabolic diseases.  To evaluate the rs rs628031 variant in the SLC22A1 gene and its relationship with the metabolic syndrome in women from the state of Guerrero.  A cross sectional study was conducted in 438 patients. Anthropometric and biochemical measurements were made. The rapid nonenzymatic technique was used for DNA extraction from leukocytes isolated from peripheral blood for genotyping PCR, using TaqMan probes.  a relationship between rs628031 polymorphism and serum total cholesterol proteins was identified in the carriers of the A A variant with respect to the carriers of the G G and G A variant (p 0.0015) in addition to LDL cholesterole. in carriers of the A A variant compared to the other genotypes (p 0.0007)
Optimizing AI Pipelines: A Game Theoretic Cultural Algorithms Approach
Venue: 2018 IEEE Congress on Evolutionary Computation (CEC)
Year: 2018

The structure of contemporary AI applications in complex automation domains, such as robotics and autonomous driving, is multi staged and hierarchical. The overall pipeline consists of perception, planning, and actuation subsystems. Each of these in turn, consists of staged processing. Such systems consume raw sensor data, and process it to respond intelligently to their surroundings, in the pursuit of assigned goals. Further, such systems use a variety of techniques including signal processing, computer vision, machine learning and 'traditional' AI methods (e.g. rules engine, planning, and scheduling, etc. There may be complex inter and intra pipeline interactions that are governed by 100's of tunable parameters, yielding a highly complex system. Optimizing the system level performance of such complexly interacting subcomponents, is a major challenge for the industry. This paper attempts to address such a challenge with the application of a knowledge intensive evolutionary optimization framework Cultural Algorithms. A key component of Cultural Algorithms which are modeled after problem solving processes in social networks is the mechanism for distributing knowledge in the population network. Here a new, game theoretic knowledge distribution mechanism is devised which supports both cooperation and competition between players. The performance of this new mechanism is compared against the de facto Weighted Majority Win, purely competitive mechanism on a real world, computer vision based AI pipeline that supports of autonomous driving. The preliminary results suggest that a game the oretic approach is better at combining the workflow stages of the pipeline so as to improve driving behavior than the traditional competition based approach.
All India AYUSH post graduate entrance exam 2019 AYURVEDA MCQ item analysis
Venue: Journal of Ayurveda and integrative medicine
Year: 2021

AIAPGET 2019, an all India ranking entrance Test for MD/MS courses of Ayurveda, Unani, Siddha and Homeopathy stream was conducted by joint collaboration of National Testing Agency (NTA) and All India Institute of Ayurveda (AIIA) In this article, we present the item analysis of AIAPGET 2019 Ayurveda stream MCQs.  The aim of this article was to analyse the MCQs of AIAPGET 2019 of Ayurveda stream.  This exam was computer based conducted all over 25 centers across India. The question paper had 100 MCQs with 1 correct answer and 3 distractors for each item (Problem statement)  AIAPGET 2019 question paper of Ayurveda stream had a Difficulty index of 37.32 16.11 Discriminatory Index of 0.46 0.27 and Distractor Index of 89 17.8.  Our analysis showed that though ideal, the question paper trended towards difficulty side.
Polymers Based on Methacrylate Bearing Coumarin Side Group: Synthesis via Free Radical Polymerization, Monomer Reactivity Ratios, Dielectric Behavior, and Thermal Stabilities
Year: 2012

Copolymerization and homopolymerization of 7 methacryloyloxy coumarin (MAOC) and its copolymers with benzyl methacrylate (BMA) methyl methacrylate (MMA) ethyl methacrylate (EMA) and isobuthyl methacrylate (IBMA) were performed by the free radical polymerization method (FRP) at low conversions <15% The resulting polymers were characterized by FTIR, 1H NMR, GPC, DSC, and TGA. The monomer reactivity ratios of MAOC and BMA were computed using Kelen Tudos (K T) and Fineman Ross (F R) methods and were found to be r1=0.45, r2=1.29; r1=0.46; r2=1.33, respectively (r1 is monomer reactivity ratio of MAOC) Blends of poly(MAOC) and poly(BMA) obtained via FRP method were prepared by casting films from dichloromethane solution and were characterized by DTA and TGA techniques. Dielectric measurements for MAOC homopolymer and its copolymers with EMA, MMA, and IBMA were carried out by means of an impedance analyzer as a function of temperature and frequence. Dielectric properties of polymer samples prepared in a plate form were measured at room temperature over the frequency range 0.1 kHz 2 MHz and given as compared with each other.
Vehicle to Vehicle (V2V) Communication using Routing Protocols: A Review
Venue: 2019 International Conference on Smart Structures and Systems (ICSSS)
Year: 2019

The subclass of Mobile Ad hoc Network (MANET) which is an intelligent technology which provides with an efficient way to communicate, manage traffic on road and secured data transmission. A VANET provides wireless communication between vehicles in a network and between road side units (RSUs) within the coverage area. It also provides an advantage of low jitter, less transmission delay, rich sets of handling mobile nodes i.e. vehicle in mobility, within the coverage area. VANET presents a wide and unique range of opportunities and challenges behind the routing protocols due to changing of dynamic network topology subjected to the constraint of road geometry and some obstacle which limit the connectivity in urban areas. VANET provides a distinguished approach to an Intelligent Transportation System (ITS) The routing protocol designing is needed for VANET and it should support smart systems, In recent years, there is a tremendous growth in number of vehicles on road which has increased the usage of communication on move. This review paper describes the different design of routing choices which helps to develop different routing algorithms for VANETs. The routing protocols related to VANETs are described and discussed under a suitable category.
Attention Detection System Based on the Variability of Heart Rate
Year: 2019

Attention is a cognitive and psychobiological variable that lacks objective measures in natural contexts of formal learning. However, it can be objectively measured from the heart autonomic activity. In the present study, the validity and reliability of a system for recording heart rate variability are demonstrated. Twelve prototypes were created and paired with standard electrocardiogram. Long segments with cardiac pulse recordings were used within ten minutes. A highly significant correlation index (p 0.01) and a significantly high Cronbach's alpha were obtained. In the variance analysis, all data analyzed presented a value of p 0.05. It is concluded that there is no significant variation between paired systems; therefore, the attention detection system based on heart rate variability is valid and reliable.
Football activism as political contention: Contextual determinants of membership in the association of supporters of Hajduk Split
Year: 2019

Where do politically activist football supporters come from? What are the social conditions under which they are successfully recruited and mobilised? This article answers those questions by analysing a unique dataset of more than 43,000 members of Our Hajduk the association of supporters of the Croatian club Hajduk Split as well as a host of data on the communities they live in. The analysis shows that Our Hajduk thrives in exactly the same areas where most other social, civil and political organisations thrive: among the more educated and more socio economically successful. Most importantly, the analysis shows that the pattern of Our Hajduk membership closely follows the patterns of political affiliation and participation in Croatia's electoral arena and is guided by the opposition to political players who have dominated Croatian football and turned it into a social field marked by corruption and mismanagement.