bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alcohol y juventud ¿existen diferencias en consumo de hombres y mujeres según edad de inicio?
Authors: Giménez-García Cristina , Ruiz-Palomino Estefanía , Gil-Juliá Beatriz , García-Nebot Juan Enrique , Ballester-Arnal Rafael 
Published: April 2018

En la adolescencia, el consumo de alcohol supone uno de los problemas de salud más acuciantes. Sin embargo, tanto los adolescentes como la sociedad, muestran una baja percepción de gravedad. En este contexto, la edad de inicio podría establecer diferencias en los patrones de consumo, facilitando su consolidación. Por ello, se analiza si existen diferencias entre aquellas personas que iniciaron su consumo antes y después de los 14 años, en cuanto a la frecuencia de consumo, los beneficios percibidos y los problemas ocasionados. Con tal fin, 894 jóvenes españoles entre 18 y 22 años (33,6% hombres y 67,3% mujeres), cumplimentaron un cuestionario sobre hábitos de salud dirigido a población joven. Según los resultados, el 99,4% consume alcohol en el momento actual y más de un tercio comenzó antes de los 14 años. Los hombres iniciarían antes tanto el consumo, como las primeras borracheras (entre los 10 y 12 años), mostrando diferencias estadísticamente significativas con las mujeres, en el primer caso (Chi2=15,66; p≤,008). En líneas generales, tanto en hombres como en mujeres, se observa cómo las personas que iniciaron el consumo antes de los 14 años, muestran una mayor frecuencia en el mismo. En algunos casos, como en la ingesta diaria de cerveza, llegan a doblar el consumo de los que lo iniciaron después. Además, reportan en mayor medida haber sufrido consecuencias negativas por el alcohol, así como percibir beneficios relacionados con su consumo como sentirse más seguros, conocer más fácilmente a personas, sentir euforia o combatir el aburrimiento con más facilidad. Así pues, los resultados apoyan una mayor exposición al riesgo, conductual y actitudinal, entre aquellas personas que comenzaron antes el consumo. De esta forma, se vuelve a poner de manifiesto la importancia de retrasar el consumo del alcohol y, en consecuencia, de gestionar planes preventivos dirigidos a edades más tempranas.
Nuevos retos en la eduación. El impulso de metodologías alternativas aprendizaje-servicio y mentoría
Authors: Hervás Torres Mirian , Polo Sánchez M.Tamara , Fernández Jiménez Carolina , Fernández Cabezas María , Tallón Rosales Susana 
Published: April 2018

La Educación Superior se enfrenta al desafío de mejorar la productividad y competitividad del alumnado, además de revisar cuál es su función social. Para la mejorar la calidad de la educación y ser más competentes en la sociedad lleva asociado potenciar las metodologías docentes alternativas que permiten conectar el currículum con la realidad, caso del Aprendizaje-Servicio y la mentoría. En esta línea, el objetivo de este trabajo fue explorar la eficacia del Programa Huelva Educa para mejorar la motivación, estrategias de aprendizaje, y habilidades sociales de los mentores participantes y rendimiento escolar y clima escolar de los “mentees”. La muestra estuvo compuesta por 79 estudiantes de la Universidad de Huelva, y 69 alumnos de educación obligatoria seleccionados a través de un muestreo no probabilístico de conveniencia. Los resultados muestran que el alumnado universitario, tras su participación, mejora en comportamientos relacionados con estrategias de aprendizaje (p.e., tiempo y ambiente de estudio, autorregulación metacognitiva o regulación del esfuerzo), y el alumnado de educación obligatoria ha incrementado la cantidad y calidad de sus interacciones, así como tendencias de mejora en el rendimiento escolar. Estos resultados, sugieren la necesidad de implantar de este tipo de programas basados en metodologías alternativas dentro del proceso de cambio que está sufriendo la Educación Superior.
Design and Implementation of Android-Based Autonomous Human Tracking Vehicle
Authors: ÖZARSLAN YATAK Meral , GÖKTAŞ Batuhan , DURAN Fecir 
Published: April 2018

Design and properties of an Android-based autonomous
human tracking vehicle has been presented in this paper. It has been developed by using 3G technology
with a smartphone. Real time control of the vehicle and transfer of captured
image are performed by connecting the smartphone on the vehicle to the user’s
smartphone. The aim of this paper is the design and implementation of a
solution for supplying autonomous human tracking for especially using in
unmanned ground vehicle cost effectively, user friendly and real time. Object
tracking was implemented with OpenCV (Open Source Computer Vision) library,
introduced to the develop software on the vehicle. The vehicle tracks human
autonomously when track button is switched on. It is controlled remotely by the
user. A compact and cost effective system has been realized by XMPP protocol
and using minimum hardware. In addition, unnecessary power consumption was
prevented through the developed software with the accelerometer by detecting
the vehicle condition. Performance tests have been done on command and image
transmission. The commanded autonomous transmission for the control process and
real time image transmission can be achieved in short time
as 240 ms and 158 ms, respectively.
Makine Öğrenmesi ve Öznitelik Seçim Yöntemleriyle Saldırı Tespiti
Authors: KAYNAR Oğuz , ARSLAN Halil , GÖRMEZ Yasin , IŞIK Yunus Emre 
Published: April 2018

Bilgisayar
ve internetin, günlük yaşamın vazgeçilmez bir unsuru haline gelmesi ile
birlikte internet sitelerinin ve web tabanlı uygulamaların sayısı da hızla
artmıştır. Bilgi, fikir, para gibi birçok önemli unsurun internet siteleri ve
uygulamalar aracılığıyla paylaşımının yapılması ise bilgi güvenliği konusunu
önemli ve güncel bir hale getirmiştir. Günümüze kadar güvenlik duvarı, virüs
programları gibi yazılımlar bilgisayar ve sistem güvenliği için kullanılmış
ancak yeterli olmamıştır. Bu nedenle mevcut yazılımlara alternatif olarak
ortaya atılan saldırı tespit sistemleri ile anormal davranışlar tespit edilerek
olası tehlikelerin çözümlenmesi amaçlanmıştır. Bu çalışmada ise saldırı tespit
sistemleri için üretilen KDDCup99 veri seti üzerinde ki kare, bilgi kazancı,
kazanım oranı, gini katsayısı, oneR, reliefF, genetik, ileriye doğru ve geriye
doğru öznitelik seçim algoritmaları uygulanarak yeni veri setleri elde
edilmiştir. Elde edilen yeni veri setlerini, orijinal boyuttaki veri seti ile
karşılaştırmak için en yakın k komşu, destek vektör makineleri ve aşırı öğrenme
makineleri kullanılarak farklı modeller geliştirilmiştir. Çalışmada, her üç yöntem için belirtilen
öznitelik seçme yöntemleri kullanılarak test verileri için en yüksek başarıma
sahip modeler başarı oranı, hassasiyet yanlış alarm oranı, f-ölçütü gibi
çeşitli metrikler yardımıyla karşılaştırılmıştır. Yapılan analizlerin sonucunda
öznitelik seçim yöntemlerinin her üç sınıflama yöntemi içinde başarı oranını
artırdığı ve modellerin daha hızlı çalışmasını sağladığı görülmüştür. Ayrıca,
yüksek başarı oranları, diğer sınıflama yöntemlerine oranla son derece hızlı
olması, eğitim algoritmasının basit
olması gibi nedenlerden dolayı aşırı öğrenme makinalarının çevrimiçi saldırı
tespit sistemlerine rahatlıkla entegre edilebileceğini ve alternatif bir yöntem
olarak kullanılabileceğini göstermiştir.
Classification of PVC Beat in ECG Using Basic Temporal Features
Authors: KAYA Yasin 
Published: April 2018

Premature ventricular contraction (PVC) is
one of the most important arrhythmias among the various hearth abnormalities. Premature
depolarization of the myocardium in the ventricular region causes PVC and it is
usually associated with
structural heart conditions. Arrhythmias can be detected by examining the ECG
signal and this review requires large-size data to be examined by physicians. The
time spent by the physician in examining the signal can be reduced using CAD
systems. In this study, we propose a high performance
PVC detection system using the feature extraction and classification scheme
bringing low computational burden. The test set consisting of 81844 beats from
the MIT-BIH arrhythmia database was used for the experimental results. We
compared the performances of the various classifiers using proposed feature set
in the experiments and obtained classification accuracy of 98.71% using NN
classifier.&nbsp;
FPGA-based ANN Design for Detecting Epileptic Seizure in EEG Signal
Authors: KARAKAYA Baris , KAYA Turgay , GULTEN Arif 
Published: April 2018

This study aims to represent an FPGA (Field
Programmable Gate Array) design of Artificial Neural Network (ANN) for
Electroencephalography (EEG) signal processing in order to detect epileptic
seizure. For analyzing brain’s electrical activity, feedforward ANN model is
used for classification of EEG signals. The designed ANN output layer makes a
decision whether the person has epilepsy or not. In the proposed system, the
ANN model is programmed and simulated on Xilinx ISE editor via computer and
then, EEG signal data are transferred to FPGA-based ANN emulator core. The Core
is trained on data which are patient’s data and healthy person’s data. After
training, test data is loaded to ANN Emulator Core to detect any epileptic seizure
of person’s EEG signal. The main advantage of FPGA in the system is to improve
speed and accuracy for epileptic seizure detection.
A Review of Turkish Sentiment Analysis and Opinion Mining
Authors: KARAYİĞİT Habibe , ACI Çiğdem , AKDAĞLI Ali 
Published: April 2018

Social Media is one of the most frequently
used platforms today. Users can easily share their views, ideas, and thoughts on this platform. The data shared on social media platforms is actually a great
deal that can be transformed into meaningful information. The obtained big data
can be analyzed and evaluated by various data analysis methods. Whether or not
the data contain a feeling, if it is included; the type of the feeling (i.e.
positive, negative or neutral) can be determined by emotion analysis methods. Sentiment
Analysis studies in later times began to turn to analysis indicating different
sentiments. Thus the foundations of Opinion Mining were laid. When ideas
conveyed by social media information are presented semantically, they are
expressed by Opinion Mining. The purpose of this paper is to explain the relationship
between the concepts of Sentiment Analysis and Opinion Mining. The terms used
in Sentiment Analysis and Opinion Mining are explained and examples of Turkish Sentiment
Analysis are given. It has been tried to suggest solutions for the problems
encountered in Turkish studies.
Investigation Of Feature Selection Algorithms On A Cognitive Task Classification: A Comparison Study
Authors: ERALDEMİR Server Göksel , ARSLAN Mustafa Turan , YILDIRIM Esen 
Published: April 2018

In this study, the effects of feature selection on classification of
the electrical signals generated in the brain during numerical and verbal
operations are investigated. 18 healthy university/college students were chosen
for the experimental study. EEG signals were recorded during silent reading and
mental arithmetic operations without using any pen and paper. A total of 60
slides, 30 of which contained reading passages and the rest contained
arithmetic operations, were presented in the experiment. &nbsp;EEG signals recorded from 26 channels during
the slide show. The recorded EEG signals were analyzed by Hilbert Huang
Transform (HHT), and then features were extracted. 312 features were classified
by Bayesian Network algorithm without applying feature selection with 92.60%
average accuracy. Consistency measures and Correlation based Feature Selection
methods were, then, used for feature selection and the numbers of selected
features are 8 and 39 on average, respectively. Classification accuracies by
using these feature selection algorithms were obtained as 93.98% and 95.58%,
respectively. The results showed that feature selection algorithms contribute
positively to the classification performance.
A Distributed K Nearest Neighbor Classifier for Big Data
Authors: TULGAR Tamer , HAYDAR Ali , ERŞAN İbrahim 
Published: April 2018

The
K-Nearest Neighbor classifier is a well-known and widely applied method in data
mining applications. Nevertheless, its high computation and memory usage cost
makes the classical K-NN not feasible for today’s Big Data analysis
applications. To overcome the cost drawbacks of the known data mining methods,
several distributed environment alternatives have emerged. Among these
alternatives, Hadoop MapReduce distributed ecosystem attracted significant
attention. Recently, several K-NN based classification algorithms have been
proposed which are distributed methods tested in Hadoop environment and
suitable for emerging data analysis needs. In this work, a new distributed
Z-KNN algorithm is proposed, which improves the classification accuracy
performance of the well-known K-Nearest Neighbor (K-NN) algorithm by benefiting
from the representativeness relationship of the instances belonging to
different data classes. The proposed algorithm relies on the data class
representations derived from the Z data instances from each class, which are
the closest to the test instance. The Z-KNN algorithm was tested in a physical
Hadoop Cluster using several real-datasets belonging to different application
areas. The performance results acquired after extensive experiments are
presented in this paper and they prove that the proposed Z-KNN algorithm is a
competitive alternative to other studies recently proposed in the literature
Classification of Down Syndrome of Mice Protein Dataset on MongoDB Database
Authors: FURAT Fahriye Gemci , IBRİKCİ Turgay 
Published: April 2018

There are samples both with Down Syndrome and without
in mice protein expression data set. It is important to define the reason of
Down Syndrome treatment by means of mice protein for the same treatment seem
human being. In the present study, mice protein expression data set from UCI
repository are classified using Bayesian Network algorithm, K- Nearest
Neighbor, Decision Table, Random Forest and Support Vector Machine which are
some of classification methods.&nbsp; The classification
algorithms with 10-fold cross validation and by splitting equally as test and
train data are tested to classify on the mice protein data set. The
classification of the data set was succeeded with 94.3519% accuracy in 0.06
seconds using Bayesian
Network, with 99.2593% accuracy in 0.01 seconds using KNN, with 95.4630 % accuracy in 1.2 seconds using
Decision Table, with 100% accuracy in 0.58 seconds using Random Forest and with 100% accuracy in 1.17 seconds using SVM, with 10-fold cross validation. On the other hand, the
classification of the data set was succeeded with 95.3704% accuracy in 0.22
seconds using Bayesian
Network, with 98.3333% accuracy in 0 seconds using KNN, with 98.3333% accuracy in 0.72 seconds using
Decision Table, with 100% accuracy in 0.77 seconds using Random Forest and with 100% accuracy in 1.48 seconds using SVM, by equally train-test data partition.
Analysis of Photonic Crystal Tuned by Nematic Liquid Crystals
Authors: KARAOMERLIOGLU Filiz 
Published: April 2018

Modelling of left-handed metamaterial-based
photonic nanostructures in functional optoelectronic devices have been studied
in present paper. Two dimensional photonic crystal array on a narrow-band
semiconductor base filled with a liquid crystal was analyzed. Photonic band structure
and isofrequency contours of the nanostructures containing both inorganic and
organic components were calculated for both TE and TM modes by using the plane
wave expansion method. Silver telluride was used as a narrow-band semiconductor
and E7 type as a liquid crystal. The photonic crystal structure that is
designed as hexagonal rods shape in an air background is planned for the square
lattice.&nbsp;
Speech Emotion Classification and Recognition with different methods for Turkish Language
Authors: BAKIR Cigdem , YUZKAT Mecit 
Published: April 2018

In several
application, emotion&nbsp; recognition from
the speech signal has been research topic since many years. To determine the
emotions from the speech signal, many systems have been developed. To solve the
speaker emotion recognition problem, hybrid model is proposed to classify five
speech emotions, including&nbsp; anger,
sadness, fear, happiness and neutral. The aim this study of was to actualize
automatic voice and speech emotion recognition system using hybrid model taking
Turkish sound forms and properties into consideration.&nbsp; Approximately 3000 Turkish voice samples of
words and clauses with differing lengths have been collected from 25 males
and&nbsp; 25 females. In this study, an
authentic and unique&nbsp; Turkish&nbsp; database has been used. Features of these
voice samples have been obtained using Mel Frequency Cepstral Coefficients
(MFCC) and Mel Frequency Discrete Wavelet Coefficients (MFDWC). Moreover,
spectral features of these voice samples have been obtained&nbsp; using Support Vector Machine (SVM). Feature
vectors of the voice samples obtained have been trained with such methods as
Gauss Mixture Model( GMM), Artifical Neural Network (ANN), Dynamic Time Warping
(DTW), Hidden Markov Model (HMM) and hybrid model(GMM with combined SVM).&nbsp; This hybrid model has been carried out by
combining with SVM and GMM.&nbsp; In first
stage of this model, with SVM has been performed&nbsp; subsets obtained vector of&nbsp; spectral features. In the second&nbsp; phase, a set of training and tests have been
formed from these spectral features. In the test phase, owner of a given voice
sample has been identified taking the trained voice samples into consideration.
Results and performances of the algorithms employed in the study for
classification have been also demonstrated in a comparative manner.&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;
Spectral Ratio Method for Fault Detection in Rotating Machines
Authors: DIKUN Jelena , URMONIENE Lione , STANELYTE Daiva 
Published: April 2018

This study presents
the ratio, which is defined between two vibration signals in the spectral
domain, to be used in extracting the fault signatures from the signals. These
two signals are considered as two different cases of the electric motor of 5 HP
in terms of the faulty and healthy motor cases and hence, the comparison
between two spectral variations is used as a method to show the fault
characteristic. In this manner, the bearing damage of the electric motor of 5
HP are given within the range of 0-4 kHz and its J-curve is presented as an
indication of the motor aging.
Role of plasma asymmetric dimethylarginine levels in diagnosis and follow-up of acute pulmonary thromboembolism
Authors: BOZKURT YILMAZ Hatice Eylül , YILMAZ Mustafa , ÖNER EYÜPOĞLU Füsun 
Published: April 2018

Purpose: Nitric oxide is an important mediator that plays a major role in platelet adhesion/aggregation. Asymmetric dimethylarginine (ADMA) is a competitive inhibitor of endothelial nitric oxide synthase. In this study, we aimed to examine the ADMA levels in diagnosis and follow-up of acute pulmonary thromboembolism.Materials and Methods: The study was designed as a prospective study. Thirty consecutive patients with acute PTE and 20 healthy volunteers were enrolled into the study. Patients were followed 1 month. Plasma ADMA levels were measured on admission and following the first month.Results: Ona dmision there was statistically significant difference between two groups. When we compared serum ADMA levels difference between patients group with resolution and without resolution, there was not any statistically significant difference. There was a significant difference between serum ADMA levels of massive group and the other 2 groups.Conclusion: Plasma ADMA levels elevated in patients with pulmonary thromboembolism. This finding supports the idea ADMA levels correlated with thrombus burden.
Trinta anos da Constituição Federal e a participação popular no SUS
Authors: Kruger Tânia Regina , Oliveira Andréia 
Published: April 2018

No texto busca-se entender as bases teórico-políticas da participação em saúde, após a promulgação da Constituição Federal do Brasil de 1988, e os desafios do processo de desconstitucionalização do Sistema Único de Saúde – SUS. O artigo, de natureza descritiva, foi desenvolvido por meio de estudo bibliográfico e documental. Pretendeu-se desnaturalizar o sentido da participação popular nas políticas sociais, cunhada pelas políticas neoliberais, e debater sobre as possibilidades e limites dessa participação nos espaços institucionalizados. Focalizou-se a participação popular no SUS, nos trinta anos da Constituição, no âmbito dos Conselhos e Conferências de Saúde, visando demonstrar o potencial de interferência dessas instâncias na política pública e na reprodução da cultura política. Na conjuntura regressiva potencializada no país a partir de 2016 destacam-se as ameaças ao SUS, a desconsideração do poder governante às resistências do Conselho Nacional de Saúde e a relevância da participação popular nesse cenário.
Trabalhadores estatutários e a Empresa Brasileira de Serviços Hospitalares
Authors: Teixeira Janine Vieira , Cruz César Albenes de Mendonça , Lima Rita de Cássia Duarte 
Published: April 2018

Percepção dos trabalhadores estatutários sobre a implantação da EBSERH no HUCAMPerceptions of statutarian workers about the EBSERH’s implementation in HUCAMRESUMO A nova abordagem da gestão pública traz consequências ruins para os trabalhadores. A pesquisa teve por objetivo analisar o impacto da implantação da Empresa Brasileira de Serviços Hospitalares – EBSERH - na saúde dos trabalhadores contratados pelo Regime Jurídico Único – RJU - do Hospital Universitário Cassiano Antônio de Morais – HUCAM. O método qualitativo incluiu: entrevistas com trabalhadores e gestores, utilizando um instrumento semiestruturado; dados institucionais de atendimentos psicológicos e absenteísmo. Emergiram as categorias: Consolidação da EBSERH: Implantação, Principais Mudanças e Processo de (Des) integração; Trabalho: Processo de Trabalho, Metas Pactuadas com o SUS e Conflitos; Adoecimento no Trabalho: Insegurança, Desrespeito, Falta de Reconhecimento e Exclusão. Os trabalhadores desenvolveram diferentes estratégias de resistência: do embate, contestar, ao silêncio, só observar. Eles não conseguiram desenvolver uma resistência coletiva às imposições, o que gerou conflitos entre os trabalhadores contratados pela EBSERH e os do RJU, transformando o local de trabalho em um lugar adoecedor. ABSTRACT The new public management approach brings bad consequences for the workers. The main objective of the research was to analyze the impact of the Empresa Brasileira de Serviços Hospitalares – EBSERH – implementation, on the labour health of workers hired with “Regime Jurídico Único”, from Hospital Universitário Cassiano Antônio de Morais. The qualitative method included interviews of workers and managers with a semi-structured instrument, psychological counselling data and absenteeism data. The categories raised was: EBSERH’s Consolidation: Implementation, Main Changes, and the (Des)Integration Process; Work: Work Process, Goals contracted with the SUS, Conflict; Work Ilness: Insecure, Disrespect, Lack of Recognizing and Exclusion. The workers developed different resistances: conflict, like contesting, silence, like only observing. They didn’t develop a collective resistance against the requirements, and conflicts between EBSERH workers against RJU workers took place, changing the work space in a place of sickness.