Classification of the cardiotocogram data for anticipation of fetal risks using machine learning techniques

The aim of the research is evaluating the classification performances of eight different machine-learning methods on the antepartum cardiotocography (CTG) data. The classification is necessary to predict newborn health, especially for the critical cases. Cardiotocography is used for assisting the obstetricians’ to obtain detailed information during the pregnancy as a technique of measuring fetal well-being, essentially in pregnant women having potential complications. The obstetricians describe CTG shortly as a continuous electronic record of the baby's heart rate took from the mother's abdomen. The acquired information is necessary to visualize unhealthiness of the embryo and gives an opportunity for early intervention prior to happening a permanent impairment to the embryo. The aim of the machine learning methods is by using attributes of data obtained from the uterine contraction (UC) and fetal heart rate (FHR) signals to classify as pathological or normal. The dataset contains 1831 instances with 21 attributes, examined by applying the methods. In the paper, the highest accuracy displayed as 99.2%.     

Exactly satisfying initial conditions neural network models for numerical treatment of first Painlevé equation

In this paper, novel computing approach using three different models of feed-forward artificial neural networks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painlevé equation. These mathematical models of ANNs are developed in an unsupervised manner with capability to satisfy the initial conditions exactly using log-sigmoid, radial basis and tan-sigmoid transfer functions in hidden layers to approximate the solution of the problem. The training of design parameters in each model is performed with sequential quadratic programming technique. The accuracy, convergence and effectiveness of the proposed schemes are evaluated on the basis of the results of statistical analyses through sufficient large number of independent runs with different number of neurons in each model as well. The comparisons of these results of proposed schemes with standard numerical and analytical solutions validate the correctness of the design models.     

Risk factors associated with online game addiction: A hierarchical model

Online gaming addiction has been increasingly recognized as a mental disorder. However, the predictive factors that lead to online gaming addiction are not well established. The aim of this study was to identify factors that may influence the development of online gaming addiction. A total of 263 patients with problematic online gaming addiction (255 males (97%) and 8 females (3%), age: mean = 20.4 ± 5.8 years) and153 healthy comparison subjects (118 males (77%) and 35 females (23%), age: 21.2 ± 5.5 years, range) were recruited for participation in the current study. Hierarchical logistic regression analyses among each set of variables were conducted. Individual factors (sex and age), cognitive factors (IQ and perseverative errors), psychopathological conditions (ADHD, depression, anxiety, and impulsivity), and social interaction factors (family environment, social anxiety, and self-esteem) were evaluated in a stepwise fashion. All four factors were associated with online gaming addiction, with psychopathological conditions being the strongest risk factors for the addiction. Individual factors, psychological factors, and social interactions were associated with the development of pure online gaming addiction. As before, psychological factors (attention, mood, anxiety and impulsivity) were the strongest risk factors for online gaming addiction in patients with pure online gaming addiction. Psychopathologies, including ADHD and depression, were the strongest factors associated with the development of online gaming addiction in individuals.     

铝冷轧制油应用和生产工艺研究

通过对铝材冷轧工艺的分析。研究，以退火工艺中的斑痕为重点，提出采用加氢处理，异构化精制的石蜡基航空煤油组分为基础油，采用不同复合添加剂生产的通用铝冷轧制油完全可以满足客户要求。     

CMF300M355NU型质量流量计在油库汽车装车中的应用

介绍了质量流量计的工作原理有应用效果。这种新型质量流量计精度高，稳定性好，示值计量简便，可直接显示质量、流量、介质温度、密度等，维护量低，但必须正确安装、使用，才能发挥其应有的作用。     

Adhesive element modelling and weighted static shape control of composite plates with piezoelectric actuator patches

A novel finite element model is presented for static and dynamic analysis of composite plates integrated with a laminated piezoelectric layer, a host laminated composite plate and an adhesive layer between them. A new adhesive element is developed which includes both peel and shear effects in the adhesive layer based on first‐order shear deformation plate theory. The thin adhesive layer between the piezoelectric layer and the host plate is modelled by assuming that it carries constant shear and peel strains throughout its thickness. In addition, a weighted static shape control scheme for finding the optimal voltage distribution for static shape control is given. By selecting different weighting matrices, a variety of items such as displacements, slopes, curvatures, strains and even generalized forces, can be included in finding the optimal actuating voltage for static shape control. The present model is validated by comparing with those results available in the literature. The numerical results show that the weighted linear least method can give a satisfactory voltage distribution to best match the desired shape. Copyright © 2004 John Wiley & Sons, Ltd.     

Terminal velocity of non-spherical particles falling through a Carreau model liquid

A procedure has been proposed for the estimation of the terminal falling velocity of non-spherical particles moving in a Carreau model fluid in the transition flow region. The procedure is based on a modification of the relationship formerly developed for the fall of spherical particles including the particle dynamic shape factor. The suitability of the proposed procedure has been confirmed by good agreement between experimental and calculated terminal falling velocity data. In the experiments, the terminal falling velocity of short cylinders and rectangular prisms in polymer solutions of different measure of shear thinning and elasticity has been measured.     

SHS of shape memory CuZnAl alloys

Aiming at preparation of shape memory alloys (SMAs), we explored the SHS of Cu_{1 − x} Zn_{1 − y} Al_{1 − z} alloys (0.29 < x < 0.30, 0.74 < y < 0.75, and 0.83 < z < 0.96). The most pronounced shape memory effect was exhibited by the alloys of the following compositions (wt %): (1) Cu(70.6)Zn(25.4)Al(4.0), (2) Cu(70.1)Zn(25.9)Al(4.0), and (3) Cu(69.9)Zn(26.1)Al(4.0). The effect of process parameters on the synthesis of CuZnAl alloys was studied by XRD, optical microscopy, and scanning electron microscopy (SEM). The grain size of CuZnAl was found to depend on the relative amount of the primary CuZn and AlZn phases. Changes in the transformation temperature and heat of transformation are discussed in terms of ignition intensity and compaction. Mechanism of the process depends on the level of the temperature attained relative to the melting point of components. At the melting point of AlZn, the process is controlled by the solid-state diffusion of AlZn into a product layer. The ignition temperature for this system depends on the temperature of the austenite-martensite transformation in CuZnAl alloys. The composition and structure of the products was found to markedly depend on process parameters. The SHS technique has been successfully used to prepare a variety of SMAs.