Search results for: features comparison

Authors: Sadegh Marzban, Mohamad Sobhan Sheikh Andalibi, Farnaz Ghassemi, Farzad Towhidkhah

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Parkinson's disease (PD), which is characterized by the tremor at rest, rigidity, akinesia or bradykinesia and postural instability, affects the quality of life of involved individuals. The concept of a fractal is most often associated with irregular geometric objects that display self-similarity. Fractal dimension (FD) can be used to quantify the complexity and the self-similarity of an object such as tremor. In this work, we are aimed to propose a new method for evaluating hyperkinetic movements such as tremor, by using the FD and other correlated parameters in patients who are suffered from PD. In this study, we used 'the tremor data of Physionet'. The database consists of fourteen participants, diagnosed with PD including six patients with high amplitude tremor and eight patients with low amplitude. We tried to extract features from data, which can distinguish between patients before and after medication. We have selected fractal dimensions, including correlation dimension, box dimension, and information dimension. Lilliefors test has been used for normality test. Paired t-test or Wilcoxon signed rank test were also done to find differences between patients before and after medication, depending on whether the normality is detected or not. In addition, two-way ANOVA was used to investigate the possible association between the therapeutic effects and features extracted from the tremor. Just one of the extracted features showed significant differences between patients before and after medication. According to the results, correlation dimension was significantly different before and after the patient's medication (p=0.009). Also, two-way ANOVA demonstrates significant differences just in medication effect (p=0.033), and no significant differences were found between subject's differences (p=0.34) and interaction (p=0.97). The most striking result emerged from the data is that correlation dimension could quantify medication treatment based on tremor. This study has provided a technique to evaluate a non-linear measure for quantifying medication, nominally the correlation dimension. Furthermore, this study supports the idea that fractal dimension analysis yields additional information compared with conventional spectral measures in the detection of poor prognosis patients.

Keywords: correlation dimension, non-linear measure, Parkinson’s disease, tremor

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

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We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: Tobias Beyer, Christoph Friedrich

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Modern simulation methodology using finite element models is nowadays a recognized tool for product design/optimization. Likewise, manufacturing process design is increasingly becoming the focus of simulation methodology in order to enable sustainable results based on reduced real-life tests here as well. In this article, two process simulations -radial riveting and roller burnishing- used for mechanical joining of components are explained. In the first step, the required boundary conditions are developed and implemented in the respective simulation models. This is followed by process space validation. With the help of the validated models, the interdependencies of the input parameters are investigated and evaluated by means of sensitivity analyses. Limit case investigations are carried out and evaluated with the aid of the process simulations. Likewise, a comparison of the two joining methods to each other becomes possible.

Keywords: FEM, model-based process development, process simulation, radial riveting, roller burnishing, sensitivity analysis

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Authors: Alexander A. Tokmakov

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Cell-free protein synthesis is widely used to synthesize recombinant proteins. It allows genome-scale expression of various polypeptides under strictly controlled uniform conditions. However, only a minor fraction of all proteins can be successfully expressed in the systems of protein synthesis that are currently used. The factors determining expression success are poorly understood. At present, the vast volume of data is accumulated in cell-free expression databases. It makes possible comprehensive bioinformatics analysis and identification of multiple features associated with successful cell-free expression. Here, we describe an approach aimed at identification of multiple physicochemical and structural properties of amino acid sequences associated with protein solubility and aggregation and highlight major correlations obtained using this approach. The developed method includes: categorical assessment of the protein expression data, calculation and prediction of multiple properties of expressed amino acid sequences, correlation of the individual properties with the expression scores, and evaluation of statistical significance of the observed correlations. Using this approach, we revealed a number of statistically significant correlations between calculated and predicted features of protein sequences and their amenability to cell-free expression. It was found that some of the features, such as protein pI, hydrophobicity, presence of signal sequences, etc., are mostly related to protein solubility, whereas the others, such as protein length, number of disulfide bonds, content of secondary structure, etc., affect mainly the expression propensity. We also demonstrated that amenability of polypeptide sequences to cell-free expression correlates with the presence of multiple sites of post-translational modifications. The correlations revealed in this study provide a plethora of important insights into protein folding and rationalization of protein production. The developed bioinformatics approach can be of practical use for predicting expression success and optimizing cell-free protein synthesis.

Keywords: bioinformatics analysis, cell-free protein synthesis, expression success, optimization, recombinant proteins

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Authors: Chusak Thanawattano, Roongroj Bhidayasiri

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This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

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Authors: Engin Eroğlu, Oktay Yıldız, Necmi Aksoy, Akif Keten, Mehmet Kıvanç Ak, Şeref Keskin, Elif Atmaca, Sertaç Kaya

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Nowadays, green spaces in urban areas are under threat and decreasing their percentages in the urban areas because of increasing population, urbanization, migration, and some cultural changes in quality. An important element of the natural landscape water and water-related natural ecosystems are exposed to corruption due to these pressures. A landscape has owned many different types of elements or units, a more dominant structure than other landscapes as good or bad perceptible extent different direction and variable reveals a unique structure and character of the landscape. Whereas landscapes deal with two main groups as urban and rural according to their location on the world, especially intersection areas of urban and rural named semi-urban or semi-rural present variety landscape features. The main components of the landscape are defined as patch-matrix-corridor. The corridors include quite various vegetation types such as riparian, wetland and the others. In urban areas, natural water corridors are an important elements of the diversity of the riparian vegetation cover. In particular, water corridors attract attention with a natural diversity and lack of fragmentation, degradation and artificial results. Thanks to these features, without a doubt, water corridors are the important component of all cities in the world. These corridors not only divide the city into two separate sides, but also assured the ecological connectivity between the two sides of the city. The main objective of this study is to determine the vegetation and habitat features of urban stream corridor according to environmental interactions. Within this context, this study will be realized that 'Asar Suyu' is an important component of the city of Düzce. Moreover, the riparian zone touched contiguous area borders of the city and overlaid the urban development limits of the city, determining of characteristics of the corridor will be carried out as floristic and habitat analysis. Consequently, vegetation structure and habitat features which play an important role between riparian zone vegetation covers and environmental interaction will be determined. This study includes first results of The Scientific and Technological Research Council of Turkey (TUBITAK-116O596; 'Determining of Landscape Character of Urban Water Corridors as Visual and Ecological; A Case Study of Asar Suyu in Duzce').

Keywords: corridor, Duzce, landscape ecology, riparian vegetation

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Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo

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SMPL-X was a powerful parametric human body model that included male, neutral, and female models, with significant gender differences between these three models. During the process of 3D human body reconstruction, the correct selection of standard templates was crucial for obtaining accurate results. To address this issue, we developed an efficient gender classification algorithm to automatically select the appropriate template for 3D human body reconstruction. The key to this gender classification algorithm was the precise analysis of human body features. By using the SMPL-X model, the algorithm could detect and identify gender features of the human body, thereby determining which standard template should be used. The accuracy of this algorithm made the 3D reconstruction process more accurate and reliable, as it could adjust model parameters based on individual gender differences. SMPL-X and the related gender classification algorithm have brought important advancements to the field of 3D human body reconstruction. By accurately selecting standard templates, they have improved the accuracy of reconstruction and have broad potential in various application fields. These technologies continue to drive the development of the 3D reconstruction field, providing us with more realistic and accurate human body models.

Keywords: gender classification, joint detection, SMPL-X, 3D reconstruction

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Authors: Vu Thu Trang, Lam Xuan Thanh, Samira Sarter, Tomoko Shimamura, Hiroaki Takeuchi　　

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Antimicrobial activities of aminoreductone (AR), a product formed in the initial stage of Maillard reaction, were screened against pathogenic bacteria. A significant growth inhibition of AR against all 7 isolates (Staphylococcus aureus ATCC® 25923™, Salmonella Typhimurium ATCC® 14028™, Bacillus cereus ATCC® 13061™, Bacillus subtilis ATCC® 11774™, Escherichia coli ATCC® 25922™, Enterococcus faecalis ATCC® 29212™, Listeria innocua ATCC® 33090™) were observed by the standard disc diffusion methods. The inhibition zone for each isolate by AR (2.5 mg) ranged from 15±0 mm to 28.3±0.4 mm in diameter. The minimum inhibitory concentration (MIC) of AR ranging from 20 mM to 26 mM was proven in the seven isolates tested. AR also showed the similar effect of growth inhibition in comparison with antibiotics frequently used for the treatment of infections bacteria, such as amikacin, ciprofloxacin, meropennem, and levofloxacin. The results indicated that foods containing AR are valuable sources of bioactive compounds towards pathogenic bacteria.

Keywords: pathogenic bacteria, aminoreductone, Maillard reaction, antimicrobial activity

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Authors: Shishay T. Kidanu

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The study area is located in Southwestern Missouri and is mainly underlain by Mississippian Age limestone which is highly susceptible to karst processes. The area is known for the presence of various karst features like caves, springs and more importantly Sinkholes. Sinkholes are one of the most common karst features and the primary hazard in karst areas. Investigating the subsurface structure and development mechanism of existing sinkholes enables to understand their long-term impact and chance of reactivation and also helps to provide effective mitigation measures. In this study ERT (Electrical Resistivity Tomography), MASW (Multichannel Analysis of Surface Waves) and borehole control data have been used to image the subsurface structure and investigate the development mechanism of a sinkhole in Southwestern Missouri. The study shows that the main process responsible for the development of the sinkhole is the downward piping of fine grained soils. Furthermore, the study reveals that the sinkhole developed along a north-south oriented vertical joint set characterized by a vertical zone of water seepage and associated fine grained soil piping into preexisting fractures.

Keywords: ERT, Karst, MASW, sinkhole

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Aminur Rahman

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The Unique feature of BROTHERS Furniture sofa stands in ergonomic Design, skilled hand work and art work. Present world market is passing through a contentious competitive situation that is rapidly and dramatic. Competitive strategy concerns how to create competitive advantage in upholstery businesses. In order to competitive advantage in upholstery sofa market, Design and develop a sofa that have to ergonomic features. Design an ergonomic upholstery sofa knowing and understanding the appropriate seat depth, seat height, angle between Seat & back, back height which is concurrent market demand, world class sofa has to incorporate ergonomic factors. The study the relationships between human, seat and context variables comfort and discomfort. We must have conduct market survey among users whose are need and use sofa. Health & safety factors should be examined from a variety of angle. An attractive design and meet customer requirements, ergonomically fit should be considered for sofa development. This paper will explain how to design & develop sofa’s as per standard specifications which have ergonomic features for users all over the world.

Keywords: ergonomics, angle between seat & back, standard dimension, seat comfort

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Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: Faiza Babur Khan, Sohail Asghar

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With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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Authors: Arup Saha Chaudhuri

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Structural steel is a very ductile material with high strength carrying capacity, thus it is very useful to make earthquake resistant buildings. It is a homogeneous material also. The member section and the structural system can be made very efficient for economical design. As the steel is recyclable and reused, it is a green material. The embodied energy for the efficiently designed steel structure is less than the RC structure. For sustainable green building steel is the best material nowadays. Moreover, pre-engineered and pre-fabricated faster construction methodologies help the development work to complete within the stipulated time. In this paper, the usefulness of Eccentric Bracing Frame (EBF) in steel structure over Moment Resisting Frame (MRF) and Concentric Bracing Frame (CBF) is shown. Stability of the steel structures against horizontal forces especially in seismic condition is efficiently possible by Eccentric bracing systems with economic connection details. The EBF is pin–ended, but the beam-column joints are designed for pin ended or for full connectivity. The EBF has several desirable features for seismic resistance. In comparison with CBF system, EBF system can be designed for appropriate stiffness and drift control. The link beam is supposed to yield in shear or flexure before initiation of yielding or buckling of the bracing member in tension or compression. The behavior of a 2-D steel frame is observed under seismic loading condition in the present paper. Ductility and brittleness of the frames are compared with respect to time period of vibration and dynamic base shear. It is observed that the EBF system is better than MRF system comparing the time period of vibration and base shear participation.

Keywords: steel building, green and sustainable, earthquake resistant, EBF system

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Authors: T. D. Ibragimov, A. R. Imamaliyev, G. M. Bayramov

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Influence of barium titanate particles on electro-optic properties of liquid crystal 4-cyano-4′-pentylbiphenyl (5CB) with positive dielectric anisotropy and the liquid crystalline (LC) mixture Н-37 consisting of 4-methoxybezylidene-4'–butylaniline and 4-ethoxybezylidene-4'–butylaniline with negative dielectric anisotropy was investigated. It was shown that a presence of particles inside 5СВ and H-37 decreased the clearing temperature from 35.2 °С to 32.5°С and from 61.2 oC to 60.1oC, correspondingly. The threshold voltage of the Fredericksz effect became 0.3 V for the BaTiO3-5CB colloid while the beginning of this effect of the pure 5СВ was observed at 2.1 V. Threshold voltage of the Fredericksz effect increased from 2.8 V to up 3.1 V at additive of particles into H-37. A rise time of the BaTiO3-5CB colloid improved while a decay time worsened in comparison with the pure 5CB at all applied voltages. The inverse trends were observed for the H-37 matrix, namely, a rise time worsened and a decay time improved. Among other things, the effect of fast light modulation was studied at application of the rectangular impulse with direct bias to an electro-optical cell with the BaTiO3 particles+5CB and the pure 5CB. At this case, a rise time of the composite worsened, a decay time improved in comparison with the pure 5CB. The pecularities of electrohydrodynamic instability (EHDI) formation was also investigated into the composite with the H-37 matrix. It was found that the voltage of the EHDI formation decreased, a rise time increased and a decay time decreased in comparison with the pure H-37. First of all, experimental results are explained by appearance of local electric fields near the polarized ferroelectric particles at application of external electric field and an existence of the additional obstacles (particles) for movement of ions.

Keywords: liquid crystal, ferroelectric particles, composite, electro-optics

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Authors: Tawfik Thelaidjia, Salah Chenikher

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Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

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Authors: Frieda Amitai

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The field of Translation Studies includes both descriptive and applied aspects, one of which is developing curricula. Within this topic there are theories dealing with curricula aimed at translator training, and theories meant to explore teaching translation as means through which awareness to language is developed in order to enhance language knowledge. An example of the latter is a unique study program in Israeli high schools – Teaching Translation Skills Program (TTSP). This study program has been taught in Israel for more than two decades and is aimed at raising students' meta-linguistic awareness as well as their language proficiency in both source language and target language in order to enable them become better language learners. The objective of the current research was to examine whether the goals of this program are achieved – increase in students' metalinguistic awareness and language proficiency. A follow-up case study was aimed at examining the level of proficiency which would develop most by this way of teaching English. The study was conducted in two stages – before and after participating in the program. 400 subjects took part in the first stage, and 100 took part in the second. In both parts of the study, participants were given the same five tasks in both Hebrew and English in addition to a questionnaire, in which they were asked about their own knowledge of Hebrew and in comparison to that of their peers. Their teachers were asked about the success of the program and about the methodology they use in class. Findings show significant change in the level of meta-linguistic awareness of the students as well as their language proficiency. A comparison between their answers before and after the program shows that their meta-linguistic awareness increased, as did their ability to recognize linguistic mistakes. These findings serve as strong evidence for the positive effect such study program has on the development of meta-linguistic awareness and linguistic knowledge. The follow-up case study tests the change among weaker language learners.

Keywords: comparison, metalinguistic awareness, language learning, translation skills

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Authors: K. Bensafia, A. Mansour, G. Le Maillot, B. Clement, O. Reynet, P. Ariès, S. Haddab

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This paper presents a system designed for wireless acquisition, the recording of electrocardiogram (ECG) signals and the monitoring of the heart’s health during surgery. This wireless recording system allows us to visualize and monitor the state of the heart’s health during a surgery, even if the patient is moved from the operating theater to post anesthesia care unit. The acquired signal is transmitted via a Bluetooth unit to a PC where the data are displayed, stored and processed. To test the reliability of our system, a comparison between ECG signals processed by a conventional ECG monitoring system (Datex-Ohmeda) and by our wireless system is made. The comparison is based on the shape of the ECG signal, the duration of the QRS complex, the P and T waves, as well as the position of the ST segments with respect to the isoelectric line. The proposed system is presented and discussed. The results have confirmed that the use of Bluetooth during surgery does not affect the devices used and vice versa. Pre- and post-processing steps are briefly discussed. Experimental results are also provided.

Keywords: electrocardiography, monitoring, surgery, wireless system

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Authors: Rajkumar Ghosh

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The study focuses on the tectonics of out-of-sequence thrusting (OOST) in the NW region of the Himalaya, particularly in Himachal Pradesh. The research aims to identify the features and nature of OOST in the field and the associated rock types and lithological boundaries in the field of NW Himalaya, Himachal Pradesh, India. The research employs fieldwork and micro-structure observations, correlations, and analyses to identify and analyze the OOST features and associated rock types. The study reveals the presence of three OOSTs, namely Jhakri Thrust (JT), Sarahan Thrust (ST), and Chaura Thrust (CT), which consist of several branches, some of which are still active. The thrust system exhibits varying internal geometry, including box folds, boudins, scar folds, crenulation cleavages, kink folds, and tension gashes. The CT, which is concealed beneath Jutogh Thrust sheet, represents a steepened downward thrust, while the JT has a western dip and is south-westward verging. The research provides crucial information on the tectonics of OOST in the NW region of the Himalaya, particularly in Himachal Pradesh, which is crucial in understanding the regional geological evolution and associated hazards. The data were collected through fieldwork and micro-structure observations, correlations, and analyses of rock samples. The data were analyzed using tectonic and geochronological techniques to identify the nature and characteristics of OOST. The research addressed the question of identifying Higher Himalayan OOST in the field of NW Himalaya, Himachal Pradesh, India, and the associated rock types and lithological boundaries. The study concludes that there is minimal documentation and a lack of suitable exposure of rocks to generalize the features of OOST in the field in NW Higher Himalaya, Himachal Pradesh. The study recommends more extensive mapping and fieldwork to improve understanding of OOST in the region.

Keywords: out-of-sequence thrust (OOST), main central thrust (MCT), jhakri thrust (JT), sarahan thrust (ST), chaura thrust (CT), higher himalaya (HH)

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Authors: Tatyana Suvorkina

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It is indisputable that the problem of the origin of Manichaeism is very complex. Manichaeism is characterized as a syncretic religion, which was influenced by many teachings, but it is difficult to define one which can be called fundamental. The aim of this paper is an attempt to regard Jewish apocalyptic tradition as one of the most defining source of formation of Manichaean systems. To realize this aim a comparison of the Manichean texts and the Jewish apocryphal literature is made. Consideration is given first to the Coptic Manichaean treatise Kephalaia, The Cologne Mani Codex and to books of Enoch. Under the article it is not denied that Manichaeism was influenced by different doctrines and, passed through centuries, it could adapt and strengthen this influence at an even deeper level. But the fact that the Judeo-Christian environment where Mani grew up and where the first sprouts of his teaching were formed had impact on future prophet seems obvious. Nevertheless, attempts to analyze the system of Mani within the Jewish tradition are quite rare, although such studies were carried out for Gnosticism. But Manichaeism, despite the Gnostic features it contains, is not 'one of the Gnostics' to place it under this term among the rest. Frequently, gnostic currents are pointed out as the main sources for the formation of Mani’s teachings. But it seems possible that Mani's interest in Gnosticism was motivated by the fact that he considered it as something close to that interpretation of Hebrew texts, which he aspired to undertake. The question of understanding the Manichaean system is connected not only with Manichaeism but also with other dualistic teachings, which were recognized by contemporaries as Manichaean. It is seen that polemics between Manicheans and Hellenized Christianity separated from Judaism and continued to separate with every century, were polemics between adherents of initially two different worldviews who had, however, a common source. Therefore an analysis of the controversy in the context of interpretations of this common source by disputing parties is seen very important for further study.

Keywords: dualism, Jewish apocalypticism, Manichaeism, syncretism

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Authors: Yin Yuanling

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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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Authors: Rachnavy Pornthep, Khaothin Thawichai

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The purpose of this paper was to investigate the effects of rowing ergometer exercise on older persons health. The subjects were divided into two groups. Group 1 was control group (10 male and 10 female) Group 2 was experimental group (10 male and 10 female). The time for study was 12 week. Group 1 engage in normal daily activities Group 2 Training with rowing machine for 20 minutes three days a week. The average age of the experimental group was 73.7 years old, mean weight 55.4 kg, height 154.8 cm in the control group, mean age was 74.95 years, mean weight 48.6 kg, mean height 153.85 cm. Physical fitness test composted of body size, flexibility, Strength, muscle endurance and cardiovascular endurance. The comparison between the experimental and control groups before training showed that body weight, body mass index and waist to hip ratio were significantly different. The flexibility, strength, cardiovascular endurance was not significantly different. The comparison between the control group and the experimental group after training showed that body weight, body mass index and cardiovascular endurance were significantly different. The ratio of waist to hips, flexibility and muscular strength were not significantly different. Comparison of physical fitness before training and after training of the control group showed that body weight, flexibility (Sit and reach) and muscular strength (30 – Second chair stand) were significantly different. Body mass index, waist to hip ratio, muscles flexible (Shoulder girdle flexibility), muscle strength (30 – Second arm curl) and the cardiovascular endurance were not significantly difference. Comparison of physical fitness before training and after training the experimental group showed that waist to hip ratio, flexibility (sit and reach) muscle strength (30 – Second chair stand), cardiovascular endurance (Standing leg raises - up to 2 minutes) were significantly different. The Body mass index and the flexibility (Shoulder girdle flexibility) no significantly difference. The study found that exercising with rowing machine can improve the physical fitness of the elderly, especially the cardiovascular endurance, corresponding with the past research on the effects of exercise in the elderly with different exercise such as cycling, treadmill, walking on the elliptical machine. Therefore, we can conclude that exercise by using rowing machine can improve cardiovascular system and flexibility in the elderly.

Keywords: effect, rowing, exercise, elderly

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Authors: Zhihui Liu, Dongmei Hao, Qian Qiu, Yang An, Lin Yang, Song Zhang, Yimin Yang, Xuwen Li, Dingchang Zheng

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Premature birth, defined as birth before 37 completed weeks of gestation is a leading cause of neonatal morbidity and mortality and has long-term adverse consequences for health. It has recently been reported that the worldwide preterm birth rate is around 10%. The existing measurement techniques for diagnosing preterm delivery include tocodynamometer, ultrasound and fetal fibronectin. However, they are subjective, or suffer from high measurement variability and inaccurate diagnosis and prediction of preterm labor. Electrohysterography (EHG) method based on recording of uterine electrical activity by electrodes attached to maternal abdomen, is a promising method to assess uterine activity and diagnose preterm labor. The purpose of this study is to analyze the difference of EHG signal features between term labor and preterm labor. Free access database was used with 300 signals acquired in two groups of pregnant women who delivered at term (262 cases) and preterm (38 cases). Among them, EHG signals from 38 term labor and 38 preterm labor were preprocessed with band-pass Butterworth filters of 0.08–4Hz. Then, EHG signal features were extracted, which comprised classical time domain description including root mean square and zero-crossing number, spectral parameters including peak frequency, mean frequency and median frequency, wavelet packet coefficients, autoregression (AR) model coefficients, and nonlinear measures including maximal Lyapunov exponent, sample entropy and correlation dimension. Their statistical significance for recognition of two groups of recordings was provided. The results showed that mean frequency of preterm labor was significantly smaller than term labor (p < 0.05). 5 coefficients of AR model showed significant difference between term labor and preterm labor. The maximal Lyapunov exponent of early preterm (time of recording < the 26th week of gestation) was significantly smaller than early term. The sample entropy of late preterm (time of recording > the 26th week of gestation) was significantly smaller than late term. There was no significant difference for other features between the term labor and preterm labor groups. Any future work regarding classification should therefore focus on using multiple techniques, with the mean frequency, AR coefficients, maximal Lyapunov exponent and the sample entropy being among the prime candidates. Even if these methods are not yet useful for clinical practice, they do bring the most promising indicators for the preterm labor.

Keywords: electrohysterogram, feature, preterm labor, term labor

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Authors: Joseph Uzuazomaro Oju

Abstract:

The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.

Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media

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Authors: Raghad Dwaik

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It is well known in language acquisition literature that a mere understanding of a reading text is not enough to help students build proficiency in comprehension. Students should rather follow understanding by attempting to express what has been understood by pushing their competence to the limit. Learners' attempt to push their competence was given the term "comprehensible output" by Swain (1985). Teachers in large classes, however, find it sometimes difficult to give all students a chance to communicate their views or to share their ideas during the short class time. In most cases, students who are outgoing dominate class discussion and get more opportunities for practice which leads to ignoring the shy students totally while helping the good ones become better. This paper presents the idea of using Google Classroom features of posting and commenting to allow students who hesitate to participate in class discussions about a reading text to write their views on the wall of a Google Classroom and share them later after they have received feedback and comments from classmates. Such attempts lead to developing their proficiency through additional practice in comprehensible output and to enhancing their confidence in themselves and their views. It was found that virtual classroom interaction would help students maintain vocabulary, use more complex structures and focus on meaning besides form.

Keywords: learning groups, reading TESOL, Google Classroom, comprehensible output

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Authors: Woei-Shyan Lee, Hao-Chien Kao

Abstract:

The impact deformation and fracture behaviour of cobalt-based Haynes 188 superalloy are investigated by means of a split Hopkinson pressure bar. Impact tests are performed at strain rates ranging from 1×103 s-1 to 5×103 s-1 and temperatures between 25°C and 800°C. The experimental results indicate that the flow response and fracture characteristics of cobalt-based Haynes 188 superalloy are significantly dependent on the strain rate and temperature. The flow stress, work hardening rate and strain rate sensitivity all increase with increasing strain rate or decreasing temperature. It is shown that the impact response of the Haynes 188 specimens is adequately described by the Zerilli-Armstrong fcc model. The fracture analysis results indicate that the Haynes 188 specimens fail predominantly as the result of intensive localised shearing. Furthermore, it is shown that the flow localisation effect leads to the formation of adiabatic shear bands. The fracture surfaces of the deformed Haynes 188 specimens are characterised by dimple- and / or cleavage-like structure with knobby features. The knobby features are thought to be the result of a rise in the local temperature to a value greater than the melting point.

Keywords: Haynes 188 alloy, impact, strain rate and temperature effect, adiabatic shearing

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Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

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Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

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Authors: Anna D. Kotrova, Alexandr N. Shishkin, Elena I. Ermolenko

Abstract:

The aim. To study the quantitative and qualitative colon bacteria ratio from patients with metabolic syndrome. Materials and methods. Fecal samples from patients of 2 groups were identified and analyzed: the first group was formed by patients with metabolic syndrome, the second one - by healthy individuals. The metagenomics method was used with the analysis of 16S rRNA gene sequences. The libraries of the variable sites (V3 and V4) gene 16S RNA were analyzed using the MiSeq device (Illumina). To prepare the libraries was used the standard recommended by Illumina, a method based on two rounds of PCR. Results. At the phylum level in the microbiota of patients with metabolic syndrome compared to healthy individuals, the proportion of Tenericutes was reduced, the proportion of Actinobacteria was increased. At the genus level, in the group with metabolic syndrome, relative to the second group was increased the proportion of Lachnospira. Conclusion. Changes in the colon bacteria ratio in the gut microbiota of patients with metabolic syndrome were found both at the type and the genus level. In the metabolic syndrome group, there is a decrease in the proportion of bacteria that do not have a cell wall. To confirm the revealed microbiota features in patients with metabolic syndrome, further study with a larger number of samples is required.

Keywords: gut microbiota, metabolic syndrome, metagenomics, tenericutes

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Authors: Qasim A. El Dwairi, Saleh M. Banihani, Ayat S. Banihani, Ziad M. Bataineh

Abstract:

Neurons in the spinal trigeminal nucleus of the camel were studied by Golgi impregnation. Neurons were classified based on differences in size and shape of their cell bodies, density of their dendritic trees, morphology and distribution of their appendages. In the spinal trigeminal nucleus of the camel, at least twelve types of neurons were identified. These neurons include, stalked, islets, octubus-like, lobulated, boat-like, pyramidal, multipolar, round, oval and elongated neurons. They have large number of different forms of appendages not only for their dendrites but also for their cell bodies. Neurons with unique large dilatations especially at their dendritic branching points were found. The morphological features of these neurons were described and compared with their counterparts in other species. Finding of large number of neuronal types with different size and shapes and large number of different forms of appendages for cell bodies and dendrites together with the presence of cells with unique features such as large dilated parts for dendrites may indicate to a very complex information processing for pain and temperature at the level of the spinal trigeminal nucleus in the camel that traditionally live in a very hard environment (the desert).

Keywords: camel, golgi, neurons , spinal trigeminal nucleus

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Authors: Isobel Hambleton, Mark Carrington

Abstract:

Trypanosoma brucei, the causal agent of a range of diseases in humans and livestock, evades the mammalian immune system through a population survival strategy based on the expression of a series of antigenically distinct variant surface glycoproteins (VSGs). RNAi mediated knockdown of the active VSG gene triggers a precytokinesis cell cycle arrest. To determine whether this phenotype is the result of reduced VSG transcript or depleted VSG protein, we used morpholino antisense oligonucleotides to block translation of VSG mRNA. The same precytokinesis cell cycle arrest was observed, suggesting that VSG protein abundance is monitored closely throughout the cell cycle. An inducible expression system has been developed to test various GPI-anchored proteins for their ability to rescue this cell cycle arrest. This system has been used to demonstrate that wild-type VSG expressed from a T7 promoter rescues this phenotype. This indicates that VSG expression from one of the specialised bloodstream expression sites (BES) is not essential for cell division. The same approach has been used to define the minimum essential features of a VSG necessary for function.

Keywords: bloodstream expression site, morpholino, precytokinesis cell cycle arrest, variant surface glycoprotein

Procedia PDF Downloads 139