Search results for: Neural Processing Element (NPE)

Authors: Haozheng Luo, Ruiyang Qin

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People with visual impairments urgently need assistance, not only on the fundamental tasks such as guiding and retrieving objects but on the advanced like picturing the new environments. More than a guiding dog, they might want such devices that can provide linguistic interaction. Building on this idea, we aim to study the interaction between the robot agent and visually impaired people. In our research, we are going to develop a robot agent that will be able to analyze the test environment and answer the participants’ questions. We also will study the relevant issues regarding the interaction between human beings and the robot agents to figure out which and how the factors will affect the interaction.

Keywords: HRI, video question answering, visual question answering, natural language processing

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Authors: M. J. Uddin, M. M. Rahman

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Transient natural convective flow dynamics of nanofluids in a horizontal homocentric annulus using nonhomogeneous dynamic model has been experimented numerically. The simulation is carried out for four different shapes of the inner wall, which is either cylindrical, elliptical, square or triangular. The outer surface of the annulus is maintained at constant low temperature while the inner wall is maintained at a uniform temperature; higher than the outer one. The enclosure is permeated by a uniform magnetic field having variable orientation. The Brownian motion and thermophoretic deposition phenomena of the nanoparticles are taken into account in model construction. The governing nonlinear momentum, energy, and concentration equations are solved numerically using Galerkin weighted residual finite element method. To find the best performer, the local Nusselt number is demonstrated for different shapes of the inner wall. The heat transfer enhancement for different nanofluids for four different shapes of the inner wall is exhibited.

Keywords: nanofluids, annulus, nonhomogeneous dynamic model, heat transfer

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Authors: Subrato Saha, Yun-Hyun Cho

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In electric power steering (EPS), spoke type brushless ac (BLAC) motors offer distinct advantages over other electric motor types in terms torque smoothness, reliability and efficiency. This paper deals with the shape optimization of spoke type BLAC motor, in order to reduce cogging torque. This paper examines 3 steps skewing rotor angle, optimizing rotor core edge and rotor overlap length for reducing cogging torque in spoke type BLAC motor. The methods were applied to existing machine designs and their performance was calculated using finite- element analysis (FEA). Prototypes of the machine designs were constructed and experimental results obtained. It is shown that the FEA predicted the cogging torque to be nearly reduce using those methods.

Keywords: EPS, 3-Step skewing, spoke type BLAC, cogging torque, FEA, optimization

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Authors: Hyungoo Kang, Minsung Kim, Jinkoo Kim

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This study investigates the performance of a 2D and 3D steel moment frame subjected to vehicle collision at a first story column using LS-DYNA. The finite element models of vehicles provided by the National Crash Analysis Center (NCAC) are used for numerical analysis. Nonlinear dynamic time history analysis of the 2D and 3D model structures are carried out based on the arbitrary column removal scenario, and the vertical displacement of the damaged structures are compared with that obtained from collision analysis. The analysis results show that the model structure remains stable when the speed of the vehicle is 40km/h. However, at the speed of 80 and 120km/h both the 2D and 3D structures collapse by progressive collapse. The vertical displacement of the damaged joint obtained from collision analysis is significantly larger than the displacement computed based on the arbitrary column removal scenario.

Keywords: vehicle collision, progressive collapse, FEM, LS-DYNA

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Authors: Tareq Al Muhareb, Jasper Graham-Jones

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The service quality is a significant element in aviation industry especially in the international airports. Through this paper, the researchers built a model based on Lean six sigma methodologies and applied it in the departure area at KKIA (King Khalid International Airport) in order to assess it. This model characterized with many special features that can become over the cultural differences in aviation industry since it is considered the most critical circumstance in this field. Applying the model of this study is depending on following the DMAIC procedure systemized in lean thinking aspects. This model of Lean-six-sigma as a managerial procedure is mostly focused on the change management culture that requires high level of planning, organizing, modifying, and controlling in order to benefit from strengths as well as revoke weaknesses.

Keywords: lean-six-sigma, service quality, aviation industry, KKIA (King Khalid International Airport), SERVQUAL

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Authors: Galuh Asri Bestari, Hajar Shofiyya

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Double burden of malnutrition (DBM) has been a global problem in these last decades occurs in both developed and developing countries. Overweight in adults and stunting among preschool children have dramatically increased and become the main problems of malnutrition that should be solved immediately since they are directly related with the health status and productivity. Reformulation of food product by using the local sea resources called terasi shrimp (Acetes indicus) has a potential possibility in facing the DBM. A study was carried out in Indonesia to determine the acceptability of terasi shrimp powder through sensory evaluation. Terasi shrimps were processed into powder form through sun drying and pounding methods. The powder form was directly added in food as alternative seasonings and tested among stunted and normal preschool children. Meanwhile, a further processing method is given to the shrimp powder tested in overweight and normal-weighed adults. The shrimp powder was mixed with sago flour and formed into balls, then steamed for 15-20 minutes, and finally served as alternative snacks. Based on the sensory evaluation, the shrimp powder has a good acceptance in taste (54%), shape (60%), and color properties (63%), while the shrimp balls has a good acceptance in size (65%), shape (50%), color (48%), taste (40%), and texture (36%). Terasi shrimp powder can be stored for a month in room temperature. In addition, carried out chemical analysis revealed that terasi shrimp (Acetes indicus) has higher percentage of protein, calcium, and iron than other animal sources, but conversely contains zero sodium and very low percentage of fat. Terasi shrimp’s shell also contains a substance called chitosan which acts by forming gels in the intestinal tract to entrap lipids, thus interfering with their absorption. After going through some processing methods, the shrimp powder and balls did not show any significant changes in their nutrient contents. So that, terasi shrimp powder is good to be consumed not only by overweight adults, but also by children to support their optimum growth. Intervention of terasi shrimp powder should be implemented step by step from national up to global governance program to face the DBM.

Keywords: Acetes indicus, alternative food, double burden of malnutrition, sensory evaluation

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Authors: Aida Alemany, Laura Ballester, Ana González-Urteaga

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From 2007 subprime crisis to the recent Eurozone debt crisis the European banking industry has experienced a terrible financial instability situation with increasing levels of CDS spreads (used as a proxy of credit risk). This paper investigates whether volatility transmission channels in European banking markets have changed after three significant crises’ events during the period January 2006 to March 2013. The global financial crisis is characterized by a unidirectional volatility shocks spillovers effect in credit risk from inside to outside the Eurozone. By contrast, the Eurozone debt crisis is revealed to be local in nature with the euro as the key element suggesting a market fragmentation between distressed peripheral and non-distressed core Eurozone countries, whereas retaining the local currency have acted as a firewall. With these findings we are able to shed light on the impact of the different crises on the European banking credit risk dynamics.

Keywords: CDS spreads, credit risk, volatility spillovers, financial crisis

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Authors: Waheed Ahmad Safi, Shunichi Nakamura

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Steel/concrete composite bridge with the concrete filled steel I-girder (CFIG) was proposed, and the bending and shear strength was studied by experiments and FEM analysis. The area surrounded by the upper and lower flanges and the web is filled with concrete in CFIG, which is used at the intermediate support of a continuous girder. The bending and shear tests of the CFIG were carried out, showing that the bending strength of CFIG was 2.8 times of the conventional steel I-girder and the shear strength was 3.0 times of the steel I-girder. Finite element models were established to clarify bending and shear behaviors and the load transfer mechanism of CFIG. FEM result agreed very well with the test results. The FEM model was also applied to simulate the shear tests of the CFIG specimens. A trail design was carried out for a four-span continuous highway bridge and the design method was established.

Keywords: bending strength, concrete filled steel I-girder, steel I-girder, FEM, limit states design and shear strength

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization

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Authors: Masoud Nasiri Sarvi, Yunhua Luo

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Low-trauma hip fracture, usually caused by fall from standing height, has become a main source of morbidity and mortality for the elderly. Factors affecting hip fracture include sex, race, age, body weight, height, body mass distribution, etc., and thus, hip fracture risk in fall differs widely from subject to subject. It is therefore necessary to develop a subject-specific biomechanical model to predict hip fracture risk. The objective of this study is to develop a two-level, image-based, subject-specific biomechanical model consisting of a whole-body dynamics model and a proximal-femur finite element (FE) model for more accurately assessing the risk of hip fracture in lateral falls. Required information for constructing the model is extracted from a whole-body and a hip DXA (Dual Energy X-ray Absorptiometry) image of the subject. The proposed model considers all parameters subject-specifically, which will provide a fast, accurate, and non-expensive method for predicting hip fracture risk.

Keywords: bone mineral density, hip fracture risk, impact force, sideways falls

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Authors: Dorothea Voß, Tobias Esser, Michael Huber, Jakob Albert

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The growing world population and the associated increase in demand for energy and consumer goods, as well as increasing waste production, requires the development of sustainable processes. In addition, the increasing environmental awareness of our society is a driving force for the requirement that processes must be as resource and energy efficient as possible. In this context, the use of polyoxometalate catalysts (POMs) has emerged as a promising approach for the development of green processes. POMs are bifunctional polynuclear metal-oxo-anion cluster characterized by a strong Brønsted acidity, a high proton mobility combined with fast multi-electron transfer and tunable redox potential. In addition, POMs are soluble in many commonly known solvents and exhibit resistance to hydrolytic and oxidative degradation. Due to their structure and excellent physicochemical properties, POMs are efficient acid and oxidation catalysts that have attracted much attention in recent years. Oxidation processes with molecular oxygen are worth mentioning here. However, the fact that the POM catalysts are homogeneous poses a challenge for downstream processing of product solutions and recycling of the catalysts. In this regard, nanofiltration membranes have gained increasing interest in recent years, particularly due to their relative sustainability advantage over other technologies and their unique properties such as increased selectivity towards multivalent ions. In order to establish an efficient downstream process for the highly selective separation of homogeneous POM catalysts from aqueous solutions using nanofiltration membranes, a laboratory-scale membrane system was designed and constructed. By varying various process parameters, a sensitivity analysis was performed on a model system to develop an optimized method for the recovery of POM catalysts. From this, process-relevant key figures such as the rejection of various system components were derived. These results form the basis for further experiments on other systems to test the transferability to serval separation tasks with different POMs and products, as well as for recycling experiments of the catalysts in processes on laboratory scale.

Keywords: downstream processing, nanofiltration, polyoxometalates, homogeneous catalysis, green chemistry

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Authors: Dongchuan Su, Hai Xie, Naibin Jiang

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Under severe accident cases, the nuclear reactor core may meltdown inside the lower head of the reactor pressure vessel (RPV). Retaining the melt pool inside the RPV is an important strategy of severe accident management. During this process, the inner wall of the lower head will be heated to high temperature of a thousand centigrade, and the outer wall is immersed in a large amount of cooling water. The material of the lower head will have serious creep damage under the high temperature and the temperature difference, and this produces a great threat to the integrity of the RPV. In this paper, the ANSYS program is employed to build the finite element method (FEM) model of the lower head, the creep phenomena is simulated under the severe accident case, the time dependent strain and stress distribution is obtained, the creep damage of the lower head is investigated, the integrity of the RPV is evaluated and the theoretical basis is provided for the optimized design and safety assessment of the RPV.

Keywords: severe accident, lower head of RPV, creep, FEM

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Authors: Alaa Chasib Ghaleb, Muntadher M. Abbood

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This paper presents a study of the problem of the optimum design of piled-raft foundation systems. The study has been carried out using a hypothetic problem and soil investigations of six sites locations in Basrah city to evaluate the adequacy of using the piled-raft foundation concept. Three dimensional finite element analysis method has been used, to perform the structural analysis. The problem is optimized using Hooke and Jeeves method with the total weight of the foundation as objective function and each of raft thickness, piles length, number of piles and piles diameter as design variables. It is found that the total and differential settlement decreases with increasing the raft thickness, the number of piles, the piles length, and the piles diameter. Finally parametric study for load values, load type and raft dimensions have been studied and the results have been discussed.

Keywords: Hooke and Jeeves, optimum design, piled-raft, foundations

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Authors: Kuei-Ling Sun, Emily Chia-Yu Su

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Allergy is a hypersensitive overreaction of the immune system to environmental stimuli, and a major health problem. These overreactions include rashes, sneezing, fever, food allergies, anaphylaxis, asthmatic, shock, or other abnormal conditions. Allergies can be caused by food, insect stings, pollen, animal wool, and other allergens. Their development of allergies is due to both genetic and environmental factors. Allergies involve immunoglobulin E antibodies, a part of the body’s immune system. Immunoglobulin E antibodies will bind to an allergen and then transfer to a receptor on mast cells or basophils triggering the release of inflammatory chemicals such as histamine. Based on the increasingly serious problem of environmental change, changes in lifestyle, air pollution problem, and other factors, in this study, we both collect allergens and non-allergens from several databases and use several machine learning methods for classification, including logistic regression (LR), stepwise regression, decision tree (DT) and neural networks (NN) to do the model comparison and determine the permutations of allergen amino acid’s sequence.

Keywords: allergy, classification, decision tree, logistic regression, machine learning

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Authors: Belayneh Matebie, Michael Melese

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The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: Janusz Bobulski, Kamila Pasternak

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Despite many years of effort and research, the problem of waste management is still current. So far, no fully effective waste management system has been developed. Many programs and projects improve statistics on the percentage of waste recycled every year. In these efforts, it is worth using modern Computer Vision techniques supported by artificial intelligence. In the article, we present a method of identifying plastic waste based on the asymmetry analysis of the histogram of the image containing the waste. The method is simple but effective (94%), which allows it to be implemented on devices with low computing power, in particular on microcomputers. Such de-vices will be used both at home and in waste sorting plants.

Keywords: waste management, environmental protection, image processing, computer vision

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Authors: Bharti Gupta, V. K. Kukreja

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A comprehensive numerical study is presented for the solution of time-dependent advection diffusion problems by using cubic B-spline collocation method. The linear combination of cubic B-spline basis, taken as approximating function, is evaluated using the zeros of shifted Chebyshev polynomials as collocation points in each element to obtain the best approximation. A comparison, on the basis of efficiency and accuracy, with the previous techniques is made which confirms the superiority of the proposed method. An asymptotic convergence analysis of technique is also discussed, and the method is found to be of order two. The theoretical analysis is supported with suitable examples to show second order convergence of technique. Different numerical examples are simulated using MATLAB in which the 3-D graphical presentation has taken at different time steps as well as different domain of interest.

Keywords: cubic B-spline basis, spectral norms, shifted Chebyshev polynomials, collocation points, error estimates

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Authors: Thomas Ousterhout

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In an effort to test the ability of a commercial grade EEG headset to effectively measure the N400 ERP, a replication study was conducted to see if similar results could be produced as that which used a medical grade EEG. Pictures of meaningful and meaningless hand postures were borrowed from the original author and subjects were required to perform a semantic discrimination task. The N400 was detected indicating semantic processing of the meaningfulness of the hand postures. The results corroborate those of the original author and support the use of some commercial grade EEG headsets for non-critical research applications.

Keywords: EEG, ERP, N400, semantics, congruency, gestures, emotiv

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Authors: Karlygash Adamova

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This article is focused on the KazTest as one of the most important high-stakes tests and the key tool in Kazakh language assessment. The research will also include the brief introduction to the language policy in Kazakhstan. Particularly, it is going to be changed significantly and turn from bilingualism (Kazakh, Russian) to multilingual policy (three languages - Kazakh, Russian, English). Therefore, the current status of the abovementioned languages will be described. Due to the various educational reforms in the country, the language evaluation system should also be improved and moderated. The research will present the most significant test of Kazakhstan – the KazTest, which is aimed to evaluate the Kazakh language proficiency. Assessment is an ongoing process that encompasses a wide area of knowledge upon the productive performance of the learners. Test is widely defined as a standardized or standard method of research, testing, diagnostics, verification, etc. The two most important characteristics of any test, as the main element of the assessment - validity and reliability - will also be described in this paper. Therefore, the preparation and design of the test, which is assumed to be an indicator of knowledge, and it is highly important to take into account all these properties.

Keywords: multilingualism, language assessment, testing, language policy

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Authors: Shuyi Wu, Chuang Li, Quanshui Zheng, Luping Xu

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Stretching and snipping DNA molecule by microfluidic has important application value in gene analysis by lab on a chip. Movement, deformation and fragmenting of DNA in microfluidic are typical fluid-solid coupling problems. An efficient and common simulation system for researching the movement, deformation and fragmenting of DNA by microfluidic has not been well developed. In our study, Brownian dynamics-finite element method (BD-FEM) is used to simulate the dynamic process of stretching and fragmenting DNA by contraction flow. The shape and parameters of micro-channels are changed to optimize the stretching and fragmenting properties of DNA. Our results indicate that strain rate, resulting from contraction microchannel, is the main control parameter for stretching and fragmenting DNA. There is good consistency between the simulation data and previous experimental result about the single DNA molecule behavior and averaged fragmenting properties in this study. BD-FEM method is an efficient calculating tool to research stretching and fragmenting behavior of single DNA molecule and optimize microfluidic devices for manipulating, stretching and fragmenting DNA.

Keywords: fragmenting, DNA, microfluidic, optimize.

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Authors: Nikhil Padhye, Ellen Kintz, Dan Dorci

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Recent years have seen a rising interest in study and applications of materially uniform thin-structures (plates/shells) subject to finite-bending and stretching deformations. We introduce a well-posed 2D-model involving finite-bending and stretching of thin-structures to approximate the three-dimensional equilibria. Key features of this approach include: Non-Uniform Rational B-Spline (NURBS)-based spatial discretization for finite elements, method of dynamic relaxation to predict stable equilibria, and no a priori kinematic assumption on the deformation fields. The approach is validated against the benchmark problems,and the use of NURBS for spatial discretization facilitates exact spatial representation and computation of curvatures (due to C1-continuity of interpolated displacements) for this higher-order accuracy 2D-model.

Keywords: Isogeometric Analysis, Plates/Shells , Finite Element Methods, Dynamic Relaxation

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Authors: W. Sun, W. Wen, J. Lu, A. A. Becker

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In this work, methods for determining creep properties which can be used to represent the full life until failure from miniature specimen creep tests based on analytical solutions are presented. Examples used to demonstrate the application of the methods include a miniature rectangular thin beam specimen creep test under three-point bending and a miniature two-material tensile specimen creep test subjected to a steady load. Mathematical expressions for deflection and creep strain rate of the two specimens were presented for the Kachanov-Rabotnov creep damage model. On this basis, an inverse procedure was developed which has potential applications for deriving the full life creep damage constitutive properties from a very small volume of material, in particular, for various microstructure constitutive  regions, e.g. within heat-affected zones of power plant pipe weldments. Further work on validation and improvement of the method is addressed.

Keywords: creep damage property, miniature specimen, inverse approach, finite element modeling

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Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

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Authors: Hamid Fazlollahi, Behzad Rafezy, Hassan Afshin

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There masonry infill increases the stiffness of reinforced concrete frames, thus increasing the force of the earthquake also the interaction between the frame and infill, which can have devastating effects on structures. In contrast presence of infill to increase the structural strength and stability. What is seen in the construction and design of structures has largely ignored the effects of infill and regardless infill structure and its positive and negative effects analyzes and designs, that it is not economically justified and the positive effects of positive infill to be increased and almost all of the useful capacity of moment frames used for infill. In this paper, by using ABAQUS software, reinforced concrete frame with masonry infill will be modeled, then add a mechanical rubber element to modify the interaction between the frame and infill and thus reduce the losses caused by the presence of infill explains. Finally, by comparing the analytical curves, benefits of this approach we will study and to present the results of the interaction between the frame and infill masonry needs modification and methods it will provide.

Keywords: masonry infill, mechanical rubber, reinforced concrete frame, interaction, ductility

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Authors: Amar Sabih, James Nemes

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The occurrence of internal ductile failure within the Adiabatic Shear Band (ASB) in cold-headed products presents a significant barrier in the fast-expanding cold-heading (CH) industry. The presence of internal ductile failure in cold-headed products may lead to catastrophic fracture under tensile loads despite the ductile nature of the material causing expensive industrial recalls. Therefore, this paper presents a new workability criterion that uses stress instability as an indicator to accurately reveal the locus of initiation of internal ductile failures. The concept of the instability criterion is to use the stress ratio at failure as a weighting function to indicate the initiation of ductile failure inside the ASBs. This paper presents a comprehensive experimental, metallurgical, and finite element simulation study to calculate the material constants used in this criterion.

Keywords: adiabatic sher band, ductile failure, stress instability, workability criterion

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Authors: Aliakbar Golshani, Armin Ramezanzad

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Tensile strength which is an important parameter of the rock for engineering applications is difficult to measure directly through physical experiment (i.e. uniaxial tensile test). Therefore, indirect experimental methods such as Brazilian test have been taken into consideration and some relations have been proposed in order to obtain the tensile strength for rocks indirectly. In this research, to calculate numerically the tensile strength for granitic rocks, Particle Flow Code in three-dimension (PFC3D) software were used. First, uniaxial compression tests were simulated and the tensile strength was determined for Inada granite (from a quarry in Kasama, Ibaraki, Japan). Then, by simulating Brazilian test condition for Inada granite, the tensile strength was indirectly calculated again. Results show that the tensile strength calculated numerically agrees well with the experimental results obtained from uniaxial tensile tests on Inada granite samples.

Keywords: numerical simulation, particle flow code, PFC, tensile strength, Brazilian Test

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Authors: Nurlan Smagulov, Aiman Konkabayeva, Akerke Sadykova, Arailym Serik

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Introduction. Adverse environmental factors do not immediately lead to pathological changes in the body. They can exert the growth of pre-pathology characterized by shifts in physiological, biochemical, immunological and other indicators of the body state. These disorders are unstable, reversible and indicative of body reactions. There is an opportunity to objectively judge the internal structure of the adaptive body reactions at the level of individual organs and systems. In order to obtain a stable response of the body to the chronic effects of unfavorable environmental factors of low intensity (compared to production environment factors), a time called the «lag time» is needed. The obtained results without considering this factor distort reality and, for the most part, cannot be a reliable statement of the main conclusions in any work. A technique is needed to reduce methodological errors and combine mathematical logic using statistical methods and a medical point of view, which ultimately will affect the obtained results and avoid a false correlation. Objective. Development of a methodology for assessing and predicting the environmental factors impact on the population health considering the «lag time.» Methods. Research objects: environmental and population morbidity indicators. The database on the environmental state was compiled from the monthly newsletters of Kazhydromet. Data on population morbidity were obtained from regional statistical yearbooks. When processing static data, a time interval (lag) was determined for each «argument-function» pair. That is the required interval, after which the harmful factor effect (argument) will fully manifest itself in the indicators of the organism's state (function). The lag value was determined by cross-correlation functions of arguments (environmental indicators) with functions (morbidity). Correlation coefficients (r) and their reliability (t), Fisher's criterion (F) and the influence share (R2) of the main factor (argument) per indicator (function) were calculated as a percentage. Results. The ecological situation of an industrially developed region has an impact on health indicators, but it has some nuances. Fundamentally opposite results were obtained in the mathematical data processing, considering the «lag time». Namely, an expressed correlation was revealed after two databases (ecology-morbidity) shifted. For example, the lag period was 4 years for dust concentration, general morbidity, and 3 years – for childhood morbidity. These periods accounted for the maximum values of the correlation coefficients and the largest percentage of the influencing factor. Similar results were observed in relation to the concentration of soot, dioxide, etc. The comprehensive statistical processing using multiple correlation-regression variance analysis confirms the correctness of the above statement. This method provided the integrated approach to predicting the degree of pollution of the main environmental components to identify the most dangerous combinations of concentrations of leading negative environmental factors. Conclusion. The method of assessing the «environment-public health» system (considering the «lag time») is qualitatively different from the traditional (without considering the «lag time»). The results significantly differ and are more amenable to a logical explanation of the obtained dependencies. The method allows presenting the quantitative and qualitative dependence in a different way within the «environment-public health» system.

Keywords: ecology, morbidity, population, lag time

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Authors: I. Algul, G. Akgun, H. Kurtaran

Abstract:

Dynamic analysis of composite doubly curved panels with variable thickness subjected to different pulse types using Generalized Differential Quadrature method (GDQ) is presented in this study. Panels with variable thickness are used in the construction of aerospace and marine industry. Giving variable thickness to panels can allow the designer to get optimum structural efficiency. For this reason, estimating the response of variable thickness panels is very important to design more reliable structures under dynamic loads. Dynamic equations for composite panels with variable thickness are obtained using virtual work principle. Partial derivatives in the equation of motion are expressed with GDQ and Newmark average acceleration scheme is used for temporal discretization. Several examples are used to highlight the effectiveness of the proposed method. Results are compared with finite element method. Effects of taper ratios, boundary conditions and loading type on the response of composite panel are investigated.

Keywords: differential quadrature method, doubly curved panels, laminated composite materials, small displacement

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