Search results for: damage prediction models

Authors: Mustafa Saeed Omar

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The formula which contains the maximum increase of mean bond length, melting entropy and critical particle radius is used to calculate lattice volume in nanoscale size crystals of Ga₂Se₃. This compound belongs to the binary group of III₂VI₃. The critical radius is calculated from the values of the first surface atomic layer height which is equal to 0.336nm. The size-dependent mean bond length is calculated by using an equation-free from fitting parameters. The size-dependent lattice parameter then is accordingly used to calculate the size-dependent lattice volume. The lattice size in the nanoscale region increases to about 77.6 A³, which is up to four times of its bulk state value 19.97 A³. From the values of the nanosize scale dependence of lattice volume, the nanoscale size dependence of melting temperatures is calculated. The melting temperature decreases with the nanoparticles size reduction, it becomes zero when the radius reaches to its critical value. Bulk melting temperature for Ga₂Se₃, for example, has values of 1293 K. From the size-dependent melting temperature and mean bond length, the size-dependent lattice thermal expansion is calculated. Lattice thermal expansion decreases with the decrease of nanoparticles size and reaches to its minimum value as the radius drops down to about 5nm.

Keywords: Ga₂Se₃, lattice volume, lattice thermal expansion, melting point, nanoparticles

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Authors: B. Varaprasad, C. Srinivasa Rao

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In the manufacturing sector, hard turning has emerged as vital machining process for cutting hardened steels. Besides many advantages of hard turning operation, one has to implement to achieve close tolerances in terms of surface finish, high product quality, reduced machining time, low operating cost and environmentally friendly characteristics. In the present study, three-dimensional CAE (Computer Aided Engineering) based simulation of  hard turning by using commercial software DEFORM 3D has been compared to experimental results of  stresses, temperatures and tool forces in machining of AISI D3 steel using mixed Ceramic inserts (CC6050). In the present analysis, orthogonal cutting models are proposed, considering several processing parameters such as cutting speed, feed, and depth of cut. An exhaustive friction modeling at the tool-work interfaces is carried out. Work material flow around the cutting edge is carefully modeled with adaptive re-meshing simulation capability. In process simulations, feed rate and cutting speed are constant (i.e.,. 0.075 mm/rev and 155 m/min), and analysis is focused on stresses, forces, and temperatures during machining. Close agreement is observed between CAE simulation and experimental values.

Keywords: hard turning, computer aided engineering, computational machining, finite element method

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Authors: Sathwik Sarvadevabhatla Kasyap, Kostas Senetakis

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The mechanical behavior of geological materials is very complex, and this complexity is related to the discrete nature of soils and rocks. Characteristics of a material at the grain scale such as particle size and shape, surface roughness and morphology, and particle contact interface are critical to evaluate and better understand the behavior of discrete materials. This study investigates experimentally the micro-mechanical behavior of quartz sand grains with emphasis on the influence of the presence of microparticles in their contact region. The outputs of the study provide some fundamental insights on the contact mechanics behavior of artificially coated grains and can provide useful input parameters in the discrete element modeling (DEM) of soils. In nature, the contact interfaces between real soil grains are commonly observed with microparticles. This is usually the case of sand-silt and sand-clay mixtures, where the finer particles may create a coating on the surface of the coarser grains, altering in this way the micro-, and thus the macro-scale response of geological materials. In this study, the micro-mechanical behavior of Leighton Buzzard Sand (LBS) quartz grains, with interference of different microparticles at their contact interfaces is studied in the laboratory using an advanced custom-built inter-particle loading apparatus. Special techniques were adopted to develop the coating on the surfaces of the quartz sand grains so that to establish repeatability of the coating technique. The characterization of the microstructure of coated particles on their surfaces was based on element composition analyses, microscopic images, surface roughness measurements, and single particle crushing strength tests. The mechanical responses such as normal and tangential load – displacement behavior, tangential stiffness behavior, and normal contact behavior under cyclic loading were studied. The behavior of coated LBS particles is compared among different classes of them and with pure LBS (i.e. surface cleaned to remove any microparticles). The damage on the surface of the particles was analyzed using microscopic images. Extended displacements in both normal and tangential directions were observed for coated LBS particles due to the plastic nature of the coating material and this varied with the variation of the amount of coating. The tangential displacement required to reach steady state was delayed due to the presence of microparticles in the contact region of grains under shearing. Increased tangential loads and coefficient of friction were observed for the coated grains in comparison to the uncoated quartz grains.

Keywords: contact interface, microparticles, micro-mechanical behavior, quartz sand

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Authors: Lourdes Hanna, Edward Poluyi, Chibuikem Ikwuegbuenyi, Eghosa Morgan, Grace Imaguezegie

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Background: Degeneration of the central nervous system (CNS), also known as neurodegeneration, describes an age-associated progressive loss of the structure and function of neuronal materials, leading to functional and mental impairments. Main body: Neuroinflammation contributes to the continuous worsening of neurodegenerative states which are characterised by functional and mental impairments due to the progressive loss of the structure and function of neu-ronal materials. Some of the most common neurodegenerative diseases include Alzheimer’s disease (AD), Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS). Whilst neuroinflammation is a key contributor to the progression of such disease states, it is not the single cause as there are multiple factors which contribute. Theoretically, non-steroidal anti-inflammatory drugs (NSAIDs) have potential to target neuroinflammation to reduce the severity of disease states. Whilst some animal models investigating the effects of NSAIDs on the risk of neurodegenerative diseases have shown a beneficial effect, this is not the same finding. Conclusion: Further investigation using more advanced research methods is required to better understand neuroinflammatory pathways and understand if there is still a potential window for NSAID efficacy.

Keywords: intervention, central nervous system, neurodegeneration, neuroinflammation

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Authors: Ivan Todorović, Stefan Komazec, Jelena Anđelković-Labrović, Ondrej Jaško, Miha Marič

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Micro, small and medium enterprises (MSME) are important factors of the economy in each country. Recent years have brought increased number and higher sophistication of scientific research related to numerous aspects of entrepreneurship. Various authors try to find the positive correlation between entrepreneur's personal characteristics, skills and knowledge on one hand, and company growth and success of small business on the other hand. Different models recognize staff as one of the key elements in every organizational system. Human resource (HR) function is present in almost all large companies, despite the geographical location or industry. Small and medium enterprises also often have separate positions or even departments for HR administration. However, in early stages of organizational life cycle human resources are usually managed by the founder, entrepreneur. In this paper we want to question whether the companies where founder, entrepreneur, recognizes the significance of human capital in the organization and understands the importance of HR management have higher growth rate and better business results. The findings of this research can be implemented in practice, but also in the academia, for improving the curricula related to the MSME and entrepreneurship.

Keywords: entrepreneurship, MSME, micro small and medium enterprises, company growth, human resources, HR management

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Authors: Tahseen Saad, Halim Ceylan, Jonathan Weaver, Osman Nuri Çelik, Onur Gungor Sahin

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A new concept of uniform delay offset dependent mathematical optimization problem is derived as the main objective for this study using a differential evolution algorithm. To control the coordination problem, which depends on offset selection and to estimate uniform delay based on the offset choice in a traffic signal network. The assumption is the periodic sinusoidal function for arrival and departure patterns. The cycle time is optimized at the entry links and the optimized value is used in the non-entry links as a common cycle time. The offset optimization algorithm is used to calculate the uniform delay at each link. The results are illustrated by using a case study and are compared with the canonical uniform delay model derived by Webster and the highway capacity manual’s model. The findings show new model minimizes the total uniform delay to almost half compared to conventional models. The mathematical objective function is robust. The algorithm convergence time is fast.

Keywords: area traffic control, traffic flow, differential evolution, sinusoidal periodic function, uniform delay, offset variable

Procedia PDF Downloads 263

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: Preston Nabors, Nasseh Tabrizi

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Portable Document Format (PDF) files have gained significant popularity for sharing and distributing documents due to their universal compatibility. However, the widespread use of PDF files has made them attractive targets for cybercriminals, who exploit vulnerabilities to deliver malware and compromise the security of end-user systems. This paper reviews notable contributions in PDF malware detection, including static, dynamic, signature-based, and hybrid analysis. It presents a comprehensive examination of PDF malware detection techniques, focusing on the emerging threat of adversarial sampling and the need for robust defense mechanisms. The paper highlights the vulnerability of machine learning classifiers to evasion attacks. It explores adversarial sampling techniques in PDF malware detection to produce mimicry and reverse mimicry evasion attacks, which aim to bypass detection systems. Improvements for future research are identified, including accessible methods, applying adversarial sampling techniques to malicious payloads, evaluating other models, evaluating the importance of features to malware, implementing adversarial defense techniques, and conducting comprehensive examination across various scenarios. By addressing these opportunities, researchers can enhance PDF malware detection and develop more resilient defense mechanisms against adversarial attacks.

Keywords: adversarial attacks, adversarial defense, adversarial machine learning, intrusion detection, PDF malware, malware detection, malware detection evasion

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Authors: Chengwei Wang, Shuqing Xu, Philipp M. Schlüter

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The genus Ophrys is remarkable for its mimicry, flower-lip closely resembling pollinator females in a species-specific manner. Therefore, floral traits associated with pollinator attraction, especially scent, are suitable models for investigating the molecular basis of adaption, speciation, and evolution. Within the two Ophrys species groups: O. sphegodes (S) and O. fusca (F), pollinator shifts among the same insect species have taken place. Preliminary data suggest that they involve a comparable hydrocarbon profile in their scent, which is mainly composed of alkanes and alkenes. Genes encoding stearoyl-acyl carrier protein desaturases (SAD) involved in alkene biosynthesis have been identified in the S group. This study aims to investigate the control and parallel evolution of ecologically significant alkene production in Ophrys. Owing to the central role those SAD genes play in determining positioning of the alkene double-bonds, a detailed understanding of their functional mechanism and of regulatory aspects is of utmost importance. We have identified 5 transcription factors potentially related to SAD expression in O. sphegodes which belong to the MYB, GTE, WRKY, and MADS families. Ultimately, our results will contribute to understanding genes important in the regulatory control of floral scent synthesis.

Keywords: floral traits, transcription factors, biosynthesis, parallel evolution

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Authors: James M. Wakiru, Liliane Pintelon, Peter Muchiri, Peter Chemweno

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The fast-changing business and operational environment are forcing organizations to adopt asset performance management strategies, not only to reduce costs but also maintain operational and production policies while addressing demand. To attain optimal asset performance management, a framework that ensures a continuous and systematic approach to analyzing an organization’s current maturity level and expected improvement regarding asset maintenance processes, strategies, technologies, capabilities, and systems is essential. Moreover, this framework while addressing maintenance-intensive organizations should consider the diverse business, operational and technical context (often dynamic) an organization is in and realistically prescribe or relate to the appropriate tools and systems the organization can potentially employ in the respective level, to improve and attain their maturity goals. This paper proposes an asset maintenance maturity model to assess the current capabilities, strength and weaknesses of maintenance processes an organization is using and analyze gaps for improvement via structuring set levels of achievement. At the epicentre of the proposed framework is the utilization of maintenance objective selected by an organization for various maintenance optimization programs. The framework adapts the Capability Maturity Model of assessing the maintenance process maturity levels in the organization.

Keywords: asset maintenance, maturity models, maintenance objectives, optimization

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Authors: A. N. Fouda

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A novel well identified hexagonal graphene oxide (GO) nano-sheets were synthesized using modified Hummer method. Low temperature thermal reduction at 350°C in air ambient was performed. After thermal reduction, typical few layers of thermal reduced GO (TRGO) with dimension of few hundreds nanometers were observed using high resolution transmission electron microscopy (HRTEM). GO has a lot of structure models due to variation of the preparation process. Determining the atomic structure of GO is essential for a better understanding of its fundamental properties and for realization of the future technological applications. Structural characterization was identified by x-ray diffraction (XRD), Fourier transform infra-red spectroscopy (FTIR) measurements. A comparison between exper- imental and theoretical IR spectrum were done to confirm the match between experimentally and theoretically proposed GO structure. Partial overlap of the experimental IR spectrum with the theoretical IR was confirmed. The electrochemical properties of TRGO nano-sheets as electrode materials for supercapacitors were investigated by cyclic voltammetry and electrochemical impedance spectroscopy (EIS) measurements. An enhancement in supercapacitance after reduction was confirmed and the area of the CV curve for the TRGO electrode is larger than those for the GO electrode indicating higher specific capacitance which is promising in super-capacitor applications

Keywords: hexagonal graphene oxide, thermal reduction, cyclic voltammetry

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: B. Adcock, H. van Rensburg

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Education is ever-changing to keep up with innovative technological development and the rapid acceleration of globalisation. This chapter introduces the historical development and transformation of teaching in distance education from correspondence to on-line learning in Queensland universities. It furthermore investigates changes to the delivery models of distance education that have impacted on teaching at tertiary level in Queensland, and reflects on the social changes that have taken place during the past 100 years. This includes an analysis of the following five different periods in time: Foundation period (1911-1919) including World War I; 1920-1939 including the Great Depression; 1940-1970s, including World War II and the post war reconstruction; and the current technological era (1980s to present). In Queensland, the concept of distance education was begun by the University of Queensland (UQ) in 1911, when it began offering extension courses. The introduction of modern technology, in the form of electronic delivery, dramatically changed tertiary distance education due to political initiatives. The inclusion of electronic delivery in education signifies change at many levels, including policy, pedagogy, curriculum and governance. Changes in delivery not only affect the way study materials are delivered, but also the way courses are be taught and adjustments made by academics to their teaching methods.

Keywords: distance education, innovative technological development, on line education, tertiary education

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Authors: Mindaye Teshome, Evaldo Muñoz Braz, Carlos M. M. Eleto Torres, Patricia Mattos

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Sustainable forest management planning requires up-to-date information on the structure, standing volume, biomass, and growth rate of trees from a given forest. This kind of information is lacking in many forests in Ethiopia. The objective of this study was to quantify the population structure, diameter growth rate, and standing volume of wood from Juniperus procera trees in the Chilimo forest. A total of 163 sample plots were set up in the forest to collect the relevant vegetation data. Growth ring measurements were conducted on stem disc samples collected from 12 J. procera trees. Diameter and height measurements were recorded from a total of 1399 individual trees with dbh ≥ 2 cm. The growth rate, maximum current and mean annual increments, minimum logging diameter, and cutting cycle were estimated, and alternative cutting cycles were established. Using these data, the harvestable volume of wood was projected by alternating four minimum logging diameters and five cutting cycles following the stand table projection method. The results show that J. procera trees have an average density of 183 stems ha⁻¹, a total basal area of 12.1 m² ha⁻¹, and a standing volume of 98.9 m³ ha⁻¹. The mean annual diameter growth ranges between 0.50 and 0.65 cm year⁻¹ with an overall mean of 0.59 cm year⁻¹. The population of J. procera tree followed a reverse J-shape diameter distribution pattern. The maximum current annual increment in volume (CAI) occurred at around 49 years when trees reached 30 cm in diameter. Trees showed the maximum mean annual increment in volume (MAI) around 91 years, with a diameter size of 50 cm. The simulation analysis revealed that 40 cm MLD and a 15-year cutting cycle are the best minimum logging diameter and cutting cycle. This combination showed the largest harvestable volume of wood potential, volume increments, and a 35% recovery of the initially harvested volume. It is concluded that the forest is well stocked and has a large amount of harvestable volume of wood from J. procera trees. This will enable the country to partly meet the national wood demand through domestic wood production. The use of the current population structure and diameter growth data from tree ring analysis enables the exact prediction of the harvestable volume of wood. The developed model supplied an idea about the productivity of the J. procera tree population and enables policymakers to develop specific management criteria for wood harvesting.

Keywords: logging, growth model, cutting cycle, minimum logging diameter

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Authors: Shatabdi Goon

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OBJECTIVE: To determine the prevalence and associations between breakfast skipping and health status for university professionals in Bangladesh. DESIGN: A cross-sectional descriptive study design was performed using information on respondent’s sociodemographic status and eating behavior. Factors associated with breakfast skipping were identified using multivariate regression models. SETTINGS: Data obtained from a representative sample (n 120) of university professionals randomly selected from two distinct universities in Dhaka city, Bangladesh. SUBJECT: A total number of one hundred and twenty university professionals with a mean age of 29 years. RESULT: Results indicated that approximately 35.8% of the sample skipped breakfast. Gender was the only statistically significant sociodemographic variable, with females skipping at over two times the rate of males (OR 95% CI: 1.9; 0.90-4.13). The reasons given for skipping breakfast were almost exclusively habit (39.5%), work pressure (23.2%) and lack of time (16.2%). Skippers were significantly more likely to be obese (OR 2.4; 95% CI 1.02- 5.7), less energetic (OR 3.5; 95% CI 1.5-8.6), associated with health problems (OR 4.3; 95% CI 1.8- 10.17) and eating tendency of fast food (OR 2.5; 95% CI 1.13 - 5.5). Gastric and heart burn (X2=4.19, p<0.05) and high blood pressure (X2=5.027, p<0.05) were detected among 34.9% and 27.9 % of those employees respectively identified as breakfast skippers and they showed significantly high prevalence. CONCLUSION: Breakfast skipping is highly prevalent among university professionals with significant association of different health problems in Bangladesh. Health promotion strategies should be used to encourage all adults to eat breakfast regularly.

Keywords: breakfast, healthy lifestyle, breakfast skipping, health status, university professionals

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Authors: Lahcen Daoudi, Fatima Zahra Omdi, Abldelali Gourfi

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In Morocco, as in most Mediterranean countries, water scarcity is a common situation because of low and unevenly distributed rainfall. The expansions of irrigated lands, as well as the growth of urban and industrial areas and tourist resorts, contribute to an increase of water demand. Therefore in the 1960s Morocco embarked on an ambitious program to increase the number of dams to boost water retention capacity. However, the decrease in the capacity of these reservoirs caused by sedimentation is a major problem; it is estimated at 75 million m3/year. Dams and reservoirs became unusable for their intended purposes due to sedimentation in large rivers that result from soil erosion. Soil erosion presents an important driving force in the process affecting the landscape. It has become one of the most serious environmental problems that raised much interest throughout the world. Monitoring soil erosion risk is an important part of soil conservation practices. The estimation of soil loss risk is the first step for a successful control of water erosion. The aim of this study is to estimate the soil loss risk and its spatial distribution in the different fields of Morocco and to prioritize areas for soil conservation interventions. The approach followed is the Revised Universal Soil Loss Equation (RUSLE) using remote sensing and GIS, which is the most popular empirically based model used globally for erosion prediction and control. This model has been tested in many agricultural watersheds in the world, particularly for large-scale basins due to the simplicity of the model formulation and easy availability of the dataset. The spatial distribution of the annual soil loss was elaborated by the combination of several factors: rainfall erosivity, soil erodability, topography, and land cover. The average annual soil loss estimated in several basins watershed of Morocco varies from 0 to 50t/ha/year. Watersheds characterized by high-erosion-vulnerability are located in the North (Rif Mountains) and more particularly in the Central part of Morocco (High Atlas Mountains). This variation of vulnerability is highly correlated to slope variation which indicates that the topography factor is the main agent of soil erosion within these basin catchments. These results could be helpful for the planning of natural resources management and for implementing sustainable long-term management strategies which are necessary for soil conservation and for increasing over the projected economic life of the dam implemented.

Keywords: soil loss, RUSLE, GIS-remote sensing, watershed, Morocco

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Authors: E. Feulefack Songong, A. Zingoni

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A vibration is a mechanical phenomenon whereby oscillations occur about an equilibrium point. Although vibrations can be linear or nonlinear depending on the basic components of the system, the interest is mostly pointed towards nonlinear vibrations. This is because most structures around us are to some extent nonlinear and also because we need more accurate values in an analysis. The goal of this research is the integration of nonlinearities in the development and validation of structural models and to ameliorate the resistance of structures when subjected to loads. Although there exist many types of nonlinearities, this thesis will mostly focus on the vibration of free and undamped systems incorporating nonlinearity due to stiffness. Nonlinear stiffness has been a concern to many engineers in general and Civil engineers in particular because it is an important factor that can bring a good modification and amelioration to the response of structures when subjected to loads. The analysis of systems will be done analytically and then numerically to validate the analytical results. We will first show the benefit and importance of stiffness nonlinearity when it is implemented in the structure. Secondly, We will show how its integration in the structure can improve not only the structure’s performance but also its response when subjected to loads. The results of this study will be valuable to practicing engineers as well as industry practitioners in developing better designs and tools for their structures and mechanical devices. They will also serve to engineers to design lighter and stronger structures and to give good predictions as for the behavior of structures when subjected to external loads.

Keywords: elastic foundation, nonlinear, plates, stiffness, structures, vibration

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Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

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In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

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Authors: Arezoo Fallahi‎

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Background: Exercise behavior (EB) has a significant impact on infertility, but the magnitude of the effect is not easily determined. The aim of the present study was to assess the effect of social support and self-regulation, as external and internal factors, on changes in exercise behavior among infertile women. Methods: For a cross-sectional study conducted in Sanandaj (Iran) in 2020, we recruited infertile women (n=483) from 35 comprehensive healthcare centers by means of convenience sampling. Standardized face-to-face interviews were conducted using established and reliable instruments for the assessment of EB, social support, and self-regulation. Logistic regression models were applied to assess the association between EB, social support and self-regulation. Results: The majority of the participants (56.7%) had secondary infertility, while 70.8% of them did not perform any exercise. Self-regulation and social support were significantly higher in women with secondary infertility than in those with primary infertility (p < 0.01). Self-regulation was significantly lower in women whose height was below 160 centimeters (cm) (p<0.05). Social support was significantly higher among participants aged ≥ 35 years and weighing ≥ 60 kilograms (kg) (p < 0.01). The odds of EB adoption increased with self-regulation and social support (OR=1.05, 95% CI=1.02-1.09, p <0.01), (OR=1.06, 95% CI=1.02-1.11, p <0.01). Conclusion: Social support and self-regulation almost equally influenced EB in infertile women. Designing support and consultation programs can be considered in encouraging infertile women to do exercise in future research.

Keywords: social support, regulation, infertility, women, exercise

Procedia PDF Downloads 78

Authors: Shuang Qiu, Zhipeng Chen, Lingfeng Wang, Shijian Ge

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Biowastes are a concern due to the large amounts of commercial food required for model animals during the biomedical research. Searching for sustainable food alternatives with negligible physiological effects on animals is critical to solving or reducing this challenge. Microalgae have been demonstrated as suitable for both human consumption and animal feed in addition to biofuel and bioenergy applications. In this study, the possibility of using Chlorella vulgaris and Senedesmus obliquus as a feed replacement to Drosophila melanogaster, one of the fly models commonly used in biomedical studies, was investigated to assess the fly locomotor activity, motor pattern, lifespan, and body weight. Compared to control, flies fed on 60% or 80% (w/w) microalgae exhibited varied walking performance including travel distance and apparent step size, and flies treated with 40% microalgae had shorter lifespans and decreased body weight. However, the 20% microalgae treatment showed no statistical differences in all parameters tested with respect to the control. When partially including 20% microalgae in the standard food, it can annually reduce the food waste (~ 202 kg) by 22.7 % and save $ 7,200 of the food cost, offering an environmentally superior and cost-effective food alternative without compromising physiological performance.

Keywords: animal feed, Chlorella vulgaris, Drosophila melanogaster, food waste, microalgae

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Authors: Kemka C. Ihemelandu, Chukwuemeka U. Ihemelandu

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The incidence of melanoma has been increasing rapidly over the past two decades, making melanoma a current public health crisis. Unfortunately, even as screening efforts continue to expand in an effort to ameliorate the death rate from melanoma, there is a need to improve diagnostic accuracy to decrease misdiagnosis. Artificial intelligence (AI) a new frontier in patient care has the ability to improve the accuracy of melanoma diagnosis. Convolutional neural network (CNN) a form of deep neural network, most commonly applied to analyze visual imagery, has been shown to outperform the human brain in pattern recognition. However, there are noted limitations with the accuracy of the CNN models. Our aim in this study was the optimization of convolutional neural network algorithms for the automated diagnosis of melanoma. We hypothesized that Optimal selection of the momentum and batch hyperparameter increases model accuracy. Our most successful model developed during this study, showed that optimal selection of momentum of 0.25, batch size of 2, led to a superior performance and a faster model training time, with an accuracy of ~ 83% after nine hours of training. We did notice a lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone. Training set image transformations did not result in a superior model performance in our study.

Keywords: melanoma, convolutional neural network, momentum, batch hyperparameter

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Authors: Faraj M. Elkhatri

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The spatial and temporal distribution of diagenetic alterations related impact on the reservoir quality of the Sarir Formation. ( present day burial depth of about 9000 feet) Depositional facies and diagenetic alterations are the main controls on reservoir quality of Sarir Formation Sirt Basin Libya; these based on lithology and grain size as well as authigenic clay mineral types and their distributions. However, petrology investigation obtained on study area with five sandstone wells concentrated on main rock components and the parameters that may have impacts on reservoirs. the main authigenic clay minerals are kaolinite and dickite, these investigations have confirmed by X.R.D analysis and clay fraction. mainly Kaolinite and Dickite were extensively presented on all of wells with high amounts. As well as trace of detrital smectite and less amounts of illitized mud-matrix are possibly find by SEM image. Thin layers of clay presented as clay-grain coatings in local depth interpreted as remains of dissolved clay matrix is partly transformed into kaolinite adjacent and towards pore throat. This also may have impacts on most of the pore throats of this sandstone which are open and relatively clean with some fine martial have been formed on occluded pores. This material is identified by EDS analysis to be collections of not only kaolinite booklets but also small disaggregated kaolinite platelets derived from the disaggregation of larger kaolinite booklets. These patches of kaolinite not only fill this pore but also coat some of the surrounding framework grains. Quartz grains often enlarged by authigenic quartz overgrowths partially occlude and reduce porosity. Scanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM) was conducted on the post-test samples to examine any mud filtrate particles that may be in the pore throats. Semi-qualitative elemental data on selected minerals observed during the SEM study were obtained through the use of an Energy Dispersive Spectroscopy (EDS) unit. The samples showed mostly clean open pore throats with limited occlusion by kaolinite. very fine-grained elemental combinations (Si/Al/Na/Cl, Si/Al Ca/Cl/Ti, and Qtz/Ti) have been identified and conformed by EDS analysis. However, the identification of the fine grained disaggregated material as mainly kaolinite though study area.

Keywords: pore throat, fine migration, formation damage, solids plugging, porosity loss

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Authors: P. Nafisi Poor, P. Javid

Abstract:

Over the past few years, the idea of adaptive buildings and specifically, adaptive building energy management systems (ABEMS) has become popular. Well-performed management in terms of energy is to create a balance between energy consumption and user comfort; therefore, in new energy management models, efficient energy consumption is not the sole factor and the user's comfortability is also considered in the calculations. One of the main ways of measuring this factor is by analyzing user feedback on the conditions to understand whether they are satisfied with conditions or not. This paper provides a comprehensive review of recent approaches towards energy management systems based on users' feedbacks and subsequently performs a comparison between them premised upon their efficiency and accuracy to understand which approaches were more accurate and which ones resulted in a more efficient way of minimizing energy consumption while maintaining users' comfortability. It was concluded that the highest accuracy rate among the presented works was 95% accuracy in determining satisfaction and up to 51.08% energy savings can be achieved without disturbing user’s comfort. Considering the growing interest in designing and developing adaptive buildings, these studies can support diverse inquiries about this subject and can be used as a resource to support studies and researches towards efficient energy consumption while maintaining the comfortability of users.

Keywords: adaptive buildings, energy efficiency, intelligent buildings, user comfortability

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Authors: Ramiro Gustavo Ramirez Camacho, Waldir De Oliveira, Eraldo Cruz Dos Santos, Edna Raimunda Da Silva, Tania Marie Arispe Angulo, Carlos Eduardo Alves Da Costa, Tânia Cristina Alves Dos Reis

Abstract:

It presents a preliminary design methodology of an axial fan based on the lift wing theory and the potential vortex hypothesis. The literature considers a study of acoustic and engineering expertise to model a fan with low noise. Axial fans with inadequate intake geometry, often suffer poor condition of the flow at the entrance, varying from velocity profiles spatially asymmetric to swirl floating with respect to time, this produces random forces acting on the blades. This produces broadband gust noise which in most cases triggers the tonal noise. The analysis of the axial flow fan will be conducted for the solution of the Navier-Stokes equations and models of turbulence in steady and transitory (RANS - URANS) 3-D, in order to find an efficient aerodynamic design, with low noise and suitable for industrial installation. Therefore, the process will require the use of computational optimization methods, aerodynamic design methodologies, and numerical methods as CFD- Computational Fluid Dynamics. The objective is the development of the methodology of the construction axial fan, provide of design the geometry of the blade, and evaluate aerodynamic performance

Keywords: Axial fan design, CFD, Preliminary Design, Optimization

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Authors: Semra Sirin Kiris

Abstract:

Nonlinear dynamic analysis is permitted to be used for structures without any restrictions. The important issue is the selection of the design earthquake to conduct the analyses since quite different response may be obtained using ground motion records at the same general area even resulting from the same earthquake. In seismic design codes, the method requires scaling earthquake records based on site response spectrum to a specified hazard level. Many researches have indicated that this limitation about selection can cause a large scatter in response and other charecteristics of ground motion obtained in different manner may demonstrate better correlation with peak seismic response. For this reason influence of eleven different ground motion parameters on the peak displacement of reinforced concrete systems is examined in this paper. From conducting 7020 nonlinear time history analyses for single degree of freedom systems, the most effective earthquake parameters are given for the range of the initial periods and strength ratios of the structures. In this study, a hysteresis model for reinforced concrete called Q-hyst is used not taken into account strength and stiffness degradation. The post-yielding to elastic stiffness ratio is considered as 0.15. The range of initial period, T is from 0.1s to 0.9s with 0.1s time interval and three different strength ratios for structures are used. The magnitude of 260 earthquake records selected is higher than earthquake magnitude, M=6. The earthquake parameters related to the energy content, duration or peak values of ground motion records are PGA(Peak Ground Acceleration), PGV (Peak Ground Velocity), PGD (Peak Ground Displacement), MIV (Maximum Increamental Velocity), EPA(Effective Peak Acceleration), EPV (Effective Peak Velocity), teff (Effective Duration), A95 (Arias Intensity-based Parameter), SPGA (Significant Peak Ground Acceleration), ID (Damage Factor) and Sa (Spectral Response Spectrum).Observing the correlation coefficients between the ground motion parameters and the peak displacement of structures, different earthquake parameters play role in peak displacement demand related to the ranges formed by the different periods and the strength ratio of a reinforced concrete systems. The influence of the Sa tends to decrease for the high values of strength ratio and T=0.3s-0.6s. The ID and PGD is not evaluated as a measure of earthquake effect since high correlation with displacement demand is not observed. The influence of the A95 is high for T=0.1 but low related to the higher values of T and strength ratio. The correlation of PGA, EPA and SPGA shows the highest correlation for T=0.1s but their effectiveness decreases with high T. Considering all range of structural parameters, the MIV is the most effective parameter.

Keywords: earthquake parameters, earthquake resistant design, nonlinear analysis, reinforced concrete

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Authors: Nicolae Daniel Stoica, Ion Mierlus Mazilu

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This work is one of numerical research and aims to address the issue of the design of new buildings in a 3D location of existing buildings. In today's continuous development and congestion of urban centers is a big question about the influence of the new buildings on an already existent vicinity site. Thus, in this study, we tried to focus on how existent buildings may be affected by any newly constructed buildings and in how far this influence is really decreased. The problem of modeling the influence of interaction between buildings is not simple in any area in the world, and neither in Romania. Unfortunately, most often the designers not done calculations that can determine how close to reality these 3D influences nor the simplified method and the more superior methods. In the most literature making a "shield" (the pilots or molded walls) is absolutely sufficient to stop the influence between the buildings, and so often the soil under the structure is ignored in the calculation models. The main causes for which the soil is neglected in the analysis are related to the complexity modeling of interaction between soil and structure. In this paper, based on a new simple but efficient methodology we tried to determine for a lot of study cases the influence, in terms of assessing the interaction land structure on the behavior of structures that influence a new building on an existing one. The study covers additional subsidence that may occur during the execution of new works and after its completion. It also highlighted the efforts diagrams and deflections in the soil for both the original case and the final stage. This is necessary to see to what extent the expected impact of the new building on existing areas.

Keywords: soil, structure, interaction, piles, earthquakes

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Authors: Leonardo Ramirez Lopez, Edward Guillen Pinto, Carlos Ramos Linares

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The controversy brought about by the increasing use of mHealth apps and their effectiveness for disease prevention and diagnosis calls for immediate control. Although a critical topic in research areas such as medicine, engineering, economics, among others, this issue lacks reliable implementation models. However, projects such as Open Web Application Security Project (OWASP) and various studies have helped to create useful and reliable apps. This research is conducted under a quality model to optimize two mHealth apps for older adults. Results analysis on the use of two physical activity monitoring apps - AcTiv (physical activity) and SMCa (energy expenditure) - is positive and ideal. Through a theoretical and practical analysis, precision calculations and personal information control of older adults for disease prevention and diagnosis were performed. Finally, apps are validated by a physician and, as a result, they may be used as health monitoring tools in physical performance centers or any other physical activity. The results obtained provide an effective validation model for this type of mobile apps, which, in turn, may be applied by other software developers that along with medical staff would offer digital healthcare tools for elderly people.

Keywords: model, validation, effective, healthcare, elderly people, mobile app

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Authors: Vincent Andrew Cappellano

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In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

Abstract:

Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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Authors: Yafa Haron, Hanna Adami

Abstract:

Background: World Health Organization emphasizes the contribution of nurses in planning and implementing health policies and reforms. Aim: To evaluate nursing students’ attitudes towards nurses’ involvement in health policy issues. Methods: Mixed-methods; qualitative and quantitative – a descriptive study. Participants - nursing students who were enrolled in their last year in the undergraduate program (BSN). Qualitative data included two open-ended questions: What is health policy and what is the importance of studying health policy, and 18 statements on the Likert Scale range 1-5. Results: Qualitativeanalysisrevealed that the majority of students defined health policy as a set of rules and regulations that defined procedures, borders, and proper conduct. 73% of students responded that nurses should be active in policymaking, but only 22% thought that nurses were currently involved in political issues. 28% thought that nurses do not have the knowledge and the time needed (60%) for political activity. 77% thought that the work environment did not encourage nurses to be politically active. Nursing students are aware of the importance towards nurses’ involvement in health policy issues, however, they do not have role models based on their low evaluation regarding nurses’ involvement in the health policy decision making process at the local or national level. Conclusions: Results emphasize the importance and the need of implementation the recommendation to include “advance policy changes” as core competency in nursing education and practice.

Keywords: health policy, nursing education, health systems, student perceptions

Procedia PDF Downloads 85