Search results for: Random Kernel Density

Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

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In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

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Authors: Gadisa Demie, Mesele Negash, Zerihun Asrat, Lojka Bohdan

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Deforestation and forest degradation in the tropics have led to significant carbon (C) emissions. Agroforestry (AF) is a suitable land-use option for tackling such declines in ecosystem services, including climate change mitigation. However, it is unclear how biomass models, AF practices, and socio-ecological factors determine these roles, which hinders the implementation of climate change mitigation initiatives. This study aimed to estimate the ecosystem C stocks of the studied AF practices in relation to socio-ecological variables in central Ethiopia. Out of 243 AF farms inventoried, 108 were chosen at random from three AF practices to estimate their biomass and soil organic carbon. A total of 432 soil samples were collected from 0–30 and 30–60 cm soil depths; 216 samples were taken for each soil organic carbon fraction (%C) and bulk density computation. The study found that the currently developed allometric equations were the most accurate to estimate biomass C for trees growing in the landscape when compared to previous models. The study found higher overall biomass C in woodlots (165.62 Mg ha-¹) than in homegardens (134.07 Mg ha-¹) and parklands (19.98 Mg ha-¹). Conversely, overall, SOC was higher for homegardens (143.88 Mg ha-¹), but lower for parklands (53.42 Mg ha-¹). The ecosystem C stock was comparable between homegardens (277.95 Mg ha-¹) and woodlots (275.44 Mg ha-¹). The study found that elevation, wealthy levels, AF farm age, and size have a positive and significant (P < 0.05) effect on overall biomass and ecosystem C stocks but non-significant with slope (P > 0.05). Similarly, SOC increased with increasing elevation, AF farm age, and wealthy status but decreased with slope and non-significant with AF farm size. The study also showed that species diversity had a positive (P <0.05) effect on overall biomass C stocks in homegardens. The overall study highlights that AF practices have a great potential to lock up more carbon in biomass and soils; however, these potentials were determined by socioecological variables. Thus, these factors should be considered in management strategies that preserve trees in agricultural landscapes in order to mitigate climate change and support the livelihoods of farmers.

Keywords: agricultural landscape, biomass, climate change, soil organic carbon

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Authors: Habte Tadesse Likassa, Bacha Edosa

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Customer’s satisfaction was very important thing that is required for the existence of banks to be more productive and success in any organization and business area. The main goal of the study is assessing and identifying factors that influence customer’s satisfaction in West Shoa Zone of Commercial Bank of Ethiopia (Holeta, Ginchi, Ambo, Gedo and Bako). Stratified random sampling procedure was used in the study and by using simple random sampling (lottery method) 520 customers were drawn from the target population. By using Probability Proportional Size Techniques sample size for each branch of banks were allocated. Both descriptive and inferential statistics methods were used in the study. A binary logistic regression model was fitted to see the significance of factors affecting customer’s satisfaction in this study. SPSS statistical package was used for data analysis. The result of the study reveals that the overall level of customer’s satisfaction in the study area is low (38.85%) as compared those who were not satisfied (61.15%). The result of study showed that all most all factors included in the study were significantly associated with customer’s satisfaction. Therefore, it can be concluded that based on the comparison of branches on their customers satisfaction by using odd ratio customers who were using Ambo and Bako are less satisfied as compared to customers who were in Holeta branch. Additionally, customers who were in Ginchi and Gedo were more satisfied than that of customers who were in Holeta. Since the level of customers satisfaction was low in the study area, it is more advisable and recommended for concerned body works cooperatively more in maximizing satisfaction of their customers.

Keywords: customers, satisfaction, binary logistic, complain handling process, waiting time

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Authors: Yohannes Bisa Biramo

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This study examined the meditational role of surface acting and deep acting on the relationship between calling orientation and work engagement of teachers in secondary schools of Wolaita Zone, Wolaita, Ethiopia. A predictive non-experimental correlational design was performed among 300 secondary school teachers. Stratified random sampling followed by a systematic random sampling technique was used as the basis for selecting samples from the target population. To analyze the data, Structural Equation Modeling (SEM) was used to test the association between the independent variables and the dependent variables. Furthermore, the goodness of fit of the study variables was tested using SEM to see and explain the path influence of the independent variable on the dependent variable. Confirmatory factor analysis (CFA) was conducted to test the validity of the scales in the study and to assess the measurement model fit indices. The analysis result revealed that calling was significantly and positively correlated with surface acting, deep acting and work engagement. Similarly, surface acting was significantly and positively correlated with deep acting and work engagement. And also, deep acting was significantly and positively correlated with work engagement. With respect to mediation analysis, the result revealed that surface acting mediated the relationship between calling and work engagement and also deep acting mediated the relationship between calling and work engagement. Besides, by using the model of the present study, the school leaders and practitioners can identify a core area to be considered in recruiting and letting teachers teach, in giving induction training for newly employed teachers and in performance appraisal.

Keywords: calling, surface acting, deep acting, work engagement, mediation, teachers

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Authors: E. M. Rifqi Wilda Pradana, Bagus Bayu Prabowo, Meida Riski Pujiyati, Efraim Maykhel Hagana Ginting, Virgiawan Arya Hangga Reksa

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The VLF (Very Low Frequency) method is an electromagnetic method that uses low frequencies between 10-30 KHz which results in a fairly deep penetration. In this study, the VLF method was used for zonation of disaster-prone areas by identifying geological structures in the form of faults. Data acquisition was carried out in Trimulyo Region, Jetis District, Bantul Regency, Special Region of Yogyakarta, Indonesia with 8 measurement paths. This study uses wave transmitters from Japan and Australia to obtain Tilt and Elipt values that can be used to create RAE (Rapat Arus Ekuivalen or Current Density) sections that can be used to identify areas that are easily crossed by electric current. This section will indicate the existence of a geological structure in the form of faults in the study area which is characterized by a high RAE value. In data processing of VLF method, it is obtained Tilt vs Elliptical graph and Moving Average (MA) Tilt vs Moving Average (MA) Elipt graph of each path that shows a fluctuating pattern and does not show any intersection at all. Data processing uses Matlab software and obtained areas with low RAE values that are 0%-6% which shows medium with low conductivity and high resistivity and can be interpreted as sandstone, claystone, and tuff lithology which is part of the Semilir Formation. Whereas a high RAE value of 10% -16% which shows a medium with high conductivity and low resistivity can be interpreted as a fault zone filled with fluid. The existence of the fault zone is strengthened by the discovery of a normal fault on the surface with strike N550W and dip 630E at coordinates X= 433256 and Y= 9127722 so that the activities of residents in the zone such as housing, mining activities and other activities can be avoided to reduce the risk of natural disasters.

Keywords: current density, faults, very low frequency, zonation

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Authors: Rafik Ouared

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The purpose of this paper is to invalidate decisions made by the Islamic conference led at Istanbul in 2016, which had defined two basic criteria to determine the start of the lunar month: (1)they are all based on the sighting of the crescent, be it observed or computed with modern methods, and (2) they've strongly recommended the adoption of the principle of 'unification of sighting', by which any occurrence of sighting anywhere would be applicable everywhere. To demonstrate the invalidation of those statements, a survey of 101 years of data, from 1938 to 2038, have been analyzed to compare the probability density function (PDF) of time difference between different types of fajr and new moon. Two groups of fajr have been considered: the 'natural fajr', which is the very first fajr following new moon, and the 'biased fajr', which is defined by human being inclusively of all chosen definitions. The parametric and non-parametric statistical comparisons between the different groups have shown the all the biased PDFs are significantly different from the unbiased (natural) PDF with probability value (p-value) less than 0.001. The significance level was fixed to 0.05. Conclusion: the on-going reference to sighting of crescent is inducing an significant bias in defining lunar calendar. Therefore, 'natural' calendar would be more applicable requiring a more contextualized revision of issue in fiqh.

Keywords: biased fajr, lunar calendar, natural fajr, probability density function, sighting of crescent, time difference between fajr and new moon

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Authors: S. Dias, A. Tadeu, J. Antonio, F. Pedro, C. Serra

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The goal of the present work is to experimentally evaluate the feasibility of using vibration isolators made of expanded cork agglomerate. Even though this material, also known as insulation cork board (ICB), has mainly been studied for thermal and acoustic insulation purposes, it has strong potential for use in vibration isolation. However, the adequate design of expanded cork blocks vibration isolators will depend on several factors, such as excitation frequency, static load conditions and intrinsic dynamic behavior of the material. In this study, transmissibility tests for different static and dynamic loading conditions were performed in order to characterize the material. Since the material’s physical properties can influence the vibro-isolation performance of the blocks (in terms of density and thickness), this study covered four mass density ranges and four block thicknesses. A total of 72 expanded cork agglomerate specimens were tested. The test apparatus comprises a vibration exciter connected to an excitation mass that holds the test specimen. The test specimens under characterization were loaded successively with steel plates in order to obtain results for different masses. An accelerometer was placed at the top of these masses and at the base of the excitation mass. The test was performed for a defined frequency range, and the amplitude registered by the accelerometers was recorded in time domain. For each of the signals (signal 1- vibration of the excitation mass, signal 2- vibration of the loading mass) a fast Fourier transform (FFT) was applied in order to obtain the frequency domain response. For each of the frequency domain signals, the maximum amplitude reached was registered. The ratio between the amplitude (acceleration) of signal 2 and the amplitude of signal 1, allows the calculation of the transmissibility for each frequency. Repeating this procedure allowed us to plot a transmissibility curve for a certain frequency range. A number of transmissibility experiments were performed to assess the influence of changing the mass density and thickness of the expanded cork blocks and the experimental conditions (static load and frequency of excitation). The experimental transmissibility tests performed in this study showed that expanded cork agglomerate blocks are a good option for mitigating vibrations. It was concluded that specimens with lower mass density and larger thickness lead to better performance, with higher vibration isolation and a larger range of isolated frequencies. In conclusion, the study of the performance of expanded cork agglomerate blocks presented herein will allow for a more efficient application of expanded cork vibration isolators. This is particularly relevant since this material is a more sustainable alternative to other commonly used non-environmentally friendly products, such as rubber.

Keywords: expanded cork agglomerate, insulation cork board, transmissibility tests, sustainable materials, vibration isolators

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Authors: Richard J. Hanowski, Rebecca L. Hammond

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Very few studies have been conducted to investigate safety issues associated with motorcoach/bus operations. The current study investigates the impact that roadway infrastructure, including locality, roadway grade, traffic flow and traffic density, have on bus safety. A naturalistic driving study was conducted in the U.S.A that involved 43 motorcoaches. Two fleets participated in the study and over 600,000 miles of naturalistic driving data were collected. Sixty-five bus drivers participated in this study; 48 male and 17 female. The average age of the drivers was 49 years. A sophisticated data acquisition system (DAS) was installed on each of the 43 motorcoaches and a variety of kinematic and video data were continuously recorded. The data were analyzed by identifying safety critical events (SCEs), which included crashes, near-crashes, crash-relevant conflicts, and unintentional lane deviations. Additionally, baseline (normative driving) segments were also identified and analyzed for comparison to the SCEs. This presentation highlights the need for bus safety research and the methods used in this data collection effort. With respect to elements of roadway infrastructure, this study highlights the methods used to assess locality, roadway grade, traffic flow, and traffic density. Locality was determined by manual review of the recorded video for each event and baseline and was characterized in terms of open country, residential, business/industrial, church, playground, school, urban, airport, interstate, and other. Roadway grade was similarly determined through video review and characterized in terms of level, grade up, grade down, hillcrest, and dip. The video was also used to make a determination of the traffic flow and traffic density at the time of the event or baseline segment. For traffic flow, video was used to assess which of the following best characterized the event or baseline: not divided (2-way traffic), not divided (center 2-way left turn lane), divided (median or barrier), one-way traffic, or no lanes. In terms of traffic density, level-of-service categories were used: A1, A2, B, C, D, E, and F. Highlighted in this abstract are only a few of the many roadway elements that were coded in this study. Other elements included lighting levels, weather conditions, roadway surface conditions, relation to junction, and roadway alignment. Note that a key component of this study was to assess the impact that driver distraction and fatigue have on bus operations. In this regard, once the roadway elements had been coded, the primary research questions that were addressed were (i) “What environmental condition are associated with driver choice of engagement in tasks?”, and (ii) “what are the odds of being in a SCE while engaging in tasks while encountering these conditions?”. The study may be of interest to researchers and traffic engineers that are interested in the relationship between roadway infrastructure elements and safety events in motorcoach bus operations.

Keywords: bus safety, motorcoach, naturalistic driving, roadway infrastructure

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Authors: Robert Cazar, Nathaly Maza

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Energy drinks and sports drinks are quite popular among young adults and teenagers worldwide. Some concerns regarding their health effects – particularly those of the energy drinks - have been raised based on scientific findings. Differentiating between these two types of drinks by means of their chemical properties seems to be an instructive task. Chemometrics provides the most appropriate strategy to do so. In this study, a discrimination analysis of the energy and sports drinks has been carried out applying chemometric methods. A set of eleven samples of available commercial brands of drinks – seven energy drinks and four sports drinks – were collected. Each sample was characterized by eight chemical variables (carbohydrates, energy, sugar, sodium, pH, degrees Brix, density, and citric acid). The data set was standardized and examined by exploratory chemometric techniques such as clustering and principal component analysis. As a preliminary step, a variable selection was carried out by inspecting the variable correlation matrix. It was detected that some variables are redundant, so they can be safely removed, leaving only five variables that are sufficient for this analysis. They are sugar, sodium, pH, density, and citric acid. Then, a hierarchical clustering `employing the average – linkage criterion and using the Euclidian distance metrics was performed. It perfectly separates the two types of drinks since the resultant dendogram, cut at the 25% similarity level, assorts the samples in two well defined groups, one of them containing the energy drinks and the other one the sports drinks. Further assurance of the complete discrimination is provided by the principal component analysis. The projection of the data set on the first two principal components – which retain the 71% of the data information – permits to visualize the distribution of the samples in the two groups identified in the clustering stage. Since the first principal component is the discriminating one, the inspection of its loadings consents to characterize such groups. The energy drinks group possesses medium to high values of density, citric acid, and sugar. The sports drinks group, on the other hand, exhibits low values of those variables. In conclusion, the application of chemometric methods on a data set that features some chemical properties of a number of energy and sports drinks provides an accurate, dependable way to discriminate between these two types of beverages.

Keywords: chemometrics, clustering, energy drinks, principal component analysis, sports drinks

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Authors: Kathleen Moyer, Nora Ait Boucherbil, Murtaza Zohair, Janna Eaves-Rathert, Cary Pint

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This study demonstrates the significance of interface engineering in the field of structural energy by being the first case where the performance of the system with the structural battery is greater than the performance of the same system with a battery separate from the system. The benefits of improving the interface in the structural battery were tested by creating carbon fiber composite batteries (and independent graphite electrodes and lithium iron phosphate electrodes) with and without an improved interface. Mechanical data on the structural batteries were collected using tensile tests and electrochemical data was collected using scanning electron microscopy equipment. The full-cell lithium-ion structural batteries had capacity retention of over 80% exceeding 100 cycles with an average energy density of 52 W h kg−1 and a maximum energy density of 58 W h kg−1. Most scientific developments in the field of structural energy have been done with supercapacitors. Most scientific developments with structural batteries have been done where batteries are simply incorporated into the structural element. That method has limited advantages and can create mechanical disadvantages. This study aims to show that a large improvement in structure energy research can be made by improving the interface between the structural device and the battery.

Keywords: composite materials, electrochemical performance, mechanical properties, polymer interface, structural batteries

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Authors: Lukas Kano Mangalla, Raden Rinova Sisworo, Luther Pagiling

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Torrefaction is an emerging thermo-chemical treatment process that aims to improve the quality of biomass fuels. This study focused on upgrading the waste teakwood through microwave torrefaction processes and investigating the key operating parameters to improve energy density for the quality of biochar production. The experiments were carried out in a 250 mL reactor placed in a microwave cavity on two different media, inert and non-inert. The microwave was operated at a frequency of 2.45GHz with power level variations of 540W, 720W, and 900W, respectively. During torrefaction processes, the nitrogen gas flows into the reactor at a rate of 0.125 mL/min, and the air flows naturally. The temperature inside the reactor was observed every 0.5 minutes for 20 minutes using a K-Type thermocouple. Changes in the mass and the properties of the torrefied products were analyzed to predict the correlation between calorific value, mass yield, and level power of the microwave. The results showed that with the increase in the operating power of microwave torrefaction, the calorific value and energy density of the product increased significantly, while mass and energy yield tended to decrease. Air can be a great potential media for substituting the expensive nitrogen to perform the microwave torrefaction for teakwood biomass.

Keywords: torrefaction, microwave heating, energy enhancement, mass and energy yield

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Authors: Xia Huo

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The composition and metabolites of the gut microbiota can be altered by environmental pollutants. However, the effect of co-exposure to multiple pollutants on the human gut microbiota has not been sufficiently studied. In this study, gut microorganisms and their metabolites were compared between 33 children from Guiyu and 34 children from Haojiang. The exposure level was assessed by estimating the daily intake (EDI) of polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), 6PPD-quinone (6PPDQ), and metal(loid)s in dust. Significant correlations were found between the EDIs of 6PPDQ, BDE28, PCB52, Ni, Cu, and both the alpha diversity index and specific metabolites in single-element models. The study found that the Bayesian kernel machine regression (BKMR) model showed a negative correlation between the EDIs of five pollutants (6PPDQ, BDE28, PCB52, Ni, and Cu) and the Chao 1 index, particularly beyond the 55th percentile. Furthermore, the EDIs of these five pollutants were positively correlated with the levels of the metabolite 2,4-diaminobutyric acid while negatively correlated with the levels of d-erythro-sphingosine and d-threitol. Our research suggests that exposure to 6PPDQ, BDE28, PCB52, Ni, and Cu in kindergarten dust is associated with alterations in the gut microbiota and its metabolites. These alterations may be associated with neurodevelopmental abnormalities in children.

Keywords: gut microbiota, 6PPDQ, PBDEs, PCBs, metal(loid)s, BKMR

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Authors: Tengfei He, Mengjie Zhang, Baosheng Jin

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In this study, the low-cost halloysite (Hal) was utilized for the first time to enhance the solid-phase enrichment and stability of heavy metals (HMs) during solid waste pyrolysis through experimental and theoretical methods, and compared with kaolinite (Kao). Experimental results demonstrated that Hal was superior to Kao in improving the solid-phase enrichment of HMs. Adding Hal reduced the proportion of HMs in the unstable fraction (F1+F2), consequently lowering the environmental risk of biochar and the extractable state of HMs. Through Grand canonical Monte Carlo and Density Functional Theory (DFT) simulations, the adsorption amounts and adsorption mechanisms of Cd/Pb compound on Hal/Kao surfaces were analyzed. The adsorption amounts of HMs by Hal were significantly higher than Kao and decreased with increasing temperature, and the difference in adsorption performance caused by structural bending was negligible. The DFT results indicated that Cd/Pb monomers were stabilized by establishing covalent bonds with OH or reactive O atoms on the Al-(0 0 1) surface, whereas the covalent bonds with ionic bonding properties formed between Cl atoms and unsaturated Al atoms played a crucial role in stabilizing HM chlorides. This study highlights the potential of Hal in stabilizing HMs during pyrolysis without requiring any modifications.

Keywords: heavy metals, halloysite, density functional theory, grand canonical Monte Carlo

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Authors: Nam-Seok Joo, Da-Eun Jung, Beom-Hee Choi

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Background and Objectives: Recently, the triglyceride/high-density lipoprotine cholesterol (TG/HDL) ratio and pericardial adipose tissue (PAT) has gained attention as an indicator related to metabolic syndrome (MS). To date, there has been no research on the relationship between TG/HDL and PAT, we aimed to investigate the association between the TG/HDL and PAT. Methods: In this cross-sectional study, we investigated 627 patients who underwent coronary multidetector computed tomography and metabolic parameters. We divided subjects into two groups according to the cut-off PAT volume associated with MS, which is 142.2 cm³, and we compared metabolic parameters between those groups. We divided the TG/HDL ratio into tertiles according to Log(TG/HDL) and compared PAT-related parameters by analysis of variance. Finally, we applied logistic regression analysis to obtain the odds ratio of high PAT (PAT volume≥142.2 cm³) in each tertile, and we performed receiver operating characteristic (ROC) analysis to get the cut-off of TG/HDL ratio according to high PAT. Results: The mean TG/ HDL ratio of the high PAT volume group was 3.6, and TG/ HDL ratio had a strong positive correlation with various metabolic parameters. In addition, in the Log (TG/HDL) tertile groups, the higher tertile had more metabolic derangements, including PAT, and showed higher odds ratios of having high PAT (OR=4.10 in the second tertile group and OR=5.06 in their third tertile group, respectively) after age, sex, smoking adjustments. TG/HDL ratio according to the having increased PAT by ROC curve showed 1.918 (p < 0.001). Conclusion: TG/HDL ratio and high PAT volume have a significant positive correlation, and higher TG/HDL ratio showed high PAT. The cut-off value of the TG/HDL ratio was 1.918 to have a high PAT.

Keywords: triglyceride, high-density lipoprotein, pericardial adipose tissue, cut-off value

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Authors: Mitsuhiro Okayasu, Lele Yang, Koji Shimotsu

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The effects of microstructural characteristics on the mechanical and hydrogen embrittlement properties of 1,800MPa grade hot stamping carbon steel were investigated experimentally. The tensile strength increased with increasing the hot stamping temperature until around 921°C, but that decreased with increasing the temperature in more than 921°C due to the increment of the size of lath martensite and prior austenite. With the hot stamping process, internal strain was slightly created in the sample, which led to the slight increment of the hardness value although no clear change of the microstructural formation was detected. Severity of hydrogen embrittlement was investigated using the hot stamped carbon steels after the immersion in a hydrogen gas, and that was directly attributed to the infiltration of the hydrogen into their grain boundaries. The high strength carbon steel with tiny lath martensite microstructure could make severe hydrogen brittleness as the hydrogen was strongly penetrated in the grain boundaries in the hydrogen gas for a month. Because of weak embrittlement for the as-received carbon (ferrite and pearlite), hydrogen embrittlement is caused by the high internal strain and high dislocation density. The hydrogen embrittlement for carbon steel is attributed to amount of the hydrogen immersed in-between grain boundaries, which is caused by the dislocation density and internal strain.

Keywords: hydrogen embrittlement, hot stamping process, carbon steel, mechanical property

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Authors: Partha Sarathi Majee, S. Bhattacharyya

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Migration of a core-shell soft particle under the influence of an external electric field in an electrolyte solution is studied numerically. The soft particle is coated with a positively charged polyelectrolyte layer (PEL) and the rigid core is having a uniform surface charge density. The Darcy-Brinkman extended Navier-Stokes equations are solved for the motion of the ionized fluid, the non-linear Nernst-Planck equations for the ion transport and the Poisson equation for the electric potential. A pressure correction based iterative algorithm is adopted for numerical computations. The effects of convection on double layer polarization (DLP) and diffusion dominated counter ions penetration are investigated for a wide range of Debye layer thickness, PEL fixed surface charge density, and permeability of the PEL. Our results show that when the Debye layer is in order of the particle size, the DLP effect is significant and produces a reduction in electrophoretic mobility. However, the double layer polarization effect is negligible for a thin Debye layer or low permeable cases. The point of zero mobility and the existence of mobility reversal depending on the electrolyte concentration are also presented.

Keywords: debye length, double layer polarization, electrophoresis, mobility reversal, soft particle

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Authors: Md. Jahidul Islam, A. K. M. Rakinul Islam, M. Salamah Meherier

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This study investigates the suitability of using plastic, such as polyethylene terephthalate (PET), as a partial replacement of natural coarse and fine aggregates (for example, brick chips and natural sand) to produce lightweight concrete for load bearing structural members. The plastic coarse aggregate (PCA) and plastic fine aggregate (PFA) were produced from melted polyethylene terephthalate (PET) bottles. Tests were conducted using three different water–cement (w/c) ratios, such as 0.42, 0.48, and 0.57, where PCA and PFA were used as 50% replacement of coarse and fine aggregate respectively. Fresh and hardened properties of concrete have been compared for natural aggregate concrete (NAC), PCA concrete (PCC) and PFA concrete (PFC). The compressive strength of concrete at 28 days varied with the water–cement ratio for both the PCC and PFC. Between PCC and PFC, PFA concrete showed the highest compressive strength (23.7 MPa) at 0.42 w/c ratio and also the lowest compressive strength (13.7 MPa) at 0.57 w/c ratio. Significant reduction in concrete density was mostly observed for PCC samples, ranging between 1977–1924 kg/m³. With the increase in water–cement ratio PCC achieved higher workability compare to both NAC and PFC. It was found that both the PCA and PFA contained concrete achieved the required compressive strength to be used for structural purpose as partial replacement of the natural aggregate; but to obtain the desired lower density as lightweight concrete the PCA is most suited.

Keywords: polyethylene terephthalate, plastic aggregate, concrete, fresh and hardened properties

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Authors: Obied A. Alwan, Elgerbi, M. Ali

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This study was conducted on the cow milk which is used in the local milk factories of Zawia. This was completely random sampling the unscheduled samples. The microbiologic result have approved that the count of bacteria and the count of E.Coli are very high and all the manufacturing places which were included in the study have lacked the health conditions.

Keywords: raw milk, dairy factories, Libya, microbiologic

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Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: Laura Dembovska, Ina Pundiene, Diana Bajare

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Alkali-activated aluminium-silicate composites (AASC) can be used in the production of innovative materials with a wide range of properties and applications. AASC are associated with low CO₂ emissions; in the production process, it is possible to use industrial by-products and waste, thereby minimizing the use of a non-renewable natural resource. This study deals with the preparation of heat-resistant porous AASC based on chamotte for high-temperature applications up to 1200°C. Different fillers, aluminium scrap recycling waste as pores forming agent and alkali activation with 6M sodium hydroxide (NaOH) and potassium hydroxide (KOH) solution were used. Sodium hydroxide (NaOH) is widely used for the synthesis of AASC compared to potassium hydroxide (KOH), but comparison of using different activator for geopolymer synthesis is not well established. Changes in chemical composition of AASC during heating were identified and quantitatively analyzed by using DTA, dimension changes during the heating process were determined by using HTOM, pore microstructure was examined by SEM, and mineralogical composition of AASC was determined by XRD. Lightweight porous AASC activated with NaOH have been obtained with density in range from 600 to 880 kg/m³ and compressive strength from 0.8 to 2.7 MPa, but for AAM activated with KOH density was in range from 750 to 850 kg/m³ and compressive strength from 0.7 to 2.1 MPa.

Keywords: alkali activation, alkali activated materials, elevated temperature application, heat resistance

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Authors: Mariam Badmus, Bothina Manasreh

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Transition metal dichalcogenides (TMDs) have gained significant attention as two-dimensional (2D) materials due to their intrinsic band gaps and unique properties, which make them ideal candidates for electronic and photonic applications. Unlike graphene, which lacks a band gap, TMDs (MX₂, where M is a transition metal and X is a chalcogen such as sulfur, selenium, or tellurium) exhibit semiconductor behavior and can be exfoliated into monolayers, enhancing their properties. The properties of these materials are investigated using density functional theory, a quantum mechanical computational method to solve Schrodinger equation for many body problems to calculate electron density of the atoms involved on which the energy and properties of a system depend. They show promise for use in photodetectors, biosensors, memory devices, and other technologies in communications, health, and energy sectors. In particular, metallic TMDs, which lack an intrinsic band gap, benefit from doping with transition metals, this improves their electronic and optical properties. Doping monolayer TMDs yields more significant improvements than doping bulk materials. Notably, doping with metals such as vanadium enhances the magnetization of TMDs, expanding their potential applications in spintronics. This work highlights the effects of doping on TMDs and explores strategies for optimizing their performance for advanced technological applications.

Keywords: concentration, doping, magnetization, monolayer

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Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

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The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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Authors: Vânia Costa, Nuno De Sá Teixeira, Ana C. Santos, Eduardo Santos

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Financial literacy and numeracy have been regarded as paramount for rational household decision making in the increasing complexity of financial markets. However, financial decisions are often made under sub-optimal circumstances, including cognitive overload. The present study aims to clarify how financial literacy and numeracy, taken as relevant expert knowledge for financial decision-making, modulate possible effects of cognitive load. Participants were required to perform a choice between a sure loss or a gambling pertaining a financial investment, either with or without a competing memory task. Two experiments were conducted varying only the content of the competing task. In the first, the financial choice task was made while maintaining on working memory a list of five random letters. In the second, cognitive load was based upon the retention of six random digits. In both experiments, one of the items in the list had to be recalled given its serial position. Outcomes of the first experiment revealed no significant main effect or interactions involving cognitive load manipulation and numeracy and financial literacy skills, strongly suggesting that retaining a list of random letters did not interfere with the cognitive abilities required for financial decision making. Conversely, and in the second experiment, a significant interaction between the competing mnesic task and level of financial literacy (but not numeracy) was found for the frequency of choice of a gambling option. Overall, and in the control condition, both participants with high financial literacy and high numeracy were more prone to choose the gambling option. However, and when under cognitive load, participants with high financial literacy were as likely as their illiterate counterparts to choose the gambling option. This outcome is interpreted as evidence that financial literacy prevents intuitive risk-aversion reasoning only under highly favourable conditions, as is the case when no other task is competing for cognitive resources. In contrast, participants with higher levels of numeracy were consistently more prone to choose the gambling option in both experimental conditions. These results are discussed in the light of the opposition between classical dual-process theories and fuzzy-trace theories for intuitive decision making, suggesting that while some instances of expertise (as numeracy) are prone to support easily accessible gist representations, other expert skills (as financial literacy) depend upon deliberative processes. It is furthermore suggested that this dissociation between types of expert knowledge might depend on the degree to which they are generalizable across disparate settings. Finally, applied implications of the present study are discussed with a focus on how it informs financial regulators and the importance and limits of promoting financial literacy and general numeracy.

Keywords: decision making, cognitive load, financial literacy, numeracy

Procedia PDF Downloads 182

Authors: Aziza Barnawi

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Background: Regular exercise reduces risk factors associated with cardiovascular diseases. Over the past decade, exercise interventions have been introduced to reduce the risk of and prevent coronary artery disease (CAD). Elevated low-density lipoproteins (LDL) contribute to the formation of atherosclerosis, its manifestations on the endothelial narrow the coronary artery and affect the endothelial function. Therefore, flow-mediated dilation (FMD) technique is used to assess the function. The results of previous studies have been inconsistent and difficult to interpret across different types of exercise programs. The relationship between exercise therapy and lipid levels has been extensively studied, and it is known to improve the lipid profile and endothelial function. However, the effectiveness of exercise in altering LDL levels and improving blood flow is controversial. Objective: This review aims to explore the evidence and quantify the impact of exercise training on LDL levels and vascular function by FMD. Methods: Electronic databases were searched PubMed, Google Scholar, Web of Science, the Cochrane Library, and EBSCO using the keywords: “low and/or moderate aerobic training”, “blood flow”, “atherosclerosis”, “LDL mediated blood flow”, “Cardiac Rehabilitation”, “low-density lipoproteins”, “flow-mediated dilation”, “endothelial function”, “brachial artery flow-mediated dilation”, “oxidized low-density lipoproteins” and “coronary artery disease”. The studies were conducted for 6 weeks or more and influenced LDL levels and/or FMD. Studies with different intensity training and endurance training in healthy or CAD individuals were included. Results: Twenty-one randomized controlled trials (RCTs) (14 FMD and 7 LDL studies) with 776 participants (605 exercise participants and 171 control participants) met eligibility criteria and were included in the systematic review. Endurance training resulted in a greater reduction in LDL levels and their subfractions and a better FMD response. Overall, the training groups showed improved physical fitness status compared with the control groups. Participants whose exercise duration was ≥150 minutes /week had significant improvement in FMD and LDL levels compared with those with <150 minutes/week.Conclusion: In conclusion, although the relationship between physical training, LDL levels, and blood flow in CAD is complex and multifaceted, there are promising results for controlling primary and secondary prevention of CAD by exercise. Exercise training, including resistance, aerobic, and interval training, is positively correlated with improved FMD. However, the small body of evidence for LDL studies (resistance and interval training) did not prove to be significantly associated with improved blood flow. Increasing evidence suggests that exercise training is a promising adjunctive therapy to improve cardiovascular health, potentially improving blood flow and contributing to the overall management of CAD.

Keywords: exercise training, low density lipoprotein, flow mediated dilation, coronary artery disease

Procedia PDF Downloads 72

Authors: Barzin Rajabloo, Martin Desilets

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First, an electrochemical model for the reduction of CO₂ into CH₃OH is developed in which mass and charge transfer, reactions at the surface of the electrodes and fluid flow of the electrolyte are considered. This mathematical model is developed in COMSOL Multiphysics® where both secondary and tertiary current distribution interfaces are coupled to consider concentrations and potentials inside different parts of the cell. Constant reaction rates are assumed as the fitted parameters to minimize the error between experimental data and modeling results. The model is validated through a comparison with experimental data in terms of faradaic efficiency for production of CH₃OH, the current density in different applied cathode potentials as well as current density in different electrolyte flow rates. The comparison between model outputs and experimental measurements shows a good agreement. The model indicates the higher hydrogen evolution in comparison with CH₃OH production as well as mass transfer limitation caused by CO₂ concentration, which are consistent with findings in the literature. After validating the model, in the second part of the study, some design parameters of the cell, such as cathode geometry and catholyte/anolyte channel widths, are modified to reach better performance and higher faradaic efficiency of methanol production.

Keywords: carbon dioxide, electrochemical reduction, methanol, modeling

Procedia PDF Downloads 109

Authors: Abid Ali Abid

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One-dimensional (1-D) particle-in-cell (PIC) electrostatic simulations are carried out to investigate the electrostatic waves, whose constituents are hot, cold and beam electrons in the background of motionless positive ions. In fact, the electrostatic modes excited are electron acoustic waves, beam driven waves as well as Langmuir waves. It is assessed that the relevant plasma parameters, for example, hot electron temperature, beam electron drift speed, and the electron beam density significantly modify the electrostatics wave's profiles. In the nonlinear stage, the wave-particle interaction becomes more evident and the waves have obtained its saturation level. Consequently, electrons become trapped in the waves and trapping vortices are clearly formed. Because of this trapping vortices and mixing of the electrons in phase space, finally, lead to electrons thermalization. It is observed that for the high-density value of the beam-electron, the solitary waves having a bipolar form of the electric field. These solitons are the nonlinear Brenstein-Greene and Kruskal wave mode that attributes the trapping of electrons potential well of phase-space hole. These examinations revealed that electrostatic waves have been exited in beam-plasma model and producing waves having broad-frequency ranges, which may clarify the broadband electrostatic noise (BEN) spectrum studied in the auroral zone.

Keywords: electron acoustic waves, trapping of cold electron, Langmuir waves, particle-in cell simulation

Procedia PDF Downloads 206

Authors: Li Guoyou, Zhang Tao, Ji Wenzhan, Huo Liang, Lin Xiqiang, Zhang Nan

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The three dimensional (3D) printing technology has undergone rapid development in the last few years and it is possible to print engineering structures. 3D printing buildings use wastes from constructions, industries and mine tailings as “ink”, and mix it with property improved materials, such as cement, fiber etc. This paper presents a study of the Thermodynamic performance of 3D printed walls using cement and steel slag powder. Analyses the thermal simulation regarding 3D printed walls and solid brick wall by the way of the hot-box methods and the infrared technology, and the results were contrasted with theoretical calculation. The results show that the excellent thermodynamic performance of 3D printed concrete wall made it suitable as the partial materials for self-thermal insulation walls in residential buildings. The thermodynamic performance of 3D printed concrete walls depended on the density of materials, distribution of holes, and the filling materials. Decreasing the density of materials, increasing the number of holes or replacing the filling materials with foamed concrete could improve its thermodynamic performance significantly. The average of heat transfer coefficient and thermal inertia index of 3D printed steel slag powder concrete wall all better than the traditional solid brick wall with a thickness of 240mm.

Keywords: concrete, 3D printed walls, thermodynamic performance, steel slag powder

Procedia PDF Downloads 183

Authors: Harsh Agarwal, Pratikkumar Patel, Maharshi Pathak

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Recently the low prices of Crude oil and increase in strict environmental regulations limit limits the use of diesel based muds as these muds are relatively costlier and toxic, as a result disposal of cuttings into the eco-system is a major issue faced by the drilling industries. To overcome these issues faced by the Oil Industry, an attempt has been made to develop oil-in-water emulsion mud system using nettlespurge oil. Nettlespurge oil could be easily available and its cost is around ₹30/litre which is about half the price of diesel in India. Oil-based mud (OBM) was formulated with Nettlespurge oil extracted from Nettlespurge seeds using the Soxhlet extraction method. The formulated nettlespurge oil mud properties were analysed with diesel oil mud properties. The compared properties were rheological properties, yield point and gel strength, and mud density and filtration loss properties, fluid loss and filter cake. The mud density measurement showed that nettlespurge OBM was slightly higher than diesel OBM with mud density values of 9.175 lb/gal and 8.5 lb/gal, respectively, at barite content of 70 g. Thus it has a higher lubricating property. Additionally, the filtration loss test results showed that nettlespurge mud fluid loss volumes, oil was 11 ml, compared to diesel oil mud volume of 15 ml. The filtration loss test indicated that the nettlespurge oil mud with filter cake thickness of 2.2 mm had a cake characteristic of thin and squashy while the diesel oil mud resulted in filter cake thickness of 2.7 mm with cake characteristic of tenacious, rubbery and resilient. The filtration loss test results showed that nettlespurge oil mud fluid loss volumes was much less than the diesel based oil mud. The filtration loss test indicated that the nettlespurge oil mud filter cake thickness less than the diesel oil mud filter cake thickness. So Low formation damage and the emulsion stability effect was analysed with this experiment. The nettlespurge oil-in-water mud system had lower coefficient of friction than the diesel oil based mud system. All the rheological properties have shown better results relative to the diesel based oil mud. Therefore, with all the above mentioned factors and with the data of the conducted experiment we could conclude that the Nettlespurge oil based mud is economically and well as eco-logically much more feasible than the worn out and shabby diesel-based oil mud in the Drilling Industry.

Keywords: economical feasible, ecological feasible, emulsion stability, nettle spurge oil, rheological properties, soxhlet extraction method

Procedia PDF Downloads 203

Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães

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This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.

Keywords: path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart

Procedia PDF Downloads 167

Authors: Tejasvi Parupudi, Mochen Li, Lakshya Mittal, Ignacio G. Camarillo, Raji Sundararajan

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With breast cancer becoming a global pandemic, it is very important to assess a woman’s risk profile accurately in a timely manner. Providing an estimate of the risk of developing breast cancer to a woman gives her an opportunity to consider options to decrease this risk. Women at low risk may be suggested yearly screenings whereas women with a high risk of developing breast cancer would be candidates for aggressive surveillance. Fortunately, there is a set of risk factors that are used to predict the probability of a woman being diagnosed with breast cancer in the future. Studying risk factors and understanding how they correlate to cancer is important for early diagnosis, prevention and reducing mortality rates. The effect of crucial risk factors among black and white women was compared in this study. The various risk factors analyzed include breast density, age, cancer in a first-degree relative, menopausal status, body mass index (BMI) and prior breast cancer diagnosis, etc. Breast density, age at first full-term birth and BMI were utilized in this study as important risk factors for the comparison of incidence rates between women of black and white races in the USA. Understanding the differences could lead to the development of solutions to reduce disparity in mortality rates among black women by improving overall access to care.

Keywords: big data, breast cancer, risk factors, incidence rates, mortality, race

Procedia PDF Downloads 275