Search results for: scientific modeling

Authors: Obaid Alotaibi

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The geographical location of the State of Kuwait contributed significantly to the suffering of Kuwait in the past, due to the scarcity of natural water resources and the inability of the State's financial resources to provide other water resources to meet the needs of the population. The problem of water scarcity in Kuwait remained until the beginning of the second half of the twentieth century, as the country's economic conditions revived with the emergence and export of oil; which was clearly reflected in the steady growth of the population. To cope with this population, increase, it was necessary to expand the various development programs to include all sectors of the state. The process of development and urbanization could not start without finding solutions to the problem of water shortage in Kuwait. The only option for officials to meet the needs of the population and the different sectors of water development is the desalination of seawater. This process necessitated the establishment of six desalination plants along the coast of Kuwait and extended freshwater arteries to reach everywhere on the land. However, this does not mean that the problem of water shortage has been completely solved. The desalination plants are not meeting the country's future water needs, especially considering the increasing population growth. These stations are nearing completion and they need to be replaced, renovation and maintenance, require significant expenses. Therefore, it was necessary for scientific research to address the issue of water in Kuwait, whether in the field of development of existing resources or in the field of rationalization of consumption and protection of available resources. The study focused on how to address the increasing demand for water resulting from population increase, the impact of water on economic and social development, the prospects of water resources in Kuwait and its ability to meet the needs of the country by 2030.

Keywords: economic, development, Kuwait, social, water resources

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Authors: Dimitris Kokkinos, Panagiotis Prinos

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In the last three decades, climate change has been studied extensively from scientific community, and its consequences are more than clear all around the world. Most countries have carried out a great effort to reduce global warming rates with the ratification and implementation of several international treaties. Moreover, many of them have already adopted national plans in order to adapt to climate change effects and mitigate human and economic losses. Coastal environments, with their inherent physical sensitivity, will face important challenges as a result of projected changes in climate conditions and hundreds of millions of people will be affected. Coastal zones are of high social and economic value and this research focuses on the Mediterranean basin, which is a densely populated and highly urbanized area. With 40% of its land used for human activity and the inevitability of the impacts of the climate change, it is obvious that some form of adaptation measures will be necessary. In this regard, the EU tools, policies and legislation concerning adaptation to climate change are presented. Additionally, the National Adaptation Strategies of State members of the Mediterranean basin are compared and analyzed concerning the coastal areas, along with an overview of projects and programs results focused on coastal issues at different spatial scales. The purpose of this research is to stress the differences between Mediterranean State members at methodologies implemented, to highlight the possible gaps in co-ordination and to emphasize on research initiatives that EU can build upon moving towards an integrated adaptation planning on a region-wide basis.

Keywords: coastal adaptation, Mediterranean Basin, climate change, coastal environments

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Authors: Mohammed S. Razali, Kamel Khimeche, Dahah Hichem, Ammar Boudjellal, Djamel E. Kaderi, Nourddine Ramdani

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The use of additive manufacturing technologies has revolutionized various aspects of our daily lives. In particular, 3D printing has greatly advanced biomedical applications. While fused filament fabrication (FFF) technologies have made it easy to produce or prototype various medical devices, it is crucial to minimize the risk of contamination. New materials with antibacterial properties, such as those containing compounded silver nanoparticles, have emerged on the market. In a previous study, we prepared a newly sintered seashell filler (SSh) from bio-based seashells found along the Mediterranean coast using a suitable heat treatment process. We then prepared a series of polylactic acid (PLA) and polybutylene succinate (PBS) biocomposites filled with these SSh particles using a melt mixing technique with a twin-screw extruder to use them as feedstock filaments for 3D printing. The study consisted of two parts: evaluating the antibacterial activity of newly prepared biocomposites made of PLA and PBS reinforced with a sintered seashell in the first part and experimental and modeling analysis of the non-isothermal crystallization kinetics of these biocomposites in the second part. In the first part, the bactericidal activity of the biocomposites against three different bacteria, including Gram-negative bacteria such as (E. coli and Pseudomonas aeruginosa), as well as Gram-positive bacteria such as (Staphylococcus aureus), was examined. The PLA-based biocomposite containing 20 wt.% of SSh particles exhibited an inhibition zone with radial diameters of 8mm and 6mm against E. coli and Pseudo. Au, respectively, while no bacterial activity was observed against Staphylococcus aureus. In the second part, the focus was on investigating the effect of the sintered seashell filler particles on the non-isothermal crystallization kinetics of PLA and PBS 3D-printing composite materials. The objective was to understand the impact of the filler particles on the crystallization mechanism of both PLA and PBS during the cooling process of a melt-extruded filament in (FFF) to manage the dimensional accuracy and mechanical properties of the final printed part. We conducted a non-isothermal melt crystallization kinetic study of a series of PLA-SS and PBS-SS composites using differential scanning calorimetry at various cooling rates. We analyzed the obtained kinetic data using different crystallization kinetic models such as modified Avrami, Ozawa, and Mo's methods. Dynamic mode describes the relative crystallinity as a function of temperature; it found that time half crystallinity (t1/2) of neat PLA decreased from 17 min to 7.3 min for PLA+5 SSh and the (t1/2) of virgin PBS was reduced from 3.5 min to 2.8 min for the composite containing 5wt.% of SSh. We found that the coated SS particles with stearic acid acted as nucleating agents and had a nucleation activity, as observed through polarized optical microscopy. Moreover, we evaluated the effective energy barrier of the non-isothermal crystallization process using the Iso conversional methods of Flynn-Wall-Ozawa (F-W-O) and Kissinger-Akahira-Sunose (K-A-S). The study provides significant insights into the crystallization behavior of PLA and PBS biocomposites.

Keywords: avrami model, bio-based reinforcement, dsc, gram-negative bacteria, gram-positive bacteria, isoconversional methods, non-isothermal crystallization kinetics, poly(butylene succinate), poly(lactic acid), antbactirial activity

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Authors: Kunwar Paritosh, Vivekanand Vivekanand, Nidhi Pareek

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Presently, India depends primarily on fossil fuels for its acute energy demand. The swift in development of India in last two decades is accentuating its natural resources and compelling expenditures to cope energy security for the habitats. A total inhabitant of 1.2 billion, observing growing industrialization; is generating 68.8 million tonnes of municipal solid waste per year, 53.7 million tonnes is collected, and only trifling amount of 10.3 million tonnes of waste is treated per year that integrates to a massive amount of unimaginable land hill. In India, waste is mostly landfilled and/or incinerated with low technology and is poorly managed. Underutilization of this waste not only gulps resources but also stresses environment, public health and bionetwork thus affecting the bioeconomy negatively. It also creates conditions that invoke inevitable expenditures and loss of its renewable energy potential. The non-scientific approach to manage waste may lead to an economy downfall, underutilization and degradation of natural resources. Waste treatment technologies must be scientifically tailored and engineered as per the type of waste where it may be utilized as a source of energy (here biogas) and nutrients employing anaerobic digestion to the sorted waste. This paper presents a brief review on current practices, key achievements and forthcoming aspects of harnessing energy from municipal solid waste in Indian scenario.

Keywords: municipal discards, organic waste, anaerobic digestion, incineration, energy

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Authors: Silvia Lorenzo, Hongmian Gong

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With the influx of research assessing the economic impact of the global financial crisis of 2007-8, a spatial analysis based on empirical data is needed to better understand the spatial significance of the financial crisis in New York, a key international financial center also considered the origin of the crisis. Using spatial statistics, the existence of financial clusters specializing in credit and securities throughout the New York metropolitan area are identified for 2000 and 2010, the time period before and after the height of the global financial crisis. Geographically Weighted Regressions are then used to examine processes underlying the formation and movement of financial geographies across state, county and ZIP codes of the New York metropolitan area throughout the 2000s with specific attention to tax regimes, employment, household income, technology, and transportation hubs. This analysis provides useful inputs for financial risk management and public policy initiatives aimed at addressing regional economic sustainability across state boundaries, while also developing the groundwork for further research on a spatial analysis of the global financial crisis.

Keywords: financial clusters, New York, global financial crisis, geographically weighted regression

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Authors: Nargiz Ismayilova

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The issue of modernism and the concept of postmodernism has been the focus of world researchers for many years, and there are very few researchers who have come to a common denominator about this term. During the independence period, the expansion of the relations of Azerbaijani literature with the world has led to the spread of many currents and tendencies formed in the West to the literary environment in our country. In this context, the works created in our environment are distinguished by their extreme richness in terms of subject matter and diversity in terms of genre. As an interesting example of contemporary postmodern prose in Azerbaijan, Parviz Jabrayil's novel "In a Foreign Language" pays attention with its more different plotline. The disagreement exists among the critics about the novel. Some are looking for high artistry in work; others are satisfied with the elements of postmodernism in work. Delimitation of the border between modernism and postmodernism can serve to carry out a deep scientific study of the novel. The novel depicts the world in the author's consciousness against the background of water shortage (thirst) in the Old City (Icharishahar). The author deconstructs today's Ichari Shahar mould. Along with modernism, elements of postmodernism occupy a large place in the work. When we look at the general tendencies of postmodernist art, we see that science and individuality are questioned, criticizing the sharp boundaries of modernism and the negativity of these restrictions, and modernism offers alternatives to artistic production by identifying its negatives and shortcomings in the areas of artistic freedom. The novel is extremely interesting in this point of view.

Keywords: concept of postmodernism, modernism, delimitation, political postmodernism, modern postmodern prose, Azerbaijani literature, novel, comparison, world literature, analysis

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Authors: Katja Wiedemann, Melinda Gainschnigg

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This paper deals with gender inequality in companies. In the context of this paper, it is analyzed how women are discriminated by means of Human Resources instruments. The existing gender inequality is made apparent by the ‘Equal Pay Day. Women in Austria work without payment from 20 October onwards, which represents inequality of 21.7 percent points. This gender pay gap is due to the unequal distribution of paid and unpaid work between men and women. Since the majority of activities related to the family and care are carried out by women, there are human capital deficits on women’s side. In addition to the discrimination of women in compensation, there are also discrimination cases caused by other Human Resources instruments. The aim of this paper is to analyze the use of Human Resources instruments with regard to the discrimination of women and to identify measures to counteract this discrimination. Within the scope of this paper, possible instructions for companies on how to design and implement Human Resources instruments will be elaborated. Therefore personnel planning, recruiting, workforce management, compensation, and leadership are used as the basis for that analysis. The data were collected by a literature review and evaluated by means of a summary content analysis. The literature analysis includes papers of scientific journals from various business fields. On the basis of the results of the literature review, it is clear that women are discriminated by all analyzed Human Resources instruments. As a result, existing potentials are not optimally used. In order to limit or even prevent this loss of potential, companies must take specific measures to counteract the discrimination of women.

Keywords: employment issues, gender inequality , women's studies, workplace

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Authors: Şebnem Aslan, Demet Akarçay

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The objective of this study is to investigate the feelings of health employees occurred by bullying and the relationships between these feelings at work place. In this context, the relationships between bullying and the feelings of self-esteem, employee silence, anger, self- blame and shame. This study was conducted among 512 health employees in three hospitals in Konya by using survey method and simple random sampling. The scales of bullying, self-esteem, employee silence, anger, self-blame, and shame were performed within the study. The obtained data were analyzed with descriptive analysis, correlation, confirmative factor analysis, structural equation modeling and path analysis. The results of the study showed that while bullying had a positive effect on self-esteem (.61), employee silence (.41), anger (.18), a negative effect on self-blame and shame (-.26) was observed. Employee silence affected self-blame and shame (.83) as positively. Besides, self-esteem impacted on self- blame and shame (.18), employee silence (.62) positively and self-blame and shame was observed as negatively affecting on anger (-.20). Similarly, self-esteem was found as negatively affected on anger (-.13).

Keywords: bullying, self-esteem, employee silence, anger, shame and guilt, healthcare employee

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Authors: Genady Shlomper

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During the process of language teaching, each teacher faces some general and some specific problems. Some of these problems are mutual to all languages because they yield to the rules of cognition, conscience, perception, understanding and memory; to the physiological and psychological principles pertaining to the human race irrespective of origin and nationality. Still, every language is a distinctive system, possessing individual properties and an obvious identity, as a result of a development in specific natural, geographical, cultural and historical conditions. The individual properties emerge in the script, in the phonetics, morphology and syntax. All these problems can and should be a subject of a detailed research and scientific analysis, mainly from practical considerations and language teaching requirements. There are some formidable obstacles in the language acquisition process. Among the first to be mentioned is the existence of concepts and entire categories in foreign languages, which are absent in the language of the students. Such phenomena reflect specific ways of thinking and the world-outlook, which were shaped during the evolution. Hindi is the national language of India, which belongs to the group of Indo-Iranian languages from the Indo-European family of languages. The lecturer has gained experience in teaching Hindi language to native speakers of Uzbek, Russian and Hebrew languages. He will show the difficulties in the field of phonetics, morphology and syntax, which the students have to deal with during the acquisition of the language. In the proposed lecture the lecturer will share his experience in making the process of language teaching more efficient by using non-formal semantic approach.

Keywords: applied linguistics, foreign language teaching, language teaching methodology, semantics

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Authors: Hasan Keshavarzian, Tayebeh Nesari

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Bolted rail joint is one of the most vulnerable areas in railway track. A comprehensive approach was developed for studying the reliability of fatigue crack initiation of railroad bolt hole under random axle loads and random material properties. The operation condition was also considered as stochastic variables. In order to obtain the comprehensive probability model of fatigue crack initiation life prediction in railroad bolt hole, we used FEM, response surface method (RSM), and reliability analysis. Combined energy-density based and critical plane based fatigue concept is used for the fatigue crack prediction. The dynamic loads were calculated according to the axle load, speed, and track properties. The results show that axle load is most sensitive parameter compared to Poisson’s ratio in fatigue crack initiation life. Also, the reliability index decreases slowly due to high cycle fatigue regime in this area.

Keywords: rail-wheel tribology, rolling contact mechanic, finite element modeling, reliability analysis

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Authors: Tahir Nawaz Cheema, Dumitru Baleanu, Ali Raza

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In this research work, we design intelligent computing through Bayesian Regularization artificial neural networks (BRANNs) introduced to solve the mathematical modeling of infectious diseases (Covid-19). The dynamical transmission is due to the interaction of people and its mathematical representation based on the system's nonlinear differential equations. The generation of the dataset of the Covid-19 model is exploited by the power of the explicit Runge Kutta method for different countries of the world like India, Pakistan, Italy, and many more. The generated dataset is approximately used for training, testing, and validation processes for every frequent update in Bayesian Regularization backpropagation for numerical behavior of the dynamics of the Covid-19 model. The performance and effectiveness of designed methodology BRANNs are checked through mean squared error, error histograms, numerical solutions, absolute error, and regression analysis.

Keywords: mathematical models, beysian regularization, bayesian-regularization backpropagation networks, regression analysis, numerical computing

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Authors: I. F. Ejim, F. L. Kamen

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Aims: In this experiment, algae oil extraction with a combination of n-hexane and ethanol was investigated. The effects of extraction solvent concentration, extraction time and temperature on the yield and quality of oil were studied using Response Surface Methodology (RSM). Experimental Design: Optimization of algae oil extraction using Box-Behnken design was used to generate 17 experimental runs in a three-factor-three-level design where oil yield, specific gravity, acid value and saponification value were evaluated as the response. Result: In this result, a minimum oil yield of 17% and maximum of 44% was realized. The optimum values for yield, specific gravity, acid value and saponification value from the overlay plot were 40.79%, 0.8788, 0.5056 mg KOH/g and 180.78 mg KOH/g respectively with desirability of 0.801. The maximum point prediction was yield 40.79% at solvent concentration 66.68 n-hexane, temperature of 40.0°C and extraction time of 4 hrs. Analysis of Variance (ANOVA) results showed that the linear and quadratic coefficient were all significant at p<0.05. The experiment was validated and results obtained were with the predicted values. Conclusion: Algae oil extraction was successfully optimized using RSM and its quality indicated it is suitable for many industrial uses.

Keywords: algae oil, response surface methodology, optimization, Box-Bohnken, extraction

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: Nan Ding, Motoki Shino, Nobuyasu Tomokuni, Genki Murata

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The wheelchair is the major means of transport for physically disabled people. However, it cannot overcome architectural barriers such as curbs and stairs. In this paper, the authors proposed a method to avoid falling down of a wheeled inverted pendulum type robotic wheelchair for climbing stairs. The problem of this system is that the feedback gain of the wheels cannot be set high due to modeling errors and gear backlash, which results in the movement of wheels. Therefore, the wheels slide down the stairs or collide with the side of the stairs, and finally the wheelchair falls down. To avoid falling down, the authors proposed a slider control strategy based on skyhook model in order to decrease the movement of wheels, and a rotary link control strategy based on the staircase dimensions in order to avoid collision or slide down. The effectiveness of the proposed fall avoidance control strategy was validated by ODE simulations and the prototype wheelchair.

Keywords: EPW, fall avoidance control, skyhook, wheeled inverted pendulum

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Authors: Wooyoung Jung, Ghang Lee

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This paper paper reports the worldwide status of building information modeling (BIM) adoption from the perspectives of the engagement level, the Hype Cycle model, the technology diffusion model, and BIM-uses. An online survey was distributed, and 156 experts from six continents responded. Overall, North America was the most advanced continent, followed by Oceania and Europe. Countries in Asia perceived their phase mainly as slope of enlightenment (mature) in the Hype Cycle model. In the technology diffusion model, the main BIM-users worldwide were “early majority” (third phase), but those in the Middle East/Africa and South America were “early adopters” (second phase). In addition, the more advanced the country, the more number of BIM services employed in general. In summary, North America, Europe, Oceania, and Asia were advancing rapidly toward the mature stage of BIM, whereas the Middle East/Africa and South America were still in the early phase. The simple indexes used in this study may be used to track the worldwide status of BIM adoption in long-term surveys.

Keywords: BIM adoption, BIM services, hype cycle model, technology diffusion model

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Authors: Irfan Ahmad, Raza Ghafoor, Hammad Raza Ahmad, Muhammad Asif, Farrakh Nawaz, M. Tahir Siddiqui

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Due to the exploding population of Pakistan the pressure on natural forests is increasing to meet the demands of wood and wood based products. Agroforestry is being practiced throughout the world on scientific basis but unfortunately the farmers of Pakistan are reluctant in its adoption. The presents study was designed to assess the adoption of agroforestry practices in Faisalabad with respect to land holdings of farmers and future suitability by using Geographic information system (GIS). Faisalabad is the third largest city of the country and is famous due to the textile industry. A comprehensive survey from target villages of the Lyallpur town of Faisalabad district was carried out. Out of total 65 villages, 40 were selected for study. From each selected village, one farmer who was actively engaged in farming activities was selected. It was observed that medium sized farmers having 10-20 acre were more in number as compared to small and large farmers. Number of trees was found maximum in large farm lands, ratio of diseased trees was almost similar in all categories with maximum in small farmlands (24.1%). Regarding the future prospects 35% farmer were interested in agroforestry practices 65% were not interested in the promotion of trees due to the non-availability of technical guidance and proper markets. Geographic images of the study site can further help the researchers and policy makers in the promotion of agroforestry.

Keywords: agroforestry trends, adoption, Faisalabad, geographic information system (GIS)

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Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an "optimal" value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: cross validation, parameter averaging, parameter selection, regularization parameter search

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Authors: Indhumathi Gopal

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Undergraduate research is well documented in Science, Technology, Engineering, and Mathematics (STEM), neurosciences, and microbiology disciplines, though it is hardly part of a physical fitness & wellness discipline. However, students need experiential learning opportunities, like internships and research assistantships, to get ahead with graduate schools and be gainfully employed. The first step towards this goal is to have students do a simple research project in a semester-long course. The value of research experiences and how to integrate research activity in a physical fitness & wellness course are discussed. The investigator looks into a mini research project, “Awareness of Obesity among College Students” and explains how to guide students through the research process, including journal search, data collection, and basic statistics. Besides, students will be introduced to the statistical package program SPSS 22.0 to assist with data evaluation. The lab component of the combined lecture-physical activity course could include the measurement of student’s weight with respect to their height to obtain body mass index (BMI). Students could categorize themselves in accordance with the World Health Organization’s guidelines. Results obtained after completing the data analysis help students be aware of their own potential health risks associated with overweight and obesity. Overweight and obesity are risk factors for hypertension, hypercholesterolemia, heart disease, stroke, diabetes, and certain types of cancer. It is hoped that this experience will get students interested in scientific studies, gain confidence, think critically, and develop problem-solving and good communication skills.

Keywords: physical fitness, undergraduate research experience, obesity, BMI

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Authors: Zhongyang Sun, Shu Zhang

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In osteoblasts, L-type voltage sensitive calcium channels (LTCCs), especially the Cav1.2 LTCCs, play fundamental roles in cellular responses to external stimuli including both mechanical forces and hormonal signals. Several lines of evidence have revealed that the density of bone is increased and the resorption of bone is decreased when these calcium channels in osteoblasts are activated. And numerous studies have shown that mechanical loading promotes bone formation in the modeling skeleton, whereas removal of this stimulus in microgravity results in a reduction in bone mass. However, the effect of microgravity on LTCCs in osteoblasts is still unknown. The aim of this study was to determine whether microgravity exerts influence on LTCCs in osteoblasts and the possible mechanisms underlying. In this study, we demonstrate that simulated microgravity substantially inhibits LTCCs in osteoblast by suppressing the expression of Cav1.2. Then we show that the up-regulation of miR-103 is involved in the down-regulation of Cav1.2 expression and inhibition of LTCCs by simulated microgravity in osteoblasts. Our study provides a novel mechanism of simulated microgravity-induced adverse effects on osteoblasts, offering a new avenue to further investigate the bone loss caused by microgravity.

Keywords: L-type voltage sensitive calcium channels, Cav1.2, osteoblasts, microgravity

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Authors: Luciano E. Sewaybricker

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Psychology has faced many challenges in order to claim its right to study happiness. Probably the major issue has been to present a clear definition of happiness, which has a long history outside the scientific field and has been used imprecisely in the daily life. Even after years of great improvement, different meanings of happiness still have been seen in academic studies. This scenario allows to question if any definition is consistent enough to sustain the recent findings of the psychological processes behind happiness. Moreover, does it make sense to seek a single definition of happiness? By investigating the history of happiness and the theoretical foundations of Positive Psychology, it can be advocated that it’s proper for happiness to be polysemic. Since Ancient Greece most attempts to outline happiness consists of an appreciation of the "best way to live" and consequently requires a delineation of the most important things in life. Besides this generic definition, it’s hard to find consensus about happiness. In fact, what and how much something will be considered important to happiness depend on social influence. This compels happiness to vary between groups, historical periods, and even for the same person over time. Therefore, the same psychological processes will not necessarily be behind all forms of happiness. Consequently, three assumptions should be considered when studying happiness: it’s intrinsic of happiness to be transitory and socially influenced; happiness refers not only to what is possible in the present, but also to an ideal future; when someone (including a scientist) talks about happiness they describe and prescribe a better way to live. Because any attempt to define happiness will be limited in space and time, it's more suitable to study its variations than its universalities. This may have considerable consequences to political agenda on happiness evaluation and maximization, like Gross National Happiness and utilitarian initiatives. Happiness policies should be understood as an arbitrary choice amongst all kinds of happiness and as prescriptive of what “the best way to live” should be.

Keywords: happiness, politics, positive psychology, well-being

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Haozhe Xiang

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With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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Authors: I. O. Nascimento, J. T. Manzi

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The drying process is an important operation in the chemical industry and it is widely used in the food, grain industry and fertilizer industry. However, for demanding a considerable consumption of energy, such a process requires a deep energetic analysis in order to reduce operating costs. This paper deals with thermodynamic optimization applied to rotary dryers based on the entropy production minimization, aiming at to reduce the energy consumption. To do this, the mass, energy and entropy balance was used for developing a relationship that represents the rate of entropy production. The use of the Second Law of Thermodynamics is essential because it takes into account constraints of nature. Since the entropy production rate is minimized, optimals conditions of operations can be established and the process can obtain a substantial gain in energy saving. The minimization strategy had been led using classical methods such as Lagrange multipliers and implemented in the MATLAB platform. As expected, the preliminary results reveal a significant energy saving by the application of the optimal parameters found by the procedure of the entropy minimization It is important to say that this method has shown easy implementation and low cost.

Keywords: thermodynamic optimization, drying, entropy minimization, modeling dryers

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Hussam Alrabaiah

Abstract:

Some new projects (new proposed harbor, recreational projects) are considered in the eastern coasts of Dammam city, Saudi Arabia. Dredging operations would significantly alter coast hydrological and sediment transport processes. It is important that the project areas must keep flushing the fresh sea water in and out with good water quality parameters, which are currently facing increased pressure from urbanization and navigation requirements in conjunction with industrial developments. A suspended solids or sediments are expected to affect the flora and fauna in that area. Governing advection-diffusion equations are considered to understand the consequences of such projects. A numerical modeling study is developed to study the effect of dredging and, in particular, the suspended sediments concentrations (mg/L) changed in the region. The results were obtained using finite element method using an in-house or commercial software. Results show some consistency with data observed in that region. Recommendations based on results could be formulated for decision makers to protect the environment in the long term.

Keywords: finite element, method, suspended solids transport, advection-diffusion

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Authors: Faezeh Shalchy

Abstract:

Concrete is the most used materials in the world. It is also one of the most versatile while complex materials which human have used for construction. However, concrete is weak in tension, over the past thirty years many studies were accomplished to improve the tensile properties of concrete (cement-based materials) using a variety of methods. One of the most successful attempts is to use polymeric fibers in the structure of concrete to obtain a composite with high tensile strength and ductility. Understanding the mechanical behavior of fiber reinforced concrete requires the knowledge of the fiber/matrix interfaces at the small scale. In this study, a combination of numerical simulations and experimental techniques have been used to study the nano structure of fiber/matrix interfaces. A new model for calcium-silicate-hydrate (C-S-H)/fiber interfaces is proposed based on Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDX) analysis. The adhesion energy between the C-S-H gel and 2 different polymeric fibers (polyvinyl alcohol and polypropylene) was numerically studied at the atomistic level since adhesion is one of the key factors in the design of fiber reinforced composites. The mechanisms of adhesion as a function of the nano structure of fiber/matrix interfaces are also studied and discussed.

Keywords: fiber-reinforced concrete, adhesion, molecular modeling

Procedia PDF Downloads 331

Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

Abstract:

A Functional Model to mimic the functional correctness of a Neural Network Compute Accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of gcc compilers to BF-16 datatype, which we addressed with a native BF-16 generator integrated to our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex Neural Network Accelerator design by proposing a Functional Model-based scoreboard or Software model using SystemC. The proposed Functional Model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT bringing up micro-steps of execution.

Keywords: ISA (instruction set architecture), NN (neural network), TLM (transaction-level modeling), GEMM (general matrix multiplication)

Procedia PDF Downloads 90

Authors: Zainab Fadil, Mouath Alawadhi, Abdullah Alhusainan, Fahad Alqadiri, Abdulaziz Alqadiri

Abstract:

This study investigates how lightweight a fire resistance door will perform with under types of insulation materials. Data is initially collected from various websites, scientific books and research papers. Results show that different layers of insulation in a single door can perform better than one insulator. Furthermore, insulation materials that are lightweight, high strength and low thermal conductivity are the most preferred for fire-rated doors. Whereas heavy weight, low strength, and high thermal conductivity are least preferred for fire-resistance doors. Fire-rated doors specifications, theoretical test methodology, structural analysis, and comparison between five different models with diverse layers insulations are presented. Five different door models are being investigated with different insulation materials and arrangements. Model 1 contains an air gap between door layers. Model 2 includes phenolic foam, mild steel and polyurethane. Model 3 includes phenolic foam and glass wool. Model 4 includes polyurethane and glass wool. Model 5 includes only rock wool between the door layers. It is noticed that model 5 is the most efficient model and its design is simple compared to other models. For this model, numerical calculations are performed to check its efficiency and the results are compared to data from experiments for validation. Good agreement was noticed.

Keywords: fire resistance, insulation, strength, thermal conductivity, lightweight, layers

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Authors: Amar Al-Obaidi, Verena Kräusel, Dirk Landgrebe

Abstract:

Induction assisted single point incremental forming (IASPIF) is a flexible method and can be simply utilized to form a high strength alloys. Due to the interaction between the mechanical and thermal properties during IASPIF an evaluation for the process is necessary to be performed analytically. Therefore, a numerical simulation was carried out in this paper. The numerical analysis was operated at both room and elevated temperatures then compared with experimental results. Fully coupled dynamic temperature displacement explicit analysis was used to simulated the hot single point incremental forming. The numerical analysis was indicating that during hot single point incremental forming were a combination between complicated compression, tension and shear stresses. As a result, the equivalent plastic strain was increased excessively by rising both the formed part depth and the heating temperature during forming. Whereas, the forming forces were decreased from 5 kN at room temperature to 0.95 kN at elevated temperature. The simulation shows that the maximum true strain was occurred in the stretching zone which was the same as in experiment.

Keywords: induction heating, single point incremental forming, FE modeling, advanced high strength steel

Procedia PDF Downloads 211