Search results for: empirical modeling

Authors: Aadita Chaudhury

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Since at least the early 2000s, DNA profiling has achieved a preeminent status in forensic investigations into criminal acts. While the criminal justice system has a long history of using forensic evidence and testing them through establish technoscientific means, the primacy of DNA in establishing 'truth' or reconstructing a series of events is unparalleled in the history of forensic science. This paper seeks to elucidate the ways in which DNA profiling has become the most authoritative instrument of 'truth' in criminal investigations, and how it is used in the legal process to ascertain culpability, create the notion of infallible evidence, and advance the search for justice. It is argued that DNA profiling has created a paradigm shift in how the legal system and the general public understands crime and culpability, but not without limitations. There are indications that even trace amounts of DNA evidence can point to causal links in a criminal investigation, however, there still remains many rooms to create confusion and doubt from empirical evidence within the narrative of crimes. Many of the shortcomings of DNA-based forensic investigations are explored and evaluated with regards to claims of the authority of biological evidence and implications for the public understanding of the elusive concepts of truth and justice in the present era. Public misinformation about the forensic analysis processes could produce doubt or faith in the judgements rooted in them, depending on other variables presented at the trial. A positivist understanding of forensic science that is shared by the majority of the population does not take into consideration that DNA evidence is far from definitive, and can be used to support any theories of culpability, to create doubt and to deflect blame.

Keywords: DNA profiling, epistemology of forensic science, philosophy of forensic science, sociology of scientific knowledge

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Authors: Carola Cappa

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Chickpea cooking water (known as aquafaba, AF) is a “waste” product having interesting technological properties exploitable for sustainable plant-based food applications that can encounter a larger consumers demand. Different process conditions to obtain AF were defined; the addition of hydrocolloid (i.e., guar gum) and lactic acid to improve the techno-functionalities of aquafaba was explored, and the effects of these ingredients on the foaming properties and the quality of plant-based target confectionery products were investigated. Meringues having a solid foam structure and a simple formulation (i.e., foaming agent and sugar) and chocolate mousse were chosen as target foods. The effects of the sugar particle size reduction on the empirical and fundamental rheological properties of the foaming agent and of the mousse were evaluated. The treatment did not significantly change the viscosity of the system, while the overrun and foam stability were affected by sugar particle size, and mousse with coarse sugar was characterized by a higher consistency, confirming the importance of the particle size of the ingredients on the texture of the final product. This study proved that AF, a recycled “waste” product, possesses interesting techno-functionalities properties further enhanced by adding lactic acid and modulable according to ingredient particle size; these AF results are useable for plant-based food applications.

Keywords: foaming properties, foam stability, foam texture, particle size, acidification, aquafaba

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Authors: Javad Khazaei, Rick Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: consensus tracking, distributed control, model-free control, sparse identification of dynamical systems

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Authors: Miron A, Tadmor R, Pinkert S

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Soil contamination is a pressing environmental concern, drawing considerable focus due to its adverse ecological and health outcomes, and the frequent occurrence of contamination incidents in recent years. The interaction between the oil pollutant and the host soil can alter the mechanical properties of the soil in a manner that can crucially affect engineering challenges associated with the stability of soil systems. The geotechnical investigation of contaminated soils has gained momentum since the Gulf War in the 1990s, when a massive amount of oil was spilled into the ocean. Over recent years, various types of soil contaminations have been studied to understand the impact of pollution type, uncovering the mechanical complexity that arises not just from the pollutant type but also from the properties of the host soil and the interplay between them. This complexity is associated with diametrically opposite effects in different soil types. For instance, while certain oils may enhance the frictional properties of cohesive soils, they can reduce the friction in granular soils. This striking difference can be attributed to the different mechanisms at play: physico-chemical interactions predominate in the former case, whereas lubrication effects are more significant in the latter. this study introduces an empirical law designed to quantify the mechanical effect of oil contamination in granular soils, factoring the properties of both the contaminating oil and the host soil. This law is achieved by comprehensive experimental research that spans a wide array of oil types and soils with unique configurations and morphologies. By integrating these diverse data points, our law facilitates accurate predictions of how oil contamination modifies the frictional characteristics of general granular soils.

Keywords: contaminated soils, lubrication, friction, granular media

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Authors: Eddegdag Nasser, Naamane Azzeddine, Radouani Mohammed, Ensam Meknes

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In this study, we are interested in the asymptotic modeling of the two-dimensional stationary supersonic flow of a viscous compressible fluid around wing airfoil. The aim of this article is to solve the partial differential equations of the flow far from the leading edge and near the wall using the triple-deck technique is what brought again in precision according to the principle of least degeneration. In order to validate our theoretical model, these obtained results will be compared with the experimental results. The comparison of the results of our model with experimentation has shown that they are quantitatively acceptable compared to the obtained experimental results. The experimental study was conducted using the AF300 supersonic wind tunnel and a NACA Reduced airfoil model with two pressure Taps on extrados. In this experiment, we have considered the incident upstream supersonic Mach number over a dissymmetric NACA airfoil wing. The validation and the accuracy of the results support our model.

Keywords: supersonic, viscous, triple deck technique, asymptotic methods, AF300 supersonic wind tunnel, reduced airfoil model

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Authors: Ching-I Chen

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The continued rise of e-commerce is the main driver of the rapid growth of global online purchase. Consumers can nearly buy everything they want at one occasion through online shopping. The purchase behavior models which focus on single product category are insufficient to describe online shopping behavior. Therefore, analysis of multi-category purchase gets more and more popular. For example, market basket analysis explores customers’ buying tendency of the association between product categories. The information derived from market basket analysis facilitates to make cross-selling strategies and product recommendation system. To detect the association between different product categories, we use the market basket analysis with the multidimensional scaling technique to build an associated map which describes how likely multiple product categories are bought at the same time. Besides, we also build an inter-purchase time model for associated products to describe how likely a product will be bought after its associated product is bought. We classify inter-purchase time behaviors of multi-category products into nine types, and use a mixture regression model to integrate those behaviors under our assumptions of purchase sequences. Our sample data is from comScore which provides a panelist-label database that captures detailed browsing and buying behavior of internet users across the United States. Finding the inter-purchase time from books to movie is shorter than the inter-purchase time from movies to books. According to the model analysis and empirical results, this research finally proposes the applications and recommendations in the management.

Keywords: multiple-category purchase behavior, inter-purchase time, market basket analysis, e-commerce

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Authors: Zahid Ullah, Atlas Khan

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The presented research is dedicated to an extensive examination of the regularity properties associated with a specific class of equations, namely extremely degenerate elliptic equations. This study holds significance in unraveling the complexities inherent in these equations and understanding the smoothness of their solutions. The focus is on analyzing the regularity of results, aiming to contribute to the broader field of mathematical theory. By delving into the intricacies of extremely degenerate elliptic equations, the research seeks to advance our understanding beyond conventional analyses, addressing challenges posed by degeneracy and pushing the boundaries of classical analytical methods. The motivation for this exploration lies in the practical applicability of mathematical models, particularly in real-world scenarios where physical phenomena exhibit characteristics that challenge traditional mathematical modeling. The research aspires to fill gaps in the current understanding of regularity properties within solutions to extremely degenerate elliptic equations, ultimately contributing to both theoretical foundations and practical applications in diverse scientific fields.

Keywords: investigating smoothness, extremely degenerate elliptic equations, regularity properties, mathematical analysis, complexity solutions

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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: Tien-Hui Chiang

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The code theory, proposed by Basil Bernstein, indicates that framing can be viewed as the core element in constituting the phenomenon of cultural reproduction because it is able to regulate the transmission of pedagogical information. Strong framing increases the social relation boundary between a teacher and pupils, which obstructs information transmission, so that in order to improve underachieving students’ academic performances, teachers need to reduce to strength of framing. Weak framing enables them to transform academic knowledge into commonsense knowledge in daily life language. This study posits that most teachers would deliver strong framing due to their belief mainly confined within the aspect of instrumental rationality that deprives their critical minds. This situation could make them view the normal distribution bell curve of students’ academic performances as a natural outcome. In order to examine the interplay between framing, instrumental rationality and pedagogical action, questionnaires were completed by over 5,000 primary school teachers in Henan province, China, who were stratified sample. The statistical results show that most teachers employed psychological concepts to measure students’ academic performances and, in turn, educational inequity was legitimatized as a natural outcome in the efficiency-led approach. Such efficiency-led minds made them perform as the agent practicing the mechanism of social control and in turn sustaining the phenomenon of cultural reproduction.

Keywords: code, cultural reproduction, framing, instrumental rationality, social relation and interaction

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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: Lethamaga Tladi, Ray Kekwaletswe

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This study sought to conceptualise a multi-level framework for the effective use of stock ordering system in small enterprises in a rural area context. The interpretive research methodology has been used to enable the researcher to analyse, in-depth, and the subjective meanings of small enterprises’ employees in using the stock ordering system. The empirical data was collected from 13 small enterprises’ employees as participants through semi-structured interviews and observations. Interpretive Phenomenological Analysis (IPA) approach was used to analyse the small enterprises’ employee’s own account of lived experiences in relations to stock ordering system use in terms of their relatedness to, and cognitive engagement with. A case study of Kgautswane, a rural area in Limpopo Province, South Africa, served as a social context where the phenomenon manifested. Technology-Organisation-Environment Theory (TOE), Technology-to-Performance Chain Model (TPC), and Representation Theory (RT) underpinned this study. In this multi-level study, the findings revealed that; At the organisational level, the effective use of stock ordering system was found to be associated with the organisational performance gains such as efficiency, productivity, quality, competitiveness, and market share. Equally so, at the individual level, the effective use of stock ordering system minimised the end-user’s efforts and time to accomplish their tasks, which yields improved individual performance. The Multi-level framework for effective use of stock ordering system was presented.

Keywords: effective use, multi-dimensions of use, multi-level of use, multi-level research, small enterprises, stock ordering system

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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: Volker Koch, Sigrid Swobodnik, Bernd M. Zunk

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The success of companies on globalized markets is significantly influenced by the performance of purchasing departments and, of course, the individuals employed as professional purchasers. Nonetheless, this is generally accepted in practice, in literature as well as in empirical research, only insufficient attention was given to the assessment of this relationship between the personality of professional purchasers and their individual performance. This paper aims to describe the relationship against the background of the 'Big Five Inventory'. Based on the five dimensions of a personality (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) a research model was designed. The research model divides the individual performance of professional purchasers into two major dimensions: operational and strategic. The operational dimension consists of the items 'cost', 'quality delivery' and 'flexibility'; the strategic dimension comprises the positions 'innovation', 'supplier satisfaction' as wells as 'purchasing and supply management integration in the organization'. To test the research model, a survey study was performed, and an online questionnaire was sent out to purchasing professionals in Austrian companies. The data collected from 78 responses was used to test the research model applying a group comparison. The comparison points out that there is (i) an influence of the purchasers’ personality on the individual performance of professional purchasers and (ii) a link between purchasers’ personality to a high or a low individual performance of professional purchasers. The findings of this study may help human resource managers during staff recruitment processes to identify the 'right performing personality' for an operational and/or a strategic position in purchasing departments.

Keywords: big five inventory, individual performance, personality, purchasing professionals

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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: Sonja Goegele, Petra Kletzenbauer

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The FH JOANNEUM- a university of applied sciences based in Austria - cooperates in teaching and research with well-known international universities and thus aims to foster so-called strategic partnerships. The exchange of university lecturers and other faculty members is a way to achieve and secure strategic company goals, in which excellent research and teaching play a central role in order to improve both the development of academics and administration. Thanks to mobility not only the university but also the involved people truly benefit in their professional development which can be seen on several levels: increased foreign language proficiency, excellent networking possibilities within the scientific community as well as reinforced didactic competencies in the form of different teaching and learning methodologies. The paper discusses mobility in the light of the university’s strategic paper entitled ‘Hands on 2022’ by presenting results from an empirical research study among faculty members who participate in exchange programmes on a regular basis. In the form of an online questionnaire, mobility was discussed from different angles such as networking, collaborative research, professional training for academics and the overall impact of the exchange within and outside the organization. From the findings, it can be concluded that mobility is an asset for any university. However, keeping in constant dialogue with partner universities requires more than the purpose of the exchange itself. Building rapport and keeping a relationship of trust are challenges that need to be addressed more closely in order to run successful mobility programmes. Best Practice examples should highlight the importance of mobility as a vital initiative to transfer disciplines.

Keywords: higher education, internationalization, mobility, strategic partnerships

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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: Seipati Baloyi-Mothibedi, Wendy Setlalentoa

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Recently scholars have shown much interest in the engagement and involvement of educational stakeholders in early childhood development (ECD) research, which has yielded positive results for ECD globally, especially in South Africa. Realising this gap, this study reports on the establishment of the research group comprising teachers, parents, and education stakeholders, which aimed to enhance curriculum practice in a grade R mathematics class. We adopted bricolage as a theoretical lens, mainly for its multi-layered, multi-methodological, multi-perspectival, and metatheoretical benefits to make sense in reviewing the literature as well as the empirical part of the study. A participatory action research (PAR) study using collaborative information sessions, meetings, workshops, and as well transcend movements were employed in order to engage the team to have first-hand information in enhancing curriculum practice in a grade R mathematics class was conducted. We adopted audiovisuals, photo voices, and lesson demonstrations to generate the data. The generated data were transcribed into texts that were further analysed using three levels based on the spoken or written texts and social and discursive practices. At the end of the discourses, the findings showed that engagement, involvement, and inclusion of different education stakeholders were instrumental in enhancing curriculum practice in a grade R mathematics class for the highest attainment. From the findings, we developed a strategy for engagement and involvement of teachers, parents, and the education stakeholders in enhancing curriculum practice in grade R mathematics class.

Keywords: engagement, involvement, curriculum practice, grade R, mathematics class

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Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze

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Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.

Keywords: groundwater, vulnerability, DRASTIC model, pollution

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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: Tanja Salary

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This study uncovers a gap in the research and adds to the body of knowledge regarding medication errors in a juvenile justice facility. The study includes an introduction to data collected about medication errors in a juvenile justice facility and explores contributing factors that relate to those errors. The data represent electronic incident records of the medication errors that were documented from the years 2011 through 2019. In addition, this study reviews both current and historical research of empirical data about patient safety standards and quality care comparing traditional healthcare facilities to juvenile justice residential facilities. The theoretical/conceptual framework for the research study pertains to Bandura and Adams’s (1977) framework of self-efficacy theory of behavioral change and Mark Friedman’s results-based accountability theory (2005). Despite the lack of evidence in previous studies about addressing medication errors in juvenile justice facilities, this presenter will relay information that adds to the body of knowledge to note the importance of how assessing the potential relationship between medication errors. Implications for more research include recommendations for more education and training regarding increased communication among juvenile justice staff, including nurses, who administer medications to juveniles to ensure adherence to patient safety standards. There are several opportunities for future research concerning other characteristics about factors that may affect medication administration errors within the residential juvenile justice facility.

Keywords: juvenile justice, medication errors, psychotropic medications, behavioral health, juveniles, incarcerated youth, recidivism, patient safety

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Authors: Adetunji Abiola Olaoye

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The study examined the students’ self-concepts and mathematics achievement viz-a-viz the existing three theoretical models: Humanist self-concept (M1), Contemporary self-concept (M2) and Skills development self-concept (M3). As a qualitative research study, it comprised of one research question, which was transformed into hypothesis viz-a-viz the existing theoretical models. Sample to the study comprised of twelve public secondary schools from which twenty-five mathematics teachers, twelve counselling officers and one thousand students of Upper Basic II were selected based on intact class as school administrations and system did not allow for randomization. Two instruments namely 10 items ‘Achievement test in Mathematics’ (r1=0.81) and 10 items Student’s self-concept questionnaire (r2=0.75) were adapted, validated and used for the study. Data were analysed through descriptive, one way ANOVA, t-test and correlation statistics at 5% level of significance. Finding revealed mean and standard deviation of pre-achievement test scores of (51.322, 16.10), (54.461, 17.85) and (56.451, 18.22) for the Humanist Self-Concept, Contemporary Self-Concept and Skill Development Self-Concept respectively. Apart from that study showed that there was significant different in the academic performance of students along the existing models (F-cal>F-value, df = (2,997); P<0.05). Furthermore, study revealed students’ achievement in mathematics and self-concept questionnaire with the mean and standard deviation of (57.4, 11.35) and (81.6, 16.49) respectively. Result confirmed an affirmative relationship with the Contemporary Self-Concept model that expressed an individual subject and specific self-concept as the primary determinants of higher academic achievement in the subject as there is a statistical correlation between students’ self-concept and mathematics achievement viz-a-viz the existing three theoretical models of Contemporary (M2) with -Z_cal<-Z_val, df=998: P<0.05*. The implication of the study was discussed with recommendations and suggestion for further studies proffered.

Keywords: contemporary, humanists, self-concepts, skill development

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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: Ki Hyun Park, Hye Min Park, Jeong Ho Kim, Chan Jong Park, Koan Sik Joo

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In the modern days, the use of radioactive substances is on the rise in the areas like chemical weaponry, industrial usage, and power plants. Although there are various technologies available to detect and monitor radioactive substances in the air, the technologies to detect underwater radioactive substances are scarce. In this study, computer simulation of the underwater detection system measuring beta-ray, a radioactive substance, has been done through MCNP. CaF₂, YAP(Ce) and YAG(Ce) have been used in the computer simulation to detect beta-ray as scintillator. Also, the source used in the computer simulation is Sr-90 and Y-90, both of them emitting only pure beta-ray. The distance between the source and the detector was shifted from 1mm to 10mm by 1 mm in the computer simulation. The result indicated that Sr-90 was impossible to measure below 1 mm since its emission energy is low while Y-90 was able to be measured up to 10mm underwater. In addition, the detector designed with CaF₂ had the highest efficiency among 3 scintillators used in the computer simulation. Since it was possible to verify the detectable range and the detection efficiency according to modeling through MCNP simulation, it is expected that such result will reduce the time and cost in building the actual beta-ray detector and evaluating its performances, thereby contributing the research and development.

Keywords: Beta-ray, CaF₂, detector, MCNP simulation, scintillator

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

Abstract:

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

Abstract:

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

Procedia PDF Downloads 280