Search results for: Multiple Factorial Correspondence Analysis

Authors: Matheus Borges Carneiro, Fabiane Leticia Lizarelli, José Carlos De Toledo

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The evolution of quality management by companies was strongly enabled by, among others, ISO 9001 certification, which is considered a crucial requirement for several customers. Likewise, performance measurement provides useful insights for companies to identify the reflection of their decision-making process on their improvement. One of the most used performance measurement models is the balanced scorecard (BSC), which uses four perspectives to address a firm’s performance: financial, internal process, customer satisfaction, and learning and growth. Studies related to ISO 9001 and business performance have mostly adopted a quantitative approach to identify the standard’s causal effect on a firm’s performance. However, to verify how this influence may occur, an in-depth analysis within a qualitative approach is required. Therefore, this paper aims to verify the impact of ISO 9001:2015 on Brazilian firms’ performance based on the balanced scorecard perspective. Hence, nine certified companies located in the Southeast region of Brazil were studied through a multiple case study approach. Within this study, it was possible to identify the positive impact of ISO 9001 on firms’ overall performance, and four Critical Success Factors (CSFs) were identified as relevant on the linkage among ISO 9001 and firms’ performance: employee involvement, top management, process management, and customer focus. Due to the COVID-19 pandemic, the number of interviews was limited to the quality manager specialist, and the sample was limited since several companies were closed during the period of the study. This study presents an in-depth analysis of how the relationship between ISO 9001 certification and firms’ performance in a developing country is.

Keywords: balanced scorecard, Brazilian firms’ performance, critical success factors, ISO 9001 certification, performance measurement

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Authors: Aiman Mazhar Qureshi, Ahmed Rachid

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Extreme heat events are emerging human environmental health concerns in dense urban areas due to anthropogenic activities. High spatial and temporal resolution heat maps are important for urban heat adaptation and mitigation, helping to indicate hotspots that are required for the attention of city planners. The Heat Vulnerability Index (HVI) is the important approach used by decision-makers and urban planners to identify heat-vulnerable communities and areas that require heat stress mitigation strategies. Amiens is a medium-sized French city, where the average temperature has been increasing since the year 2000 by +1°C. Extreme heat events are recorded in the month of July for the last three consecutive years, 2018, 2019 and 2020. Poor air quality, especially ground-level ozone, has been observed mainly during the same hot period. In this study, we evaluated the HVI in Amiens during extreme heat days recorded last three years (2018,2019,2020). The Principal Component Analysis (PCA) technique is used for fine-scale vulnerability mapping. The main data we considered for this study to develop the HVI model are (a) socio-economic and demographic data; (b) Air pollution; (c) Land use and cover; (d) Elderly heat-illness; (e) socially vulnerable; (f) Remote sensing data (Land surface temperature (LST), mean elevation, NDVI and NDWI). The output maps identified the hot zones through comprehensive GIS analysis. The resultant map shows that high HVI exists in three typical areas: (1) where the population density is quite high and the vegetation cover is small (2) the artificial surfaces (built-in areas) (3) industrial zones that release thermal energy and ground-level ozone while those with low HVI are located in natural landscapes such as rivers and grasslands. The study also illustrates the system theory with a causal diagram after data analysis where anthropogenic activities and air pollution appear in correspondence with extreme heat events in the city. Our suggested index can be a useful tool to guide urban planners and municipalities, decision-makers and public health professionals in targeting areas at high risk of extreme heat and air pollution for future interventions adaptation and mitigation measures.

Keywords: heat vulnerability index, heat mapping, heat health-illness, remote sensing, urban heat mitigation

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Authors: Yongjian Du, Jinhua Sun, Kim M. Liew, Huahua Xiao

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Optimal allocation of emergency resources before a disaster is of great importance for emergency response. In reality, the pre-protection for a single critical node where accidents may occur is common. In this study, a model is developed to determine location and inventory decisions of multiple emergency resources among a set of candidate stations to minimize the total cost based on the constraints of budgetary and capacity. The total cost includes the economic accident loss which is accorded with probability distribution of time and the warehousing cost of resources which is increasing over time. A ratio is set to measure the degree of a storage station only serving the target node that becomes larger with the decrease of the distance between them. For the application of linear program, it is assumed that the length of travel time to the accident scene of emergency resources has a linear relationship with the economic accident loss. A computational experiment is conducted to illustrate how the proposed model works, and the results indicate its effectiveness and practicability.

Keywords: emergency response, integer linear program, multiple emergency resources, pre-allocation decisions, single potential accident node

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Authors: Muhammad Fezan Afzal, Asad Abbas, Imran Khan, Salma Imtiaz

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Software Product Line (SPL) paradigm is used for the development of the family of software products that share common and variable features. Feature model is a domain of SPL that consists of common and variable features with predefined relationships and constraints. Multiple SPLs consist of a number of similar common and variable features, such as mobile phones and Tabs. Reusability of common and variable features from the different domains of SPL is a complex task due to the external relationships and constraints of features in the feature model. To increase the reusability of feature model resources from domain engineering, it is required to manage the commonality of features at the level of SPL application development. In this research, we have proposed an approach that combines multiple SPLs into a single domain and converts them to a common feature model. Extracting the common features from different feature models is more effective, less cost and time to market for the application development. For extracting features from multiple SPLs, the proposed framework consists of three steps: 1) find the variation points, 2) find the constraints, and 3) combine the feature models into a single feature model on the basis of variation points and constraints. By using this approach, reusability can increase features from the multiple feature models. The impact of this research is to reduce the development of cost, time to market and increase products of SPL.

Keywords: software product line, feature model, variability management, multi-SPLs

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Authors: Mercedes Sepulveda, Saras Henderson, Dana Farrell, Gaby Heuft

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In Australia, there is a significant number of Culturally and Linguistically Diverse (CALD) Grandparent Carers who are sole carers for their grandchildren. Services in the community such as accessible healthcare, financial support, legal aid, and transport to services can assist Grandparent Carers to continue to live in their own home whilst caring for their grandchildren. Community nurses can play a major role by being aware of the needs of these grandparents and link them to services via information and referrals. The CALD Grandparent Carer experiences have only been explored marginally and may be similar to the general Grandparent Carer population, although cultural aspects may add to their difficulties. This Needs-Gap Analysis aimed to uncover ‘hidden issues’ for CALD Grandparent Carers such as service gaps and actions needed to address these issues. The stakeholders selected for this Needs-Gap Analysis were drawn from relevant service providers such as community and aged care services, child and/or grandparents support services and CALD specific services. One hundred relevant service providers were surveyed using six structured questions via face to face, phone interviews, or email correspondence. CALD Grandparents who had a significant or sole role of being a carer for grandchildren were invited to participate through their CALD community leaders. Consultative Forums asking five questions that focused on the caring role, issues encountered, and what needed to be done, were conducted with the African, Asian, Spanish-Speaking, Middle Eastern, European, Pacific Islander and Maori Grandparent Carers living in South-east Queensland, Australia. Data from the service provider survey and the CALD Grandparent Carer forums were content analysed using thematic principles. Our findings highlighted social determinants of health grouped into six themes. These were; 1) service providers and Grandparent Carer perception that there was limited research data on CALD grandparents as carers; 2) inadequate legal and financial support; 3) barriers to accessing information and advice; 4) lack of childcare options in the light of aging and health issues; 5) difficulties around transport; and 6) inadequate technological skills often leading to social isolation for both carer and grandchildren. Our Needs-Gap Analysis provides insight to service providers especially health practitioners such as doctors and community nurses, particularly on the impact of caring for grandchildren on CALD Grandparent Carers. Furthermore, factors such as cultural differences, English language difficulties, and migration experiences also impacted on the way CALD Grandparent Carers are able to cope. The findings of this Need-Gap Analysis signposts some of the ‘ hidden issues’ that CALD Grandparents Carers face and draws together recommendations for the future as put forward by the stakeholders themselves.

Keywords: CALD grandparents, carer needs, community nurses, grandparent carers

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Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri

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Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.

Keywords: connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks

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Authors: Sabiu Bala Muhammad, Rosli Saad

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Multiple linear regression (MLR) models for fast estimation of true subsurface resistivity from apparent resistivity field measurements are developed and assessed in this study. The parameters investigated were apparent resistivity (ρₐ), horizontal location (X) and depth (Z) of measurement as the independent variables; and true resistivity (ρₜ) as the dependent variable. To achieve linearity in both resistivity variables, datasets were first transformed into logarithmic domain following diagnostic checks of normality of the dependent variable and heteroscedasticity to ensure accurate models. Four MLR models were developed based on hierarchical combination of the independent variables. The generated MLR coefficients were applied to another data set to estimate ρₜ values for validation. Contours of the estimated ρₜ values were plotted and compared to the observed data plots at the colour scale and blanking for visual assessment. The accuracy of the models was assessed using coefficient of determination (R²), standard error (SE) and weighted mean absolute percentage error (wMAPE). It is concluded that the MLR models can estimate ρₜ for with high level of accuracy.

Keywords: apparent resistivity, depth, horizontal location, multiple linear regression, true resistivity

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Authors: Azene Tesfaye, Yohannes Petros, Habtamu Zeleke

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To evaluate genetic variation among Ethiopian lentil, laboratory experiment were conducted to screen 12 accessions of lentil (Lens culinaris M.) for salt tolerance. Seeds of 12 Lentil accessions were grown at laboratory (Petri dish) condition with different levels of salinity (0, 2, 4, and 8 dSm-1 NaCl) for 4 weeks. The experimental design was completely randomized design (CRD) in factorial combination with three replications. Data analysis was carried out using SAS software. Average germination time, germination percentage, seedling shoot and root traits, seedling shoot and root weight were evaluated. The two way ANOVA for varieties revealed statistically significant variation among lentil accession, NaCl level and their interactions (p<0.001) with respect to the entire parameters. It was found that salt stress significantly delays germination rate and decreases germination percentage, shoot and root length, seedling shoot and root weight of lentil accessions. The degree of decrement varied with accessions and salinity levels. Accessions 36120, 9235 and 36004 were better salt tolerant than the other accessions. As the result, it is recommended to be used as a genetic resource for the development of lentil accession and other very salt sensitive crop with improved germination under salt stress condition.

Keywords: accession, germination, lentil, NaCl, screening, seedling stage

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Authors: Syed Asif Hassan, Tabrej Khan

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Multiple sclerosis (MS) is a chronic demyelinating autoimmune disorder, of the central nervous system (CNS). In the present scenario, the current therapies either do not halt the progression of the disease or have side effects which limit the usage of current Disease Modifying Therapies (DMTs) for a longer period of time. Therefore, keeping the current treatment failure schema, we are focusing on screening novel analogues of the available DMTs that specifically bind and inhibit the Sphingosine1-phosphate receptor1 (S1PR1) thereby hindering the lymphocyte propagation toward CNS. The novel drug-like analogs molecule will decrease the frequency of relapses (recurrence of the symptoms associated with MS) with higher efficacy and lower toxicity to human system. In this study, an integrated approach involving ligand-based virtual screening protocol (Ultrafast Shape Recognition with CREDO Atom Types (USRCAT)) to identify the non-toxic drug like analogs of the approved DMTs were employed. The potency of the drug-like analog molecules to cross the Blood Brain Barrier (BBB) was estimated. Besides, molecular docking and simulation using Auto Dock Vina 1.1.2 and GOLD 3.01 were performed using the X-ray crystal structure of Mtb LprG protein to calculate the affinity and specificity of the analogs with the given LprG protein. The docking results were further confirmed by DSX (DrugScore eXtented), a robust program to evaluate the binding energy of ligands bound to the ligand binding domain of the Mtb LprG lipoprotein. The ligand, which has a higher hypothetical affinity, also has greater negative value. Further, the non-specific ligands were screened out using the structural filter proposed by Baell and Holloway. Based on the USRCAT, Lipinski’s values, toxicity and BBB analysis, the drug-like analogs of fingolimod and BG-12 showed that RTL and CHEMBL1771640, respectively are non-toxic and permeable to BBB. The successful docking and DSX analysis showed that RTL and CHEMBL1771640 could bind to the binding pocket of S1PR1 receptor protein of human with greater affinity than as compared to their parent compound (Fingolimod). In this study, we also found that all the drug-like analogs of the standard MS drugs passed the Bell and Holloway filter.

Keywords: antagonist, binding affinity, chemotherapeutics, drug-like, multiple sclerosis, S1PR1 receptor protein

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Authors: Luciana Brandao Ferreira, Janaina de Moura Engracia Giraldi, Fabiana Gondim Mariutti, Marina Toledo de Arruda Lourencao

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Developing countries, such as BRICS (Brazil, Russia, India, China and South Africa) are hosting sports mega-events to promote socio-economic development and image enhancement. Thus, this paper aims to verify the image of Rio de Janeiro, in Brazil, as the host city of 2016 Olympic Games, considering the main cognitive and affective image dimensions. The research design uses exploratory factorial analysis to find the most important factors highlighted in the city image dimensions. The data were collected by structured questionnaires with an international respondents sample (n=274) with high international travel experience. The results show that Rio’s image as a sport mega-event host city has two main factors in each dimension: Cognitive ('General Infrastructure'; 'Services and Attractions') and Affective ('Positive Feelings'; 'Negative Feelings'). The most important factor related to cognitive dimension was 'Services and Attractions' which is more related to tourism activities. In the affective dimension 'Positive Feelings' was the most important factor, which means a good result considering that is a city in an emerging country with many unmet social demands.

Keywords: Rio de Janeiro, 2016 olympic games, host city image, cognitive image dimension, affective image dimension

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Authors: Tzu-Ling Hsieh

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When the Taiwan Ministry of Education implemented a new university multiple entrance policy in 2002, most colleges and universities still use testing scores as mainly admission criteria. With forthcoming 12 basic-year education curriculum, the Ministry of Education provides a new college admission policy, which will be implemented in 2021. The new college admission policy will highlight the importance of holistic education by more emphases on the learning process of senior high school, except only on the outcome of academic testing. However, the development of college admission criteria doesn’t have a thoughtful process. Universities and colleges don’t have an idea about how to make suitable multi-admission criteria. Although there are lots of studies in other countries which have implemented multi-college admission criteria for years, these studies still cannot represent Taiwanese students. Also, these studies are limited without the comparison of two different academic fields. Therefore, this study investigated multiple admission criteria and its relationship with college success. This study analyzed the Taiwan Higher Education Database with 12,747 samples from 156 universities and tested a conceptual framework that examines factors by structural equation model (SEM). The conceptual framework of this study was adapted from Pascarella's general causal model and focused on how different admission criteria predict students’ college success. It discussed the relationship between admission criteria and college success, also the relationship how motivation (one of admission standard) influence college success through engagement behaviors of student effort and interactions with agents of socialization. After processing missing value, reliability and validity analysis, the study found three indicators can significantly predict students’ college success which was defined as average grade of last semester. These three indicators are the Chinese language scores at college entrance exam, high school class rank, and quality of student academic engagement. In addition, motivation can significantly predict quality of student academic engagement and interactions with agents of socialization. However, the multi-group SEM analysis showed that there is no difference to predict college success between the students from liberal arts and science. Finally, this study provided some suggestions for universities and colleges to develop multi-admission criteria through the empirical research of Taiwanese higher education students.

Keywords: college admission, admission criteria, structural equation modeling, higher education, education policy

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Authors: Majid Pourahmadi

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The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.

Keywords: microwave imaging, time reversal, MUSIC algorithm, minimum description length (MDL)

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Authors: Chokri Slim

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The objective of this research is attempting to respond to this question: Is there a significant difference between the regression model and statistical learning models in predicting credit risk management? A Multiple Linear Regression (MLR) model was compared with neural networks including Multi-Layer Perceptron (MLP), and a Support vector regression (SVR). The population of this study includes 50 listed Banks in Tunis Stock Exchange (TSE) market from 2000 to 2016. Firstly, we show the factors that have significant effect on the quality of loan portfolios of banks in Tunisia. Secondly, it attempts to establish that the systematic use of objective techniques and methods designed to apprehend and assess risk when considering applications for granting credit, has a positive effect on the quality of loan portfolios of banks and their future collectability. Finally, we will try to show that the bank governance has an impact on the choice of methods and techniques for analyzing and measuring the risks inherent in the banking business, including the risk of non-repayment. The results of empirical tests confirm our claims.

Keywords: credit risk management, multiple linear regression, principal components analysis, artificial neural networks, support vector machines

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Authors: Abolfazl Hosseinkhani, Sepehr Sanaye

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Different approaches have been used to predict the performance of the vertical axis wind turbines (VAWT), such as experimental, computational fluid dynamics (CFD), and analytical methods. Analytical methods, such as momentum models that use streamtubes, have low computational cost and sufficient accuracy. The double multiple streamtube (DMST) is one of the most commonly used of momentum models, which divide the rotor plane of VAWT into upwind and downwind. In fact, results from the DMST method have shown some discrepancy compared with experiment results; that is because the Darrieus turbine is a complex and aerodynamically unsteady configuration. In this study, analytical-experimental-based corrections, including dynamic stall, streamtube expansion, and finite blade length correction are used to improve the DMST method. Results indicated that using these corrections for a SANDIA 17-m VAWT will lead to improving the results of DMST.

Keywords: vertical axis wind turbine, analytical, double multiple streamtube, streamtube expansion model, dynamic stall model, finite blade length correction

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Authors: Reza Vakili

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The aim of this experiment was to optimize the effect of moisture, the production rate, grain particle size and steam conditioning temperature on pellet quality in broiler feed using Taguchi method and a 43 fractional factorial arrangement was conducted. Production rate, steam conditioning temperatures, particle sizes and moisture content were performed. During the production process, sampling was done, and then pellet durability index (PDI) and hardness evaluated in broiler feed grower and finisher. There was a significant effect of processing parameters on PDI and hardness. Based on the results of this experiment Taguchi method can be used to find the best combination of factors for optimal pellet quality.

Keywords: broiler, feed physical quality, hardness, processing parameters, PDI

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Authors: Sina Mahdavi

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Background and Objective: Multiple sclerosis (MS) is the most common inflammatory autoimmune disease of the central nervous system (CNS) that affects the myelination process in the CNS. Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially Epstein-Barr virus (EBV) and MS, is one potential cause that is not well understood. In this study, we aim to summarize the available data on EBV infection in MS disease progression. Materials and Methods: For this study, the keywords "Multiple sclerosis," "Epstein-Barr virus," and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2016 and 2022 were searched, and 14 articles were chosen, studied, and analyzed. Results: Demyelinated lesions isolated from MS patients contain EBNAs from EBV proteins. The EBNA1 domain contains a pentapeptide fragment identical to B-crystallin, a heat shock peptide, that is increased in peripheral B cells in response to B-crystallin infection, resulting in myelin-directed autoimmunity mediated by proinflammatory T cells. EBNA2, which is involved in the regulation of viral transcription, may enhance transcription from MS risk loci. A 7-fold increase in the risk of MS has been observed in EBV infection with HLA-DR15 synergy. Conclusion: EBV infection along with a variety of specific genetic risk alleles, cause inflammatory cascades in the CNS by infected B cells. There is a high expression of EBV during the course of MS, which indicates the relationship between EBV and MS, that this virus can play a role in the development of MS by creating an inflammatory state. Therefore, measures to modulate the expression of EBV may be effective in reducing inflammatory processes in demyelinated areas of MS patients.

Keywords: multiple sclerosis, Epstein-Barr virus, central nervous system, EBNAs

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Authors: Segun Jacob Ogunkunle

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The study examined the moderating effects of future career interest in science and gender on achievement in basic science of students taught in a simulated laboratory and enriched laboratory guide material environments. It adopted the pretest-posttest control group quasi experimental design with a 3x2x2 factorial matrix. A total of 277 (130 males, 147 females; ± 17 years) junior secondary three students randomly selected from six purposively selected secondary schools based on availability of functional computer and physics laboratories participated in the study. Data were collected using achievement test in basic science (r=0.87) and future career interest in science (r=0.99) while analysis of covariance and estimated marginal means were used to test three hypotheses at 0.05 level of significance. The findings of the study show that future career interest in science had significant effect on students’ achievement in basic science whereas gender did not. The interaction effect of future career interest in science and gender on students’ achievement in basic science was not significant. It is therefore recommended that prior knowledge of students’ future career interest in science could be used to improve participation in basic science practical in order to enhance achievement in biology, chemistry, and physics at the post-basic education level in Nigeria.

Keywords: future career interest in science, basic science, simulated laboratory, enriched laboratory guide materials, achievement in science

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Authors: Emily Rowe

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Introduction: Balance assessments can be used to help evaluate a person’s risk of falls, determine causes of balance deficits and inform intervention decisions. It is widely accepted that instrumented quantitative analysis can be more reliable and specific than semi-qualitative ordinal scales or itemised scoring methods. However, the uptake of quantitative methods is hindered by expense, lack of portability, and set-up requirements. During stepping, foot placement is actively coordinated with the body centre of mass (COM) kinematics during pre-initiation. Based on this, the potential to use COM velocity just prior to foot off and foot placement error as an outcome measure of dynamic balance is currently being explored using complex 3D motion capture. Inertial sensors and pressure mats might be more practical technologies for measuring these parameters in clinical settings. Objective: The aim of this study was to test the criterion validity and test-retest reliability of a synchronised inertial sensor and pressure mat-based approach to measure foot placement error and COM velocity while stepping. Methods: Trials were held with 15 healthy participants who each attended for two sessions. The trial task was to step onto one of 4 targets (2 for each foot) multiple times in a random, unpredictable order. The stepping target was cued using an auditory prompt and electroluminescent panel illumination. Data was collected using 3D motion capture and a combined inertial sensor-pressure mat system simultaneously in both sessions. To assess the reliability of each system, ICC estimates and their 95% confident intervals were calculated based on a mean-rating (k = 2), absolute-agreement, 2-way mixed-effects model. To test the criterion validity of the combined inertial sensor-pressure mat system against the motion capture system multi-factorial two-way repeated measures ANOVAs were carried out. Results: It was found that foot placement error was not reliably measured between sessions by either system (ICC 95% CIs; motion capture: 0 to >0.87 and pressure mat: <0.53 to >0.90). This could be due to genuine within-subject variability given the nature of the stepping task and brings into question the suitability of average foot placement error as an outcome measure. Additionally, results suggest the pressure mat is not a valid measure of this parameter since it was statistically significantly different from and much less precise than the motion capture system (p=0.003). The inertial sensor was found to be a moderately reliable (ICC 95% CIs >0.46 to >0.95) but not valid measure for anteroposterior and mediolateral COM velocities (AP velocity: p=0.000, ML velocity target 1 to 4: p=0.734, 0.001, 0.000 & 0.376). However, it is thought that with further development, the COM velocity measure validity could be improved. Possible options which could be investigated include whether there is an effect of inertial sensor placement with respect to pelvic marker placement or implementing more complex methods of data processing to manage inherent accelerometer and gyroscope limitations. Conclusion: The pressure mat is not a suitable alternative for measuring foot placement errors. The inertial sensors have the potential for measuring COM velocity; however, further development work is needed.

Keywords: dynamic balance, inertial sensors, portable, pressure mat, reliability, stepping, validity, wearables

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Authors: Yi Shan Cheng, Ya Hui Yeh, Hsiao Wen Hsu

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Delirium is an acute state of confusion, which is mainly the result of the interaction of many factors, including: age>65 years, comorbidity, cognitive function and visual/auditory impairment, dehydration, pain, sleep disorder, pipeline retention, general anesthesia and major surgery… etc. Researches show the prevalence of delirium in hospitalized elderly patients over 50%. If it doesn't improve in time, may cause cognitive decline or impairment, not only prolong the length of hospital stay but also increase mortality. Some studies have shown that multiple nonpharmacological interventions are the most effective and common strategies, which are reorientation, early mobility, promoting sleep and nutritional support (including water intake), could improve or prevent delirium in the hospitalized elderly. In Taiwan, only one research to compare the delirium incidence of the older patients who have received orthopedic surgery between multi-nonpharmacological interventions and general routine care. Therefore, the purpose of this study is to address the prevention or improvement of delirium incidence density in medical hospitalized elderly, provide clinical nurses as a reference for clinical implementation, and develop follow-up related research. This study is a quasi-experimental design using purposive sampling. Samples are from two wards: the geriatric ward and the general medicine ward at a medical center in central Taiwan. The sample size estimated at least 100, and then the data will be collected through a self-administered structured questionnaire, including: demographic and professional evaluation items. Case recruiting from 5/13/2023. The research results will be analyzed by SPSS for Windows 22.0 software, including descriptive statistics and inferential statistics: logistic regression、Generalized Estimating Equation(GEE)、multivariate analysis of variance(MANOVA).

Keywords: multiple nonpharmacological interventions, hospitalized elderly, delirium incidence, delirium

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Authors: Amy M. Kwon

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Support vector machine (SVM) is a well-known algorithm in machine learning due to its superior performance, and it also functions well in multiple-instance (MI) problems. Our study proposes a schematic algorithm to select instances based on Hausdorff distance, which can be adapted to SVMs as input vectors under the MI setting. Based on experiments on five benchmark datasets, our strategy for adapting representation outperformed in comparison with original approach. In addition, task execution times (TETs) were reduced by more than 80% based on MissSVM. Hence, it is noteworthy to consider this representation adaptation to SVMs under MI-setting.

Keywords: support vector machine, Margin, Hausdorff distance, representation selection, multiple-instance learning, machine learning

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

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We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: Mahua Banerjee, Debtanu Maiti

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Zero-tillage cultivation is a farming practice that reduces costs while maintaining harvests and protecting the environment. Innovative partnerships among researchers, farmers, and other actors in the agricultural value chain have enabled the adoption of zero-tillage to sow rice in the Indo-Gangetic Plains, increasing farmers' incomes, fostering more sustainable use of soil and water, and providing a platform for cropping diversification and the introduction of other resource-conserving practices. A field experiment was conducted in the farmer’s field of Ausgram I Block, Burdwan, West Bengal, India under sandy loam soil with soil pH of 5.2, which is low in Nitrogen, medium in Phosphorus and Potassium. There were three techniques of tillage-T1: Zero tillage in Rice, T2: conventional tillage in Rice, T3: Rice grown with Drum seeder and three varieties namely V1: MTU 7029 V2-MTU 1010, V3: Pratikha thus making nine treatment combinations which were replicated thrice and the experiment was laid out in Factorial Randomised Block Design. Among the three varieties, rice variety MTU 7029 gave higher yield in all the tillage techniques. The highest yield was obtained under Zero tillage followed by conventional tillage. From economic analysis it was revealed that the benefit:cost ratio was higher in Zero tillage and rice cultivation by drum seeder. Zero-till is increasingly being adopted because it gives more yield at less cost, saves labour and farmer time. Farmers will be interested in this technology once they overcome their tillage biases.

Keywords: economics, Indo-Gangetic plain, rice, zero tillage, yield

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Authors: Veronika Lesáková, Silvia Slezáková, František Štěpánek

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Additive manufacturing technologies producing drug dosage forms aimed at personalized medicine applications are promising strategies with several advantages over the conventional production methods. One of the emerging technologies is 3D printing which reduces manufacturing steps and thus allows a significant drop in expenses. A decrease in material consumption is also a highly impactful benefit as the tested drugs are frequently expensive substances. In addition, 3D printed dosage forms enable increased patient compliance and prevent misdosing as the dosage forms are carefully designed according to the patient’s needs. The incorporation of multiple drugs into a single dosage form further increases the degree of personalization. Our research focuses on the development of 3D printed tablets incorporating multiple drugs (candesartan, losartan) and thermoplastic polymers (e.g., KlucelTM HPC EF). The filaments, an essential feed material for 3D printing,wereproduced via hot-melt extrusion. Subsequently, the extruded filaments of various formulations were 3D printed into tablets using an FDM 3D printer. Then, we have assessed the influence of the internal structure of 3D printed tablets and formulation on dissolution behaviour by obtaining the dissolution profiles of drugs present in the 3D printed tablets. In conclusion, we have developed tablets containing multiple drugs providing modified release profiles. The 3D printing experiments demonstrate the high tunability of 3D printing as each tablet compartment is constructed with a different formulation. Overall, the results suggest that the 3D printing technology is a promising manufacturing approach to dual tablet preparation for personalized medicine.

Keywords: 3D printing, drug delivery, hot-melt extrusion, dissolution kinetics

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Authors: Veronica Diaz Quezada

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In this article, the performance and errors are featured and analysed in the limit problems solving of a real-valued function, in correspondence to competency-based education in engineering careers, in the south of Chile. The methodological component is contextualised in a qualitative research, with a descriptive and explorative design, with elaboration, content validation and application of quantitative instruments, consisting of two parallel forms of open answer tests, based on limit application problems. The mathematical competences and errors made by students from five engineering careers from a public University are identified and characterized. Results show better performance only to solve routine-context problem-solving competence, thus they are oriented towards a rational solution or they use a suitable problem-solving method, achieving the correct solution. Regarding errors, most of them are related to techniques and the incorrect use of theorems and definitions of real-valued function limits of real variable.

Keywords: engineering education, errors, limits, mathematics competences, problem solving

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Authors: Kunal Garg, Louise Theusen Hermansan, Kanoktip Puttaraska, Oliver Hendricks, Heidi Pirttinen, Leona Gilbert

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The Germ Theory (one infectious determinant is equal to one disease) has unarguably evolved our capability to diagnose and treat infectious diseases over the years. Nevertheless, the advent of technology, climate change, and volatile human behavior has brought about drastic changes in our environment, leading us to question the relevance of the Germ Theory in our day, i.e. will vector-borne disease (VBD) sufferers produce multiple immune responses when tested for multiple microbes? Vector diseased patients producing multiple immune responses to different microbes would evidently suggest human polymicrobial infections (HPI). Ongoing diagnostic tools are exceedingly unequipped with the current research findings that would aid in diagnosing patients for polymicrobial infections. This shortcoming has caused misdiagnosis at very high rates, consequently diminishing the patient’s quality of life due to inadequate treatment. Equipped with the state-of-art scientific knowledge, PolyScan intends to address the pitfalls in current VBD diagnostics. PolyScan is a multiplex and multifunctional enzyme linked Immunosorbent assay (ELISA) platform that can test for numerous VBD microbes and allow simultaneous screening for multiple types of antibodies. To validate PolyScan, Lyme Borreliosis (LB) and spondyloarthritis (SpA) patient groups (n = 54 each) were tested for Borrelia burgdorferi, Borrelia burgdorferi Round Body (RB), Borrelia afzelii, Borrelia garinii, and Ehrlichia chaffeensis against IgM and IgG antibodies. LB serum samples were obtained from Germany and SpA serum samples were obtained from Denmark under relevant ethical approvals. The SpA group represented chronic LB stage because reactive arthritis (SpA subtype) in the form of Lyme arthritis links to LB. It was hypothesized that patients from both the groups will produce multiple immune responses that as a consequence would evidently suggest HPI. It was also hypothesized that the multiple immune response proportion in SpA patient group would be significantly larger when compared to the LB patient group across both antibodies. It was observed that 26% LB patients and 57% SpA patients produced multiple immune responses in contrast to 33% LB patients and 30% SpA patients that produced solitary immune responses when tested against IgM. Similarly, 52% LB patients and an astounding 73% SpA patients produced multiple immune responses in contrast to 30% LB patients and 8% SpA patients that produced solitary immune responses when tested against IgG. Interestingly, IgM immune dysfunction in both the patient groups was also recorded. Atypically, 6% of the unresponsive 18% LB with IgG antibody was recorded producing multiple immune responses with the IgM antibody. Similarly, 12% of the unresponsive 19% SpA with IgG antibody was recorded producing multiple immune responses with the IgM antibody. Thus, results not only supported hypothesis but also suggested that IgM may atypically prevail longer than IgG. The PolyScan concept will aid clinicians to detect patients for early, persistent, late, polymicrobial, & immune dysfunction conditions linked to different VBD. PolyScan provides a paradigm shift for the VBD diagnostic industry to follow that will drastically shorten patient’s time to receive adequate treatment.

Keywords: diagnostics, immune dysfunction, polymicrobial, TICK-TAG

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Authors: Yasin Tadayonrad

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

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Authors: T. T. Tham

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The aim of this study is to propose an integrated approach to determine the most suitable programs, based on Quality Function Deployment (QFD), Sensitivity Analysis (SA) and Multi-Objective Linear Programming model (MOLP). Firstly, QFD is used to determine business requirements and transform them into business and supply chain programs. From the QFD, technical scores of all programs are obtained. All programs are then evaluated through five criteria (productivity, quality, cost, technical score, and feasibility). Sets of weight of these criteria are built using Sensitivity Analysis. Multi-Objective Linear Programming model is applied to select suitable programs according to multiple conflicting objectives under a budget constraint. A case study from the Sai Gon-Mien Tay Beer Company is given to illustrate the proposed methodology. The outcome of the study provides a comprehensive picture for companies to select suitable programs to obtain the optimal solution according to their preference.

Keywords: business program, multi-objective linear programming model, quality function deployment, sensitivity analysis, supply chain management

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Authors: Ntandazo Dlatu, Benjamin Longo-Mbenza, Andre Renzaho, Ruffin Appalata, Yolande Yvonne Valeria Matoumona Mavoungou, Mbenza Ben Longo, Kenneth Ekoru, Blaise Makoso, Gedeon Longo Longo

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Background: The gap between complexities related to the integration of Tuberculosis /HIV control and evidence-based knowledge motivated the initiation of the study. Therefore, the objective of this study was to explore correlations between national TB management guidelines, multiple deprivation indexes, quantiles, components and levels of Tuberculosis control programme using mathematical modeling in rural O.R. Tambo District Health Facilities, South Africa. Methods: The study design used mixed secondary data analysis and cross-sectional analysis between 2009 and 2013 across O.R Tambo District, Eastern Cape, South Africa using univariate/ bivariate analysis, linear multiple regression models, and multivariate discriminant analysis. Health inequalities indicators and component of an impediment to the tuberculosis control programme were evaluated. Results: In total, 62 400 records for TB notification were analyzed for the period 2009-2013. There was a significant but negative between Financial Year Expenditure (r= -0.894; P= 0.041) Seropositive HIV status(r= -0.979; P= 0.004), Population Density (r = -0.881; P= 0.048) and the number of TB defaulter in all TB cases. It was shown unsuccessful control of TB management program through correlations between numbers of new PTB smear positive, TB defaulter new smear-positive, TB failure all TB, Pulmonary Tuberculosis case finding index and deprivation-concentration-dispersion index. It was shown successful TB program control through significant and negative associations between declining numbers of death in co-infection of HIV and TB, TB deaths all TB and SMIAD gradient/ deprivation-concentration-dispersion index. The multivariate linear model was summarized by unadjusted r of 96%, adjusted R2 of 95 %, Standard Error of estimate of 0.110, R2 changed of 0.959 and significance for variance change for P=0.004 to explain the prediction of TB defaulter in all TB with equation y= 8.558-0.979 x number of HIV seropositive. After adjusting for confounding factors (PTB case finding the index, TB defaulter new smear-positive, TB death in all TB, TB defaulter all TB, and TB failure in all TB). The HIV and TB death, as well as new PTB smear positive, were identified as the most important, significant, and independent indicator to discriminate most deprived deprivation index far from other deprivation quintiles 2-5 using discriminant analysis. Conclusion: Elimination of poverty such as overcrowding, lack of sanitation and environment of highest burden of HIV might end the TB threat in O.R Tambo District, Eastern Cape, South Africa. Furthermore, ongoing adequate budget comprehensive, holistic and collaborative initiative towards Sustainable Developmental Goals (SDGs) is necessary for complete elimination of TB in poor O.R Tambo District.

Keywords: tuberculosis, HIV/AIDS, success, failure, control program, health inequalities, South Africa

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Authors: Fang Liu, JiaJia Yao, GuanLin Wu, ZuMaoLi, XueYan Yang, HePeng Zhang, ZhiPeng Sun, JunShuai Xue

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The explosive increasing needs of data processing and information storage strongly drive the advancement of the binary logic system to multiple-valued logic system. Inherent negative differential resistance characteristic, ultra-high-speed switching time, and robust anti-irradiation capability make III-nitride resonant tunneling diode one of the most promising candidates for multi-valued logic devices. Here we report the monolithic integration of GaN resonant tunneling diodes in series to realize multiple negative differential resistance regions, obtaining at least three stable operating states. A multiply-by-three circuit is achieved by this combination, increasing the frequency of the input triangular wave from f0 to 3f0. The resonant tunneling diodes are grown by plasma-assistedmolecular beam epitaxy on free-standing c-plane GaN substrates, comprising double barriers and a single quantum well both at the atomic level. Device with a peak current density of 183kA/cm² in conjunction with a peak-to-valley current ratio (PVCR) of 2.07 is observed, which is the best result reported in nitride-based resonant tunneling diodes. Microwave oscillation event at room temperature was discovered with a fundamental frequency of 0.31GHz and an output power of 5.37μW, verifying the high repeatability and robustness of our device. The switching behavior measurement was successfully carried out, featuring rise and fall times in the order of picoseconds, which can be used in high-speed digital circuits. Limited by the measuring equipment and the layer structure, the switching time can be further improved. In general, this article presents a novel nitride device with multiple negative differential regions driven by the resonant tunneling mechanism, which can be used in high-speed multiple value logic field with reduced circuit complexity, demonstrating a new solution of nitride devices to break through the limitations of binary logic.

Keywords: GaN resonant tunneling diode, negative differential resistance, multiple-valued logic system, switching time, peak-to-valley current ratio

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Authors: Andreas D. Jansson

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The availability of inexpensive, yet competent hardware allows for increased level of automation and self-optimization in the context of Industry 4.0. However, such agents require high quality information about their surroundings along with a robust strategy for collision avoidance, as they may cause expensive damage to equipment or other agents otherwise. Manually defining a strategy to cover all possibilities is both time-consuming and counter-productive given the capabilities of modern hardware. This paper explores the idea of a model-free self-optimizing obstacle avoidance strategy for multiple autonomous agents in a simulated dynamic environment using the Q-learning algorithm.

Keywords: autonomous vehicles, industry 4.0, multi-agent system, obstacle avoidance, Q-learning, simulation

Procedia PDF Downloads 138