Search results for: robust regression

Authors: Jorge Urrutia-Mosquera, Luz Flórez-Calderón, Yasna Cortés

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We assessed the state of progress in terms of urban sustainability indicators and studied the impact of current land use conditions and the level of spatial accessibility to basic urban amenities on travel patterns and sustainable mobility in Santiago de Chile. We determined the spatial impact of urban facilities on sustainable travel patterns through the statistical analysis, data visualisation, and weighted regression models. The results show a need to diversify land use in more than 60% of the communes, although in 85% of the communes, accessibility to public spaces is guaranteed. The findings also suggest improving access to early education facilities, as only 26% of the communes meet the sustainability standard, negatively impacting travel in sustainable modes. It is also observed that the level of access to urban facilities generates spatial heterogeneity in the city, which negatively affects travel patterns in terms of time over 60 minutes and modes of travel in private vehicles. The results obtained allow us to identify opportunities for public policy intervention to promote and adopt sustainable mobility.

Keywords: land use, urban sustainability, travel patterns, spatial heterogeneity, GWR model, sustainable mobility

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Authors: Harman Dwi R., Alwin Mugiyantoro, Heppy Chintya P.

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The location of this research is a part of Geoheritage that located in Nglipar, Gunung Kidul Regency, Yogyakarta Special Region. Whereas in this location, the carbonate sandstone of Sambipitu Formation (early-middle Miocene) is well exposed along Ngalang River, also there are ichnofossil presence which causes this formation to be interesting. The determination of paleobathymetry is particularly important in determining paleoenvironment and paleogeographic. Paleobathymetry can be determined by identifying the presence of Foraminifera bentonik fossil and parasequence emerge. The methods that used in this study are spatial method of field observation with systematic sampling, descriptive method of paleontology, biostratigraphy analysis, geometrical analysis of Ichnofossil, and study literature. The result obtained that paleobathymetry of this location is bathyal zone with maximum regression known by Bulliminoides williamsonianus showing depth 17 fathoms at the age of N3-N5 (Oligocenne-Early Miocene) and the maximum transgression is known by Cibicides pseudoungarianus showing depth 862 fathoms at the age of N8-N9 (Early-Middle Miocene). Where the obtained paleobathymetry supported of the presence and formed the pattern of ichnofossil that found in the study area.

Keywords: paleobathymetry, biostratigraphy, ichnofossil, Ngalang river

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Authors: Niranjani Ruba Pandian

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In today’s multicultural global business community, most of the businesses and industries are linked with various countries in which different nationalities have different roles and responsibilities throughout the project. The purpose of this research is to examine the cross-cultural challenges between Indian and French and the ways to minimize these challenges to manage effectively the cross-cultural aspect of human resources for the success of global business in an automotive industry. The conducted study utilized quantitative methodology to analyze the data on Indian and French employees' perceptions of 6 cultural dimensions such as power versus distance, individualism versus collectivism, masculinity versus femininity, uncertainty versus avoidance, pragmatic versus normative and indulgence versus restraint. Employees of 4 multinational companies filled in the questionnaire based on the 5-point Likert scale to present quantitative results. The data was analysed with the correlation and multiple regression statistical analyses. It was found that Indian and French have major gap in uncertainty versus avoidance followed by individualism versus collectivism. However, this article highlights the way to minimize these gaps by adopting certain sequenced methodologies.

Keywords: automotive industry, cross cultural challenges, globalization, global business

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Authors: H. Taylan Selamlar, I. Yavuz, G. Yapar

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It is difficult to make predictions especially about the future and making accurate predictions is not always easy. However, better predictions remain the foundation of all science therefore the development of accurate, robust and reliable forecasting methods is very important. Numerous number of forecasting methods have been proposed and studied in the literature. There are still two dominant major forecasting methods: Box-Jenkins ARIMA and Exponential Smoothing (ES), and still new methods are derived or inspired from them. After more than 50 years of widespread use, exponential smoothing is still one of the most practically relevant forecasting methods available due to their simplicity, robustness and accuracy as automatic forecasting procedures especially in the famous M-Competitions. Despite its success and widespread use in many areas, ES models have some shortcomings that negatively affect the accuracy of forecasts. Therefore, a new forecasting method in this study will be proposed to cope with these shortcomings and it will be called ATA method. This new method is obtained from traditional ES models by modifying the smoothing parameters therefore both methods have similar structural forms and ATA can be easily adapted to all of the individual ES models however ATA has many advantages due to its innovative new weighting scheme. In this paper, the focus is on modeling the trend component and handling seasonality patterns by utilizing classical decomposition. Therefore, ATA method is expanded to higher order ES methods for additive, multiplicative, additive damped and multiplicative damped trend components. The proposed models are called ATA trended models and their predictive performances are compared to their counter ES models on the M3 competition data set since it is still the most recent and comprehensive time-series data collection available. It is shown that the models outperform their counters on almost all settings and when a model selection is carried out amongst these trended models ATA outperforms all of the competitors in the M3- competition for both short term and long term forecasting horizons when the models’ forecasting accuracies are compared based on popular error metrics.

Keywords: accuracy, exponential smoothing, forecasting, initial value

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Authors: Wannakorn Sangthongngam, Melissa Huerta, Jaewoo Kim, Doyeon Kim

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Continuous glucose monitoring systems are essential for diabetics to avoid health complications but come at a costly price, especially when insurance does not fully cover the diabetic testing kits needed. This paper proposes a noninvasive continuous glucose monitoring system to provide an accessible, low-cost, and painless alternative method of accurate glucose measurements to help improve quality of life. Using a light source with a wavelength of 850nm illuminates the fingertip for the photodetector to detect the transmitted light. Utilizing SeeDevice’s photon-assisted tunneling photodetector (PAT-PD)-based QMOS™ sensor, fluctuations of voltage based on photon absorption in blood cells are comparable to traditional glucose measurements. The performance of the proposed method was validated using 4 test participants’ transmitted voltage readings compared with measurements obtained from the Accu-Chek glucometer. The proposed method was able to successfully measure concentrations from linear regression calculations.

Keywords: continuous glucose monitoring, non-invasive continuous glucose monitoring, NIR, photon-assisted tunneling photodetector, QMOS™, wearable device

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Authors: D. Kuvshinov, A. Siswanto, J. Lozano-Parada, W. Zimmerman

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Ozone is well known as a powerful fast reaction rate oxidant. The ozone based processes produce no by-product left as a non-reacted ozone returns back to the original oxygen molecule. Therefore an application of ozone is widely accepted as one of the main directions for a sustainable and clean technologies development. There are number of technologies require ozone to be delivered to specific points of a production network or reactors construction. Due to space constrains, high reactivity and short life time of ozone the use of ozone generators even of a bench top scale is practically limited. This requires development of mini/micro scale ozone generator which can be directly incorporated into production units. Our report presents a feasibility study of a new micro scale rector for ozone generation (MROG). Data on MROG calibration and indigo decomposition at different operation conditions are presented. At selected operation conditions with residence time of 0.25 s the process of ozone generation is not limited by reaction rate and the amount of ozone produced is a function of power applied. It was shown that the MROG is capable to produce ozone at voltage level starting from 3.5kV with ozone concentration of 5.28E-6 (mol/L) at 5kV. This is in line with data presented on numerical investigation for a MROG. It was shown that in compare to a conventional ozone generator, MROG has lower power consumption at low voltages and atmospheric pressure. The MROG construction makes it applicable for emerged and dry systems. With a robust compact design MROG can be used as incorporated unit for production lines of high complexity.

Keywords: dielectric barrier discharge (DBD), micro reactor, ozone, plasma

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Authors: Suhaila Isaak, Yusmeeraz Yusof, Khairunnisa Mohd Yusof, Ahmad Safuan Abdul Rashid

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Soil fertility is commonly evaluated by soil macronutrients such as nitrate, potassium, and phosphorus contents. Optical spectroscopy is an emerging technology which is rapid and simple has been widely used in agriculture to measure soil fertility. For visible and near infrared absorption spectroscopy, the absorbed light level in is useful for soil macro-nutrient measurement. This is because the absorption of light in a soil sample influences sensitivity of the measurement. This paper reports the performance of visible and near infrared absorption spectroscopy in the 400–1400 nm wavelength range using light-emitting diode as the excitation light source to predict the soil macronutrient content of nitrate, potassium, and phosphorus. The experimental results show an improved linear regression analysis of various soil specimens based on the Beer–Lambert law to determine sensitivity of soil spectroscopy by evaluating the absorption of characteristic peaks emitted from a light-emitting diode and detected by high sensitivity optical spectrometer. This would denote in developing a simple and low-cost soil spectroscopy with light-emitting diode for future implementation.

Keywords: macronutrients absorption, optical spectroscopy, soil, absorption

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Authors: Ayoub Kafyulilo, Petra Fisser, Joke Voogt

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This study was conducted to assess the continuation of the use of technology in science and mathematics teaching of the pre-service and in-service teachers who attended the professional development programme. It also assessed professional development, personal, institutional, and technological factors contributing to the continuous use of technology in teaching. The study involved 42 teachers, thirteen pre-service teachers, and twenty-nine in-service teachers. A mixed-method research approach was used to collect data for this study. Findings showed that the continuous use of technology in teaching after the termination of the professional development arrangement was high among the pre-service teachers, and differed for the in-service teachers. The regression model showed that knowledge and skills, access to technology and ease of use were strong predictors (R2 = 55.3%) of the teachers’ continuous use of technology after the professional development arrangement. The professional development factor did not have a direct effect on the continuous use of technology, rather had an influence on personal factors (knowledge and skills). In turn, the personal factors had influence on the institutional factors (access to technology) and technological factors (ease of use), which together had an effect on the teachers’ continuous use of technology in teaching.

Keywords: technology, professional development, teachers, science and mathematics

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Authors: Joseph Uche Azubike, Evelyn Ngozi Agbasi, M. I. Ogbonna

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The audit committee of the board of directors could no longer handle the enterprise's risks. Therefore, a risk management committee was created to control them. Thus, this study examined how enterprise risk management committee characteristics affected Nigerian exchange-listed banks' financial performance from 2013 to 2022. The study's hypotheses and three objectives were to determine how enterprise risk management committee size, composition, and gender diversity affect Nigerian banks' performance. An ex-post facto study design collected secondary data from bank annual reports. We used descriptive statistics, correlation analysis, and Ordinary least square regression to analyze panel data. Enterprise risk management committee size and composition had both negative and no significant effect on bank financial performance in Nigeria, whereas enterprise risk committee gender diversity has a 10% favorable effect. The report advises that adding more women with relevant knowledge to the risk committee to boost performance and allowing women to be at the lead of such risk management could improve bank performance in Nigeria since they are noted to be thorough in their tasks.

Keywords: bank, committee, enterprise, management, performance, risk

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Authors: I. D. Mngutyo, T. T. Gyuse, D. S. A. Alaci, J. Atser

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Streets are public spaces that are meaningful to all people because of lack of restriction on streets. Studies show that conditions, activities and people contribute to the success of public spaces. Also, self-organization potential in activity patterns offers a prospect for the revitalization of an urban area. This potential is mostly ignored hence many African streets appear disorganized giving African urban areas an unplanned look. Therefore, this study aims to analyze street utilization patterns and explore the relationship between the pattern of street use and condition of streets in Makurdi.These activity patterns form a data base for the revitalization of public space. Three major and minor arterials streets in nine out of the eleven wards that make up the built up part of Makurdi were purposively selected as units for measurement. A street activity audit was done on streets for activities that can be observed. For activities that cannot be easily observed 4 questionnaires were randomly administered on each of the three streets giving a total of 108 questionnaires. Multivariate statistical tools such as factor analysis and regression will be used to show emerging streets activity patterns and spatial variation among the nine wards.

Keywords: streets, utilization patterns, revitalization, urban design, urban, areas, developing countries

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Authors: Vishnu V. Pillai, Sunil P. Lonkar, Akhil M. Abraham, Saeed M. Alhassan

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An effectual technology for wastewater treatment is a great demand now in order to encounter the water pollution caused by organic pollutants. Photocatalytic oxidation technology is widely used in removal of such unsafe contaminants. Among the semi-conducting metal oxides, robust and thermally stable TiO2 has emerged as a fascinating material for photocatalysis. Enhanced catalytic activity was observed for nanostructured TiO2 due to its higher surface, chemical stability and higher oxidation ability. However, higher charge carrier recombination and wide band gap of TiO2 limits its use as a photocatalyst in the UV region. It is desirable to develop a photocatalyst that can efficiently absorb the visible light, which occupies the main part of the solar spectrum. Hence, in order to extend its photocatalytic efficiency under visible light, TiO2 nanoparticles are often doped with metallic or non-metallic elements. Non-metallic doping of TiO2 has attracted much attention due to the low thermal stability and enhanced recombination of charge carriers endowed by metallic doping of TiO2. Amongst, sulfur doped TiO2 is most widely used photocatalyst in environmental purification. However, the most of S-TiO2 synthesis technique uses toxic chemicals and complex procedures. Hence, a facile, scalable and environmentally benign preparation process for S-TiO2 is highly desirable. In present work, we have demonstrated new and facile solid-state reaction method for S-TiO2 synthesis that uses abundant elemental sulfur as S source and moderate temperatures. The resulting nano-sized S-TiO2 has been successfully employed as visible light photocatalyst in methylene blue dye removal from aqueous media.

Keywords: ecofriendly, nanomaterials, methylene blue, photocatalysts

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Authors: Sepase K. Ivande

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Morality and frugality are two of the strongest motivations for pro-environmental behavior. However, formulating interventions based on these motivations requires knowledge of who is likely to be motivated by morality and who by frugality. This study investigated which personality traits make someone predisposed to morality motivation and which to frugality motivation for pro-environmental behavior. Results from a series of multiple regression analyses indicated that openness and agreeableness had a positive association with morality motivation, while conscientiousness had a positive association with frugality motivation. The link of agreeableness to morality motivation was stronger when the individuals were also higher on openness. Furthermore, a pair of Wilcoxon signed-rank tests revealed that individuals high on openness and agreeableness but low on conscientiousness scored higher on morality than frugality motivation. On the other hand, individuals low on openness and agreeableness but high on conscientiousness scored higher on frugality than morality motivation. The results of this study could inform the formulation of personalized interventions based on people’s personal predisposition to morality and frugality motivation for pro-environmental behavior, which could be more effective in getting them to be pro-environmental.

Keywords: agreeableness, conscientiousness, frugality, higher order motivations, morality, openness to experience, personality traits, pro-environmental behavior

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Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam

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Threatened tree species (TTS) play a significant role in ecosystem functioning and services, land use dynamics, and other socio-economic aspects. Such aspects include ecological, economic, livelihood, security-based, and well-being benefits. The development of techniques for mapping and monitoring TTS is thus critical for understanding the functioning of ecosystems. The advent of advanced imaging systems and supervised learning algorithms has provided an opportunity to classify TTS over fragmenting landscape. Recently, vegetation maps have been produced using advanced imaging systems such as WorldView-2 (WV-2) and robust classification algorithms such as support vectors machines (SVM) and artificial neural network (ANN). However, delineation of TTS in a fragmenting landscape using high resolution imagery has widely remained elusive due to the complexity of the species structure and their distribution. Therefore, the objective of the current study was to examine the utility of the advanced WV-2 data for mapping TTS in the fragmenting Dukuduku indigenous forest of South Africa using SVM and ANN classification algorithms. The results showed the robustness of the two machine learning algorithms with an overall accuracy (OA) of 77.00% (total disagreement = 23.00%) for SVM and 75.00% (total disagreement = 25.00%) for ANN using all eight bands of WV-2 (8B). This study concludes that SVM and ANN classification algorithms with WV-2 8B have the potential to classify TTS in the Dukuduku indigenous forest. This study offers relatively accurate information that is important for forest managers to make informed decisions regarding management and conservation protocols of TTS.

Keywords: artificial neural network, threatened tree species, indigenous forest, support vector machines

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Authors: D. Motlhanka, M. Mine, T. Bagaketse, T. Ngakane

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There is a plethora of evidence from numerous sources that highlights the triumph of naturally derived medicinal plant metabolites with antioxidant capability for repurposed therapeutics. As post-COVID-19 syndromes and non-communicable diseases are on the rise, there is an urgent need to come up with new therapeutic strategies to address the problem. Non-communicable diseases and Post COVID-19 syndromes are classified as socio-economic diseases and are ranked high among threats to health security due to the economic burden they pose to any government budget commitment. Research has shown a strong link between accumulation of free radicals and oxidative stress critical for pathogenesis of non-communicable diseases and COVID-19 syndromes. Botswana has embarked on a robust programme derived from ethno-pharmacognosy and drug repurposing to address these threats to health security. In the current approach, a number of medicinally active plant-derived polyphenolics are repurposed and combined into new medicinal tools to target diabetes, Hypertension, Prostate Cancer and oxidative stress induced Post COVID 19 syndromes such as “brain fog”. All four formulants demonstrated Free Radical scavenging capacities above 95% at 200µg/ml using the diphenylpicryalhydrazyl free radical scavenging assay and the total phenolic contents between 6899-15000GAE(g/L) using the folin-ciocalteau assay respectively. These repurposed medicinal tools offer new hope and potential in the fight against emerging health threats driven by hyper-inflammation and free radical-induced oxidative stress.

Keywords: drug repurposed plant polyphenolics, free radical damage, non-communicable diseases, post COVID 19 syndromes

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Authors: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu

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Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.

Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq

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Authors: Jin-Ming Wu, Te-Wei Ho, Yu-Wen Tien

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Background: The aim of this population-based study was to determine the occurrence of diabetes and exocrine pancreatic insufficiencies (EPI) on non-diabetes subjects receiving distal pancreatectomy (DP). Method: A nationwide cohort study between 2000 and 2010 was collected from the Taiwan National Health Insurance Research Database. Among 3264 DP patients, we identified 1410 non-diabetes and 966 non-diabetes non-EPI. Results. Of 1410 non-diabetes DP subjects, 312 patients (22.1%) developed newly-diagnosed diabetes after PD. On a multiple logistic regression model, co-morbid hyperlipidemia (odds ratio, 1.640; 95% CI, 1.362–2.763; P < 0.001) and pancreatitis (odds ratio, 2.428; 95% CI, 1.889–3.121; P < 0.001) significantly contributed to higher incidences of diabetes after DP. Moreover, 380 subjects (39.3%) developed EPI, and pancreatic cancer is the statistically significant risk factor (odds ratio, 4.663; 95% CI, 2.108–6.085; P < 0.001). Conclusion: The patients with co-morbid hyperlipidemia and chronic pancreatitis had higher rates of newly-diagnosed diabetes after DP, moreover, pancreatic cancer subjects had higher rates of pancreatic exocrine insufficiency after DP. The clinicians should be alert to follow up glucose metabolism and clinical symptoms of fat intolerance for DP patients.

Keywords: distal pancreatectomy, National database, diabetes, exocrine insufficiency

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Authors: Jean-François Pouilly

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This study addresses the growing complexity of embedded systems and the critical need for secure, reliable software. Traditional cybersecurity testing methods, often conducted late in the development cycle, struggle to keep pace. This talk explores how formal methods, integrated with advanced analysis tools, empower C/C++ developers to 1) Proactively address vulnerabilities and bugs, which includes formal methods and abstract interpretation techniques to identify potential weaknesses early in the development process, reducing the reliance on penetration and fuzz testing in later stages. 2) Streamline development by focusing on bugs that matter, with close to no false positives and catching flaws earlier, the need for rework and retesting is minimized, leading to faster development cycles, improved efficiency and cost savings. 3) Enhance software dependability which includes combining static analysis using abstract interpretation with full context sensitivity, with hardware memory awareness allows for a more comprehensive understanding of potential vulnerabilities, leading to more dependable and secure software. This approach aligns with industry best practices (ISO2626 or ISO 21434) and empowers C/C++ developers to deliver robust, secure embedded systems that meet the demands of today's and tomorrow's applications. We will illustrate this approach with the TrustInSoft analyzer to show how it accelerates verification for complex cases, reduces user fatigue, and improves developer efficiency, cost-effectiveness, and software cybersecurity. In summary, integrating formal methods and sound Analyzers enhances software reliability and cybersecurity, streamlining development in an increasingly complex environment.

Keywords: safety, cybersecurity, ISO26262, ISO24434, formal methods

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Authors: Sabrina Boutaleb, Kouider Halim Benrahou, François Schosseler, Abdelouahed Tounsi, El Abbas Adda Bedia

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The use of polyurethane in different areas becomes more frequent. This is due to significant advantages they have including their lightness and resistance. However, their use requires a mastery of their mechanical performance. We will present in this work, a COAPUR 6050 which can be used to develop composite materials. COAPUR 6050 is an associative polyurethane thickener allowing fine rheological adjustment of flat or semi-gloss paints. COAPUR 6050 is characterised by its thickening efficiency at low shear rate. It is a solvent-free liquid product. It promotes good paint pick up, while maintaining a low yield point after shearing, and consequently a good levelling. We will then determine its rheological behaviour experimentally using different annular gaps. The rheological properties of COAPUR 6050 were researched by rotational rheometer (Rheometer-Mars III) using different annular gaps. There is the influence of the size of the annular gap on the behaviour as well as on the rheological parameters of the COAPUR 6050. The rheological properties data of COAPUR 6050 were regressed by nonlinear regression method and their rheological models were established, are characterized by yield pseudoplastic model. In this case, it is essential to make a viscometric correction. The latter was developed and presented in the experimental results.

Keywords: COAPUR 6050, flow’s couette, polyurethane, rheological behaviours

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Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan

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Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.

Keywords: stream speed, urban roads, machine learning, traffic flow

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Authors: Reshaa Alruwaili

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This study was inspired by previous studies with young children that found (a) that they need both inhibitory control and working memory when drawing an unfamiliar subject (e.g., animals) by adapting their schema of the human figure and (b) that when drawing something familiar (e.g., a person) they use inhibitory control mediated through fine motor control to execute their drawing. This study, therefore, systematically investigated whether direct effects for both working memory and inhibitory control and/or effects mediated through fine motor control existed when drawing both familiar and unfamiliar subjects. Participants were 95 children (41-66 months old) required to draw both a man and a dog, scored respectively for how representational they were and for differences from a human figure. Regression and mediation analyses showed that inhibitory control alone predicted drawing a recognizable man while working memory alone predicted drawing a dog that was not human-like when fine motor control, age, and gender were controlled. Contrasting with some previous studies, these results suggest that the roles of working memory and inhibitory control are sensitive to the familiarity of the drawing task and are not necessarily mediated through fine motor control. Implications for research on drawing development are discussed.

Keywords: child drawing, inhibitory control, working memory, fine motor control, mediation, familiar and unfamiliar subjects

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Authors: M. Johnson, R. Faggian, V. Sposito

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A participatory and engaged approach is key in connecting agricultural managers to sustainable agricultural systems to support and optimize production in Victoria’s food bowl. A sustainable intensification (SI) approach is well documented globally, but participation rates amongst Victorian farmers is fragmentary, and key outcomes and implementation strategies are poorly understood. Improvement in decision-support management tools and a greater understanding of the productivity gains available upon implementation of SI is necessary. This paper reviews the current understanding and uptake of SI practices amongst farmers in one of Victoria’s premier food producing regions, the Goulburn Broken; and it spatially analyses the potential for this region to adapt to climate change and optimize food production. A Geographical Information Systems (GIS) approach is taken to develop an interactive decision-support tool that can be accessible to on-ground agricultural managers. The tool encompasses multiple criteria analysis (MCA) that identifies factors during the construction phase of the tool, using expert witnesses and regional knowledge, framed within an Analytical Hierarchy Process. Given the complexities of the interrelations between each of the key outcomes, this participatory approach, in which local realities and factors inform the key outcomes and help to strategies for a particular region, results in a robust strategy for sustainably intensifying production in key food producing regions. The creation of an interactive, locally embedded, decision-support management and education tool can help to close the gap between farmer knowledge and production, increase on-farm adoption of sustainable farming strategies and techniques, and optimize farm productivity.

Keywords: agriculture, decision-support management tool, Geographic Information System, GIS, sustainable intensification

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Authors: Khurram Shahzad, Muhammad Usman

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The main aim of this study is to examine the direct and interactive effects of job insecurity and Islamic work ethics on employee’s attitude towards change and organizational citizenship behavior. Design/methodology/approach: The data was collected from 171 male and female university teachers of Pakistan. Self administered, close ended questionnaires were used to collect the data. Data was analyzed through correlation and regression analysis. Findings: Through the analysis of data, it was found that job insecurity has a strong negative effect on the attitude towards change of university teachers. On the contrary, job insecurity has no significant effect on organizational citizenship behavior of university teachers. Our results also show that Islamic work ethics does not moderate the relationship of job insecurity and attitude towards change, while a strong moderation effect of Islamic wok ethics is found on the relationship of job insecurity and organizational citizenship behavior. Originality/value: This study for the first time examines the relationship of job insecurity with employee’s attitude towards change and organizational citizenship behavior with the moderating effect of Islamic work ethics.

Keywords: job security, islamic work ethics, attitude towards change, organizational citizenship behavior

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

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

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

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Authors: Mohammed Nishat, Ahmad Ghazali

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This study empirically examines the corporate governance and firm performance, and tries to evaluate the governance, ownership and control related variables which are hypothesized to affect on firms performance. This study tries to evaluate the effectiveness of corporate governance mechanism to achieve high level performance among companies listed on the Karachi Stock Exchange (KSE) over the period from 2005 to 2008. To measure the firm performance level this research uses three measures of performance; Return on assets (ROA), Return on Equity (ROE) and Tobin’s Q. To link the performance of firms with the corporate governance three categories of corporate governance variables are tested which includes governance, ownership and control related variables. Fixed effect regression model is used to test the link between corporate governance and firm performance for 267 KSE listed Pakistani firms. The result shows that corporate governance variables such as percentage block holding by individuals have positive impact on firm performance. When CEO is also the chairperson of board then it is found that firm performance is adversely affected. Also negative relationship is found between share held by insiders and performance of firm. Leverage has negative impact on the performance of the firm and firm size is positively related with the firms performance.

Keywords: corporate governance, performance, agency cost, Karachi stock market

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Authors: Theresa Marie Miller, Ma. Nympha Joaquin

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The aim of this study was to check the predictive power of social-oriented and individual-oriented achievement motivation on student engagement and collaborative problem-solving skills in mathematics. A sample of 277 fourth year high school students from the Philippines were selected. Surveys and videos of collaborative problem solving activity were used to collect data from respondents. The mathematics teachers of the participants were interviewed to provide qualitative support on the data. Systemaitc correlation and regression analysis were employed. Results of the study showed that achievement motivations−SOAM and IOAM− linearly predicted student engagement but was not significantly associated to the collaborative problem-solving skills in mathematics. Student engagement correlated positively with collaborative problem-solving skills in mathematics. The results contribute to theorizing about the predictive power of achievement motivations, SOAM and IOAM on the realm of academic behaviors and outcomes as well as extend the understanding of collaborative problem-solving skills of 21st century learners.

Keywords: achievement motivation, collaborative problem-solving skills, individual-oriented achievement motivation, social-oriented achievement motivation, student engagement

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Authors: S. A. Khan, B. Mishra, O. Sherchan

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Background and Aims: Thyroid disorder is the most common endocrine disorder after diabetes mellitus. Females are more vulnerable to this disease, and old age is an important risk factor. This study was undertaken to investigate the burden of thyroid disorder in Nepalese postmenopausal women. Methods: In the present cross-sectional study, we included 271 post-menopausal women. Three ml of blood was collected following standard protocol after taking the written consent. Serum was separated and analyzed for free T3, free T4, and Thyroid Stimulating Hormone (TSH) by Chemiluminescence Immunoassay (CLIA) method in Snibe Maglumi 1000 analyzer. Data obtained was analyzed in SPSS Version 21. P < 0.05 was set for statistical significant at 95% Confidence Interval (CI). Results: Majority of the participants belong to Janjati (46.5%) ethnicity, followed by Brahmin/Chhetri (41.7%), residing either in urban or suburban locality. Most of them were non-vegetarian, non-smoker, and non-alcoholic. Subjects were divided into hyperthyroid (TSH < 0.3 uIU/ml), hypothyroid (TSH > 4.5 uIU/ml), and euthyroid (TSH=0.3-4.5 uIU/ml) based on TSH value. We reported 10.3% hyperthyroid and 29.2% hypothyroid cases. TSH was significantly correlated with T3 (r=-0.244; p < 0.001) T4 (r=-0.398; p < 0.001); age (r=-0.138; p=0.023) and BMI (r=0.123; p=0.043). Multiple linear regression model for TSH reveals only T3 and T4 were significantly associated with TSH (p < 0.001; p=0.001). Conclusion: To conclude, nearly 39.5% of the postmenopausal women had thyroid disorder. Postmenopausal women are vulnerable to thyroid disorder; therefore, requires regular thyroid monitoring.

Keywords: thyroid stimulating hormone, TSH, T3, T4, thyroid disorder

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Authors: Musaab Mohammed Ahmed Ali, Vladimir Vodichev

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work deals with an universal control technique or single controller for linear and nonlinear stabilization and tracing control systems. These systems may be structured as SISO and MIMO. Parameters of controlled plants can vary over a wide range. Introduced a novel control systems design method, construction of stable platform orbits using derivative balance, solved transfer function stability preservation problem of linear system under partial substitution of a rational function. Universal controller is proposed as a polar system with the multiple orbits to simplify design procedure, where each orbit represent single order of controller transfer function. Designed controller consist of proportional, integral, derivative terms and multiple feedback and feedforward loops. The controller parameters synthesis method is presented. In generally, controller parameters depend on new polynomial equation where all parameters have a relationship with each other and have fixed values without requirements of retuning. The simulation results show that the proposed universal controller can stabilize infinity number of linear and nonlinear plants and shaping desired previously ordered performance. It has been proven that sensor errors and poor performance will be completely compensated and cannot affect system performance. Disturbances and noises effect on the controller loop will be fully rejected. Technical and economic effect of using proposed controller has been investigated and compared to adaptive, predictive, and robust controllers. The economic analysis shows the advantage of single controller with fixed parameters to drive infinity numbers of plants compared to above mentioned control techniques.

Keywords: derivative balance, fixed parameters, stable platform, universal control

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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Authors: Mohammad K. Parvez, Mohammed S. Al-Dosari

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Hepatitis E virus (HEV) is an emerging RNA virus that causes acute and chronic liver disease with a global mortality rate of about 2%. Despite milestone developments in understanding of HEV biology, there is still lack of a robust culture system or animal model. Therefore, in a novel approach, two recombinant-baculoviruses (vBac-ORF2 and vBac-ORF3) that could overexpress HEV ORF2 (structural/capsid) and ORF3 (nonstructural/regulatory) proteins, respectively were constructed. The established HEV-SAR55 (genotype 1) replicon that contained GFP gene, in place of ORF2/ORF3 sequences was in vitro transcribed, and GFP production in RNA transfected S10-3 cells was scored by FACS. Enhanced infectivity, if any, of nascent virions produced by exogenously-supplied ORF2 and viral RNA by co-expression of ORF3 was tested on naïve HepG2 cells. Co-transduction with vBac-ORF2/vBac-ORF3 (108 pfu/microL) produced high amounts of native ORF2/ORF3 in approximately 60% of S10-3 cells, determined by immunofluorescence microscopy and Western analysis. FACS analysis showed about 9% GFP positivity of S10-3 cells on day6 post-transfection (i.e, day5 post-transduction). Further, FACS scoring indicated that lysates from S10-3 cultures receiving the RNA plus vBac-ORF2 were capable of producing HEV particles with about 4% infectivity in HepG2 cells. However, lysates of cultures co-transduced with vBac-ORF3, were found to further enhance virion infectivity by approximately 17%. This supported a previously proposed role of ORF3 as a minor-structural protein in HEV virion assembly and infectivity. In conclusion, the present model for efficient genomic RNA packaging and production of infectious virions could be a valuable tool to study various aspects of HEV molecular biology, in vitro.

Keywords: chronic liver disease, hepatitis E virus, ORF2, ORF3, replicon

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Authors: Muhammad Tariq, Hammad Tahir, Fawwad Mahmood Butt

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Purpose: This study attempts to examine the best forecasting methodologies in the time series. The time series forecasting models such as VAR, ARCH and the ARMA are considered for the analysis. Methodology: The Bench Marks or the parameters such as Adjusted R square, F-stats, Durban Watson, and Direction of the roots have been critically and empirically analyzed. The empirical analysis consists of time series data of Consumer Price Index and Closing Stock Price. Findings: The results show that the VAR model performed better in comparison to other models. Both the reliability and significance of VAR model is highly appreciable. In contrary to it, the ARCH model showed very poor results for forecasting. However, the results of ARMA model appeared double standards i.e. the AR roots showed that model is stationary and that of MA roots showed that the model is invertible. Therefore, the forecasting would remain doubtful if it made on the bases of ARMA model. It has been concluded that VAR model provides best forecasting results. Practical Implications: This paper provides empirical evidences for the application of time series forecasting model. This paper therefore provides the base for the application of best time series forecasting model.

Keywords: forecasting, time series, auto regression, ARCH, ARMA

Procedia PDF Downloads 351