Search results for: binary logistic model

Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

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Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

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Authors: Maba Boniface Matadi

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This paper analyses the model of Malaria endemic from the point of view of the group theoretic approach. The study identified new independent variables that lead to the transformation of the nonlinear model. Furthermore, corresponding determining equations were constructed, and new symmetries were found. As a result, the findings of the study demonstrate of the integrability of the model to present an invariant solution for the Malaria model.

Keywords: group theory, lie symmetry, invariant solutions, malaria

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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: Javier López

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This Paper presents the evaluation model designed for the virtual education branch of The “Universidad Manuela Beltrán, Bogotá-Colombia”. This was the result of a research, developed as a case study, which had three stages: Document review, observation, and a perception survey for teachers. In the present model, the evaluation is a cross-cutting issue to the educational process. Therefore, it consists in a group of actions and guidelines which lead to analyze the student’s learning process from the admission, during the academic training, and to the graduation. This model contributes to the evaluation components which might interest other educational institutions or might offer methodological guidance to consolidate an own model

Keywords: model, evaluation, virtual education, learning process

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Authors: D. Leibman, D. Wolf, A. Gal-On

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Viral diseases of tomato crops result in heavy yield losses and may even jeopardize the production of these crops. Classical tomato breeding for disease resistance against Tomato yellow leaf curl virus (TYLCV), leads to partial resistance associated with a number of recessive genes. To author’s best knowledge Pepino mosaic virus (PepMV) genetic resistance is not yet available. The generation of viral resistance by means of genetic engineering was reported and implemented for many crops, including tomato. Transgenic resistance against viruses is based, in most cases, on Post Transcriptional Gene Silencing (PTGS), an endogenous mechanism which destroys the virus genome. In this work, we developed immunity against PepMV and TYLCV in a tomato based on a PTGS mechanism. Tomato plants were transformed with a hairpin-construct-expressed transgene-derived double-strand-RNA (tr-dsRNA). In the case of PepMV, the binary construct harbored three consecutive fragments of the replicase gene from three different PepMV strains (Italian, Spanish and American), to provide resistance against a range of virus strains. In the case of TYLCV, the binary vector included three consecutive fragments of the IR, V2 and C2 viral genes constructed in a hairpin configuration. Selected transgenic lines (T0) showed a high accumulation of transgene siRNA of 21-24 bases, and T1 transgenic lines showed complete immunity to PepMV and TYLCV. Graft inoculation displayed immunity of the transgenic scion against PepMV and TYLCV. The study presents the engineering of resistance in tomato against two serious diseases, which will help in the production of high-quality tomato. However, unfortunately, these resistant plants have not been implemented due to public ignorance and opposition against breeding by genetic engineering.

Keywords: PepMV, PTGS, TYLCV, tr-dsRNA

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Authors: L. S. Zavodna, J. Zavodny Pospisil

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The aim of this paper is to identify the factors for sustainability in the accommodation sector. Although sustainability is a current trend in tourism, not many facilities know how to apply the concept in practice. This paper presents a model for the implementation of sustainability in hotels, hostels, campgrounds, or other facilities. First, there are identified sections of each accommodation facility, which can contribute to sustainability. Furthermore, concrete steps are presented to transfer this model into reality.

Keywords: accommodation sector, model, sustainable tourism, sustainability

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Authors: Luke S. Carlos A. Thompson

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The medical model of disability, though beneficial for the medical professional, is often exclusionary, restrictive and dehumanizing when applied to the lived experience of disability. As a result, a critique of this model was constructed called the social model of disability. Much of the language used to articulate the purpose behind the social model of disability can be summed up within the word inclusion. However, this essay asserts that inclusiveness is an incomplete aspiration. The social model, as it currently stands, does not aid in creating a society where those with impairments actually belong. Rather, the social model aids in lessening the visibility, or negative consequence of, difference. Therefore, the social model does not invite society to welcome those with physical and intellectual impairments. It simply aids society in ignoring the existence of impairment by removing explicit forms of exclusion. Rather than simple inclusion, then, this essay uses John Swinton’s concept of friendship and Jean Vanier’s understanding of belonging to better articulate the intended outcome of the social model—a society where everyone can belong.

Keywords: belong, community, differently-able, disability, exclusion, friendship, inclusion, normality

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Authors: Urmi Khatri

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Capital asset pricing model (CAPM) draws a direct relationship between the risk and the expected rate of return. There was a criticism on the beta and the assumptions of CAPM, as they are not applicable in the real world. Fama French Three Factor Model and Fama French Five Factor Model have given different factors, which have an impact on the return of any asset like size, value, investment and profitability. This study proposes to see Capital Asset pricing Model through the lenses of the quality aspect. In the study, the six factors are studied. The Fama French Five Factor Model and addition of the quality dimension are studied. Here, Graham’s seven quality and quantity criteria are measured to determine the score of the sample firms. Thus, this study tries to check the model fit. The beta coefficient of the quality dimension and the R square value is seen to determine validity of the proposed model. The sample is drawn from the firms listed on Indian Stock Exchange (BSE). For the study, only nonfinancial firms are been selected. The time period of the study is from January 1999 to December 2019. Hence, the primary objective of the study is to check how robust the model becomes after giving the quality dimension to the capital asset pricing model in addition to the size, value, profitability and investment.

Keywords: asset pricing model, CAPM, Graham’s score, G-score, multifactor model, quality

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Authors: Abdelouaheb Rouabhi

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In order to study the plastic resource of structures, the elastic-plastic single degree of freedom model described by Prandtl diagram is widely used. The generalization of this model to tow degree of freedom beyond the scope of a simple rigid-plastic system allows investigating the plastic resource of structures under complex disproportionate by individual components of deformation (earthquake). This macro-model greatly increases the accuracy of the calculations carried out. At the same time, the implementation of the proposed macro-model calculations easier than the detailed dynamic elastic-plastic calculations existing software systems such as ANSYS.

Keywords: elastic-plastic, single degree of freedom model, rigid-plastic system, plastic resource, complex plastic deformation, macro-model

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

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Authors: Arezoo Fallahi

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We aimed at investigating the association between health beliefs and exercise behavior in infertile women who were at risk of developing osteoporosis. This cross-sectional study was conducted in Sanandaj city, west of Iran in 2018. From 35 comprehensive healthcare centers, 483 infertile women were included in the study through convenience sampling. Standardized face-to-face interviews were conducted using established, reliable instruments for the assessment of exercise behavior behavior and health beliefs. Logistic regression models were applied to assess the association between exercise behavior and health beliefs. Estimates were adjusted for age, job status, income, literacy, and duration and type of infertility. We reported estimated logits and Odds Ratios (OR) with corresponding 95% confidence intervals (95% CI). Employed women compared to housewives had substantially higher odds of adopting exercise behavior behaviors (OR=3.19, 95% CI=1.53-6.66, p<0.01). Moreover, the odds of exercise behavior adoption increased with self-efficacy (OR=1.35, 95% CI=1.20-1.52, p<0.01), and decreased with perceived barriers (OR=0.90, 95% CI=0.84-0.97, p<0.01). It is essential to increase perceived self-efficacy and reduce perceived barriers to promote EB in infertile women. Consequently, health professionals should develop or adopt appropriate strategies to decrease barriers and increase self-efficacy to enhance exercise behavior in this group of women.

Keywords: infertility, women, exercise, osteoporosis

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Authors: Martin Goubej, Tomas Popule, Alois Krejci

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This paper deals with experimental identification of mechanical systems with nonlinear friction characteristics. Dynamic LuGre friction model is adopted and a systematic approach to parameter identification of both linear and nonlinear subsystems is given. The identification procedure consists of three subsequent experiments which deal with the individual parts of plant dynamics. The proposed method is experimentally verified on an industrial-grade robotic manipulator. Model fidelity is compared with the results achieved with a static friction model.

Keywords: mechanical friction, LuGre model, friction identification, motion control

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Authors: Trupti Meher, Harihar Sahoo

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Premature menopause refers to the occurrence of menopause before the age of 40 years. Women who experience premature menopause either due to biological or induced reasons have a longer duration of exposure to severe symptoms and adverse health consequences when compared to those who undergo menopause at a later age, despite the fact that premature menopause has a profound effect on the health of women. This study attempted to determine the prevalence and predictors of premature menopause among women aged 25-39 years, using data from the National Family Health Survey (NFHS-4) conducted during 2015–16 in India. Descriptive statistics and multinomial logistic regression were used to carry out the result. The results revealed that the prevalence of premature menopause in India was 3.7 percent. Out of which, 2.1 percent of women had experienced natural premature menopause, whereas 1.7 percent had premature surgical menopause. The prevalence of premature menopause was highest in the southern region of India. Further, results of the multivariate model indicated that rural women, women with higher parity, early age at childbearing and women with smoking habits were at a greater risk of premature menopause. A sizeable proportion of women in India are attaining menopause prematurely. Unless due attention is given to this matter, it will emerge as a major problem in India in the future. The study also emphasized the need for further research to enhance knowledge on the problems of premature menopausal women in different socio-cultural settings in India.

Keywords: India, natural menopause, premature menopause, surgical menopause

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Authors: Arash Najmaei, Jo Rhodes, Peter Lok, Zahra Sadeghinejad

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In this article, we endeavor to explore how a new business model comes into existence in the Australian cloud-computing eco-system. Findings from multiple case study methodology reveal that to develop a business model new ventures adopt a three-phase approach. In the first phase, labelled as business model ideation (BMID) various ideas for a viable business model are generated from both internal and external networks of the entrepreneurial team and the most viable one is chosen. Strategic consensus and commitment are generated in the second phase. This phase is a business modelling strategic action phase. We labelled this phase as business model strategic commitment (BMSC) because through commitment and the subsequent actions of executives resources are pooled, coordinated and allocated to the business model. Three complementary sets of resources shape the business model: managerial (MnRs), marketing (MRs) and technological resources (TRs). The third phase is the market-test phase where the business model is reified through the delivery of the intended value to customers and conversion of revenue into profit. We labelled this phase business model actualization (BMAC). Theoretical and managerial implications of these findings will be discussed and several directions for future research will be illuminated.

Keywords: entrepreneur business model, high-tech venture, resources, conversion of revenue

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Authors: El Harraj Abdeslam, Raissouni Naoufal

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The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes in variance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: video surveillance, background subtraction, contrast limited histogram equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes

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Authors: Juraj Camaj, Martin Kendra, Jaroslav Masek

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The paper is focused to the evaluation railway tracks in the Slovakia by using Multi-Criteria method. Evaluation of railway tracks has important impacts for the assessment of investment in technical equipment. Evaluation of railway tracks also has an important impact for the allocation of marshalling yards. Marshalling yards are in transport model as centers for the operation assigned catchment area. This model is one of the effective ways to meet the development strategy of the European Community's railways. By applying this model in practice, a transport company can guarantee a higher quality of service and then expect an increase in performance. The model is also applicable to other rail networks. This model supplements a theoretical problem of train formation problem of new ways of looking at evaluation of factors affecting the organization of wagon flows.

Keywords: railway track, multi-criteria methods, evaluation, transportation model

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Authors: Changtong Wang, Lingyun Wei

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The combination of auctions and supply chains is of great significance in improving the supply chain management system and enhancing the efficiency of economic and social operations. To address the gap in research on supply chain strategies under the auction mechanism, a model is developed for the 1-N auction model in a complete information environment, and it is concluded that the two-part contract auction model for retailers in this model can achieve supply chain coordination. The model is validated by substituting the model into the scenario of a fresh-cut flower industry flower auction in exchange for arithmetic examples to further prove the validity of the conclusions.

Keywords: auction mechanism, supply chain coordination strategy, fresh cut flowers industry, supply chain management

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Authors: B. T. Chew, S. N. Kazi, A. Amiri

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This paper presents an adaptive thermal comfort model study in the tropical country of Malaysia. A number of researchers have been interested in applying the adaptive thermal comfort model to different climates throughout the world, but so far no study has been performed in Malaysia. For the use as a thermal comfort model, which better applies to hot and humid climates, the adaptive thermal comfort model was developed as part of this research by using the collected results from a large field study in six lecture halls with 178 students. The relationship between the operative temperature and behavioral adaptations was determined. In the developed adaptive model, the acceptable indoor neutral temperatures lay within the range of 23.9-26.0 oC, with outdoor temperatures ranging between 27.0–34.6oC. The most comfortable temperature for students in the lecture hall was 25.7 oC.

Keywords: hot and humid, lecture halls, neutral temperature, adaptive thermal comfort model

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Authors: Arosha Rashmi De Silva, Ananda Chandrasekara

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This study seeks to comprehensively examine the influence of fast-food consumption and physical activity levels on the body weight of young employees within the private sector of Sri Lanka. The escalating popularity of fast food has raised concerns about its nutritional content and associated health ramifications. To investigate this phenomenon, a cohort of 100 individuals aged between 25 and 45, employed in Sri Lanka's private sector, participated in this research. These participants provided socio-demographic data through a standardized questionnaire, enabling the characterization of their backgrounds. Additionally, participants disclosed their frequency of fast-food consumption and engagement in physical activities, utilizing validated assessment tools. The collected data was meticulously compiled into an Excel spreadsheet and subjected to rigorous statistical analysis. Descriptive statistics, such as percentages and proportions, were employed to delineate the body weight status of the participants. Employing chi-square tests, our study identified significant associations between fast-food consumption, levels of physical activity, and body weight categories. Furthermore, through binary logistic regression analysis, potential risk factors contributing to overweight and obesity within the young employee cohort were elucidated. Our findings revealed a disconcerting trend, with 6% of participants classified as underweight, 32% within the normal weight range, and a substantial 62% categorized as overweight or obese. These outcomes underscore the alarming prevalence of overweight and obesity among young private-sector employees, particularly within the bustling urban landscape of Colombo, Sri Lanka. The data strongly imply a robust correlation between fast-food consumption, sedentary behaviors, and higher body weight categories, reflective of the evolving lifestyle patterns associated with the nation's economic growth. This study emphasizes the urgent need for effective interventions to counter the detrimental effects of fast-food consumption. The implementation of awareness campaigns elucidating the adverse health consequences of fast food, coupled with comprehensive nutritional education, can empower individuals to make informed dietary choices. Workplace interventions, including the provision of healthier meal alternatives and the facilitation of physical activity opportunities, are essential in fostering a healthier workforce and mitigating the escalating burden of overweight and obesity in Sri Lanka

Keywords: fast food consumption, obese, overweight, physical activity level

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Authors: Nutcha Taneepanichskul, Helen C. Hailes, Mark Miodownik

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Plastic waste has emerged as a critical global environmental challenge, primarily driven by the prevalent use of conventional plastics derived from petrochemical refining and manufacturing processes in modern packaging. While these plastics serve vital functions, their persistence in the environment post-disposal poses significant threats to ecosystems. Addressing this issue necessitates approaches, one of which involves the development of biodegradable plastics designed to degrade under controlled conditions, such as industrial composting facilities. It is imperative to note that compostable plastics are engineered for degradation within specific environments and are not suited for uncontrolled settings, including natural landscapes and aquatic ecosystems. The full benefits of compostable packaging are realized when subjected to industrial composting, preventing environmental contamination and waste stream pollution. Therefore, effective sorting technologies are essential to enhance composting rates for these materials and diminish the risk of contaminating recycling streams. In this study, it leverage hyperspectral imaging technology (HSI) coupled with advanced machine learning algorithms to accurately identify various types of plastics, encompassing conventional variants like Polyethylene terephthalate (PET), Polypropylene (PP), Low density polyethylene (LDPE), High density polyethylene (HDPE) and biodegradable alternatives such as Polybutylene adipate terephthalate (PBAT), Polylactic acid (PLA), and Polyhydroxyalkanoates (PHA). The dataset is partitioned into three subsets: a training dataset comprising uncontaminated conventional and biodegradable plastics, a validation dataset encompassing contaminated plastics of both types, and a testing dataset featuring real-world packaging items in both pristine and contaminated states. Five distinct machine learning algorithms, namely Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Logistic Regression, and Decision Tree Algorithm, were developed and evaluated for their classification performance. Remarkably, the Logistic Regression and CNN model exhibited the most promising outcomes, achieving a perfect accuracy rate of 100% for the training and validation datasets. Notably, the testing dataset yielded an accuracy exceeding 80%. The successful implementation of this sorting technology within recycling and composting facilities holds the potential to significantly elevate recycling and composting rates. As a result, the envisioned circular economy for plastics can be established, thereby offering a viable solution to mitigate plastic pollution.

Keywords: biodegradable plastics, sorting technology, hyperspectral imaging technology, machine learning algorithms

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Authors: Xiang Zhang, David Rey, S. Travis Waller

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Stochastic User Equilibrium (SUE) model is a widely used traffic assignment model in transportation planning, which is regarded more advanced than Deterministic User Equilibrium (DUE) model. However, a problem exists that the performance of the SUE model depends on its error term parameter. The objective of this paper is to propose a systematic method of determining the appropriate error term parameter value for the SUE model. First, the significance of the parameter is explored through a numerical example. Second, the parameter calibration method is developed based on the Logit-based route choice model. The calibration process is realized through multiple nonlinear regression, using sequential quadratic programming combined with least square method. Finally, case analysis is conducted to demonstrate the application of the calibration process and validate the better performance of the SUE model calibrated by the proposed method compared to the SUE models under other parameter values and the DUE model.

Keywords: parameter calibration, sequential quadratic programming, stochastic user equilibrium, traffic assignment, transportation planning

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Authors: A. D. Susanti, W. B. Sediawan, S. K. Wirawan, Budhijanto, Ritmaleni

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Rice bran oil contains significant amounts of oryzanol, a natural antioxidant that considered has higher antioxidant activity than vitamin E (tocopherol). Oryzanol reviewed has several health properties and interested in pharmacy, nutrition, and cosmetics. For practical usage, isolation and purification would be necessary due to the low concentration of oryzanol in crude rice bran oil (0.9-2.9%). Batch chromatography has proved as a promising process for the oryzanol recovery, but productivity was still low and scale-up processes of industrial interest have not yet been described. In order to improve productivity of batch chromatography, a continuous chromatography design namely Simulated Moving Bed (SMB) concept have been proposed. The SMB concept has interested for continuous commercial scale separation of binary system (oryzanol and rice bran oil), and rice bran oil still obtained as side product. Design of SMB chromatography for oryzanol separation requires quantification of its equilibrium. In this study, equilibrium of oryzanol separation conducted in batch adsorption using silica as the adsorbent and n-hexane/acetone (9:1) as the eluent. Three isotherm models, namely the Henry, Langmuir, and Freundlich equations, have been applied and modified for the experimental data to establish appropriate correlation for each sample. It turned out that the model quantitatively describe the equilibrium experimental data and will directed for design of SMB chromatography.

Keywords: adsorption, equilibrium, oryzanol, rice bran oil, simulated moving bed

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Authors: Jin-Wei Liang, Hung-Yi Chen, Lung Lin

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In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller.

Keywords: the Bouc-Wen hysteresis model, particle swarm optimization, Prandtl-Ishlinskii model, automation engineering

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Authors: Yiseyon Sunday Hosu, Motebang Dominic Vincent Nakin, Elphina N. Cishe

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Universal access to clean and safe drinking water and basic sanitation is one of the targets of the 6th Sustainable Development Goals (SDGs). This paper explores the evidence-based indicators of Water Rights Acts (2013) among households in the rural communities in the Mthatha River catchment of OR Tambo District Municipality of South Africa. Daily access to minimum 25 litres/person and the factors influencing clean water access were investigated in the catchment. A total number of 420 households were surveyed in the upper, peri-urban, lower and coastal regions of Mthatha Rivier catchment. Descriptive and logistic regression analyses were conducted on the data collected from the households to elicit vital information on domestic water security among rural community dwellers. The results show that approximately 68 percent of total households surveyed have access to the required minimum 25 litre/person/day, with 66.3 percent in upper region, 76 per cent in the peri-urban, 1.1 percent in the lower and 2.3 percent in the coastal regions. Only 30 percent among the total surveyed households had access to piped water either in the house or public taps. The logistic regression showed that access to clean water was influenced by lack of water infrastructure, proximity to urban regions, daily flow of pipe-borne water, household size and distance to public taps. This paper recommends that viable integrated rural community-based water infrastructure provision strategies between NGOs and local authority and the promotion of point of use (POU) technologies to enhance better access to clean water.

Keywords: domestic water, household technology, water security, rural community

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Authors: Seung-Yeon Kim

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The Ising model, consisting magnetic spins, is the simplest system showing phase transitions and critical phenomena at finite temperatures. The Ising model has played a central role in our understanding of phase transitions and critical phenomena. Also, the Ising model explains the gas-liquid phase transitions accurately. However, the Ising model in a nonzero magnetic field has been one of the most intriguing and outstanding unsolved problems. We study analytically the partition function zeros in the complex magnetic-field plane and the Yang-Lee edge singularity of the infinite-range Ising model in an external magnetic field. In addition, we compare the Yang-Lee edge singularity of the infinite-range Ising model with that of the square-lattice Ising model in an external magnetic field.

Keywords: Ising ferromagnet, magnetic field, partition function zeros, Yang-Lee edge singularity

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Authors: Hyuk-Hoon Kim, Young Gi Min

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Background: In carbon monoxide (CO) intoxication, the pathophysiology of delayed neurological sequelae (DNS) is very complex and remains poorly understood. And predicting whether patients who exhibit resolved acute symptoms have escaped or will experience DNS represents a very important clinical issue. Brain magnetic resonance (MR) imaging has been conducted to assess the severity of brain damage as an objective method to predict prognosis. And co-ingestion of a second poison in patients with intentional CO poisoning occurs in almost one-half of patients. Among patients with co-ingestions, 66% ingested ethanol. We assessed the effects of ethanol on neurologic sequelae prevalence in acute CO intoxication by means of abnormal lesion in brain MR. Method: This study was conducted retrospectively by collecting data for patients who visited an emergency medical center during a period of 5 years. The enrollment criteria were diagnosis of acute CO poisoning and the measurement of the serum ethanol level and history of taking a brain MR during admission period. Official readout data by radiologist are used to decide whether abnormal lesion is existed or not. The enrolled patients were divided into two groups: patients with abnormal lesion and without abnormal lesion in Brain MR. A standardized extraction using medical record was performed; Mann Whitney U test and logistic regression analysis were performed. Result: A total of 112 patients were enrolled, and 68 patients presented abnormal brain lesion on MR. The abnormal brain lesion group had lower serum ethanol level (mean, 20.14 vs 46.71 mg/dL) (p-value<0.001). In addition, univariate logistic regression analysis showed the serum ethanol level (OR, 0.99; 95% CI, 0.98 -1.00) was independently associated with the development of abnormal lesion in brain MR. Conclusion: Ethanol could have neuroprotective effect in acute CO intoxication by sedative effect in stressful situation and mitigative effect in neuro-inflammatory reaction.

Keywords: carbon monoxide, delayed neuropsychological sequelae, ethanol, intoxication, magnetic resonance

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Authors: K. Khanafer

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The aim of this investigation was to validate the fluid-structure interaction (FSI) model of type B aortic dissection with our experimental results from a bench-top-model. Another objective was to study the relationship between the size of a septectomy that increases the outflow of the false lumen and its effect on the values of the differential of pressure between true lumen and false lumen. FSI analysis based on Galerkin’s formulation was used in this investigation to study flow pattern and hemodynamics within a flexible type B aortic dissection model using boundary conditions from our experimental data. The numerical results of our model were verified against the experimental data for various tear size and location. Thus, CFD tools have a potential role in evaluating different scenarios and aortic dissection configurations.

Keywords: aortic dissection, fluid-structure interaction, in vitro model, numerical

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Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

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In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange

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Authors: Pratap K. Chhotaray, Jitendriya Swain, Ashok Mishra, Ramesh L. Gardas

Abstract:

Ionic liquids (ILs) are molten salts, consist predominantly of ions and found to be liquid below 100°C. The unparalleled growing interest in ILs is based upon their never ending design flexibility. The use of ILs as a co-solvent in binary as well as a ternary mixture with molecular solvents multifold it’s utility. Since polarity is one of the most widely applied solvent concepts which represents simple and straightforward means for characterizing and ranking the solvent media, its study for a binary mixture of ILs is crucial for its widespread application and development. The primary approach to the assessment of solution phase intermolecular interactions, which generally occurs on the picosecond to nanosecond time scales, is to exploit the optical response of photophysical probe. Pyrene butyric acid (PBA) is used as fluorescence probe due to its high quantum yield, longer lifetime and high solvent polarity dependence of fluorescence spectra. Propylammonium formate (PAF) is the IL used for this study. Both the UV-absorbance spectra and steady state fluorescence intensity study of PBA in different concentration of aqueous PAF, reveals that with an increase in PAF concentration, both the absorbance and fluorescence intensity increases which indicate the progressive solubilisation of PBA. Whereas, near about 50% of IL concentration, all of the PBA molecules get solubilised as there are no changes in the absorbance and fluorescence intensity. Furthermore, the ratio II/IV, where the band II corresponds to the transition from S1 (ν = 0) to S0 (ν = 0), and the band IV corresponds to transition from S1 (ν = 0) to S0 (ν = 2) of PBA, indicates that the addition of water into PAF increases the polarity of the medium. Time domain lifetime study shows an increase in lifetime of PBA towards the higher concentration of PAF. It can be attributed to the decrease in non-radiative rate constant at higher PAF concentration as the viscosity is higher. The monoexponential decay suggests that homogeneity of solvation environment whereas the uneven width at full width at half maximum (FWHM) indicates there might exist some heterogeneity around the fluorophores even in the water-IL mixed solvents.

Keywords: fluorescence, ionic liquid, lifetime, polarity, pyrene butyric acid

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Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

Abstract:

In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

Procedia PDF Downloads 357