Search results for: equation modeling methods

Authors: Anna Gramza-Michałowska, Dominik Kmiecik, Justyna Bilon, Joanna Skręty, Joanna Kobus-Cisowska, Józef Korczak, Andrzej Sidor

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Background: Hypertension is one of the civilization diseases with a global scope. Many research showed that every day diet influences significantly our health, helping with the prophylaxis and diseases treatment. The key factor here is the presence of plant origin natural bio active components. Aim: The following research describes snack health-oriented products for hypertension sufferers enriched with selected plant ingredients. Various analytical methods have been applied to determine product’s basic composition and their antioxidant activity. Methods: Snack products was formulated from a composition of different flours, oil, yeast, plant particles and extracts. Basic composition of a product was evaluated as content of protein, lipids, fiber, ash and caloricity. Antioxidant capacity of snacks was evaluated with use radical scavenging methods (DPPH, ABTS) and ORAC value. Proposed snacks as new product was also characterized with sensory analysis. Results and discussion: Results showed that addition of phyto nutrients allowed to improve nutritional and antioxidative value of examined products. Also the anti radical potential was significantly increased, with no loss of sensory value of a snacks. Conclusions: Designed snack is rich in polyphenolics, that express high antioxidant activity, helpful in hypertension and as low calories product obesity prophylaxis.

Keywords: antioxidant, well-being, hypertension, bioactive compounds

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Authors: Akshay B. Pawar, Rohit Y. Parasnis

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Heart Rate Variability (HRV) is a widely used indicator of the regulation between the autonomic nervous system (ANS) and the cardiovascular system. Besides being non-invasive, it also has the potential to predict mortality in cases involving critical injuries. The gold standard method for determining HRV is based on the analysis of RR interval time series extracted from ECG signals. However, because it is much more convenient to obtain photoplethysmogramic (PPG) signals as compared to ECG signals (which require the attachment of several electrodes to the body), many researchers have used pulse cycle intervals instead of RR intervals to estimate HRV. They have also compared this method with the gold standard technique. Though most of their observations indicate a strong correlation between the two methods, recent studies show that in healthy subjects, except for a few parameters, the pulse-based method cannot be a surrogate for the standard RR interval- based method. Moreover, the former tends to overestimate short-term variability in heart rate. This calls for improvements in or alternatives to the pulse-cycle interval method. In this study, besides the systolic peak-peak interval method (PP method) that has been studied several times, four recent PPG-based techniques, namely the first derivative peak-peak interval method (P1D method), the second derivative peak-peak interval method (P2D method), the valley-valley interval method (VV method) and the tangent-intersection interval method (TI method) were compared with the gold standard technique. ECG and PPG signals were obtained from 10 young and healthy adults (consisting of both males and females) seated in the armchair position. In order to de-noise these signals and eliminate baseline drift, they were passed through certain digital filters. After filtering, the following HRV parameters were computed from PPG using each of the five methods and also from ECG using the gold standard method: time domain parameters (SDNN, pNN50 and RMSSD), frequency domain parameters (Very low-frequency power (VLF), Low-frequency power (LF), High-frequency power (HF) and Total power or “TP”). Besides, Poincaré plots were also plotted and their SD1/SD2 ratios determined. The resulting sets of parameters were compared with those yielded by the standard method using measures of statistical correlation (correlation coefficient) as well as statistical agreement (Bland-Altman plots). From the viewpoint of correlation, our results show that the best PPG-based methods for the determination of most parameters and Poincaré plots are the P2D method (shows more than 93% correlation with the standard method) and the PP method (mean correlation: 88%) whereas the TI, VV and P1D methods perform poorly (<70% correlation in most cases). However, our evaluation of statistical agreement using Bland-Altman plots shows that none of the five techniques agrees satisfactorily well with the gold standard method as far as time-domain parameters are concerned. In conclusion, excellent statistical correlation implies that certain PPG-based methods provide a good amount of information on the pattern of heart rate variation, whereas poor statistical agreement implies that PPG cannot completely replace ECG in the determination of HRV.

Keywords: photoplethysmography, heart rate variability, correlation coefficient, Bland-Altman plot

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Authors: J. Fernandez de Canete, S. Fernandez-Calvo, I. García-Moral

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This paper presents and discusses the application of the object-oriented modelling software SIMSCAPE to hydraulic systems, with particular reference to multivariable proportional-integral-derivative (PID) control. As a result, a particular modelling approach of a double cylinder-piston coupled system is proposed and motivated, and the SIMULINK based PID tuning tool has also been used to select the proper controller parameters. The paper demonstrates the usefulness of the object-oriented approach when both physical modelling and control are tackled.

Keywords: object-oriented modeling, multivariable hydraulic system, multivariable PID control, computer simulation

Procedia PDF Downloads 332

Authors: J. Satya Eswari, J. Sekhar Babub, Meena Murmu, Govardhan Bhat

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Electrical Discharge Machining (EDM) is an unconventional manufacturing process based on removal of material from a part by means of a series of repeated electrical sparks created by electric pulse generators at short intervals between a electrode tool and the part to be machined emmersed in dielectric fluid. In this paper, a study will be performed on the influence of the factors of peak current, pulse on time, interval time and power supply voltage. The output responses measured were material removal rate (MRR) and surface roughness. Finally, the parameters were optimized for maximum MRR with the desired surface roughness. RSM involves establishing mathematical relations between the design variables and the resulting responses and optimizing the process conditions. RSM is not free from problems when it is applied to multi-factor and multi-response situations. Design of experiments (DOE) technique to select the optimum machining conditions for machining AISI 4140 using EDM. The purpose of this paper is to determine the optimal factors of the electro-discharge machining (EDM) process investigate feasibility of design of experiment techniques. The work pieces used were rectangular plates of AISI 4140 grade steel alloy. The study of optimized settings of key machining factors like pulse on time, gap voltage, flushing pressure, input current and duty cycle on the material removal, surface roughness is been carried out using central composite design. The objective is to maximize the Material removal rate (MRR). Central composite design data is used to develop second order polynomial models with interaction terms. The insignificant coefficients’ are eliminated with these models by using student t test and F test for the goodness of fit. CCD is first used to establish the determine the optimal factors of the electro-discharge machining (EDM) for maximizing the MRR. The responses are further treated through a objective function to establish the same set of key machining factors to satisfy the optimization problem of the electro-discharge machining (EDM) process. The results demonstrate the better performance of CCD data based RSM for optimizing the electro-discharge machining (EDM) process.

Keywords: electric discharge machining (EDM), modeling, optimization, CCRD

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Authors: Bin Liu

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Prokaryotic promoter, consisted of two short DNA sequences located at in -35 and -10 positions, is responsible for controlling the initiation and expression of gene expression. Different types of promoters have different functions, and their consensus sequences are similar. In addition, their consensus sequences may be different for the same type of promoter, which poses difficulties for promoter identification. Unfortunately, all existing computational methods treat promoter identification as a binary classification task and can only identify whether a query sequence belongs to a specific promoter type. It is desired to develop computational methods for effectively identifying promoters and their types. Here, a two-layer predictor is proposed to try to deal with the problem. The first layer is designed to predict whether a given sequence is a promoter and the second layer predicts the type of promoter that is judged as a promoter. Meanwhile, we also analyze the importance of feature and sequence conversation in two aspects: promoter identification and promoter type identification. To the best knowledge of ours, it is the first computational predictor to detect promoters and their types.

Keywords: promoter, promoter type, random forest, sequence information

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Authors: Ujjal Chattaraj, P. C. Dasbebartta, S. Bhuyan

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This paper aims to propose a method to detect the action of the driver’s eyes, using the concept of face detection. There are three major key contributing methods which can rapidly process the framework of the facial image and hence produce results which further can program the reactions of the vehicles as pre-programmed for the traffic safety. This paper compares and analyses the methods on the basis of their reaction time and their ability to deal with fluctuating images of the driver. The program used in this study is simple and efficient, built using the AdaBoost learning algorithm. Through this program, the system would be able to discard background regions and focus on the face-like regions. The results are analyzed on a common computer which makes it feasible for the end users. The application domain of this experiment is quite wide, such as detection of drowsiness or influence of alcohols in drivers or detection for the case of identification.

Keywords: AdaBoost learning algorithm, face detection, framework, traffic safety

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Authors: Akhmylovskaia Larisa, Barysh Andriana

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The present paper is introducing the translation score developing methodology and methods in the cross-cultural communication. The ideas and examples presented by the authors illustrate the universal character of translation score developing methods under analysis. Personal experience in the international theatre-making projects, opera laboratories, cross-cultural master-classes, movie and theatre festivals give more opportunities to single out the conditions, forms, means and principles of translation score developing as well as the translator/interpreter’s functions as cultural liaison for multiethnic collaboration.

Keywords: methodology of translation score developing, pre-production, analysis, production, post-production, ethnic scene theory, theatre anthropology, laboratory, master-class, educational project, academic project, Stanislavski terminology meta-language, super-objective, participant observation

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Authors: Misra Ayse Adsiz, Selim Selvi

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In today's world, technology is competing with time. In order to catch up with the world's companies and adapt quickly to the changes, it is necessary to speed up the processes and keep pace with the rate of change of the technology. The missile system design processes, which are handled with classical methods, keep behind in this race. Because customer requirements are not clear, and demands are changing again and again in the design process. Therefore, in the system design process, a methodology suitable for the missile system design dynamics has been investigated and the processes used for catching up the era are examined. When commonly used design processes are analyzed, it is seen that any one of them is dynamic enough for today’s conditions. So a hybrid design process is established. After a detailed review of the existing processes, it is decided to focus on the Scrum Framework and Agile Philosophy. Scrum is a process framework. It is focused on to develop software and handling change management with rapid methods. In addition, agile philosophy is intended to respond quickly to changes. In this study, it is aimed to integrate Scrum framework and agile philosophy, which are the most appropriate ways for rapid production and change adaptation, into the missile system design process. With this approach, it is aimed that the design team, involved in the system design processes, is in communication with the customer and provide an iterative approach in change management. These methods, which are currently being used in the software industry, have been integrated with the product design process. A team is created for system design process. The roles of Scrum Team are realized with including the customer. A scrum team consists of the product owner, development team and scrum master. Scrum events, which are short, purposeful and time-limited, are organized to serve for coordination rather than long meetings. Instead of the classic system design methods used in product development studies, a missile design is made with this blended method. With the help of this design approach, it is become easier to anticipate changing customer demands, produce quick solutions to demands and combat uncertainties in the product development process. With the feedback of the customer who included in the process, it is worked towards marketing optimization, design and financial optimization.

Keywords: agile, design, missile, scrum

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Authors: Mina Sadat Orooje, Mohammad Mehdi Latifi, Behnam Fereydooni Eftekhari

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The integration of cutting-edge Internet of Things (IoT) technologies with advanced Artificial Intelligence (AI) systems is revolutionizing healthcare facility management. However, the current landscape of hospital building maintenance suffers from slow, repetitive, and disjointed processes, leading to significant financial, resource, and time losses. Additionally, the potential of Building Information Modeling (BIM) in facility maintenance is hindered by a lack of data within digital models of built environments, necessitating a more streamlined data collection process. This paper presents a robust framework that harmonizes AI with BIM-IoT technology to elevate healthcare Facility Maintenance Management (FMM) and address these pressing challenges. The methodology begins with a thorough literature review and requirements analysis, providing insights into existing technological landscapes and associated obstacles. Extensive data collection and analysis efforts follow to deepen understanding of hospital infrastructure and maintenance records. Critical AI algorithms are identified to address predictive maintenance, anomaly detection, and optimization needs alongside integration strategies for BIM and IoT technologies, enabling real-time data collection and analysis. The framework outlines protocols for data processing, analysis, and decision-making. A prototype implementation is executed to showcase the framework's functionality, followed by a rigorous validation process to evaluate its efficacy and gather user feedback. Refinement and optimization steps are then undertaken based on evaluation outcomes. Emphasis is placed on the scalability of the framework in real-world scenarios and its potential applications across diverse healthcare facility contexts. Finally, the findings are meticulously documented and shared within the healthcare and facility management communities. This framework aims to significantly boost maintenance efficiency, cut costs, provide decision support, enable real-time monitoring, offer data-driven insights, and ultimately enhance patient safety and satisfaction. By tackling current challenges in healthcare facility maintenance management it paves the way for the adoption of smarter and more efficient maintenance practices in healthcare facilities.

Keywords: artificial intelligence, building information modeling, healthcare facility maintenance, internet of things integration, maintenance efficiency

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Authors: Kanokwan Chancharoenchai

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Economic growth can be considered as an important element of countries’ development process. For developing countries, like Thailand, to ensure the continuous growth of the economy, the Thai government usually implements various policies to stimulate economic growth. They may take the form of fiscal, monetary, trade, and other policies. Because of these different aspects, understanding factors relating to economic growth could allow the government to introduce the proper plan for the future economic stimulating scheme. Consequently, this issue has caught interest of not only policymakers but also academics. This study, therefore, investigates explanatory variables for economic growth in Thailand from 2005 to 2017 with a total of 52 quarters. The findings would contribute to the field of economic growth and become helpful information to policymakers. The investigation is estimated throughout the production function with non-linear Cobb-Douglas equation. The rate of growth is indicated by the change of GDP in the natural logarithmic form. The relevant factors included in the estimation cover three traditional means of production and implicit effects, such as human capital, international activity and technological transfer from developed countries. Besides, this investigation takes the internal and external instabilities into account as proxied by the unobserved inflation estimation and the real effective exchange rate (REER) of the Thai baht, respectively. The unobserved inflation series are obtained from the AR(1)-ARCH(1) model, while the unobserved REER of Thai baht is gathered from naive OLS-GARCH(1,1) model. According to empirical results, the AR(|2|) equation which includes seven significant variables, namely capital stock, labor, the imports of capital goods, trade openness, the REER of Thai baht uncertainty, one previous GDP, and the world financial crisis in 2009 dummy, presents the most suitable model. The autoregressive model is assumed constant estimator that would somehow cause the unbias. However, this is not the case of the recursive coefficient model from the state space model that allows the transition of coefficients. With the powerful state space model, it provides the productivity or effect of each significant factor more in detail. The state coefficients are estimated based on the AR(|2|) with the exception of the one previous GDP and the 2009 world financial crisis dummy. The findings shed the light that those factors seem to be stable through time since the occurrence of the world financial crisis together with the political situation in Thailand. These two events could lower the confidence in the Thai economy. Moreover, state coefficients highlight the sluggish rate of machinery replacement and quite low technology of capital goods imported from abroad. The Thai government should apply proactive policies via taxation and specific credit policy to improve technological advancement, for instance. Another interesting evidence is the issue of trade openness which shows the negative transition effect along the sample period. This could be explained by the loss of price competitiveness to imported goods, especially under the widespread implementation of free trade agreement. The Thai government should carefully handle with regulations and the investment incentive policy by focusing on strengthening small and medium enterprises.

Keywords: autoregressive model, economic growth, state space model, Thailand

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Authors: Bayan Ahmed Alsaffar

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The aim of this study is to assess the sustainability initiatives at Applied Sciences University (ASU) in Bahrain using a mixed-methods approach based on students, staff, and faculty perceptions. The study involves a literature review, interviews with faculty members and students, and a survey of ASU's level of sustainability in education, research, operations, administration, and finance that depended on the Sustainability Tracking, Assessment & Rating System (STARS). STARS is a tool used to evaluate the sustainability performance of higher education institutions. The study concludes that a mixed-methods approach can provide a powerful tool for assessing sustainability initiatives at ASU and ultimately lead to insights that can inform effective strategies for improving sustainability efforts. The current study contributes to the field of sustainability in universities and highlights the importance of user engagement and awareness for achieving sustainability goals.

Keywords: environment, initiatives, society, sustainability, STARS, university

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Authors: Abdulameer K. Hussain

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When dealing with a cryptographic system we note that there are many activities performed by parties of this cryptographic system and the most prominent of these activities is the process of agreement between the parties involved in the cryptographic system on how to deal and perform the cryptographic system tasks to be more secure, more confident and reliable. The most common agreement among parties is a key agreement and other types of agreements. Despite the fact that there is an attempt from some quarters to find other effective agreement methods but these methods are limited to the traditional agreements. This paper presents different parameters to perform more effectively the task of the agreement, including the key alternative, the agreement on the encryption method used and the agreement to prevent the denial of the services. To manage and achieve these goals, this method proposes the existence of an control and monitoring entity to manage these agreements by collecting different statistical information of the opinions of the authorized parties in the cryptographic system. These statistics help this entity to take the proper decision about the agreement factors. This entity is called Agreement Manager (AM).

Keywords: agreement parameters, key agreement, key exchange, security management

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Authors: Pedro Augusto Da Silva E Souza Miranda, Niloofar Jalali, Shweta Mistry

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BACKGROUND: Software developers utilize automated solutions to scrape users’ reviews to extract meaningful knowledge to identify problems (e.g., bugs, compatibility issues) and possible enhancements (e.g., users’ requests) to their solutions. However, most of these solutions do not consider the health risk aspects to users. Recent works have shed light on the importance of including health risk considerations in the development cycle of mHealth apps to prevent harm to its users. PROBLEM: The COVID-19 Pandemic in Canada (and World) is currently forcing physical distancing upon the general population. This new lifestyle made the usage of mHealth applications more essential than ever, with a projected market forecast of 332 billion dollars by 2025. However, this new insurgency in mHealth usage comes with possible risks to users’ health due to mHealth apps problems (e.g., wrong insulin dosage indication due to a UI error). OBJECTIVE: These works aim to raise awareness amongst mHealth developers of the importance of considering risks to users’ health within their development lifecycle. Moreover, this work also aims to help mHealth developers with a Proof-of-Concept (POC) solution to understand, process, and identify possible health risks to users of mHealth apps based on users’ reviews. METHODS: We conducted a mixed-method study design. We developed a crawler to mine the negative reviews from two samples of mHealth apps (my fitness, medisafe) from the Google Play store users. For each mHealth app, we performed the following steps: • The reviews are divided into two groups, before starting the COVID-19 (reviews’ submission date before 15 Feb 2019) and during the COVID-19 (reviews’ submission date starts from 16 Feb 2019 till Dec 2020). For each period, the Latent Dirichlet Allocation (LDA) topic model was used to identify the different clusters of reviews based on similar topics of review The topics before and during COVID-19 are compared, and the significant difference in frequency and severity of similar topics are identified. RESULTS: We successfully scraped, filtered, processed, and identified health-related topics in both qualitative and quantitative approaches. The results demonstrated the similarity between topics before and during the COVID-19.

Keywords: natural language processing (NLP), topic modeling, mHealth, COVID-19, software engineering, telemedicine, health risks

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Authors: Milan Podlena, Stepan Hysek, Jiri Prochazka, Martin Bohm, Jan Bomba

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Corner joints are the weakest part of windows, where the members are connected together. Since the dimensions of the windows started become bigger, the strength requirements for corner joints started to increase as well. Therefore, the aim of this study was to test the samples of corner joints of wooden windows. Moisture content of test specimens was stabilized in the climate chamber. After conditioning, test specimens were loaded in the laboratory conditions onto an universal testing machine and the failure load was measured. Data was recalculated by using goniometric, bending moment and stiffness equation to the stiffness coefficients and the bending moments were investigated. The results showed difference that was observed for the mortise with tenon joint and the dowel joint. This difference was explained by a varied adhesive bond area, which is related to the dimensions of dowels (diameter and length) as well. The bending moments and stiffness ware (except of type of corner joint) also affected by type of used adhesive, type of dowels and wood species.

Keywords: corner joint, wooden window, bending moment, stiffness

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Authors: Samar Alharbi, Yota Dimitriadi

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With the exponential growth of information and communication technologies in higher education, new online teaching strategies have become increasingly important for student engagement and learning. In particular, some institutions depend solely on asynchronous e-learning to provide courses for their students. The major challenge facing these institutions is how to improve the quality of teaching and learning in their asynchronous tools. One of the most important methods that can help e-learner to enhance their social learning and social presence in asynchronous learning setting is immediacy. This study explores tutors perceptions of their instructional immediacy practices as part of their communication actions in online learning environments. It was used a mixed-methods design under the umbrella of pragmatic philosophical assumption. The participants included tutors at an educational institution in a Saudi university. The participants were selected with a purposive sampling approach and chose an institution that offered fully online courses to students. The findings of the quantitative data show the importance of teachers’ immediacy practices in an online text-based learning environment. The qualitative data contained three main themes: the tutors’ encouragement of student interaction; their promotion of class participation; and their addressing of the needs of the students. The findings from these mixed methods can provide teachers with insights into instructional designs and strategies that they can adopt in order to use e-immediacy in effective ways, thus improving their students’ online learning experiences.

Keywords: asynchronous e-learning, higher education, immediacy, tutor

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Authors: Shohreh Ghasemi

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Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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Authors: Sahar Elsaleh, Ghada Farhat, Shaikha Al-Derham, Fasih Alam

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Background: Cesarean section (CS) delivery is one of the major concerns both in developing and developed countries. The rate of CS deliveries are on the rise globally, and especially in Qatar. Many socio-economic, demographic, clinical and institutional factors play an important role for cesarean sections. This study aims to investigate factors affecting the prevalence of CS among women in Qatar using the UNICEF’s Multiple Indicator Cluster Survey (MICS) 2012 database. Methods: The study has focused on the women’s questionnaire of the MICS, which was successfully distributed to 5699 participants. Following study inclusion and exclusion criteria, a final sample of 761 women aged 19- 49 years who had at least one delivery of giving birth in their lifetime before the survey were included. A number of socio-economic, demographic, clinical and institutional factors, identified through literature review and available in the data, were considered for the analyses. Bivariate and multivariate logistic regression models, along with a multi-level modeling to investigate clustering effect, were undertaken to identify the factors that affect CS prevalence in Qatar. Results: From the bivariate analyses the study has shown that, a number of categorical factors are statistically significantly associated with the dependent variable (CS). When identifying the factors from a multivariate logistic regression, the study found that only three categorical factors -‘age of women’, ‘place at delivery’ and ‘baby weight’ appeared to be significantly affecting the CS among women in Qatar. Although the MICS dataset is based on a cluster survey, an exploratory multi-level analysis did not show any clustering effect, i.e. no significant variation in results at higher level (households), suggesting that all analyses at lower level (individual respondent) are valid without any significant bias in results. Conclusion: The study found a statistically significant association between the dependent variable (CS delivery) and age of women, frequency of TV watching, assistance at birth and place of birth. These results need to be interpreted cautiously; however, it can be used as evidence-base for further research on cesarean section delivery in Qatar.

Keywords: cesarean section, factors, multiple indicator cluster survey, MICS database, Qatar

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Authors: Khaled R. Khater

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The weight of the SPT hammer is standard (0.623kN). The locally manufacturer drilling rigs use hammers, sometimes deviating off the standard weight. This affects the field measured blow counts (Nf) consequentially, affecting most of correlations previously obtained, as they were obtained based on standard hammer weight. The literature presents energy corrections factor (η2) to be applied to the SPT total input energy. This research investigates the effect of the hammer weight variation, as a single parameter, on the field measured blow counts (Nf). The outcome is a correction factor (ηk), equation, and correction chart. They are recommended to adjust back the measured misleading (Nf) to the standard one as if the standard hammer is used. This correction is very important to be done in such cases where a non-standard hammer is being used because the bore logs in any geotechnical report should contain true and representative values (Nf), let alone the long records of correlations, already in hand. The study here-in is achieved by using laboratory physical model to simulate the SPT dripping hammer mechanism. It is designed to allow different hammer weights to be used. Also, it is manufactured to avoid and eliminate the energy loss sources. This produces a transmitted efficiency up to 100%.

Keywords: correction factors, hammer weight, physical model, standard penetration test

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Authors: Inigo Beckett

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In forensic investigations, it is often the case that the most potentially useful recorded evidence derives from coincidental imagery, recorded immediately before or during an incident, and that during the incident (e.g. a ‘failure’ or fire event), the evidence is changed or destroyed. To an image analysis expert involved in photogrammetric analysis for Civil or Criminal Proceedings, traditional computer vision methods involving calibrated cameras is often not appropriate because image metadata cannot be relied upon. This paper presents an approach for resolving this problem, considering in particular and by way of a case study, the angle of a simple ladder shown in a photograph. The UK Health and Safety Executive (HSE) guidance document published in 2014 (INDG455) advises that a leaning ladder should be erected at 75 degrees to the horizontal axis. Personal injury cases can arise in the construction industry because a ladder is too steep or too shallow. Ad-hoc photographs of such ladders in their incident position provide a basis for analysis of their angle. This paper presents a direct approach for ascertaining the position of the camera and the angle of the ladder simultaneously from the photograph(s) by way of a workflow that encompasses a novel application of projective geometry and matrix analysis. Mathematical analysis shows that for a given pixel ratio of directly measured collinear points (i.e. features that lie on the same line segment) from the 2D digital photograph with respect to a given viewing point, we can constrain the 3D camera position to a surface of a sphere in the scene. Depending on what we know about the ladder, we can enforce another independent constraint on the possible camera positions which enables us to constrain the possible positions even further. Experiments were conducted using synthetic and real-world data. The synthetic data modeled a vertical plane with a ladder on a horizontally flat plane resting against a vertical wall. The real-world data was captured using an Apple iPhone 13 Pro and 3D laser scan survey data whereby a ladder was placed in a known location and angle to the vertical axis. For each case, we calculated camera positions and the ladder angles using this method and cross-compared them against their respective ‘true’ values.

Keywords: image analysis, projective geometry, homography, photogrammetry, ladders, Forensics, Mathematical modeling, planar geometry, matrix analysis, collinear, cameras, photographs

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Authors: Nouri Sabrina

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Numerical parametric study is conducted to study the effects of ampoule rotation on the flows and the dopant segregation in Vertical Bridgman (VB) crystal growth. Calculations were performed in unsteady state. The extended darcy model, whıch includes the time derivative and coriolis terms, has been employed in the momentum equation. It is found that the convection, and dopant segregation can be affected significantly by ampoule rotation, and the effect is similar to that by an axial magnetıc field. Ampoule rotation decreases the intensity of convection and stretches the flow cell axıally. When the convectıon is weak, the flow can be suppressed almost completely by moderate ampoule rotation and the dopant segregation becomes diffusion-controlled. For stronger convection, the elongated flow cell by ampoule rotation may bring dopant mixing into the bulk melt reducing axial segregation at the early stage of the growth. However, if the cellular flow cannot be suppressed completely, ampoule rotation may induce larger radial segregation due to poor mixing.

Keywords: rotating vertical solidification, Finite Volume Method, heat and mass transfer, porous medium, phase change

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Authors: V. Yu. Shungin, A. V. Popov

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At present, one of the main tasks of Russian shipbuilding yards is implementation of new technologies and replacement of main process equipment. In particular, conventional bending technologies with dies are being replaced with resource-saving methods of rotation (roller) banding. Such rolling bending is performed by multiple rolling of a plat in special bending rollers. Studies, conducted in JSC SSTC, allowed developing a theory of rotation bending, methods for calculation of process parameters, requirements to roller presses and bending accessories. This technology allows replacing old and expensive presses with new cheaper roller ones, having less power consumption and bending force. At first, roller presses were implemented in ship repair, however now they are widely employed at major shipbuilding yards. JSC SSTC develops bending technology and carries out design, manufacturing and delivery of roller presses.

Keywords: bending/straightening machines, rotational bending, ship hull structures, multifunctional bending

Procedia PDF Downloads 558

Authors: Mohammed Abaoli Abafogi, Sinem Satiroglu, M. Misir

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The current study has addressed the effect of Hazelnut (Corylus avellana) agroforestry on carbon sequestration. Eight sample plots were collected from Hazelnut (Corylus avellana) agroforestry using random sampling method. The diameter of all trees in each plot with ≥ 2cm at 1.3m DBH was measured by using a calliper. Average diameter, aboveground biomass, and carbon stock were calculated for each plot. Comparative data for natural forestland was used for C was taken from KTU, and the soil C was converted from the biomass conversion equation. Biomass carbon was significantly higher in the Natural forest (68.02Mgha⁻¹) than in the Hazelnut agroforestry (16.89Mgha⁻¹). SOC in Hazelnut agroforestry, Natural forest, and arable agricultural land were 7.70, 385.85, and 0.00 Mgha⁻¹ respectively. Biomass C, on average accounts for only 0.00% of the total C in arable agriculture, and 11.02% for the Hazelnut agroforestry while 88.05% for Natural forest. The result shows that the conversion of arable crop field to Hazelnut agroforestry can sequester a large amount of C in the soil as well as in the biomass than Arable agricultural lands.

Keywords: arable agriculture, biomass carbon, carbon sequestration, hazelnut (Corylus avellana) agroforestry, soil organic carbon

Procedia PDF Downloads 290

Authors: Azad Hussain, Shoaib Ali, M. Y. Malik, Saba Nazir, Sarmad Jamal

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This article reports a fundamental numerical investigation to analyze the impact of thermal radiations on MHD flow of differential type nanofluid past a porous plate. Here, viscosity is taken as function of temperature. Energy equation is deliberated in the existence of viscous dissipation. The mathematical terminologies of nano concentration, velocity and temperature are first cast into dimensionless expressions via suitable conversions and then solved by using Shooting technique to obtain the numerical solutions. Graphs has been plotted to check the convergence of constructed solutions. At the end, the influence of effective parameters on nanoparticle concentration, velocity and temperature fields are also deliberated in a comprehensive way. Moreover, the physical measures of engineering importance such as the Sherwood number, Skin friction and Nusselt number are also calculated. It is perceived that the thermal radiation enhances the temperature for both Vogel's and Reynolds' models but the normal stress parameter causes a reduction in temperature profile.

Keywords: MHD flow, differential type nanofluid, Porous medium, variable viscosity, thermal radiation

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Authors: O. Alaa, D. Ahmed, R. Baher, K. Matjaz

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This paper provides a study of the factors influencing the purchasing of low emission vehicles. In order to achieve the objectives of the paper, and in the light of the pool of literature and availability of data, the authors relied on qualitative methods to offers a comparison between Egypt as a developing country and Slovenia as a developed country, through analysing a survey that involves an Egyptian sample and Slovenian samples, it also studies the effect of different push and pull methods on different buyers in order to help the governments as well as the manufacturers to understand the most significant factors that affect the purchasing behaviour of LEV in the future. The results of this paper show the important vehicle performance factors, financial considerations, and environmental considerations along with the gender and age of the consumer show that consumers are more interested in the total price of the car than in different taxes.

Keywords: low emission vehicles, purchasing behavior, developed countries, developing countries

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Authors: Abbas Ahmadi, Bijan Raie, Mohammad Reza Neyshabouri, Mohammad Ali Ghorbani, Farrokh Asadzadeh

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In recent years, vast areas of Urmia Lake in Dasht-e-Tabriz has dried up leading to saline sediments exposure on the surface lake coastal areas being highly susceptible to wind erosion. This study was conducted to investigate wind erosion and its relevance to soil physicochemical properties and also modeling of wind erodibility (WE) using artificial intelligence techniques. For this purpose, 96 soil samples were collected from 0-5 cm depth in 414000 hectares using stratified random sampling method. To measure the WE, all samples (<8 mm) were exposed to 5 different wind velocities (9.5, 11, 12.5, 14.1 and 15 m s-1 at the height of 20 cm) in wind tunnel and its relationship with soil physicochemical properties was evaluated. According to the results, WE varied within the range of 76.69-9.98 (g m-2 min-1)/(m s-1) with a mean of 10.21 and coefficient of variation of 94.5% showing a relatively high variation in the studied area. WE was significantly (P<0.01) affected by soil physical properties, including mean weight diameter, erodible fraction (secondary particles smaller than 0.85 mm) and percentage of the secondary particle size classes 2-4.75, 1.7-2 and 0.1-0.25 mm. Results showed that the mean weight diameter, erodible fraction and percentage of size class 0.1-0.25 mm demonstrated stronger relationship with WE (coefficients of determination were 0.69, 0.67 and 0.68, respectively). This study also compared efficiency of multiple linear regression (MLR), gene expression programming (GEP), artificial neural network (MLP), artificial neural network based on genetic algorithm (MLP-GA) and artificial neural network based on whale optimization algorithm (MLP-WOA) in predicting of soil wind erodibility in Dasht-e-Tabriz. Among 32 measured soil variable, percentages of fine sand, size classes of 1.7-2.0 and 0.1-0.25 mm (secondary particles) and organic carbon were selected as the model inputs by step-wise regression. Findings showed MLP-WOA as the most powerful artificial intelligence techniques (R2=0.87, NSE=0.87, ME=0.11 and RMSE=2.9) to predict soil wind erodibility in the study area; followed by MLP-GA, MLP, GEP and MLR and the difference between these methods were significant according to the MGN test. Based on the above finding MLP-WOA may be used as a promising method to predict soil wind erodibility in the study area.

Keywords: wind erosion, erodible fraction, gene expression programming, artificial neural network

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Authors: Linghua Kong, Xinxia Chen, Mika Gissler, Catharina Lavebratt

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Background: Prenatal exposure to preeclampsia has been associated with an increased risk of offspring attention-deficit/hyperactivity disorders (ADHD), autism spectrum disorder (ASD), and intellectual disability. However, little is known about the association between prenatal exposure to severe preeclampsia and neurodevelopmental and psychiatric disorders in offspring. Objective: This study aimed to assess the risk of maternal preeclampsia combined with perinatal problems, specifically low birth weight and prematurity, on offspring neuropsychiatric disorders. Methods: All singleton live births in Finland between 1996 and 2014 (n=1 012 723) were followed up in nation-wide registries until 2018. Main exposures included pre-eclampsia, small for gestational age, and delivery before 34 gestational weeks. Offspring neurodevelopmental and psychiatric disorders (ICD-10 codes) were examined as outcomes variables. Offspring birth year, sex, maternal age at delivery, parity, marital status at birth, mother's country of birth, maternal smoking, maternal gestational diabetes, maternal use of psychotropic medication during pregnancy, and maternal systemic inflammatory diseases were used as covariates. Risks for neurodevelopmental and psychiatric disorders were estimated using Cox proportional hazards modeling. Results: Of the 1 012 723 offspring, 25 901 (2.6%) were exposed to preeclampsia, and 93 281 (9.2%) were diagnosed with a neuropsychiatric disorder. Compared to births unexposed to preeclampsia, small for gestational age or delivery before 34 gestational weeks, those exposed to preeclampsia only had a 21% increase in the likelihood of any neuropsychiatric disorders after adjusting for potential confounding (adjusted HR=1.21, 95% CI: 1.15-1.26), while exposure to preeclampsia combined with small for gestational age or delivery before 34 gestational weeks had a more than twofold increased risk of having a child with neuropsychiatric disorders (adjusted HR=2.16, 95% CI: 2.02-2.32). The adjusted HR for neuropsychiatric disorders in offspring with small for gestational age or delivery before 34 gestational weeks only was 1.79 (95% CI: 1.73-1.83). In addition, the risk estimate in offspring exposed to both preeclampsia and perinatal problems was greater than those only exposed to preeclampsia for having personality disorders (adjusted HR=1.66; 95% CI: 1.07-2.57), intellectual disabilities (adjusted HR=3.47; 95% CI: 2.86-4.22), specific developmental disorders (adjusted HR=2.91; 95% CI: 2.69-3.15), ASD (adjusted HR=1.75; 95% CI: 1.42-2.17), ADHD and conduct disorders (adjusted HR=2.00; 95%CI: 1.76-2.27), and other behavioral and emotional disorders (adjusted HR=2.09; 95% CI: 1.84-2.37). Conclusion: In utero exposure to severe preeclampsia increased the risk of several neurodevelopmental and psychiatric disorders in offspring. Our findings are relevant to women with hypertensive disorders with regard to pregnancy consultation and management and may yield effective clues for the prevention of neurodevelopmental and psychiatric disorders in childhood.

Keywords: low birth weight, neurodevelopmental disorders, preeclampsia, prematurity, psychiatric disorders

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Authors: Zainal Abidin Akasah, Maizam Alias, Azuin Ramli

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The safety and health performances aspects of a building are the most challenging aspect of facility management. It requires a deep understanding by the building managers on the factors that contribute to health and safety performances. This study attempted to develop an explanatory architectural safety performance model for stratified low-cost housing in Malaysia. The proposed Building Safety and Health Performance (BSHP) model was tested empirically through a survey on 308 construction practitioners using Partial Least Squares (PLS) and Structural Equation Modelling (SEM) tool. Statistical analysis results supports the conclusion that architecture, building services, external environment, management approaches and maintenance management have positive influence on safety and health performance of stratified low-cost housing in Malaysia. The findings provide valuable insights for construction industry to introduce BSHP model in the future where the model could be used as a guideline for training purposes of managers and better planning and implementation of building management.

Keywords: building management, stratified low-cost housing, safety, health model

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Authors: Varun Joshi, Manish K. Rathod

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The latent heat thermal energy storage system is a thrust area of research due to exuberant thermal energy storage potential. The thermal performance of PCM is significantly augmented by installation of the high thermal conductivity fins. The objective of the present study is to obtain optimum size and location of the fins to enhance diffusion heat transfer without altering overall melting time. Hence, the constructal theory is employed to eliminate, resize, and re-position the fins. A numerical code based on conjugate heat transfer coupled enthalpy porosity approached is developed to solve Navier-Stoke and energy equation.The numerical results show that the constructal fin design has enhanced the thermal performance along with the increase in the overall volume of PCM when compared to conventional. The overall volume of PCM is found to be increased by half of total of volume of fins. The elimination and repositioning the fins at high temperature gradient from low temperature gradient is found to be vital.

Keywords: constructal theory, enthalpy porosity approach, phase change materials, fins

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Authors: Tomoaki Hashimoto

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In recent decades, probabilistic constrained optimal control problems have attracted much attention in many research field. Although probabilistic constraints are generally intractable in an optimization problem, several tractable methods haven been proposed to handle probabilistic constraints. In most methods, probabilistic constraints are reduced to deterministic constraints that are tractable in an optimization problem. However, there is a gap between the transformed deterministic constraints in case of known and unknown probability distribution. This paper examines the conservativeness of probabilistic constrained optimization method with the unknown probability distribution. The objective of this paper is to provide a quantitative assessment of the conservatism for tractable constraints in probabilistic constrained optimization with the unknown probability distribution.

Keywords: optimal control, stochastic systems, discrete time systems, probabilistic constraints

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Authors: Yiming Jin, Ping Dong

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The primary resonance of a pipeline close to a plane boundary is investigated in this paper. Based on classic Van der Pol equation and added a nonlinear item, a new wake oscillator model is proposed to predict the vortex-induced vibration (VIV) of a circular cylinder close to a plane boundary. Then, with the multi-scale method, the approximate solution for the case of the primary resonance is obtained. Besides, to study the characteristic of the primary resonance, the effects of the mass ration, frequency, damp ratio and gap ratio on the frequency-response curves of the pipeline are analysed. On the whole, the trend of the numerical results match up with that of the experimental data well and the mass ration, frequency, damp ratio and gap ratio play an important role in the vortex-induced vibration (VIV) of a circular cylinder close to a plane boundary, especially, the smaller is the mass ratio, the larger impact the gap ratio has on the frequency-response curves of the primary resonance.

Keywords: primary resonance, gap ratio, vortex-induced vibration, multi-scale method

Procedia PDF Downloads 354