Search results for: time series fractal analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 40952

Search results for: time series fractal analysis

36422 Optimization of Ultrasound Assisted Extraction of Polysaccharides from Plant Waste Materials: Selected Model Material is Hazelnut Skin

Authors: T. Yılmaz, Ş. Tavman

Abstract:

In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

Procedia PDF Downloads 327
36421 Big Data Analysis with RHadoop

Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

Abstract:

It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

Procedia PDF Downloads 432
36420 Team Teaching, Students Perception, Challenges, and Remedies for Effective Implementation: A Case Study of the Department of Biology, Alvan Ikoku Federal College of Education, Owerri Imo State, Nigeria

Authors: Daniel Ihemtuge Akim, Micheal O. Ikeanumba

Abstract:

This research focused on team teaching; students perception, challenges, and remedies for effective implementation, a case study of the department of Biology, Alvan Ikoku Federal College of Education, Owerri Imo State, Nigeria. It seeks to address the misconception by students on the use of team teaching as a methodology for learning. Five purposes and five research questions guided this study. Descriptive survey design was used in the study. The students of biology department enrolled in both Bachelor degree and National Certificate in Education in Alvan Ikoku Federal College of Education, Owerri, formed the population size. Simple random sampling technique was used to select the sampled students and 20% of whole lecturers were selected out of the whole given sample size of three hundred and forty (340). The instrument used for data collection was structured 4 point Likert scale questionnaire and analysis was made using mean method. The result revealed that poor time management by lectures, lack of lecture venues, manpower are some of the challenges hindering the effective implementation of team teaching. It was also observed that students perform better in academic when team teaching approach is used than single teaching approach. Finally, recommendations made suggested that teachers involved in team teaching should work together with their teaching strategies and within the time frame to achieve the stated objectives.

Keywords: challenges, implementation, perception, team teaching

Procedia PDF Downloads 377
36419 Development of Standard Evaluation Technique for Car Carpet Floor

Authors: In-Sung Lee, Un-Hwan Park, Jun-Hyeok Heo, Tae-Hyeon Oh, Dae-Gyu Park

Abstract:

Statistical Energy Analysis is to be the most effective CAE Method for air-born noise analysis in the Automotive area. This study deals with a method to predict the noise level inside of the car under the steady-state condition using the SEA model of car for air-born noise analysis. We can identify weakened part due to the acoustic material properties using it. Therefore, it is useful for the material structural design.

Keywords: air-born noise, material structural design, acoustic material properties, absorbing

Procedia PDF Downloads 419
36418 Traffic Analysis and Prediction Using Closed-Circuit Television Systems

Authors: Aragorn Joaquin Pineda Dela Cruz

Abstract:

Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

Procedia PDF Downloads 101
36417 Legal Allocation of Risks: A Computational Analysis of Force Majeure Clauses

Authors: Farshad Ghodoosi

Abstract:

This article analyzes the effect of supervening events in contracts. Contracts serve an important function: allocation of risks. In spite of its importance, the case law and the doctrine are messy and inconsistent. This article provides a fresh look at excuse doctrines (i.e., force majeure, impracticability, impossibility, and frustration) with a focus on force majeure clauses. The article makes the following contributions: First, it furnishes a new conceptual and theoretical framework of excuse doctrines. By distilling the decisions, it shows that excuse doctrines rests on the triangle of control, foreseeability, and contract language. Second, it analyzes force majeure clauses used by S&P 500 companies to understand the stickiness and similarity of such clauses and the events they cover. Third, using computational and statistical tools, it analyzes US cases since 1810 in order to assess the weight given to the triangle of control, foreseeability, and contract language. It shows that the control factor plays an important role in force majeure analysis, while the contractual interpretation is the least important factor. The Article concludes that it is the standard for control -whether the supervening event is beyond the control of the party- that determines the outcome of cases in the force majeure context and not necessarily the contractual language. This article has important implications on COVID-19-related contractual cases. Unlike the prevailing narrative that it is the language of the force majeure clause that’s determinative, this article shows that the primarily focus of the inquiry will be on whether the effects of COVID-19 have been beyond the control of the promisee. Normatively, the Article suggests that the trifactor of control, foreseeability, and contractual language are not effective for allocation of legal risks in times of crises. It puts forward a novel approach to force majeure clauses whereby that the courts should instead focus on the degree to which parties have relied on (expected) performance, in particular during the time of crisis.

Keywords: contractual risks, force majeure clauses, foreseeability, control, contractual language, computational analysis

Procedia PDF Downloads 144
36416 Navigating Rapids And Collecting Medical Insights: A Data Collection Of Athletes Presenting To The Medical Team At The International Canoe Federation Canoe Slalom World Championships 2023

Authors: Grace Scaplehorn, Muhammad Adeel Akhtar, Jane Gibson

Abstract:

Background: Canoe Slalom entails the skilful navigation of a carbon composite canoe or kayak through a series of 18-25 hanging gates, strategically positioned along the course, either upstream or downstream, amidst currents of whitewater rapids in natural and man-made river settings. Athletes compete individually in timed trials, competing for the fastest course time, typically around 80 to 120 seconds. In the new discipline of Kayak Cross, descents of the course are initiated by groups of four athletes freefalling simultaneously from a starting platform situated 3m above the river. Kayak Cross athletes, in contrast to Canoe Slalom, can make physical contact with suspended gates without incurring time penalties and are required to perform a kayak roll half way down the course. The Canoe Slalom World Championships were held at Lee Valley Whitewater Centre, London, from 19th to 24th September 2023. The event comprised 299 international athletes competing for 10 World Championship titles in Canoe/Kayak Slalom events (Olympic Debut Munich 1972), and the new Kayak Cross discipline (Olympic Debut Paris 2024). The inaugural appearance of Kayak Cross at the World Championships occurred in 2017, in Pau, France. There is limited literature surrounding Kayak Cross and the incidence of athlete injuries compared to traditional Canoe Slalom, hence it was felt important to undertake this review to address the perception that the event is dangerous. Aim: The study aimed to quantify and collate data collected from athletes presenting to the event medical centre. Methods: Athletes’ details were collected at initial assessments from the start of the practice period (16th–18th September) and throughout the event. Demographics such as age, sex and nationality were recorded along with presenting complaints, treatment, medication administered and outcome. Specifically, injuries were then sub-classified into body regions. The data does not include athletes who sought medical attention from their own governing body’s medical team. Results: During the 8-day period, there were 11 individual presentations to the medical centre, 3.7% of the athlete population (n=299). The mean age was 23.9 years (n=7), 6 were male (n=10). The most common presentation was minor injury (n=9), with 6 being musculoskeletal and 3 comprising skin damage, followed by insect sting/allergy (n=1) and pain relief requests (n=1). Five presentations were event-related, all being musculoskeletal injuries; 2 shoulder/arm, 1 head/neck, 1 hand/wrist and 1 other (data was not recorded). Of these injuries, the only intervention was 2 cases of 400mg Ibuprofen, which was given to both shoulder/arm injuries. Four of the 11 presentations were pre-existing injuries, which had been exacerbated due to increased intensity of practice. Two patients were advised to return for review, with 100% compliance. There were no unplanned re-presentations, and no emergency transfers to secondary care. Both the Kayak Cross and Canoe Slalom competitions resulted in 1 new event-related athlete presentation each. Conclusion: The event resulted in a negligible incidence of presentations at the medical centre, for both Kayak Cross and Canoe Slalom. This data holds significance in informing risk assessments and medical protocols necessary for the organisation of canoe slalom events.

Keywords: canoe slalom, kayak cross, athlete injuries, event injuries

Procedia PDF Downloads 54
36415 Forecasting for Financial Stock Returns Using a Quantile Function Model

Authors: Yuzhi Cai

Abstract:

In this paper, we introduce a newly developed quantile function model that can be used for estimating conditional distributions of financial returns and for obtaining multi-step ahead out-of-sample predictive distributions of financial returns. Since we forecast the whole conditional distributions, any predictive quantity of interest about the future financial returns can be obtained simply as a by-product of the method. We also show an application of the model to the daily closing prices of Dow Jones Industrial Average (DJIA) series over the period from 2 January 2004 - 8 October 2010. We obtained the predictive distributions up to 15 days ahead for the DJIA returns, which were further compared with the actually observed returns and those predicted from an AR-GARCH model. The results show that the new model can capture the main features of financial returns and provide a better fitted model together with improved mean forecasts compared with conventional methods. We hope this talk will help audience to see that this new model has the potential to be very useful in practice.

Keywords: DJIA, financial returns, predictive distribution, quantile function model

Procedia PDF Downloads 362
36414 An Extensible Software Infrastructure for Computer Aided Custom Monitoring of Patients in Smart Homes

Authors: Ritwik Dutta, Marylin Wolf

Abstract:

This paper describes the trade-offs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The back-end consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Keywords: flask, Java, JavaScript, health monitoring, long-term care, Mongo, Python, smart home, software engineering, webserver

Procedia PDF Downloads 384
36413 Breeding Cotton for Annual Growth Habit: Remobilizing End-of-season Perennial Reserves for Increased Yield

Authors: Salman Naveed, Nitant Gandhi, Grant Billings, Zachary Jones, B. Todd Campbell, Michael Jones, Sachin Rustgi

Abstract:

Cotton (Gossypium spp.) is the primary source of natural fiber in the U.S. and a major crop in the Southeastern U.S. Despite constant efforts to increase the cotton fiber yield, the yield gain has stagnated. Therefore, we undertook a novel approach to improve the cotton fiber yield by altering its growth habit from perennial to annual. In this effort, we identified genotypes with high-expression alleles of five floral induction and meristem identity genes (FT, SOC1, FUL, LFY, and AP1) from an upland cotton mini-core collection and crossed them in various combinations to develop cotton lines with annual growth habit, optimal flowering time and enhanced productivity. To facilitate the characterization of genotypes with the desired combinations of stacked alleles, we identified markers associated with the gene expression traits via genome-wide association analysis using a 63K SNP Array (Hulse-Kemp et al. 2015 G3 5:1187). Over 14,500 SNPs showed polymorphism and were used for association analysis. A total of 396 markers showed association with expression traits. Out of these 396 markers, 159 mapped to genes, 50 to untranslated regions, and 187 to random genomic regions. Biased genomic distribution of associated markers was observed where more trait-associated markers mapped to the cotton D sub-genome. Many quantitative trait loci coincided at specific genomic regions. This observation has implications as these traits could be bred together. The analysis also allowed the identification of candidate regulators of the expression patterns of these floral induction and meristem identity genes whose functions will be validated via virus-induced gene silencing.

Keywords: cotton, GWAS, QTL, expression traits

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36412 Development and Validation of High-Performance Liquid Chromatography Method for the Determination and Pharmacokinetic Study of Linagliptin in Rat Plasma

Authors: Hoda Mahgoub, Abeer Hanafy

Abstract:

Linagliptin (LNG) belongs to dipeptidyl-peptidase-4 (DPP-4) inhibitor class. DPP-4 inhibitors represent a new therapeutic approach for the treatment of type 2 diabetes in adults. The aim of this work was to develop and validate an accurate and reproducible HPLC method for the determination of LNG with high sensitivity in rat plasma. The method involved separation of both LNG and pindolol (internal standard) at ambient temperature on a Zorbax Eclipse XDB C18 column and a mobile phase composed of 75% methanol: 25% formic acid 0.1% pH 4.1 at a flow rate of 1.0 mL.min-1. UV detection was performed at 254nm. The method was validated in compliance with ICH guidelines and found to be linear in the range of 5–1000ng.mL-1. The limit of quantification (LOQ) was found to be 5ng.mL-1 based on 100µL of plasma. The variations for intra- and inter-assay precision were less than 10%, and the accuracy values were ranged between 93.3% and 102.5%. The extraction recovery (R%) was more than 83%. The method involved a single extraction step of a very small plasma volume (100µL). The assay was successfully applied to an in-vivo pharmacokinetic study of LNG in rats that were administered a single oral dose of 10mg.kg-1 LNG. The maximum concentration (Cmax) was found to be 927.5 ± 23.9ng.mL-1. The area under the plasma concentration-time curve (AUC0-72) was 18285.02 ± 605.76h.ng.mL-1. In conclusion, the good accuracy and low LOQ of the bioanalytical HPLC method were suitable for monitoring the full pharmacokinetic profile of LNG in rats. The main advantages of the method were the sensitivity, small sample volume, single-step extraction procedure and the short time of analysis.

Keywords: HPLC, linagliptin, pharmacokinetic study, rat plasma

Procedia PDF Downloads 239
36411 Network Analysis and Sex Prediction based on a full Human Brain Connectome

Authors: Oleg Vlasovets, Fabian Schaipp, Christian L. Mueller

Abstract:

we conduct a network analysis and predict the sex of 1000 participants based on ”connectome” - pairwise Pearson’s correlation across 436 brain parcels. We solve the non-smooth convex optimization problem, known under the name of Graphical Lasso, where the solution includes a low-rank component. With this solution and machine learning model for a sex prediction, we explain the brain parcels-sex connectivity patterns.

Keywords: network analysis, neuroscience, machine learning, optimization

Procedia PDF Downloads 144
36410 Designing an Integrated Platform for Real-Time Recommendations Sharing among the Aged and People Living with Cancer

Authors: Adekunle O. Afolabi, Pekka Toivanen

Abstract:

The world is expected to experience growth in the number of ageing population, and this will bring about high cost of providing care for these valuable citizens. In addition, many of these live with chronic diseases that come with old age. Providing adequate care in the face of rising costs and dwindling personnel can be challenging. However, advances in technologies and emergence of the Internet of Things are providing a way to address these challenges while improving care giving. This study proposes the integration of recommendation systems into homecare to provide real-time recommendations for effective management of people receiving care at home and those living with chronic diseases. Using the simplified Training Logic Concept, stakeholders and requirements were identified. Specific requirements were gathered from people living with cancer. The solution designed has two components namely home and community, to enhance recommendations sharing for effective care giving. The community component of the design was implemented with the development of a mobile app called Recommendations Sharing Community for Aged and Chronically Ill People (ReSCAP). This component has illustrated the possibility of real-time recommendations, improved recommendations sharing among care receivers and between a physician and care receivers. Full implementation will increase access to health data for better care decision making.

Keywords: recommendation systems, Internet of Things, healthcare, homecare, real-time

Procedia PDF Downloads 151
36409 Reliability Modeling of Repairable Subsystems in Semiconductor Fabrication: A Virtual Age and General Repair Framework

Authors: Keshav Dubey, Swajeeth Panchangam, Arun Rajendran, Swarnim Gupta

Abstract:

In the semiconductor capital equipment industry, effective modeling of repairable system reliability is crucial for optimizing maintenance strategies and ensuring operational efficiency. However, repairable system reliability modeling using a renewal process is not as popular in the semiconductor equipment industry as it is in the locomotive and automotive industries. Utilization of this approach will help optimize maintenance practices. This paper presents a structured framework that leverages both parametric and non-parametric approaches to model the reliability of repairable subsystems based on operational data, maintenance schedules, and system-specific conditions. Data is organized at the equipment ID level, facilitating trend testing to uncover failure patterns and system degradation over time. For non-parametric modeling, the Mean Cumulative Function (Mean Cumulative Function) approach is applied, offering a flexible method to estimate the cumulative number of failures over time without assuming an underlying statistical distribution. This allows for empirical insights into subsystem failure behavior based on historical data. On the parametric side, virtual age modeling, along with Homogeneous and Non-Homogeneous Poisson Process (Homogeneous Poisson Process and Non-Homogeneous Poisson Process) models, is employed to quantify the effect of repairs and the aging process on subsystem reliability. These models allow for a more structured analysis by characterizing repair effectiveness and system wear-out trends over time. A comparison of various Generalized Renewal Process (GRP) approaches highlights their utility in modeling different repair effectiveness scenarios. These approaches provide a robust framework for assessing the impact of maintenance actions on system performance and reliability. By integrating both parametric and non-parametric methods, this framework offers a comprehensive toolset for reliability engineers to better understand equipment behavior, assess the effectiveness of maintenance activities, and make data-driven decisions that enhance system availability and operational performance in semiconductor fabrication facilities.

Keywords: reliability, maintainability, homegenous poission process, repairable system

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36408 Application of Dissolved Air Flotation for Removal of Oil from Wastewater

Authors: Talat Ghomashchi, Zahra Akbari, Shirin Malekpour, Marjan Alimirzaee

Abstract:

Mixing the waste water of industries with natural water has caused environmental pollution. So researcher try to obtain methods and optimum conditions for waste water treatment. One of important stage in waste water treatment is dissolved air flotation. DAF is used for the removal of suspended solids and oils from waste water. In this paper, the effect of several parameters on flotation efficiency with Cationic polyacrylamide as flocculant, was examined, namely, (a) concentration of cationic flocculants, (b) pH (c) fast mixing time, (d) fast mixing speed,(e) slow mixing time,(f) retention time and temperature. After design of experiment, in each trial turbidity of waste water was measured by spectrophotometer. Results show that contribution of pH and concentration of flocculant on flotation efficiency are 75% and 9% respectively. Cationic polyacrylamide led to a significant increase in the settling speed and effect of temperature is negligible. In the optimum condition, the outcome of the DAF unit is increased and amount of suspended solid and oil in waste water is decreased effectively.

Keywords: dissolved air flotation, oil industry, waste water, treatment

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36407 Electrochemical Synthesis and Morphostructural Study of the Cuprite Thin Film

Authors: M. El Hajji, A. Hallaoui, L. Bazzi, A. Benlhachemi, Lh. Bazzi, M. Hilali, O. Jbara, A. Tara, B. Bakiz

Abstract:

The cathodic electro deposition of the cuprite Cu2O by chrono potentiometry is performed on two types of electrodes "titanium and stainless steel", in a basic medium containing the precursor of copper. The plot produced vs SCE, shows the formation of a brown layer on the electrode surface. The chrono potentiometric recording made between - 0.2 and - 1 mA/cm2, has allowed us to have a deposit having different morphologies and structural orientation obtained as a function of the variation of many parameters. The morphology, the size of crystals, and the phase of the deposits produced were studied by conventional techniques of analysis of the solid, particularly the X-ray diffraction (XRD), scanning electron microscopy analysis (SEM) and quantitative chemical analysis (EDS). The results will be presented and discussed, they show that the majority of deposits are pure and uniform.

Keywords: cathodic electrodeposition, cuprite Cu2O, XRD, SEM, EDS analysis

Procedia PDF Downloads 416
36406 From CBGB to F21: The Ramone's Band T-Shirt and Its Representations in the Mainstream Culture

Authors: Cláudia Pereira, Lívia Boeschenstein

Abstract:

This article aims to present an analysis of rock band t-shirts as an element that claims a certain identity in modern-contemporary culture. This work focuses on the study of t-shirts that display the name, related elements and the logo of punk band The Ramones, because of its strong presence in the collective mind along the last decades. As we shall see, it is possible to observe a phenomenon of symbolic transition from the original cultural place of that object. At first, it was a piece of cloth that had been part of a specific subculture and then it became just a generic item diluted by the mainstream. This symbolic transitional phenomenon is significant in many ways and will be discussed furthermore. For the analysis, we begin with a brief introduction to the history of the band, followed by the study about the vintage rock band T-shirts and their meanings. From there, we will turn to a historical contextualization of band T-shirts as a subcultural item and to its redefinition after the appropriation made by the mainstream. To guide this reasoning, it will be used theories about the styles, subcultures and youth culture and about material culture from an anthropological perspective. In addition, we shall see the theories and concepts of social representations in order to understand the ways of using the Ramones’s T-shirt as a representative element of a fashionable style. This T-shirt, after being resignified by the standardization and the massive consumption, no longer symbolizes the punk movement, its behavioral motivations and original policies. Also has little to do with the rage the working class suburbs of London or New York. It seems to be a mute and vague sign of a restricted rebellion, foreseen and framed establishing a stylistic contrast to the designer clothes and good behavior predicted by establishment. It's an item that composes a specific style available on the market, but at the same time is accepted by the mainstream and provides a subcultural association that has some prestige in society. Another perspective is that of resignification loop. As the same way that punk resignified the conventional goods for their own social standards, fashion resignifies what was said to be an object of a subculture and absorbs in their own mass culture standards. Therefore, outsiders to the punk phenomenon wearing Ramones’s T-shirts can be perceived negatively by subcultural members, but at the same time are well received by those who are partially unaware or completely out of subcultural context. For the general public, the stamp of the Ramones’s logo happens to be appreciated as a diffuse allusion to a punk style, since its original meaning has being entirely neutralized.

Keywords: social representations, subcultures, material culture, punk

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36405 The Mask of Motherhood a Changing Identity During the Transition to Motherhood

Authors: Geraldine Mc Loughlin, Mary Horgan, Rosaleen Murphy

Abstract:

Childbirth is a life-changing event, a psychological transition for the mother that must be viewed in a social context. Much has been written and documented regarding the preparation for birth and the immediate postnatal period, but the full psychological impact on the mother is not clear. One aspect of the transition process is Identity. Depending on a person’s worldview, the concept of identity is viewed differently; the nature of reality and how they construct knowledge influence these perspectives. Becoming a mother is not just an event but a process that time and experience will help to shape the understanding of the woman. To explore the emotional and psychological aspects of first-time mother’s experience during the transition to new motherhood. To identify factors affecting women’s identities in the period of 36 weeks gestation to 12 weeks postpartum. Interpretative Phenomenological Analysis (IPA) was used. It explores how these women make sense of and give meaning to their experiences. IPA is underpinned by 3 key principles: phenomenology, hermeneutics and idiographics. A purposeful sample of 10 women was recruited for this longitudinal study, to enable data to be collected during the transition to motherhood. Individual identity was interpreted and viewed as developing in response to changing contexts, such as the birth event becoming a parent, enabling one to construct one’s own sense of a meaningful life. Women effectively differentiated themselves from their personal and social identities and took responsibility for their actions. Identity is culturally and socially shaped and experienced, though not experienced similarly by all women. The individualized perspective on identity recognizes that (a) social influences are seen as external to the individual and (b) the view that social influences are, in fact, internalized by the individual.

Keywords: motherhood, transition, identity, IPA

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36404 The Influence of Beta Shape Parameters in Project Planning

Authors: Αlexios Kotsakis, Stefanos Katsavounis, Dimitra Alexiou

Abstract:

Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.

Keywords: beta distribution, PERT, Monte Carlo simulation, skewness, project completion time distribution

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36403 Applying (1, T) Ordering Policy in a Multi-Vendor-Single-Buyer Inventory System with Lost Sales and Poisson Demand

Authors: Adel Nikfarjam, Hamed Tayebi, Sadoullah Ebrahimnejad

Abstract:

This paper considers a two-echelon inventory system with a number of warehouses and a single retailer. The retailer replenishes its required items from warehouses, and assembles them into a single final product. We assume that each warehouse supplies only one kind of the raw material for the retailer. The demand process of the final product is assumed to be Poissson, and unsatisfied demand of the final product will be lost. The retailer applies one-for-one-period ordering policy which is also known as (1, T) ordering policy. In this policy the retailer orders to each warehouse a fixed quantity of each item at fixed time intervals, which the fixed quantity is equal to the utilization of the item in the final product. Since, this policy eliminates all demand uncertainties at the upstream echelon, the standard lot sizing model can be applied at all warehouses. In this paper, we calculate the total cost function of the inventory system. Then, based on this function, we present a procedure to obtain the optimal time interval between two consecutive order placements from retailer to the warehouses, and the optimal order quantities of warehouses (assuming that there are positive ordering costs at warehouses). Finally, we present some numerical examples, and conduct numerical sensitivity analysis for cost parameters.

Keywords: two-echelon supply chain, multi-vendor-single-buyer inventory system, lost sales, Poisson demand, one-for-one-period policy, lot sizing model

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36402 Iron Catalyst for Decomposition of Methane: Influence of Al/Si Ratio Support

Authors: A. S. Al-Fatesh, A. A. Ibrahim, A. M. AlSharekh, F. S. Alqahtani, S. O. Kasim, A. H. Fakeeha

Abstract:

Hydrogen is the expected future fuel since it produces energy without any pollution. It can be used as a fuel directly or through the fuel cell. It is also used in chemical and petrochemical industry as reducing agent or in hydrogenation processes. It is produced by different methods such as reforming of hydrocarbon, electrolytic method and methane decomposition. The objective of the present paper is to study the decomposition of methane reaction at 700°C and 800°C. The catalysts were prepared via impregnation method using 20%Fe and different proportions of combined alumina and silica support using the following ratios [100%, 90%, 80%, and 0% Al₂O₃/SiO₂]. The prepared catalysts were calcined and activated at 600 OC and 500 OC respectively. The reaction was carried out in fixed bed reactor at atmospheric pressure using 0.3g of catalyst and feed gas ratio of 1.5/1 CH₄/N₂ with a total flow rate 25 mL/min. Catalyst characterizations (TPR, TGA, BET, XRD, etc.) have been employed to study the behavior of catalysts before and after the reaction. Moreover, a brief description of the weight loss and the CH₄ conversions versus time on stream relating the different support ratios over 20%Fe/Al₂O₃/SiO₂ catalysts has been added as well. The results of TGA analysis provided higher weights losses for catalysts operated at 700°C than 800°C. For the 90% Al₂O₃/SiO₂, the activity decreases with the time on stream using 800°C reaction temperature from 73.9% initial CH₄ conversion to 46.3% for a period of 300min, whereas the activity for the same catalyst increases from 47.1% to 64.8% when 700°C reaction temperature is employed. Likewise, for 80% Al₂O₃/SiO₂ the trend of activity is similar to that of 90% Al₂O₃/SiO₂ but with a different rate of activity variation. It can be inferred from the activity results that the ratio of Al₂O₃ to SiO₂ is crucial and it is directly proportional with the activity. Whenever the Al/Si ratio decreases the activity declines. Indeed, the CH₄ conversion of 100% SiO₂ support was less than 5%.

Keywords: Al₂O₃, SiO₂, CH₄ decomposition, hydrogen, iron

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36401 A Kinetic Study on Recovery of High-Purity Rutile TiO₂ Nanoparticles from Titanium Slag Using Sulfuric Acid under Sonochemical Procedure

Authors: Alireza Bahramian

Abstract:

High-purity TiO₂ nanoparticles (NPs) with size ranging between 50 nm and 100 nm are synthesized from titanium slag through sulphate route under sonochemical procedure. The effect of dissolution parameters such as the sulfuric acid/slag weight ratio, caustic soda concentration, digestion temperature and time, and initial particle size of the dried slag on the extraction efficiency of TiO₂ and removal of iron are examined. By optimizing the digestion conditions, a rutile TiO₂ powder with surface area of 42 m²/g and mean pore diameter of 22.4 nm were prepared. A thermo-kinetic analysis showed that the digestion temperature has an important effect, while the acid/slag weight ratio and initial size of the slag has a moderate effect on the dissolution rate. The shrinking-core model including both chemical surface reaction and surface diffusion is used to describe the leaching process. A low value of activation energy, 38.12 kJ/mol, indicates the surface chemical reaction model is a rate-controlling step. The kinetic analysis suggested a first order reaction mechanism with respect to the acid concentrations.

Keywords: TiO₂ nanoparticles, titanium slag, dissolution rate, sonochemical method, thermo-kinetic study

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36400 Marine Propeller Cavitation Analysis Using BEM

Authors: Ehsan Yari

Abstract:

In this paper, a numerical study of sheet cavitation has been performed on DTMB4119 and E779A marine propellers with the boundary element method. In propeller design, various parameters of geometry and fluid are incorporated. So a program is needed to solve the flow taking the whole parameters changing into account. The capability of analyzing the wetted and cavitation flow around propellers in steady, unsteady, uniform, and non-uniform conditions while decreasing computational time compared to numerical finite volume methods with acceptable precision are the characteristic features of the present method. Moreover, modifying the position of the detachment point and its corresponding potential value has been considered. Numerical results have been validated with experimental data, showing a good conformation.

Keywords: cavitation, BEM, DTMB4119, E779A

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36399 Reinforced Concrete, Problems and Solutions: A Literature Review

Authors: Omar Alhamad, Waleed Eid

Abstract:

Reinforced concrete is a concrete lined with steel so that the materials work together in the resistance forces. Reinforcement rods or mesh are used for tensile, shear, and sometimes intense pressure in a concrete structure. Reinforced concrete is subject to many natural problems or industrial errors. The result of these problems is that it reduces the efficiency of the reinforced concrete or its usefulness. Some of these problems are cracks, earthquakes, high temperatures or fires, as well as corrosion of reinforced iron inside reinforced concrete. There are also factors of ancient buildings or monuments that require some techniques to preserve them. This research presents some general information about reinforced concrete, the pros and cons of reinforced concrete, and then presents a series of literary studies of some of the late published researches on the subject of reinforced concrete and how to preserve it, propose solutions or treatments for the treatment of reinforced concrete problems, raise efficiency and quality for a longer period. These studies have provided advanced and modern methods and techniques in the field of reinforced concrete.

Keywords: reinforced concrete, treatment, concrete, corrosion, seismic, cracks

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36398 Risk Allocation in Public-Private Partnership (PPP) Projects for Wastewater Treatment Plants

Authors: Samuel Capintero, Ole H. Petersen

Abstract:

This paper examines the utilization of public-private partnerships for the building and operation of wastewater treatment plants. Our research focuses on risk allocation in this kind of projects. Our analysis builds on more than hundred wastewater treatment plants built and operated through PPP projects in Aragon (Spain). The paper illustrates the consequences of an inadequate management of construction risk and an unsuitable transfer of demand risk in wastewater treatment plants. It also shows that the involvement of many public bodies at local, regional and national level further increases the complexity of this kind of projects and make time delays more likely.

Keywords: wastewater, treatment plants, PPP, construction

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36397 Modeling the Impact of Time Pressure on Activity-Travel Rescheduling Heuristics

Authors: Jingsi Li, Neil S. Ferguson

Abstract:

Time pressure could have an influence on the productivity, quality of decision making, and the efficiency of problem-solving. This has been mostly stemmed from cognitive research or psychological literature. However, a salient scarce discussion has been held for transport adjacent fields. It is conceivable that in many activity-travel contexts, time pressure is a potentially important factor since an excessive amount of decision time may incur the risk of late arrival to the next activity. The activity-travel rescheduling behavior is commonly explained by costs and benefits of factors such as activity engagements, personal intentions, social requirements, etc. This paper hypothesizes that an additional factor of perceived time pressure could affect travelers’ rescheduling behavior, thus leading to an impact on travel demand management. Time pressure may arise from different ways and is assumed here to be essentially incurred due to travelers planning their schedules without an expectation of unforeseen elements, e.g., transport disruption. In addition to a linear-additive utility-maximization model, the less computationally compensatory heuristic models are considered as an alternative to simulate travelers’ responses. The paper will contribute to travel behavior modeling research by investigating the following questions: how to measure the time pressure properly in an activity-travel day plan context? How do travelers reschedule their plans to cope with the time pressure? How would the importance of the activity affect travelers’ rescheduling behavior? What will the behavioral model be identified to describe the process of making activity-travel rescheduling decisions? How do these identified coping strategies affect the transport network? In this paper, a Mixed Heuristic Model (MHM) is employed to identify the presence of different choice heuristics through a latent class approach. The data about travelers’ activity-travel rescheduling behavior is collected via a web-based interactive survey where a fictitious scenario is created comprising multiple uncertain events on the activity or travel. The experiments are conducted in order to gain a real picture of activity-travel reschedule, considering the factor of time pressure. The identified behavioral models are then integrated into a multi-agent transport simulation model to investigate the effect of the rescheduling strategy on the transport network. The results show that an increased proportion of travelers use simpler, non-compensatory choice strategies instead of compensatory methods to cope with time pressure. Specifically, satisfying - one of the heuristic decision-making strategies - is adopted commonly since travelers tend to abandon the less important activities and keep the important ones. Furthermore, the importance of the activity is found to increase the weight of negative information when making trip-related decisions, especially route choices. When incorporating the identified non-compensatory decision-making heuristic models into the agent-based transport model, the simulation results imply that neglecting the effect of perceived time pressure may result in an inaccurate forecast of choice probability and overestimate the affectability to the policy changes.

Keywords: activity-travel rescheduling, decision making under uncertainty, mixed heuristic model, perceived time pressure, travel demand management

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36396 The Development of Statistical Analysis in Agriculture Experimental Design Using R

Authors: Somruay Apichatibutarapong, Chookiat Pudprommart

Abstract:

The purpose of this study was to develop of statistical analysis by using R programming via internet applied for agriculture experimental design. Data were collected from 65 items in completely randomized design, randomized block design, Latin square design, split plot design, factorial design and nested design. The quantitative approach was used to investigate the quality of learning media on statistical analysis by using R programming via Internet by six experts and the opinions of 100 students who interested in experimental design and applied statistics. It was revealed that the experts’ opinions were good in all contents except a usage of web board and the students’ opinions were good in overall and all items.

Keywords: experimental design, r programming, applied statistics, statistical analysis

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36395 Implementation of Correlation-Based Data Analysis as a Preliminary Stage for the Prediction of Geometric Dimensions Using Machine Learning in the Forming of Car Seat Rails

Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

Abstract:

When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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36394 Urban Health and Strategic City Planning: A Case from Greece

Authors: Alexandra P. Alexandropoulou, Andreas Fousteris, Eleni Didaskalou, Dimitrios A. Georgakellos

Abstract:

As urbanization is becoming a major stress factor not only for the urban environment but also for the wellbeing of city dwellers, incorporating the issues of urban health in strategic city planning and policy-making has never been more relevant. The impact of urbanization can vary from low to severe and relates to all non-communicable diseases caused by the different functions of cities. Air pollution, noise pollution, water and soil pollution, availability of open green spaces, and urban heat island are the major factors that can compromise citizens' health. Urban health describes the effects of the social environment, the physical environment, and the availability and accessibility to health and social services. To assess the quality of urban wellbeing, all urban characteristics that might have an effect on citizens' health must be considered, evaluated, and introduced in integrated local planning. A series of indices and indicators can be used to better describe these effects and set the target values in policy making. Local strategic planning is one of the most valuable development tools a local city administration can possess; thus, it has become mandatory under Greek law for all municipalities. It involves a two-stage procedure; the first aims to collect, analyse and evaluate data on the current situation of the city (administrative data, population data, environmental data, social data, swot analysis), while the second aims to introduce a policy vision described and supported by distinct (nevertheless integrated) actions, plans and measures to be implemented with the aim of city development and citizen wellbeing. In this procedure, the element of health is often neglected or under-evaluated. A relative survey was conducted among all Greek local authorities in order to shed light on the current situation. Evidence shows that the rate of incorporation of health in strategic planning is lacking behind. The survey also highlights key hindrances and concerns raised by local officials and suggests a path for the way forward.

Keywords: urban health, strategic planning, local authorities, integrated development

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36393 Ultrasonic Extraction of Phenolics from Leaves of Shallots and Peels of Potatoes for Biofortification of Cheese

Authors: Lila Boulekbache-Makhlouf, Fatiha Brahmi

Abstract:

This study was carried out with the aim of enriching fresh cheese with the food by-products, which are the leaves of shallots and the peels of potatoes. Firstly, the conditions for extracting the total polyphenols using ultrasound are optimized. Then, the contents of total polyphenols PPT , flavonoids and antioxidant activity were evaluated for the extracts obtained by adopting the optimal parameter. On the other hand, we have carried out some physicochemical, microbiological and sensory analyzes of the cheese produced. The maximum total polyphenols value of 70.44 mg GAE gallic acid equivalent / g of dry matter DM of shallot leaves was reached with 40% (v/v) ethanol, an extraction time of 90 min and a temperature of 10 °C. While, the maximum TPP total polyphenols content of potato peels of 45.03 ± 4.16 mg gallic acid equivalent / g of dry matter DM was obtained using an ethanol /water mixture (40%, v/v), a time of 30 min and a temperature of 60 °C and the flavonoid contents were 13.99 and 7.52 QE quercetin equivalent/g dry matter DM, respectively. From the antioxidant tests, we deduced that the potato peels present a higher antioxidant power with the concentration of extracts causing a 50% inhibition IC50s of 125.42 ± 2.78 μg/mL for 2,2-diphényl 1-picrylhydrazyle DPPH, of 87.21 ± 7.72 μg/mL for phosphomolybdate and 200.77 ± 13.38 μg/mL for iron chelation, compared with the results obtained for shallot leaves which were 204.29 ± 0.09, 45.85 ± 3,46 and 1004.10 ± 145.73 μg/mL, respectively. The results of the physicochemical analyzes have shown that the formulated cheese was compliant with standards. Microbiological analyzes show that the hygienic quality of the cheese produced was satisfactory. According to the sensory analysis, the experts liked the cheese enriched with the powder and pieces of the leaves of the shallots.

Keywords: shallots leaves, potato peels, ultrasound extraction, phenolics, cheese

Procedia PDF Downloads 85