Search results for: statistical techniques

Authors: Orkide Donma, M. Metin Donma, Burcin Nalbantoglu, Birol Topcu, Feti Tulubas, Murat Aydin, Tuba Gokkus, Ahmet Gurel

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Increasing prevalence of childhood obesity has increased the interest in early and late indicators of gaining weight. Cell blood counts may be indicators of proinflammatory states. The aim was to evaluate associations of hematological parameters, including Hematocrit (HTC), hemoglobin, blood cell counts, and their indices with the degree of obesity in pediatric population. A total of 249; -139 morbidly obese (MO), 82 healthy Normal Weight (NW) and 28 Overweight (OW) children were included into the scope of the study. WHO BMI-for age percentiles were used to form age- and sex-matched groups. Informed consent forms and the Ethics Committee approval were obtained. Anthropometric measurements were performed. Hematological parameters were determined. Statistical analyses were performed using SPSS. The degree for statistical significance was p≤0.05. Significant differences (p=0.000) between waist-to-hip ratios and head-to-neck ratios (hnrs) of MO and NW children were detected. A significant difference between hnrs of OW and MO children (p=0.000) was observed. Red cell Distribution Width (RDW) was higher in OW children than NW group (p=0.030). Such finding couldn’t be detected between MO and NW groups. Increased RDW was prominent in OW children. The decrease in Mean Corpuscular Hemoglobin Concentration (MCHC) values in MO children was sharper than the values in OW children (p=0.006 vs p=0.042) compared to those in NW group. Statistically higher HTC levels were observed between MO-NW (p=0.014), but none between OW-NW. Though the cause-effect relationship between obesity and erythrocyte indices still needs further investigation, alterations in RDW, HTC, MCHC during obesity may be of significance in the early life.

Keywords: anthropometry, children, erythrocytes, obesity

Procedia PDF Downloads 334

Authors: Gus Salazar, Jeremy Bekker, Lauren Linford, Jared Warren

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Positive psychology practices allow for its principles to be applied to all people, regardless of their current level of functioning. To increase the dissemination of these practices, interventions are being adapted for use with digital technology, such as mobile apps. However, the research regarding positive psychology mobile app interventions is still in its infancy. In an effort to facilitate progress in this important area, we 1) conducted a qualitative review to summarize the current state of the positive psychology mobile app literature and 2) developed research-supported recommendations for positive psychology app development to maximize behavior change. In our literature review, we found that while positive psychology apps varied widely in content and purpose, there was a near-complete lack of research supporting their effectiveness. Most apps provided no rationale for the behavioral change techniques (BCTs) they employed in their app, and most did not develop their app with specific theoretical frameworks or design models in mind. Given this problem, we recommended four steps for effective positive psychology app design. First, developers must establish their app in a research-supported theory of change. Second, researchers must select appropriate behavioral change techniques which are consistent with their app’s goals. Third, researchers must leverage effective design principles. These steps will help mobile applications use data-driven methods for encouraging behavior change in their users. Lastly, we discuss directions for future research. In particular, researchers must investigate the effectiveness of various BCTs in positive psychology interventions. Although there is some research on this point, we do not yet clearly understand the mechanisms within the apps that lead to behavior change. Additionally, app developers must also provide data on the effectiveness of their mobile apps. As developers follow these steps for effective app development and as researchers continue to investigate what makes these apps most effective, we will provide millions of people in need with access to research-based mental health resources.

Keywords: behavioral change techniques, mobile app, mobile intervention, positive psychology

Procedia PDF Downloads 209

Authors: Samia Rabet, Rachida Chemini, Gerhard Schäfer, Farid Aiouache

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The textile industry generates large quantities of wastewater, which poses significant environmental problems due to its complex composition and high levels of pollutants loaded principally with heavy metals, large amounts of COD, and dye. Separation treatment methods are often known for their effectiveness in removing contaminants whereas membrane separation techniques are a promising process for the treatment of textile effluent due to their versatility, efficiency, and low energy requirements. This study focuses on the modeling and simulation of membrane separation technologies with a cross-flow filtration process for textile effluent treatment. It aims to explore the application of mathematical models and computational simulations using ASPEN Plus Software in the prediction of a complex and real effluent separation. The results demonstrate the effectiveness of modeling and simulation techniques in predicting pollutant removal efficiencies with a global deviation percentage of 1.83% between experimental and simulated results; membrane fouling behavior, and overall process performance (hydraulic resistance, membrane porosity) were also estimated and indicating that the membrane losses 10% of its efficiency after 40 min of working.

Keywords: membrane separation, ultrafiltration, textile effluent, modeling, simulation

Procedia PDF Downloads 41

Authors: Gregory Chown, Benjamin Infantolino, Christopher Wise, Rachel Holmes, Samantha O'Donnell, Katelyn Pfeiffer, Victoria Ward

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Background: There is a lack of understanding of how Kinesio Tape® physiologically works. Furthermore, few studies compare Kinesio Tape® to other forms of taping. The research question is: Does Kinesio Tape® cause a difference in muscle facilitation, inhibition, and pain, between Kinesio Tape® and no tape for collegiate athletes with self-reported shoulder pain? Method: This quantitative non-randomized design used a convenience sampling method. There were eleven participants with self-reported shoulder pain who were athletes on the men’s and women’s lacrosse and tennis teams. Participants attended one 30-45 minute session for data collection. Each participant received all three taping conditions and performed four repetitions of 120 degrees of active shoulder flexion for the three separate trials (no tape, Kinesio Tape® inhibition, and Kinesio Tape® facilitation). Surface electromyography (sEMG) electrodes were placed on the anterior deltoid, supraspinatus, and lower trapezius to measure muscle facilitation and inhibition. Each participant completed the visual analogue scale (VAS) before and after each trial to measure pain. Results: No statistical significance was found for pain scores on the VAS between the taping methods of facilitation, inhibition, and no tape (p = .118). No statistical significance was found for the percentage of change in muscle function for each taping method; Anterior deltoid (p = .993), supraspinatus (p = .997) and lower trapezius (p = .922). Conclusion: Based on the results, Kinesio Tape® appears to not have an effect on muscle function or pain when utilizing the facilitation or inhibition taping method when compared to no tape.

Keywords: Kinesio tape, muscle facilitation, muscle inhibition, pain

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Authors: Gopal Ji, Priyanka Dwivedi, Shanthi Sundaram, Rajiv Prakash

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Inhibition effect of aqueous Argemone Mexicana root extract (AMRE) on mild steel corrosion in 1 M HCl has been studied by weight loss, Tafel polarization curves, electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM) and atomic force microscopy (AFM) techniques. Results indicate that inhibition ability of AMRE increases with the increasing amount of the extract. A maximum corrosion inhibition of 94% is acknowledged at the extract concentration of 400 mg L-1. Polarization curves and impedance spectra reveal that both cathodic and anodic reactions are suppressed due to passive layer formation at metal-acid interface. It is also confirmed by SEM micro graphs and FTIR studies. Furthermore, the effects of acid concentration (1-5 M), immersion time (120 hours) and temperature (30-60˚C) on inhibition potential of AMRE have been investigated by weight loss method and electrochemical techniques. Adsorption mechanism is also proposed on the basis of weight loss results, which shows good agreement with Langmuir isotherm.

Keywords: mild steel, polarization, SEM, acid corrosion, EIS, green inhibition

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Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

Procedia PDF Downloads 95

Authors: Abdullah Özbilgin, Oguzhan Kahraman, Mustafa Selçuk Alataş

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Plant breeders have made and will continue to make important contributions toward meeting the need for more and better feed and food. The use of new techniques to modify the genetic makeup of plants to improve their properties has led to a new generation of crops, grains and their by-products for feed. Plant breeders have made and will continue to make important contributions toward meeting the need for more and better feed and food. The use of new techniques to modify the genetic makeup of plants to improve their properties has led to a new generation of crops, grains and their by-products for feed. The land area devoted to the cultivation of genetically modified (GM) plants has increased in recent years: in 2012 such plants were grown on over 170 million hectares globally, in 28 different countries, and are at resent used by 17.3 million farmers worldwide. The majority of GM plants are used as feed material for food-producing farm animals. Despite the facts that GM plants have been used as feed for years and a number of feeding studies have proved their safety for animals, they still give rise to emotional public discussion.

Keywords: crops, genetical modified plant(GM), plant, safety

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Authors: M. Timoracká, A. Vollmannová., D.S. Ismael, J. Musilová

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We investigated the effect of targeted contaminated soil by Zn model conditions. The soil used in the pot trial was uncontaminated. Faba beans (cvs Saturn, Zobor) were harvested in milk ripeness. With increased doses applied into the soil the strong statistical relationship between soil Zn content and Zn amount in seeds of both of faba bean cultivars was confirmed. Despite the high Zn doses applied into the soil in model conditions, in all variants the determined Zn amount in faba bean cv. Saturn was just below the maximal allowed content in foodstuffs given by the legislative. In cv. Zobor the determined Zn content was higher than maximal allowed amount (by 2% and 12%, respectively). Faba bean cvs. Saturn and Zobor accumulated (in all variants higher than hygienic limits) high amounts of Pb and Cd. The contents of all other heavy metals were lower than hygienic limits. With increased Zn doses applied into the soil the total polyphenols contents as well as the total antioxidant capacity determined in seeds of both cultivars Saturn and Zobor were increased. The strong statistical relationship between soil Zn content and the total polyphenols contents as well as the total antioxidant capacity in seeds of faba bean cultivars was confirmed.

Keywords: antioxidant capacity, faba bean, polyphenols, zinc

Procedia PDF Downloads 379

Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Jing Yuan, Hongwei Yang

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This paper aims to understand U.S. middle school students’ mathematics achievements by examining relevant student and school-level predictors. Through a variance component analysis, the study first identifies evidence supporting the use of multilevel modeling. Then, a multilevel analysis is performed under Bayesian statistical inference where prior information is incorporated into the modeling process. During the analysis, independent variables are entered sequentially in the order of theoretical importance to create a hierarchy of models. By evaluating each model using Bayesian fit indices, a best-fit and most parsimonious model is selected where Bayesian statistical inference is performed for the purpose of result interpretation and discussion. The primary dataset for Bayesian modeling is derived from the Program for International Student Assessment (PISA) in 2012 with a secondary PISA dataset from 2003 analyzed under the traditional ordinary least squares method to provide the information needed to specify informative priors for a subset of the model parameters. The dependent variable is a composite measure of mathematics literacy, calculated from an exploratory factor analysis of all five PISA 2012 mathematics achievement plausible values for which multiple evidences are found supporting data unidimensionality. The independent variables include demographics variables and content-specific variables: mathematics efficacy, teacher-student ratio, proportion of girls in the school, etc. Finally, the entire analysis is performed using the MCMCpack and MCMCglmm packages in R.

Keywords: Bayesian multilevel modeling, mathematics education, PISA, multilevel

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Authors: Sher Muhammad, Mirza Muhammad Waqar

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It is necessary to monitor and identify mangroves types and spatial extent near coastal areas because it plays an important role in coastal ecosystem and environmental protection. This research aims at identifying and mapping mangroves types along Karachi coast ranging from 24.79 to 24.85 degree in latitude and 66.91 to 66.97 degree in longitude using hyperspectral remote sensing data and techniques. Image acquired during February, 2012 through Hyperion sensor have been used for this research. Image preprocessing includes geometric and radiometric correction followed by Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The output of MNF and PPI has been analyzed by visualizing it in n-dimensions for end-member extraction. Well-distributed clusters on the n-dimensional scatter plot have been selected with the region of interest (ROI) tool as end members. These end members have been used as an input for classification techniques applied to identify and map mangroves species including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF), and Spectral Information Diversion (SID). Only two types of mangroves namely Avicennia Marina (white mangroves) and Avicennia Germinans (black mangroves) have been observed throughout the study area.

Keywords: mangrove, hyperspectral, hyperion, SAM, SFF, SID

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Authors: S. Jeyarajan

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Concept of knowledge is discovered from conducted study for successive Competition in Sri Lankan Non-State Higher Educational Institutes. The Concept discovered out of collected Knowledge Management Practices from Emerald inside likewise reputed literatures and of Non-State Higher Educational sector. A test is conducted to reveal existences and its reason behind of these collected practices in Sri Lankan Non-State Higher Education Institutes. Further, unavailability of such study and uncertain on number of participants for data collection in the Sri Lankan context contributed selection of research method as qualitative method, which used attributes of Delphi Method to manage those likewise uncertainty. Data are collected under Dramaturgical Method, which contributes efficient usage of the Delphi method. Grounded theory is selected as data analysis techniques, which is conducted in intermixed discourse to manage different perspectives of data that are collected systematically through perspective and modified snowball sampling techniques. Data are then analysed using Grounded Theory Development Techniques in Intermix discourses to manage differences in Data. Consequently, Agreement in the results of Grounded theories and of finding in the Foreign Study is discovered in the analysis whereas present study conducted as Qualitative Research and The Foreign Study conducted as Quantitative Research. As such, the Present study widens the discovery in the Foreign Study. Further, having discovered reason behind of the existences, the Present result shows Concept for Knowledge from Sri Lankan Non-State sector to manage higher educational Institutes in successful manner.

Keywords: adherence of snowball sampling into perspective sampling, Delphi method in qualitative method, grounded theory development in intermix discourses of analysis, knowledge management for success of higher educational institutes

Procedia PDF Downloads 155

Authors: Eman Tadros

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Solution Focused Therapy sheds a positive light on a client’s problem(s) by instilling hope, focusing on the connection with the client, and describing the problem in a way to display change being possible. Solution focused therapists highlight clients’ positive strengths, reframe what clients say, do, or believe in a positive statement, action, or belief. Narrative Therapy focuses on the stories individuals tell about their past in which shape their current and future lives. Changing the language used aids clients in reevaluating their values and views of themselves, this then constructs a more positive way of thinking about their story. Both therapies are based on treating each client as an individual with a problem rather than that the individual is a problem and being able to give power back to the client. The purpose of these ideologies is to open a client to alternative understandings. This paper displays how clinicians can empower and identify their clients’ positive strengths and resiliency factors. Narrative and Solution-Focused Techniques will be integrated to instill positivity and empowerment in clients. Techniques such as deconstruction, collaboration, complimenting, miracle/exception/scaling questioning will be analyzed and modeled. Furthermore, bridging Solution Focused Therapy and Narrative Therapy gives a voice to unheard client(s).

Keywords: solution focused therapy, narrative therapy, empowerment, resilience

Procedia PDF Downloads 228

Authors: Samaneh Farokhirad, Fatemeh Ahmadpoor

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Biological membranes are constantly in contact with various filamentous soft nanostructures that either reside on their surface or are being transported between the cell and its environment. In particular, viral infections are determined by the interaction of viruses (such as filovirus) with cell membranes, membrane protein organization (such as cytoskeletal proteins and actin filament bundles) has been proposed to influence the mechanical properties of lipid membranes, and the adhesion of filamentous nanoparticles influence their delivery yield into target cells or tissues. The goal of this research is to integrate the rapidly increasing but still fragmented experimental observations on the adhesion and self-assembly of nanofilaments (including filoviruses, actin filaments, as well as natural and synthetic nanofilaments) on cell membranes into a general, rigorous, and unified knowledge framework. The global outbreak of the coronavirus disease in 2020, which has persisted for over three years, highlights the crucial role that nanofilamentbased delivery systems play in human health. This work will unravel the role of a unique property of all cell membranes, namely flexoelectricity, and the significance of nanofilaments’ flexibility in the adhesion and self-assembly of nanofilaments on cell membranes. This will be achieved utilizing a set of continuum mechanics, statistical mechanics, and molecular dynamics and Monte Carlo simulations. The findings will help address the societal needs to understand biophysical principles that govern the attachment of filoviruses and flexible nanofilaments onto the living cells and provide guidance on the development of nanofilament-based vaccines for a range of diseases, including infectious diseases and cancer.

Keywords: virus nanofilaments, cell mechanics, computational biophysics, statistical mechanics

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Authors: Emily Simango, T. Chitura

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Background: Bovine brucellosis is among the most neglected zoonotic diseases in developing countries, where it is endemic and a growing challenge to public health. The development of cost-effective control measures for the disease can only be affirmed by the knowledge of the disease epidemiology and the ability to define its risk profiles. The aim of the study was to document the trend of bovine brucellosis and the control measures adopted following reported cases during the period 2014 to 2019 in South Africa. Methods: Data on confirmed cases of bovine brucellosis was retrieved from the website of the World Organisation of Animal Health (WOAH). Data was analysed using the Statistical Package for Social Sciences (IBM SPSS, 2022) version 29.0. Descriptive analysis (frequencies and percentages) and the Analysis of variance (ANOVA) were utilized for statistical significance (p<0.05). Results: The data retrieved in our study revealed an overall average bovine brucellosis prevalence of 8.48. There were statistically significant differences in bovine brucellosis prevalence across the provinces for the years 2016 and 2019 (p≥0.05), with the Eastern Cape Province having the highest prevalence in both instances. Documented control measures for the disease were limited to killing and disposal of disease cases as well as vaccination of susceptible animals. Conclusion: Bovine brucellosis is real in South Africa, with the risk profiles differing across the provinces. Information on brucellosis control measures in South Africa, as reported to the WOAH, is not comprehensive.

Keywords: zoonotic, endemic, Eastern Cape province, vaccination

Procedia PDF Downloads 47

Authors: Zahid Ullah, Atlas Khan

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The rapid advancements in data collection, storage, and processing capabilities have led to an explosion of data in various domains. In this era of big data, mathematical sciences play a crucial role in uncovering valuable insights and driving informed decision-making through data analytics. The purpose of this abstract is to present the latest advances in mathematical sciences and their application in harnessing the power of data analytics. This abstract highlights the interdisciplinary nature of data analytics, showcasing how mathematics intersects with statistics, computer science, and other related fields to develop cutting-edge methodologies. It explores key mathematical techniques such as optimization, mathematical modeling, network analysis, and computational algorithms that underpin effective data analysis and interpretation. The abstract emphasizes the role of mathematical sciences in addressing real-world challenges across different sectors, including finance, healthcare, engineering, social sciences, and beyond. It showcases how mathematical models and statistical methods extract meaningful insights from complex datasets, facilitating evidence-based decision-making and driving innovation. Furthermore, the abstract emphasizes the importance of collaboration and knowledge exchange among researchers, practitioners, and industry professionals. It recognizes the value of interdisciplinary collaborations and the need to bridge the gap between academia and industry to ensure the practical application of mathematical advancements in data analytics. The abstract highlights the significance of ongoing research in mathematical sciences and its impact on data analytics. It emphasizes the need for continued exploration and innovation in mathematical methodologies to tackle emerging challenges in the era of big data and digital transformation. In summary, this abstract sheds light on the advances in mathematical sciences and their pivotal role in unveiling the power of data analytics. It calls for interdisciplinary collaboration, knowledge exchange, and ongoing research to further unlock the potential of mathematical methodologies in addressing complex problems and driving data-driven decision-making in various domains.

Keywords: mathematical sciences, data analytics, advances, unveiling

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: hybrid storage system, data mining, recurrent neural network, support vector machine

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Authors: Miky Lee, K. Kim, D. Lim, D. Cho

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This paper presents the planning, rationale for test specification derivation, sampling requirements, test facilities, and result analysis used to conduct lifetime expectancy endurance tests on power window switches (PWS) considering thermally induced mechanical stress under diurnal cyclic temperatures during normal operation (power cycling). The detail process of analysis and test results on the selected PWS set were discussed in this paper. A statistical approach to ‘life time expectancy’ was given to the measurement standards dealing with PWS lifetime determination through endurance tests. The approach choice, within the framework of the task, was explained. The present task was dedicated to voltage drop measurement to derive lifetime expectancy while others mostly consider contact or surface resistance. The measurements to perform and the main instruments to measure were fully described accordingly. The failure data from tests were analyzed to conclude lifetime expectancy through statistical method using Weibull cumulative distribution function. The first goal of this task is to develop realistic worst case lifetime endurance test specification because existing large number of switch test standards cannot induce degradation mechanism which makes the switches less reliable. 2nd goal is to assess quantitative reliability status of PWS currently manufactured based on test specification newly developed thru this project. The last and most important goal is to satisfy customer’ requirement regarding product reliability.

Keywords: power window switch, endurance test, Weibull function, reliability, degradation mechanism

Procedia PDF Downloads 220

Authors: Prathama Guha Chaudhuri, Arunima Datta, Ashis Mukhopadhyay

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Background: Visualization (guided imagery) is a set of techniques which induce relaxation and help people create positive mental images in order to reduce stress.It is relatively inexpensive and can even be practised by bed bound people. Studies have shown visualization to be an effective tool to improve cancer patients’ anxiety, depression and quality of life. The common images used with cancer patients in the developed world are those involving the individual’s body and its strengths. Since breast cancer patients in India are more family oriented and often their main concerns are the stigma of having cancer and subsequent isolation of their families, including their children, we figured that positive images involving acceptance and integration within family and society would be more effective for them. Method: Data was collected from 119 breast cancer patients on chemotherapy willing to undergo psychotherapy, with no history of past psychiatric illness. Their baseline stress, anxiety, depression and quality of life were assessed using validated tools. The participants were then randomly divided into three groups: a) those who received visualization therapy with standard imageries involving the body and its strengths (sVT), b) those who received visualization therapy using indigenous family oriented imageries (mVT) and c) a control group who received supportive therapy. There were six sessions spread over two months for each group. The psychological outcome variables were measured post intervention. Appropriate statistical analyses were done. Results:Both forms of visualization therapy were more effective than supportive therapy alone in reducing patients’ depression, anxiety and quality of life.Modified VT proved to be significantly more effective in improving patients’ anxiety and quality of life. Conclusion: Visualization is a valuable therapeutic option for reduction of psychological distress and improving quality of life of breast cancer patients.In order to be more effective, the images used need to be modified according to the sociocultural background and individual needs of the patients.

Keywords: breast cancer, visualization therapy, quality of life, anxiety, depression

Procedia PDF Downloads 247

Authors: Kouzi Katia

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This paper proposes a Direct Torque Control (DTC) algorithm of dual Stator Induction Motor (DSIM) drive using two approach intelligent techniques: Artificial Neural Network (ANN) approach replaces the switching table selector block of conventional DTC and Mamdani Fuzzy Logic controller (FLC) is used for stator resistance estimation. The fuzzy estimation method is based on an online stator resistance correction through the variations of stator current estimation error and its variation. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of suggested algorithm control is to reduce the hardware complexity of conventional selectors, to avoid the drive instability that may occur in certain situation and ensure the tracking of the actual of the stator resistance. The effectiveness of the technique and the improvement of the whole system performance are proved by results.

Keywords: artificial neural network, direct torque control, dual stator induction motor, fuzzy logic estimator, switching table

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Authors: Oliver Chunho Ma, Tszying Chang

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Background: Traditional Chinese Medicine (TCM) has been widely used in the treatment of eczema. However, there is currently a lack of comprehensive research on the overall effectiveness of TCM in treating eczema, particularly using the Eczema Area and Severity Index (EASI) score as an evaluation tool. Meta-analysis can integrate the results of multiple studies to provide more convincing evidence. Objective: To conduct a systematic review and meta-analysis based on the EASI score to evaluate the overall effectiveness of TCM in the treatment of eczema. Specifically, the study will review and analyze published clinical studies that investigate TCM treatments for eczema and use the EASI score as an outcome measure, comparing the differences in improving the severity of eczema between TCM and other treatment modalities, such as conventional Western medicine treatments. Methods: Relevant studies, including randomized controlled trials (RCTs) and non-randomized controlled trials, that involve TCM treatment for eczema and use the EASI score as an outcome measure will be searched in medical literature databases such as PubMed, CNKI, etc. Relevant data will be extracted from the selected studies, including study design, sample size, treatment methods, improvement in EASI score, etc. The methodological quality and risk of bias of the included studies will be assessed using appropriate evaluation tools (such as the Cochrane Handbook). The results of the selected studies will be statistically analyzed, including pooling effect sizes (such as standardized mean differences, relative risks, etc.), subgroup analysis (e.g., different TCM syndromes, different treatment modalities), and sensitivity analysis (e.g., excluding low-quality studies). Based on the results of the statistical analysis and quality assessment, the overall effectiveness of TCM in improving the severity of eczema will be interpreted. Expected outcomes: By integrating the results of multiple studies, we expect to provide more convincing evidence regarding the specific effects of TCM in improving the severity of eczema. Additionally, subgroup analysis and sensitivity analysis can further elucidate whether the effectiveness of TCM treatment is influenced by different factors. Besides, we will compare the results of the meta-analysis with the clinical data from our clinic. For both the clinical data and the meta-analysis results, we will perform descriptive statistics such as means, standard deviations, percentages, etc. and compare the differences between the two using statistical tests such as independent samples t-test or non-parametric tests to assess the statistical differences between them.

Keywords: Eczema, traditional Chinese medicine, EASI, systematic review, meta-analysis

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Authors: Sarah A. Goodchild, Rachel Gao, Philip N. Bartlett

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A novel detection approach using immobilized DNA probes labeled with Anthraquinone (AQ) as an electrochemically active reporter moiety has been successfully developed as a new, simple, reliable method for the detection of DNA. This method represents a step forward in DNA detection as it can discriminate between multiple nucleotide polymorphisms within target DNA strands without the need for any additional reagents, reporters or processes such as melting of DNA strands. The detection approach utilizes single-stranded DNA probes immobilized on gold surfaces labeled at the distal terminus with AQ. The effective immobilization has been monitored using techniques such as AC impedance and Raman spectroscopy. Simple voltammetry techniques (Differential Pulse Voltammetry, Cyclic Voltammetry) are then used to monitor the reduction potential of the AQ before and after the addition of complementary strand of target DNA. A reliable relationship between the shift in reduction potential and the number of base pair mismatch has been established and can be used to discriminate between DNA from highly related pathogenic organisms of clinical importance. This indicates that this approach may have great potential to be exploited within biosensor kits for detection and diagnosis of pathogenic organisms in Point of Care devices.

Keywords: Anthraquinone, discrimination, DNA detection, electrochemical biosensor

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Authors: Mohsen Sanayei, Jerzy Szpunar, Sami Penttilä

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Exposure of Nickel-based superalloys to high temperature and harsh environment such as Super-Critical Water (SCW) environment leads to the formation of oxide scales composed of multiple and complex phases that are difficult to differentiate with conventional analysis techniques. In this study, we used simultaneous Electron Backscatter Diffraction (EBSD) and Energy Dispersive X-ray Spectroscopy (EDS) to analyze the complex oxide scales formed on several Nickel-based Superalloys exposed to high temperature SCW. Multi-layered structures of Iron, Nickel, Chromium and Molybdenum oxides and spinels were clearly identified using the simultaneous EBSD-EDS analysis technique. Furthermore, the orientation relationship between the oxide scales and the substrate has been investigated.

Keywords: electron backscatter diffraction, energy dispersive x-ray spectroscopy, superalloy, super-critical water

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Oum Elkhir Mahmoudi, Nebiha Ben Haj Ali

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Micropaleontological, sedimentological and statistical studies were carried out on the late Paleocene-early Eocene succession of Sra Ouertaine and Dyr El Kef in Northern open phosphatic Basin of Tunisia. Based on the abundance and stratigraphic distribution of planktic foraminiferal species, five planktic zones have been recognized from the base to the top of the phosphatic layers. The El Acarinina sibaiyaensis Zone, the E2 Pseudohastigerina wilcoxensis Zone, the E3 Morozovella marginodentata Zone, the E4 Morozovella formosa Zones and the E5 Morozovella subbotinae Zone. The placement of Paleocene-Eocene boundary (PETM) is just below the base of the phosphatic interval. The ETM-2 event may be detectable in the analyzed biotic record of Sra Ouertaine. Based on benthic assemblages, abundances, cluster and multivariate statistical analyses, two biofacies were recognized for each section. The recognized ecozones are typical of warm and shallow water inner neritic setting (dominance of epifaunal fauna Anomalinoides, Dentalina and Cibicidoides associated with Frondicularia phosphatica, Trochamminoides globigeriniformis and Eponides elevatus). The paleoenvironment is eutrophic (presence of several bolivinitids and verneuilinids). For the Dyr El Kef section and P5 and E2 of Sra Ouertaine section, our records indicate that paleoenvironment is influenced by coastal upwelling without oxygen-deficiency, the paleodepth is estimated to be around 50 m. The paleoecosystem is diversified and balanced with a general tendency to stressed condition. While the upper part of Sra Ouertaine section is more eutrophic, influenced by coastal upwelling with oxygen-deficiency, the paleodepth is estimated to be less than 50 m and the ecosystem is unsettled.

Keywords: Tunisia, Sra ouertaine Dyr el kef, early Eocene, foraminifera, chronostratigraphy, paleoecology, paleoenvironment

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Authors: Seyfollah Fazlollahi, Ahmad Bayan Memar

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Background: A review of manpower planning includes a training analysis based on job descriptions and job specifications which looks carefully at training from the points of view of the company, its various departments and personnel. This may show weaknesses in some departments and as a result, training is needed for the staff. Purpose: The aim of this research is to investigate the effects of training on employee’s efficiency in different aspects of work. Methodology: This is a descriptive-survey study. Statistical population was 85 official employees of University of Qom, Iran. 70 of these individuals were selected on a statistical random sampling method using Morgan&Gorki table. The instrument used in this study was a questionnaire including 22 questions. Result: Findings in this study according to data analysis indicate that majority of respondents had positive attitude towards training programs, in the job or off the job. They believed that training programs promoted and enhanced their behavior positively which leads to high efficiency in their job. In fact, data support the main hypothesis that training has positive effects on job performance and efficiency. Conclusion: It is concluded from this study and other related researches that training (on the job and off the job) has positive and effective role in human development and labor as employee’s efficiency. Employees get acquainted with different tasks of a job. Group co-operation, creativity and innovation will be enforced. Training leads to job skills, increasing knowledge and information about a job. It also increases technical and conceptual human skills, which are important in an organization. We can also mention workers' increasing positive motivation toward their job, enforcement of coordinating moral, their good human relations and good contact with clients.

Keywords: training, work efficiency, employee, human relation, job satisfaction

Procedia PDF Downloads 184

Authors: M. I. Youssef, A. E. Emam, M. Abd Elghany

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This paper evaluates the bit error rate (BER) performance of MIMO-OFDM communication system. MIMO system uses multiple transmitting and receiving antennas with different coding techniques to either enhance the transmission diversity or spatial multiplexing gain. Utilizing alamouti algorithm were the same information transmitted over multiple antennas at different time intervals and then collected again at the receivers to minimize the probability of error, combat fading and thus improve the received signal to noise ratio. While utilizing V-BLAST algorithm, the transmitted signals are divided into different transmitting channels and transferred over the channel to be received by different receiving antennas to increase the transmitted data rate and achieve higher throughput. The paper provides a study of different diversity gain coding schemes and spatial multiplexing coding for MIMO systems. A comparison of various channels' estimation and equalization techniques are given. The simulation is implemented using MATLAB, and the results had shown the performance of transmission models under different channel environments.

Keywords: MIMO communication, BER, space codes, channels, alamouti, V-BLAST

Procedia PDF Downloads 163

Authors: Temitope Olumide Olugbade

Abstract:

Low resistance and delayed fracture to corrosion, especially in harsh environmental conditions, often limit the wide application of high-manganese (high-Mn) steels. To address this issue, the present work investigates the influence of microalloying on the corrosion properties of high-Mn steels. Microalloyed and base high-Mn steels were synthesized through an arc melting process under an argon atmosphere. To generate different microstructures, the temperature and duration were varied via thermal homogenization treatments. The electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization techniques were used to determine the corrosion properties in 0.6 M NaCl aqueous solution at room temperature. The relationship between the microstructures and corrosion properties was investigated via Scanning Kelvin Probe Microscopy (SKPFM), energy dispersive X-ray spectroscopy (EDX), and Scanning electron microscopy (SEM) techniques. The local corrosion properties were investigated via in situ atomic force spectroscopy (AFM), considering the homogenization treatments. The results indicate that microalloying is a successful technique for enhancing the corrosion behavior of high-Mn steels. Compared to other alloying elements, Vanadium has shown improvement in corrosion properties for both general and local corrosion in chloride environments.

Keywords: corrosion, high-manganese steel, homogenization, microalloying, vanadium

Procedia PDF Downloads 71

Authors: Abisuga Oluwayemisi Adebola, Kerri Akiwowo, Deon de Beer, Kobus Van Der Walt

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The convergence of additive manufacturing (AM) and traditional textile dyeing techniques has initiated innovative possibilities for improving the visual application and customization potential of 3D-printed polymer objects. Textile dyeing techniques have progressed to transform fabrics with vibrant colours and complex patterns over centuries. The layer-by-layer deposition characteristic of AM necessitates adaptations in dye application methods to ensure even colour penetration across complex surfaces. Compatibility between dye formulations and polymer matrices influences colour uptake and stability, demanding careful selection and testing of dyes for optimal results. This study investigates the development interaction between these areas, revealing the challenges and opportunities of applying textile dyeing methods to colour 3D-printed polymer materials. The method explores three innovative approaches to colour the 3D-printed polymer object: (a) Additive Manufacturing of a Prototype, (b) the traditional dyebath method, and (c) the contemporary digital sublimation technique. The results show that the layer lines inherent to AM interact with dyes differently and affect the visual outcome compared to traditional textile fibers. Skillful manipulation of textile dyeing methods and dye type used for this research reduced the appearance of these lines to achieve consistency and desirable colour outcomes. In conclusion, integrating textile dyeing techniques into colouring 3D-printed polymer materials connects historical craftsmanship with innovative manufacturing. Overcoming challenges of colour distribution, compatibility, and layer line management requires a holistic approach that blends the technical consistency of AM with the artistic sensitivity of textile dyeing. Hence, applying textile dyeing methods to 3D-printed polymers opens new dimensions of aesthetic and functional possibilities.

Keywords: polymer, 3D-printing, sublimation, textile, dyeing, additive manufacturing

Procedia PDF Downloads 55

Authors: H. Khanfari, M. Johari Fard

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Dealing with carbonate reservoirs can be mind-boggling for the reservoir engineers due to various digenetic processes that cause a variety of properties through the reservoir. A good estimation of the reservoir heterogeneity which is defined as the quality of variation in rock properties with location in a reservoir or formation, can better help modeling the reservoir and thus can offer better understanding of the behavior of that reservoir. Most of reservoirs are heterogeneous formations whose mineralogy, organic content, natural fractures, and other properties vary from place to place. Over years, reservoir engineers have tried to establish methods to describe the heterogeneity, because heterogeneity is important in modeling the reservoir flow and in well testing. Geological methods are used to describe the variations in the rock properties because of the similarities of environments in which different beds have deposited in. To illustrate the heterogeneity of a reservoir vertically, two methods are generally used in petroleum work: Dykstra-Parsons permeability variations (V) and Lorenz coefficient (L) that are reviewed briefly in this paper. The concept of Lorenz is based on statistics and has been used in petroleum from that point of view. In this paper, we correlated the statistical-based Lorenz method to a petroleum concept, i.e. Kozeny-Carman equation and derived the straight line plot of Lorenz graph for a homogeneous system. Finally, we applied the two methods on a heterogeneous field in South Iran and discussed each, separately, with numbers and figures. As expected, these methods show great departure from homogeneity. Therefore, for future investment, the reservoir needs to be treated carefully.

Keywords: carbonate reservoirs, heterogeneity, homogeneous system, Dykstra-Parsons permeability variations (V), Lorenz coefficient (L)

Procedia PDF Downloads 202