Search results for: self-learning methods

Authors: Patricia B. Cruz, Catrina Jean G. Valenzuela, Analyn N. Yumang

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Nearly a hundred per million of the Filipino population is diagnosed with Chronic Kidney Disease (CKD). The early stage of CKD has no symptoms and can only be discovered once the patient undergoes urinalysis. Over the years, different methods were discovered and used for the quantification of the urinary albumin such as the immunochemical assays where most of these methods require large machinery that has a high cost in maintenance and resources, and a dipstick test which is yet to be proven and is still debated as a reliable method in detecting early stages of microalbuminuria. This research study involves the use of the liquid chromatography concept in microfluidic instruments with biosensor as a means of separation and detection respectively, and linear regression to quantify human urinary albumin. The researchers’ main objective was to create a miniature system that quantifies and detect patients’ urinary albumin while reducing the amount of volume used per five test samples. For this study, 30 urine samples of unknown albumin concentrations were tested using VITROS Analyzer and the microfluidic system for comparison. Based on the data shared by both methods, the actual vs. predicted regression were able to create a positive linear relationship with an R² of 0.9995 and a linear equation of y = 1.09x + 0.07, indicating that the predicted values and actual values are approximately equal. Furthermore, the microfluidic instrument uses 75% less in total volume – sample and reagents combined, compared to the VITROS Analyzer per five test samples.

Keywords: Chronic Kidney Disease, Linear Regression, Microfluidics, Urinary Albumin

Procedia PDF Downloads 118

Authors: Z. Bouattou, R. Laurini, H. Belbachir

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This paper describes a new approach for the automatic generation of the visual summaries dealing with cartographic visualization methods and sensors real time data modeling. Hence, the concept of chorems seems an interesting candidate to visualize real time geographic database summaries. Chorems have been defined by Roger Brunet (1980) as schematized visual representations of territories. However, the time information is not yet handled in existing chorematic map approaches, issue has been discussed in this paper. Our approach is based on spatial analysis by interpolating the values recorded at the same time, by sensors available, so we have a number of distributed observations on study areas and used spatial interpolation methods to find the concentration fields, from these fields and by using some spatial data mining procedures on the fly, it is possible to extract important patterns as geographic rules. Then, those patterns are visualized as chorems.

Keywords: geovisualization, spatial analytics, real-time, geographic data streams, sensors, chorems

Procedia PDF Downloads 382

Authors: P. Srinivas, P. V. N. Prasad

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Since torque ripple is the main cause of noise and vibrations, the performance of Switched Reluctance Motor (SRM) can be improved by minimizing its torque ripple using a novel control technique called Direct Torque Control (DTC). In DTC technique, torque is controlled directly through control of magnitude of the flux and change in speed of the stator flux vector. The flux and torque are maintained within set hysteresis bands. The DTC of SRM is analysed by two methods. In one of the methods, the actual torque is computed by conducting Finite Element Analysis (FEA) on the design specifications of the motor. In the other method, the torque is computed by Simplified Torque Equation. The variation of peak current, average current, torque ripple and speed settling time with Simplified Torque Equation model is compared with FEA based model.

Keywords: direct toque control, simplified torque equation, finite element analysis, torque ripple

Procedia PDF Downloads 460

Authors: Fulya Gokalp Yavuz, Mark Daniel Ward

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This study focuses on a contemporary and inevitable topic of Data Science and its exemplary application for early career building: Big Data and Leaving Learning Community (LLC). ‘Academia’ and ‘Industry’ have a common sense on the importance of Big Data. However, both of them are in a threat of missing the training on this interdisciplinary area. Some traditional teaching doctrines are far away being effective on Data Science. Practitioners needs some intuition and real-life examples how to apply new methods to data in size of terabytes. We simply explain the scope of Data Science training and exemplified its early stage application with LLC, which is a National Science Foundation (NSF) founded project under the supervision of Prof. Ward since 2014. Essentially, we aim to give some intuition for professors, researchers and practitioners to combine data science tools for comprehensive real-life examples with the guides of mentees’ feedback. As a result of discussing mentoring methods and computational challenges of Big Data, we intend to underline its potential with some more realization.

Keywords: Big Data, computation, mentoring, training

Procedia PDF Downloads 341

Authors: Bhuvnesh Narayanan, Bernhard Weiss, Tvrtko Mandic, Adrijan Baric

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This paper discusses a method to reconstruct internal high-frequency signals through subsampling techniques in an IC using an on-chip sensor. Though there are existing methods to internally probe and reconstruct high frequency signals through subsampling techniques; these methods have been applicable mainly for synchronized systems. This paper demonstrates a method for making such non-intrusive on-chip reconstructions possible also in non-synchronized systems. The TLP pulse is used to demonstrate the experimental validation of the concept. The on-chip sensor measures the voltage in an internal node. The jitter in the input pulse causes a varying pulse delay with respect to the on-chip sampling command. By measuring this pulse delay and by correlating it with the measured on-chip voltage, time domain waveforms can be reconstructed, and the influence of the pulse on the internal nodes can be better understood.

Keywords: on-chip sensor, jitter, transmission line pulse, subsampling

Procedia PDF Downloads 125

Authors: Samir Al-Zobaidi

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This study attempts to understand the effect of different UV irradiation methods on the intercalation of LDPE/MMT nanocomposites, and its molecular behavior at certain isothermal crystallization temperature. Three different methods of UV exposure were employed using single composition of LDPE/MMT nanocomposites. All samples were annealed for 5 hours at a crystallization temperature of 100°C. The crystallization temperature was chosen to be at large supercooling temperature to ensure quick and complete crystallization. The raw material of LDPE consisted of two stable monoclinic and orthorhombic phases according to XRD results. The thermal behavior of both phases acted differently when UV exposure method was changed. The monoclinic phase was more dependent on the method used compared to the orthorhombic phase. The intercalation of clay, as well as, the non-isothermal crystallization temperature, has also shown a clear dependency on the type of UV exposure. A third phase that is thermally less stable was also observed. Its respond to UV irradiation was greater since it contains low molecular weight entities which make it more vulnerable to any UV exposure.

Keywords: LDPE/MMt nanocomposites, crystallization, UV irradiation, intercalation

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Authors: Manar Aslan, Ayfer Karaaslan

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Purpose: The aim of this study was to determine the attitude towards the use of the maiden name of the Turkish people. Methods: For the study group who lives in the center of Konya/Turkey and people aged 16-65 years, as the sample identified 1,000 people with simple random between the months of February to May 2013. The survey created by the researchers, for investigating the perception of using the maiden name of the people of Konya consists of 25 questions with demographic characteristics. For statistical analysis of the obtained data made using SPSS 20, chi-square test and one-way analysis of variance methods of frequency, average, were evaluated as percentage distribution. Results: The traditional view of Konya increasing age increases, decreases the desire to use her maiden name. So look favorably than younger generations to use maiden name. In parallel with the level of educational levels are increasing utilization rates maiden name. Thus, individuals with higher levels of education are more positive look at the use of her maiden name. Looking at the marital status; compared to individuals with a single against the use of her maiden name of individuals who are married are more negative attitude.

Keywords: Maiden name, public viewpoint, utilization, women

Procedia PDF Downloads 277

Authors: Umi Pudji Astuti, Dedi Sugandi

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The effectiveness of agricultural extension is determined by the component in the agricultural extension system among others are agricultural extension methods. Effective methods should be selected and defined based on the characteristics of the target, the resources, the materials, and the objectives to be achieved. Citrus agribusiness development in Lebong is certainly supported by the role of stakeholders and citrus farmers, as well as the proper dissemination methods. Adoption in the extension process substantially can be interpreted as the changes of behavior process such as knowledge (cognitive), attitudes (affective), and skill (psycho-motoric) in a person after receiving "innovation" from extension submitted by target communities. Knowledge and perception are needed as a first step in adopting a innovation, especially of citrus agribusiness development in Lebong. The process of Specific technology adoption is influenced by internal factors and farmer perceptions of technological innovation. Internal factors such as formal education, experience trying to farm, owned land, production farm goods. The output of this study: 1) to analyze the effectiveness of field trial methods in improving cognitive and affective farmers; 2) Knowing the relationship of adoption level and knowledge of farmers; 3) to analyze the factors that influence farmers' adoption of citrus technology innovation. The method of this study is through the survey to 40 respondents in Rimbo Pengadang Sub District, Lebong District in 2014. Analyzing data is done by descriptive and statistical parametric (multiple linear functions). The results showed that: 1) Field trip method is effective to improve the farmer knowledge (23,17% ) and positively affect the farmer attitude; 2) the knowledge level of PTKJS innovation farmers "positively and very closely related".; 3) the factors that influence the level of farmers' adoption are internal factors (education, knowledge, and the intensity of training), and external factors respondents (distance from the house to the garden and from the house to production facilities shop).

Keywords: affect, adoption technology, citrus gerga, effectiveness dissemination

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Authors: Zenaide Carvalho da Silva, Leandro Rodrigues Ferreira, Andrey Ricardo Pimentel

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Learning styles (LS) refer to the ways and forms that the student prefers to learn in the teaching and learning process. Each student has their own way of receiving and processing information throughout the learning process. Therefore, knowing their LS is important to better understand their individual learning preferences, and also, understand why the use of some teaching methods and techniques give better results with some students, while others it does not. We believe that knowledge of these styles enables the possibility of making propositions for teaching; thus, reorganizing teaching methods and techniques in order to allow learning that is adapted to the individual needs of the student. Adapting learning would be possible through the creation of online educational resources adapted to the style of the student. In this context, this article presents the structure of a learning object interface adaptation based on the LS. The structure created should enable the creation of the adapted learning object according to the student's LS and contributes to the increase of student’s motivation in the use of a learning object as an educational resource.

Keywords: adaptation, interface, learning object, learning style

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Authors: Ainagul Yermekova, Liudmila Goncharenko, Ali Baghirzade, Sergey Sybachin

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In this article, we address the problem of Kazakhstan's transition to the Latin alphabet. The transition process started in 2017 and is scheduled to be completed in 2025. In connection with these events, the problem of recognizing the characters of the new alphabet is raised. Well-known character recognition programs such as ABBYY FineReader, FormReader, MyScript Stylus did not recognize specific Kazakh letters that were used in Cyrillic. The author tries to give an assessment of the well-known method of character recognition that could be in demand as part of the country's transition to the Latin alphabet. Three methods of character recognition: template, structured, and feature-based, are considered through the algorithms of operation. At the end of the article, a general conclusion is made about the possibility of applying a certain method to a particular recognition process: for example, in the process of population census, recognition of typographic text in Latin, or recognition of photos of car numbers, store signs, etc.

Keywords: text detection, template method, recognition algorithm, structured method, feature method

Procedia PDF Downloads 163

Authors: Akbar Gharbali, Ali Abbasian Ardekani, Afshin Mohammadi

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Introduction: Thyroid nodules have an incidence of 33-68% in the general population. More than 5-15% of these nodules are malignant. Early detection and treatment of thyroid nodules increase the cure rate and provide optimal treatment. Between the medical imaging methods, Ultrasound is the chosen imaging technique for assessment of thyroid nodules. The confirming of the diagnosis usually demands repeated fine-needle aspiration biopsy (FNAB). So, current management has morbidity and non-zero mortality. Objective: To explore diagnostic potential of automatic texture analysis (TA) methods in differentiation benign and malignant thyroid nodules by ultrasound imaging in order to help for reliable diagnosis and monitoring of the thyroid nodules in their early stages with no need biopsy. Material and Methods: The thyroid US image database consists of 70 patients (26 benign and 44 malignant) which were reported by Radiologist and proven by the biopsy. Two slices per patient were loaded in Mazda Software version 4.6 for automatic texture analysis. Regions of interests (ROIs) were defined within the abnormal part of the thyroid nodules ultrasound images. Gray levels within an ROI normalized according to three normalization schemes: N1: default or original gray levels, N2: +/- 3 Sigma or dynamic intensity limited to µ+/- 3σ, and N3: present intensity limited to 1% - 99%. Up to 270 multiscale texture features parameters per ROIs per each normalization schemes were computed from well-known statistical methods employed in Mazda software. From the statistical point of view, all calculated texture features parameters are not useful for texture analysis. So, the features based on maximum Fisher coefficient and the minimum probability of classification error and average correlation coefficients (POE+ACC) eliminated to 10 best and most effective features per normalization schemes. We analyze this feature under two standardization states (standard (S) and non-standard (NS)) with Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA). The 1NN classifier was performed to distinguish between benign and malignant tumors. The confusion matrix and Receiver operating characteristic (ROC) curve analysis were used for the formulation of more reliable criteria of the performance of employed texture analysis methods. Results: The results demonstrated the influence of the normalization schemes and reduction methods on the effectiveness of the obtained features as a descriptor on discrimination power and classification results. The selected subset features under 1%-99% normalization, POE+ACC reduction and NDA texture analysis yielded a high discrimination performance with the area under the ROC curve (Az) of 0.9722, in distinguishing Benign from Malignant Thyroid Nodules which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Conclusions: Our results indicate computer-aided diagnosis is a reliable method, and can provide useful information to help radiologists in the detection and classification of benign and malignant thyroid nodules.

Keywords: ultrasound imaging, thyroid nodules, computer aided diagnosis, texture analysis, PCA, LDA, NDA

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Authors: Leila Tabrizi, Farnaz Dezhaboun

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In order to study the effect of plant nutrient source and different drying methods on physical and phytochemical characteristics of pot marigold (Calendula officinalis L., Asteraceae) flowers, a factorial experiment was conducted based on completely randomized design with three replications in Research Laboratory of University of Tehran in 2010. Different nutrient sources (vermicompost, municipal waste compost, cattle manure, mushroom compost and control) which were applied in a field experiment for flower production and different drying methods including microwave (300, 600 and 900 W), oven (60, 70 and 80oC) and natural-shade drying in room temperature, were tested. Criteria such as drying kinetic, antioxidant activity, total flavonoid content, total phenolic compounds and total carotenoid of flowers were evaluated. Results indicated that organic inputs as nutrient source for flowers had no significant effects on quality criteria of pot marigold except of total flavonoid content, while drying methods significantly affected phytochemical criteria. Application of microwave 300, 600 and 900 W resulted in the highest amount of total flavonoid content, total phenolic compounds and antioxidant activity, respectively, while oven drying caused the lowest amount of phytochemical criteria. Also, interaction effect of nutrient source and drying method significantly affected antioxidant activity in which the highest amount of antioxidant activity was obtained in combination of vermicompost and microwave 900 W. In addition, application of vermicompost combined with oven drying at 60oC caused the lowest amount of antioxidant activity. Based on results of drying trend, microwave drying showed a faster drying rate than those oven and natural-shade drying in which by increasing microwave power and oven temperature, time of flower drying decreased whereas slope of moisture content reduction curve showed accelerated trend.

Keywords: drying kinetic, medicinal plant, organic fertilizer, phytochemical criteria

Procedia PDF Downloads 321

Authors: Johanna Renny Octavia, Meliana Nurdin, Ignatius Kevin Kurniawan, Ricca Aksara

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It is widely believed that usability evaluation is necessary to evaluate a website design for further improvement. Traditional methods of usability evaluation have given sufficient insights to reveal usability problems of websites. Eye-tracking analysis has been considered as a useful method that adds a powerful dimension to web usability evaluation. It allows web designers and usability researchers to understand exactly what users do and do not see on a web page, thus disclose more information on web usability and provide a more complete insights on a website design. This paper elaborates on moving beyond traditional methods of web usability evaluation by integrating eye-tracking analysis to enhance the evaluation of website design, and presents three case studies to support this approach. In these case studies, eye movement metrics such as gaze plots and fixation-derived metrics, and user performance data such as task completion times and number of errors were recorded as objective measurements that can inform the necessity for website design improvements.

Keywords: design, eye-tracking, usability evaluation, website

Procedia PDF Downloads 283

Authors: Rema Daher, Theodor Chakhachiro, Daniel Asmar

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In the era of autonomous robot mapping, assessing the goodness of the generated maps is important, and is usually performed by aligning them to ground truth. Map alignment is difficult for two reasons: first, the query maps can be significantly distorted from ground truth, and second, establishing what constitutes ground truth for different settings is challenging. Most map alignment techniques to this date have addressed the first problem, while paying too little importance to the second. In this paper, we propose a benchmark dataset, which consists of synthetically transformed maps with their corresponding displacement fields. Furthermore, we propose a new system for comparison, where the displacement field of any map alignment technique can be computed and compared to the ground truth using statistical measures. The local information in displacement fields renders the evaluation system applicable to any alignment technique, whether it is linear or not. In our experiments, the proposed method was applied to different alignment methods from the literature, allowing for a comparative assessment between them all.

Keywords: assessment methods, benchmark, image deformation, map alignment, robot mapping, robot motion

Procedia PDF Downloads 101

Authors: Darren Zou

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Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: BART, Bayesian, predict, stock

Procedia PDF Downloads 106

Authors: Haitham Magdy Hamad, Mohamed Ahmed Madkour

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The essential role of the digital library in developing museum display methods, recording ancient Egyptian antiquities, facilitating scientific research, and storing antiquities in the Grand Egyptian Museum, which helped and saved a lot of time and money spent to equip the Grand Egyptian Museum. The technology of digital libraries, linking it to ancient Egyptian antiquities and the latest results, which scientific research has reached in the field of libraries and its impact on many areas of tourism and antiquities. The research also aims to show the main role of the digital library and the Arab countries emulating European countries in digitizing libraries and recent developments in Egyptian libraries and their role in many areas of life and linking them to Egyptology. The research will also explain how the museum display methods will be developed in the Grand Egyptian Museum, and the recording of ancient Egyptian antiquities in order to facilitate the process of scientific research and methods of storing antiquities will also work to save time and effort for researchers. The research will also deal with lighting and its prominent role in the display in the interior design and coordination of the Grand Egyptian Museum, through which the unique artifacts and artifacts displayed can be displayed, and they can be used in a strong or simple form. Depending on the condition of the piece to be displayed. The research will also go to show the role of the digital library in how the Grand Egyptian Museum contains gathering areas and how to distribute spaces, guidance, information, reception, libraries, lecture halls, restaurants, cafeterias, shops, permanent and temporary galleries, and bathrooms.

Keywords: knowledge, library, culture, archaeology, grand Egyptian museum, numbering

Procedia PDF Downloads 60

Authors: Bhavatharani S., Boopathy V., Kavin S., Naveethkumar R.

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Context: Resistance training with blood flow restriction (BFR) has increased in clinical rehabilitation due to the substantial benefits observed in augmenting muscle mass and strength using low loads. However, there is a great variability of training pressures for clinical populations as well as methods to estimate it. The aim of this study was to estimate the percentage of maximal BFR that could result by applying different methodologies based on arbitrary or individual occlusion levels using a cuff width between 9 and 13 cm. Design: A secondary analysis was performed on the combined databases of 2 previous larger studies using BFR training. Methods: To estimate these percentages, the occlusion values needed to reach complete BFR (100% limb occlusion pressure [LOP]) were estimated by Doppler ultrasound. Seventy-five participants (age 24.32 [4.86] y; weight: 78.51 [14.74] kg; height: 1.77 [0.09] m) were enrolled in the laboratory study for measuring LOP in the thigh, arm, or calf. Results: When arbitrary values of restriction are applied, a supra-occlusive LOP between 120% and 190% LOP may result. Furthermore, the application of 130% resting brachial systolic blood pressure creates a similar occlusive stimulus as 100% LOP. Conclusions: Methods using 100 mm Hg and the resting brachial systolic blood pressure could represent the safest application prescriptions as they resulted in applied pressures between 60% and 80% LOP. One hundred thirty percent of the resting brachial systolic blood pressure could be used to indirectly estimate 100% LOP at cuff widths between 9 and 13 cm. Finally, methodologies that use standard values of 200 and, 300 mm Hg far exceed LOP and may carry additional risk during BFR exercise.

Keywords: lower limb rehabilitation, ESP32, pneumatics for medical, programmed rehabilitation

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Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

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Authors: Afia Naheed, Manmohan Singh, David Lucy

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This work is based on a mathematical as well as statistical study of an SEIJTR deterministic model for the interpretation of transmission of severe acute respiratory syndrome (SARS). Based on the SARS epidemic in 2003, the parameters are estimated using Runge-Kutta (Dormand-Prince pairs) and least squares methods. Possible graphical and numerical techniques are used to validate the estimates. Then effect of the model parameters on the dynamics of the disease is examined using sensitivity and uncertainty analysis. Sensitivity and uncertainty analytical techniques are used in order to analyze the affect of the uncertainty in the obtained parameter estimates and to determine which parameters have the largest impact on controlling the disease dynamics.

Keywords: infectious disease, severe acute respiratory syndrome (SARS), parameter estimation, sensitivity analysis, uncertainty analysis, Runge-Kutta methods, Levenberg-Marquardt method

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Authors: Abbas Moradi, Mohsen Safajoy, Reza Yazdanparast

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Analysis of blade-disc dovetail joints is one of the biggest challenges facing designers of aero-engines. To avoid comparatively expensive experimental full-scale tests, numerical methods can be used to simulate loaded disc-blades assembly. Mortar method provides a powerful and flexible tool for solving frictional contact problems. In this study, 2D frictional contact in dovetail has been analysed based on the mortar algorithm. In order to model the friction, the classical law of coulomb and moving friction cone algorithm is applied. The solution is then obtained by solving the resulting set of non-linear equations using an efficient numerical algorithm based on Newton–Raphson Method. The numerical results show that this approach has better convergence rate and accuracy than other proposed numerical methods.

Keywords: computational contact mechanics, dovetail joints, nonlinear FEM, mortar approach

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Authors: Adel Ahmadi Hosseini, Fatemeh Tavanaei, Alessandro Navarra, Ferri Hassani

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Mining engineering, as a part of geoscience, must address modern concerns. Traditional mining methods incorporate drill and blast technologies, which are followed by different issues, including excessive noise, vibration, air pollution, and safety hazards. Over the past two decades, mining engineers have sought alternative solutions to move from drill and blast to continuous methods to prevent such issues and improve sustainability in mining. Among the suggested methods, microwave treatment has shown promising results by creating micro/macro cracks in the rock structure prior to the operations. This research utilizes an energy-based analysis methodology to evaluate the efficiency of the microwave treatment in improving mining operations. The data analysis shows that increasing the input microwave energy dosage intensifies the rock damage. However, this approach can decrease the energy efficiency of the method by more than 50% in some cases. In this study, rock samples were treated with three power levels (3 kW, 7 kW, and 12 kW) and two energy dosages (20 kWh/t and 50 kWh/t), resulting in six conditions. To evaluate the impact of microwave treatment on the geomechanical behavior of the rocks, Unconfined Compressive Strength (UCS) tests were conducted on the microwave-treated samples, yielding stress-strain curves. Using the stress-strain curves, the effect of the different powers and energy dosages of microwaves are discussed. This research shows the potential of using microwave treatment to lead the industry to more sustainable mining.

Keywords: microwave treatment, microwave energy dosage, sustainable mining, rock fragmentation

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Authors: Kritin K. Verma, Brian L. Ransdell

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White patches are a symptom of vitiligo, a chronic autoimmune dermatological condition that causes a loss of pigmentation in the skin. Vitiligo can cause issues of self-esteem and quality of life while also progressing the development of other autoimmune diseases. Current treatments in allopathy and homeopathy exist; some treatments have been found to be toxic, whereas others have been helpful. Allopathy has seemed to offer several treatment plans, such as phototherapy, skin lightening preparations, immunosuppressive drugs, combined modality therapy, and steroid medications to improve vitiligo. This presentation will review the FDA-approved topical cream, Opzelura, a JAK inhibitor, and its effects on limiting vitiligo progression. Meanwhile, other non-conventional methods, such as Arsenic Sulphuratum Flavum used in homeopathy, will be debunked based on current literature. Most treatments still serve to arrest progression and induce skin repigmentation. Treatment plans may differ between patients due to depigmentation location on the skin. Since there is no gold standard plan for treating patients with vitiligo, the oral presentation will review all topical and systemic pharmacological therapies that fight the depigmentation of the skin and categorize their validity from a systematic review of the literature. Since treatment plans are limited in nature, all treatment methods will be mentioned and an attempt will be made to make a golden standard treatment process for these patients.

Keywords: vitiligo, phototherapy, immunosuppressive drugs, skin lightening preparations, combined modality therapy, arsenic sulphuratum flavum, homeopathy, allopathy, golden standard, Opzelura

Procedia PDF Downloads 67

Authors: Subrato Saha, Yun-Hyun Cho

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In electric power steering (EPS), spoke type brushless ac (BLAC) motors offer distinct advantages over other electric motor types in terms torque smoothness, reliability and efficiency. This paper deals with the shape optimization of spoke type BLAC motor, in order to reduce cogging torque. This paper examines 3 steps skewing rotor angle, optimizing rotor core edge and rotor overlap length for reducing cogging torque in spoke type BLAC motor. The methods were applied to existing machine designs and their performance was calculated using finite- element analysis (FEA). Prototypes of the machine designs were constructed and experimental results obtained. It is shown that the FEA predicted the cogging torque to be nearly reduce using those methods.

Keywords: EPS, 3-Step skewing, spoke type BLAC, cogging torque, FEA, optimization

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Authors: Yousif M. Yousif Abdallah, Mohamed E. Gar-Elnabi, Abdoelrahman H. A. Bakary, Alaa M. H. Eltoum, Abdelazeem K. M. Ali

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The study was established to measure the amount of radiation outside the treatment field in external beam radiation therapy using day method of dose calculation, the data was collected from 89 patients of cervical carcinoma in order to determine if the dose outside side the irradiation treatment field for spleen, liver, both kidneys, small bowel, large colon, skin within the acceptable limit or not. The cervical field included mainly 4 organs which are bladder, rectum part of small bowel and hip joint these organ received mean dose of (4781.987±281.321), (4736.91±331.8), (4647.64±387.1) and (4745.91±321.11) respectively. The mean dose received by outfield organs was (77.69±15.24cGy) to large colon, (93.079±12.31cGy) to right kidney (80.688±12.644cGy) to skin, (155.86±17.69cGy) to small bowel. This was more significant value noted.

Keywords: radiation dose, cervical carcinoma, day’s methods, radiation medicine

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Authors: Sol Girouard, Zona Kostic

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A home is often the largest and most expensive purchase a person makes. Whether the decision leads to a successful outcome will be determined by a combination of critical factors. In this paper, we propose a method that efficiently handles all the factors in residential real estate and performs predictions given a feature space with high dimensionality while controlling for overfitting. The proposed method was built on gradient descent and boosting algorithms and uses a mixed optimizing technique to improve the prediction power. Usually, a single model cannot handle all the cases thus our approach builds multiple models based on different subsets of the predictors. The algorithm was tested on 3 million homes across the U.S., and the experimental results demonstrate the efficiency of this approach by outperforming techniques currently used in forecasting prices. With everyday changes on the real estate market, our proposed algorithm capitalizes from new events allowing more efficient predictions.

Keywords: real estate prediction, gradient descent, boosting, ensemble methods, active learning, training

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: V. G. Rifert, V. V. Gorin, V. V. Sereda, V. V. Treputnev

Abstract:

The analysis of heat transfer design methods in condensing inside plain tubes under existing influence of shear stress is presented in this paper. The existing discrepancy in more than 30-50% between rating heat transfer coefficients and experimental data has been noted. The analysis of existing theoretical and semi-empirical methods of heat transfer prediction is given. The influence of a precise definition concerning boundaries of phase flow (it is especially important in condensing inside horizontal tubes), shear stress (friction coefficient) and heat flux on design of heat transfer is shown. The substantiation of boundary conditions of the values of parameters, influencing accuracy of rated relationships, is given. More correct relationships for heat transfer prediction, which showed good convergence with experiments made by different authors, are substantiated in this work.

Keywords: film condensation, heat transfer, plain tube, shear stress

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Authors: Joanna Estkowska

Abstract:

Sensory integration methods are very useful and improve daily functioning autistic and mentally disabled children. Autism is a neurobiological disorder that impairs one's ability to communicate with and relate to others as well as their sensory system. Children with autism, even highly functioning kids, can find it difficult to process language with surrounding noise or smells. They are hypersensitive to things we can ignore such as sight, sounds and touch. Adolescents with highly functioning autism or Asperger Syndrome can study Science and Math but the social aspect is difficult for them. Nature science is an area of study that attracts many of these kids. It is a systematic field in which the children can focus on a small aspect. If you follow these rules you can come up with an expected result. Sensory integration program and systematic classroom observation are quantitative methods of measuring classroom functioning and behaviors from direct observations. These methods specify both the events and behaviors that are to be observed and how they are to be recorded. Our students with and without autism attended the lessons in the classroom of nature science in the school and in the laboratory of University of Science and Technology in Bydgoszcz. The aim of this study is investigation the effects of sensory integration methods in teaching to students with autism. They were observed during experimental lessons in the classroom and in the laboratory. Their physical characteristics, sensory dysfunction, and behavior in class were taken into consideration by comparing their similarities and differences. In the chemistry classroom, every autistic student is paired with a mentor from their school. In the laboratory, the children are expected to wear goggles, gloves and a lab coat. The chemistry classes in the laboratory were held for four hours with a lunch break, and according to the assistants, the children were engaged the whole time. In classroom of nature science, the students are encouraged to use the interactive exhibition of chemical, physical and mathematical models constructed by the author of this paper. Our students with and without autism attended the lessons in those laboratories. The teacher's goals are: to assist the child in inhibiting and modulating sensory information and support the child in processing a response to sensory stimulation.

Keywords: autism spectrum disorder, science education, sensory integration techniques, student with special educational needs

Procedia PDF Downloads 176

Authors: M. Poveda, S. Lozecznik, J. Oleszkiewicz, Q. Yuan

Abstract:

The goal of this experiment is to evaluate the effectiveness of different leachate pre-treatment options in terms of COD and ammonia removal. This research focused on the evaluation of physical-chemical methods for pre-treatment of leachate that would be effective and rapid in order to satisfy the requirements of the sewer discharge by-laws. The four pre-treatment options evaluated were: air stripping, chemical coagulation, electro-coagulation and advanced oxidation with sodium ferrate. Chemical coagulation reported the best COD removal rate at 43%, compared to 18 % for both air stripping and electro-coagulation, and 20 % for oxidation with sodium ferrate. On the other hand, air stripping was far superior to the other treatment options in terms of ammonia removal with 86 %. Oxidation with sodium ferrate reached only 16 %, while chemical coagulation and electro-coagulation removed less than 10 %. When combined, air stripping and chemical coagulation removed up to 50 % COD and 85 % ammonia.

Keywords: leachate pretreatment, air stripping, chemical coagulation, electro-coagulation, oxidation

Procedia PDF Downloads 814

Authors: Chandra Upadhyaya, Arup Kumar Sarma

Abstract:

In the North Eastern part of India several hydro power projects are being proposed and execution for some of them are already initiated. There are controversies surrounding these constructions. Impact of these dams in the downstream part of the rivers needs to be assessed so that eco-system and people living downstream are protected by redesigning the projects if it becomes necessary. This may result in reducing the stresses to the affected ecosystem and people living downstream. At present many index based ecological methods are present to assess impact on ecology. However, none of these methods are capable of assessing the affect resulting from dam induced diurnal variation of flow in the downstream. We need environmental flow methodology based on hydrological index which can address the affect resulting from dam induced diurnal variation of flow and play an important role in a riverine ecosystem management and be able to provide a qualitative idea about changes in the habitat for aquatic and riparian species.

Keywords: ecosystem, environmental flow assessment, entropy, IHA, TNC

Procedia PDF Downloads 361