Search results for: Library of Support Vector Machines (LIBSVM)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8842

Search results for: Library of Support Vector Machines (LIBSVM)

8062 Predicting the Quality of Life on the Basis of Perceived Social Support among Patients with Coronary Artery Bypass Graft

Authors: Azadeh Yaraghchi, Reza Bagherian Sararoodi, Niknaz Salehi Moghadam, Mohammad Hossein Mandegar, Adis Kraskian Mujembari, Omid Rezaei

Abstract:

Background: Quality of life is one of the most important consequences of disease in psychosomatic disorders. Many psychological factors are considered in predicting quality of life in patients with coronary artery bypass graft (CABG). The present study was aimed to determine the relationship between perceived social support and quality of life in patients with coronary artery bypass graft (CABG). Methods: The population included 82 patients who had undergone CABG from October 2014 to May 2015 in four different hospitals in Tehran. The patients were evaluated with Multi-dimension scale of perceived social support (MSPSS) and after three months follow up were evaluated by Short-Form quality of life questionnaire (SF-36). The obtained data were analyzed through Pearson correlation test and multiple variable regression models. Findings: A relationship between perceived social support and quality of life in patients with CABG was observed (r=0.374, p<0.01). The results showed that 22.4% of variation in quality of life is predicted by perceived social support components (p<0.01, R2 =0.224). Conclusion: Based on the results, perceived social support is one of the predictors of quality of life in patients with coronary artery bypass graft. Accordingly, these results can be useful in conceiving proactive policies, detecting high risk patients and planning for psychological interventions.

Keywords: coronary artery bypass graft, perceived social support, psychological factors, quality of life

Procedia PDF Downloads 369
8061 Examining Resilience, Social Supports, and Self-Esteem as Predictors of the Quality of Life of ODAPUS (Orang Dengan Lupus)

Authors: Yulmaida Amir, Fahrul Rozi, Insany C. Kamil, Fanny Aryani

Abstract:

ODAPUS (Orang dengan Lupus) is an Indonesian term for people with Lupus, a chronic autoimmune disease in which immune system of the body becomes hyperactive and attacks normal tissue. The number of ODAPUS indicate an increase in Indonesia, thereby helping to improve their quality of life to be important to help their recovery. This study aims to examine the effect of resilience, self-esteem, and social support on the quality of life of women who had been diagnosed as having Lupus. Data were collected from 64 ODAPUS in Indonesia, using the World Health Organization Quality of Life (WHOQOL), Resilience Scale from Wagnil and Young (1993), self-esteem scale (developed from Coopersmith’s theory), and Social Support Questioner from Northouse (1988). Regression data analysis showed that resilience, social support, and self-esteem predict the quality of life of the ODAPUS simultaneously. If the variable was analysed individually, self-esteem did not significantly contribute to the quality of life. Resilience contributed most significantly to the quality of life, followed by social support. Of five sources of social supports included in the research, support from family members (parents and brother/sisters) has the most significant contribution to the quality of life, followed by support from spouse, and from friends. Interestingly, social support from medical personnel (medical doctors and nurses) had not a significant contribution to the quality of life of ODAPUS. As a conclusion, this research showed that the ability of ODAPUS to cope with difficulty in life, and support from family members, spouse, and friends were the significant predictors for their quality of life.

Keywords: quality of life, resilience, self-esteem, social supports

Procedia PDF Downloads 169
8060 Fourier Transform and Machine Learning Techniques for Fault Detection and Diagnosis of Induction Motors

Authors: Duc V. Nguyen

Abstract:

Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest bene t based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

Procedia PDF Downloads 170
8059 Indigenous Knowledge Management: Towards Identification of Challenges and Opportunities in Developing Countries

Authors: Desmond Chinedu Oparaku, Emmanuel Uwazie Anyanwu, Oyemike Victor Benson, Ogbonna Isaac-Nnadimele

Abstract:

The purpose of this paper is to provide a theoretical discourse that highlights the challenges associated with management of indigenous knowledge with reference to developing countries. Literature review and brainstorming were used to collect relevant data and draw inferences. The findings indicate that non-existence of indigenous knowledge management policy (IKMP), low level of partnership drive among library and information services providers, non-uniformity of format and content of indigenous knowledge, inadequate funding, and lack of access to ICTs, lack of indigenous people with indigenous expertise and hoarding of knowledge as challenges to indigenous knowledge management. The study is based on literature review and information gathered through brain storming with professional colleagues the geographic scope as developing countries. The study has birth several implication based on the findings made. Professionally, it has necessitated the need for formulating a viable indigenous knowledge management policy (IKMP), creating of collaborative network through partnership, and integration of ICTs to indigenous knowledge management practices by libraries in developing countries etc. The originality of this paper is revealed in its capability as serving as an eye opener to librarians on the need for preserving and managing indigenous knowledge in developing countries. It further unlocks the possibilities of exploring empirical based researches to substantiate the theoretical issues raised in this paper. The findings may be used by library managers to improve indigenous knowledge management (IKM).

Keywords: developing countries, ICTs, indigenous knowledge, knowledge management

Procedia PDF Downloads 342
8058 Effects of Training on Self-Efficacy, Competence, and Target Complaints of Dementia Family Support Program Facilitators

Authors: Myonghwa Park, Eun Jeong Choi

Abstract:

Persons with dementia living at home have complex caregiving demands, which can be significant sources of stress for the family caregivers. Thus, the dementia family support program facilitators struggle to provide various health and social services, facing diverse challenges. The purpose of this study was to research the effects of training program for the dementia family support program facilitators on self-efficacy, competence, and target complaints concerning operating their program. We created a training program with systematic contents, which was composed of 10 sessions and we provided the program for the facilitators. The participants were 32 people at 28 community dementia support centers who manage dementia family support programs and they completed quantitative and qualitative self-report questionnaire before and after participating in the training program. For analyzing the data, descriptive statistics were used and with a paired t-test, pretest and posttest scores of self-efficacy, competence, and target complaints were analyzed. We used Statistical Package for the Social Sciences (SPSS) statistics (Version 21) to analyze the data. The average age of the participants was 39.6 years old and the 84.4% of participants were nurses. There were statistically meaningful increases in facilitators’ self-efficacy scores (t = -4.45, p < .001) and competence scores (t = -2.133, p = 0.041) after participating in training program and operating their own dementia family support program. Also, the facilitators’ difficulties in conducting their dementia family support program were decreased which was assessed with target complaints. Especially, the facilitators’ lack of dementia expertise and experience was decreased statistically significantly (t = 3.520, p = 0.002). Findings provided evidence of the benefits of the training program for facilitators to enhance managing dementia family support program by improving the facilitators’ self-efficacy and competence and decreasing their difficulties regarding operating their program.

Keywords: competence, dementia, facilitator, family, self-efficacy, training

Procedia PDF Downloads 213
8057 Reliability Analysis of a Life Support System in a Public Aquarium

Authors: Mehmet Savsar

Abstract:

Complex Life Support Systems (LSS) are used in all large commercial and public aquariums in order to keep the fish alive. Reliabilities of individual equipment, as well as the complete system, are extremely important and critical since the life and safety of important fish depend on these life support systems. Failure of some critical device or equipment, which do not have redundancy, results in negative consequences and affects life support as a whole. In this paper, we have considered a life support system in a large public aquarium in Kuwait Scientific Center and presented a procedure and analysis to show how the reliability of such systems can be estimated by using appropriate tools and collected data. We have also proposed possible improvements for systems reliability. In particular, addition of parallel components and spare parts are considered and the numbers of spare parts needed for each component to achieve a required reliability during specified lead time are calculated. The results show that significant improvements in system reliability can be achieved by operating some LSS components in parallel and having certain numbers of spares available in the spare parts inventories. The procedures and the results presented in this paper are expected to be useful for aquarium engineers and maintenance managers dealing with LSS.

Keywords: life support systems, aquariums, reliability, failures, availability, spare parts

Procedia PDF Downloads 280
8056 Characteristics of an Impact on Reading Comprehension of Elementary School Students

Authors: Judith Hanke

Abstract:

Due to the rise of students with reading difficulties, a digital reading support was developed. The digital reading support focuses on reading comprehension of elementary school students. It consists of literary texts and reading exercises with diagnostics. To analyze the use of the reading packages an intervention study took place in 2023. For the methodology, an ABA-design was selected for the intervention study to examine the reading packages. The study was expedited from April 2023 until July 2023 and collected quantitative data of individuals, groups, and classes. It consisted of a survey group (N = 58) and a control group (N = 53). The pretest was conducted before the reading support intervention. The students of the survey group received reading support on their ability level to aid the individual student’s needs. At the beginning of the study characteristics of the students were collected. The characteristics included gender, age, repetition of a class, spoken language at home, German as a second language, and special support needs such as dyslexia; right after the intervention, the posttest was examined. At least three weeks after the intervention, the follow-up testing was administered. A standardized reading comprehension test was used for the three test times. The test consists of three subtests: word comprehension, sentence comprehension, and text comprehension. The focus of this paper is to determine which characteristics have an impact on reading comprehension of elementary school students. The students’ characteristics were correlated with the three test times through a Pearson correlation. The main findings are that age, repetition of a class, spoken language at home, German as a second language have an effect on reading comprehension. Interestingly gender and special support needs did not have a significant effect on the reading comprehension of the students. The significance of the study is to determine which characteristics have an impact on reading comprehension and then to assess how reading support can be modified to support the diverse students.

Keywords: class repetition, reading comprehension, reading support, second language, spoken language at home

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8055 Tumor Boundary Extraction Using Intensity and Texture-Based on Gradient Vector

Authors: Namita Mittal, Himakshi Shekhawat, Ankit Vidyarthi

Abstract:

In medical research study, doctors and radiologists face lot of complexities in analysing the brain tumors in Magnetic Resonance (MR) images. Brain tumor detection is difficult due to amorphous tumor shape and overlapping of similar tissues in nearby region. So, radiologists require one such clinically viable solution which helps in automatic segmentation of tumor inside brain MR image. Initially, segmentation methods were used to detect tumor, by dividing the image into segments but causes loss of information. In this paper, a hybrid method is proposed which detect Region of Interest (ROI) on the basis of difference in intensity values and texture values of tumor region using nearby tissues with Gradient Vector Flow (GVF) technique in the identification of ROI. Proposed approach uses both intensity and texture values for identification of abnormal section of the brain MR images. Experimental results show that proposed method outperforms GVF method without any loss of information.

Keywords: brain tumor, GVF, intensity, MR images, segmentation, texture

Procedia PDF Downloads 432
8054 Vehicle Type Classification with Geometric and Appearance Attributes

Authors: Ghada S. Moussa

Abstract:

With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management. This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.

Keywords: appearance attributes, geometric attributes, support vector machine, vehicle classification

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8053 Multisymplectic Geometry and Noether Symmetries for the Field Theories and the Relativistic Mechanics

Authors: H. Loumi-Fergane, A. Belaidi

Abstract:

The problem of symmetries in field theory has been analyzed using geometric frameworks, such as the multisymplectic models by using in particular the multivector field formalism. In this paper, we expand the vector fields associated to infinitesimal symmetries which give rise to invariant quantities as Noether currents for classical field theories and relativistic mechanic using the multisymplectic geometry where the Poincaré-Cartan form has thus been greatly simplified using the Second Order Partial Differential Equation (SOPDE) for multi-vector fields verifying Euler equations. These symmetries have been classified naturally according to the construction of the fiber bundle used.  In this work, unlike other works using the analytical method, our geometric model has allowed us firstly to distinguish the angular moments of the gauge field obtained during different transformations while these moments are gathered in a single expression and are obtained during a rotation in the Minkowsky space. Secondly, no conditions are imposed on the Lagrangian of the mechanics with respect to its dependence in time and in qi, the currents obtained naturally from the transformations are respectively the energy and the momentum of the system.

Keywords: conservation laws, field theories, multisymplectic geometry, relativistic mechanics

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8052 A Look at the Quantum Theory of Atoms in Molecules from the Discrete Morse Theory

Authors: Dairo Jose Hernandez Paez

Abstract:

The quantum theory of atoms in molecules (QTAIM) allows us to obtain topological information on electronic density in quantum mechanical systems. The QTAIM starts by considering the electron density as a continuous mathematical object. On the other hand, the discretization of electron density is also a mathematical object, which, from discrete mathematics, would allow a new approach to its topological study. From this point of view, it is necessary to develop a series of steps that provide the theoretical support that guarantees its application. Some of the steps that we consider most important are mentioned below: (1) obtain good representations of the electron density through computational calculations, (2) design a methodology for the discretization of electron density, and construct the simplicial complex. (3) Make an analysis of the discrete vector field associating the simplicial complex. (4) Finally, in this research, we propose to use the discrete Morse theory as a mathematical tool to carry out studies of electron density topology.

Keywords: discrete mathematics, Discrete Morse theory, electronic density, computational calculations

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8051 Flywheel Energy Storage Control Using SVPWM for Small Satellites Application

Authors: Noha El-Gohary, Thanaa El-Shater, A. A. Mahfouz, M. M. Sakr

Abstract:

Searching for high power conversion efficiency and long lifetime are important goals when designing a power supply subsystem for satellite applications. To fulfill these goals, this paper presents a power supply subsystem for small satellites in which flywheel energy storage system is used as a secondary power source instead of chemical battery. In this paper, the model of flywheel energy storage system is introduced; a DC bus regulation control algorithm for charging and discharging of flywheel based on space vector pulse width modulation technique and motor current control is also introduced. Simulation results showed the operation of the flywheel for charging and discharging mode during illumination and shadowed period. The advantages of the proposed system are confirmed by the simulation results of the power supply system.

Keywords: small-satellites, flywheel energy storage system, space vector pulse width modulation, power conversion

Procedia PDF Downloads 400
8050 Optimal Feature Extraction Dimension in Finger Vein Recognition Using Kernel Principal Component Analysis

Authors: Amir Hajian, Sepehr Damavandinejadmonfared

Abstract:

In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

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8049 Propylene Self-Metathesis to Ethylene and Butene over WOx/SiO2, Effect of Nano-Sized Extra Supports (SiO2 and TiO2)

Authors: Adisak Guntida

Abstract:

Propylene self-metathesis to ethylene and butene was studied over WOx/SiO2 catalysts at 450 °C and atmospheric pressure. The WOx/SiO2 catalysts were prepared by incipient wetness impregnation of ammonium metatungstate aqueous solution. It was found that, adding nano-sized extra supports (SiO2 and TiO2) by physical mixing with the WOx/SiO2 enhanced propylene conversion. The UV-Vis and FT-Raman results revealed that WOx could migrate from the original silica support to the extra support, leading to a better dispersion of WOx. The ICP-OES results also indicate that WOx existed on the extra support. Coke formation was investigated on the catalysts after 10 h time-on-stream by TPO. However, adding nano-sized extra supports led to higher coke formation which may be related to acidity as characterized by NH3-TPD.

Keywords: extra support, nanomaterial, propylene self-metathesis, tungsten oxide

Procedia PDF Downloads 245
8048 Quality Control Assessment of X-Ray Equipment in Hospitals of Katsina State, Nigeria

Authors: Aminu Yakubu Umar

Abstract:

X-ray is the major contributor to the effective dose of both the patient and the personnel. Because of the radiological risks involved, it is usually recommended that dose to patient from X-ray be kept as low as reasonably achievable (ALARA) with adequate image quality. The implementation of quality assurance in diagnostic radiology can help greatly in achieving that, as it is a technique designed to reduce X-ray doses to patients undergoing radiological examination. In this study, quality control was carried out in six hospitals, which involved KVp test, evaluation of total filtration, test for constancy of radiation output, and check for mA linearity. Equipment used include KVp meter, Rad-check meter, aluminum sheets (0.1–1.0 mm) etc. The results of this study indicate that, the age of the X-ray machines in the hospitals ranges from 3-13 years, GHI and GH2 being the oldest and FMC being the newest. In the evaluation of total filtration, the HVL of the X-ray machines in the hospitals varied, ranging from 2.3-5.2 mm. The HVL was found to be highest in AHC (5.2 mm), while it was lowest in GH3 (2.3 mm). All HVL measurements were done at 80 KVp. The variation in voltage accuracy in the hospitals ranges from 0.3%-127.5%. It was only in GH1 that the % variation was below the allowed limit. The test for constancy of radiation output showed that, the coefficient of variation ranges from 0.005–0.550. In GH3, FMC and AHC, the coefficient of linearity were less than the allowed limit, while in GH1, GH2 and GH4 the coefficient of linearity had exceeded the allowed limit. As regard to mA linearity, FMC and AHC had their coefficients of linearity as 0.12 and 0.10 respectively, which were within the accepted limit, while GH1, GH3 and GH4 had their coefficients as 0.16, 0.69 and 0.98 respectively, which exceeded the allowed limit.

Keywords: radiation, X-ray output, quality control, half-value layer, mA linearity, KVp variation

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8047 Impacts of Social Support on Perceived Level of Stress and Self-Esteem among Students of Private Universities of Karachi-Pakistan

Authors: Sheeba Farhan

Abstract:

This study is conducted to explore the predictive relationship of perceived stress and self-esteem with social support of students and to explore the factors, which contribute to develop or enhance the level of stress in students of private universities in Karachi-Pakistan. After literature review following hypotheses were formulated; 1)social support would predict perceived stress of students of business administration of private organizations of Higher education, 2) social support would predict the self-esteem of students of private organizations of Higher education, 3) there will be a relationship of perceived stress and self-esteem of students of private organizations of Higher education, 4) there will be a relationship of self esteem and social support of students of private organizations of Higher education. Sample of the study is comprise of 100 students of private organizations of Higher education in Karachi- Pakistan (i.e. males= 50 & females= 50). The age range of participants is 18-26 years. The measures, used in the study are: Demographic information form, a semi structured interview form, Rosenberg self esteem scale (Rosenberg, 1965) and perceived stress scale (Cohen, Kamarck, and Mermelstein, 1983) and multidimensional scale of perceived social support (Zimet, 1988) Descriptive statistics is used for getting a better statistical view of characteristics of sample. Regression analysis is used to explore the predictive relationship of study related stress and self esteem with academic achievement of students of private organizations of Higher education. Percentages and ratios were calculated to explore the level of perceived stress with respect to Socio-demographic characteristics in students of private organizations of Higher education. Finding shows that social support is significantly associated with the higher level of self-esteem among students of graduation but insignificantly associated with stress that has been experienced by them. These results are correlated with a wide variety of studies in which social support has proposed to be a predictor of well being for the students.

Keywords: private universities of Karachi-Pakistan, Self-esteem, social support, stress

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8046 Representative Concentration Pathways Approach on Wolbachia Controlling Dengue Virus in Aedes aegypti

Authors: Ida Bagus Mandhara Brasika, I Dewa Gde Sathya Deva

Abstract:

Wolbachia is recently developed as the natural enemy of Dengue virus (DENV). It inhibits the replication of DENV in Aedes aegypti. Both DENV and its vector, Aedes aegypty, are sensitive to climate factor especially temperature. The changing of climate has a direct impact on temperature which means changing the vector transmission. Temperature has been known to effect Wolbachia density as it has an ideal temperature to grow. Some scenarios, which are known as Representative Concentration Pathways (RCPs), have been developed by Intergovernmental Panel on Climate Change (IPCC) to predict the future climate based on greenhouse gases concentration. These scenarios are applied to mitigate the future change of Aedes aegypti migration and how Wolbachia could control the virus. The prediction will determine the schemes to release Wolbachia-injected Aedes aegypti to reduce DENV transmission.

Keywords: Aedes aegypti, climate change, dengue virus, Intergovernmental Panel on Climate Change, representative concentration pathways, Wolbachia

Procedia PDF Downloads 300
8045 Decision Support System for Optimal Placement of Wind Turbines in Electric Distribution Grid

Authors: Ahmed Ouammi

Abstract:

This paper presents an integrated decision framework to support decision makers in the selection and optimal allocation of wind power plants in the electric grid. The developed approach intends to maximize the benefice related to the project investment during the planning period. The proposed decision model considers the main cost components, meteorological data, environmental impacts, operation and regulation constraints, and territorial information. The decision framework is expressed as a stochastic constrained optimization problem with the aim to identify the suitable locations and related optimal wind turbine technology considering the operational constraints and maximizing the benefice. The developed decision support system is applied to a case study to demonstrate and validate its performance.

Keywords: decision support systems, electric power grid, optimization, wind energy

Procedia PDF Downloads 153
8044 A Reliable Multi-Type Vehicle Classification System

Authors: Ghada S. Moussa

Abstract:

Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

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8043 First Survey of Seasonal Abundance and Daily Activity of Stomoxys calcitrans: In Zaouiet Sousse, the Sahel Area of Tunisia

Authors: Amira Kalifa, Faïek Errouissi

Abstract:

The seasonal changes and the daily activity of Stomoxys calcitrans (Diptera: Muscidae) were examined, using Vavoua traps, in a dairy cattle farm in Zaouiet Sousse, the Sahel area of Tunisia during May 2014 to October 2014. Over this period, a total of 4366 hematophagous diptera were captured and Stomoxys calcitrans was the most commonly trapped species (96.52%). Analysis of the seasonal activity, showed that S.calcitrans is bivoltine, with two peaks: a significant peak is recorded in May-June, during the dry season, and a second peak at the end of October, which is quite weak. This seasonal pattern would depend on climatic factors, particularly the temperature of the manure and that of the air. The activity pattern of Stomoxys calcitrans was diurnal with seasonal variations. The daily rhythm shows a peak between 11:00 am to 15:00 pm in May and between 11:00 am to 17:00 pm in June. These vector flies are important pests of livestock in Tunisia, where they are known as a mechanical vector of several pathogens and have a considerable economic and health impact on livestock. A better knowledge of their ecology is a prerequisite for more efficient control measures.

Keywords: cattle farm, daily rhythm, Stomoxys calcitrans, seasonal activity

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8042 Reducing Support Structures in Design for Additive Manufacturing: A Neural Networks Approach

Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

Abstract:

This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

Procedia PDF Downloads 253
8041 Low-Voltage Multiphase Brushless DC Motor for Electric Vehicle Application

Authors: Mengesha Mamo Wogari

Abstract:

In this paper, low voltage multiphase brushless DC motor with square wave air-gap flux distribution for electric vehicle application is proposed. Ten-phase, 5 kW motor, has been designed and simulated by finite element methods demonstrating the desired high torque capability at low speed and flux weakening operation for high-speed operations. The motor torque is proportional to number of phases for a constant phase current and air-gap flux. The concept of vector control and simple space vector modulation technique is used on MATLAB to control the motor demonstrating simple switching pattern for selected number of phases. The low voltage DC and inverter output AC are desired characteristics to avoid any electric shock in the vehicle, accidentally and during abnormal conditions. The switching devices for inverter are of low-voltage rating and cost effective though their number is equal to twice the number of phases.

Keywords: brushless DC motors, electric Vehicle, finite element methods, Low-voltage inverter, multiphase

Procedia PDF Downloads 154
8040 The Role of Interpersonal and Institutional Trusts for the Public Support of Welfare State

Authors: Nazim Habibov, Alena Auchynnikava, Lida Fan

Abstract:

The exploration of the relationship between social trust and the support of the welfare system in transitional countries has attracted growing interests in recent decades. This study estimates the effects of interpersonal and institutional trust on the support of the welfare system in 27 countries in Eastern Europe the former Soviet Union. We estimate the data sets from the Life-in-Transition Survey 2010 and 2016 with binomial regression models. The results indicate that both interpersonal and institutional trust have positive effects on the support for the welfare system in all the three areas under investigation: helping the needy, public healthcare and public education, both in the less developed countries of the former Soviet Union and in the more developed Eastern European countries. Furthermore, the positive effects of interpersonal and institutional trust on support for helping the needy, public healthcare and public education were found to grow over time. In conclusion, this study confirms that interpersonal and institutional trusts have positive effects for the public support of the welfare system in these transitional countries under investigation, regardless of their level of development.

Keywords: central and eastern Europe, former Soviet union, international social welfare policy, comparative social welfare policy

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8039 ANN Based Simulation of PWM Scheme for Seven Phase Voltage Source Inverter Using MATLAB/Simulink

Authors: Mohammad Arif Khan

Abstract:

This paper analyzes and presents the development of Artificial Neural Network based controller of space vector modulation (ANN-SVPWM) for a seven-phase voltage source inverter. At first, the conventional method of producing sinusoidal output voltage by utilizing six active and one zero space vectors are used to synthesize the input reference, is elaborated and then new PWM scheme called Artificial Neural Network Based PWM is presented. The ANN based controller has the advantage of the very fast implementation and analyzing the algorithms and avoids the direct computation of trigonometric and non-linear functions. The ANN controller uses the individual training strategy with the fixed weight and supervised models. A computer simulation program has been developed using Matlab/Simulink together with the neural network toolbox for training the ANN-controller. A comparison of the proposed scheme with the conventional scheme is presented based on various performance indices. Extensive Simulation results are provided to validate the findings.

Keywords: space vector PWM, total harmonic distortion, seven-phase, voltage source inverter, multi-phase, artificial neural network

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8038 Towards a Model of Support in the Areas of Services of Educational Assistance and Mentoring in Middle Education in Mexico

Authors: Margarita Zavala, Gabriel Chavira, José González, Jorge Orozco, Julio Rolón, Roberto Pichardo

Abstract:

Adolescence is a neuralgic stage in the formation of every human being, generally this stage is when the middle school level is studied. In 2006, Mexico incorporated 'mentoring' space to assist students in their integration and participation in life. In public middle schools, it is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. With this, they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

Procedia PDF Downloads 480
8037 Comparison of Machine Learning-Based Models for Predicting Streptococcus pyogenes Virulence Factors and Antimicrobial Resistance

Authors: Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Diego Santibañez Oyarce, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

Streptococcus pyogenes is a gram-positive bacteria involved in a wide range of diseases and is a major-human-specific bacterial pathogen. In Chile, this year the 'Ministerio de Salud' declared an alert due to the increase in strains throughout the year. This increase can be attributed to the multitude of factors including antimicrobial resistance (AMR) and Virulence Factors (VF). Understanding these VF and AMR is crucial for developing effective strategies and improving public health responses. Moreover, experimental identification and characterization of these pathogenic mechanisms are labor-intensive and time-consuming. Therefore, new computational methods are required to provide robust techniques for accelerating this identification. Advances in Machine Learning (ML) algorithms represent the opportunity to refine and accelerate the discovery of VF associated with Streptococcus pyogenes. In this work, we evaluate the accuracy of various machine learning models in predicting the virulence factors and antimicrobial resistance of Streptococcus pyogenes, with the objective of providing new methods for identifying the pathogenic mechanisms of this organism.Our comprehensive approach involved the download of 32,798 genbank files of S. pyogenes from NCBI dataset, coupled with the incorporation of data from Virulence Factor Database (VFDB) and Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. These datasets provided labeled examples of both virulent and non-virulent genes, enabling a robust foundation for feature extraction and model training. We employed preprocessing, characterization and feature extraction techniques on primary nucleotide/amino acid sequences and selected the optimal more for model training. The feature set was constructed using sequence-based descriptors (e.g., k-mers and One-hot encoding), and functional annotations based on database prediction. The ML models compared are logistic regression, decision trees, support vector machines, neural networks among others. The results of this work show some differences in accuracy between the algorithms, these differences allow us to identify different aspects that represent unique opportunities for a more precise and efficient characterization and identification of VF and AMR. This comparative analysis underscores the value of integrating machine learning techniques in predicting S. pyogenes virulence and AMR, offering potential pathways for more effective diagnostic and therapeutic strategies. Future work will focus on incorporating additional omics data, such as transcriptomics, and exploring advanced deep learning models to further enhance predictive capabilities.

Keywords: antibiotic resistance, streptococcus pyogenes, virulence factors., machine learning

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8036 The Ability of Forecasting the Term Structure of Interest Rates Based on Nelson-Siegel and Svensson Model

Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

Abstract:

Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector auto-regressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel Model, neural networks, Svensson Model, vector autoregressive model, yield curve

Procedia PDF Downloads 335
8035 Bioinformatic Screening of Metagenomic Fosmid Libraries for Identification of Biosynthetic Pathways Derived from the Colombian Soils

Authors: María Fernanda Quiceno Vallejo, Patricia del Portillo, María Mercedes Zambrano, Jeisson Alejandro Triana, Dayana Calderon, Juan Manuel Anzola

Abstract:

Microorganisms from tropical ecosystems can be novel in terms of adaptations and conservation. Given the macrodiversity of Colombian ecosystems, it is possible that this diversity is also present in Colombian soils. Tropical soil bacteria could offer a potentially novel source of bioactive compounds. In this study we analyzed a metagenomic fosmid library constructed with tropical bacterial DNAs with the aim of understanding its underlying diversity and functional potential. 8640 clones from the fosmid library were sequenced by NANOPORE MiniOn technology, then analyzed with bioinformatic tools such as Prokka, AntiSMASH and Bagel4 in order to identify functional biosynthetic pathways in the sequences. The strains showed ample difference when it comes to biosynthetic pathways. In total we identified 4 pathways related to aryl polyene synthesis, 12 related to terpenes, 22 related to NRPs (Non ribosomal peptides), 11 related PKs (Polyketide synthases) and 7 related to RiPPs (bacteriocins). We designed primers for the metagenomic clones with the most BGCs (sample 6 and sample 2). Results show the biotechnological / pharmacological potential of tropical ecosystems. Overall, this work provides an overview of the genomic and functional potential of Colombian soil and sets the groundwork for additional exploration of tropical metagenomic sequencing.

Keywords: bioactives, biosyntethic pathways, bioinformatic, bacterial gene clusters, secondary metabolites

Procedia PDF Downloads 165
8034 Supporting Young Emergent Multilingual Learners in Prekindergarten Classrooms: Policy Implications

Authors: Tiedan Huang, Chun Zhang, Caitlin Coe

Abstract:

This study investigated the quality of instructional support for young Emergent Multilingual Learners (EMLs) in 50 Universal Prekindergarten (UPK) classroom in New York City (NYC). This is one of the first empirical studies examining the instructional support for this student population. We collected data using a mixed method of structured observations of teacher-child interactions in 50 classrooms, and surveys and interviews with program leaders and the teaching teams. We found that NYC’s UPK classrooms offered warm and supportive environments for EMLs. Nevertheless, in general, instructional support was relatively low. This study identified large mindset, knowledge, and practice gaps—and a real opportunity—among NYC early childhood professionals, specifically in the areas of providing adequate instructional and linguistic support for EMLs as well as partnering with families in capturing their cultural and home literacy assets. Consistent, rigorous, and meaningful use of data is necessary to support both EMLs’ language and literacy development and teachers’/leaders’ professional development.

Keywords: high quality instruction, culturally and linguistically responsive practices, professional development, workforce development

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8033 Divorce Advice and Parents' Council Support Groups: Help for Divorced Parents to Create Co-Parenting after Divorce

Authors: Paivi Hietanen

Abstract:

At family with children, divorce is a risk for a child to lose the relationship to the parent with whom the child doesn't live. A child has the right to the get care from both parents after the divorce. Even though your ex-spouse isn’t longer your companion, to the child he or she is still unique as a parent and parents must cooperate and support their child in the new family situation. To divorcee, it's necessary to understand the difference between the intimate relationship that ends and parenthood that continues. Cooperative parenting takes a lot of effort and flexibility for the parents to make joint custody work well. It is vital that parents get help to understand the situation from child points of view. When parent is facing divorce, and all the emotions that it brings along, can the child easily be forgotten. To help children, we must help parents to understand, that a relationship can end, parenthood cannot. As professionals, we should help the parents to see the significance and value of both parents to the child and try to support and protect parenthood-relationship between parents. The Federation of Mother and Child Homes and Shelters have developed group models to work with parents during or after divorce. These support groups are led by professionals, but peer support is also used. These support groups have been held over 10 years and there are found from 20 different cities in Finland. Eroneuvo event (divorce advice) service is intended for parents who are considering or have already divorced. The Vanhemman neuvo (parents' council) is a peer support group that helps parents with post-divorce parenting issues. From these groups, parents receive information and peer support for matters related to divorcing and how to support the child and do co-parenting. At the groups and in given information for divorced parents, is used a method called the 'Irreversible triangle'. It's a way to picture the intimate relationship and parenthood after the divorce and what is the difference between these two things. 'Irreversible triangle' is used to help parents and professionals to understand, what happens if a child loses the relationship to the other parent or if parents co-parenting doesn't work well. From the largely collected feedback, group members tell that they feel themselves relieved after taking part of the group. Parents also experience that talking with other parents helps to survive. Group members learn to co-operate with the other parent, and they'll also learn to see the best interest of the child after the divorce. Parents would highly recommend these groups to other parents.

Keywords: child's right, co-parenting, parenthood after the divorce, peer support

Procedia PDF Downloads 166