Search results for: medical decision support
6502 Physical Training in the Context of Preparation for the Performance of Junior Two: Sports Dance Practitioners
Authors: Rosa Alin Cristian
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As in any other sports branch, there is also a relationship of dependence between the motor qualities and the technical skills in the sports dance, in the sense that superior performances from a technical, artistic point of view can be obtained only on the basis of a certain level of motor qualities and of the morphological and functional indices of the organism. Starting from the premise that physical training is a basic component of the dancers' training process, determining the efficacy and efficiency of the athletes in training and competitions, its main objectives are to obtain an optimal functional capacity of the body, which is reached through a superior level of development and manifestation of the basic and specific motor qualities, through appropriate values of the morph-functional indices, all against the background of a perfect state of health. We propose in this paper to create an inventory of the motor qualities specific to the sports dance, of their forms of manifestation, to establish some methodical priorities for their development, in order to support the specialists in their attempt to approach the physical training in the most rigorous and efficient way, according to the characteristics of each age category.Keywords: physical training, motor skills, sports dance, performance
Procedia PDF Downloads 676501 Transforming the Hazelnut Supply Chain: Opportunities and Challenges for Ontario Agri-Businesses
Authors: Kalinga Jagoda
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With changing population demographics and consumer preferences, specialty crops present significant opportunities for Ontario agri-businesses to develop niche markets. However, the greater rewards offered by such opportunities come with comparable challenges that are driven by specific productmarket attributes, as well as supply and demand-side factors, including certain risks. Thus, initiatives to promote and support such sectors need to be informed by an understanding of the impact of these product-market and industry specific factors on supply chain development. To this end, this project proposes to map selected specialty crops supply chains, using a suite of tested methodological approaches to evaluate their market potential, considering total supply chain costs, lead times and responsiveness. The project will deliver comprehensive supply chain maps identifying the points of value addition and value capture that are of benefit to key stakeholders for the purposes of developing policy interventions, conducting market appraisals and identifying industry best practices.Keywords: supply chain management, hazelnut industry, supply chain maps, market opportunity
Procedia PDF Downloads 416500 Snake Locomotion: From Sinusoidal Curves and Periodic Spiral Formations to the Design of a Polymorphic Surface
Authors: Ennios Eros Giogos, Nefeli Katsarou, Giota Mantziorou, Elena Panou, Nikolaos Kourniatis, Socratis Giannoudis
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In the context of the postgraduate course Productive Design, Department of Interior Architecture of the University of West Attica in Athens, under the guidance of Professors Nikolaos Koyrniatis and Socratis Giannoudis, kinetic mechanisms with parametric models were examined for their further application in the design of objects. In the first phase, the students studied a motion mechanism that they chose from daily experience and then analyzed its geometric structure in relation to the geometric transformations that exist. In the second phase, the students tried to design it through a parametric model in Grasshopper3d for Rhino algorithmic processor and plan the design of its application in an everyday object. For the project presented, our team began by studying the movement of living beings, specifically the snake. By studying the snake and the role that the environment has in its movement, four basic typologies were recognized: serpentine, concertina, sidewinding and rectilinear locomotion, as well as its ability to perform spiral formations. Most typologies are characterized by ripples, a series of sinusoidal curves. For the application of the snake movement in a polymorphic space divider, the use of a coil-type joint was studied. In the Grasshopper program, the simulation of the desired motion for the polymorphic surface was tested by applying a coil on a sinusoidal curve and a spiral curve. It was important throughout the process that the points corresponding to the nodes of the real object remain constant in number, as well as the distances between them and the elasticity of the construction had to be achieved through a modular movement of the coil and not some elastic element (material) at the nodes. Using mesh (repeating coil), the whole construction is transformed into a supporting body and combines functionality with aesthetics. The set of elements functions as a vertical spatial network, where each element participates in its coherence and stability. Depending on the positions of the elements in terms of the level of support, different perspectives are created in terms of the visual perception of the adjacent space. For the implementation of the model on the scale (1:3), (0.50m.x2.00m.), the load-bearing structure that was studied has aluminum rods for the basic pillars Φ6mm and Φ 2.50 mm, for the secondary columns. Filling elements and nodes are of similar material and were made of MDF surfaces. During the design process, four trapezoidal patterns were picketed, which function as filling elements, while in order to support their assembly, a different engraving facet was done. The nodes have holes that can be pierced by the rods, while their connection point with the patterns has a half-carved recess. The patterns have a corresponding recess. The nodes are of two different types depending on the column that passes through them. The patterns and knots were designed to be cut and engraved using a Laser Cutter and attached to the knots using glue. The parameters participate in the design as mechanisms that generate complex forms and structures through the repetition of constantly changing versions of the parts that compose the object.Keywords: polymorphic, locomotion, sinusoidal curves, parametric
Procedia PDF Downloads 986499 Fast Prototyping of Precise, Flexible, Multiplexed, Printed Electrochemical Enzyme-Linked Immunosorbent Assay System for Point-of-Care Biomarker Quantification
Authors: Zahrasadat Hosseini, Jie Yuan
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Point-of-care (POC) diagnostic devices based on lab-on-a-chip (LOC) technology have the potential to revolutionize medical diagnostics. However, the development of an ideal microfluidic system based on LOC technology for diagnostics purposes requires overcoming several obstacles, such as improving sensitivity, selectivity, portability, cost-effectiveness, and prototyping methods. While numerous studies have introduced technologies and systems that advance these criteria, existing systems still have limitations. Electrochemical enzyme-linked immunosorbent assay (e-ELISA) in a LOC device offers numerous advantages, including enhanced sensitivity, decreased turnaround time, minimized sample and analyte consumption, reduced cost, disposability, and suitability for miniaturization, integration, and multiplexing. In this study, we present a novel design and fabrication method for a microfluidic diagnostic platform that integrates screen-printed electrochemical carbon/silver chloride electrodes on flexible printed circuit boards with flexible, multilayer, polydimethylsiloxane (PDMS) microfluidic networks to accurately manipulate and pre-immobilize analytes for performing electrochemical enzyme-linked immunosorbent assay (e-ELISA) for multiplexed quantification of blood serum biomarkers. We further demonstrate fast, cost-effective prototyping, as well as accurate and reliable detection performance of this device for quantification of interleukin-6-spiked samples through electrochemical analytics methods. We anticipate that our invention represents a significant step towards the development of user-friendly, portable, medical-grade, POC diagnostic devices.Keywords: lab-on-a-chip, point-of-care diagnostics, electrochemical ELISA, biomarker quantification, fast prototyping
Procedia PDF Downloads 766498 Fast Prototyping of Precise, Flexible, Multiplexed, Printed Electrochemical Enzyme-Linked Immunosorbent Assay Platform for Point-of-Care Biomarker Quantification
Authors: Zahrasadat Hosseini, Jie Yuan
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Point-of-care (POC) diagnostic devices based on lab-on-a-chip (LOC) technology have the potential to revolutionize medical diagnostics. However, the development of an ideal microfluidic system based on LOC technology for diagnostics purposes requires overcoming several obstacles, such as improving sensitivity, selectivity, portability, cost-effectiveness, and prototyping methods. While numerous studies have introduced technologies and systems that advance these criteria, existing systems still have limitations. Electrochemical enzyme-linked immunosorbent assay (e-ELISA) in a LOC device offers numerous advantages, including enhanced sensitivity, decreased turnaround time, minimized sample and analyte consumption, reduced cost, disposability, and suitability for miniaturization, integration, and multiplexing. In this study, we present a novel design and fabrication method for a microfluidic diagnostic platform that integrates screen-printed electrochemical carbon/silver chloride electrodes on flexible printed circuit boards with flexible, multilayer, polydimethylsiloxane (PDMS) microfluidic networks to accurately manipulate and pre-immobilize analytes for performing electrochemical enzyme-linked immunosorbent assay (e-ELISA) for multiplexed quantification of blood serum biomarkers. We further demonstrate fast, cost-effective prototyping, as well as accurate and reliable detection performance of this device for quantification of interleukin-6-spiked samples through electrochemical analytics methods. We anticipate that our invention represents a significant step towards the development of user-friendly, portable, medical-grade POC diagnostic devices.Keywords: lab-on-a-chip, point-of-care diagnostics, electrochemical ELISA, biomarker quantification, fast prototyping
Procedia PDF Downloads 776497 African American Female Caregivers’ Perceptions, Experiences, and Expectations of the Special Education Process
Authors: Lenell D. Walton
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African American families have consistently contended that their child’s special education team does not provide the services necessary to meet their child’s academic goals. Special education teams must guide and mentor African American students and their families through the special education process. This qualitative study examined African American female caregivers' perceptions, experiences, and expectations regarding the special education process. Data collection methods utilized in the study included a survey, semi-structured interviews, and three focus groups. Data were analyzed and compared to identify themes. Three themes emerged from the survey: education and training, participation, and challenges. Six major themes emerged: (a) differences in treatment and cultural disconnect, (b) lack of support and resources, (c) participants’ experiences of the special education process, (d) parent participation, (e) barriers and concerns, and (f) expectations. Implications for policy and practice to improve the special education process are discussed.Keywords: African American, caregivers, critical race theory, special education
Procedia PDF Downloads 1016496 The Application of Maintenance Strategy in Energy Power Plant: A Case Study
Authors: Steven Vusmuzi Mashego, Opeyeolu Timothy Laseinde
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This paper presents a case study on applying maintenance strategies observed in a turbo-generator at a coal power plant. Turbo generators are one of the primary and critical components in energy generation. It is essential to apply correct maintenance strategies and apply operational procedures accordingly. The maintenance strategies are implemented to ensure the high reliability of the equipment. The study was carried out at a coal power station which will transit to a cleaner energy source in the nearest future. The study is relevant as lessons learned in this system will support plans and operational models implemented when cleaner energy sources replace coal-powered turbines. This paper first outlines different maintenance strategies executed on the turbo-generator modules. Secondly, the impacts of human factors on a coal power station are discussed, and the findings prompted recommendations for future actions.Keywords: maintenance strategies, turbo generator, operational error, human factor, electricity generation
Procedia PDF Downloads 1046495 The Impact of Volunteering on the Education and Lives of Romanian Students in Leeds, UK
Authors: Sulochini Pather
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Romanians are the second largest group of non-British nationals in the UK, following the Poles; over one million were reported in 2021. This follows the rapid growth in the number of Eastern Europeans settling in the UK for work which is linked to the expansion of the European Union. A recent report suggests that the growing numbers of Eastern European pupils have heightened concerns about their impact on the education of native English speakers, but little has been done to focus on the challenges faced by these students and their educational and life experiences. The pilot study presented in this paper focuses on six Romanian students aged between 14 and 19 from two schools and a college in the local area and includes data from interviews with headteachers, teachers, students, and parents. The paper highlights key findings which point to barriers and support Romanian children encounter in mainstream education, their homes, and community and the extent to which a volunteering program offered at a local charity called Community Action to Create Hope (CATCH) impacts their education and lives. The study has implications for supporting the inclusion of immigrant children.Keywords: Romanian, Eastern European, inclusion, volunteering programme
Procedia PDF Downloads 616494 Development of Computational Approach for Calculation of Hydrogen Solubility in Hydrocarbons for Treatment of Petroleum
Authors: Abdulrahman Sumayli, Saad M. AlShahrani
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For the hydrogenation process, knowing the solubility of hydrogen (H2) in hydrocarbons is critical to improve the efficiency of the process. We investigated the H2 solubility computation in four heavy crude oil feedstocks using machine learning techniques. Temperature, pressure, and feedstock type were considered as the inputs to the models, while the hydrogen solubility was the sole response. Specifically, we employed three different models: Support Vector Regression (SVR), Gaussian process regression (GPR), and Bayesian ridge regression (BRR). To achieve the best performance, the hyper-parameters of these models are optimized using the whale optimization algorithm (WOA). We evaluated the models using a dataset of solubility measurements in various feedstocks, and we compared their performance based on several metrics. Our results show that the WOA-SVR model tuned with WOA achieves the best performance overall, with an RMSE of 1.38 × 10− 2 and an R-squared of 0.991. These findings suggest that machine learning techniques can provide accurate predictions of hydrogen solubility in different feedstocks, which could be useful in the development of hydrogen-related technologies. Besides, the solubility of hydrogen in the four heavy oil fractions is estimated in different ranges of temperatures and pressures of 150 ◦C–350 ◦C and 1.2 MPa–10.8 MPa, respectivelyKeywords: temperature, pressure variations, machine learning, oil treatment
Procedia PDF Downloads 636493 Neural Network Based Approach of Software Maintenance Prediction for Laboratory Information System
Authors: Vuk M. Popovic, Dunja D. Popovic
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Software maintenance phase is started once a software project has been developed and delivered. After that, any modification to it corresponds to maintenance. Software maintenance involves modifications to keep a software project usable in a changed or a changing environment, to correct discovered faults, and modifications, and to improve performance or maintainability. Software maintenance and management of software maintenance are recognized as two most important and most expensive processes in a life of a software product. This research is basing the prediction of maintenance, on risks and time evaluation, and using them as data sets for working with neural networks. The aim of this paper is to provide support to project maintenance managers. They will be able to pass the issues planned for the next software-service-patch to the experts, for risk and working time evaluation, and afterward to put all data to neural networks in order to get software maintenance prediction. This process will lead to the more accurate prediction of the working hours needed for the software-service-patch, which will eventually lead to better planning of budget for the software maintenance projects.Keywords: laboratory information system, maintenance engineering, neural networks, software maintenance, software maintenance costs
Procedia PDF Downloads 3466492 Prevalence of Intestinal Parasite among Patients Attending Two Medical Centers in Jos
Authors: G. I. Ozumba, V. A. Pam, V. A. Adejoh, S. A. Odey
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Intestinal parasitic infections are the most common parasitic infections of the man commonly resulting in morbidity and mortality in infected individuals. Two hundred (200) patients from two medical centers were randomly examined for intestinal parasites using normal saline wet mount and formol-ether concentration methods. One hundred patients each were examined from Plateau State Specialist Hospital (PSSH) and Vom Christian Hospital (VCH) respectively. Of the 100 patients examined at PSSH, (22.0%) tested positive for intestinal parasites, while only (6.0%) was reported for VCH. Ascaris lumbricoides and Taenia spp. were significantly (P value=0.0002726) the most prevalent intestinal parasites in PSSH with (31.8%) respectively. Balantidium coli and Entamoeba histolytica were the least prevalent at (4.5%) respectively. Hookworm (50.0%) was significantly (P<0.0001) the most prevalent intestinal parasite in VCH, followed by A. lumbricoides (33.3%), while Taenia spp. (16.7%) was the least. Female subjects 12(54.5%) were more infected than their male 10(45.4%) counterparts in PSSH. The difference (P value=0.3633) in the infection between female and male subjects at PSSH was not significant. Female subjects were significantly (P value=0.0008586) more infected 4(66.7%) than male subjects 2(33.3%) at VCH. The prevalence of intestinal parasite in relation to age in PSSH shows a significantly (P-value = 0.02573) high level among age group 11-20years 9(36.0%). On the contrary, the high prevalence of intestinal parasites among age groups 31-40 years 2(9.1%) at VCH was not significant (P value=0.1595). The result in relation to a water source in patients attending PSSH shows that the boreholes sources (66.7%) had a significantly (P<0.0001) high prevalence of intestinal parasites, while the least prevalence was observed in tap source (7.9%). Results from VCH shows that streams/rivers (16.7%) revealed high prevalence, while the tap source was least parasitized (10.0%). There was no significant difference (P value=0.436) in the prevalence of parasites in relation to the water source at VCH. This prevalence is directly related to the sanitary condition, socio-economic status, educational level, the age and hygienic habits of the patients. Thus, necessary sanitary policies, awareness, screening and de-worming exercises and occasional check of intestinal parasites are recommended.Keywords: intestinal parasites, Jos, patients, prevalence
Procedia PDF Downloads 1486491 Mesoporous Carbon Ceramic SiO2/C Prepared by Sol-Gel Method and Modified with Cobalt Phthalocyanine and Used as an Electrochemical Sensor for Nitrite
Authors: Abdur Rahim, Lauro Tatsuo Kubota, Yoshitaka Gushikem
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Carbon ceramic mesoporous SiO2/50wt%C (SBET= 170 m2g-1), where C is graphite, was prepared by the sol gel method. Scanning electron microscopy images and the respective element mapping showed that, within the magnification used, no phase segregation was detectable. It presented the electric conductivities of 0.49 S cm-1. This material was used to support cobalt phthalocyanine, prepared in situ, to assure a homogeneous dispersion of the electro active complex in the pores of the matrix. The surface density of cobalt phthalocyanine, on the matrix surfaces was 0.015 mol cm-2. Pressed disk, made with SiO2/50wt%C/CoPc, was used to fabricate an electrode and tested as sensors for nitrite determination by electro chemical technique. A linear response range between 0.039 and 0.42 mmol l−1,and correlation coefficient r=0.9996 was obtained. The electrode was chemically very stable and presented very high sensitivity for this analyte, with a limit of detection, LOD = 1.087 x 10-6 mol L-1.Keywords: SiO2/C/CoPc, sol-gel method, electrochemical sensor, nitrite oxidation, carbon ceramic material, cobalt phthalocyanine
Procedia PDF Downloads 3106490 SARS-CoV-2 Transmission Risk Factors among Patients from a Metropolitan Community Health Center, Puerto Rico, July 2020 to March 2022
Authors: Juan C. Reyes, Linnette Rodríguez, Héctor Villanueva, Jorge Vázquez, Ivonne Rivera
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On July 2020, a private non-profit community health center (HealthProMed) that serves people without a medical insurance plan or with limited resources in one of the most populated areas in San Juan, Puerto Rico, implemented a COVID-19 case investigation and contact-tracing surveillance system. Nursing personnel at the health center completed a computerized case investigation form that was translated, adapted, and modified from CDC’s Patient Under Investigation (PUI) Form. Between July 13, 2020, and March 17, 2022, a total of 9,233 SARS-CoV-2 tests were conducted at the health center, 16.9% of which were classified as confirmed cases (positive molecular test) and 27.7% as probable cases (positive serologic test). Most of the confirmed cases were females (60.0%), under 20 years old (29.1%), and living in their homes (59.1%). In the 14 days before the onset of symptoms, 26.3% of confirmed cases reported going to the supermarket, 22.4% had contact with a known COVID-19 case, and 20.7% went to work. The symptoms most commonly reported were sore throat (33.4%), runny nose (33.3%), cough (24.9%), and headache (23.2%). The most common preexisting medical conditions among confirmed cases were hypertension (19.3%), chronic lung disease including asthma, emphysema, COPD (13.3%), and diabetes mellitus (12.8). Multiple logistic regression analysis revealed that patients who used alcohol frequently during the last two weeks (OR=1.43; 95%CI: 1.15-1.77), those who were in contact with a positive case (OR=1.58; 95%CI: 1.33-1.88) and those who were obese (OR=1.82; 95%CI: 1.24-2.69) were significantly more likely to be a confirmed case after controlling for sociodemographic variables. Implementing a case investigation and contact-tracing component at community health centers can be of great value in the prevention and control of COVID-19 at the community level and could be used in future outbreaks.Keywords: community health center, Puerto Rico, risk factors, SARS-CoV-2
Procedia PDF Downloads 1096489 A System Framework for Dynamic Service Deployment in Container-Based Computing Platform
Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang
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Cloud computing and virtualization technology have brought an innovative way for people to develop and use software nowadays. However, conventional virtualization comes at the expense of performance loss for applications. Container-based virtualization could be an option as it potentially reduces overhead and minimizes performance decline of the service platform. In this paper, we introduce a system framework and present an implementation of resource broker for dynamic cloud service deployment on the container-based platform to facilitate the efficient execution and improve the utilization. We target the load-aware service deployment approach for task ranking scenario. This proposed effort can collaborate with resource management system to adaptively deploy services according to the different requests. In particular, our approach relies on composing service immediately onto appropriate container according to user’s requirement in order to conserve the waiting time. Our evaluation shows how efficient of the service deployment is and how to expand its applicability to support the variety of cloud service.Keywords: cloud computing, container-based virtualization, resource broker, service deployment
Procedia PDF Downloads 1636488 Nonlinear Finite Element Analysis of Composite Cantilever Beam with External Prestressing
Authors: R. I. Liban, N. Tayşi
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This paper deals with a nonlinear finite element analysis to examine the behavior up to failure of cantilever composite steel-concrete beams which are prestressed externally. 'Pre-' means stressing the high strength external tendons in the steel beam section before the concrete slab is added. The composite beam contains a concrete slab which is connected together with steel I-beam by means of perfect shear connectors between the concrete slab and the steel beam which is subjected to static loading. A finite element analysis will be done to study the effects of external prestressed tendons on the composite steel-concrete beams by locating the tendons in different locations (profiles). ANSYS version 12.1 computer program is being used to analyze the represented three-dimensional model of the cantilever composite beam. This model gives all these outputs, mainly load-displacement behavior of the cantilever end and in the middle span of the simple support part.Keywords: composite steel-concrete beams, external prestressing, finite element analysis, ANSYS
Procedia PDF Downloads 3076487 Comprehensive Machine Learning-Based Glucose Sensing from Near-Infrared Spectra
Authors: Bitewulign Mekonnen
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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network
Procedia PDF Downloads 856486 Accelerating Quantum Chemistry Calculations: Machine Learning for Efficient Evaluation of Electron-Repulsion Integrals
Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty
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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction
Procedia PDF Downloads 1026485 A Study of Blood Alcohol Concentration in People Arrested for Various Offences and Its Demographic Pattern
Authors: Tabin Millo, Khoob Chand, Ashok Kumar Jaiswal
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Introduction: Various kinds of violence and offences are related to alcohol consumption by the offenders. The relationship between alcohol and violence is complex. But its study is important to achieve understanding of violence as well as alcohol related behavior. This study was done to know the blood alcohol concentration in people involved in various offences and its demographic pattern. The study was carried out in the forensic toxicology laboratory, department of Forensic Medicine, All India Institute of Medical Sciences, New Delhi, India. Material and methods: The blood samples were collected from the arrested people shortly after the commission of the offence by the emergency medical officers in the emergency department and forwarded to the forensic toxicology laboratory through the investigating officer. The blood samples were collected in EDTA vial with sodium fluoride preservative. The samples were analyzed by using gas chromatography with head space (GC-HS), which is ideal for alcohol estimation. The toxicology reports were given within a week. The data of seven years (2011-17) were analyzed for its alcohol concentration, associated crimes and its demographic pattern. Analysis and conclusion: Total 280 samples were analyzed in the period of 2011-2017. All were males except one female who was a bar dancer. The maximum cases were in the age group of 21-30 years (124 cases). The type of offences involved were road traffic accidents (RTA), assault cases, drunken driving, drinking in public place, drunk on duty, sexual offence, bestiality, eve teasing, fall etc. The maximum cases were of assault (75 cases) followed by RTA (64 cases). The maximum cases were in the alcohol concentration range of 101-150mg% (58 cases) followed by 51-100mg% (52 cases). The maximum blood alcohol level detected was 391.51 mg%, belonging to a security guard found unconscious. This study shows that alcohol consumption is associated with various kinds of violence and offences in society.Keywords: alcohol, crime, toxicology, violence
Procedia PDF Downloads 1376484 Unveiling the Truth of Female Reproductive Health: The Tied Shackles of Authoritative Knowledge and Domestic Violence: An Ethnographic Study on an Urban Slum of Dhaka City
Authors: Saba Nuzhat
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The present ethnographic study examines how domestic violence and authoritative knowledge affect the reproductive health of females; in terms of contraceptive behavior and induced abortion. This qualitative study has been conducted by collecting in depth informal interviews and case studies of 12 female respondents living in an urban slum of Keraniganj, located Dhaka city. The study depicts how multivariable factors are linked to a woman’s ability to contracept and make abortion decisions in a cultural context where being a wife infers to submission, limited mobility, sexual availability, and restricted autonomy on her own reproduction health. This study shows how violence is being normalized and socially acceptable, every time women do not adhere to go through expected gender roles. The study primarily explores the subjective experiences and perceptions of the females about contraceptive behavior as well as abortions from a medical anthropological perspective. A number of salient examples are highlighted into this paper where women who go through abortion or adopt various measures of contraceptives get highly influenced by authoritative knowledge or under the pressure of male dominance. The lack of female autonomy or prevalence of domestic violence challenges the gender equality of Bangladeshi society and female sovereignty in accessing sexual or reproductive rights. This paper remarks the significance of medical anthropological research that helps to understand the intricate interrelationship between authoritative knowledge and male dominance with female reproductive health in order to reduce women’s risk of experiencing domestic violence and to promote reproductive health autonomy for themselves for espousing contraceptive behaviors and abortion decisions.Keywords: abortion, authoritative knowledge, contraception, domestic violence, reproductive health
Procedia PDF Downloads 1336483 Integrated Imaging Management System: An Approach in the Collaborative Coastal Resource Management of Bagac, Bataan
Authors: Aljon Pangan
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The Philippines being an archipelagic country, is surrounded by coastlines (36,289 km), coastal waters (226,000 km²), oceanic waters (1.93 million km²) and territorial waters (2.2 million km²). Studies show that the Philippine coastal ecosystems are the most productive and biologically diverse in the world, however, plagued by degradation problems due to over-exploitation and illegal activities. The existence of coastal degradation issues in the country led to the emergence of Coastal Resource Management (CRM) as an approach to both national and local government in providing solutions for sustainable coastal resource utilization. CRM applies the idea of planning, implementing and monitoring through the lens of collaborative governance. It utilizes collective action and decision-making to achieve sustainable use of coastal resources. The Municipality of Bagac in Bataan is one of the coastal municipalities in the country who crafts its own CRM Program as a solution to coastal resource degradation and problems. Information and Communications Technology (ICT), particularly Integrated Imaging Management System (IIMS) is one approach that can be applied in the formula of collaborative governance which entails the Government, Private Sector, and Civil Society. IIMS can help policymakers, managers, and citizens in managing coastal resources through analyzed spatial data describing the physical, biological, and socioeconomic characteristics of the coastal areas. Moreover, this study will apply the qualitative approach in deciphering possible impacts of the application of IIMS in the Coastal Resource Management policy making and implementation of the Municipality of Bagac.Keywords: coastal resource management, collaborative governance, integrated imaging management system, information and communication technology
Procedia PDF Downloads 3866482 Ten Patterns of Organizational Misconduct and a Descriptive Model of Interactions
Authors: Ali Abbas
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This paper presents a descriptive model of organizational misconduct based on observed patterns that occur before and after an ethical collapse. The patterns were classified by categorizing media articles in both "for-profit" and "not-for-profit" organizations. Based on the model parameters, the paper provides a descriptive model of various organizational deflection strategies under numerous scenarios, including situations where ethical complaints build-up, situations under which whistleblowers become more prevalent, situations where large scandals that relate to leadership occur, and strategies by which organizations deflect blame when pressure builds up or when media finds out. The model parameters start with the premise of a tolerance to double standards in unethical acts when conducted by leadership or by members of corporate governance. Following this premise, the model explains how organizations engage in discursive strategies to cover up the potential conflicts that arise, including secret agreements and weakening stakeholders who may oppose the organizational acts. Deflection strategies include "preemptive" and "post-complaint" secret agreements, absence of (or vague) documented procedures, engaging in blame and scapegoating, remaining silent on complaints until the media finds out, as well as being slow (if at all) to acknowledge misconduct and fast to cover it up. The results of this paper may be used to guide organizational leaders into the implications of such shortsighted strategies toward unethical acts, even if they are deemed legal. Validation of the model assumptions through numerous media articles is provided.Keywords: ethical decision making, prediction, scandals, organizational strategies
Procedia PDF Downloads 1136481 Assessment of Ecosystem Readiness for Adoption of Circularity: A Multi-Case Study Analysis of Textile Supply Chain in Pakistan
Authors: Azhar Naila, Steuer Benjamin
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Over-exploitation of resources and the burden on natural systems have provoked worldwide concerns about the potential resource as well as supply risks in the future. It has been estimated that the consumption of materials and resources will double by 2060, substantially mounting the amount of waste and emissions produced by individuals, organizations, and businesses, which necessitates sustainable technological innovations to address the problem. Therefore, there is a need to design products and services purposefully for material resource efficiency. This directs us toward the conceptualization and implementation of the ‘Circular Economy (CE),’ which has gained considerable attention among policymakers, researchers, and businesses in the past decade. A large amount of literature focuses on the concept of CE. However, contextual empirical research on the need to embrace CE in an emerging economy like Pakistan is still scarce, where the traditional economic model of take-make-dispose is quite common. Textile exports account for approximately 61% of Pakistan's total exports, and the industry provides employment for about 40% of the country's total industrial workforce. The industry provides job opportunities to above 10 million farmers, with cotton as the main crop of Pakistan. Consumers, companies, as well as the government have explored very limited CE potential in the country. This gap has motivated us to carry out the present study. The study is based on a mixed method approach, for which key informant interviews have been conducted to get insight into the present situation of the ecosystem readiness for the adoption of CE in 20 textile manufacturing industries. The subject study has been conducted on the following areas i) the level of understanding of the CE concept among key stakeholders in the textile manufacturing industry ii) Companies are pushing boundaries to invest in circularity-based initiatives, exploring the depths of risk-taking iii) the current national policy framework support the adoption of CE. Qualitative assessment has been undertaken using MAXQDA to analyze the data received after the key informant interviews. The data has been transcribed and coded for further analysis. The results show that most of the key stakeholders have a clear understanding of the concept, whereas few consider it to be only relevant to the end-of-life treatment of waste generated from the industry. Non-governmental organizations have been observed to be key players in creating awareness among the manufacturing industries. Maximum companies have shown their consent to invest in initiatives related to the adoption of CE. Whereas a few consider themselves far behind the race due to a lack of financial resources and support from responsible institutions. Mostly, the industries have an ambitious vision for integrating CE into the company’s policy but seem not to be ready to take any significant steps to nurture a culture for experimentation. However, the government is not playing any vital role in the transition towards CE; rather, they have been busy with the state’s uncertain political situation. Presently, Pakistan does not have any policy framework that supports the transition towards CE. Acknowledging the present landscape a well-informed CE transition is immediately required.Keywords: circular economy, textile supply chain, textile manufacturing industries, resource efficiency, ecosystem readiness, multi-case study analysis
Procedia PDF Downloads 446480 Equity and Quality in Saudi Early Childhood Education: A Case Study on Inclusion School
Authors: Ahlam A. Alghamdi
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For many years and until now, education based on gendered division is endorsed in the public Saudi schools starting from the primary grades (1,2, 3rd grades). Although preschool has no boys and girls segregation restrictions, children from first grade starting their first form of cultural ideology based on gender. Ensuring high-quality education serving all children -both boys and girls- is an aim for policymakers and early learning professionals in Saudi Arabia. The past five years have witnessed a major change in terms of shifting the paradigm to educating young children in the country. In May 2018, the Ministry of Education (MoE) had declared a commencement decision of inclusion schools serve both girls and boys in primary grades with a high-quality early learning opportunity. This study sought to shed light on one of the earliest schools that have implemented the inclusion experience. The methodological approach adopted is based on the qualitative inquiry of case study to investigate complex phenomena within the contexts of inclusion school. Data collection procedures included on-site visitations and semi-structured interviews with the teachers to document their thoughts, narratives, and living experiences. The findings of this study identified three themes based on cultural, educational, and professional interpretations. An overview of recommendations highlighted the benefits and possible challenges of future implementations of inclusion schools in Saudi Arabia.Keywords: early learning, gender division, inclusion school, Saudi Arabia
Procedia PDF Downloads 1476479 Psychological Distress during the COVID-19 Pandemic in Nursing Students: A Mixed-Methods Study
Authors: Mayantoinette F. Watson
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During such an unprecedented time of the largest public health crisis, the COVID-19 pandemic, nursing students are of the utmost concern regarding their psychological and physical well-being. Questions are emerging and circulating about what will happen to the nursing students and the long-term effects of the pandemic, especially now that hospitals are being overwhelmed with a significant need for nursing staff. Expectations, demands, change, and the fear of the unknown during this unprecedented time can only contribute to the many stressors that accompany nursing students through laborious clinical and didactic courses in nursing programs. The risk of psychological distress is at a maximum, and its effects can negatively impact not only nursing students but also nursing education and academia. The high exposures to interpersonal, economic, and academic demands contribute to the major health concerns, which include a potential risk for psychological distress. Achievement of educational success among nursing students is directly affected by the high exposure to anxiety and depression from experiences within the program. Working relationships and achieving academic success is imperative to positive student outcomes within the nursing program. The purpose of this study is to identify and establish influences and associations within multilevel factors, including the effects of the COVID-19 pandemic on psychological distress in nursing students. Neuman’s Systems Model Theory was used to determine nursing students’ responses to internal and external stressors. The research in this study utilized a mixed-methods, convergent study design. The study population included undergraduate nursing students from Southeastern U.S. The research surveyed a convenience sample of undergraduate nursing students. The quantitative survey was completed by 202 participants, and 11 participants participated in the qualitative follow-up interview surveys. Participants completed the Kessler Psychological Distress Scale (K6), the Perceived Stress Scale (PSS4), and the Dundee Readiness Educational Environment Scale (DREEM12) to measure psychological distress, perceived stress, and perceived educational environment. Participants also answered open-ended questions regarding their experience during the COVID-19 pandemic. Statistical tests, including bivariate analyses, multiple linear regression analyses, and binary logistics regression analyses were performed in effort to identify and highlight the effects of independent variables on the dependent variable, psychological distress. Coding and qualitative content analysis were performed to identify overarching themes within participants’ interviews. Quantitative data were sufficient in identifying correlations between psychological distress and multilevel factors of coping, marital status, COVID-19 stress, perceived stress, educational environment, and social support in nursing students. Qualitative data were sufficient in identifying common themes of students’ perceptions during COVID-19 and included online learning, workload, finances, experience, breaks, time, unknown, support, encouragement, unchanged, communication, and transmission. The findings are significant, specifically regarding contributing factors to nursing students’ psychological distress, which will help to improve learning in the academic environment.Keywords: nursing education, nursing students, pandemic, psychological distress
Procedia PDF Downloads 786478 Assessment of Green Infrastructure for Sustainable Urban Water Management
Authors: Suraj Sharma
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Green infrastructure (GI) offers a contemporary approach for reducing the risk of flooding, improve water quality, and harvesting stormwater for sustainable use. GI promotes landscape planning to enhance sustainable development and urban resilience. However, the existing literature is lacking in ensuring the comprehensive assessment of GI performance in terms of ecosystem function and services for social, ecological, and economical system resilience. We propose a robust indicator set and fuzzy comprehensive evaluation (FCE) for quantitative and qualitative analysis for sustainable water management to assess the capacity of urban resilience. Green infrastructure in urban resilience water management system (GIUR-WMS) supports decision-making for GI planning through scenario comparisons with urban resilience capacity index. To demonstrate the GIUR-WMS, we develop five scenarios for five sectors of Chandigarh (12, 26, 14, 17, and 34) to test common type of GI (rain barrel, rain gardens, detention basins, porous pavements, and open spaces). The result shows the open spaces achieve the highest green infrastructure urban resilience index of 4.22/5. To implement the open space scenario in urban sites, suitable vacant can be converted to green spaces (example: forest, low impact recreation areas, and detention basins) GIUR-WMS is easy to replicate, customize and apply to cities of different sizes to assess environmental, social and ecological dimensions.Keywords: green infrastructure, assessment, urban resilience, water management system, fuzzy comprehensive evaluation
Procedia PDF Downloads 1376477 Investigative Study to Analyze the Impact of Incubator Practices on the Performance of Pakistani Incubation Centers
Authors: Sadaf Zahra Usman
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Business Incubation has become a pervasive phenomenon in numerous parts of the world and is seen as a tool for creating a startup ecosystem. The reason for greatest barriers to the advancement of business incubation centers is the need for an entrepreneurial ecosystem and underdeveloped financial assistance and angel investor networks for startup firms. Business incubation helps in creating successful startup ventures by providing administrative support services and assistance in creating their ventures. We identify incubators into three categories: University incubation centers (UICs), Private incubators (PICs), and Government incubator centers (GICs) to measure the influence of different types of business incubation practices and their performance by using a survey questionnaire from incubation managers across Pakistan. The analysis is conducted on eight Business incubators. Results suggest that the quality of incubation centers is extremely important in this regard. The research anticipated helping policymakers, government officials, and incubation management to utilize business incubation more effectively to “hatch” innovation-based entrepreneurial development.Keywords: entrepreneurship, unemployment, startups, economy, business incubation practice
Procedia PDF Downloads 826476 Entrepreneurial Education in the European Union
Authors: Marko Kolaković, Mladen Turuk
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Entrepreneurship is a valuable discipline important for the competitiveness of the European economy. The European Union's economy is constantly changing, and there is an increased demand for special knowledge and skills to help actors cope in a turbulent business environment. By promoting entrepreneurship in education, the citizens of the European Union are encouraged to be enterprising, innovative, and creative in designing solutions to perceived commercial and social problems in the form of offered products and services created as a result of the entrepreneurial process. The European Union has developed a series of guidelines to encourage entrepreneurship in education and training, and it supports entrepreneurship itself through various activities such as Erasmus + and other programs. A number of tools have been developed to support the development of entrepreneurial spirit among the citizens of the European Union. Special emphasis is placed on the methods of developing creativity, critical thinking, and the development of digital competencies. The aim of this paper is to investigate the initiatives of the European Union in the field of entrepreneurship education and to analyze the concept of entrepreneurship education in selected EU member states. Also, an overview of the desired learning outcomes acquired as a result of the successfully completed entrepreneurship education process will be provided.Keywords: entrepreneurship, entrepreneurial education, EU, croatia
Procedia PDF Downloads 1136475 The Impact of Unemployment on the Sexual Behaviour of Male Youth in Quzini, Eastern Cape, South Africa: A Qualitative Study
Authors: Jabulani Gilford Kheswa
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This paper reports on the effects of unemployment on the sexual behaviour of male youth. Drawing from Jahoda’s deprivation theory, unemployed male youth is prone to psychological distress and as a result, they resort to drugs and alcohol abuse as a way to cope with discrimination. Studies showed that such youth is more inclined to be sexually aggressive and very often engage in criminal activities and risky sexual behaviour such as multiple sexual partners and unprotected sex to cover their feelings of emotional insecurities and negative self-concept. The purpose of the study was to investigate the impact of unemployment on the sexual behaviour of Xhosa- speaking male youth, aged 19-35, from Quzini Location, Eastern Cape, South Africa. A qualitative, explorative, descriptive and contextual design was followed using phenomenological method. The purposively sampled comprised fifteen unemployed males who gave their informed consent to be interviewed. For trustworthiness of the study, the researcher met the Lincoln and Guba’s principles, namely; credibility, dependability confirmability and transferability. The following themes were identified, namely; patriarchy, gender- based violence, drug abuse, stigma and discrimination, criminal activities, depression and low- self-esteem. Based on the findings, the recommendations are that the government and private sectors should create jobs aimed at reducing unemployment for unemployed youth and psycho-educational programmes that will equip them in the areas of sexual values and attitudes, communication and decision-making skills.Keywords: discrimination, male-youth, sex, unemployment
Procedia PDF Downloads 2696474 The Impact of Intelligent Control Systems on Biomedical Engineering and Research
Authors: Melkamu Tadesse Getachew
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Intelligent control systems have revolutionized biomedical engineering, advancing research and enhancing medical practice. This review paper examines the impact of intelligent control on various aspects of biomedical engineering. It analyzes how these systems enhance precision and accuracy in biomedical instrumentation, improving diagnostics, monitoring, and treatment. Integration challenges are addressed, and potential solutions are proposed. The paper also investigates the optimization of drug delivery systems through intelligent control. It explores how intelligent systems contribute to precise dosing, targeted drug release, and personalized medicine. Challenges related to controlled drug release and patient variability are discussed, along with potential avenues for overcoming them. The comparison of algorithms used in intelligent control systems in biomedical control is also reviewed. The implications of intelligent control in computational and systems biology are explored, showcasing how these systems enable enhanced analysis and prediction of complex biological processes. Challenges such as interpretability, human-machine interaction, and machine reliability are examined, along with potential solutions. Intelligent control in biomedical engineering also plays a crucial role in risk management during surgical operations. This section demonstrates how intelligent systems improve patient safety and surgical outcomes when integrated into surgical robots, augmented reality, and preoperative planning. The challenges associated with these implementations and potential solutions are discussed in detail. In summary, this review paper comprehensively explores the widespread impact of intelligent control on biomedical engineering, showing the future of human health issues promising. It discusses application areas, challenges, and potential solutions, highlighting the transformative potential of these systems in advancing research and improving medical practice.Keywords: Intelligent control systems, biomedical instrumentation, drug delivery systems, robotic surgical instruments, Computational monitoring and modeling
Procedia PDF Downloads 346473 Comparative Analysis of Automation Testing Tools
Authors: Amit Bhanushali
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In the ever-changing landscape of software development, automated software testing has emerged as a critical component of the Software Development Life Cycle (SDLC). This research undertakes a comparative study of three major automated testing tools -UFT, Selenium, and RPA- evaluating them on usability, maintenance, and effectiveness. Leveraging existing JAVA-based applications as test cases, the study aims to guide testers in selecting the optimal tool for specific applications. By exploring key features such as source and licensing, testing expenses, object repositories, usability, and language support, the research provides practical insights into UFT, Selenium, and RPA. Acknowledging the pivotal role of these tools in streamlining testing processes amid time constraints and resource limitations, the study assists professionals in making informed choices aligned with their organizational needs.Keywords: software testing tools, software development lifecycle (SDLC), test automation frameworks, automated software, JAVA-based, UFT, selenium and RPA (robotic process automation), source and licensing, object repository
Procedia PDF Downloads 87