Search results for: equation modeling methods
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19343

Search results for: equation modeling methods

9953 Preparation of Essential Oil Capsule (Carum Copticum) In Chitosan Nanoparticles and Investigation of Its Biological Properties

Authors: Akbar Esmaeili, Azadeh Asgari

Abstract:

Essential oils’ unique and practical properties have been widely reported in recent years. Still, the sensitivity of critical oils to environmental factors and their poor solubility in aqueous solutions have limited their use in industries. Therefore, we encapsulated C. copticum essential oil in chitosan nanoparticles by emulsion-ionic gelation with sodium tripolyphosphate and sodium hexametaphosphate cross-linkers. The nanoparticles showed a round shape with an average size of 30-80 nm and a regular distribution. The release profile in the laboratory environment showed a burst in the initial release and then a stable release of C. copticum essential oil from chitosan nanoparticles at different pH. Antioxidant and antibacterial properties of C. copticum essential oil before and after the encapsulation process were evaluated by 2,2-diphenyl-1-picrylhydrazyl radical and disc diffusion methods, respectively. The results showed that the encapsulation of C. copticum essential oil in chitosan nanoparticles could protect its quality and bioactive compounds and improve the properties of the crucial oil.

Keywords: essential oils, Carum copticum, biological activities, nanotechnology

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9952 Taxonomic Classification for Living Organisms Using Convolutional Neural Networks

Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

Abstract:

Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

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9951 Training Engineering Students in Sustainable Development

Authors: Hoong C. Chin, Soon H. Chew, Zhaoxia Wang

Abstract:

Work on sustainable developments and the call for action in education for sustainable development have been ongoing for a number of years. Training engineering students with the relevant competencies, particularly in sustainable development literacy, has been identified as an urgent task in universities. This requires not only a holistic, multi-disciplinary approach to education but also a suitable training environment to develop the needed skills and to inculcate the appropriate attitudes in students towards sustainable development. To demonstrate how this can be done, a module involving an overseas field trip was introduced in 2013 at the National University of Singapore. This paper provides details of the module and describes its training philosophy and methods. Measured against the student learning outcomes, stipulated by the Engineering Accreditation Board, the module scored well on all of them, particularly those related to complex problem solving, environmental and sustainability awareness, multi-disciplinary team work and varied-level communications.

Keywords: civil engineering education, socio-economically sustainable infrastructure, student learning outcome, sustainable development

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9950 Predicting the Impact of Scope Changes on Project Cost and Schedule Using Machine Learning Techniques

Authors: Soheila Sadeghi

Abstract:

In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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9949 Assessment of Microclimate in Abu Dhabi Neighborhoods: On the Utilization of Native Landscape in Enhancing Thermal Comfort

Authors: Maryam Al Mheiri, Khaled Al Awadi

Abstract:

Urban population is continuously increasing worldwide and the speed at which cities urbanize creates major challenges, particularly in terms of creating sustainable urban environments. Rapid urbanization often leads to negative environmental impacts and changes in the urban microclimates. Moreover, when rapid urbanization is paired with limited landscape elements, the effects on human health due to the increased pollution, and thermal comfort due to Urban Heat Island effects are increased. Urban Heat Island (UHI) describes the increase of urban temperatures in urban areas in comparison to its rural surroundings, and, as we discuss in this paper, it impacts on pedestrian comfort, reducing the number of walking trips and public space use. It is thus very necessary to investigate the quality of outdoor built environments in order to improve the quality of life incites. The main objective of this paper is to address the morphology of Emirati neighborhoods, setting a quantitative baseline by which to assess and compare spatial characteristics and microclimate performance of existing typologies in Abu Dhabi. This morphological mapping and analysis will help to understand the built landscape of Emirati neighborhoods in this city, whose form has changed and evolved across different periods. This will eventually help to model the use of different design strategies, such as landscaping, to mitigate UHI effects and enhance outdoor urban comfort. Further, the impact of different native plants types and native species in reducing UHI effects and enhancing outdoor urban comfort, allowing for the assessment of the impact of increasing landscaped areas in these neighborhoods. This study uses ENVI-met, an analytical, three-dimensional, high-resolution microclimate modeling software. This micro-scale urban climate model will be used to evaluate existing conditions and generate scenarios in different residential areas, with different vegetation surfaces and landscaping, and examine their impact on surface temperatures during summer and autumn. In parallel to these simulations, field measurement will be included to calibrate the Envi-met model. This research therefore takes an experimental approach, using simulation software, and a case study strategy for the evaluation of a sample of residential neighborhoods. A comparison of the results of these scenarios constitute a first step towards making recommendations about what constitutes sustainable landscapes for Abu Dhabi neighborhoods.

Keywords: landscape, microclimate, native plants, sustainable neighborhoods, thermal comfort, urban heat island

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9948 ExactData Smart Tool For Marketing Analysis

Authors: Aleksandra Jonas, Aleksandra Gronowska, Maciej Ścigacz, Szymon Jadczak

Abstract:

Exact Data is a smart tool which helps with meaningful marketing content creation. It helps marketers achieve this by analyzing the text of an advertisement before and after its publication on social media sites like Facebook or Instagram. In our research we focus on four areas of natural language processing (NLP): grammar correction, sentiment analysis, irony detection and advertisement interpretation. Our research has identified a considerable lack of NLP tools for the Polish language, which specifically aid online marketers. In light of this, our research team has set out to create a robust and versatile NLP tool for the Polish language. The primary objective of our research is to develop a tool that can perform a range of language processing tasks in this language, such as sentiment analysis, text classification, text correction and text interpretation. Our team has been working diligently to create a tool that is accurate, reliable, and adaptable to the specific linguistic features of Polish, and that can provide valuable insights for a wide range of marketers needs. In addition to the Polish language version, we are also developing an English version of the tool, which will enable us to expand the reach and impact of our research to a wider audience. Another area of focus in our research involves tackling the challenge of the limited availability of linguistically diverse corpora for non-English languages, which presents a significant barrier in the development of NLP applications. One approach we have been pursuing is the translation of existing English corpora, which would enable us to use the wealth of linguistic resources available in English for other languages. Furthermore, we are looking into other methods, such as gathering language samples from social media platforms. By analyzing the language used in social media posts, we can collect a wide range of data that reflects the unique linguistic characteristics of specific regions and communities, which can then be used to enhance the accuracy and performance of NLP algorithms for non-English languages. In doing so, we hope to broaden the scope and capabilities of NLP applications. Our research focuses on several key NLP techniques including sentiment analysis, text classification, text interpretation and text correction. To ensure that we can achieve the best possible performance for these techniques, we are evaluating and comparing different approaches and strategies for implementing them. We are exploring a range of different methods, including transformers and convolutional neural networks (CNNs), to determine which ones are most effective for different types of NLP tasks. By analyzing the strengths and weaknesses of each approach, we can identify the most effective techniques for specific use cases, and further enhance the performance of our tool. Our research aims to create a tool, which can provide a comprehensive analysis of advertising effectiveness, allowing marketers to identify areas for improvement and optimize their advertising strategies. The results of this study suggest that a smart tool for advertisement analysis can provide valuable insights for businesses seeking to create effective advertising campaigns.

Keywords: NLP, AI, IT, language, marketing, analysis

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9947 Winter – Not Spring - Climate Drives Annual Adult Survival in Common Passerines: A Country-Wide, Multi-Species Modeling Exercise

Authors: Manon Ghislain, Timothée Bonnet, Olivier Gimenez, Olivier Dehorter, Pierre-Yves Henry

Abstract:

Climatic fluctuations affect the demography of animal populations, generating changes in population size, phenology, distribution and community assemblages. However, very few studies have identified the underlying demographic processes. For short-lived species, like common passerine birds, are these changes generated by changes in adult survival or in fecundity and recruitment? This study tests for an effect of annual climatic conditions (spring and winter) on annual, local adult survival at very large spatial (a country, 252 sites), temporal (25 years) and biological (25 species) scales. The Constant Effort Site ringing has allowed the collection of capture - mark - recapture data for 100 000 adult individuals since 1989, over metropolitan France, thus documenting annual, local survival rates of the most common passerine birds. We specifically developed a set of multi-year, multi-species, multi-site Bayesian models describing variations in local survival and recapture probabilities. This method allows for a statistically powerful hierarchical assessment (global versus species-specific) of the effects of climate variables on survival. A major part of between-year variations in survival rate was common to all species (74% of between-year variance), whereas only 26% of temporal variation was species-specific. Although changing spring climate is commonly invoked as a cause of population size fluctuations, spring climatic anomalies (mean precipitation or temperature for March-August) do not impact adult survival: only 1% of between-year variation of species survival is explained by spring climatic anomalies. However, for sedentary birds, winter climatic anomalies (North Atlantic Oscillation) had a significant, quadratic effect on adult survival, birds surviving less during intermediate years than during more extreme years. For migratory birds, we do not detect an effect of winter climatic anomalies (Sahel Rainfall). We will analyze the life history traits (migration, habitat, thermal range) that could explain a different sensitivity of species to winter climate anomalies. Overall, we conclude that changes in population sizes for passerine birds are unlikely to be the consequences of climate-driven mortality (or emigration) in spring but could be induced by other demographic parameters, like fecundity.

Keywords: Bayesian approach, capture-recapture, climate anomaly, constant effort sites scheme, passerine, seasons, survival

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9946 Virtual Reality Exposure Therapy for Post-Traumatic Stress Disorder: A Literature Review

Authors: Daniel Azizyan, Marina Vardanyan, Astghik Dallakyan

Abstract:

The objective of this literature review is to bring valuable and much-needed insight into Virtual Reality Exposure Therapy (VRET) for the treatment of Post-Traumatic Stress Disorder (PTSD) among military personnel. As the issues regarding war veterans who suffer from PTSD become more and more widespread, the task of finding possible solutions that would provide alternative approaches to existing methods being used today becomes more relevant than ever. By analyzing the previous applications of VRET, this literature review covers the state of the research done currently on the topic, reviews the known information while identifying the main problems, and aims to use missed opportunities and find potential solutions. It provides the answers to the most relevant questions concerning VRET and leads to important conclusions in the hope of making the technology more practical, widespread, and effective.

Keywords: military PTSD, post-traumatic stress disorder, prolonged exposure, virtual reality exposure therapy, VRE

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9945 Islamophobia: A Study of Unfounded Fear of Islam in Nigeria

Authors: AbdulHameed Badmas Yusuf

Abstract:

Islamophobia is unfounded fear of Islam and, more accurately, of his adherents. This phenomenon has found a fertile terrain in Nigeria given her status as a multireligious society where Muslims and Christians co-exist. Over the years, Islamophobia has taken constitutional, diplomatic, educational, financial, and political dimensions in the country. Any move by Muslims to adhere to their religious dictates, within the constitutional framework, is misconstrued by Christians - their religious counterparts- as a systematic way of Islamizing the country. Against this backdrop, this paper casts a look at Islamophobia from the five dimensions mentioned above. It shall identify possible causes of Islamophobia and proffer solutions accordingly. Available resources as well as events in the recent past reveal that Islamophobia is not unconnected with orientalism and terrorism, which are informed by prejudice and ignorance respectively. As such, the paper suggests adequate knowledge and tolerance as inevitable tools to curtail the menace of Islamophobia. This will go a long way in enhancing mutual tolerance and peaceful co-existence among the adherents of Christianity, Islam, and other religions in Nigeria. Both historical and analytical methods are used in this paper.

Keywords: islamophobia, islam, Nigeria, orientalism, terrorism

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9944 Antimicrobial Activity of Biosynthesized Silver Nanoparticles with Handroanthus Chrysanthus Flower Extract

Authors: Eduardo Padilla, Luis Daniel Rodriguez, Ivan Sanchez, Angelica Sofia Go

Abstract:

The synthesis and application of metallic nanoparticles have increased in recent years. Biological methods go beyond the chemical and physical synthesis that is expensive and not friendly to the environment. Therefore, in this study, silver nanoparticles were synthesized biologically in an environmentally friendly way by Handroanthus chrysanthus flower aqueous extract (AgNPs) that contains phytochemicals capable of reducing silver nitrate. AgNPs were characterized visually by UV-visible spectroscopy and TEM. The antimicrobial activity of the AgNPs was tested by determining the minimum inhibitory concentration (MIC), and minimal bactericidal concentration (MBC) in Escherichia coli and Staphylococcus aureus strains AgNPs showed potent antimicrobial activity against gram-negative and gram-positive bacteria. MIC and MBC values were as low as 41.6, and 83.2 ug/mL using AgNPs biosynthesized by H. chrysanthus flower extract. This nanoparticle could be the basis for the formulation of disinfectants for use in the food and pharmaceutical industry.

Keywords: antimicrobial, silver nanoparticles, flower extract, Handroanthus

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9943 Novel Spoke-Type BLDC Motor Design for Cost Effective and High Power Density

Authors: Suyong Kim

Abstract:

Recently because of the rise in the price of rare earth magnet, interest of non-rare earth or less-rare earth motor is growing. Especially to achieve the high power density, Spoke-Type BLDC (Brushless Permanent Magnet) Motor with ferrite permanent magnet are spotlighted. But Spoke-Type Ferrite BLDC Motor has much of magnetic flux leakage in the direction of rotor shaft. In order to solve this problem, there are two conventional ways. But conventional ways bring the increases of product cost or the decreases of the power density. Therefore, this paper proposes new Spoke-Type BLDC Rotor shape that has the advantages of both conventional methods. The new shape is consists of a one-piece core. The inside and the outside of the rotor are open alternately. So it can take reduced production cost and high power density.

Keywords: motor, BLDC, spoke, ferrite

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9942 The Effect of Irgafos 168 in the Thermostabilization of High Density Polyethylene

Authors: Mahdi Almaky

Abstract:

The thermostabilization of High Density Polyethylene (HDPE) is realized through the action of primary antioxidant such as phenolic antioxidants and secondary antioxidants as aryl phosphates. The efficiency of two secondary antioxidants, commercially named Irgafos 168 and Weston 399, was investigated using different physical, mechanical, spectroscopic, and calorimetric methods. The effect of both antioxidants on the processing stability and long term stability of HDPE produced in Ras Lanuf oil and gas processing Company were measured and compared. The combination of Irgafos 168 with Irganox 1010, as used in smaller concentration, results in a synergetic effect against thermo-oxidation and protect better than the combination of Weston 399 with Irganox 1010 against the colour change at processing temperature and during long term oxidation process.

Keywords: thermostabilization, high density polyethylene, primary antioxidant, phenolic antioxidant, Irgafos 168, Irganox 1010, Weston 399

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9941 Photocatalytic Degradation of Organic Pollutants Using Strontium Titanate Synthesized by Electrospinning Method

Authors: Hui-Hsin Huang, Yi-Feng Lin, Che-Chia Hu

Abstract:

To date, photocatalytic wastewater treatment using solar energy has attracted considerable attention. In this study, strontium titanates with various morphologies, i.e., nanofibers and cubic-like particles, were prepared as photocatalysts using the electrospinning (ES), solid-state (SS), and sol-gel (SG) methods. X-ray diffraction (XRD) analysis showed that ES and SS can be assigned to pure phase SrTiO3, while SG was referred to Sr2TiO4. These samples displayed optical absorption edges at 385-395 nm, indicating they can be activated in UV light irradiation. Scanning electron microscope (SEM) analyses revealed that ES SrTiO3 has a uniform fibrous structure with length and diameter of several microns and 100-200 nm, respectively. After loading of nanoparticulate Ag as a co-catalyst onto the surface of strontium titanates, ES sample exhibited highest photocatalytic activity to degrade methylene orange dye solution in comparison to that of SS and SG ones. These results indicate that Ag-loaded ES SrTiO3, which has a desirable SrTiO3 phase and a facile electron transfer along the preferential direction in fibrous structure, can be a promising photocatalyst.

Keywords: photocatalytic degradation, strontium titanate, electrospinning, co-catalyst

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9940 Estimating Lost Digital Video Frames Using Unidirectional and Bidirectional Estimation Based on Autoregressive Time Model

Authors: Navid Daryasafar, Nima Farshidfar

Abstract:

In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared.

Keywords: error steganography, unidirectional estimation, bidirectional estimation, AR linear estimation

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9939 Right Atrial Tissue Morphology in Acquired Heart Diseases

Authors: Edite Kulmane, Mara Pilmane, Romans Lacis

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Introduction: Acquired heart diseases remain one of the leading health care problems in the world. Changes in myocardium of the diseased hearts are complex and pathogenesis is still not fully clear. The aim of this study was to identify appearance and distribution of apoptosis, homeostasis regulating factors, and innervation and ischemia markers in right atrial tissue in different acquired heart diseases. Methods: During elective open heart surgery were taken right atrial tissue fragments from 12 patients. All patients were operated because of acquired heart diseases- aortic valve stenosis (5 patients), coronary heart disease (5 patients), coronary heart disease and secondary mitral insufficiency (1 patient) and mitral disease (1 patient). The mean age was (mean±SD) 70,2±7,0 years (range 58-83 years). The tissues were stained with haematoxylin and eosin methods for routine light-microscopical examination and for immunohistochemical detection of protein gene peptide 9.5 (PGP 9.5), human atrial natriuretic peptide (hANUP), vascular endothelial growth factor (VEGF), chromogranin A and endothelin. Apoptosis was detected by TUNEL method. Results: All specimens showed degeneration of cardiomyocytes with lysis of myofibrils, diffuse vacuolization especially in perinuclear region, different size of cells and their nuclei. The severe invasion of connective tissue was observed in main part of all fragments. The apoptotic index ranged from 24 to 91%. One specimen showed region of newly performed microvessels with cube shaped endotheliocytes that were positive for PGP 9.5, endothelin, chromogranin A and VEGF. From all fragments, taken from patients with coronary heart disease, there were observed numerous PGP 9.5-containing nerve fibres, except in patient with secondary mitral insufficiency, who showed just few PGP 9.5 positive nerves. In majority of specimens there were regions observed with cube shaped mixed -VEGF immunoreactive endocardial and epicardial cells. Only VEGF positive endothelial cells were observed just in few specimens. There was no significant difference of hANUP secreting cells among all specimens. All patients operated due to the coronary heart disease moderate to numerous number of chromogranin A positive cells were seen while in patients with aortic valve stenosis tissue demonstrated just few factor positive cells. Conclusions: Complex detection of different factors may indicate selectively disordered morphopathogenetical event of heart disease: decrease of PGP 9.5 nerves suggests the decreased innervation of organ; increased apoptosis indicates the cell death without ingrowth of connective tissue; persistent presence of hANUP proves the unchanged homeostasis of cardiomyocytes probably supported by expression of chromogranins. Finally, decrease of VEGF detects the regions of affected blood vessels in heart affected by acquired heart disease.

Keywords: heart, apoptosis, protein-gene peptide 9.5, atrial natriuretic peptide, vascular endothelial growth factor, chromogranin A, endothelin

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9938 Potential Applications and Future Prospects of Zinc Oxide Thin Films

Authors: Temesgen Geremew

Abstract:

ZnO is currently receiving a lot of attention in the semiconductor industry due to its unique characteristics. ZnO is widely used in solar cells, heat-reflecting glasses, optoelectronic bias, and detectors. In this composition, we provide an overview of the ZnO thin flicks' packages, methods of characterization, and implicit operations. They consist of Transmission spectroscopy, Raman spectroscopy, Field emigration surveying electron microscopy, and X-ray diffraction. This review content also demonstrates how ZnO thin flicks function in electrical components for piezoelectric bias, optoelectronics, detectors, and renewable energy sources. Zinc oxide (ZnO) thin films offer a captivating tapestry of possibilities due to their unique blend of electrical, optical, and mechanical properties. This review delves into the realm of their potential applications and future prospects, highlighting the pivotal contributions of research endeavors aimed at tailoring their functionalities.

Keywords: Zinc oxide, raman spectroscopy, thin films, piezoelectric devices

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9937 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries

Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

Abstract:

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

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9936 Development of Extemporaneous Pediatric Syrup of Prednisone

Authors: Amel Chenafa, Sihem Boulenouar, Linda Aoued, Imane Sediri, Ismahan Djebbar, Mohamed Adil Selka

Abstract:

Introduction: The specialties intended for adults are often inadequate marketed for pediatric use, such as for a galenic form or in the dosage. For an industrial, development of a pediatric drug is confronted to various problems. So, the hospital pharmacies have to respond to adaptation needs of pharmaceutical forms for pediatric use. The objective of our work is to develop an oral form of prednisone for pediatric use since no adapted form to children is commercialized. Materials and Methods: Therefore an extemporaneous syrup of prednisone was prepared at the concentration of 0,5mg/ml from 5mg tablets and stored in amber glass bottles. Organoleptic and microbiological stability was studied in two temperatures: 5°C and 25°C, and evaluated at D0, D15, and D30. Results: No organoleptic changes have been detected on the syrup conserved at 25 and 5°C. The results show that there is no presence of bacteria, yeasts, and molds in the syrups stored at both temperatures during the analysis period. Conclusion: Sheltered from light, the developed syrup of prednisone remained stable at room temperature and/or refrigerator for 30 days.

Keywords: extemporaneous syrup, pediatric drug, prednisone, stability

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9935 A Data-Driven Optimal Control Model for the Dynamics of Monkeypox in a Variable Population with a Comprehensive Cost-Effectiveness Analysis

Authors: Martins Onyekwelu Onuorah, Jnr Dahiru Usman

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Introduction: In the realm of public health, the threat posed by Monkeypox continues to elicit concern, prompting rigorous studies to understand its dynamics and devise effective containment strategies. Particularly significant is its recurrence in variable populations, such as the observed outbreak in Nigeria in 2022. In light of this, our study undertakes a meticulous analysis, employing a data-driven approach to explore, validate, and propose optimized intervention strategies tailored to the distinct dynamics of Monkeypox within varying demographic structures. Utilizing a deterministic mathematical model, we delved into the intricate dynamics of Monkeypox, with a particular focus on a variable population context. Our qualitative analysis provided insights into the disease-free equilibrium, revealing its stability when R0 is less than one and discounting the possibility of backward bifurcation, as substantiated by the presence of a single stable endemic equilibrium. The model was rigorously validated using real-time data from the Nigerian 2022 recorded cases for Epi weeks 1 – 52. Transitioning from qualitative to quantitative, we augmented our deterministic model with optimal control, introducing three time-dependent interventions to scrutinize their efficacy and influence on the epidemic's trajectory. Numerical simulations unveiled a pronounced impact of the interventions, offering a data-supported blueprint for informed decision-making in containing the disease. A comprehensive cost-effectiveness analysis employing the Infection Averted Ratio (IAR), Average Cost-Effectiveness Ratio (ACER), and Incremental Cost-Effectiveness Ratio (ICER) facilitated a balanced evaluation of the interventions’ economic and health impacts. In essence, our study epitomizes a holistic approach to understanding and mitigating Monkeypox, intertwining rigorous mathematical modeling, empirical validation, and economic evaluation. The insights derived not only bolster our comprehension of Monkeypox's intricate dynamics but also unveil optimized, cost-effective interventions. This integration of methodologies and findings underscores a pivotal stride towards aligning public health imperatives with economic sustainability, marking a significant contribution to global efforts in combating infectious diseases.

Keywords: monkeypox, equilibrium states, stability, bifurcation, optimal control, cost-effectiveness

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9934 A Minimum Spanning Tree-Based Method for Initializing the K-Means Clustering Algorithm

Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

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The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: degree, initial cluster center, k-means, minimum spanning tree

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9933 The Necessity of Neurolinguistics in Master’s Studies in the English Language Department

Authors: Dielleza Namani, Laureta Kadrijaj-Qerimi

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Neurolinguistics studies the relationship between the brain and language. It is a subject not often found in the syllabus of universities in the Balkans but more spread in Europe and especially the United States of America. The purpose of this study is to see what importance this subject has for studies in the English language department. It contains an analysis of other research papers written regarding neurolinguistics, a questionnaire made for professors and deans at private and public universities in Kosovo, and an interview with a neurolinguistics professor in England. Since this subject is not found in the syllabus of any of the universities in Kosovo, the researchers wanted to find out why this happens but, at the same time, provide reasons why they should consider having it in the future. The results showed that for this subject, there had been researching made, but not enough so far, which gives more information and feedback on why it needs to be in the syllabus, and how linguists can use the knowledge they receive from this subject in their workplace. Also, the professors and deans see this subject as too medical for their students to learn and not necessary for their future jobs. Hopefully, in the near future, there will be more research done on why this is important and how English language students can benefit from it.

Keywords: English language department, neurolinguistics, second language acquisition, teaching methods

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9932 Barriers of Successful Employment of Individuals with Mild Intellectual Disabilities

Authors: Mubarak Aldosari

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The focus of this qualitative study was to explore the main barriers of successful employment of individuals with intellectual disabilities (ID). Methods: The semi-structured interviews were used to explore perception of a sample of eight managers/supervisors of employees who had ID regarding the main barriers that face successful employment of individuals with ID. Results: Thematic analysis of the interviews revealed four major themes that impede successful employment of individuals with ID: experiences of work, (b) social skills, (c) attitudes to individuals with ID, and (d) transportation. Conclusion: The current study was designed to provide important information to policymakers, officials, educators and parents regarding the challenges and barriers that face the successful employment of individuals with ID. The study show the importance of the support as well as effective and planned preparation for individuals with ID during schools to be qualified and have skills that they to be successful in the employment. Additionally, the results of this study will encourage further study of transition to post schools for individuals with ID in Saudi Arabia.

Keywords: barriers, employment, individuals with mild intellectual disabilities, social skills

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9931 Delivery of Sustainable Construction in South Africa – Assessing the Roles of Organisational Leadership

Authors: Ayodeji Emmanuel Oke, Mathew O. Ikuabe, Clinton O. Aigbavboa, Douglas O. Aghimien

Abstract:

The call for sustainable construction has received significant drive in recent time considering the overwhelming impacts of its adoption. However, not much has been deliberated on this subject with regards to the roles of organisational leadership in delivering sustainable construction. To this end, the study empirically scrutinised the roles of organisational leadership in delivering sustainable construction. The study adopted a quantitative approach while construction professionals formed the population of the study. A well-articulated questionnaire was used in eliciting responses from the respondents, while appropriate methods of data analysis were used. Findings from the study depicted that the major role of organisational leadership in the delivery of sustainable construction is acting as sustainability integrators. Equally revealed are the internal and external factors affecting organisational leadership in delivering sustainable construction. The study concluded by emphasizing the core roles for delivering sustainable construction by organisational leadership and further recommended that sustainable construction should serve as a prominent and focal organisation goal by organisational leadership when steering the organisation towards meeting its objectives

Keywords: organisational leadership, project delivery, roles, sustainable construction

Procedia PDF Downloads 103
9930 Simultaneous Determination of Some Phenolic Pesticides in Environmental and Biological Samples

Authors: Yasmeen F. Pervez, Etesh K. Janghel, Santosh Kumar Sar

Abstract:

Simple and sensitive analytical thermal gradient-thin layer chromatography technique has been developed for the simultaneous determination of phenolic pesticides like carbaryl, propoxur and carbofuran. It is based on the differential migration of colored derivatives formed by the reaction of hydrolysed phenolic compound with diazotized 3, 4 dimethyl aniline on a silica gel plate. Quantitative evaluation of hydrolyzed phenolic compound is made by visual comparison of intensities of color by spectrophotometry. The color system obeys Beer’s law in the following working range in ppm : carbaryl, 0.5-6.6; propoxur, 0.8-7.2; and carbofuran, 0.2-3.3 respectively. The Molar absorptivity, Sandell’s sensitivity, Correlation coefficient have been determined. The effects of analytical parameters on migration and analysis have been evaluated. The methods are highly reproducible and have been successfully applied to determination of phenolic pesticides in environmental and biological samples.

Keywords: phenolic pesticides (carbaryl, propoxur and carbofuran), 3.4 dimethyl aniline, environmental, biological samples

Procedia PDF Downloads 391
9929 Application of Metroxylon Sagu Waste in Textile Process

Authors: Nazlina Shaari

Abstract:

Sustainability is economic, social and environmental systems that make up the community in providing a healthy, productive, meaningful life for all community residents, present and future. The environmental profile of goods and services that satisfy our individual and societal needs were shaped by design activities. The integration of environmental aspect of product design, especially in textiles present much confusion surrounds the incorporation of environmental objectives into the design process. This paper explores the effective use of waste materials that can contribute to the development of more environmentally responsible practice in textile sector. It introduces key elements of the ecological approach and innovative ideas from waste to wealth. The paper focuses on the potential methods of utilizing sago residue as a natural colour enhancer in natural dyeing process. It will discover the potential of waste materials to be fully utilized to attempt to make the production of that textile more environmentally friendly.

Keywords: sustainability, textiles, waste materials, environmentally friendly

Procedia PDF Downloads 297
9928 Data Poisoning Attacks on Federated Learning and Preventive Measures

Authors: Beulah Rani Inbanathan

Abstract:

In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

Procedia PDF Downloads 73
9927 Design of Intelligent Scaffolding Learning Management System for Vocational Education

Authors: Seree Chadcham, Niphon Sukvilai

Abstract:

This study is the research and development which is intended to: 1) design of the Intelligent Scaffolding Learning Management System (ISLMS) for vocational education, 2) assess the suitability of the Design of Intelligent Scaffolding Learning Management System for Vocational Education. Its methods are divided into 2 phases. Phase 1 is the design of the ISLMS for Vocational Education and phase 2 is the assessment of the suitability of the design. The samples used in this study are work done by 15 professionals in the field of Intelligent Scaffolding, Learning Management System, Vocational Education, and Information and Communication Technology in education selected using the purposive sampling method. Data analyzed by arithmetic mean and standard deviation. The results showed that the ISLMS for vocational education consists of 2 main components which are: 1) the Intelligent Learning Management System for Vocational Education, 2) the Intelligent Scaffolding Management System. The result of the system suitability assessment from the professionals is in the highest range.

Keywords: intelligent, scaffolding, learning management system, vocational education

Procedia PDF Downloads 785
9926 Preparation of Nanocomposites Based on Biodegradable Polycaprolactone by Melt Mixture

Authors: Mohamed Amine Zenasni, Bahia Meroufel, André Merlin, Said Benfarhi, Stéphane Molina, Béatrice George

Abstract:

The introduction of nano-fillers into polymers field lead to the creation of the nano composites. This creation is starting up a new revolution into the world of materials. Nano composites are similar to traditional composite of a polymer blend and filler with at least one nano-scopic dimension. In our project, we worked with nano composites of biodegradable polymer: polycaprolactone, combined with nano-clay (Maghnite) and with different nano-organo-clays. These nano composites have been prepared by melt mixture method. The advantage of this polymer is its degradability and bio compatibility. A study of the relationship between development, micro structure and physico chemical properties of nano composites, clays modified with 3-aminopropyltriethoxysilane (APTES) and Hexadecyltriméthy ammonium bromide (CTAB) and untreated clays were made. Melt mixture method is most suitable methods to get a better dispersion named exfoliation.

Keywords: nanocomposite, biodegradable, polycaprolactone, maghnite, melt mixture, APTES, CTAB

Procedia PDF Downloads 417
9925 Development of a Congestion Controller of Computer Network Using Artificial Intelligence Algorithm

Authors: Mary Anne Roa

Abstract:

Congestion in network occurs due to exceed in aggregate demand as compared to the accessible capacity of the resources. Network congestion will increase as network speed increases and new effective congestion control methods are needed, especially for today’s very high speed networks. To address this undeniably global issue, the study focuses on the development of a fuzzy-based congestion control model concerned with allocating the resources of a computer network such that the system can operate at an adequate performance level when the demand exceeds or is near the capacity of the resources. Fuzzy logic based models have proven capable of accurately representing a wide variety of processes. The model built is based on bandwidth, the aggregate incoming traffic and the waiting time. The theoretical analysis and simulation results show that the proposed algorithm provides not only good utilization but also low packet loss.

Keywords: congestion control, queue management, computer networks, fuzzy logic

Procedia PDF Downloads 378
9924 Prioritizing The Evaluation factors of Hospital Information System with The Analytical Hierarchy Process

Authors: F.Sadoughi, A. Sarsarshahi, L, Eerfannia, S.M.A. Khatami

Abstract:

Hospital information systems with lots of ability would lead to health care quality improvement. Evaluation of this system has done according different method and criteria. The main goal of present study is to prioritize the most important factors which are influence these systems evaluation. At the first step, according relevant literature, three main factor and 29 subfactors extracted. Then, study framework was designed. Based on analytical hierarchical process (AHP), 28 paired comparisons with Saaty range, in a questionnaire format obtained. Questionnaires were filled by 10 experts in health information management and medical informatics field. Human factors with weight of 0.55 were ranked as the most important. Organization (0.25) and technology (0.14) were in next place. It seems MADM methods such as AHP have enough potential to use in health research and provide positive opportunities for health domain decision makers.

Keywords: Analytical hierarchy process, Multiple criteria decision-making (MCDM), Hospital information system, Evaluation factors

Procedia PDF Downloads 440