Search results for: full reference image quality assessment (FR-IQA)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20219

Search results for: full reference image quality assessment (FR-IQA)

17969 The Adoption of Process Management for Accounting Information Systems in Thailand

Authors: Manirath Wongsim

Abstract:

Information Quality (IQ) has become a critical, strategic issue in Accounting Information Systems (AIS) adoption. In order to implement AIS adoption successfully, it is important to consider the quality of information use throughout the adoption process, which seriously impacts the effectiveness of AIS adoption practice and the optimization of AIS adoption decisions. There is a growing need for research to provide insights into issues and solutions related to IQ in AIS adoption. The need for an integrated approach to improve IQ in AIS adoption, as well as the unique characteristics of accounting data, demands an AIS adoption specific IQ framework. This research aims to explore ways of managing information quality and AIS adoption to investigate the relationship between the IQ issues and AIS adoption process. This study has led to the development of a framework for understanding IQ management in AIS adoption. This research was done on 44 respondents as ten organisations from manufacturing firms in Thailand. The findings of the research’s empirical evidence suggest that IQ dimensions in AIS adoption to provide assistance in all process of decision making. This research provides empirical evidence that information quality of AIS adoption affect decision making and suggests that these variables should be considered in adopting AIS in order to improve the effectiveness of AIS.

Keywords: information quality, information quality dimensions, accounting information systems, accounting information system adoption

Procedia PDF Downloads 471
17968 Intelligent Rheumatoid Arthritis Identification System Based Image Processing and Neural Classifier

Authors: Abdulkader Helwan

Abstract:

Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

Procedia PDF Downloads 537
17967 Early Detection of Breast Cancer in Digital Mammograms Based on Image Processing and Artificial Intelligence

Authors: Sehreen Moorat, Mussarat Lakho

Abstract:

A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

Procedia PDF Downloads 265
17966 Similarity Based Retrieval in Case Based Reasoning for Analysis of Medical Images

Authors: M. Dasgupta, S. Banerjee

Abstract:

Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients.

Keywords: case based reasoning, exudates, retina image, similarity based retrieval

Procedia PDF Downloads 350
17965 The Effect of Addition of White Mulberry Fruit on the Sensory Quality of the New Developed Bioactive Bread

Authors: Kmiecik Dominik, Kobus-Cisowska Joanna, Gramza-Michalowska Anna, Marcinkowska Agata, Korczak Józef

Abstract:

The relationship between the choice of a proper diet, a diet, lifestyle man and his health has been known for a long time. Because of the increase in public awareness of food ingredients and their influence on health status, measures have been taken towards the production of food, which is designed to not only eat, but also to protect against the incidence of lifestyle diseases. For this purpose, the bio active products with healthy properties was developed. Mulberry have a very high nutritional value, rich in chemical composition and many properties used in the prevention of lifestyle diseases. In addition to basic chemical components, nutrients, mulberry fruit contain compounds having a physiological effect. The aim of this study was to assess the effect of white mulberry fruit on the sensory quality of bread to be healthy diet of people suffering from anemia, diabetes, obesity and cardiovascular disease. Sensory analysis was carried out by the profile method. Intra-operative differentiators color, aroma, taste, texture, and overall assessment. Sensory analysis showed that all test trials were characterized by a uniform and concise consistency, similar in color from dark to light beige. The taste and smell of herbal characteristic was designed in an attempt to prevention of diabetes, while the other samples were characterized by a typical taste and smell of bread grain. There were no foreign taste and odor in the test bread. It was found that the addition of white mulberry fruit does not affect the sensory quality of the newly developed bioactive bread.

Keywords: mulberry, bread, bioactive, sensory analysis

Procedia PDF Downloads 466
17964 Use of Machine Learning Algorithms to Pediatric MR Images for Tumor Classification

Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

Abstract:

Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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17963 Towards Understanding the Notions of Quality Education among Internationally-Accredited Christian Schools in Southeast Asia

Authors: Selaphares Jatico Tajale

Abstract:

This research aims to understand the notions of quality education by conducting case studies among internationally-accredited Christian schools in Southeast Asia. Five internationally-accredited Christian schools from Cambodia, Indonesia, Malaysia, The Philippines, and Singapore will be chosen as cases for this study. This study will utilize the processes of interviews, filling up of questionnaires, and writing of reflections in order to obtain data and relevant information. These processes will be conducted through multi-sectoral respondents such as administrators, academic heads, and faculty. This study employs five aspects within the realm of education as guides in the formulation of questionnaire and guide questions in the interview, namely: a) school context, b) classroom, c) quality assurance, d) stakeholders, e) faculty and staff. Guide interview questions and questions in the questionnaires are formulated to uncover information on how those five aspects were managed to achieve desired student learning outcomes and uncover other information useful for the study.

Keywords: internationally-accredited, notions of quality education, quality education, quality education in Southeast Asia

Procedia PDF Downloads 244
17962 From Biowaste to Biobased Products: Life Cycle Assessment of VALUEWASTE Solution

Authors: Andrés Lara Guillén, José M. Soriano Disla, Gemma Castejón Martínez, David Fernández-Gutiérrez

Abstract:

The worldwide population is exponentially increasing, which causes a rising demand for food, energy and non-renewable resources. These demands must be attended to from a circular economy point of view. Under this approach, the obtention of strategic products from biowaste is crucial for the society to keep the current lifestyle reducing the environmental and social issues linked to the lineal economy. This is the main objective of the VALUEWASTE project. VALUEWASTE is about valorizing urban biowaste into proteins for food and feed and biofertilizers, closing the loop of this waste stream. In order to achieve this objective, the project validates three value chains, which begin with the anaerobic digestion of the biowaste. From the anaerobic digestion, three by-products are obtained: i) methane that is used by microorganisms, which will be transformed into microbial proteins; ii) digestate that is used by black soldier fly, producing insect proteins; and iii) a nutrient-rich effluent, which will be transformed into biofertilizers. VALUEWASTE is an innovative solution, which combines different technologies to valorize entirely the biowaste. However, it is also required to demonstrate that the solution is greener than other traditional technologies (baseline systems). On one hand, the proteins from microorganisms and insects will be compared with other reference protein production systems (gluten, whey and soybean). On the other hand, the biofertilizers will be compared to the production of mineral fertilizers (ammonium sulphate and synthetic struvite). Therefore, the aim of this study is to provide that biowaste valorization can reduce the environmental impacts linked to both traditional proteins manufacturing processes and mineral fertilizers, not only at a pilot-scale but also at an industrial one. In the present study, both baseline system and VALUEWASTE solution are evaluated through the Environmental Life Cycle Assessment (E-LCA). The E-LCA is based on the standards ISO 14040 and 14044. The Environmental Footprint methodology was the one used in this study to evaluate the environmental impacts. The results for the baseline cases show that the food proteins coming from whey have the highest environmental impact on ecosystems compared to the other proteins sources: 7.5 and 15.9 folds higher than soybean and gluten, respectively. Comparing feed soybean and gluten, soybean has an environmental impact on human health 195.1 folds higher. In the case of biofertilizers, synthetic struvite has higher impacts than ammonium sulfate: 15.3 (ecosystems) and 11.8 (human health) fold, respectively. The results shown in the present study will be used as a reference to demonstrate the better environmental performance of the bio-based products obtained through the VALUEWASTE solution. Other originalities that the E-LCA performed in the VALUEWASTE project provides are the diverse direct implications on investment and policies. On one hand, better environmental performance will serve to remove the barriers linked to these kinds of technologies, boosting the investment that is backed by the E-LCA. On the other hand, it will be a germ to design new policies fostering these types of solutions to achieve two of the key targets of the European Community: being self-sustainable and carbon neutral.

Keywords: anaerobic digestion, biofertilizers, circular economy, nutrients recovery

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17961 Harmonic Assessment and Mitigation in Medical Diagonesis Equipment

Authors: S. S. Adamu, H. S. Muhammad, D. S. Shuaibu

Abstract:

Poor power quality in electrical power systems can lead to medical equipment at healthcare centres to malfunction and present wrong medical diagnosis. Equipment such as X-rays, computerized axial tomography, etc. can pollute the system due to their high level of harmonics production, which may cause a number of undesirable effects like heating, equipment damages and electromagnetic interferences. The conventional approach of mitigation uses passive inductor/capacitor (LC) filters, which has some drawbacks such as, large sizes, resonance problems and fixed compensation behaviours. The current trends of solutions generally employ active power filters using suitable control algorithms. This work focuses on assessing the level of Total Harmonic Distortion (THD) on medical facilities and various ways of mitigation, using radiology unit of an existing hospital as a case study. The measurement of the harmonics is conducted with a power quality analyzer at the point of common coupling (PCC). The levels of measured THD are found to be higher than the IEEE 519-1992 standard limits. The system is then modelled as a harmonic current source using MATLAB/SIMULINK. To mitigate the unwanted harmonic currents a shunt active filter is developed using synchronous detection algorithm to extract the fundamental component of the source currents. Fuzzy logic controller is then developed to control the filter. The THD without the active power filter are validated using the measured values. The THD with the developed filter show that the harmonics are now within the recommended limits.

Keywords: power quality, total harmonics distortion, shunt active filters, fuzzy logic

Procedia PDF Downloads 480
17960 Notions of Criticality in Strategic Management of Hospitality Services in Nigeria

Authors: Chigozie P. Ugochukwu Okoro

Abstract:

While the needs of the traveling public are becoming more evolving due to the ever-changing tourism ecosphere; there is a seeming inability to sustain competitive advantage through hospitality enterprise service quality differentials and effective service delivery. Contending with these evolving needs demands a re-assessment of the notions that drive service evolvement thoughts pattern and service delivery processes management in the hospitality enterprise. The intent of this study was to explicate the trends of the evolving needs of the traveling public that are critical to hospitality enterprise service management. The hypothetical study used customer satisfaction to dissect the strategic implication of perception, experience, and socio-cultural engagements in customization of hospitality enterprise services. The study found out that customer perception is cognitive and does not shape service customization. The study also elucidated that customer experience which can be evaluated, is critical in service structure determination and delivery. Socio-cultural engagement is intrinsic in driving service diversification. The study recommends tourists’ audit and cognitive insights as strategic actions for re-designing service efficiency and delivery in hospitality enterprise service management.

Keywords: hospitality enterprise services, strategic management, quality service delivery, notions of criticality

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17959 Ultrasonographic Study of Normal Scapula in Horse

Authors: Mohamad Saeed Ahrari-Khafi, Abutorab Tabatabai-Naini, Niloofar Ajvadi

Abstract:

Scapular fracture is not common in horses, due to the proper protection of scapular muscles. However, if it happens, it can cause lameness in horses. Because of the overlapping of the scapula on the contralateral scapula and the thorax, usually radiography cannot be helpful in evaluation, except in small amount of its ventral part. Although ultrasonography is mainly used for diagnosis of soft tissue injuries, it also can be used for evaluation of bone surface abnormalities. This study was intended to document the normal ultrasonographic appearance of the equine scapula. Right forelimb of six horses was used. To facilitate the image assessment, a zoning system was developed. Ultrasonography was performed by using a 5-11 MHz linear array transducer. Ultrasonographic anatomy of scapula in different parts and planes was imaged and documented, hoping to help practitioners to diagnose fractures and injuries. Results showed that ultrasonography is capable to depict different parts of the scapula and regional muscles, and can be used for detecting fractures and other abnormalities.

Keywords: horse, scapula, scapular fracture, ultrasonography

Procedia PDF Downloads 311
17958 An Overview of Sustainable Development for Greening Roadmap in Asia

Authors: Robby Dwiko Juliardi, Queena K. Qian

Abstract:

Economic, environmental, and human considerations, as sustainable building design principles, are to be balanced and integrated into building design strategy. Building codes often suggest the efficient and sustainable building products, such as energy-efficient fixtures. However, building departments sometimes fail to manage the full range of requirements in the building assessment, such as siting, neighborhood proximity, and public facility, etc. Hence, it shows roadmap develops the future, an extended look at the future of a chosen field of inquiry composed from the collective knowledge and imagination of the brightest drivers of change in that field. This paper is taken from the best practice of green building implementation in a few countries of Asia (China, Malaysia, and India). Sustainable development will be presented on developing the roadmap of sustainability development of a country. Findings on the similarities and dissimilarities of those countries will show: (1) A general knowledge development on the sustainable green roadmap in Asia, (2) What are the components of developing the roadmap, and (3) What affects the government regulation in a political ecology.

Keywords: developing roadmap, green building, political ecology, sustainable development

Procedia PDF Downloads 321
17957 Gap Analysis of Service Quality: The Veterinary Teaching Hospital, University of Peradeniya, Sri Lanka

Authors: Preethi Sudarshanie Dassanayake, R. A. Sudath Weerasiri

Abstract:

Objective: The objective of this study were to find out highest expectation and perception,highest gap between perception and expectation of service quality, and to find out such gaps between perception and expectation with regard to service quality dimensions were whether statistically significant. Methodology: This study carried out at the Out Patient Department (OPD) of the Veterinary Teaching Hospital (VTH), University of Peradeniya. Modified version of SERVQUAL with 22-pairs of items regarding expectation and perception of service quality in dimensions of tangible, reliability, responsiveness, assurance and empathy were included in Part 1 and the Part 2 of the questionnaire consisted of questions regarding socio-demographic factors. Sample size was 200 and sampling procedure was Systematic Random Sampling. Customers above 18 years of age, able to read, write and understand Sinhala or English language, visits more than twice in last six months and who willing to respond were selected. Findings: The analysis revealed customers expectations of service higher than the perceived for all 22- items of the SERVQUAL. This high expectation suggests that there is sufficient room for further improvement of service quality in all five dimensions. Originality/Value of the Paper: This study gave a new insight for poorly researched area of veterinary health service quality in Sri Lankan context. It provides hospital administrators and policy makers to develop strategies for further improvement of service quality according to customers' view.

Keywords: expectation, perception, service quality, SERVQUAL, veterinary health care

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17956 A Tool for Assessing Performance and Structural Quality of Business Process

Authors: Mariem Kchaou, Wiem Khlif, Faiez Gargouri

Abstract:

Modeling business processes is an essential task when evaluating, improving, or documenting existing business processes. To be efficient in such tasks, a business process model (BPM) must have high structural quality and high performance. Evidently, evaluating the performance of a business process model is a necessary step to reduce time, cost, while assessing the structural quality aims to improve the understandability and the modifiability of the BPMN model. To achieve these objectives, a set of structural and performance measures have been proposed. Since the diversity of measures, we propose a framework that integrates both structural and performance aspects for classifying them. Our measure classification is based on business process model perspectives (e.g., informational, functional, organizational, behavioral, and temporal), and the elements (activity, event, actor, etc.) involved in computing the measures. Then, we implement this framework in a tool assisting the structural quality and the performance of a business process. The tool helps the designers to select an appropriate subset of measures associated with the corresponding perspective and to calculate and interpret their values in order to improve the structural quality and the performance of the model.

Keywords: performance, structural quality, perspectives, tool, classification framework, measures

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17955 A Nonlinear Parabolic Partial Differential Equation Model for Image Enhancement

Authors: Tudor Barbu

Abstract:

We present a robust nonlinear parabolic partial differential equation (PDE)-based denoising scheme in this article. Our approach is based on a second-order anisotropic diffusion model that is described first. Then, a consistent and explicit numerical approximation algorithm is constructed for this continuous model by using the finite-difference method. Finally, our restoration experiments and method comparison, which prove the effectiveness of this proposed technique, are discussed in this paper.

Keywords: anisotropic diffusion, finite differences, image denoising and restoration, nonlinear PDE model, anisotropic diffusion, numerical approximation schemes

Procedia PDF Downloads 315
17954 Employees’ Work Performance Quality Development for Organizational Competency

Authors: Pornpong Porpraphant

Abstract:

This paper aimed to demonstrate how work performance quality development activity carried out for employees in an organization could lead to the organizational success and competency as a whole. The case studies selected for this research were the Thai huge corporate including Siam Cement Group or SCG, PTT Public Company Limited, and Electricity Generating Authority of Thailand or EGAT. The in- depth interview was applied with the three main groups that included the facilitator group, the managerial group, and the operational officer group. The Plan- Do- Check- Act approach was also utilized as to build up a conceptual model in corporate management that fostered employees’ knowledge acquisition, resulting in an improved work performance.

Keywords: high performance organization, quality, work performance quality development

Procedia PDF Downloads 297
17953 Changing Trends and Attitudes towards Online Assessment

Authors: Renáta Nagy, Alexandra Csongor, Jon Marquette, Vilmos Warta

Abstract:

The presentation aims at eliciting insight into the results of ongoing research regarding evolving trends and attitudes towards online assessment of English for Medical Purposes. The focus pinpointsonline as one of the most trending formsavailable during the global pandemic. The study was first initiated in 2019 in which its main target was to reveal the intriguing question of students’ and assessors’ attitudes towards online assessment. The research questions the attitudes towards the latest trends, possible online task types, their advantagesand disadvantages through an in-depth experimental process currently undergoing implementation. Material and methods include surveys, needs and wants analysis, and thorough investigations regarding candidates’ and assessors’ attitudes towards online tests in the field of Medicine. The examined test tasks include various online tests drafted in both English and Hungarian by student volunteers at the Medical School of the University of Pécs, Hungary. Over 400 respondents from more than 28 countries participated in the survey, which gives us an international and intercultural insight into how students with different cultural and educational background deal with the evolving online world. The results show the pandemic’s impact, which brought the slumbering online world of assessing roaring alive, fully operational andnowbearsphenomenalrelevancein today’s global education. Undeniably, the results can be used as a perspective in a vast array of contents. The survey hypothesized the generation of the 21st century expect everything readily available online, however, questions whether they are ready for this challenge are lurking in the background.

Keywords: assessment, changes, english, ESP, online assessment, online, trends

Procedia PDF Downloads 208
17952 Investigation of Elastic Properties of 3D Full Five Directional (f5d) Braided Composite Materials

Authors: Apeng Dong, Shu Li, Wenguo Zhu, Ming Qi, Qiuyi Xu

Abstract:

The primary objective of this paper is to focus on the elasticity properties of three-dimensional full five directional (3Df5d) braided composite. A large body of research has been focused on the 3D four directional (4d) and 3D five directional (5d) structure but not much research on the 3Df5d material. Generally, the influence of the yarn shape on mechanical properties of braided materials tends to be ignored, which makes results too ideal. Besides, with the improvement of the computational ability, people are accustomed to using computers to predict the material parameters, which fails to give an explicit and concise result facilitating production and application. Based on the traditional mechanics, this paper firstly deduced the functional relation between elasticity properties and braiding parameters. In addition, considering the actual shape of yarns after consolidation, the longitudinal modulus is modified and defined practically. Firstly, the analytic model is established based on the certain assumptions for the sake of clarity, this paper assumes that: A: the cross section of axial yarns is square; B: The cross section of braiding yarns is hexagonal; C: the characters of braiding yarns and axial yarns are the same; D: The angle between the structure boundary and the projection of braiding yarns in transverse plane is 45°; E: The filling factor ε of composite yarns is π/4; F: The deformation of unit cell is under constant strain condition. Then, the functional relation between material constants and braiding parameters is systematically deduced aimed at the yarn deformation mode. Finally, considering the actual shape of axial yarns after consolidation, the concept of technology factor is proposed and the longitudinal modulus of the material is modified based on the energy theory. In this paper, the analytic solution of material parameters is given for the first time, which provides a good reference for further research and application for 3Df5d materials. Although the analysis model is established based on certain assumptions, the analysis method is also applicable for other braided structures. Meanwhile, it is crucial that the cross section shape and straightness of axial yarns play dominant roles in the longitudinal elastic property. So in the braiding and solidifying process, the stability of the axial yarns should be guaranteed to increase the technology factor to reduce the dispersion of material parameters. Overall, the elastic properties of this materials are closely related to the braiding parameters and can be strongly designable, and although the longitudinal modulus of the material is greatly influenced by the technology factors, it can be defined to certain extent.

Keywords: analytic solution, braided composites, elasticity properties, technology factor

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17951 Accurate Mass Segmentation Using U-Net Deep Learning Architecture for Improved Cancer Detection

Authors: Ali Hamza

Abstract:

Accurate segmentation of breast ultrasound images is of paramount importance in enhancing the diagnostic capabilities of breast cancer detection. This study presents an approach utilizing the U-Net architecture for segmenting breast ultrasound images aimed at improving the accuracy and reliability of mass identification within the breast tissue. The proposed method encompasses a multi-stage process. Initially, preprocessing techniques are employed to refine image quality and diminish noise interference. Subsequently, the U-Net architecture, a deep learning convolutional neural network (CNN), is employed for pixel-wise segmentation of regions of interest corresponding to potential breast masses. The U-Net's distinctive architecture, characterized by a contracting and expansive pathway, enables accurate boundary delineation and detailed feature extraction. To evaluate the effectiveness of the proposed approach, an extensive dataset of breast ultrasound images is employed, encompassing diverse cases. Quantitative performance metrics such as the Dice coefficient, Jaccard index, sensitivity, specificity, and Hausdorff distance are employed to comprehensively assess the segmentation accuracy. Comparative analyses against traditional segmentation methods showcase the superiority of the U-Net architecture in capturing intricate details and accurately segmenting breast masses. The outcomes of this study emphasize the potential of the U-Net-based segmentation approach in bolstering breast ultrasound image analysis. The method's ability to reliably pinpoint mass boundaries holds promise for aiding radiologists in precise diagnosis and treatment planning. However, further validation and integration within clinical workflows are necessary to ascertain their practical clinical utility and facilitate seamless adoption by healthcare professionals. In conclusion, leveraging the U-Net architecture for breast ultrasound image segmentation showcases a robust framework that can significantly enhance diagnostic accuracy and advance the field of breast cancer detection. This approach represents a pivotal step towards empowering medical professionals with a more potent tool for early and accurate breast cancer diagnosis.

Keywords: mage segmentation, U-Net, deep learning, breast cancer detection, diagnostic accuracy, mass identification, convolutional neural network

Procedia PDF Downloads 88
17950 Translation and Adaptation of the Assessment Instrument “Kiddycat” for European Portuguese

Authors: Elsa Marta Soares, Ana Rita Valente, Cristiana Rodrigues, Filipa Gonçalves

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Background: The assessment of feelings and attitudes of preschool children in relation to stuttering is crucial. Negative experiences can lead to anxiety, worry or frustration. To avoid the worsening of attitudes and feelings related to stuttering, it is important the early detection in order to intervene as soon as possible through an individualized intervention plan. Then it is important to have Portuguese instruments that allow this assessment. Aims: The aim of the present study is to realize the translation and adaptation of the Communication Attitude Test for Children in Preschool Age and Kindergarten (KiddyCat) for EP. Methodology: For the translation and adaptation process, a methodological study was carried out with the following steps: translation, back translation, assessment by a committee of experts and pre-test. This abstract describes the results of the first two phases of this process. The translation was accomplished by two bilingual individuals without experience in health and any knowledge about the instrument. One of them was an English teacher and the other one a Translator. The back-translation was conducted by two Senior Class Teachers that live in United Kingdom without any knowledge in health and about the instrument. Results and Discussion: In translation there were differences in semantic equivalences of various expressions and concepts. A discussion between the two translators, mediated by the researchers, allowed to achieve the consensus version of the translated instrument. Taking into account the original version of KiddyCAT the results demonstrated that back-translation versions were similar to the original version of this assessment instrument. Although the back-translators used different words, they were synonymous, maintaining semantic and idiomatic equivalences of the instrument’s items. Conclusion: This project contributes with an important resource that can be used in the assessment of feelings and attitudes of preschool children who stutter. This was the first phase of the research; expert panel and pretest are being developed. Therefore, it is expected that this instrument contributes to an holistic therapeutic intervention, taking into account the individual characteristics of each child.

Keywords: assessment, feelings and attitudes, preschool children, stuttering

Procedia PDF Downloads 155
17949 Spin-Polarized Structural, Electronic and Magnetic Properties of Intermetallic Dy2Ni2Pb from Computational Study

Authors: O. Arbouche, Y. Benallou, K. Amara

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We report a first-principles study of structural, electronic and magnetic properties of ternary plumbides (rare earth-transition metal-Plumb) Dy2Ni2Pb crystallizes with the orthorhombic structure of the Mn2AlB2 type (space group Cmmm), were studied by means of the full-relativistic version of the full-potential augmented plane wave plus local orbital method within the frame work of spin-polarized density functional theory (SP-DFT). The electronic exchange-correlation energy is described by generalized gradient approximation (GGA). We have calculated the lattice parameters, bulk modulii and the first pressure derivatives of the bulk modulii, total densities of states and magnetic properties. The calculated total magnetic moment is found to be equal to 9.52 μB.

Keywords: spin-polarized, magnetic properties, Dy2Ni2Pb, Density functional theory

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17948 AI-Based Autonomous Plant Health Monitoring and Control System with Visual Health-Scoring Models

Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

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This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

Procedia PDF Downloads 65
17947 Effects of Four Dietary Oils on Cholesterol and Fatty Acid Composition of Egg Yolk in Layers

Authors: A. F. Agboola, B. R. O. Omidiwura, A. Oyeyemi, E. A. Iyayi, A. S. Adelani

Abstract:

Dietary cholesterol has elicited the most public interest as it relates with coronary heart disease. Thus, humans have been paying more attention to health, thereby reducing consumption of cholesterol enriched food. Egg is considered as one of the major sources of human dietary cholesterol. However, an alternative way to reduce the potential cholesterolemic effect of eggs is to modify the fatty acid composition of the yolk. The effect of palm oil (PO), soybean oil (SO), sesame seed oil (SSO) and fish oil (FO) supplementation in the diets of layers on egg yolk fatty acid, cholesterol, egg production and egg quality parameters were evaluated in a 42-day feeding trial. One hundred and five Isa Brown laying hens of 34 weeks of age were randomly distributed into seven groups of five replicates and three birds per replicate in a completely randomized design. Seven corn-soybean basal diets (BD) were formulated: BD+No oil (T1), BD+1.5% PO (T2), BD+1.5% SO (T3), BD+1.5% SSO (T4), BD+1.5% FO (T5), BD+0.75% SO+0.75% FO (T6) and BD+0.75% SSO+0.75% FO (T7). Five eggs were randomly sampled at day 42 from each replicate to assay for the cholesterol, fatty acid profile of egg yolk and egg quality assessment. Results showed that there were no significant (P>0.05) differences observed in production performance, egg cholesterol and egg quality parameters except for yolk height, albumen height, yolk index, egg shape index, haugh unit, and yolk colour. There were no significant differences (P>0.05) observed in total cholesterol, high density lipoprotein and low density lipoprotein levels of egg yolk across the treatments. However, diets had effect (P<0.05) on TAG (triacylglycerol) and VLDL (very low density lipoprotein) of the egg yolk. The highest TAG (603.78 mg/dl) and VLDL values (120.76 mg/dl) were recorded in eggs of hens on T4 (1.5% sesame seed oil) and was similar to those on T3 (1.5% soybean oil), T5 (1.5% fish oil) and T6 (0.75% soybean oil + 0.75% fish oil). However, results revealed a significant (P<0.05) variations on eggs’ summation of polyunsaturated fatty acid (PUFA). In conclusion, it is suggested that dietary oils could be included in layers’ diets to produce designer eggs low in cholesterol and high in PUFA especially omega-3 fatty acids.

Keywords: dietary oils, egg cholesterol, egg fatty acid profile, egg quality parameters

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17946 An 8-Bit, 100-MSPS Fully Dynamic SAR ADC for Ultra-High Speed Image Sensor

Authors: F. Rarbi, D. Dzahini, W. Uhring

Abstract:

In this paper, a dynamic and power efficient 8-bit and 100-MSPS Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) is presented. The circuit uses a non-differential capacitive Digital-to-Analog (DAC) architecture segmented by 2. The prototype is produced in a commercial 65-nm 1P7M CMOS technology with 1.2-V supply voltage. The size of the core ADC is 208.6 x 103.6 µm2. The post-layout noise simulation results feature a SNR of 46.9 dB at Nyquist frequency, which means an effective number of bit (ENOB) of 7.5-b. The total power consumption of this SAR ADC is only 1.55 mW at 100-MSPS. It achieves then a figure of merit of 85.6 fJ/step.

Keywords: CMOS analog to digital converter, dynamic comparator, image sensor application, successive approximation register

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17945 Time Series Forecasting (TSF) Using Various Deep Learning Models

Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

Abstract:

Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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17944 A Question of Ethics and Faith

Authors: Madhavi-Priya Singh, Liam Lowe, Farouk Arnaout, Ludmilla Pillay, Giordan Perez, Luke Mischker, Steve Costa

Abstract:

An Emergency Department consultant identified the failure of medical students to complete the task of clerking a patient in its entirety. As six medical students on our first clinical placement, we recognised our own failure and endeavoured to examine why this failure was consistent among all medical students that had been given this task, despite our best motivations as adult learner. Our aim is to understand and investigate the elements which impeded our ability to learn and perform as medical students in the clinical environment, with reference to the prescribed task. We also aim to generate a discussion around the delivery of medical education with potential solutions to these barriers. Six medical students gathered together to have a comprehensive reflective discussion to identify possible factors leading to the failure of the task. First, we thoroughly analysed the delivery of the instructions with reference to the literature to identify potential flaws. We then examined personal, social, ethical, and cultural factors which may have impacted our ability to complete the task in its entirety. Through collation of our shared experiences, with support from discussion in the field of medical education and ethics, we identified two major areas that impacted our ability to complete the set task. First, we experienced an ethical conflict where we believed the inconvenience and potential harm inflicted on patients did not justify the positive impact the patient interaction would have on our medical learning. Second, we identified a lack of confidence stemming from multiple factors, including the conflict between preclinical and clinical learning, perceptions of perfectionism in the culture of medicine, and the influence of upward social comparison. After discussions, we found that the various factors we identified exacerbated the fears and doubts we already had about our own abilities and that of the medical education system. This doubt led us to avoid completing certain aspects of the tasks that were prescribed and further reinforced our vulnerability and perceived incompetence. Exploration of philosophical theories identified the importance of the role of doubt in education. We propose the need for further discussion around incorporating both pedagogic and andragogic teaching styles in clinical medical education and the acceptance of doubt as a driver of our learning. Doubt will continue to permeate our thoughts and actions no matter what. The moral or psychological distress that arises from this is the key motivating factor for our avoidance of tasks. If we accept this doubt and education embraces this doubt, it will no longer linger in the shadows as a negative and restrictive emotion but fuel a brighter dialogue and positive learning experience, ultimately assisting us in achieving our full potential.

Keywords: medical education, clinical education, andragogy, pedagogy

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17943 Model of MSD Risk Assessment at Workplace

Authors: K. Sekulová, M. Šimon

Abstract:

This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

Keywords: ergonomics, musculoskeletal disorders, occupational diseases, risk factors

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17942 The Effect of Environmental Assessment Learning in Evacuation Centers on the COVID-19 Situation

Authors: Hiromi Kawasaki, Satoko Yamasaki, Mika Iwasa, Tomoko Iki, Akiko Takaki

Abstract:

In basic nursing, the conditions necessary for maintaining human health -temperature, humidity, illumination, distance from others, noise, moisture, meals, and excretion- were explained. Nursing students often think of these conditions in the context of a hospital room. In order to make students think of these conditions in terms of an environment necessary for maintaining health and preventing illness for residents, in the third year of community health nursing, students learned how to assess and improve the environment -particularly via the case of shelters in the event of a disaster. The importance of environmental management has increased in 2020 as a preventive measure against COVID-19 infection. We verified the effect of the lessons, which was decided to be conducted through distance learning. Sixty third-year nursing college students consented to participate in this study. Environmental standard knowledge for conducting environmental assessment was examined before and after class, and the percentage of correct answers was compared. The χ² test was used for the test, with a 5% significance level employed. Measures were evaluated via a report submitted by the students after class. Student descriptions were analyzed both qualitatively and descriptively with respect to expected health problems and suggestions for improvement. Students have already learned about the environment in terms of basic nursing in their second year. The correct answers for external environmental values concerning interpersonal distance, illumination, noise, and room temperature (p < 0.001) increased significantly after taking the class. Humidity was registered 83.3% before class and 93.3% after class (p = 0.077). Regarding the body, the percentage of students who answered correctly was 70% or more, both before and after the class. The students’ reports included overcrowding, high humidity/high temperature, and the number of toilets as health hazards. Health disorders to be prevented were heat stroke, infectious diseases, and economy class syndrome; improvement methods were recommended for hyperventilation, stretching, hydration, and waiting at home. After the public health nursing class, the students were able to not only propose environmental management of a hospital room but also had an understanding of the environment in terms of the lives of individuals, environmental assessment, and solutions to health problems. The response rate for basic items learned in the second year was already high before and after class, and interpersonal distance and ventilation were described by students. Students were able to use what they learned in basic nursing about the standards of the human mind and body. In the external environment, the memory of specific numerical values was ambiguous. The environment of the hospital room is controlled, and interest in numerical values may decrease. Nursing staff needs to maintain and improve human health as well as hospital rooms. With COVID-19, it was thought that students would continue to not only consider this point in reference to hospital rooms but also in regard to places where people gather. Even in distance learning, students were able to learn the important issues and lessons.

Keywords: environmental assessment, evacuation center, nursing education, nursing students

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17941 Hydraulic Headloss in Plastic Drainage Pipes at Full and Partially Full Flow

Authors: Velitchko G. Tzatchkov, Petronilo E. Cortes-Mejia, J. Manuel Rodriguez-Varela, Jesus Figueroa-Vazquez

Abstract:

Hydraulic headloss, expressed by the values of friction factor f and Manning’s coefficient n, is an important parameter in designing drainage pipes. Their values normally are taken from manufacturer recommendations, many times without sufficient experimental support. To our knowledge, currently there is no standard procedure for hydraulically testing such pipes. As a result of research carried out at the Mexican Institute of Water Technology, a laboratory testing procedure was proposed and applied on 6 and 12 inches diameter polyvinyl chloride (PVC) and high-density dual wall polyethylene pipe (HDPE) drainage pipes. While the PVC pipe is characterized by naturally smooth interior and exterior walls, the dual wall HDPE pipe has corrugated exterior wall and, although considered smooth, a slightly wavy interior wall. The pipes were tested at full and partially full pipe flow conditions. The tests for full pipe flow were carried out on a 31.47 m long pipe at flow velocities between 0.11 and 4.61 m/s. Water was supplied by gravity from a 10 m-high tank in some of the tests, and from a 3.20 m-high tank in the rest of the tests. Pressure was measured independently with piezometer readings and pressure transducers. The flow rate was measured by an ultrasonic meter. For the partially full pipe flow the pipe was placed inside an existing 49.63 m long zero slope (horizontal) channel. The flow depth was measured by piezometers located along the pipe, for flow rates between 2.84 and 35.65 L/s, measured by a rectangular weir. The observed flow profiles were then compared to computer generated theoretical gradually varied flow profiles for different Manning’s n values. It was found that Manning’s n, that normally is assumed constant for a given pipe material, is in fact dependent on flow velocity and pipe diameter for full pipe flow, and on flow depth for partially full pipe flow. Contrary to the expected higher values of n and f for the HDPE pipe, virtually the same values were obtained for the smooth interior wall PVC pipe and the slightly wavy interior wall HDPE pipe. The explanation of this fact was found in Henry Morris’ theory for smooth turbulent conduit flow over isolated roughness elements. Following Morris, three categories of the flow regimes are possible in a rough conduit: isolated roughness (or semi smooth turbulent) flow, wake interference (or hyper turbulent) flow, and skimming (or quasi-smooth) flow. Isolated roughness flow is characterized by friction drag turbulence over the wall between the roughness elements, independent vortex generation, and dissipation around each roughness element. In this regime, the wake and vortex generation zones at each element develop and dissipate before attaining the next element. The longitudinal spacing of the roughness elements and their height are important influencing agents. Given the slightly wavy form of the HDPE pipe interior wall, the flow for this type of pipe belongs to this category. Based on that theory, an equation for the hydraulic friction factor was obtained. The obtained coefficient values are going to be used in the Mexican design standards.

Keywords: drainage plastic pipes, hydraulic headloss, hydraulic friction factor, Manning’s n

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17940 Hydrocarbon Source Rocks of the Maragh Low

Authors: Elhadi Nasr, Ibrahim Ramadan

Abstract:

Biostratigraphical analyses of well sections from the Maragh Low in the Eastern Sirt Basin has allowed high resolution correlations to be undertaken. Full integration of this data with available palaeoenvironmental, lithological, gravity, seismic, aeromagnetic, igneous, radiometric and wireline log information and a geochemical analysis of source rock quality and distribution has led to a more detailed understanding of the geological and the structural history of this area. Pre Sirt Unconformity two superimposed rifting cycles have been identified. The oldest is represented by the Amal Group of sediments and is of Late Carboniferous, Kasimovian / Gzelian to Middle Triassic, Anisian age. Unconformably overlying is a younger rift cycle which is represented the Sarir Group of sediments and is of Early Cretaceous, late Neocomian to Aptian in age. Overlying the Sirt Unconformity is the marine Late Cretaceous section. An assessment of pyrolysis results and a palynofacies analysis has allowed hydrocarbon source facies and quality to be determined. There are a number of hydrocarbon source rock horizons in the Maragh Low, these are sometimes vertically stacked and they are of fair to excellent quality. The oldest identified source rock is the Triassic Shale, this unit is unconformably overlain by sandstones belonging to the Sarir Group and conformably overlies a Triassic Siltstone unit. Palynological dating of the Triassic Shale unit indicates a Middle Triassic, Anisian age. The Triassic Shale is interpreted to have been deposited in a lacustrine palaeoenvironment. This particularly is evidenced by the dark, fine grained, organic rich nature of the sediment and is supported by palynofacies analysis and by the recovery of fish fossils. Geochemical analysis of the Triassic Shale indicates total organic carbon varying between 1.37 and 3.53. S2 pyrolysate yields vary between 2.15 mg/g and 6.61 mg/g and hydrogen indices vary between 156.91 and 278.91. The source quality of the Triassic Shale varies from being of fair to very good / rich. Linked to thermal maturity it is now a very good source for light oil and gas. It was once a very good to rich oil source. The Early Barremian Shale was also deposited in a lacustrine palaeoenvironment. Recovered palynomorphs indicate an Early Cretaceous, late Neocomian to early Barremian age. The Early Barremian Shale is conformably underlain and overlain by sandstone units belonging to the Sarir Group of sediments which are also of Early Cretaceous age. Geochemical analysis of the Early Barremian Shale indicates that it is a good oil source and was originally very good. Total organic carbon varies between 3.59% and 7%. S2 varies between 6.30 mg/g and 10.39 mg/g and the hydrogen indices vary between 148.4 and 175.5. A Late Barremian Shale unit of this age has also been identified in the central Maragh Low. Geochemical analyses indicate that total organic carbon varies between 1.05 and 2.38%, S2 pyrolysate between 1.6 and 5.34 mg/g and the hydrogen index between 152.4 and 224.4. It is a good oil source rock which is now mature. In addition to the non marine hydrocarbon source rocks pre Sirt Unconformity, three formations in the overlying Late Cretaceous section also provide hydrocarbon quality source rocks. Interbedded shales within the Rachmat Formation of Late Cretaceous, early Campanian age have total organic carbon ranging between, 0.7 and 1.47%, S2 pyrolysate varying between 1.37 and 4.00 mg/g and hydrogen indices varying between 195.7 and 272.1. The indication is that this unit would provide a fair gas source to a good oil source. Geochemical analyses of the overlying Tagrifet Limestone indicate that total organic carbon varies between 0.26% and 1.01%. S2 pyrolysate varies between 1.21 and 2.16 mg/g and hydrogen indices vary between 195.7 and 465.4. For the overlying Sirt Shale Formation of Late Cretaceous, late Campanian age, total organic carbon varies between 1.04% and 1.51%, S2 pyrolysate varies between 4.65 mg/g and 6.99 mg/g and the hydrogen indices vary between 151 and 462.9. The study has proven that both the Sirt Shale Formation and the Tagrifet Limestone are good to very good and rich sources for oil in the Maragh Low. High resolution biostratigraphical interpretations have been integrated and calibrated with thermal maturity determinations (Vitrinite Reflectance (%Ro), Spore Colour Index (SCI) and Tmax (ºC) and the determined present day geothermal gradient of 25ºC / Km for the Maragh Low. Interpretation of generated basin modelling profiles allows a detailed prediction of timing of maturation development of these source horizons and leads to a determination of amounts of missing section at major unconformities. From the results the top of the oil window (0.72% Ro) is picked as high as 10,700’ and the base of the oil window (1.35% Ro) assuming a linear trend and by projection is picked as low as 18,000’ in the Maragh Low. For the Triassic Shale the early phase of oil generation was in the Late Palaeocene / Early to Middle Eocene and the main phase of oil generation was in the Middle to Late Eocene. The Early Barremian Shale reached the main phase of oil generation in the Early Oligocene with late generation being reached in the Middle Miocene. For the Rakb Group section (Rachmat Formation, Tagrifet Limestone and Sirt Shale Formation) the early phase of oil generation started in the Late Eocene with the main phase of generation being between the Early Oligocene and the Early Miocene. From studying maturity profiles and from regional considerations it can be predicted that up to 500’ of sediment may have been deposited and eroded by the Sirt Unconformity in the central Maragh Low while up to 2000’ of sediment may have been deposited and then eroded to the south of the trough.

Keywords: Geochemical analysis of the source rocks from wells in Eastern Sirt Basin.

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