Search results for: data databases
20433 Expanding Access and Deepening Engagement: Building an Open Source Digital Platform for Restoration-Based Stem Education in the Largest Public-School System in the United States
Authors: Lauren B. Birney
Abstract:
This project focuses upon the expansion of the existing "Curriculum and Community Enterprise for the Restoration of New York Harbor in New York City Public Schools" NSF EHR DRL 1440869, NSF EHR DRL 1839656 and NSF EHR DRL 1759006. This project is recognized locally as “Curriculum and Community Enterprise for Restoration Science,” or CCERS. CCERS is a comprehensive model of ecological restoration-based STEM education for urban public-school students. Following an accelerated rollout, CCERS is now being implemented in 120+ Title 1 funded NYC Department of Education middle schools, led by two cohorts of 250 teachers, serving more than 11,000 students in total. Initial results and baseline data suggest that the CCERS model, with the Billion Oyster Project (BOP) as its local restoration ecology-based STEM curriculum, is having profound impacts on students, teachers, school leaders, and the broader community of CCERS participants and stakeholders. Students and teachers report being receptive to the CCERS model and deeply engaged in the initial phase of curriculum development, citizen science data collection, and student-centered, problem-based STEM learning. The BOP CCERS Digital Platform will serve as the central technology hub for all research, data, data analysis, resources, materials and student data to promote global interactions between communities, Research conducted included qualitative and quantitative data analysis. We continue to work internally on making edits and changes to accommodate a dynamic society. The STEM Collaboratory NYC® at Pace University New York City continues to act as the prime institution for the BOP CCERS project since the project’s inception in 2014. The project continues to strive to provide opportunities in STEM for underrepresented and underserved populations in New York City. The replicable model serves as an opportunity for other entities to create this type of collaboration within their own communities and ignite a community to come together and address the notable issue. Providing opportunities for young students to engage in community initiatives allows for a more cohesive set of stakeholders, ability for young people to network and provide additional resources for those students in need of additional support, resources and structure. The project has planted more than 47 million oysters across 12 acres and 15 reef sites, with the help of more than 8,000 students and 10,000 volunteers. Additional enhancements and features on the BOP CCERS Digital Platform will continue over the next three years through funding provided by the National Science Foundation, NSF DRL EHR 1759006/1839656 Principal Investigator Dr. Lauren Birney, Professor Pace University. Early results from the data indicate that the new version of the Platform is creating traction both nationally and internationally among community stakeholders and constituents. This project continues to focus on new collaborative partners that will support underrepresented students in STEM Education. The advanced Digital Platform will allow for us connect with other countries and networks on a larger Global scale.Keywords: STEM education, environmental restoration science, technology, citizen science
Procedia PDF Downloads 8020432 Revised Technology Acceptance Model Framework for M-Commerce Adoption
Authors: Manish Gupta
Abstract:
Following the E-Commerce era, M-Commerce is the next big phase in the technology involvement and advancement. This paper intends to explore how Indian consumers are influenced to adopt the M-commerce. In this paper, the revised Technology Acceptance Model (TAM) has been presented on the basis of the most dominant factors that affect the adoption of M-Commerce in Indian scenario. Furthermore, an analytical questionnaire approach was carried out to collect data from Indian consumers. These collected data were further used for the validation of the presented model. Findings indicate that customization, convenience, instant connectivity, compatibility, security, download speed in M-Commerce affect the adoption behavior. Furthermore, the findings suggest that perceived usefulness and attitude towards M-Commerce are positively influenced by number of M-Commerce drivers (i.e. download speed, compatibility, convenience, security, customization, connectivity, and input mechanism).Keywords: M-Commerce, perceived usefulness, technology acceptance model, perceived ease of use
Procedia PDF Downloads 30920431 Passive Neutralization of Acid Mine Drainage Using Locally Produced Limestone
Authors: Reneiloe Seodigeng, Malwandla Hanabe, Haleden Chiririwa, Hilary Rutto, Tumisang Seodigeng
Abstract:
Neutralisation of acid-mine drainage (AMD) using limestone is cost effective, and good results can be obtained. However, this process has its limitations; it cannot be used for highly acidic water which consists of Fe(III). When Fe(III) reacts with CaCO3, it results in armoring. Armoring slows the reaction, and additional alkalinity can no longer be generated. Limestone is easily accessible, so this problem can be easily dealt with. Experiments were carried out to evaluate the effect of PVC pipe length on ferric and ferrous ions. It was found that the shorter the pipe length the more these dissolved metals precipitate. The effect of the pipe length on the hydrogen ions was also studied, and it was found that these two have an inverse relationship. Experimental data were further compared with the model prediction data to see if they behave in a similar fashion. The model was able to predict the behaviour of 1.5m and 2 m pipes in ferric and ferrous ion precipitation.Keywords: acid mine drainage, neutralisation, limestone, mathematical modelling
Procedia PDF Downloads 35620430 Identification and Classification of Fiber-Fortified Semolina by Near-Infrared Spectroscopy (NIR)
Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira
Abstract:
Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina
Procedia PDF Downloads 20520429 Fight against Money Laundering with Optical Character Recognition
Authors: Saikiran Subbagari, Avinash Malladhi
Abstract:
Anti Money Laundering (AML) regulations are designed to prevent money laundering and terrorist financing activities worldwide. Financial institutions around the world are legally obligated to identify, assess and mitigate the risks associated with money laundering and report any suspicious transactions to governing authorities. With increasing volumes of data to analyze, financial institutions seek to automate their AML processes. In the rise of financial crimes, optical character recognition (OCR), in combination with machine learning (ML) algorithms, serves as a crucial tool for automating AML processes by extracting the data from documents and identifying suspicious transactions. In this paper, we examine the utilization of OCR for AML and delve into various OCR techniques employed in AML processes. These techniques encompass template-based, feature-based, neural network-based, natural language processing (NLP), hidden markov models (HMMs), conditional random fields (CRFs), binarizations, pattern matching and stroke width transform (SWT). We evaluate each technique, discussing their strengths and constraints. Also, we emphasize on how OCR can improve the accuracy of customer identity verification by comparing the extracted text with the office of foreign assets control (OFAC) watchlist. We will also discuss how OCR helps to overcome language barriers in AML compliance. We also address the implementation challenges that OCR-based AML systems may face and offer recommendations for financial institutions based on the data from previous research studies, which illustrate the effectiveness of OCR-based AML.Keywords: anti-money laundering, compliance, financial crimes, fraud detection, machine learning, optical character recognition
Procedia PDF Downloads 13820428 The Relationship between Quality of Life and Sexual Satisfaction in Women with Severe Burns
Authors: Jafar Kazemzadeh, Soheila Rabiepoor, Saeedeh Alizadeh
Abstract:
Introduction: Burn, especially in women, can affect the quality of life and their quality of life due to a change in appearance. This study was designed to investigate the relationship between quality of life and sexual satisfaction in women with burn. Methods: This was a descriptive-analytical cross-sectional study conducted on 101 women with severe burns referring to Imam Khomeini Hospital in Urmia in 2016. The data gathering scales were demographic questionnaire, burn specific health scale-brief (BSHS-B) and index of sexual satisfaction (ISS). The data were analyzed using SPSS software version 16. Results: Mean score of quality of life was 102.94 ± 20.88 and sexual satisfaction was 57.03 ± 25.91. Also, there was a significant relationship between quality of life and its subscales with sexual satisfaction and some demographic variables (p < 0.05). Conclusion: According to the results of this study, it should be noted that interventional efforts for improving sexual satisfaction and thus improving the quality of life in these patients are important. The findings of this study appear to be effective in planning for women with a history of burns.Keywords: burn, quality of life, sexual satisfaction, women
Procedia PDF Downloads 18320427 Digital Transformation, Financing Microstructures, and Impact on Well-Being and Income Inequality
Authors: Koffi Sodokin
Abstract:
Financing microstructures are increasingly seen as a means of financial inclusion and improving overall well-being in developing countries. In practice, digital transformation in finance can accelerate the optimal functioning of financing microstructures, such as access by households to microfinance and microinsurance. Large households' access to finance can lead to a reduction in income inequality and an overall improvement in well-being. This paper explores the impact of access to digital finance and financing microstructures on household well-being and the reduction of income inequality. To this end, we use the propensity score matching, the double difference, and the smooth instrumental quantile regression as estimation methods with two periods of survey data. The paper uses the FinScope consumer data (2016) and the Harmonized Living Standards Measurement Study (2018) from Togo in a comparative perspective. The results indicate that access to digital finance, as a cultural game changer, and to financing microstructures improves overall household well-being and contributes significantly to reducing income inequality.Keywords: financing microstructure, microinsurance, microfinance, digital finance, well-being, income inequality
Procedia PDF Downloads 8320426 Utilizing the Principal Component Analysis on Multispectral Aerial Imagery for Identification of Underlying Structures
Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi
Abstract:
Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.Keywords: big data, image processing, multispectral, principal component analysis
Procedia PDF Downloads 16720425 Classification of IoT Traffic Security Attacks Using Deep Learning
Authors: Anum Ali, Kashaf ad Dooja, Asif Saleem
Abstract:
The future smart cities trend will be towards Internet of Things (IoT); IoT creates dynamic connections in a ubiquitous manner. Smart cities offer ease and flexibility for daily life matters. By using small devices that are connected to cloud servers based on IoT, network traffic between these devices is growing exponentially, whose security is a concerned issue, since ratio of cyber attack may make the network traffic vulnerable. This paper discusses the latest machine learning approaches in related work further to tackle the increasing rate of cyber attacks, machine learning algorithm is applied to IoT-based network traffic data. The proposed algorithm train itself on data and identify different sections of devices interaction by using supervised learning which is considered as a classifier related to a specific IoT device class. The simulation results clearly identify the attacks and produce fewer false detections.Keywords: IoT, traffic security, deep learning, classification
Procedia PDF Downloads 14420424 Exploring Closed-Loop Business Systems Which Eliminates Solid Waste in the Textile and Fashion Industry: A Systematic Literature Review Covering the Developments Occurred in the Last Decade
Authors: Bukra Kalayci, Geraldine Brennan
Abstract:
Introduction: Over the last decade, a proliferation of literature related to textile and fashion business in the context of sustainable production and consumption has emerged. However, the economic and environmental benefits of solid waste recovery have not been comprehensively searched. Therefore at the end-of-life or end-of-use textile waste management remains a gap. Solid textile waste reuse and recycling principles of the circular economy need to be developed to close the disposal stage of the textile supply chain. The environmental problems associated with the over-production and –consumption of textile products arise. Together with growing population and fast fashion culture the share of solid textile waste in municipal waste is increasing. Focusing on post-consumer textile waste literature, this research explores the opportunities, obstacles and enablers or success factors associated with closed-loop textile business systems. Methodology: A systematic literature review was conducted in order to identify best practices and gaps from the existing body of knowledge related to closed-loop post-consumer textile waste initiatives over the last decade. Selected keywords namely: ‘cradle-to-cradle ‘, ‘circular* economy* ‘, ‘closed-loop* ‘, ‘end-of-life* ‘, ‘reverse* logistic* ‘, ‘take-back* ‘, ‘remanufacture* ‘, ‘upcycle* ‘ with the combination of (and) ‘fashion* ‘, ‘garment* ‘, ‘textile* ‘, ‘apparel* ‘, clothing* ‘ were used and the time frame of the review was set between 2005 to 2017. In order to obtain a broad coverage, Web of Knowledge and Science Direct databases were used, and peer-reviewed journal articles were chosen. The keyword search identified 299 number of papers which was further refined into 54 relevant papers that form the basis of the in-depth thematic analysis. Preliminary findings: A key finding was that the existing literature is predominantly conceptual rather than applied or empirical work. Moreover, the enablers or success factors, obstacles and opportunities to implement closed-loop systems in the textile industry were not clearly articulated and the following considerations were also largely overlooked in the literature. While the circular economy suggests multiple cycles of discarded products, components or materials, most research has to date tended to focus on a single cycle. Thus the calculations of environmental and economic benefits of closed-loop systems are limited to one cycle which does not adequately explore the feasibility or potential benefits of multiple cycles. Additionally, the time period textile products spend between point of sale, and end-of-use/end-of-life return is a crucial factor. Despite past efforts to study closed-loop textile systems a clear gap in the literature is the lack of a clear evaluation framework which enables manufacturers to clarify the reusability potential of textile products through consideration of indicators related too: quality, design, lifetime, length of time between manufacture and product return, volume of collected disposed products, material properties, and brand segment considerations (e.g. fast fashion versus luxury brands).Keywords: circular fashion, closed loop business, product service systems, solid textile waste elimination
Procedia PDF Downloads 19320423 Effect of Drag Coefficient Models concerning Global Air-Sea Momentum Flux in Broad Wind Range including Extreme Wind Speeds
Authors: Takeshi Takemoto, Naoya Suzuki, Naohisa Takagaki, Satoru Komori, Masako Terui, George Truscott
Abstract:
Drag coefficient is an important parameter in order to correctly estimate the air-sea momentum flux. However, The parameterization of the drag coefficient hasn’t been established due to the variation in the field data. Instead, a number of drag coefficient model formulae have been proposed, even though almost all these models haven’t discussed the extreme wind speed range. With regards to such models, it is unclear how the drag coefficient changes in the extreme wind speed range as the wind speed increased. In this study, we investigated the effect of the drag coefficient models concerning the air-sea momentum flux in the extreme wind range on a global scale, comparing two different drag coefficient models. Interestingly, one model didn’t discuss the extreme wind speed range while the other model considered it. We found that the difference of the models in the annual global air-sea momentum flux was small because the occurrence frequency of strong wind was approximately 1% with a wind speed of 20m/s or more. However, we also discovered that the difference of the models was shown in the middle latitude where the annual mean air-sea momentum flux was large and the occurrence frequency of strong wind was high. In addition, the estimated data showed that the difference of the models in the drag coefficient was large in the extreme wind speed range and that the largest difference became 23% with a wind speed of 35m/s or more. These results clearly show that the difference of the two models concerning the drag coefficient has a significant impact on the estimation of a regional air-sea momentum flux in an extreme wind speed range such as that seen in a tropical cyclone environment. Furthermore, we estimated each air-sea momentum flux using several kinds of drag coefficient models. We will also provide data from an observation tower and result from CFD (Computational Fluid Dynamics) concerning the influence of wind flow at and around the place.Keywords: air-sea interaction, drag coefficient, air-sea momentum flux, CFD (Computational Fluid Dynamics)
Procedia PDF Downloads 36720422 Use of Artificial Intelligence and Two Object-Oriented Approaches (k-NN and SVM) for the Detection and Characterization of Wetlands in the Centre-Val de Loire Region, France
Authors: Bensaid A., Mostephaoui T., Nedjai R.
Abstract:
Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.Keywords: land development, GIS, sand dunes, segmentation, remote sensing
Procedia PDF Downloads 6020421 An Experimental (Wind Tunnel) and Numerical (CFD) Study on the Flow over Hills
Authors: Tanit Daniel Jodar Vecina, Adriane Prisco Petry
Abstract:
The shape of the wind velocity profile changes according to local features of terrain shape and roughness, which are parameters responsible for defining the Atmospheric Boundary Layer (ABL) profile. Air flow characteristics over and around landforms, such as hills, are of considerable importance for applications related to Wind Farm and Turbine Engineering. The air flow is accelerated on top of hills, which can represent a decisive factor for Wind Turbine placement choices. The present work focuses on the study of ABL behavior as a function of slope and surface roughness of hill-shaped landforms, using the Computational Fluid Dynamics (CFD) to build wind velocity and turbulent intensity profiles. Reynolds-Averaged Navier-Stokes (RANS) equations are closed using the SST k-ω turbulence model; numerical results are compared to experimental data measured in wind tunnel over scale models of the hills under consideration. Eight hill models with slopes varying from 25° to 68° were tested for two types of terrain categories in 2D and 3D, and two analytical codes are used to represent the inlet velocity profiles. Numerical results for the velocity profiles show differences under 4% when compared to their respective experimental data. Turbulent intensity profiles show maximum differences around 7% when compared to experimental data; this can be explained by not being possible to insert inlet turbulent intensity profiles in the simulations. Alternatively, constant values based on the averages of the turbulent intensity at the wind tunnel inlet were used.Keywords: Atmospheric Boundary Layer, Computational Fluid Dynamic (CFD), Numerical Modeling, Wind Tunnel
Procedia PDF Downloads 37620420 Security Risks Assessment: A Conceptualization and Extension of NFC Touch-And-Go Application
Authors: Ku Aina Afiqah Ku Adzman, Manmeet Mahinderjit Singh, Zarul Fitri Zaaba
Abstract:
NFC operates on low-range 13.56 MHz frequency within a distance from 4cm to 10cm, and the applications can be categorized as touch and go, touch and confirm, touch and connect, and touch and explore. NFC applications are vulnerable to various security and privacy attacks such due to its physical nature; unprotected data stored in NFC tag and insecure communication between its applications. This paper aims to determine the likelihood of security risks happening in an NFC technology and application. We present an NFC technology taxonomy covering NFC standards, types of application and various security and privacy attack. Based on observations and the survey presented to evaluate the risk assessment within the touch and go application demonstrates two security attacks that are high risks namely data corruption and DOS attacks. After the risks are determined, risk countermeasures by using AHP is adopted. The guideline and solutions to these two high risks, attacks are later applied to a secure NFC-enabled Smartphone Attendance System.Keywords: Near Field Communication (NFC), risk assessment, multi-criteria decision making, Analytical Hierarchy Process (AHP)
Procedia PDF Downloads 29320419 Status of Participative Governance Practices in Higher Education: Implications for Stakeholders' Transformative Role-Assumption
Authors: Endalew Fufa Kufi
Abstract:
The research investigated the role of stakeholders such as students, teachers and administrators in the practices of good governance in higher education by looking into the special contributions of top-officials, teachers and students in ensuring workable ties and productive interchanges in Adama Science and Technology University. Attention was given to participation, fairness and exemplariness as key indicators of good governance. The target university was chosen for its familiarity for the researcher to get dependable data, access to respondent and management of the processing of data. Descriptive survey design was used for the purpose of describing concerned roles the stakeholders in the university governance in order to reflect on the nature of participation of the practices. Centres of the research were administration where supportive groups such as central administrators and underlying service-givers had parts and academia where teachers and students were target. Generally, 60 teachers, 40 students and 15 administrative officers were referents. Data were collected in the form of self-report through open-ended questionnaires. The findings indicated that, while vertical interchanges in terms of academic and administrative routines were had normal flow on top-down basis, planned practices of stakeholders in decision-making and reasonably communicating roles and changes in decisions with top-officials were not efficiently practiced. Moreover, the practices of good modelling were not witnessed to have existed to the fullest extent. Rather, existence of a very wide gap between the academic and administrative staffs was witnessed as was reflected the case between teachers and students. The implication was such that for shortage in participative atmosphere and weaning of fairness in governance, routine practices have been there as the vicious circles of governance.Keywords: governance, participative, stakeholders, transformative, role-assumption
Procedia PDF Downloads 39220418 Consultation Time and Its Impact on Length of Stay in the Emergency Department
Authors: Esam Roshdy, Saleh AlRashdi, Turki Alharbi, Rawan Eskandarani, Zurina Cabilo
Abstract:
Introduction/ background: Consultation in the Emergency Department constitute a major part of the work flow every day. Any delay in the consultation process have a major impact on the length of stay and patient disposition and thus affect the total waiting time of patients in the ED. King Fahad medical City in Riyadh City, Saudi Arabia is considered a major Tertiary hospital where there is high flow of patients of different categories visiting the ED. The importance of decreasing consultation time and decision for final disposition of patients was recognized and interpreted in this project to find ways to improve the patient flow in the department and thus the total patient disposition and outcome. Aim / Objectives: 1. To monitor the time of consultation for patients in the Emergency department and its impact on the length of stay of patients in the ED. 2. To detect and assess the problems that lead to long consultation times in the ED, and reach a targeted time of 2 hours for final disposition of patients, according to recognized international and our institutional consultation policy, to reach the final goal of decreasing total length of stay and thus improve the patient flow in the ED. Methods: Data was collected retrospectively for a 92 charts of consultations done in the ED over 2 month’s period. The data was analyzed to get the median of Total Consultation Time. A survey was conducted among all ED staff to determine the level of knowledge about the total consultation time and the compliance to the institutional policy target of 2 hours. A second Data sample of 168 chart was collected after awareness campaign and education of all ED staff about the importance of reaching the target consultation time and compliance to the institutional policy. Results: We have found that there is room for improvement in our overall consultation time. This was found to be more frequent with certain specialties. Our surveys have showed that many ED staff are not familiar or not compliant with our consultation policy which was not clear for everyone. Post-intervention data have showed that awareness of the importance to decrease the total consultation time and compliance alone to the targeted goal have had a huge impact on overall improvement and decreasing the time of final decision and disposition of the patient and the overall patient length of stay in the ED. Conclusion: Working on improving Consultation time in the Emergency Department is a major factor in improving overall length of stay and patient flow. This improvement helps in the overall patient disposition and satisfaction. Plan: As a continuation of our project we are planning to focus on the conflict of admission cases where more than one specialty is involved in the care of patients. We are planning to collect data on the time it takes to resolve and reach final disposition of those patients, and its impact on the length of stay and our department flow and the overall patient outcome and satisfaction.Keywords: consultation time, impact, length of stay, in the ED
Procedia PDF Downloads 28220417 FMR1 Gene Carrier Screening for Premature Ovarian Insufficiency in Females: An Indian Scenario
Authors: Sarita Agarwal, Deepika Delsa Dean
Abstract:
Like the task of transferring photo images to artistic images, image-to-image translation aims to translate the data to the imitated data which belongs to the target domain. Neural Style Transfer and CycleGAN are two well-known deep learning architectures used for photo image-to-art image transfer. However, studies involving these two models concentrate on one-to-one domain translation, not one-to-multi domains translation. Our study tries to investigate deep learning architectures, which can be controlled to yield multiple artistic style translation only by adding a conditional vector. We have expanded CycleGAN and constructed Conditional CycleGAN for 5 kinds of categories translation. Our study found that the architecture inserting conditional vector into the middle layer of the Generator could output multiple artistic images.Keywords: genetic counseling, FMR1 gene, fragile x-associated primary ovarian insufficiency, premutation
Procedia PDF Downloads 11920416 Formulating a Flexible-Spread Fuzzy Regression Model Based on Dissemblance Index
Authors: Shih-Pin Chen, Shih-Syuan You
Abstract:
This study proposes a regression model with flexible spreads for fuzzy input-output data to cope with the situation that the existing measures cannot reflect the actual estimation error. The main idea is that a dissemblance index (DI) is carefully identified and defined for precisely measuring the actual estimation error. Moreover, the graded mean integration (GMI) representation is adopted for determining more representative numeric regression coefficients. Notably, to comprehensively compare the performance of the proposed model with other ones, three different criteria are adopted. The results from commonly used test numerical examples and an application to Taiwan's business monitoring indicator illustrate that the proposed dissemblance index method not only produces valid fuzzy regression models for fuzzy input-output data, but also has satisfactory and stable performance in terms of the total estimation error based on these three criteria.Keywords: dissemblance index, forecasting, fuzzy sets, linear regression
Procedia PDF Downloads 35220415 Clothes Identification Using Inception ResNet V2 and MobileNet V2
Authors: Subodh Chandra Shakya, Badal Shrestha, Suni Thapa, Ashutosh Chauhan, Saugat Adhikari
Abstract:
To tackle our problem of clothes identification, we used different architectures of Convolutional Neural Networks. Among different architectures, the outcome from Inception ResNet V2 and MobileNet V2 seemed promising. On comparison of the metrices, we observed that the Inception ResNet V2 slightly outperforms MobileNet V2 for this purpose. So this paper of ours proposes the cloth identifier using Inception ResNet V2 and also contains the comparison between the outcome of ResNet V2 and MobileNet V2. The document here contains the results and findings of the research that we performed on the DeepFashion Dataset. To improve the dataset, we used different image preprocessing techniques like image shearing, image rotation, and denoising. The whole experiment was conducted with the intention of testing the efficiency of convolutional neural networks on cloth identification so that we could develop a reliable system that is good enough in identifying the clothes worn by the users. The whole system can be integrated with some kind of recommendation system.Keywords: inception ResNet, convolutional neural net, deep learning, confusion matrix, data augmentation, data preprocessing
Procedia PDF Downloads 17820414 Destination of the PhDs: Determinants of International Mobility of UK PhD Graduates
Authors: Anna Siuda-Bak
Abstract:
This paper adopts a comparative approach to examining the determinants of international mobility of German, Italian and British researchers who completed their doctoral education in the UK. Structured sampling and data collection techniques have been developed in order to retrieve information on participants from publicly available sources. This systematically collected data was supplemented with an on-line survey which captures participants’ job trajectories, including movements between positions, institutions and countries. In total, data on 949 German, Italian and British PhDs was collected. Logistic regression was employed to identify factors associated with one’s probability of moving outside the UK after his or her graduation. The predictor variables included factors associated with one’s PhD (field of study, ranking of the university which awarded the PhD degree) and family factors (having a child, nationality of the partner). Then, 9 constrained models were estimated to test the effect each variable has on probability of going to a specific destination, being English-speaking country, non-English speaking country or returning to the home country. The results show that females, arts and humanities graduates, and respondents with a partner from the UK are less mobile than their counterparts. The effect of the ranking of the university differed in two groups. The UK graduates from higher ranked universities were more likely to move abroad than to stay in the UK after their graduation. In contrast, non-UK natives from the same universities were less likely to be internationally mobile than non-UK natives from lower ranked universities. The nationality of the partner was the most important predictor of the specific destination choices. Graduates with partner from the home county were more likely to return home and those with a partner from the third country least likely to return.Keywords: doctoral graduates, international mobility, nationality, UK
Procedia PDF Downloads 31820413 TransDrift: Modeling Word-Embedding Drift Using Transformer
Authors: Nishtha Madaan, Prateek Chaudhury, Nishant Kumar, Srikanta Bedathur
Abstract:
In modern NLP applications, word embeddings are a crucial backbone that can be readily shared across a number of tasks. However, as the text distributions change and word semantics evolve over time, the downstream applications using the embeddings can suffer if the word representations do not conform to the data drift. Thus, maintaining word embeddings to be consistent with the underlying data distribution is a key problem. In this work, we tackle this problem and propose TransDrift, a transformer-based prediction model for word embeddings. Leveraging the flexibility of the transformer, our model accurately learns the dynamics of the embedding drift and predicts future embedding. In experiments, we compare with existing methods and show that our model makes significantly more accurate predictions of the word embedding than the baselines. Crucially, by applying the predicted embeddings as a backbone for downstream classification tasks, we show that our embeddings lead to superior performance compared to the previous methods.Keywords: NLP applications, transformers, Word2vec, drift, word embeddings
Procedia PDF Downloads 8320412 Prioritizing the Most Important Information from Contractors’ BIM Handover for Firefighters’ Responsibilities
Authors: Akram Mahdaviparsa, Tamera McCuen, Vahideh Karimimansoob
Abstract:
Fire service is responsible for protecting life, assets, and natural resources from fire and other hazardous incidents. Search and rescue in unfamiliar buildings is a vital part of firefighters’ responsibilities. Providing firefighters with precise building information in an easy-to-understand format is a potential solution for mitigating the negative consequences of fire hazards. The negative effect of insufficient knowledge about a building’s indoor environment impedes firefighters’ capabilities and leads to lost property. A data rich building information modeling (BIM) is a potentially useful source in three-dimensional (3D) visualization and data/information storage for fire emergency response. Therefore, this research’s purpose is prioritizing the required information for firefighters from the most important information to the least important. A survey was carried out with firefighters working in the Norman Fire Department to obtain the importance of each building information item. The results show that “the location of exit doors, windows, corridors, elevators, and stairs”, “material of building elements”, and “building data” are the three most important information specified by firefighters. The results also implied that the 2D model of architectural, structural and way finding is more understandable in comparison with the 3D model, while the 3D model of MEP system could convey more information than the 2D model. Furthermore, color in visualization can help firefighters to understand the building information easier and quicker. Sufficient internal consistency of all responses was proven through developing the Pearson Correlation Matrix and obtaining Cronbach’s alpha of 0.916. Therefore, the results of this study are reliable and could be applied to the population.Keywords: BIM, building fire response, ranking, visualization
Procedia PDF Downloads 12720411 Optimized Electron Diffraction Detection and Data Acquisition in Diffraction Tomography: A Complete Solution by Gatan
Authors: Saleh Gorji, Sahil Gulati, Ana Pakzad
Abstract:
Continuous electron diffraction tomography, also known as microcrystal electron diffraction (MicroED) or three-dimensional electron diffraction (3DED), is a powerful technique, which in combination with cryo-electron microscopy (cryo-ED), can provide atomic-scale 3D information about the crystal structure and composition of different classes of crystalline materials such as proteins, peptides, and small molecules. Unlike the well-established X-ray crystallography method, 3DED does not require large single crystals and can collect accurate electron diffraction data from crystals as small as 50 – 100 nm. This is a critical advantage as growing larger crystals, as required by X-ray crystallography methods, is often very difficult, time-consuming, and expensive. In most cases, specimens studied via 3DED method are electron beam sensitive, which means there is a limitation on the maximum amount of electron dose one can use to collect the required data for a high-resolution structure determination. Therefore, collecting data using a conventional scintillator-based fiber coupled camera brings additional challenges. This is because of the inherent noise introduced during the electron-to-photon conversion in the scintillator and transfer of light via the fibers to the sensor, which results in a poor signal-to-noise ratio and requires a relatively higher and commonly specimen-damaging electron dose rates, especially for protein crystals. As in other cryo-EM techniques, damage to the specimen can be mitigated if a direct detection camera is used which provides a high signal-to-noise ratio at low electron doses. In this work, we have used two classes of such detectors from Gatan, namely the K3® camera (a monolithic active pixel sensor) and Stela™ (that utilizes DECTRIS hybrid-pixel technology), to address this problem. The K3 is an electron counting detector optimized for low-dose applications (like structural biology cryo-EM), and Stela is also a counting electron detector but optimized for diffraction applications with high speed and high dynamic range. Lastly, data collection workflows, including crystal screening, microscope optics setup (for imaging and diffraction), stage height adjustment at each crystal position, and tomogram acquisition, can be one of the other challenges of the 3DED technique. Traditionally this has been all done manually or in a partly automated fashion using open-source software and scripting, requiring long hours on the microscope (extra cost) and extensive user interaction with the system. We have recently introduced Latitude® D in DigitalMicrograph® software, which is compatible with all pre- and post-energy-filter Gatan cameras and enables 3DED data acquisition in an automated and optimized fashion. Higher quality 3DED data enables structure determination with higher confidence, while automated workflows allow these to be completed considerably faster than before. Using multiple examples, this work will demonstrate how to direct detection electron counting cameras enhance 3DED results (3 to better than 1 Angstrom) for protein and small molecule structure determination. We will also show how Latitude D software facilitates collecting such data in an integrated and fully automated user interface.Keywords: continuous electron diffraction tomography, direct detection, diffraction, Latitude D, Digitalmicrograph, proteins, small molecules
Procedia PDF Downloads 9920410 Application of Transportation Linear Programming Algorithms to Cost Reduction in Nigeria Soft Drinks Industry
Authors: Salami Akeem Olanrewaju
Abstract:
The transportation models or problems are primarily concerned with the optimal (best possible) way in which a product produced at different factories or plants (called supply origins) can be transported to a number of warehouses or customers (called demand destinations). The objective in a transportation problem is to fully satisfy the destination requirements within the operating production capacity constraints at the minimum possible cost. The objective of this study is to determine ways of minimizing transport cost in order to maximum profit. Data were gathered from the records of the Distribution Department of 7-Up Bottling Company Plc. Ilorin, Kwara State, Nigeria. The data were analyzed using SPSS (Statistical Package for Social Sciences) while applying the three methods of solving a transportation problem. The three methods produced the same results; therefore, any of the method can be adopted by the company in transporting its final products to the wholesale dealers in order to minimize total production cost.Keywords: cost minimization, resources utilization, distribution system, allocation problem
Procedia PDF Downloads 24820409 A Case Comparative Study of Infant Mortality Rate in North-West Nigeria
Authors: G. I. Onwuka, A. Danbaba, S. U. Gulumbe
Abstract:
This study investigated of Infant Mortality Rate as observed at a general hospital in Kaduna-South, Kaduna State, North West Nigeria. The causes of infant Mortality were examined. The data used for this analysis were collected at the statistics unit of the Hospital. The analysis was carried out on the data using Multiple Linear regression Technique and this showed that there is linear relationship between the dependent variable (death) and the independent variables (malaria, measles, anaemia, and coronary heart disease). The resultant model also revealed that a unit increment in each of these diseases would result to a unit increment in death recorded, 98.7% of the total variation in mortality is explained by the given model. The highest number of mortality was recorded in July, 2005 and the lowest mortality recorded in October, 2009.Recommendations were however made based on the results of the study.Keywords: infant mortality rate, multiple linear regression, diseases, serial correlation
Procedia PDF Downloads 31820408 Multiphase Flow Model for 3D Numerical Model Using ANSYS for Flow over Stepped Cascade with End Sill
Authors: Dheyaa Wajid Abbood, Hanan Hussien Abood
Abstract:
Stepped cascade has been utilized as a hydraulic structure for years. It has proven to be the least costly aeration system in replenishing dissolved oxygen. Numerical modeling of stepped cascade with end sill is very complicated and challenging because of the high roughness and velocity re circulation regions. Volume of fluid multiphase flow model (VOF) is used .The realizable k-ξ model is chosen to simulate turbulence. The computational results are compared with lab-scale stepped cascade data. The lab –scale model was constructed in the hydraulic laboratory, Al-Mustansiriya University, Iraq. The stepped cascade was 0.23 m wide and consisted of 3 steps each 0.2m high and 0.6 m long with variable end sill. The discharge was varied from 1 to 4 l/s. ANSYS has been employed to simulate the experimental data and their related results. This study shows that ANSYS is able to predict results almost the same as experimental findings in some regions of the structure.Keywords: stepped cascade weir, aeration, multiphase flow model, ansys
Procedia PDF Downloads 32820407 Teaching Vietnamese as the Official Language for Indigenous Preschool Children in Lai Chau, Vietnam: Exploring Teachers' Beliefs about Second Language Acquisition
Authors: Thao Thi Vu, Libby Lee-Hammond, Andrew McConney
Abstract:
In Vietnam, the Vietnamese language is normally used as the language of instruction. The dominance of this language places children who have a different first language such as Indigenous children at a disadvantage when commencing school. This study explores preschool teachers’ beliefs about second language acquisition in Lai Chau provinces where is typical of highland provinces of Vietnam and the proportion of Indigenous minority groups in high. Data were collected from surveys with both closed-end questions and opened-end questions. The participants in this study were more than 200 public preschool teachers who come from eight different districts in Lai Chau. An analysis of quantitative data survey is presented to indicate several practical implications, such as the connection between teachers’ knowledge background that gained from their pre-service and in-service teacher education programs regarding second language teaching for Indigenous children and their practice. It also explains some factors that influence teachers’ beliefs and perspective about Indigenous children and pedagogies in their classes.Keywords: indigenous children, learning Vietnamese, preschool, teachers’ beliefs
Procedia PDF Downloads 41520406 Spatio-Temporal Analysis and Mapping of Malaria in Thailand
Authors: Krisada Lekdee, Sunee Sammatat, Nittaya Boonsit
Abstract:
This paper proposes a GLMM with spatial and temporal effects for malaria data in Thailand. A Bayesian method is used for parameter estimation via Gibbs sampling MCMC. A conditional autoregressive (CAR) model is assumed to present the spatial effects. The temporal correlation is presented through the covariance matrix of the random effects. The malaria quarterly data have been extracted from the Bureau of Epidemiology, Ministry of Public Health of Thailand. The factors considered are rainfall and temperature. The result shows that rainfall and temperature are positively related to the malaria morbidity rate. The posterior means of the estimated morbidity rates are used to construct the malaria maps. The top 5 highest morbidity rates (per 100,000 population) are in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4, 97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82). According to the DIC criterion, the proposed model has a better performance than the GLMM with spatial effects but without temporal terms.Keywords: Bayesian method, generalized linear mixed model (GLMM), malaria, spatial effects, temporal correlation
Procedia PDF Downloads 44520405 Addressing the Exorbitant Cost of Labeling Medical Images with Active Learning
Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj
Abstract:
Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net
Procedia PDF Downloads 14620404 Corporate Social Responsibility and Corporate Reputation: A Bibliometric Analysis
Authors: Songdi Li, Louise Spry, Tony Woodall
Abstract:
Nowadays, Corporate Social responsibility (CSR) is becoming a buzz word, and more and more academics are putting efforts on CSR studies. It is believed that CSR could influence Corporate Reputation (CR), and they hold a favourable view that CSR leads to a positive CR. To be specific, the CSR related activities in the reputational context have been regarded as ways that associate to excellent financial performance, value creation, etc. Also, it is argued that CSR and CR are two sides of one coin; hence, to some extent, doing CSR is equal to establishing a good reputation. Still, there is no consensus of the CSR-CR relationship in the literature; thus, a systematic literature review is highly in need. This research conducts a systematic literature review with both bibliometric and content analysis. Data are selected from English language sources, and academic journal articles only, then, keyword combinations are applied to identify relevant sources. Data from Scopus and WoS are gathered for bibliometric analysis. Scopus search results were saved in RIS and CSV formats, and Web of Science (WoS) data were saved in TXT format and CSV formats in order to process data in the Bibexcel software for further analysis which later will be visualised by the software VOSviewer. Also, content analysis was applied to analyse the data clusters and the key articles. In terms of the topic of CSR-CR, this literature review with bibliometric analysis has made four achievements. First, this paper has developed a systematic study which quantitatively depicts the knowledge structure of CSR and CR by identifying terms closely related to CSR-CR (such as ‘corporate governance’) and clustering subtopics emerged in co-citation analysis. Second, content analysis is performed to acquire insight on the findings of bibliometric analysis in the discussion section. And it highlights some insightful implications for the future research agenda, for example, a psychological link between CSR-CR is identified from the result; also, emerging economies and qualitative research methods are new elements emerged in the CSR-CR big picture. Third, a multidisciplinary perspective presents through the whole bibliometric analysis mapping and co-word and co-citation analysis; hence, this work builds a structure of interdisciplinary perspective which potentially leads to an integrated conceptual framework in the future. Finally, Scopus and WoS are compared and contrasted in this paper; as a result, Scopus which has more depth and comprehensive data is suggested as a tool for future bibliometric analysis studies. Overall, this paper has fulfilled its initial purposes and contributed to the literature. To the author’s best knowledge, this paper conducted the first literature review of CSR-CR researches that applied both bibliometric analysis and content analysis; therefore, this paper achieves its methodological originality. And this dual approach brings advantages of carrying out a comprehensive and semantic exploration in the area of CSR-CR in a scientific and realistic method. Admittedly, its work might exist subjective bias in terms of search terms selection and paper selection; hence triangulation could reduce the subjective bias to some degree.Keywords: corporate social responsibility, corporate reputation, bibliometric analysis, software program
Procedia PDF Downloads 123