Search results for: formal approach

Authors: Amedeo D'Angiulli, Kylie Schibli

Abstract:

Traditionally, children’s brain development research has emphasized the limitative aspects of disability and impairment, electing as an explanatory model the classical clinical notions of brain lesion or functional deficit. In contrast, Positive Educational Neuroscience (PEN) is a new approach that emphasizes strengths and human flourishing related to the brain by exploring how learning practices have the potential to enhance neurocognitive flexibility through neuroplastic overcompensation. This mini-review provides an overview of PEN and shows how it links to the concept of neurocognitive flexibility. We provide examples of how the present concept of neurocognitive flexibility can be applied to special education by exploring examples of neuroplasticity in the learning domain, including: (1) learning to draw in congenitally totally blind children, and (2) music training in children from disadvantaged neighborhoods. PEN encourages educators to focus on children’s strengths by recognizing the brain’s capacity for positive change and to incorporate activities that support children’s individual development.

Keywords: neurocognitive development, positive educational neuroscience, sociocultural approach, special education

Procedia PDF Downloads 238

Authors: Angel Champion, Sadia Kanwal, Rafat Siddiqui

Abstract:

Harnessing phytochemicals from plant sources presents a novel opportunity to prevent or treat malignant diseases, including breast cancer. Chemotherapy lacks precision in targeting cancerous cells while sparing normal cells, but a phytopharmaceutical approach may offer a solution. Dandelion, a common weed plant, is rich in phytochemicals and provides a safer, more cost-effective alternative with lower toxicity than traditional pharmaceuticals for conditions such as breast cancer. In this study, an in-vitro experiment will be conducted using the ethanol extract of Dandelion on triple-negative MDA-231 breast cancer cell lines. The polyphenolic analysis revealed that the Dandelion extract, particularly from the root and leaf (both cut and sifted), had the most potent antioxidant properties and exhibited the most potent antioxidation activity from the powdered leaf extract. The extract exhibits prospective promising effects for inducing cell proliferation and apoptosis in breast cancer cells, highlighting its potential for targeted therapeutic interventions. Standardizing methods for Dandelion use is crucial for future clinical applications in cancer treatment. Combining plant-derived compounds with cancer nanotechnology holds the potential for effective strategies in battling malignant diseases. Utilizing liposomes as carriers for phytoconstituent anti-cancer agents offers improved solubility, bioavailability, immunoregulatory effects, advancing anticancer immune function, and reducing toxicity. This integrated approach of natural products and nanotechnology has significant potential to revolutionize healthcare globally, especially in underserved communities where herbal medicine is prevalent.

Keywords: apoptosis, antioxidant activity, cancer nanotechnology, phytopharmaceutical

Procedia PDF Downloads 49

Authors: Naila Nasreen, Dianchen Lu

Abstract:

This paper explores the dynamical behavior of the (2+1)-dimensional Boussinesq equation, which is a nonlinear water wave equation and is used to model wave packets in dispersive media with weak nonlinearity. This equation depicts how long wave made in shallow water propagates due to the influence of gravity. The (2+1)- dimensional Boussinesq equation combines the two-way propagation of the classical Boussinesq equation with the dependence on a second spatial variable, as that occurs in the two-dimensional Kadomstev- Petviashvili equation. This equation provides a description of head- on collision of oblique waves and it possesses some interesting properties. The governing model is discussed by the assistance of Ricatti equation mapping method, a relatively integration tool. The solutions have been extracted in different forms the solitary wave solutions as well as hyperbolic and periodic solutions. Moreover, the sensitivity analysis is demonstrated for the designed dynamical structural system’s wave profiles, where the soliton wave velocity and wave number parameters regulate the water wave singularity. In addition to being helpful for elucidating nonlinear partial differential equations, the method in use gives previously extracted solutions and extracts fresh exact solutions. Assuming the right values for the parameters, various graph in different shapes are sketched to provide information about the visual format of the earned results. This paper’s findings support the efficacy of the approach taken in enhancing nonlinear dynamical behavior. We believe this research will be of interest to a wide variety of engineers that work with engineering models. Findings show the effectiveness simplicity, and generalizability of the chosen computational approach, even when applied to complicated systems in a variety of fields, especially in ocean engineering.

Keywords: (2+1)-dimensional Boussinesq equation, solitary wave solutions, Ricatti equation mapping approach, nonlinear phenomena

Procedia PDF Downloads 94

Authors: L. Hamsaveni, Navya Prakash, Suresha

Abstract:

Document Image Analysis recognizes text and graphics in documents acquired as images. An approach without Optical Character Recognition (OCR) for degraded document image analysis has been adopted in this paper. The technique involves document imaging methods such as Image Fusing and Speeded Up Robust Features (SURF) Detection to identify and extract the degraded regions from a set of document images to obtain an original document with complete information. In case, degraded document image captured is skewed, it has to be straightened (deskew) to perform further process. A special format of image storing known as YCbCr is used as a tool to convert the Grayscale image to RGB image format. The presented algorithm is tested on various types of degraded documents such as printed documents, handwritten documents, old script documents and handwritten image sketches in documents. The purpose of this research is to obtain an original document for a given set of degraded documents of the same source.

Keywords: grayscale image format, image fusing, RGB image format, SURF detection, YCbCr image format

Procedia PDF Downloads 372

Authors: Rachel P. Vasconcellos

Abstract:

The Russian constructivism is usually enshrined in history as another ''modernist ism'', that is, as an artistic phenomenon related to the early twentieth century‘s zeitgeist. What we aim in this essay is to analyze the constructivist movement not over the Art History field neither through the aesthetic debate, but through a geographical critical theory, taking the main idea of construction in the concrete sense of production of space. Seen from the perspective of the critique of space, the constructivist production is presented as a plan of totality, designed as socialist society‘s spatiality, contemplating and articulating all its scalar levels: the objects of everyday life, the building, the city and the territory. The constructivist avant-garde manifests a geographical ideology, launching the foundation‘s basis of modern planning ideology. Taken in its political sense, the artistic avant-garde of the Russian Revolution intended to anticipate the forms of a social future already put in progress: their plastic research pointed to new formal expressions to revolutionary contents. With the foundation of new institutions under a new State, it was given to the specialized labor of artists, architects, and planners the task of designing the socialist society, based on the thesis of scientific socialism. Their projects were developed under the politico-economics imperatives to the Soviet modernization – that is: the structural needs of industrialization and inclusion of all people in the productive work universe. This context shapes the creative atmosphere of the constructivist avant-garde, which uses the methods of engineering to the transform everyday life. Architecture, urban planning, and state planning integrated must then operate as spatial arrangement morphologically able to produce socialist life. But due to the intrinsic contradictions of the process, the rational and geometric aesthetic of the City-Machine appears, finally, as an image of a scientific socialist utopia.

Keywords: city-machine, critique of space, production of space, soviet territorialization

Procedia PDF Downloads 273

Authors: Jia Xin Low, Keng Wah Choo

Abstract:

This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: convolutional neural network, discrete wavelet transform, deep learning, heart sound classification

Procedia PDF Downloads 342

Authors: Kristel Faye Tandog

Abstract:

The State Owned Enterprise (SOE) or also called Public Enterprise (PE) has been playing a vital role in a country’s social and economic development. Following this idea, this study focused on the Factor Structures of Financial Performance of the Local Economic Enterprises (LEEs) namely: Food Court, Market, Slaughterhouse, and Terminal in Matalam, Cotabato. It aimed to determine the profile of the LEEs in terms of organizational structure, manner of creation, years in operation, source of initial operating requirements, annual operating budget, geographical location, and size or description of the facility. This study also included the different financial ratios of LEE that covered a five year period from Calendar Year 2009 to 2013. Primary data using survey questionnaire was administered to 468 respondents and secondary data were sourced out from the government archives and financial documents of the said LGU. There were 12 dominant factors identified namely: “management”, “enforcement of laws”, “strategic location”, “existence of non-formal competitors”, “proper maintenance”, “pricing”, “customer service”, “collection process”, “rentals and services”, “efficient use of resources”, “staffing”, and “timeliness and accuracy”. On the other hand, the financial performance of the LEE of Matalam, Cotabato using financial ratios needs reformatting. This denotes that refinement as to the following ratios: Cash Flow Indicator, Activity, Profitability and Growth is necessary. The cash flow indicator ratio showed difficulty in covering its debts in successive years. Likewise, the activity ratios showed that the LEE had not been effective in putting its investment at work. Moreover, profitability ratios revealed that it had operated in minimum capacity and had incurred net losses and thus, it had a weak profit performance. Furthermore, growth ratios showed that LEE had a declining growth trend particularly in net income.

Keywords: factor structures, financial performance, financial ratios, state owned enterprises

Procedia PDF Downloads 252

Authors: K. Sathishkumar, V. Thiagarasu

Abstract:

Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

Procedia PDF Downloads 320

Authors: Rupu Yang, Cong Toan Tran, Assaad Zoughaib

Abstract:

The work provides an iterative nonlinear programming method to synthesize a heat exchanger network by manipulating the trade-offs between the heat load of process heat exchangers (HEs) and utilities. We consider for the synthesis problem two cases, the first one without fixed cost for HEs, and the second one with fixed cost. For the no fixed cost problem, the nonlinear programming (NLP) model with all the potential HEs is optimized to obtain the global optimum. For the case with fixed cost, the NLP model is iterated through adding/removing HEs. The method was applied in five case studies and illustrated quite well effectiveness. Among which, the approach reaches the lowest TAC (2,904,026$/year) compared with the best record for the famous Aromatic plants problem. It also locates a slightly better design than records in literature for a 10 streams case without fixed cost with only 1/9 computational time. Moreover, compared to the traditional mixed-integer nonlinear programming approach, the iterative NLP method opens a possibility to consider constraints (such as controllability or dynamic performances) that require knowing the structure of the network to be calculated.

Keywords: heat exchanger network, synthesis, NLP, optimization

Procedia PDF Downloads 156

Authors: Mohamed Karodia

Abstract:

Accountancy as a subject is one of the sciences that for many years has been perceived as a difficult subject to study and teach. Yet, it continuously attracts scholars graduating from school and entering Higher Education Institutions as a subject of choice and career. The teaching and learning of this subject have not been easy and has evolved and progressed over the past few decades however students still find it difficult to study and this has resulted in poor student achievement. In search of solutions, this study has considered the effect and efficacy that study skills have on the performance of Accountancy students and in particular students studying Second Year Diploma in Accountancy at the University of Johannesburg. These students appear to have a lack of appropriate study skills and as a result of these impacts on their performance in the courses, they are studying. This study also focuses on strategies to enhance Second Year Diploma Accountancy students’ academic performance. A literature review was conducted to investigate what scholarly literature suggests about study skills, in general, and in particular for Accountancy to be successful. In order to determine what study skills Second Year Accountancy students are applying when they learn and why they are failing the Accountancy examinations and formal class tests, the study adopted the quantitative research method. A questionnaire addressing various aspects of study skills, studying accountancy and studying, in general, was provided to 800 students studying Second Year Diploma in Accountancy at the University of Johannesburg’s Soweto Campus. The quantitative data collected were analyzed using descriptive statistics in the form of proportions, frequencies, means, and standard deviations, t-tests to compare differences between two groups as well as correlations between variables. Based on the findings of this study, it is recommended that students are provided with courses in time management, procrastination, reading, note taking and writing, test preparation techniques as well as study attitude. Lecturers spend more time teaching students how to study in general as well as accountancy specifically preferably at the first-year level before proceeding to the second year. It is also recommended that the University implements a study skills course to assist the students with studying.

Keywords: accountancy, skills, strategies, study

Procedia PDF Downloads 129

Authors: A. Chandra, M. Arthur, L. Mize, A. Pomeroy-Stevens

Abstract:

Background: Lower and middle-income countries (LMICs) in Asia face rapid urbanization resulting in both economic opportunities (the urban advantage) and emerging health challenges. Urban health risks are magnified in informal settlements and include infectious disease outbreaks, inadequate access to health services, and poor air quality. Over the coming years, urban spaces in Asia will face accelerating public health risks related to migration, climate change, and environmental health. These challenges are complex and require multi-sectoral and multi-stakeholder solutions. The Building Health Cities (BHC) program is funded by the United States Agency for International Development (USAID) to work with smart city initiatives in the Asia region. BHC approaches urban health challenges by addressing policies, planning, and services through a health equity lens, with a particular focus on informal settlements and migrant communities. The program works to develop data-driven decision-making, build inclusivity through stakeholder engagement, and facilitate the uptake of appropriate technology. Methodology: The BHC program has partnered with the smart city initiatives of Indore in India, Makassar in Indonesia, and Da Nang in Vietnam. Implementing partners support municipalities to improve health delivery and equity using two key approaches: political economy analysis and participatory systems mapping. Political economy analyses evaluate barriers to collective action, including corruption, security, accountability, and incentives. Systems mapping evaluates community health challenges using a cross-sectoral approach, analyzing the impact of economic, environmental, transport, security, health system, and built environment factors. The mapping exercise draws on the experience and expertise of a diverse cohort of stakeholders, including government officials, municipal service providers, and civil society organizations. Results: Systems mapping and political economy analyses identified significant barriers for health care in migrant populations. In Makassar, migrants are unable to obtain the necessary card that entitles them to subsidized health services. This finding is being used to engage with municipal governments to mitigate the barriers that limit migrant enrollment in the public social health insurance scheme. In Indore, the project identified poor drainage of storm and wastewater in migrant settlements as a cause of poor health. Unsafe and inadequate infrastructure placed residents of these settlements at risk for both waterborne diseases and injuries. The program also evaluated the capacity of urban primary health centers serving migrant communities, identifying challenges related to their hours of service and shortages of health workers. In Da Nang, the systems mapping process has only recently begun, with the formal partnership launched in December 2019. Conclusion: This paper explores lessons learned from BHC’s systems mapping, political economy analyses, and stakeholder engagement approaches. The paper shares progress related to the health of migrants in informal settlements. Case studies feature barriers identified and mitigating steps, including governance actions, taken by local stakeholders in partner cities. The paper includes an update on ongoing progress from Indore and Makassar and experience from the first six months of program implementation from Da Nang.

Keywords: informal settlements, migration, stakeholder engagement mapping, urban health

Procedia PDF Downloads 113

Authors: Skyler Kim

Abstract:

An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

Procedia PDF Downloads 183

Authors: Mohd Ridzwan Yaakub, Muhammad Iqbal Abu Latiffi

Abstract:

Online business has become popular recently due to the massive amount of information and medium available on the Internet. This has resulted in the huge number of reviews where the consumers share their opinion, criticisms, and satisfaction on the products they have purchased on the websites or the social media such as Facebook and Twitter. However, to analyze customer’s behavior has become very important for organizations to find new market trends and insights. The reviews from the websites or the social media are in structured and unstructured data that need a sentiment analysis approach in analyzing customer’s review. In this article, techniques used in will be defined. Definition of the ontology and description of its possible usage in sentiment analysis will be defined. It will lead to empirical research that related to mobile phones used in research and the ontology used in the experiment. The researcher also will explore the role of preprocessing data and feature selection methodology. As the result, ontology-based approach in sentiment analysis can help in achieving high accuracy for the classification task.

Keywords: feature selection, ontology, opinion, preprocessing data, sentiment analysis

Procedia PDF Downloads 194

Authors: Benjamin Poku

Abstract:

Purpose: The purpose of the research is to conduct systematic reviews and synthesis of existing knowledge that addresses the growing incidence and prevalence of chronic diseases across the world and its impact on public health in relation to communicable diseases. Principal results: A careful compilation and summary of 15-20 peer-reviewed publications from reputable databases such as PubMed, MEDLINE, CINAHL, and other peer-reviewed journals indicate that the Global pandemic of Chronic diseases (such as diabetes, high blood pressure, etc.) have become a greater public health burden in proportion as compared to communicable diseases. Significant conclusions: Given the complexity of the situation, efforts and strategies to mitigate the negative effect of the Global Pandemic on chronic diseases within the global community must include not only urgent and binding commitment of all stakeholders but also a multi-sectorial long-term approach to increase the public health educational approach to meet the increasing world population of over 8 billion people and also the aging population as well to meet the complex challenges of chronic diseases.

Keywords: pandemic, chronic disease, public health, health challenges

Procedia PDF Downloads 523

Authors: Sunil Chandra, Himanshu Rawat, Vikas Gusain, Triparna Barman

Abstract:

Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within reserved forests, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differenced normalized burnt ratio (dNBR) index approach that uses the burnt ratio values generated using the Short-Wave Infrared (SWIR) band and Near Infrared (NIR) bands of the Sentinel-2 image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel-2 bands. The training and testing data are generated from the Sentinel-2 data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated using spectral unmixing methods, which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.

Keywords: categorical data, log linear modeling, neural network, shifting cultivation

Procedia PDF Downloads 40

Authors: Gastão Soares Ximenes de Oliveira, Richar Nicolás Durán, Romeo Micah Szmoski, Eloiza Aparecida Avila de Matos, Elano Gustavo Rein

Abstract:

This article aims to present an experimental method to determine Planck's constant by calculating the cutting potential V₀ from LEDs with different wavelengths. The experiment is designed using Arduino as a central tool in order to make the experimental activity more engaging and attractive for students with the use of digital technologies. From the characteristic curves of each LED, graphical analysis was used to obtain the cutting potential, and knowing the corresponding wavelength, it was possible to calculate Planck's constant. This constant was also obtained from the linear adjustment of the cutting potential graph by the frequency of each LED. Given the relevance of Planck's constant in physics, it is believed that this experiment can offer teachers the opportunity to approach concepts from modern physics, such as the quantization of energy, in a more accessible and applied way in the classroom. This will not only enrich students' understanding of the fundamental nature of matter but also encourage deeper engagement with the principles of quantum physics.

Keywords: physics teaching, educational technology, modern physics, Planck constant, Arduino

Procedia PDF Downloads 69

Authors: Dongyeob Han, Jungwon Huh, Quang Huy Tran, Choonghyun Kang

Abstract:

Unmanned Aerial Vehicles (UAVs) have been used for surveillance, monitoring, inspection, and mapping. In this paper, we present a systematic approach for automatic registration of UAV images for monitoring facilities such as building, green house, and civil structures. The two-step process is applied; 1) an image matching technique based on SURF (Speeded up Robust Feature) and RANSAC (Random Sample Consensus), 2) bundle adjustment of multi-temporal images. Image matching to find corresponding points is one of the most important steps for the precise registration of multi-temporal images. We used the SURF algorithm to find a quick and effective matching points. RANSAC algorithm was used in the process of finding matching points between images and in the bundle adjustment process. Experimental results from UAV images showed that our approach has a good accuracy to be applied to the change detection of facility.

Keywords: building, image matching, temperature, unmanned aerial vehicle

Procedia PDF Downloads 287

Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

Abstract:

Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness

Procedia PDF Downloads 284

Authors: Oksana Razina, Shakeel Ahmad, Jessie Qun Ren, Olufemi Isiaq

Abstract:

The modern life of businesses is categorically reliant on their established position online, where digital (and particularly website) content plays a significant role as the first point of information. Digital content, therefore, becomes essential – from making the first impression to the building and development of client relationships. Despite a number of valuable papers suggesting a strategic approach when dealing with digital data, other sources often do not view or accept the approach to digital content as a holistic or continuous process. Associations are frequently made with merely a one-off marketing campaign or similar. The challenge is to establish an agreed definition for the notion of Digital Content Strategy, which currently does not exist, as DCS is viewed from an excessive number of different angles. A strategic approach to content, nonetheless, is required, both practically and contextually. The researchers, therefore, aimed at attempting to identify the key content components comprising a digital content strategy to ensure all the aspects were covered and strategically applied – from the company’s understanding of the content value to the ability to display flexibility of content and advances in technology. This conceptual project evaluated existing literature on the topic of Digital Content Strategy (DCS) and related aspects, using the PRISMA Systematic Review Method, Document Analysis, Inclusion and Exclusion Criteria, Scoping Review, Snow-Balling Technique and Thematic Analysis. The data was collected from academic and statistical sources, government and relevant trade publications. Based on the suggestions from academics and trading sources related to the issues discussed, the researchers revealed the key actions for content creation and attempted to define the notion of DCS. The major finding of the study presented Key Content Components of Digital Content Strategy and can be considered for implementation in a business retail setting.

Keywords: digital content strategy, key content components, websites, digital marketing strategy

Procedia PDF Downloads 140

Authors: Chijindu Okpalaoka, Charles Chinedu Onuselogu

Abstract:

COVID-19, humanity's coronavirus disease caused by SARS-CoV-2, was first detected in late 2019 in Wuhan, China. COVID-19 lacked an established conventional pharmaceutical therapy, and as a result, the outbreak quickly became an epidemic affecting the entire World. Only a qPCR assay is reliable for diagnosing COVID-19. Clustered, regularly interspaced short palindromic repeats (CRISPR) technology is being researched for speedy and specific identification of COVID-19, among other therapeutic techniques. Apart from its therapeutic capabilities, the CRISPR technique is being evaluated to develop antiviral therapies; nevertheless, no CRISPR-based medication has been approved for human use to date. Prophylactic antiviral CRISPR in living being cells, a Cas 13-based approach against coronavirus, has been developed. While this method can be evolved into a treatment approach, it may face substantial obstacles in human clinical trials for licensure. This study discussed the potential applications of CRISPR-based techniques for developing a speedy and accurate feasible treatment alternative for the COVID-19 virus.

Keywords: COVID-19, CRISPR technique, Cas13, SARS-CoV-2, prophylactic antiviral

Procedia PDF Downloads 120

Authors: Sumaira Taj

Abstract:

Blended learning is emerged as a prerequisite approach for teaching in all schools after the outbreak of the COVID-19 pandemic. However, how much public elementary and secondary schools in Pakistan are ready for adapting this approach and what should be done to prepare schools and students for blended learning are the questions that this paper attempts to answer. Mixed-method research methodology was used to collect data from 40 teachers, 500 students, and 10 mothers. Descriptive statistics was used to analyze quantitative data. As for as readiness is concerned, schools lack resources for blended/ virtual/ online classes from infra-structure to skills, parents’ literacy level hindered students’ learning process and teachers’ skills presented challenges in a smooth and swift shift of the schools from face-to-face learning to blended learning. It is recommended to establish a conducive environment in schools by providing all required resources and skills. Special trainings should be organized for low literacy level parents. Multiple ways should be adopted to benefit all students.

Keywords: blended learning, challenges in online classes, education in covid-19, public schools in pakistan

Procedia PDF Downloads 161

Authors: Hanan Eltayeb, Reem Al Refaie

Abstract:

To be able to connect and relate to shows spoken in a foreign language, advanced learners must understand not only linguistics inferences but also cultural, metacognitive, and pragmatic connotations in colloquial Egyptian TV series. These connotations are needed to both understand the different facets of the dramas put before them, and they’re also consistently grown and formulated through watching these shows. The inferences have become a staple in the Egyptian colloquial culture over the years, making their way into day-to-day conversations as Egyptians use them to speak, relate, joke, and connect with each other, without having known one another from previous times. As for advanced learners, they need to understand these inferences not only to watch these shows, but also to be able to converse with Egyptians on a level that surpasses the formal, or standard. When faced with some of the somewhat recent shows on the Egyptian screens, learners faced challenges in understanding pragmatics, cultural, and religious background of the target language and consequently not able to interact effectively with a native speaker in real-life situations. This study aims to enhance the linguistic and cultural proficiency of learners through studying two genres of TV Colloquial Egyptian series. Study samples derived from two recent comedian and social Egyptian series ('The Seventh Neighbor' سابع جار, and 'Nelly and Sherihan' نيللي و شريهان). When learners watch such series, they are usually faced with a problem understanding inferences that have to do with social, religious, and political events that are addressed in the series. Using discourse analysis of the sematic, semantic, pragmatic, cultural, and linguistic characteristics of the target language, some major deductions were highlighted and repeated, showing a pattern in both. The research paper concludes that there are many sets of lingual and para-lingual phrases, idioms, and proverbs to be acquired and used effectively by teaching these series. The strategies adopted in the study can be applied to different types of media, like movies, TV shows, and even cartoons, to enhance student proficiency.

Keywords: Egyptian series, culture, linguistic competence, pragmatics, semantics, social

Procedia PDF Downloads 139

Authors: Chahrazed Zouaoui

Abstract:

In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

Procedia PDF Downloads 370

Authors: Carlo Cogliati

Abstract:

The study of the relationship of philosophical reason with the religious domain has been very much a concern for many of the Western philosophical and theological traditions. In this essay, I will suggest a proposal for an Eastern philosophy of religion based on Nishida’s contradictory identity of the two: philosophy soku hi (is, and yes is not) religion. This will pose a challenge to the traditional Western contents and methods of the discipline. This paper aims to serve three purposes. First, I will critically assess Charlesworth’s typology of the relation between philosophy and religion in the West: philosophy as/for/against/about/after religion. I will also engage Harrison’s call for a global philosophy of religion(s) and argue that, although it expands the scope and the range of the questions to address, it is still Western in its method. Second, I will present Nishida’s logic of absolutely contradictory self-identity as the instrument to transcend the dichotomous pair of identity and contradiction: ‘A is A’ and ‘A is not A’. I will then explain how this ‘concrete’ logic of the East, as opposed to the ‘formal’ logic of the West, exhibits at best the bilateral dynamic relation between philosophy and religion. Even as Nishida argues for the non-separability of the two, he is also aware and committed to their mutual non-reducibility. Finally, I will outline the resulting new relation between God and creatures. Nishida in his philosophy soku hi religion replaces the traditional Western dualistic concept of God with the Eastern non-dualistic understanding of God as “neither transcendent nor immanent, and at the same time both transcendent and immanent.” God is therefore a self-identity of contradiction, nowhere and yet everywhere present in the world of creatures. God as absolute being is also absolute nothingness: the world of creatures is the expression of God’s absolute self-negation. The overreaching goal of this essay is to offer an alternative to traditional Western approaches to philosophy of religion based on Nishida’s logic of absolutely contradictory self-identity, as an example of philosophical and religious counter(influence). The resulting relationship between philosophy and religion calls for a revision of traditional concepts and methods. The outcome is not to reformulate the Eastern predilection to not sharply distinguish philosophical thought from religious enlightenment rather to bring together philosophy and religion in the place of identity and difference.

Keywords: basho, Nishida Kitaro, shukyotetsugaku, soku hi, zettai mujunteki jikodoitsu no ronri

Procedia PDF Downloads 186

Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

Abstract:

Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

Procedia PDF Downloads 121

Authors: Olufunmilayo Folaranmi

Abstract:

This research was carried out to examine the impact of socio-cultural factors on the management and utilization of solid waste in Ibadan Metropolis. A descriptive survey research design was adopted for the study while a systematic and stratified random sampling technique was used to select 300 respondents which were categorized into high, middle and low-density areas. Four hypothesis were tested using chi-square test on variables of unavailability of waste disposal facilities and waste management, negligence of contractors to liaise with community members, lack of adequate environmental education and waste management and utilization, low level of motivation of sanitation workers with solid wastes management, lack of community full participation with solid waste management and utilization. Results showed that significant effect of waste disposal facilities on solid waste management and utilization (X2 +16.6, P < .05). Also, there is a significant relationship between negligence of the contractors to liaise with community elites with improper disposal (X2 = 87.5, P < .05). The motivation of sanitation workers is significantly related to solid waste management (X2 = 70.4, P < .05). Adequate environmental education and awareness influenced solid waste management. There was also a significant relationship between lack of community participation with waste management disposal and improper waste disposal. Based on the findings from the study it was recommended that the quality of life in urban centers should be improved, social welfare of the populace enhanced and environment should be adequately attended to. Poverty alleviation programmes should be intensified and made to live beyond the life of a particular administration, micro-credit facilities should be available to community members to promote their welfare. Lastly, sustained environmental education programmes for citizens at all levels of education, formal and informal through the use of agencies like Ethical and Attitudinal Reorientation Commission (EARCOM) and the National Orientation Agency (NOA).

Keywords: management, social welfare, socio-cultural factors, solid waste

Procedia PDF Downloads 224

Authors: Muhammad Iqbal, Hafiz Muhammad Tauqeer, Hamza Rafaqat, Muhammad Naveed, Muhammad Awais Irshad

Abstract:

Soil pollution with chromium (Cr) has become one of the most important concerns due to its toxicity for humans. To date, various remediation approaches have been employed for the remediation and management of Cr contaminated soils. Phytoextraction is an eco-friendly and emerging remediation approach which has gained attention due to several advantages over conventional remediation approach. The use of energy crops for phytoremediation is an emerging trend worldwide. These energy crops have high tolerance against various environmental stresses, the potential to grow in diverse ecosystems and high biomass production make them a suitable candidate for phytoremediation of contaminated soils. The removal efficiency of plants in phytoextraction depends upon several soil and plant factors including solubility, bioavailability and metal speciation in soils. A pot scale experiment was conducted to evaluate the phytoextraction potential of Arundo donax L. with the application of acetic acid (A.A) in Cr contaminated soils. Plants were grown in pots filled with 5 kg soils for 90 days. After 30 days plants acclimatization in pot conditions, plants were treated with various levels of Cr (2.5 mM, 5 mM, 7.5 mM, 10 mM) and A.A (Cr 2.5 mM + A.A 2.5 mM, Cr 5 mM + A.A 2.5 mM, Cr 7.5 mM + A.A 2.5 mM, Cr 10 mM + A.A 2.5 mM). The application of A.A significantly increased metal uptake and in roots and shoots of A. donax. This increase was observed at Cr 7.5 mM + A.A 2.5 mM but at high concentrations, visual symptoms of Cr toxicity were observed on leaves. Similarly, A.A applications also affect the activities of key enzymes including catalase (CAT), superoxidase dismutase (SOD), and ascorbate peroxidase (APX) in leaves of A. donax. Based on results it is concluded that the applications of A.A acid for phytoextraction is an alternative approach for the management of Cr affected soils and synthetic chelators should be replaced with organic acids.

Keywords: acetic acid, A. donax, chromium, energy crop, phytoextraction

Procedia PDF Downloads 382

Authors: Nuo Xu, Kok Hun Goh, Jeyatharan Kumarasamy

Abstract:

Pile load testing is significant during foundation construction due to its traditional role of design validation and routine quality control of the piling works. In order to verify whether piles can take loadings at specified settlements, piles will have to undergo working load test where the test load should normally up to 150% of the working load of a pile. Selection or sampling of piles for the working load test is done subject to the number specified in Singapore National Annex to Eurocode 7 SS EN 1997-1:2010. This paper presents an innovative way to rationalize the number of pile load test by adopting statistical analysis approach and looking at the coefficient of variance of pile elastic modulus using a case study at Singapore Tuas depot. Results are very promising and have shown that it is possible to reduce the number of working load test without influencing the reliability and confidence on the pile quality. Moving forward, it is suggested that more load test data from other geological formations to be examined to compare with the findings from this paper.

Keywords: elastic modulus of pile under soil interaction, jurong formation, kentledge test, pile load test

Procedia PDF Downloads 380

Authors: Rasha Waheeb, Bjorn Andersen, Rafa Shakir

Abstract:

Purpose The purpose of this study is to avoid delays that occur in emergency reconstruction projects especially in post disaster circumstances whether if they were natural or manmade due to their particular national and humanitarian importance. We presented a theoretical and practical concepts for projects management in the field of construction industry that deal with a range of global and local trails. This study aimed to identify the factors of effective delay in construction projects in Iraq that affect the time and the specific quality cost, and find the best solutions to address delays and solve the problem by setting parameters to restore balance in this study. 30 projects were selected in different areas of construction were selected as a sample for this study. Design/methodology/approach This study discusses the reconstruction strategies and delay in time and cost caused by different delay factors in some selected projects in Iraq (Baghdad as a case study).A case study approach was adopted, with thirty construction projects selected from the Baghdad region, of different types and sizes. Project participants from the case projects provided data about the projects through a data collection instrument distributed through a survey. Mixed approach and methods were applied in this study. Mathematical data analysis was used to construct models to predict delay in time and cost of projects before they started. The artificial neural networks analysis was selected as a mathematical approach. These models were mainly to help decision makers in construction project to find solutions to these delays before they cause any inefficiency in the project being implemented and to strike the obstacles thoroughly to develop this industry in Iraq. This approach was practiced using the data collected through survey and questionnaire data collection as information form. Findings The most important delay factors identified leading to schedule overruns were contractor failure, redesigning of designs/plans and change orders, security issues, selection of low-price bids, weather factors, and owner failures. Some of these are quite in line with findings from similar studies in other countries/regions, but some are unique to the Iraqi project sample, such as security issues and low-price bid selection. Originality/value we selected ANN’s analysis first because ANN’s was rarely used in project management , and never been used in Iraq to finding solutions for problems in construction industry. Also, this methodology can be used in complicated problems when there is no interpretation or solution for a problem. In some cases statistical analysis was conducted and in some cases the problem is not following a linear equation or there was a weak correlation, thus we suggested using the ANN’s because it is used for nonlinear problems to find the relationship between input and output data and that was really supportive.

Keywords: construction projects, delay factors, emergency reconstruction, innovation ANN, post disasters, project management

Procedia PDF Downloads 160

Authors: Utkan Caliskan

Abstract:

Two types of numerical codes based on finite volume method are developed in order to solve compressible Euler equations to simulate the flow through forward facing step channel. Both algorithms have AUSM+- up (Advection Upstream Splitting Method) scheme for flux splitting and two-stage Runge-Kutta scheme for time stepping. In this study, the flux calculations differentiate between the algorithm based on OpenFOAM mesh format which is called 'face-based' algorithm and the basic algorithm which is called 'element-based' algorithm. The face-based algorithm avoids redundant flux computations and also is more flexible with hybrid grids. Moreover, some of OpenFOAM’s preprocessing utilities can be used on the mesh. Parallelization of the face based algorithm for which atomic operations are needed due to the shared memory model, is also presented. For several mesh sizes, 2.13x speed up is obtained with face-based approach over the element-based approach.

Keywords: cell centered finite volume method, compressible Euler equations, OpenFOAM mesh format, OpenMP

Procedia PDF Downloads 312