Search results for: extracurricular English learning

Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

Abstract:

Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

Procedia PDF Downloads 122

Authors: Li-Ju Chen, Hsiang-Lin Chan, Hsin-Yi Kathy Cheng, Hui-Ju Chen

Abstract:

Stereotype behavior is one of the maladaptive syndromes of the individuals with autism. Most of the previous researches focused on the stereotype behavior with stimulating type, while less on the stereotype behavior about cognition (This research names it cognitive stereotype behavior; CSB). This research explored CSB and the rationality to explain CSB with imprinting phenomenon. After excluding the samples without CSB described, the data that came from 271 individuals with autism were recruited and analyzed with quantitative and qualitative analyses. This research discovers that : (1) Most of the individuals with autism originally came out CSB at 3 years old and more than a half of them appeared before 4 years old; The average age which firstly came out CSB was 6.10 years old, the average time insisting or ossifying CSB was 31.71 minutes each time and the average longest time which they last was 358.35 minutes (5.97 hours). (2) CSB demonstrates various aspects, this research classified them into 4 fields with 26 categories. They were categorized into sudden CSB or habitual CSB by imprinting performance. (3) Most of the autism commented that their CSBs were not necessary but they could not control them well. One-third of them appeared CSB suddenly and the first occurrence accompanied a strong emotional or behavioral response. (4) Whether respondent is the person with autism himself/herself or not was the critical element: on the awareness of the severity degree, disturbance degree, and the emotional /behavioral intensity at the first-time CSB happened. This study concludes imprinting could reasonably explain the phenomenon CSB forms. There are implications leading the individuals with autism and their family to develop coping strategies to promote individuals with autism having a better learning accomplishment and life quality in their future.

Keywords: autism, cognitive stereotype behavior, constructivism, imprinting, stereotype

Procedia PDF Downloads 114

Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins

Abstract:

Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.

Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system

Procedia PDF Downloads 141

Authors: J. Jebunnesa, Y. Budd, T. Mason

Abstract:

COVID-19 changed the pedagogical expectations of early childhood education as many teachers across Australia had to quickly adapt to new teaching practices such as remote teaching. An important factor in the successful implementation of any new teaching and learning approach is teacher preparation, however, due to the pandemic, the transformation to remote teaching was immediate. A timely question to be asked is how early childhood teachers managed the transition from face-to-face teaching to remote teaching and what was learned through this time. This study explores the experiences of early childhood educators in Australia during COVID-19 lockdowns. Data were collected from an online survey conducted through the official Facebook forum of “Early Childhood Education and Care Australia,” and a constructivist grounded theory methodology was used to analyse the data. Initial research results suggest changing expectations of teachers’ roles and responsibilities during the lockdown, with a significant category related to transitioning teacher identities emerging. The concept of transitioning represents the shift from the role of early childhood educator to educational innovator, essential worker, social worker, and health officer. The findings illustrate the complexity of early childhood educators’ roles during the pandemic.

Keywords: changing role of teachers, constructivist grounded theory, lessons learned, teaching during COVID-19

Procedia PDF Downloads 84

Authors: Hui Fang Huang Su, Jia Borror

Abstract:

This study compared two interventions for teaching math to preschool-aged students with autism spectrum disorder (ASD). The first is considered the business as usual (BAU) intervention, which uses the Strategies for Teaching Based on Autism Research (STAR) curriculum and discrete trial teaching as the instructional methodology. The second is the Math is Not Difficult (Project MIND) activity-embedded, naturalistic intervention. These interventions were randomly assigned to four preschool students with ASD classrooms and implemented over three months for Project Mind. We used measurement gained during the same three months for the STAR intervention. In addition, we used A quasi-experimental, pre-test/post-test design to compare the effectiveness of these two interventions in building mathematical knowledge and skills. The pre-post measures include three standardized instruments: the Test of Early Math Ability-3, the Problem Solving and Calculation subtests of the Woodcock-Johnson Test of Achievement IV, and the Bracken Test of Basic Concepts-3 Receptive. The STAR curriculum-based assessment is administered to all Baudhuin students three times per year, and we used the results in this study. We anticipated that implementing these two approaches would improve the mathematical knowledge and skills of children with ASD. Still, it is crucial to see whether a behavioral or naturalistic teaching approach leads to more significant results.

Keywords: early learning, autism, math for pre-schoolers, special education, teaching strategies

Procedia PDF Downloads 147

Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

Abstract:

Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

Procedia PDF Downloads 326

Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

Abstract:

Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

Procedia PDF Downloads 505

Authors: Sarah Elshahat, Tina Moffat

Abstract:

Suboptimal mental health is a considerable global public health challenge that leads to considerable inequalities worldwide. Newcomers are at elevated risk for developing mental health issues as a result of social exclusion, stigmatization, racism, unequal employment opportunities, and discrimination. The problem can be especially serious amongst Arabic-speaking immigrants and refugees (ASIR) whose mental wellness may have already been affected by exposure to political violence, persecution, hunger or war in their countries of origin. A scoping review was conducted to investigate pre- and post-migration mental health determinants amongst ASIR in North America (the U.S. and Canada), who are a rapidly growing population in both regions. Pertinent peer-reviewed papers and grey literature were located through a systematic search of five electronic databases (Medline, Embase, PsycINFO, Anthropology Plus, and Sociology Database). A stakeholder consultation was implemented to validate the analyzed findings of the included 44 studies. About 80% of the studies were carried out in the US, underscoring a lack of Canadian ASIR-mental health research. A gap in qualitative, mixed-method, and longitudinal research was detected, where approximately two-thirds of the studies adopted a cross-sectional method. Pre-migration determinants of mental health were related to the political unrest, violence and armed conflict in the Arab world, increasing post-traumatic stress disorder and psychological distress levels among ASIR. English language illiteracy and generational variations in acculturation patterns were major post-migration mental health triggering factors. Exposure to domestic violence, stigmatization, poverty, racialization, and harassment were significant post-migration mental health determinants that stem from social inequalities, triggering depression, and distress amongst ASIR. Family conflicts linked to child-rearing and gendered norms were considered as both pre- and post-migration mental health triggering factors. Most post-migration mental health protective factors were socio-culturally related and included the maintenance of positive ethnic identity, faith, family support, and community cohesion. Individual resilience, articulated as self-esteem and hope, was a significant negative predictor of depression and psychological distress among ASIR. Community-engaged, mixed-methods, and longitudinal studies are required to address the current gap in mental health research among ASIR in North America. A more thorough determination of potential mental health triggers and protective factors would help inform the development of mental wellness and resilience-promoting programs that are culturally sensitive to ASIR. On the policy level, the Health in All Policies framework of the World Health Organization can be potentially useful for addressing social and health inequalities among ASIR, reducing mental health challenges.

Keywords: depression, post-traumatic stress disorder, psychological distress, resilience

Procedia PDF Downloads 123

Authors: Roseanne Sharon Borromeo, Mariana Carvalho, Mariia Karizhenskaia

Abstract:

Healthcare providers need to comprehend cultural diversity for optimal patient-centered care, especially near the end of life. Although a universal method for navigating cultural differences would be ideal, culture’s high complexity makes this strategy impossible. Adding cultural humility, a process of self-reflection to understand personal and systemic biases and humbly acknowledging oneself as a learner when it comes to understanding another's experience leads to a meaningful process in palliative care generating respectful, honest, and trustworthy relationships. This study is a systematic review of the literature on cultural humility in palliative care research and best practices. Race, religion, language, values, and beliefs can affect an individual’s access to palliative care, underscoring the importance of culture in palliative care. Cultural influences affect end-of-life care perceptions, impacting bereavement rituals, decision-making, and attitudes toward death. Cultural factors affecting the delivery of care identified in a scoping review of Canadian literature include cultural competency, cultural sensitivity, and cultural accessibility. As the different parts of the world become exponentially diverse and multicultural, healthcare providers have been encouraged to give culturally competent care at the bedside. Therefore, many organizations have made cultural competence training required to expose professionals to the special needs and vulnerability of diverse populations. Cultural competence is easily standardized, taught, and implemented; however, this theoretically finite form of knowledge can dangerously lead to false assumptions or stereotyping, generating poor communication, loss of bonds and trust, and poor healthcare provider-patient relationship. In contrast, Cultural humility is a dynamic process that includes self-reflection, personal critique, and growth, allowing healthcare providers to respond to these differences with an open mind, curiosity, and awareness that one is never truly a “cultural” expert and requires life-long learning to overcome common biases and ingrained societal influences. Cultural humility concepts include self-awareness and power imbalances. While being culturally competent requires being skilled and knowledgeable in one’s culture, being culturally humble involves the sometimes-uncomfortable position of healthcare providers as students of the patient. Incorporating cultural humility emphasizes the need to approach end-of-life care with openness and responsiveness to various cultural perspectives. Thus, healthcare workers need to embrace lifelong learning in individual beliefs and values on suffering, death, and dying. There have been different approaches to this as well. Some adopt strategies for cultural humility, addressing conflicts and challenges through relational and health system approaches. In practice and research, clinicians and researchers must embrace cultural humility to advance palliative care practices, using qualitative methods to capture culturally nuanced experiences. Cultural diversity significantly impacts patient-centered care, particularly in end-of-life contexts. Cultural factors also shape end-of-life perceptions, impacting rituals, decision-making, and attitudes toward death. Cultural humility encourages openness and acknowledges the limitations of expertise in one’s culture. A consistent self-awareness and a desire to understand patients’ beliefs drive the practice of cultural humility. This dynamic process requires practitioners to learn continuously, fostering empathy and understanding. Cultural humility enhances palliative care, ensuring it resonates genuinely across cultural backgrounds and enriches patient-provider interactions.

Keywords: cultural competency, cultural diversity, cultural humility, palliative care, self-awareness

Procedia PDF Downloads 49

Authors: Osatuyi Kehinde Micheal

Abstract:

There is much research that has contributed to an improved understanding of the future of food security, especially during the COVID-19 pandemic. A pathway was developed by using a local community kitchen in Muizenberg in western cape province, cape town, south Africa, a case study to map out the future of food security in times of crisis. This kitchen aims to provide nutritious, affordable, plant-based meals to our community. It is also a place of diverse learning, sharing, empowering the volunteers, and growth to support the local economy and future resilience by sustaining our community kitchen for the community. This document contains an overview of the story of the community kitchen on how we create self-sustainability as a new pathway development to sustain the community and reduce Zero hunger in the regional food system. This paper describes the key elements of how we respond to covid-19 pandemic by sharing food parcels and creating 13 soup kitchens across the community to tackle the immediate response to covid-19 pandemic and agricultural systems by growing home food gardening in different homes, also having a consciousness Dry goods store to reduce Zero waste and a local currency as an innovation to reduce food crisis. Insights gained from our article and outreach and their value in how we create adaptation, transformation, and sustainability as a new development pathway to solve any future problem crisis in the food security system in our society.

Keywords: sustainability, food security, community development, adapatation, transformation

Procedia PDF Downloads 64

Authors: Penn P. Wu, Jeannie Jo

Abstract:

Blockchain technology has rapidly gained popularity in industry. This paper attempts to assist academia to answer four questions. First, should community colleges begin offering education to nurture blockchain-literate students for the job market? Second, what are the appropriate topical areas to cover? Third, should it be an individual course? And forth, should it be a technical or management course? This paper starts with identifying the knowledge domains of blockchain technology and the topical areas each domain has, and continues with placing them in appropriate academic territories (Computer Sciences vs. Business) and subjects (programming, management, marketing, and laws), and then develops an evaluation model to determine the appropriate topical area for community colleges to teach. The evaluation is based on seven factors: maturity of technology, impacts on management, real-world applications, subject classification, knowledge prerequisites, textbook readiness, and recommended pedagogies. The evaluation results point to an interesting direction that offering an introductory course is an ideal option to guide students through the learning journey of what blockchain is and how it applies to business. Such an introductory course does not need to engage students in the discussions of mathematics and sciences that make blockchain technologies possible. While it is inevitable to brief technical topics to help students build a solid knowledge foundation of blockchain technologies, community colleges should avoid offering students a course centered on the discussion of developing blockchain applications.

Keywords: blockchain, pedagogies, blockchain technologies, blockchain course, blockchain pedagogies

Procedia PDF Downloads 117

Authors: Ganesh B. Shinde, Vijaya B. Musande

Abstract:

Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

Procedia PDF Downloads 301

Authors: George Onomah

Abstract:

Background: The integration of information communication technology (ICT) in Mathematics education faces notable challenges, which this study aimed to dissect and understand. Objectives: The primary goal was to assess the internal and external factors affecting the adoption of ICT by in-service Mathematics teachers. Internal factors examined included teachers' pedagogical beliefs, prior teaching experience, attitudes towards computers, and proficiency with technology. External factors included the availability of technological resources, the level of ICT training received, the sufficiency of allocated time for technology use, and the institutional culture within educational environments. Methods: A descriptive survey design was employed to methodically investigate these factors. Data collection was carried out using a five-point Likert scale questionnaire, administered to a carefully selected sample of 100 in-service Mathematics teachers through a combination of purposive and convenience sampling techniques. Findings: Results from multiple regression analysis revealed a significant underutilization of ICT in Mathematics teaching, highlighting a pronounced deficiency in current classroom practices. Recommendations: The findings suggest an urgent need for educational department heads to implement regular and comprehensive ICT training programs aimed at enhancing teachers' technological capabilities and promoting the integration of ICT in Mathematics teaching methodologies.

Keywords: ICT, Mathematics, integration, barriers

Procedia PDF Downloads 30

Authors: Julie Chuah Suan Choo

Abstract:

Due to the continuous change in workforce and the demands of the global workplace, many employers had lamented that the majority of university graduates were not prepared in the key areas of employment such as critical thinking, writing, self-direction and global knowledge which are most needed for the purposes of promotion. Further, critical thinking skills are deemed as integral parts of transformational pedagogy which aims at having a more informed society. To add to this, literature teaching has recently been advocated for enhancing students’ critical thinking and reasoning. Thus this study explored the effects of incorporating a few strategies in teaching literature, namely a Shakespeare play, into a course design to enhance these skills. An experiment involving a pretest and posttest using the California Critical Thinking Skills Test (CCTST) were administered on 80 first-year students enrolled in the Bachelor of Arts programme who were randomly assigned into the control group and experimental group. For the next 12 weeks, the experimental group was given intervention which included guided in-class discussion with Socratic questioning skills, learning log to detect their weaknesses in logical reasoning; presentations and quizzes. The results of CCTST which included paired T-test using SPSS version 22 indicated significant differences between the two groups. Findings have significant implications on the course design as well as pedagogical practice in using literature to enhance students’ critical thinking skills.

Keywords: literature teaching, critical thinking, California critical thinking skills test (CCTST), course design

Procedia PDF Downloads 450

Authors: Bin Liu

Abstract:

MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

Procedia PDF Downloads 145

Authors: Shahla Ali

Abstract:

In the context of promoting green infrastructure development, new opportunities are emerging to re-examine sustainable development practices. This paper presents an initial exploration of the development of community-investor dispute prevention and facilitation mechanisms in the context of the Belt and Road Initiative (BRI) spanning Asia, Africa, and Europe. Given the widescale impact of China’s multi-jurisdictional development initiative, learning how to coordinate with local communities is vital to realizing inclusive and sustainable growth. In the 20 years since the development of the first multilateral community-investor dispute resolution mechanism developed by the International Finance Centre/World Bank, much has been learned about public facilitation, community engagement, and dispute prevention during the early stages of major infrastructure development programs. This paper will explore initial findings as they relate to initiatives underway along the BRI within the Asian Infrastructure Investment Bank and the Asian Development Bank. Given the borderless nature of sustainability concerns, insights from diverse regions are critical to deepening insights into best practices. Drawing on a case-based methodology, this paper will explore the achievements, challenges, and lessons learned in community-investor dispute prevention and resolution for major infrastructure projects in the greater China region.

Keywords: law and development, dispute prevention, sustainable development, mitigation

Procedia PDF Downloads 88

Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

Abstract:

Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

Procedia PDF Downloads 38

Authors: Zhang Shuqi, Liu Dan

Abstract:

For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

Procedia PDF Downloads 87

Authors: Smah Almotiri

Abstract:

One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

Procedia PDF Downloads 168

Authors: Khulud Alhussain, Anna Gavine, Stephen Macgillivray, Sushila Chowdhry

Abstract:

Background: Estimates show that by the year 2030, mental illness will account for more than half of the global economic burden, second to non-communicable diseases. Often, the perinatal period is characterised by psychological ambivalence and a mixed anxiety-depressive condition. Maternal mental disorder is associated with perinatal anxiety and depression and affects breastfeeding behaviors. Studies also indicate that maternal mental health can considerably influence a baby's health in numerous aspects and impact the newborn health due to lack of adequate breastfeeding. However, studies reporting factors associated with breastfeeding behaviors are predominantly quantitative. Therefore, it is not clear what literature is available to understand the factors affecting breastfeeding and perinatal women’s perspectives and experiences. Aim: This review aimed to explore the perceptions and experiences of women with perinatal anxiety and depression, as well as how these experiences influence their breastfeeding behaviours. Methods: A systematic literature review of qualitative studies in line with the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ). Four electronic databases (CINAHL, PsycINFO, Embase, and Google Scholar) were explored for relevant studies using a search strategy. The search was restricted to studies published in the English language between 2000 and 2022. Findings from the literature were screened using a pre-defined screening criterion and the quality of eligible studies was appraised using the Walsh and Downe (2006) checklist. Findings were extracted and synthesised based on Braun and Clark. The review protocol was registered on PROSPERO (Ref: CRD42022319609). Result: A total of 4947 studies were identified from the four databases. Following duplicate removal and screening 16 studies met the inclusion criteria. The studies included 87 pregnant and 302 post-partum women from 12 countries. The participants were from a variety of economic, regional, and religious backgrounds, mainly from the age of 18 to 45 years old. Three main themes were identified: Barriers to breastfeeding, breastfeeding facilitators, emotional disturbance, and breastfeeding. Seven subthemes emerged from the data: expectation versus reality, uncertainly about maternal competencies, body image and breastfeeding, lack of sufficient breastfeeding support for family and caregivers’ support, influences positive breastfeeding practices, breastfeeding education, and causes of mental strain among breastfeeding women. Breastfeeding duration is affected in women with mental health disorders, irrespective of their desire to breastfeed. Conclusion: There is significant empirical evidence that breastfeeding behaviour and perinatal mental disturbance are linked. However, there is a lack of evidence to apply the findings to Saudi women due to lack of empirical qualitative information. To improve the psychological well-being of mothers, it is crucial to explore and recognise any concerns with their mental, physical, and emotional well-being. Therefore, robust research is needed so that breastfeeding intervention researchers and policymakers can focus on specifically what needs to be done to help mentally distressed perinatal women and their new-born.

Keywords: pregnancy, perinatal period, anxiety, depression, emotional disturbance, breastfeeding

Procedia PDF Downloads 70

Authors: Songul Cinaroglu

Abstract:

Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

Procedia PDF Downloads 385

Authors: Hussein Alahmer, Amr Ahmed

Abstract:

Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

Procedia PDF Downloads 308

Authors: Shizra Waris, Bilal Shoaib, Munib Ahmad

Abstract:

Background; The using of clinical decision support systems (CDSSs) may recover unceasing disease organization, which requires regular visits to multiple health professionals, treatment monitoring, disease control, and patient behavior modification. The objective of this survey is to determine if these CDSSs improve the processes of unceasing care including diagnosis, treatment, and monitoring of diseases. Though artificial intelligence is not a new idea it has been widely documented as a new technology in computer science. Numerous areas such as education business, medical and developed have made use of artificial intelligence Methods: The survey covers articles extracted from relevant databases. It uses search terms related to information technology and viral hepatitis which are published between 2000 and 2016. Results: Overall, 80% of studies asserted the profit provided by information technology (IT); 75% of learning asserted the benefits concerned with medical domain;25% of studies do not clearly define the added benefits due IT. The CDSS current state requires many improvements to hold up the management of liver diseases such as HCV, liver fibrosis, and cirrhosis. Conclusion: We concluded that the planned model gives earlier and more correct calculation of hepatitis B and it works as promising tool for calculating of custom hepatitis B from the clinical laboratory data.

Keywords: detection, hapataties, observation, disesese

Procedia PDF Downloads 139

Authors: Huicong Jia, Donghua Pan

Abstract:

As a key component of disaster reduction management, disaster emergency relief and reconstruction is an important process. Based on disaster system theory, this study analyzed the Jiangsu tornado from the formation mechanism of disasters, through to the economic losses, loss of life, and social infrastructure losses along the tornado disaster chain. The study then assessed the emergency relief and reconstruction efforts, based on an analytic hierarchy process method. The results were as follows: (1) An unstable weather system was the root cause of the tornado. The potentially hazardous local environment, acting in concert with the terrain and the river network, was able to gather energy from the unstable atmosphere. The wind belt passed through a densely populated district, with vulnerable infrastructure and other hazard-prone elements, which led to an accumulative disaster situation and the triggering of a catastrophe. (2) The tornado was accompanied by a hailstorm, which is an important triggering factor for a tornado catastrophe chain reaction. (3) The evaluation index (EI) of the emergency relief and reconstruction effect for the ‘‘6.23’’ tornado disaster in Yancheng was 91.5. Compared to other relief work in areas affected by disasters of the same magnitude, there was a more successful response than has previously been experienced. The results provide new insights for studies of disaster systems and the recovery measures in response to tornado catastrophe in China.

Keywords: China, disaster system, emergency relief, tornado catastrophe

Procedia PDF Downloads 252

Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

Abstract:

Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle

Procedia PDF Downloads 122

Authors: Leen Al Kassab, Sarah Johns, Helen Noble, Nawal Nour, Elizabeth Janiak, Sarrah Shahawy

Abstract:

Introduction: Immigrant and refugee women experience disparities in sexual and reproductive health (SRH) outcomes, partially as a result of barriers to SRH literacy and to regular healthcare access and engagement. Despite the existing data highlighting growing needs for culturally relevant and structurally competent care, interventions are scarce and not well-documented. Methods: In this IRB-approved study, we used a community-based participatory research approach, with the assistance of a community advisory board, to conduct a qualitative needs assessment of SRH knowledge and service engagement with immigrant and refugee women from Africa or the Middle East and currently residing in Boston. We conducted a total of nine focus group discussions (FGDs) in partnership with medical, community, and religious centers, in six languages: Arabic, English, French, Somali, Pashtu, and Dari. A total of 44 individuals participated. We explored migrant and refugee women’s current and evolving SRH care needs and gaps, specifically related to the development of interventions and clinical best practices targeting SRH literacy, healthcare engagement, and informed decision-making. Recordings of the FGDs were transcribed verbatim and translated by interpreter services. We used open coding with multiple coders who resolved discrepancies through consensus and iteratively refined our codebook while coding data in batches using Dedoose software. Results: Participants reported immigrant adaptation experiences, discrimination, and feelings of trust, autonomy, privacy, and connectedness to family, community, and the healthcare system as factors surrounding SRH knowledge and needs. The context of previously learned SRH knowledge was commonly noted to be in schools, at menstruation, before marriage, from family members, partners, friends, and online search engines. Common themes included empowering strength drawn from religious and cultural communities, difficulties bridging educational gaps with their US- born daughters, and a desire for more SRH education from multiple sources, including family, health care providers, and religious experts & communities. Regarding further SRH education, participants’ preferences varied regarding ideal platform (virtual vs. in-person), location (in religious and community centers or not), smaller group sizes, and the involvement of men. Conclusions: Based on these results, empowering SRH initiatives should include both community and religious center-based, as well as clinic-based, interventions. Interventions should be composed of frequent educational workshops in small groups involving age-grouped women, daughters, and (sometimes) men, tailored SRH messaging, and the promotion of culturally, religiously, and linguistically competent care.

Keywords: community, immigrant, religion, sexual & reproductive health, women's health

Procedia PDF Downloads 111

Authors: Iorwase Derek Kaka’an, Peter Smolianov, Steven Dion, Christopher Schoen, Jaclyn Norberg, Charles Gabriel Iortimah

Abstract:

This study examines the current state of football in Nigeria to identify the country's practices, which could be useful internationally, and to determine areas for improvement. Over 200 sources of literature on sport delivery systems in successful sports nations were analyzed to construct a globally applicable model of elite football integrated with mass participation, comprising of the following three levels: macro (socio-economic, cultural, legislative, and organizational), meso (infrastructures, personnel, and services enabling sports programs) and micro level (operations, processes, and methodologies for the development of individual athletes). The model has received scholarly validation and has shown to be a framework for program analysis that is not culturally bound. It has recently been utilized for further understanding such sports systems as US rugby, tennis, soccer, swimming, and volleyball, as well as Dutch and Russian swimming. A questionnaire was developed using the above-mentioned model. Survey questions were validated by 12 experts including academicians, executives from sports governing bodies, football coaches, and administrators. To identify best practices and determine areas for improvement of football in Nigeria, 116 coaches completed the questionnaire. Useful exemplars and possible improvements were further identified through semi-structured discussions with 10 Nigerian football administrators and experts. Finally, a content analysis of the Nigeria Football Federation's website and organizational documentation was conducted. This paper focuses on the micro level of Nigerian football delivery, particularly talent search and development as well as advanced athlete preparation and support. Results suggested that Nigeria could share such progressive practices as the provision of football programs in all schools and full-time coaches paid by governments based on the level of coach education. Nigerian football administrators and coaches could provide better football services affordable for all, where success in mass and elite sports is guided by science focused on athletes' needs. Better implemented could be international best practices such as lifelong guidelines for health and excellence of everyone and integration of fitness tests into player development and ranking as done in best Dutch, English, French, Russian, Spanish, and other European clubs; integration of educational and competitive events for elite and developing athletes as well as fans as done at the 2018 World Cup Russia; and academies with multi-stage athlete nurturing as done by Ajax in Africa as well as Barcelona FC and other top clubs expanding across the world. The methodical integration of these practices into the balanced development of mass and elite football will help contribute to international sports success as well as national health, education, crime control, and social harmony in Nigeria.

Keywords: football, high performance, mass participation, Nigeria, sport development

Procedia PDF Downloads 57

Authors: Euripides Antoniades

Abstract:

In 1821 the Greek Revolution movement, under the political influence that arose from the French revolution, and the corresponding movements in Italy, Germany and America, requested the liberation of the nation and the establishment of an independent national state. Published topics in the British press regarding the Greek Revolution, focused on : a) the right of the Greeks to claim their freedom from Turkish domination in order to establish an independent state based on the principle of national autonomy, b) criticism regarding Turkish rule as illegal and the power of the Ottoman Sultan as arbitrary, c) the recognition of the Greek identity and its distinction from the Turkish one and d) the endorsement Greeks as the descendants of ancient Greeks. The advantage of newspaper as a media is sharing information and ideas and dealing with issues in greater depth and detail, unlike other media, such as radio or television. The London Times is a print publication that presents, in chronological or thematic order, the news, opinions or announcements about the most important events that have occurred in a place during a specified period of time. This paper employs the rich archive of The London Times archive by quoting extracts from publications of that period, to convey the British public perspective regarding the Greek Revolution from its beginning until the London Protocol of 1828. Furthermore, analyses the publications of the British newspaper in terms of the number of references to the Greek revolution, front page and editorial references as well as the size of publications on the revolution during the period 1821-1828. A combination of qualitative and quantitative content analysis was applied. An attempt was made to record Greek Revolution references along with the usage of specific words and expressions that contribute to the representation of the historical events and their exposure to the reading public. Key finds of this research reveal that a) there was a frequency of passionate daily articles concerning the events in Greece, their length, and context in The London Times, b) the British public opinion was influenced by this particular newspaper and c) the newspaper published various news about the revolution by adopting the role of animator of the Greek struggle. For instance, war events and the battles of Wallachin and Moldavia, Hydra, Crete, Psara, Mesollogi, Peloponnese were presented not only for informing the readers but for promoting the essential need for freedom and the establishment of an independent Greek state. In fact, this type of news was the main substance of the The London Times’ structure, establishing a positive image about the Greek Revolution contributing to the European diplomatic development such as the standpoint of France, - that did not wish to be detached from the conclusions regarding the English loans and the death of Alexander I of Russia and his succession by the ambitious Nicholas. These factors offered a change in the attitude of the British and Russians respectively assuming a positive approach towards Greece. The Great Powers maintained a neutral position in the Greek-Ottoman conflict, same time they engaged in Greek power increasement by offering aid.

Keywords: Greece, revolution, newspaper, the London times, London, great britain, mass media

Procedia PDF Downloads 77

Authors: Mahfoodh Saleh Al Sabbagh, Venkoba Rao

Abstract:

There is plenty of research, both in academic and consultancy circles, about the importance and benefits of employee engagement and customer engagement and how it gives organization an opportunity to reduce variability and improve performance. Customer engagement is directly related to the engagement level of the organization's employees. It is therefore important to measure both. This research drawing from the work of Human Sigma by Fleming and Asplund, attempts to assess engagement level of customer and employees - the human systems of business - in an educational setup. Student is important to an educational institute and is a customer to be served efficiently and effectively. Considering student as customer and faculty as employees serving them, in–depth interviews were conducted to analyze the relationship between faculty and student engagement in two leading colleges in Oman, one from private sector and another from public sector. The study relied mainly on secondary data sources to understand the concept of engagement. However, the search of secondary sources was extensive to compensate the limited primary data. The results indicate that high faculty engagement is likely to lead to high student engagement. Engaged students were excited about learning, loved the feeling of they being cared as a person by their faculty and advocated the organization to other. The interaction truly represents an opportunity to build emotional connection to the organization. This study could be of interest to organizations interest in building and maintaining engagement with employees and customers.

Keywords: customer engagement, consumer psychology, strategy, educational institutes

Procedia PDF Downloads 453

Authors: Abhijeet Ostawal, Parmjit Lall

Abstract:

The run times for a large strategic model that we were managing had become too long leading to delays in project delivery, increased costs and loss in productivity. Software developers are continuously working towards developing more efficient tools by changing their algorithms and processes. The issue faced by our team was how do you apply the latest technologies on validated existing models which are based on much older versions of software that do not have the latest software capabilities. The multi-model transport model that we had could only be run in sequential assignment order. Recent upgrades to the software now allowed the assignment to be run in parallel, a concept called parallelization. Parallelization is a Python script working only within the latest version of the software. A full model transfer to the latest version was not possible due to time, budget and the potential changes in trip assignment. This article is to show the method to adapt and update the Python script in such a way that it can be used in older software versions by calling the latest version and then recalling the old version for assignment model without affecting the results. Through a process of trial-and-error run time savings of up to 30-40% have been achieved. Assignment results were maintained within the older version and through this learning process we’ve applied this methodology to other even older versions of the software resulting in huge time savings, more productivity and efficiency for both client and consultant.

Keywords: model run time, demand model, parallelisation, python scripting

Procedia PDF Downloads 102