Search results for: family ICT learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10001

Search results for: family ICT learning

4811 Feminist Evaluation: The Case of Mahatma Gandhi National Rural Employment Guarantee Act

Authors: Salam Abukhadrah

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This research advocates for the use of feminist evaluation (FE) as a tool of great potential in policy and program assessment in relation to women’s empowerment. This research explores the journey of women’s place into the evaluation and international development. Moreover, this research presents a case example of the use of FE on the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), in Ganaparthi village in rural India, in Andhra Pradesh state (AP). This evaluation is formed on the basis of women’s empowerment framework that seeks to examine empowerment as a process and an end in itself rather than as just simplified quantifiable outcomes. This framework is used to conduct in-depth semi-structured interviews that are later cross-validated by a focus group discussion. In addition, this evaluation draws on secondary data from the MGNREGA website and on extracted data from the National Family Health Survey of AP.

Keywords: feminist evaluation, MGNREGA, women’s empowerment, case example, India

Procedia PDF Downloads 139
4810 Investigating Student Behavior in Adopting Online Formative Assessment Feedback

Authors: Peter Clutterbuck, Terry Rowlands, Owen Seamons

Abstract:

In this paper we describe one critical research program within a complex, ongoing multi-year project (2010 to 2014 inclusive) with the overall goal to improve the learning outcomes for first year undergraduate commerce/business students within an Information Systems (IS) subject with very large enrolment. The single research program described in this paper is the analysis of student attitudes and decision making in relation to the availability of formative assessment feedback via Web-based real time conferencing and document exchange software (Adobe Connect). The formative assessment feedback between teaching staff and students is in respect of an authentic problem-based, team-completed assignment. The analysis of student attitudes and decision making is investigated via both qualitative (firstly) and quantitative (secondly) application of the Theory of Planned Behavior (TPB) with a two statistically-significant and separate trial samples of the enrolled students. The initial qualitative TPB investigation revealed that perceived self-efficacy, improved time-management, and lecturer-student relationship building were the major factors in shaping an overall favorable student attitude to online feedback, whilst some students expressed valid concerns with perceived control limitations identified within the online feedback protocols. The subsequent quantitative TPB investigation then confirmed that attitude towards usage, subjective norms surrounding usage, and perceived behavioral control of usage were all significant in shaping student intention to use the online feedback protocol, with these three variables explaining 63 percent of the variance in the behavioral intention to use the online feedback protocol. The identification in this research of perceived behavioral control as a significant determinant in student usage of a specific technology component within a virtual learning environment (VLE) suggests that VLEs could now be viewed not as a single, atomic entity, but as a spectrum of technology offerings ranging from the mature and simple (e.g., email, Web downloads) to the cutting-edge and challenging (e.g., Web conferencing and real-time document exchange). That is, that all VLEs should not be considered the same. The results of this research suggest that tertiary students have the technological sophistication to assess a VLE in this more selective manner.

Keywords: formative assessment feedback, virtual learning environment, theory of planned behavior, perceived behavioral control

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4809 Integration of STEM Education in Quebec, Canada – Challenges and Opportunities

Authors: B. El Fadil, R. Najar

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STEM education is promoted by many scholars and curricula around the world, but it is not yet well established in the province of Quebec in Canada. In addition, effective instructional STEM activities and design methods are required to ensure that students and teachers' needs are being met. One potential method is the Engineering Design Process (EDP), a methodology that emphasizes the importance of creativity and collaboration in problem-solving strategies. This article reports on a case study that focused on using the EDP to develop instructional materials by means of making a technological artifact to teach mathematical variables and functions at the secondary level. The five iterative stages of the EDP (design, make, test, infer, and iterate) were integrated into the development of the course materials. Data was collected from different sources: pre- and post-questionnaires, as well as a working document dealing with pupils' understanding based on designing, making, testing, and simulating. Twenty-four grade seven (13 years old) students in Northern Quebec participated in the study. The findings of this study indicate that STEM activities have a positive impact not only on students' engagement in classroom activities but also on learning new mathematical concepts. Furthermore, STEM-focused activities have a significant effect on problem-solving skills development in an interdisciplinary approach. Based on the study's results, we can conclude, inter alia, that teachers should integrate STEM activities into their teaching practices to increase learning outcomes and attach more importance to STEM-focused activities to develop students' reflective thinking and hands-on skills.

Keywords: engineering design process, motivation, stem, integration, variables, functions

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4808 Essential Oil Contents of Endemic Species Astragalus monspessulanus L. ssp. illyricus (Bernhardt) Chater

Authors: Nada Bezić, Valerija Dunkić, Rušćić Mirko

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Astragalus monspessulanus L. ssp. illyricus (Bernhardt) Chater is endemic species of Fabaceae family and belongs to hemicryptophyte. This plant grows wild in the sub-Mediterranean area. We analyzed the composition of the essential oil of stems and leaves of A. monspessulanus L. ssp. Illyricus, collected in Tijarica, near Split, Croatia. Water distilled essential oils from aerial parts of investigation plant have been analysed by GC and GC/MS using VF-5ms capillary column. The total yield of oil was 0.08%, based on dry weight of samples. Thirty-eight compounds were representing 88.5% of the total oil. This essential oil was characterized by a high concentration of cis-myrtanol (20.5%), geranyl acetate (9.6%) and phytone (6.6%). Previous research in the species A. monspessulanus have included flavoalkaloids and flavonoids composition. The present study gives additional knowledge about secondary metabolites contents on the genus Astragalus.

Keywords: essential oil, isovaleric acid, Valeriana tuberosa, geranyl acetate, phytone

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4807 Improving Psychological Safety in Teaching and Social Organizations in Finland

Authors: Eija Raatikainen

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The aim of the study is to examine psychological safety in the context of change in working life and continuous learning in social- and educational organizations. The participants in the study are social workers and vocational teachers working as employees and supervisors in the capital region of Finland (public and private sectors). Research data has been collected during 2022-2023 using the qualitative method called empathy-based stories (MEBS). Research participants were asked to write short stories about situations related to their work and work community. As researchers, we created and varied the framework narratives (MEBS) in line with the aim of the study and theoretical background. The data were analyzed with content analysis. According to the results, the barriers and prerequisites for psychological safety at work could be located in four different working culture dimensions. The work culture dimensions were named as follows: 1) a work culture focusing on interaction and emotional culture between colleagues, 2) communal work culture, 3) a work culture that enables learning, and 4) a work culture focused on structures and operating models. All these have detailed elements of barriers and prerequisites of psychological safety at work. The results derived from the enlivening methods can be utilized when working with the work community and have discussed psychological safety at work. Also, the method itself (MEBS) can prevent open discussion and reflection on psychological safety at work because of the sensitivity of the topic. Method aloud to imagine, not just talk and share your experiences directly. Additionally, the results of the study can offer one tool or framework while developing phycological safety at work.

Keywords: psychological safety, empathy, empathy-based stories, working life

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4806 Isolation and Characterization of Salt-Tolerance of Rhizobia under the Effects of Salinity

Authors: Sarra Sobti, Baelhadj Hamdi-Aïssa

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The bacteria of the soil, usually called rhizobium, have a considerable importance in agriculture because of their capacity to fix the atmospheric nitrogen in symbiosis with the plants of the family of legumes. The present work was to study the effect of the salinity on growth and nodulation of alfalfa-rhizobia symbiosis at different agricultural experimental sites in Ouargla. The experiment was conducted in 3 steps. The first one was the isolation and characterization of the Rhizobia; next, the evolution of the isolates tolerance to salinity at three levels of NaCl (6, 8,12 and 16 g/L); and the last step was the evolution of the tolerance on symbiotic characteristics. The results showed that the phenotypic characterizations behave practically as Rhizobia spp, and the effects of salinity affect the symbiotic process. The tolerance to high levels of salinity and the survival and persistence in severe and harsh desert conditions make these rhizobia highly valuable inoculums to improve productivity of the leguminous plants cultivated under extreme environments.

Keywords: rhizobia, symbiosis, salinity, tolerance, nodulation, soil, Medicago sativa L.

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4805 The Achievements and Challenges of Physics Teachers When Implementing Problem-Based Learning: An Exploratory Study Applied to Rural High Schools

Authors: Osman Ali, Jeanne Kriek

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Introduction: The current instructional approach entrenched in memorizing does not assist conceptual understanding in science. Instructional approaches that encourage research, investigation, and experimentation, which depict how scientists work, should be encouraged. One such teaching strategy is problem-based learning (PBL). PBL has many advantages; enhanced self-directed learning and improved problem-solving and critical thinking skills. However, despite many advantages, PBL has challenges. Research confirmed is time-consuming and difficult to formulate ill-structured questions. Professional development interventions are needed for in-service educators to adopt the PBL strategy. The purposively selected educators had to implement PBL in their classrooms after the intervention to develop their practice and then reflect on the implementation. They had to indicate their achievements and challenges. This study differs from previous studies as the rural educators were subjected to implementing PBL in their classrooms and reflected on their experiences, beliefs, and attitudes regarding PBL. Theoretical Framework: The study reinforced Vygotskian sociocultural theory. According to Vygotsky, the development of a child's cognitive is sustained by the interaction between the child and more able peers in his immediate environment. The theory suggests that social interactions in small groups create an opportunity for learners to form concepts and skills on their own better than working individually. PBL emphasized learning in small groups. Research Methodology: An exploratory case study was employed. The reason is that the study was not necessarily for specific conclusive evidence. Non-probability purposive sampling was adopted to choose eight schools from 89 rural public schools. In each school, two educators were approached, teaching physical sciences in grades 10 and 11 (N = 16). The research instruments were questionnaires, interviews, and lesson observation protocol. Two open-ended questionnaires were developed before and after intervention and analyzed thematically. Three themes were identified. The semi-structured interviews and responses were coded and transcribed into three themes. Subsequently, the Reform Teaching Observation Protocol (RTOP) was adopted for lesson observation and was analyzed using five constructs. Results: Evidence from analyzing the questionnaires before and after the intervention shows that participants knew better what was required to develop an ill-structured problem during the implementation. Furthermore, indications from the interviews are that participants had positive views about the PBL strategy. They stated that they only act as facilitators, and learners’ problem-solving and critical thinking skills are enhanced. They suggested a change in curriculum to adopt the PBL strategy. However, most participants may not continue to apply the PBL strategy stating that it is time-consuming and difficult to complete the Annual Teaching Plan (ATP). They complained about materials and equipment and learners' readiness to work. Evidence from RTOP shows that after the intervention, participants learn to encourage exploration and use learners' questions and comments to determine the direction and focus of classroom discussions.

Keywords: problem-solving, self-directed, critical thinking, intervention

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4804 Applied Transdisciplinary Undergraduate Research in Costa Rica: Five Weeks Faculty-Led Study Abroad Model

Authors: Sara Shuger Fox, Oscar Reynaga

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This session explains the process and lessons learned as Central College (USA) faculty and staff developed undergraduate research opportunities within the model of a short-term faculty-led study abroad program in Costa Rica. The program in Costa Rica increases access to research opportunities across the disciplines and was developed by faculty from English, Biology, and Exercise Science. Session attendees will benefit from learning how faculty and staff navigated the program proposal process at a small liberal arts college and, in particular, how the program was built to be inclusive of departments with lower enrollment, like those currently seen in the humanities. Vital to this last point, presenters will explain how they negotiated issues of research supervision and disciplinary authority in such a way that the program is open to students from multiple disciplines without forcing the program budget to absorb costs for multiple faculty supervisors traveling and living in-country. Additionally, session attendees will learn how scouting laid the groundwork for mutually beneficial relationships between the program and the communities with which it collaborates. Presenters will explain how they built a coalition of students, faculty advisors, study abroad staff and local research hosts to support the development of research questions that are of value not just to the students, but to the community in which the research will take place. This program also incorporates principles of fair-trade learning by intentionally reporting research findings to local community members, as well as encouraging students to proactively share their research as a way to connect with local people.

Keywords: Costa Rica, research, sustainability, transdisciplinary

Procedia PDF Downloads 1056
4803 Hepatitis B Virus Infection Among Egyptian Children Vaccinated during Infancy

Authors: Iman I. Salama, Samia M. Sami, Somaia I. Salama, Zeinab N. Said, Thanaa M. Rabah, Aida M. Abdel-Mohsin

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This is a national community-based project to evaluate the effectiveness of HBV vaccination program in prevention of infection. HBV markers were tested in the sera of 3600 vaccinated children. Infected children were followed up for 1 year. Prevalence of HBV infection was 0.39 % (0.28% positive for anti-HBc, 0.03% positive for HBsAg and 0.08% positive for both). One year later, 50% of positive anti-HBc children turned negative with sustained positivity for positive HBsAg cases. HBV infection was significantly higher at age above 9 years (0.6%) compared to 0.2% at age 3-9 years and 0% at younger age (P < 0.05). Logistic analysis revealed that predictors for HBV infection were history of blood transfusion, regular medical injection, and family history of either HBV infection or drug abuse (adjusted odds ratios 6.2, 5.6, 7.6 & 19.1 respectively). HBV vaccination program produced adequate protection. Adherence to infection control measures and safe blood transfusion are recommended.

Keywords: HBV infection, HBV vaccine, children, Egypt

Procedia PDF Downloads 438
4802 Opinion Mining to Extract Community Emotions on Covid-19 Immunization Possible Side Effects

Authors: Yahya Almurtadha, Mukhtar Ghaleb, Ahmed M. Shamsan Saleh

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The world witnessed a fierce attack from the Covid-19 virus, which affected public life socially, economically, healthily and psychologically. The world's governments tried to confront the pandemic by imposing a number of precautionary measures such as general closure, curfews and social distancing. Scientists have also made strenuous efforts to develop an effective vaccine to train the immune system to develop antibodies to combat the virus, thus reducing its symptoms and limiting its spread. Artificial intelligence, along with researchers and medical authorities, has accelerated the vaccine development process through big data processing and simulation. On the other hand, one of the most important negatives of the impact of Covid 19 was the state of anxiety and fear due to the blowout of rumors through social media, which prompted governments to try to reassure the public with the available means. This study aims to proposed using Sentiment Analysis (AKA Opinion Mining) and deep learning as efficient artificial intelligence techniques to work on retrieving the tweets of the public from Twitter and then analyze it automatically to extract their opinions, expression and feelings, negatively or positively, about the symptoms they may feel after vaccination. Sentiment analysis is characterized by its ability to access what the public post in social media within a record time and at a lower cost than traditional means such as questionnaires and interviews, not to mention the accuracy of the information as it comes from what the public expresses voluntarily.

Keywords: deep learning, opinion mining, natural language processing, sentiment analysis

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4801 A Novel Hybrid Deep Learning Architecture for Predicting Acute Kidney Injury Using Patient Record Data and Ultrasound Kidney Images

Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

Procedia PDF Downloads 126
4800 A Path for Assistance for People With Stroke in Angola

Authors: Lourenço José, Elsa Melo, Sandra Viera, Ana Pinheiro

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Introduction: People with stroke in Angola face challenges in accessing appropriate healthcare and rehabilitation services. There is a lack of information on the quality of care provided and the development of early intervention plans Methods: Two different methods will be chosen. The exploratory, descriptive, and longitudinal study (E1) to characterize health care for people with stroke, housed in 2 hospitals in Luanda; the quality and transverse study (E2) concerning the development and evaluation of a strategic early intervention plan for a stroke patient. Ethical and deontological principles for an investigation will be proposed. Results: Contributor to the knowledge of the reality of providing care to the person after a stroke, in Angola; Propose and develop an early action plan. Contribute to integration to influence policy makers on the need for assistance with stroke, aiming at their functional, family and social rehabilitation, particularly in the labor market.

Keywords: stroke, functional recovery, quality of life, health

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4799 Reduction of Patient’s Dose of I-131 Therapy by Used Local Diuretic Juice

Authors: Mosab kh. A. A. Bashir, E. Mohamed-Ahmed

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The aim of the study is to compare the results of the external exposure and the range of the dose spread by the patients, hospitalized in two different groups of 3-5 d receiving radioiodine therapy because of thyroid cancer, and one of group were giving the local diuretic plant (barley) as local juice. The control group was 28 patients they were isolated as international precautions after taken I-131 capsule 100 mCi, and their external exposure was recorded day by day after first 24 hrs. and the distance for external measurement was 1 m at the abdominal level. The mean of external exposure values of patients at fourth day were 30.24±12.92 µSv h−1. The second group after taking I-131 capsule 100 mCi we were given barley juice (250 mL) after every meal three times on day and their external exposure was recorded day by day after first 24 hrs. The mean of external exposure values of patients of this group at third day was 26.92±9.89 (14-55) µSv h−1. It was observed that the external exposure from the second group clearly decreased to low levels which contributed to the decrease in patient dose and also to the decrease in the exposure from the patient to his/her family.

Keywords: local diuretic juice, therapy, radiation medicine, diuretic plant

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4798 A West Coast Estuarine Case Study: A Predictive Approach to Monitor Estuarine Eutrophication

Authors: Vedant Janapaty

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Estuaries are wetlands where fresh water from streams mixes with salt water from the sea. Also known as “kidneys of our planet”- they are extremely productive environments that filter pollutants, absorb floods from sea level rise, and shelter a unique ecosystem. However, eutrophication and loss of native species are ailing our wetlands. There is a lack of uniform data collection and sparse research on correlations between satellite data and in situ measurements. Remote sensing (RS) has shown great promise in environmental monitoring. This project attempts to use satellite data and correlate metrics with in situ observations collected at five estuaries. Images for satellite data were processed to calculate 7 bands (SIs) using Python. Average SI values were calculated per month for 23 years. Publicly available data from 6 sites at ELK was used to obtain 10 parameters (OPs). Average OP values were calculated per month for 23 years. Linear correlations between the 7 SIs and 10 OPs were made and found to be inadequate (correlation = 1 to 64%). Fourier transform analysis on 7 SIs was performed. Dominant frequencies and amplitudes were extracted for 7 SIs, and a machine learning(ML) model was trained, validated, and tested for 10 OPs. Better correlations were observed between SIs and OPs, with certain time delays (0, 3, 4, 6 month delay), and ML was again performed. The OPs saw improved R² values in the range of 0.2 to 0.93. This approach can be used to get periodic analyses of overall wetland health with satellite indices. It proves that remote sensing can be used to develop correlations with critical parameters that measure eutrophication in situ data and can be used by practitioners to easily monitor wetland health.

Keywords: estuary, remote sensing, machine learning, Fourier transform

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4797 Modern Day Second Generation Military Filipino Amerasians and Ghosts of the U.S. Military Prostitution System in West Central Luzon's 'AMO Amerasian Triangle'

Authors: P. C. Kutschera, Elena C. Tesoro, Mary Grace Talamera-Sandico, Jose Maria G. Pelayo III

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Second generation military Filipino Amerasians comprise a formidable contemporary segment of the estimated 250,000-plus biracial Amerasians in the Philippines today. Overall, they are a stigmatized and socioeconomically marginalized diaspora, historically; they were abandoned or estranged by U.S. military personnel fathers assigned during the century-long Colonial, Post-World War II and Cold War Era of permanent military basing (1898-1992). Indeed, U.S. military personnel remain stationed in smaller numbers in the Philippines today. This inquiry is an outgrowth of two recent small sample studies. The first surfaced the impact of the U.S. military prostitution system on formation of the ‘Derivative Amerasian Family Construct’ on first generation Amerasians; a second, qualitative case study suggested the continued effect of the prostitution systems' destructive impetuous on second generation Amerasians. The intent of this current qualitative, multiple-case study was to actively seek out second generation sex industry toilers. The purpose was to focus further on this human phenomenon in the post-basing and post-military prostitution system eras. As background, the former military prostitution apparatus has transformed into a modern dynamic of rampant sex tourism and prostitution nationwide. This is characterized by hotel and resorts offering unrestricted carnal access, urban and provincial brothels (casas), discos, bars and pickup clubs, massage parlors, local barrio karaoke bars and street prostitution. A small case study sample (N = 4) of female and male second generation Amerasians were selected. Sample formation employed a non-probability ‘snowball’ technique drawing respondents from the notorious Angeles, Metro Manila, Olongapo City ‘AMO Amerasian Triangle’ where most former U.S. military installations were sited and modern sex tourism thrives. A six-month study and analysis of in-depth interviews of female and male sex laborers, their families and peers revealed a litany of disturbing, and troublesome experiences. Results showed profiles of debilitating human poverty, history of family disorganization, stigmatization, social marginalization and the ghost of the military prostitution system and its harmful legacy on Amerasian family units. Emerging were testimonials of wayward young people ensnared in a maelstrom of deep economic deprivation, familial dysfunction, psychological desperation and societal indifference. The paper recommends that more study is needed and implications of unstudied psychosocial and socioeconomic experiences of distressed younger generations of military Amerasians require specific research. Heretofore apathetic or disengaged U.S. institutions need to confront the issue and formulate activist and solution-oriented social welfare, human services and immigration easement policies and alternatives. These institutions specifically include academic and social science research agencies, corporate foundations, the U.S. Congress, and Departments of State, Defense and Health and Human Services, and Homeland Security (i.e. Citizen and Immigration Services) It is them who continue to endorse a laissez-faire policy of non-involvement over the entire Filipino Amerasian question. Such apathy, the paper concludes, relegates this consequential but neglected blood progeny to the status of humiliating destitution and exploitation. Amerasians; thus, remain entrapped in their former colonial, and neo-colonial habitat. Ironically, they are unwitting victims of a U.S. American homeland that fancies itself geo-politically as a strong and strategic military treaty ally of the Philippines in the Western Pacific.

Keywords: Asian Americans, diaspora, Filipino Amerasians, military prostitution, stigmatization

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4796 Development of an Artificial Neural Network to Measure Science Literacy Leveraging Neuroscience

Authors: Amanda Kavner, Richard Lamb

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Faster growth in science and technology of other nations may make staying globally competitive more difficult without shifting focus on how science is taught in US classes. An integral part of learning science involves visual and spatial thinking since complex, and real-world phenomena are often expressed in visual, symbolic, and concrete modes. The primary barrier to spatial thinking and visual literacy in Science, Technology, Engineering, and Math (STEM) fields is representational competence, which includes the ability to generate, transform, analyze and explain representations, as opposed to generic spatial ability. Although the relationship is known between the foundational visual literacy and the domain-specific science literacy, science literacy as a function of science learning is still not well understood. Moreover, the need for a more reliable measure is necessary to design resources which enhance the fundamental visuospatial cognitive processes behind scientific literacy. To support the improvement of students’ representational competence, first visualization skills necessary to process these science representations needed to be identified, which necessitates the development of an instrument to quantitatively measure visual literacy. With such a measure, schools, teachers, and curriculum designers can target the individual skills necessary to improve students’ visual literacy, thereby increasing science achievement. This project details the development of an artificial neural network capable of measuring science literacy using functional Near-Infrared Spectroscopy (fNIR) data. This data was previously collected by Project LENS standing for Leveraging Expertise in Neurotechnologies, a Science of Learning Collaborative Network (SL-CN) of scholars of STEM Education from three US universities (NSF award 1540888), utilizing mental rotation tasks, to assess student visual literacy. Hemodynamic response data from fNIRsoft was exported as an Excel file, with 80 of both 2D Wedge and Dash models (dash) and 3D Stick and Ball models (BL). Complexity data were in an Excel workbook separated by the participant (ID), containing information for both types of tasks. After changing strings to numbers for analysis, spreadsheets with measurement data and complexity data were uploaded to RapidMiner’s TurboPrep and merged. Using RapidMiner Studio, a Gradient Boosted Trees artificial neural network (ANN) consisting of 140 trees with a maximum depth of 7 branches was developed, and 99.7% of the ANN predictions are accurate. The ANN determined the biggest predictors to a successful mental rotation are the individual problem number, the response time and fNIR optode #16, located along the right prefrontal cortex important in processing visuospatial working memory and episodic memory retrieval; both vital for science literacy. With an unbiased measurement of science literacy provided by psychophysiological measurements with an ANN for analysis, educators and curriculum designers will be able to create targeted classroom resources to help improve student visuospatial literacy, therefore improving science literacy.

Keywords: artificial intelligence, artificial neural network, machine learning, science literacy, neuroscience

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4795 In Silico Study of the Biological and Pharmacological Activity of Nigella sativa

Authors: Ammar Ouahab, Meriem Houichi , Sanna Mihoubi

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Background: Nigella sativa is an annual flowering plant, belongs to the Ranunculaceae family. It has many pharmacological activities such as anti-inflammatory; anti-bacterial; anti-hepatotoxic activities etc. Materials: In order to predict the pharmacological activity of Nigella Sativa’s compounds, some web based servers were used, namely, PubChem, Molinspiration, ADMET-SAR, PASS online and PharMapper. In addition to that, AutoDOCK was used to investigate the different molecular interactions between the selected compounds and their target proteins. Results: All compounds displayed a stable interaction with their targets and satisfactory binding energies, which means that they are active on their targets. Conclusion: Nigella sativa is an effective medicinal plant that has several ethno-medical uses; the latter uses are proven herein via an in-silico study of their pharmacological activities.

Keywords: Nigella sativa, AutoDOCK, PubChem, Molinspiration, ADMET-SAR, PharMapper, PASS online server, docking

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4794 Empowering Transformers for Evidence-Based Medicine

Authors: Jinan Fiaidhi, Hashmath Shaik

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Breaking the barrier for practicing evidence-based medicine relies on effective methods for rapidly identifying relevant evidence from the body of biomedical literature. An important challenge confronted by medical practitioners is the long time needed to browse, filter, summarize and compile information from different medical resources. Deep learning can help in solving this based on automatic question answering (Q&A) and transformers. However, Q&A and transformer technologies are not trained to answer clinical queries that can be used for evidence-based practice, nor can they respond to structured clinical questioning protocols like PICO (Patient/Problem, Intervention, Comparison and Outcome). This article describes the use of deep learning techniques for Q&A that are based on transformer models like BERT and GPT to answer PICO clinical questions that can be used for evidence-based practice extracted from sound medical research resources like PubMed. We are reporting acceptable clinical answers that are supported by findings from PubMed. Our transformer methods are reaching an acceptable state-of-the-art performance based on two staged bootstrapping processes involving filtering relevant articles followed by identifying articles that support the requested outcome expressed by the PICO question. Moreover, we are also reporting experimentations to empower our bootstrapping techniques with patch attention to the most important keywords in the clinical case and the PICO questions. Our bootstrapped patched with attention is showing relevancy of the evidence collected based on entropy metrics.

Keywords: automatic question answering, PICO questions, evidence-based medicine, generative models, LLM transformers

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4793 Variation in Youth and Family Experiences of System of Care Principles in Community Mental Health

Authors: James D. Beauchemin

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This study tested whether youth mental health care quality, operationalized as the extent to which youth and families experienced system-of-care principles in service interactions with providers, varied by level of youth need after adjusting for sociodemographic and treatment factors. The relationship of quality to clinical outcomes was also examined. Using administrative data and cross-sectional surveys from a stratified random sample of 1,124 caregivers of youths ages 5 to 20 within a statewide system-of-care, adjusted analyses indicated youths with the most intensive needs were significantly less likely to experience high-quality care (51% vs. 63%, p=0.016), with marked deficits on 6 of 9 items. Receipt of lower-quality care predicted less improvement in youth functioning. Despite considerable effort to develop systems-of-care for youths with the most severe mental health needs, these data suggest quality disparities remain for the most impaired youths. Policy and intervention development may be needed to improve the quality of care for this population.

Keywords: system-of-care, adherence, mental health, youth

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4792 Competency and Strategy Formulation in Automobile Industry

Authors: Chandan Deep Singh

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In present days, companies are facing the rapid competition in terms of customer requirements to be satisfied, new technologies to be integrated into future products, new safety regulations to be followed, new computer-based tools to be introduced into design activities that becomes more scientific. In today’s highly competitive market, survival focuses on various factors such as quality, innovation, adherence to standards, and rapid response as the basis for competitive advantage. For competitive advantage, companies have to produce various competencies: for improving the capability of suppliers and for strengthening the process of integrating technology. For more competitiveness, organizations should operate in a strategy driven way and have a strategic architecture for developing core competencies. Traditional ways to take such experience and develop competencies tend to take a lot of time and they are expensive. A new learning environment, which is built around a gaming engine, supports the development of competences in specific subject areas. Technology competencies have a significant role in firm innovation and competitiveness; they interact with the competitive environment. Technological competencies vary according to the type of competitive environment, thus enhancing firm innovativeness. Technological competency is gained through extensive experimentation and learning in its research, development and employment in manufacturing. This is a review paper based on competency and strategic success of automobile industry. The aim here is to study strategy formulation and competency tools in the industry. This work is a review of literature related to competency and strategy in automobile industry. This study involves review of 34 papers related to competency and strategy.

Keywords: manufacturing competency, strategic success, competitiveness, strategy formulation

Procedia PDF Downloads 307
4791 Its about Cortana, Microsoft’s Virtual Assistant

Authors: Aya Idriss, Esraa Othman, Lujain Malak

Abstract:

Artificial intelligence is the emulation of human intelligence processes by machines, particularly computer systems that act logically. Some of the specific applications of AI include natural language processing, speech recognition, and machine vision. Cortana is a virtual assistant and she’s an example of an AI Application. Microsoft made it possible for this app to be accessed not only on laptops and PCs but can be downloaded on mobile phones and used as a virtual assistant which was a huge success. Cortana can offer a lot apart from the basic orders such as setting alarms and marking the calendar. Its capabilities spread past that, for example, it provides us with listening to music and podcasts on the go, managing my to-do list and emails, connecting with my contacts hands-free by simply just telling the virtual assistant to call somebody, gives me instant answers and so on. A questionnaire was sent online to numerous friends and family members to perform the study, which is critical in evaluating Cortana's recognition capacity and the majority of the answers were in favor of Cortana’s capabilities. The results of the questionnaire assisted us in determining the level of Cortana's skills.

Keywords: artificial intelligence, Cortana, AI, abstract

Procedia PDF Downloads 171
4790 Self-Concept and Self-Esteem of Adolescents in Lubango, Angola: An Exploratory Study

Authors: Miguel Maria, Tchilissila A. Simoes

Abstract:

The end of a long period of civil wars in Angola (1975-2002) paved the way for growing scientific research in the field of psychology, allowing us to broaden our knowledge on the Angolan population throughout their individual and family development. In this study, we aimed to assess the index of self-concept and self-esteem of adolescents from private and public secondary schools in Lubango, Angola. One hundred adolescents, between 16 and 18 years old (M = 17.2 years, SD = 0.81), completed the Piers-Harris Children's Self-Concept Scale 2 (Piers, 1984) and the Self-Perception Profile for Children (SPPC; Harter, 1985). Our results pointed out lower values of self-esteem and self-concept compared to international samples. Moreover, the level of education and the type of school attended did not seem to influence the level of participants' self-concept and self-esteem. These results contributed to enrich the literature on Angolan adolescents and propels intervention programs to enhance the self-concept and self-esteem of these individuals.

Keywords: African adolescents, post-war societies, self-esteem, self-concept

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4789 Transient Stability Improvement in Multi-Machine System Using Power System Stabilizer (PSS) and Static Var Compensator (SVC)

Authors: Khoshnaw Khalid Hama Saleh, Ergun Ercelebi

Abstract:

Increasingly complex modern power systems require stability, especially for transient and small disturbances. Transient stability plays a major role in stability during fault and large disturbance. This paper compares a power system stabilizer (PSS) and static Var compensator (SVC) to improve damping oscillation and enhance transient stability. The effectiveness of a PSS connected to the exciter and/or governor in damping electromechanical oscillations of isolated synchronous generator was tested. The SVC device is a member of the shunt FACTS (flexible alternating current transmission system) family, utilized in power transmission systems. The designed model was tested with a multi-machine system consisting of four machines six bus, using MATLAB/SIMULINK software. The results obtained indicate that SVC solutions are better than PSS.

Keywords: FACTS, MATLAB/SIMULINK, multi-machine system, PSS, SVC, transient stability

Procedia PDF Downloads 446
4788 An IoT-Enabled Crop Recommendation System Utilizing Message Queuing Telemetry Transport (MQTT) for Efficient Data Transmission to AI/ML Models

Authors: Prashansa Singh, Rohit Bajaj, Manjot Kaur

Abstract:

In the modern agricultural landscape, precision farming has emerged as a pivotal strategy for enhancing crop yield and optimizing resource utilization. This paper introduces an innovative Crop Recommendation System (CRS) that leverages the Internet of Things (IoT) technology and the Message Queuing Telemetry Transport (MQTT) protocol to collect critical environmental and soil data via sensors deployed across agricultural fields. The system is designed to address the challenges of real-time data acquisition, efficient data transmission, and dynamic crop recommendation through the application of advanced Artificial Intelligence (AI) and Machine Learning (ML) models. The CRS architecture encompasses a network of sensors that continuously monitor environmental parameters such as temperature, humidity, soil moisture, and nutrient levels. This sensor data is then transmitted to a central MQTT server, ensuring reliable and low-latency communication even in bandwidth-constrained scenarios typical of rural agricultural settings. Upon reaching the server, the data is processed and analyzed by AI/ML models trained to correlate specific environmental conditions with optimal crop choices and cultivation practices. These models consider historical crop performance data, current agricultural research, and real-time field conditions to generate tailored crop recommendations. This implementation gets 99% accuracy.

Keywords: Iot, MQTT protocol, machine learning, sensor, publish, subscriber, agriculture, humidity

Procedia PDF Downloads 59
4787 Entrepreneur Universal Education System: Future Evolution

Authors: Khaled Elbehiery, Hussam Elbehiery

Abstract:

The success of education is dependent on evolution and adaptation, while the traditional system has worked before, one type of education evolved with the digital age is virtual education that has influenced efficiency in today’s learning environments. Virtual learning has indeed proved its efficiency to overcome the drawbacks of the physical environment such as time, facilities, location, etc., but despite what it had accomplished, the educational system over all is not adequate for being a productive system yet. Earning a degree is not anymore enough to obtain a career job; it is simply missing the skills and creativity. There are always two sides of a coin; a college degree or a specialized certificate, each has its own merits, but having both can put you on a successful IT career path. For many of job-seeking individuals across world to have a clear meaningful goal for work and education and positively contribute the community, a productive correlation and cooperation among employers, universities alongside with the individual technical skills is a must for generations to come. Fortunately, the proposed research “Entrepreneur Universal Education System” is an evolution to meet the needs of both employers and students, in addition to gaining vital and real-world experience in the chosen fields is easier than ever. The new vision is to empower the education to improve organizations’ needs which means improving the world as its primary goal, adopting universal skills of effective thinking, effective action, effective relationships, preparing the students through real-world accomplishment and encouraging them to better serve their organization and their communities faster and more efficiently.

Keywords: virtual education, academic degree, certificates, internship, amazon web services, Microsoft Azure, Google Cloud Platform, hybrid models

Procedia PDF Downloads 89
4786 Resilience, Mental Health, and Life Satisfaction

Authors: Saba Harati, Nasrin Arian Parsa

Abstract:

The current research was an attempt to investigate the effect of resilience on mental health and life satisfaction. In one Cross Sectional research, 287 (173 females and 114 males) students of Tehran University were participated their average age was 23.17 years old (SD=4.9). The instruments used for assessing the research variables included: Cutter and Davidson resilience scale (CD-RISC), the short form of the depression-anxiety-stress scale, and life satisfaction scale. The data analysis was done in the form of structural equation model. The results of Simultaneous Hierarchical Multiple Regression Analysis indicated that there was a significant mediating role of the negative emotions (depression, anxiety, and stress), in the relationship between the family resilience (p < 0.001) and satisfaction with life (p < 0.001). Resilience results in life satisfaction by reducing the emotional problems (or increasing the mental health level). The effect of the resilience variable on life satisfaction was indirect.

Keywords: resilience, negative emotion, mental health, life satisfaction

Procedia PDF Downloads 491
4785 Efficiency of Maritime Simulator Training in Oil Spill Response Competence Development

Authors: Antti Lanki, Justiina Halonen, Juuso Punnonen, Emmi Rantavuo

Abstract:

Marine oil spill response operation requires extensive vessel maneuvering and navigation skills. At-sea oil containment and recovery include both single vessel and multi-vessel operations. Towing long oil containment booms that are several hundreds of meters in length, is a challenge in itself. Boom deployment and towing in multi-vessel configurations is an added challenge that requires precise coordination and control of the vessels. Efficient communication, as a prerequisite for shared situational awareness, is needed in order to execute the response task effectively. To gain and maintain adequate maritime skills, practical training is needed. Field exercises are the most effective way of learning, but especially the related vessel operations are resource-intensive and costly. Field exercises may also be affected by environmental limitations such as high sea-state or other adverse weather conditions. In Finland, the seasonal ice-coverage also limits the training period to summer seasons only. In addition, environmental sensitiveness of the sea area restricts the use of real oil or other target substances. This paper examines, whether maritime simulator training can offer a complementary method to overcome the training challenges related to field exercises. The objective is to assess the efficiency and the learning impact of simulator training, and the specific skills that can be trained most effectively in simulators. This paper provides an overview of learning results from two oil spill response pilot courses, in which maritime navigational bridge simulators were used to train the oil spill response authorities. The simulators were equipped with an oil spill functionality module. The courses were targeted at coastal Fire and Rescue Services responsible for near shore oil spill response in Finland. The competence levels of the participants were surveyed before and after the course in order to measure potential shifts in competencies due to the simulator training. In addition to the quantitative analysis, the efficiency of the simulator training is evaluated qualitatively through feedback from the participants. The results indicate that simulator training is a valid and effective method for developing marine oil spill response competencies that complement traditional field exercises. Simulator training provides a safe environment for assessing various oil containment and recovery tactics. One of the main benefits of the simulator training was found to be the immediate feedback the spill modelling software provides on the oil spill behaviour as a reaction to response measures.

Keywords: maritime training, oil spill response, simulation, vessel manoeuvring

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4784 Machine Learning Framework: Competitive Intelligence and Key Drivers Identification of Market Share Trends among Healthcare Facilities

Authors: Anudeep Appe, Bhanu Poluparthi, Lakshmi Kasivajjula, Udai Mv, Sobha Bagadi, Punya Modi, Aditya Singh, Hemanth Gunupudi, Spenser Troiano, Jeff Paul, Justin Stovall, Justin Yamamoto

Abstract:

The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data is considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP, to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since its data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for ex. quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP (SHapley Additive exPlanations), a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.

Keywords: competition, DAGs, facility, healthcare, machine learning, market share, random forest, SHAP

Procedia PDF Downloads 87
4783 Query in Grammatical Forms and Corpus Error Analysis

Authors: Katerina Florou

Abstract:

Two decades after coined the term "learner corpora" as collections of texts created by foreign or second language learners across various language contexts, and some years following suggestion to incorporate "focusing on form" within a Task-Based Learning framework, this study aims to explore how learner corpora, whether annotated with errors or not, can facilitate a focus on form in an educational setting. Argues that analyzing linguistic form serves the purpose of enabling students to delve into language and gain an understanding of different facets of the foreign language. This same objective is applicable when analyzing learner corpora marked with errors or in their raw state, but in this scenario, the emphasis lies on identifying incorrect forms. Teachers should aim to address errors or gaps in the students' second language knowledge while they engage in a task. Building on this recommendation, we compared the written output of two student groups: the first group (G1) employed the focusing on form phase by studying a specific aspect of the Italian language, namely the past participle, through examples from native speakers and grammar rules; the second group (G2) focused on form by scrutinizing their own errors and comparing them with analogous examples from a native speaker corpus. In order to test our hypothesis, we created four learner corpora. The initial two were generated during the task phase, with one representing each group of students, while the remaining two were produced as a follow-up activity at the end of the lesson. The results of the first comparison indicated that students' exposure to their own errors can enhance their grasp of a grammatical element. The study is in its second stage and more results are to be announced.

Keywords: Corpus interlanguage analysis, task based learning, Italian language as F1, learner corpora

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4782 Design, Synthesis and Evaluation of 4-(Phenylsulfonamido)Benzamide Derivatives as Selective Butyrylcholinesterase Inhibitors

Authors: Sushil Kumar Singh, Ashok Kumar, Ankit Ganeshpurkar, Ravi Singh, Devendra Kumar

Abstract:

In spectrum of neurodegenerative diseases, Alzheimer’s disease (AD) is characterized by the presence of amyloid β plaques and neurofibrillary tangles in the brain. It results in cognitive and memory impairment due to loss of cholinergic neurons, which is considered to be one of the contributing factors. Donepezil, an acetylcholinesterase (AChE) inhibitor which also inhibits butyrylcholinesterase (BuChE) and improves the memory and brain’s cognitive functions, is the most successful and prescribed drug to treat the symptoms of AD. The present work is based on designing of the selective BuChE inhibitors using computational techniques. In this work, machine learning models were trained using classification algorithms followed by screening of diverse chemical library of compounds. The various molecular modelling and simulation techniques were used to obtain the virtual hits. The amide derivatives of 4-(phenylsulfonamido) benzoic acid were synthesized and characterized using 1H & 13C NMR, FTIR and mass spectrometry. The enzyme inhibition assays were performed on equine plasma BuChE and electric eel’s AChE by method developed by Ellman et al. Compounds 31, 34, 37, 42, 49, 52 and 54 were found to be active against equine BuChE. N-(2-chlorophenyl)-4-(phenylsulfonamido)benzamide and N-(2-bromophenyl)-4-(phenylsulfonamido)benzamide (compounds 34 and 37) displayed IC50 of 61.32 ± 7.21 and 42.64 ± 2.17 nM against equine plasma BuChE. Ortho-substituted derivatives were more active against BuChE. Further, the ortho-halogen and ortho-alkyl substituted derivatives were found to be most active among all with minimal AChE inhibition. The compounds were selective toward BuChE.

Keywords: Alzheimer disease, butyrylcholinesterase, machine learning, sulfonamides

Procedia PDF Downloads 135