Search results for: skills gained through learning

Authors: Md. Abdul Aziz

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Sulfide ion is water soluble, highly corrosive, toxic and harmful to the human beings. As a result, knowing the exact concentration of sulfide in water is very important. However, the existing detection and quantification methods have several shortcomings, such as high cost, low sensitivity, and massive instrumentation. Consequently, the development of novel sulfide sensor is relevant. Nevertheless, electrochemical methods gained enormous popularity due to a vast improvement in the technique and instrumentation, portability, low cost, rapid analysis and simplicity of design. Successful field application of electrochemical devices still requires vast improvement, which depends on the physical, chemical and electrochemical aspects of the working electrode. The working electrode made of bulk gold (Au) and platinum (Pt) are quite common, being very robust and endowed with good electrocatalytic properties. High cost, and electrode poisoning, however, have so far hindered their practical application in many industries. To overcome these obstacles, we developed a sulfide sensor based on an indium tin oxide nanoparticle (ITONP)-modified ITO electrode. To prepare ITONP-modified ITO, various methods were tested. Drop-drying of ITONPs (aq.) on aminopropyltrimethoxysilane-functionalized ITO (APTMS/ITO) was found to be the best method on the basis of voltammetric analysis of the sulfide ion. ITONP-modified APTMS/ITO (ITONP/APTMS/ITO) yielded much better electrocatalytic properties toward sulfide electro-οxidation than did bare or APTMS/ITO electrodes. The ITONPs and ITONP-modified ITO were also characterized using transmission electron microscopy and field emission scanning electron microscopy, respectively. Optimization of the type of inert electrolyte and pH yielded an ITONP/APTMS/ITO detector whose amperometrically and chronocoulοmetrically determined limits of detection for sulfide in aqueous solution were 3.0 µM and 0.90 µM, respectively. ITONP/APTMS/ITO electrodes which displayed reproducible performances were highly stable and were not susceptible to interference by common contaminants. Thus, the developed electrode can be considered as a promising tool for sensing sulfide.

Keywords: amperometry, chronocoulometry, electrocatalytic properties, ITO-nanoparticle-modified ITO, sulfide sensor

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Authors: Manar Ahmed Elbadawy

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Background: Empirical evidence suggested that improving nursing teamwork (NTW) may be the key to reducing medical error. The functioning nursing teams require open communication, mutual respect, and shared mental models to activate quality patient care. The complexity and the high demands for specialized nursing knowledge and skill also require nursing staff to consult with one another and work in teams regularly. The current study aimed to evaluate the effect of the nursing teamwork training program on nursing teamwork effectiveness. Design: A quasi-experimental (one group pretest-posttest) design was utilized. Three medical intensive care units at a teaching hospital affiliated to Cairo University Hospital, Egypt. Subjects: A convenient sample of 48 nursing staff worked at the selected units. The Nursing Teamwork Observational Checklist was used. Results: Total (NTW) mean scores exhibited quite elevation post-program implementation compared to preprogram and showed little decrease 3 months later ( = 2.52, SD = ± 0.27, mean % =51.98, = 2.72, SD = ± 0.20, mean %=72.45, = 2.67, SD = ± 0.11, mean %= 67.48 respectively). Conclusion: Implementation of (NTW) training program had a positive effect on increasing (NTW) effectiveness. Regular and frequent short-term teamwork training is important to be introduced as well as sustainable monitoring is required to ensure nursing attitudes, knowledge and skills’ change about teamwork effectiveness.

Keywords: effectiveness, nursing, teamwork, training

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Authors: Elham Shirvani-Ghadikolaei

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In this paper, we examine the connection between the human mind and body within the framework of Merleau-Ponty's phenomenology. We study the role of this connection in designing more efficient learning environments, alongside the findings in physical recognition and educational neuroscience. Our research shows the interplay between the mind and the body in the external world and discusses its implications. Based on these observations, we make suggestions as to how the educational system can benefit from taking into account the interaction between the mind and the body in educational affairs.

Keywords: educational neurosciences, embodied cognition, pedagogical neurosciences, phenomenology

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Authors: Muhammad Suhail Ibrahim, Muhammad Nadeem, Muhammad Sultan, Uzair Sajjad, Khalid Hamid, Tahir Mahmood Qureshi, Sadaf Javaria

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Metabolic disorders, including hypertension, diabetes, cardiovascular disease etc., are major threats to public health and economy. Management and prevention of alarmingly increasing disorders have attracted researchers to explore natural barriers against these disorders. The objective of this study was to explore oats as a potential source of dietary fiber. Extraction of dietary was optimized by response surface methodology, and five indigenous oat cultivars, including SGD2011, Avon, SGD81, PD2LV65, and S2000, were also characterized for techno-functional characteristics, mineral composition and phytochemical quantification. These cultivars varied significantly (p < 0.05) for oil holding capacity, water saturation, and water holding capacity, respectively. SGD81 showed the highest oil-holding capacity, water-holding capacity, and water saturation due to the highest fraction of dietary fiber. The highest values of total phenolic contents, total flavonoid contents, total flavonol contents, 2, 2-Diphenyl-1-picrylhydrazyl radical scavenging activity, and anthocyanin were shown by SGD81, and SGD2011, respectively. All cultivars varied significantly (P<0.05) with respect to phytochemical quantification. Oat cultivars SGD81 and SGD2011 showed the best phenolic acid profile and can be effectively used as a source of nutraceuticals. Beyond the nutritional properties of oats, these also contribute and emerged as potential sources of dietary fiber and have gained attention as nutraceutical cereal crops. This approach offers oats as a natural means of dietary fiber to protect humans from alarmingly increasing metabolic disorders, and its extraction by sonication has made it a sustainable and eco-friendly strategy.

Keywords: oat cultivars, dietary fibers, mineral profile, antioxidant activity, color properties

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Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: semantic links, data mining, linked data, SKOS

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Authors: Pouya Taraghi, Yong Li, Nader Yoosef-Ghodsi, Muntaseer Kainat, Samer Adeeb

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Buried pipelines play a crucial role in the transportation of energy products such as oil, gas, and various chemical fluids, ensuring their efficient and safe distribution. However, these pipelines are often susceptible to ground movements caused by geohazards like landslides, fault movements, lateral spreading, and more. Such ground movements can lead to strain-induced failures in pipes, resulting in leaks or explosions, leading to fires, financial losses, environmental contamination, and even loss of human life. Therefore, it is essential to study how buried pipelines respond when traversing geohazard-prone areas to assess the potential impact of ground movement on pipeline design. As such, this study introduces an approach called the Physics-Informed Neural Network (PINN) to predict the strain demand in inelastic pipes subjected to permanent ground displacement (PGD). This method uses a deep learning framework that does not require training data and makes it feasible to consider more realistic assumptions regarding existing nonlinearities. It leverages the underlying physics described by differential equations to approximate the solution. The study analyzes various scenarios involving different geohazard types, PGD values, and crossing angles, comparing the predictions with results obtained from finite element methods. The findings demonstrate a good agreement between the results of the proposed method and the finite element method, highlighting its potential as a simulation-free, data-free, and meshless alternative. This study paves the way for further advancements, such as the simulation-free reliability assessment of pipes subjected to PGD, as part of ongoing research that leverages the proposed method.

Keywords: strain demand, inelastic pipe, permanent ground displacement, machine learning, physics-informed neural network

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Authors: Jerome Dalphinis, Vishal Patel

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The Bailiwick of Jersey is an island British crown dependency situated off the coast of France. Jersey General Hospital’s emergency department sees approximately 40,000 patients a year. It’s outside the NHS, with secondary care being free at the point of care. Sedation is a continuum which extends from a normal conscious level to being fully unresponsive. Procedural sedation produces a minimally depressed level of consciousness in which the patient retains the ability to maintain an airway, and they respond appropriately to physical stimulation. The goals of it are to improve patient comfort and tolerance of the procedure and alleviate associated anxiety. Indications can be stratified by acuity, emergency (cardioversion for life-threatening dysrhythmia), and urgency (joint reduction). In the emergency department, this is most often achieved using a combination of opioids and benzodiazepines. Some departments also use ketamine to produce dissociative sedation, a cataleptic state of profound analgesia and amnesia. The response to pharmacological agents is highly individual, and the drugs used occasionally have unpredictable pharmacokinetics and pharmacodynamics, which can always result in progression between levels of sedation irrespective of the intention. Therefore, practitioners must be able to ‘rescue’ patients from deeper sedation. These practitioners need to be senior clinicians with advanced airway skills (AAS) training. It can lead to adverse effects such as dangerous hypoxia and unintended loss of consciousness if incorrectly undertaken; studies by the National Confidential Enquiry into Patient Outcome and Death (NCEPOD) have reported avoidable deaths. The Royal College of Emergency Medicine, UK (RCEM) released an updated ‘Safe Sedation of Adults in the Emergency Department’ guidance in 2017 detailing a series of standards for staff competencies, and the required environment and equipment, which are required for each target sedation depth. The emergency department in Jersey undertook audit research in 2018 to assess their current practice. It showed gaps in clinical competency, the need for uniform care, and improved documentation. This spurred the development of a checklist incorporating the above RCEM standards, including contraindication for procedural sedation and difficult airway assessment. This was approved following discussion with the relevant heads of departments and the patient safety directorates. Following this, a second audit research was carried out in 2019 with 17 completed checklists (11 relocation of joints, 6 cardioversions). Data was obtained from looking at the controlled resuscitation drugs book containing documented use of ketamine, alfentanil, and fentanyl. TrakCare, which is the patient electronic record system, was then referenced to obtain further information. The results showed dramatic improvement compared to 2018, and they have been subdivided into six categories; pre-procedure assessment recording of significant medical history and ASA grade (2 fold increase), informed consent (100% documentation), pre-oxygenation (88%), staff (90% were AAS practitioners) and monitoring (92% use of non-invasive blood pressure, pulse oximetry, capnography, and cardiac rhythm monitoring) during procedure, and discharge instructions including the documented return of normal vitals and consciousness (82%). This procedural sedation checklist is a safe intervention that identifies pertinent information about the patient and provides a standardised checklist for the delivery of gold standard of care.

Keywords: advanced airway skills, checklist, procedural sedation, resuscitation

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Authors: Lovis Ingrid Hakala

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This paper provides an example of how the dating app Tinder can be used as a tool in queer research and what the use of the app among lesbians can tell us about the production of particular kinds of lesbian identities paired with technology. This study seeks to understand the ways in which the app is understood by lesbian women and how it is brought into their understandings of what being a lesbian means. Dating apps are becoming increasingly common as tools for meeting a potential partner and research has shown how these apps gain new meaning depending on the context. This paper will show both how Tinder has gained a particular meaning in a lesbian context in Bologna, and also how the use of Tinder produces specific ideas of what lesbians are and how they act. While doing ethnographic fieldwork among young lesbians (20-30 years old) in Bologna in the autumn of 2017, as a part of the research methodology, Tinder was used together with interviews and participant observation. By signing up on Tinder and contacting potential informants on the app the aim was to reach women who were not necessarily involved in the queer activist spaces in the city and who might thus provide a different perspective than their activist counterparts. Using Tinder as a tool in research proved to be a useful methodology both when it came to contacting potential informants as well as in gaining a better understanding for queer identity building, and the role Tinder played in defining lesbianism in Bologna. The app itself was often deemed useless, and informants often complained about the lack of women on the app who had their profile showing an interest in women. Apart from being away for the interlocutors to get in touch with potential romantic or sexual partners, the app did provide a concrete object around which to define particular lesbian behavior. Lesbians were described to be slow at answering and not being very eager to meet. This placed lesbian women, in contrast to gay men who were seen as doing the opposite, using dating apps a lot and be quick to propose meetings. Tinder among lesbians in Bologna thus proved to have a dual function as both a way of creating connections between queer women but also as a tool to define what a lesbian is. This paper provides insight into the ways in which dating apps provides a community and identity building function and how a certain behavior on said apps can be a part of defining identity. This work stands out among other literature on dating apps since it does not only focus on the methodological aspects of using Tinder as a tool in research but also provides an insight in how the way in which individuals use the app comes to add to an understanding of what a lesbian is.

Keywords: dating apps, identity, Italy, lesbian, queer

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Authors: Zayed Alsulami, Asma Aldosseri, Ahmed Ezziden, Abdulrahman Alonazi

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Children are more susceptible to medication errors than adults. Medication administration process is the last stage in the medication treatment process and most of the errors detected in this stage. Little research has been undertaken about medication errors in children in the Middle East countries. This study was aimed to evaluate how the paediatric nurses adhere to the medication administration policy and also to identify any medication preparation and administration errors or any risk factors. An observational, prospective study of medication administration process from when the nurses preparing patient medication until administration stage (May to August 2014) was conducted in Saudi Arabia. Twelve paediatric nurses serving 90 paediatric patients were observed. 456 drug administered doses were evaluated. Adherence rate was variable in 7 steps out of 16 steps. Patient allergy information, dose calculation, drug expiry date were the steps in medication administration with lowest adherence rates. 63 medication preparation and administration errors were identified with error rate 13.8% of medication administrations. No potentially life-threating errors were witnessed. Few logistic and administrative factors were reported. The results showed that the medication administration policy and procedure need an urgent revision to be more sensible for nurses in practice. Nurses’ knowledge and skills regarding the medication administration process should be improved.

Keywords: medication sasfety, paediatric, medication errors, paediatric ward

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Authors: Kuo-Kai Lin, Po-Lun Chang

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Research Background and Purpose: Following the development of the Internet and multimedia, the Internet and information technology have become crucial avenues of modern communication and knowledge acquisition. The advantages of using mobile devices for learning include making learning borderless and accessible. Mobile learning has become a trend in disease management and health promotion in recent years. End-stage renal disease (ESRD) is an irreversible chronic disease, and patients who do not receive kidney transplants can only rely on hemodialysis or peritoneal dialysis to survive. Due to the complexities in caregiving for patients with ESRD that stem from their advanced age and other comorbidities, the patients’ incapacity of self-care leads to an increase in the need to rely on their families or primary caregivers, although whether the primary caregivers adequately understand and implement patient care is a topic of concern. Therefore, this study explored whether primary caregivers’ health care provisions can be improved through the intervention of an automatic speech intelligent system, thereby improving the objective health outcomes of patients undergoing long-term dialysis. Method: This study developed an automatic speech intelligent system with healthcare functions such as health information voice prompt, two-way feedback, real-time push notification, and health information delivery. Convenience sampling was adopted to recruit eligible patients from a hemodialysis center at a regional teaching hospital as research participants. A one-group pretest-posttest design was adopted. Descriptive and inferential statistics were calculated from the demographic information collected from questionnaires answered by patients and primary caregivers, and from a medical record review, a health care scale (recorded six months before and after the implementation of intervention measures), a subjective health assessment, and a report of objective physiological indicators. The changes in health care behaviors, subjective health status, and physiological indicators before and after the intervention of the proposed automatic speech intelligent system were then compared. Conclusion and Discussion: The preliminary automatic speech intelligent system developed in this study was tested with 20 pretest patients at the recruitment location, and their health care capacity scores improved from 59.1 to 72.8; comparisons through a nonparametric test indicated a significant difference (p < .01). The average score for their subjective health assessment rose from 2.8 to 3.3. A survey of their objective physiological indicators discovered that the compliance rate for the blood potassium level was the most significant indicator; its average compliance rate increased from 81% to 94%. The results demonstrated that this automatic speech intelligent system yielded a higher efficacy for chronic disease care than did conventional health education delivered by nurses. Therefore, future efforts will continue to increase the number of recruited patients and to refine the intelligent system. Future improvements to the intelligent system can be expected to enhance its effectiveness even further.

Keywords: automatic speech intelligent system for health care, primary caregiver, long-term hemodialysis, health care capabilities, health outcomes

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Authors: Peter Akayuure

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One key determinant of the quality of mathematics learning is the teacher’s ability to assess students adequately and effectively and make assessment an integral part of the instructional practices. If the mathematics teacher lacks the required literacy to perform classroom assessment roles, the true trajectory of learning success and attainment of curriculum expectations might be indeterminate. It is therefore important that educators and policymakers understand and seek ways to improve the literacy level of mathematics teachers to implement classroom assessments that would meet curriculum demands. This study employed a descriptive survey design to explore perceived levels of assessment literacy of mathematics teachers to implement classroom assessment with the school based assessment framework in Ghana. A 25-item classroom assessment inventory on teachers’ assessment scenarios was adopted, modified, and administered to a purposive sample of 48 mathematics teachers from eleven Senior High Schools. Seven other items were included to further collect data on their self-efficacy towards assessment literacy. Data were analyzed using descriptive and bivariate correlation statistics. The result shows that, on average, 48.6% of the mathematics teachers attained standard levels of assessment literacy. Specifically, 50.0% met standard one in choosing appropriate assessment methods, 68.3% reached standard two in developing appropriate assessment tasks, 36.6% reached standard three in administering, scoring, and interpreting assessment results, 58.3% reached standard four in making appropriate assessment decisions, 41.7% reached standard five in developing valid grading procedures, 45.8% reached standard six in communicating assessment results, and 36.2 % reached standard seven by identifying unethical, illegal and inappropriate use of assessment results. Participants rated their self-efficacy belief in performing assessments high, making the relationships between participants’ assessment literacy scores and self-efficacy scores weak and statistically insignificant. The study recommends that institutions training mathematics teachers or providing professional developments should accentuate assessment literacy development to ensure standard assessment practices and quality instruction in mathematics education at senior high schools.

Keywords: assessment literacy, mathematics teacher, senior high schools, Ghana

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Authors: Alshutwi Sitah

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Many countries around the world are struggling to maintain an adequate number of nurses. Inadequate nursing staffing could compromise the quality of patient care. Among many factors that contribute to registered nurses (RN) turnover, the influence of work–family conflict (WFC) has gained little attention. WFC was found to be significantly associated with increased turnover intention (TI) among employees. Furthermore, WFC has been linked to a number of negative consequences, including lower job satisfaction and organizational commitment, sleep insufficiency, insomnia symptoms, obesity, cardiovascular diseases, sleep insufficiency, and high cholesterol. In an effort to find strategies to manage the consequences of WFC, many behavioral, psychological, and career scholars have focused on the role of supervisor support. Family Supportive Supervisor Behaviors (FSSB) has been found to be a promising approach contributing to the reduction of TI in employees’ experiencing WFC. Despite the importance of work–family issues and the influence of FSSB, limited studies have been conducted among the nursing population and none were found that included a sample from Saudi Arabia. Therefore, the main Purpose of this study was to evaluate the influence of FSSB on the relationship among WFC, Stress, and TI in Saudi Arabian registered nurses. Method: A cross-sectional study. Sample: Convenience sampling; 113 Saudi female nurse. Result: Fifty percent of nurses intended to leave their workplace, 68 % of nurses reported having a conflict between work and family, and 44% reported having a high level of stress. A significant positive correlation was found between WFC and TI (r= .43, P < 0.01). A negative correlation was found between FSSB and TI (r= -.53, P < 0.01). Both WFC and stress were associated with TI; however, these associations were buffered (weaken), when nurses had higher FSSB. Conclusion: The FSSB could be seen as a tool to help married, female nurses to demonstrate their professional role without compromising their family responsibilities. Nurses’ turnover is a complex issue that may require multiple prevention strategies; however, enhancing FSSB could be a key resource for maintaining a positive workplace environment and reducing TI.

Keywords: turnover intention, work-family conflict, supervisor support, nursing retention

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Authors: Antonios Panagopoulos, Stamoulis Georgios

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Dyslexia's diagnosis is made taking into account reading and writing skills and is carried out by qualified scientific staff. In addition, there are screening tests that are designed to give an indication of possible dyslexic difficulties. Their main advantage is that they create a pleasant environment for the user and reduce the stress that can lead to false results. An online application was created for the first time, as far as authors' knowledge, for screening Dyslexia in Greek high school students named «DyScreTe». Thus, a sample of 240 students between 16 and 18 years old in Greece was taken, of which 120 were diagnosed with dyslexia by an official authority in Greece, and 120 were typically developed. The main hypothesis that was examined is that students who were diagnosed with dyslexia by official authorities in Greece had significantly lower performance in the respective software tests. The results verified the hypothesis we made those children with dyslexia in each test had a lower performance com-pared to the type developed in successful responses, except for the intelligence test. After random sampling, it was shown that the new online application was a useful tool for screening dyslexia. However, computer evaluation cannot replace the diagnosis by a professional expert, but with the results of this application, the interdisciplinary team that deals with the differential diagnosis will create and evaluate, at a later time, the appropriate intervention program.

Keywords: dyslexia, screening tests, deficits, application

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Authors: Rohan Shinde, Shreya Chugh

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Imagine a world where innovation is natural and not unusual. Imagine a world that works on inner wisdom rather than just information. Children live in such a world which is full of possibilities. If they learn to listen to their own intuition, genius would be common. We all are born with a natural intuitive ability to perceive beyond our senses. This is especially visible in children whose minds are still fresh, less obsessive and more in tune with nature. As we grow older, our modern lifestyle overloads with information and stresses our mind which obscures this innate intuitive capacity. The Art of Living Prajñā Yoga (Intuition Process), a 2-day program introduced for kids and teenagers between 5-18 years of age helps to kindle this intuitive ability and build confidence to act on their gut feeling. This program helps them to tap into the intuitive abilities of the mind, which is demonstrated by them seeing colors, reading text and identifying pictures with eyes closed. To make these faculties blossom and get more established, the mind needs proper nurturing and nourishment which is done in the Intuition Process. A research study has been conducted to measure these abilities manifested in students who have this program on different parameters such as confidence level, clarity of mind, problem solving skills, focus, increase in overall performance etc. The results have been plotted on the graph and conclusions are made on effectiveness of intuition process. Experience of few students with special abilities have also been documented.

Keywords: Abilities, Art of Living, Intuition, Mind

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Authors: Gwyneth Bernier

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An authoritative literature review of peer-reviewed journals and edited books on East African refugees' coping strategies identifies the four most common coping skills among this group as the following: (1) relying on faith, religion, or another belief system, (2) turning to communities or social supports, (3) cognitive reframing--in other words, finding meaning in one's traumas or hardships--and (4) finding hope for the future, especially through education. However, this review recognizes that there are gaps in knowledge in this field and that the validity of these general findings must be further investigated in East African refugees who are women, have not been resettled in Western countries, and belong to specific nationality groups. This review also suggests studies that build on the current body of research begin to use qualitative methods of data collection and analysis. This paper aims to bridge part of that gap in understanding using a qualitative methodology. Specifically, it provides a more holistic view of East African refugees' psychological coping mechanisms through its analysis of trends observed across life story interviews from two participant groups: Sudanese refugee women in Cairo's informal settlements, Egypt and Congolese refugee women in Rwanda's Mahama camp.

Keywords: Congolese refugees, coping mechanisms, refugee women, Sudanese refugees

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Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

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The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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Authors: S. B. Tende, H. L. Abubakar

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It is acknowledged that small and medium enterprises (SMEs) may encounter different ethical issues and pressures that could affect the way in which they strategize or make decisions concerning the outcome of their business. Therefore, this research aimed at assessing entrepreneurial ethics in the business of SMEs in Nigeria. Secondary data were adopted as source of corpus for the analysis. The findings conclude that a sound entrepreneurial ethics system has a significant effect on the level of performance of SMEs in Nigeria. The Nigerian Government needs to provide both guiding and physical structures; as well as learning systems that could inculcate these entrepreneurial ethics.

Keywords: culture, entrepreneurial ethics, performance, SME

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Authors: M. Shaheed Hartley

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There has been increasing pressure on education researchers and practitioners at higher education institutions to focus on the development of South Africa’s rural and peri-urban communities and improving their quality of life. Many tertiary institutions are obliged to review their outreach interventions in schools. To ensure that the support provided to schools is still relevant, a systemic evaluation of science educator needs is central to this process. These prioritised needs will serve as guide not only for the outreach projects of tertiary institutions, but also to service providers in general so that the process of addressing educators needs become coordinated, organised and delivered in a systemic manner. This paper describes one area of a broader needs assessment exercise to collect data regarding the needs of educators in a district of 45 secondary schools in the Western Cape Province of South Africa. This research focuses on the needs and challenges faced by science educators at these schools as articulated by the relevant stakeholders. The objectives of this investigation are two-fold: (1) to create a data base that will capture the needs and challenges identified by science educators of the selected secondary schools; and (2) to develop a needs profile for each of the participating secondary schools that will serve as a strategic asset to be shared with the various service providers as part of a community of practice whose core business is to support science educators and science education at large. The data was collected by a means of a needs assessment questionnaire (NAQ) which was developed in both actual and preferred versions. An open-ended questionnaire was also administered which allowed teachers to express their views. The categories of the questionnaire were predetermined by participating researchers, educators and education department officials. Group interviews were also held with the science teachers at each of the schools. An analysis of the data revealed important trends in terms of science educator needs and identified schools that can be clustered around priority needs, logistic reasoning and educator profiles. The needs database also provides opportunity for the community of practice to strategise and coordinate their interventions.

Keywords: needs assessment, science and mathematics education, evaluation, teaching and learning, South Africa

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Authors: Asmaa Abazaid, Maram Al-Ostah, Nadeen Abu-Zahra, Ruba Bawab, Refaat Abdel-Razek

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Innovation audit is defined as a tool that can be used to reflect on how the innovation is managed in an organization. The aim of this study is to audit innovation in the second top Engineering Firms in the world, and one of the Small Medium Enterprises (SMEs) companies that are working in United Arab Emirates (UAE). The obtained results are then compared with four international companies from China and Brazil. The Diamond model has been used for auditing innovation in the two companies in UAE to evaluate their innovation management and to identify each company’s strengths and weaknesses from an innovation perspective. The results of the comparison between the two companies (Jacobs and Hyper General Contracting) revealed that Jacobs has support for innovation, its innovation processes are well managed, the company is committed to the development of its employees worldwide and the innovation system is flexible. Jacobs was doing best in all innovation management dimensions: strategy, process, organization, linkages and learning, while Hyper General Contracting did not score as Jacobs in any of the innovation dimensions. Furthermore, the audit results of both companies were compared with international companies to examine how well the two construction companies in UAE manage innovation relative to SABIC (Saudi company), Poly Easy and Arnious (Brazilian companies), Huagong tools and Guizohou Yibai (Chinese companies). The results revealed that Jacobs is doing best in learning and organization dimensions, while PolyEasy and Jacobs are equal in the linkage dimension. Huagong Tools scored the highest score in process dimension among all the compared companies. However, the highest score of strategy dimension was given to PolyEasy. On the other hand, Hyper General Contracting scored the lowest in all of the innovation management dimensions. It needs to improve its management of all the innovation management dimensions with special attention to be given to strategy, process, and linkage as they got scores below 4 out of 7 comparing with other dimensions. Jacobs scored the highest in three innovation management dimensions related to the six companies. However, the strategy dimension is considered low, and special attention is needed in this dimension.

Keywords: Brazil, China, innovation audit, innovation evaluation, innovation management, Saudi Arabia, United Arab Emirates

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Authors: Abdulbaset Mazarzaei

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Natural killer (NK) cells are innate immune effectors that play a pivotal role in combating tumors and infected cells. In recent years, the therapeutic potential of NK cells has gained significant attention due to their remarkable cytotoxic ability. This study focuses on investigating the cytotoxic effect of expanded NK cells enriched with interleukin 12 (IL12) and interleukin 15 (IL15), derived from the leukoreduction filter, on the K562 cell line. Firstly, NK cells were isolated from whole blood samples obtained from healthy volunteers. These cells were subsequently expanded ex vivo using a combination of feeder cells, IL12, and IL15. The expanded NK cells were then harvested and assessed for their cytotoxicity against K562, a well-established human chronic myelogenous leukemia cell line. The cytotoxicity was evaluated using flow cytometry assay. Results demonstrate that the expanded NK cells significantly exhibited enhanced cytotoxicity against K562 cells compared to non-expanded NK cells. Interestingly, the expanded NK cells derived specifically from IL12 and IL15-enriched leukoreduction filters showed a robust cytotoxic effect similar to the whole blood-derived NK cells. These findings suggest that IL12 and IL15 in the leukoreduction filter are crucial in promoting NK cell cytotoxicity. Furthermore, the expanded NK cells displayed relatively similar cytotoxicity profiles to whole blood-derived NK cells, indicating their comparable capability in targeting and eliminating tumor cells. This observation is of significant relevance as expanded NK cells from the leukoreduction filter could potentially serve as a readily accessible and efficient source for adoptive immunotherapy. In conclusion, this study highlights the significant cytotoxic effect of expanded NK cells enriched with IL12 and IL15 obtained from the leukoreduction filter on the K562 cell line. Moreover, it emphasizes that these expanded NK cells exhibit comparable cytotoxicity to whole blood-derived NK cells. These findings reinforce the potential clinical utility of using expanded NK cells from the leukoreduction filter as an effective strategy in adoptive immunotherapy for the treatment of cancer. Further studies are warranted to explore the broader implications of this approach in clinical settings.

Keywords: natural killer (NK) cells, Cytotoxicity, Leukoreduction filter, IL-12 and IL-15 Cytokines

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Authors: Maria Krambia-Kapardis, Andreas Kapardis

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The relevant literature has been inundated with arguments for ethics, moral values, honesty, resilience, trust in leadership as well as responsible leadership. In many countries around the globe, and as shown by some recent reports, many political leaders are not role models and do not show best practices by being ethical, responsible, compassionate, and resilient. Journalists, whistleblowers, WikiLeaks, Al Jazeera, and the International Consortium of Investigative Journalists (ICIJ) have been brought out from the shadow of political leaders who lack the virtues/attributes outlined above by the UN Global Compact. A number of political leaders who lack ethical and responsible leadership skills will continue to find loopholes to enrich themselves and their close friends and relatives. Some researchers use the Millon Inventory of Diagnostic; however, this test, while it provides helpful and useful insights into the personality of a person who leads or inspire his/her people but does not show if that person is ethical, motivating, and empowers his people with trust and honesty. Thus, it is recommended that political leaders ought to undergo training that encompasses Aristotelian Ethics by embedding the appropriate values and behaviours in their strategies, policies, and decisions, enhancing the change factors that will help in the implementation of a more sustainable development model. Finally, there is a need to develop a pedagogy and a curriculum which enables the development of responsible political leaders.

Keywords: political leaders, corruption, anti-corruption, political corruption

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Authors: Kim Alvin De Lara

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The research aimed to assess the level of acceptability of the developed activity sheets in Science 5 integrating climate change adaptation of grade 5 science teachers in the District of Pililla school year 2016-2017. In this research, participants were able to recognize and understand the importance of environmental education in improving basic education and integrating them in lessons through localization and contextualization. The researcher conducted the study to develop a material to use by Science teachers in Grade 5. It served also as a self-learning resource for students. The respondents of the study were the thirteen Grade 5 teachers teaching Science 5 in the District of Pililla. Respondents were selected purposively and identified by the researcher. A descriptive method of research was utilized in the research. The main instrument was a checklist which includes items on the objectives, content, tasks, contextualization and localization of the developed activity sheets. The researcher developed a 2-week lesson in Science 5 for 4th Quarter based on the curriculum guide with integration of climate change adaptation. The findings revealed that majority of respondents are female, 31 years old and above, 10 years above in teaching science and have units in master’s degree. With regards to the level of acceptability, the study revealed developed activity sheets in science 5 is very much acceptable. In view of the findings, lessons in science 5 must be contextualized and localized to improve to make the curriculum responds, conforms, reflects, and be flexible to the needs of the learners, especially the 21st century learners who need to be holistically and skillfully developed. As revealed by the findings, it is more acceptable to localized and contextualized the learning materials for pupils. Policy formation and re-organization of the lessons and competencies in Science must be reviewed and re-evaluated. Lessons in science must also be integrated with climate change adaptation since nowadays, people are experiencing change in climate due to global warming and other factors. Through developed activity sheets, researcher strongly supports environmental education and believes this to serve as a way to instill environmental literacy to students.

Keywords: activity sheets, climate change adaptation, contextualization, localization

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Simone F. Medeiros, Jessica M. Fonseca, Gizelda M. Alves, Danilo M. Santos, Sérgio P. Campana-Filho, Amilton M. Santos

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Stimuli responsive and biocompatible hydrogel nanoparticles have gained special attention as systems for potential applications in controlled release of drugs to improve their therapeutic efficacy while minimizing side effects. In this work, novel solid dispersions based on thermo- and pH-responsive poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate) hydrogel nanoparticles embedded in chitosan matrices were prepared via spray drying for controlled release of ketoprofen. Firstly, the hydrogel nanoparticles containing ketoprofen were prepared via precipitation polymerization and their stimuli-responsive behavior, thermal properties, chemical composition, encapsulation efficiency and morphology were characterized. Then, hydrogel nanoparticles with different particles size were embedded into chitosan matrices via spray-drying. Scanning electron microscopy (SEM) analyses were performed to investigate the particles size, dispersity and morphology. Finally, ketoprofen release profiles were studied as a function of pH and temperature. Chitosan/poly(NVCL-co-IA-co-EGDMA)-ketoprofen microparticles presented spherical shape, rough surface and pronounced agglomeration, indicating that hydrogels nanoparticles loaded with ketoprofen modified the surface of chitosan matrix. The maximum encapsulation efficiency of ketoprofen into hydrogel nanoparticles was 57.8% and the electrostatic interactions between amino groups from chitosan and carboxylic groups from hydrogel nanoparticles were able to control ketoprofen release. The hydrogel nanoparticles themselves were capable to retard the release of ketoprofen-loaded until 48h of in vitro release tests, while their incorporation into chitosan matrix achieved a maximum percentage of drug release of 45%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 10:7, and 69%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 5:2.

Keywords: hydrogel nanoparticles, poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate), chitosan, ketoprofen, spray-drying

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Huda Zakaria

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The concept of the glass ceiling persists as a barrier to women's advancement in leadership roles, shaped significantly by organizational culture and climate. This study examines the impact of organizational culture on advancing women to top leadership roles in the Egyptian banking sector. The research explores how varying organizational cultures and climates either facilitate or hinder women's progress in breaking through the glass ceiling. Data suggests that women are underrepresented in senior management positions globally, including in Egypt, indicating a barrier to their advancement. Organizational norms often align more with masculine traits, creating challenges for women in leadership. Stereotypes and biases affect how women are treated, leading to limited advancement opportunities and a lack of sponsors advocating for their skills. Female managers also exhibit lower levels of career confidence compared to male counterparts. To address these issues, organizations must tackle cultural biases and provide equal opportunities to promote genuine gender diversity and empower women in leadership roles. Understanding the impact of organizational culture is crucial for creating inclusive workplaces that foster gender equality and provide equal opportunities for women to succeed in leadership roles.

Keywords: glass ceiling, leadership, banking, bias

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Authors: G.S. Patel

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In this research paper the discussion have been made on teachers work mental stress and coping strategies. Stress Measurement scale was developed for school teachers. All the scientific steps of test construction was followed. For this test construction, different factors like teachers workplace, teachers' residential area, teachers' family life, teachers' ability and skills, economic factors and other factors to construct teachers stress measurement scale. In this research tool, situational statements have been made and teachers have to give a response in each statement on five-point rating scale what they experienced in their daily life. Special features of the test also established like validity and reliability of this test and also computed norms for its interpretation. A sample of 320 teachers of school teachers of Gujarat state was selected by Cluster sampling technique. t-test was computed for testing null hypothesis. The main findings of the present study are Urban area teachers feel more stressful situation compare to rural area teachers. Those teachers who live in the joint family feel less stress compare to teachers who live in a nuclear family. This research work is very useful to prepare list of activities to reduce teachers mental stress.

Keywords: stress measurement scale, level of stress, validity, reliability, norms

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

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Authors: Dong Seop Lee, Byung Sik Kim

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In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

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Authors: Sufia Khowaja, Nishat Fatima

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Social networking sites are significant for visually impaired to overcome the unique challenges they face and access the resources they need to succeed in their education and beyond which might be difficult to obtain through traditional means. It provides them an opportunity to build relationships, stay connected with their support network as well as to develop social skills which give them emotional support to fell less isolated. In this connection the study is conducted with the aim to determine the use of social networking sites, purpose of using and activities performed by visually impaired at Delhi University, Delhi, Jawaharlal Nehru University, Delhi and Jamia Milia Islamia, Delhi. The study followed survey technique in which structured interview is followed to collect data from 137 visually impaired students and analysed using ‘SPSS ver23’. The findings of the study revealed that mostly used social networking sites are whatsapp by 89.23% students of DU, 95.12% of JNU, 87.09% of JMI, followed by e-mail by 78.46% of DU, 78.04% of JNU, 64.51%; youtube by 73.84% DU, 90.24% JNU, 80.64% JMI. Purpose for using these sites is for academics mentioned by 96.92% DU, 100% JNU, 93.54% JMI. Activities performed on sites are sending and receiving messaging 96.92% DU, 92.68% JNU, 93.55% JMI, communicating with friends and family as well as getting academic information. Findings of the study will be helpful for libraries to disseminate their services and resources as well as latest updates to their visually impaired users with the help of most used tools.

Keywords: social networking sites, visually impaired, Delhi University, Jawaharlal Nehru University, Jamia Milia Islamia

Procedia PDF Downloads 75