Search results for: Arrhenius methodology

Authors: Noman Shahzad, Amyn Pardhan, Hasnain Zafar

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Introduction: Though short term survival advantage of damage control laparotomy in management of critically ill trauma patients is established, there is little known about the long-term quality of life of these patients. Facial closure rate after damage control laparotomy is reported to be 20-70 percent. Abdominal wall reconstruction in those who failed to achieve facial closure is challenging and can potentially affect quality of life of these patients. Methodology: We conducted retrospective matched cohort study. Adult patients who underwent damage control laparotomy from Jan 2007 till Jun 2013 were identified through medical record. Patients who had concomitant disabling brain injury or limb injuries requiring amputation were excluded. Age, gender and presentation time matched non exposure group of patients who underwent laparotomy for trauma but no damage control were identified for each damage control laparotomy patient. Quality of life assessment was done via telephonic interview at least one year after the operation, using Urdu version of EuroQol Group Quality of Life (QOL) questionnaire EQ5D after permission. Wilcoxon signed rank test was used to compare QOL scores and McNemar test was used to compare individual parameters of QOL questionnaire. Study was approved by institutional ethical review committee. Results: Out of 32 patients who underwent damage control laparotomy during study period, 20 fulfilled the selection criteria for which 20 matched controls were selected. Median age of patients (IQ Range) was 33 (26-40) years. Facial closure rate in damage control laparotomy group was 40% (8/20). One third of those who did not achieve facial closure (4/12) underwent abdominal wall reconstruction. Self-reported QOL score of damage control laparotomy patients was significantly worse than non-damage control group (p = 0.032). There was no statistically significant difference in two groups regarding individual QOL measures. Significantly, more patients in damage control group were requiring use of abdominal binder, and more patients in damage control group had to either change their job or had limitations in continuing previous job. Our study was not adequately powered to detect factors responsible for worse QOL in damage control group. Conclusion: Quality of life of damage control patients is worse than their age and gender matched patients who underwent trauma laparotomy but not damage control. Adequately powered studies need to be conducted to explore factors responsible for this finding for potential improvement.

Keywords: damage control laparotomy, laparostomy, quality of life

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Authors: Kayne Uriel K. Rodrigo, Jerriane Hillary Heart S. Marcial, Samuel C. Brillo

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Rice leaf diseases significantly impact yield production in rice-dependent countries, affecting their agricultural sectors. As part of precision agriculture, early and accurate detection of these diseases is crucial for effective mitigation practices and minimizing crop losses. Hence, this study proposes an enhancement to the Convolutional Neural Network (CNN), a widely-used method for Rice Leaf Disease Image Classification, by incorporating MobileViTV2—a recently advanced architecture that combines CNN and Vision Transformer models while maintaining fewer parameters, making it suitable for broader deployment on edge devices. Our methodology utilizes a publicly available rice disease image dataset from Kaggle, which was validated by a university structural biologist following the guidelines provided by the Philippine Rice Institute (PhilRice). Modifications to the dataset include renaming certain disease categories and augmenting the rice leaf image data through rotation, scaling, and flipping. The enhanced dataset was then used to train the MobileViTV2 model using the Timm library. The results of our approach are as follows: the model achieved notable performance, with 98% accuracy in both training and validation, 6% training and validation loss, and a Receiver Operating Characteristic (ROC) curve ranging from 95% to 100% for each label. Additionally, the F1 score was 97%. These metrics demonstrate a significant improvement compared to a conventional CNN-based approach, which, in a previous 2022 study, achieved only 78% accuracy after using 5 convolutional layers and 2 dense layers. Thus, it can be concluded that MobileViTV2, with its fewer parameters, outperforms traditional CNN models, particularly when applied to Rice Leaf Disease Image Identification. For future work, we recommend extending this model to include datasets validated by international rice experts and broadening the scope to accommodate biotic factors such as rice pest classification, as well as abiotic stressors such as climate, soil quality, and geographic information, which could improve the accuracy of disease prediction.

Keywords: convolutional neural network, MobileViTV2, rice leaf disease, precision agriculture, image classification, vision transformer

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Authors: Seyedeh Bahar Hashemi, Alireza Rahimi, Mehdi Arjmand

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Food is the source of energy and growth through the breakdown of its vital components and plays a vital role in human health and nutrition. Many natural compounds found in plant and animal materials play a special role in biological systems and the origin of many such compounds directly or indirectly is algae. Algae is an enormous source of polysaccharides and have gained much interest in human flourishing. In this study, algae biomass extraction is conducted using deep eutectic-based solvents (NADES) and Ultrasound-assisted extraction (UAE). The aim of this research is to extract bioactive compounds including total carotenoid, antioxidant activity, and polyphenolic contents. For this purpose, the influence of three important extraction parameters namely, biomass-to-solvent ratio, temperature, and time are studied with respect to their impact on the recovery of carotenoids, and phenolics, and on the extracts’ antioxidant activity. Here we employ the Response Surface Methodology for the process optimization. The influence of the independent parameters on each dependent is determined through Analysis of Variance. Our results show that Ultrasound-assisted extraction (UAE) for 50 min is the best extraction condition, and proline:lactic acid (1:1) and choline chloride:urea (1:2) extracts show the highest total phenolic contents (50.00 ± 0.70 mgGAE/gdw) and antioxidant activity [60.00 ± 1.70 mgTE/gdw, 70.00 ± 0.90 mgTE/gdw in 2.2-diphenyl-1-picrylhydrazyl (DPPH), and 2.2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS)]. Our results confirm that the combination of UAE and NADES provides an excellent alternative to organic solvents for sustainable and green extraction and has huge potential for use in industrial applications involving the extraction of bioactive compounds from algae. This study is among the first attempts to optimize the effects of ultrasonic-assisted extraction, ultrasonic devices, and deep natural eutectic point and investigate their application in bioactive compounds extraction from algae. We also study the future perspective of ultrasound technology which helps to understand the complex mechanism of ultrasonic-assisted extraction and further guide its application in algae.

Keywords: natural deep eutectic solvents, ultrasound-assisted extraction, algae, antioxidant activity, phenolic compounds, carotenoids

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Authors: E. M. D. Akuoko, Eliana Vasquez Osorio, Marcel Van Herk, Marianne Aznar

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Radiotherapy is an integral part of treatment for many patients with breast cancer. However, side effects can occur, e.g., fibrosis or erythema. If patients at higher risks of radiation-induced side effects could be identified before treatment, they could be given more individual information about the risks and benefits of radiotherapy. We hypothesize that breast density is correlated with the risk of side effects and present a novel method for automatic evaluation based on radiotherapy planning CT scans. Methods: 799 supine CT scans of breast radiotherapy patients were available from the REQUITE dataset. The methodology was first established in a subset of 114 patients (cohort 1) before being applied to the whole dataset (cohort 2). All patients were scanned in the supine position, with arms up, and the treated breast (ipsilateral) was identified. Manual experts contour available in 96 patients for both the ipsilateral and contralateral breast in cohort 1. Breast tissue was segmented using atlas-based automatic contouring software, ADMIRE® v3.4 (Elekta AB, Sweden). Once validated, the automatic segmentation method was applied to cohort 2. Breast density was then investigated by thresholding voxels within the contours, using Otsu threshold and pixel intensity ranges based on Hounsfield units (-200 to -100 for fatty tissue, and -99 to +100 for fibro-glandular tissue). Volumetric breast density (VBD) was defined as the volume of fibro-glandular tissue / (volume of fibro-glandular tissue + volume of fatty tissue). A sensitivity analysis was performed to verify whether calculated VBD was affected by the choice of breast contour. In addition, we investigated the correlation between volumetric breast density (VBD) and patient age and breast size. VBD values were compared between ipsilateral and contralateral breast contours. Results: Estimated VBD values were 0.40 (range 0.17-0.91) in cohort 1, and 0.43 (0.096-0.99) in cohort 2. We observed ipsilateral breasts to be denser than contralateral breasts. Breast density was negatively associated with breast volume (Spearman: R=-0.5, p-value < 2.2e-16) and age (Spearman: R=-0.24, p-value = 4.6e-10). Conclusion: VBD estimates could be obtained automatically on a large CT dataset. Patients’ age or breast volume may not be the only variables that explain breast density. Future work will focus on assessing the usefulness of VBD as a predictive variable for radiation-induced side effects.

Keywords: breast cancer, automatic image segmentation, radiotherapy, big data, breast density, medical imaging

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Authors: W. L. Tsang, H. Y. Li, S. L. Wong, T. Y. Kwok, S. C. Yuen, S. S. Kwok, P. S. Ko, S. Y. Lau

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Introduction: Palliative care is no doubt necessary in surgery. When one looks at studies of what patients with life-threatening illness want and compares to what they experience in surgical units, the gap is huge. Surgical nurses, being patient advocates, should engage with patients and families sooner rather than later in their illness trajectories to consider how to manage the illness, not just their capacity to survive. Objective: This clinical practice guide aims to fill the service gap of palliative care in surgery by producing a quality-driven, evidence-based yet straightforward clinical practice guide based on a focus strategy. Methodology: In line with Guide to Good Nursing Practice: End-of-Life Care recommended by Nursing Council of Hong Kong and the strategic goal of improving quality of palliative care proposed in HA Strategic Plan 2017-2022, multiple phases of work were undertaken from July 2015 to December 2017. A pragmatic clinical practice guide for surgical patients facing life-threatening conditions was developed based on assessments on knowledge of and attitudes towards end-of-life care of surgical nurses. Key domains, including preparation for bereavement, nursing care for imminently dying patients and at the dying scene were crystallized according to the results of the assessments and the palliative care checklist formulated by UCH Palliative Care Team. After a year of rollout, its content was refined through analyses of implementation in routine practice and consensus opinions from frontline nurses. Results and Outcomes: This clinical practice guide inspires surgical nurses with the art of care to provide for patients’ comfort, function, and longevity. It provides practical directions and assists nurses to master the skills on advance care planning and learn how to be clear with patients, families and themselves about the realities of the disease pictures. Through the implementation, patients and families are included in the decision process, and their wishes are honored. The delivery of explicit and high-quality palliative care maintains good nurse-to-patient relations and enhances satisfaction of hospital care of patients and families. Conclusion: Surgical nursing has always been up to the unique challenges of the era. This clinical practice guide has become an island of credibility for our nurses as they traverse the often stormy waters of life-limiting illness.

Keywords: palliative care delivery, palliative care in surgery, hospice care, end-of-life care

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Authors: Mohammed Asiri, Saleh Alsuwayt, Mohammed Bin Mugren, Abdulmalik Almufarrih, Tariq Alotaibi, Saad Almodameg

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Background: End-stage renal disease is a major public health concern with high incidence and mortality rate. Most of ESRD patients are on hemodialysis therapy which is a long-term treatment that disturbs patients’ lifestyle. As a result, he will be susceptible to develop psychiatric disorders like anxiety that may direct him to non-compliance on physician instructions and hemodialysis therapy. Although there are studies conducted on psychiatric issues in hemodialysis patients, but few studies focused on the effect of anxiety disorder and the patient’s compliance. Hence, we are interested in determining the prevalence of anxiety disorder among hemodialysis patients in Saudi Arabia, as well as in defining the correlation between anxiety disorder and compliance on physician instructions and hemodialysis therapy. We hypothesize that our study will show a higher prevalence of anxiety in hemodialysis patients than in general population. Also, we expect the anxiety to have a negative impact on their compliance. Methodology: We used a cross-sectional study design carried out at dialysis unit of four major hospitals in Riyadh, KSA. We interviewed 235 End Stage Renal Disease male and female patients who are on hemodialysis. We divided the patients into two categories according to their compliance. we used modified general questionnaire to get their demographic data, then we used a psychometric response scale called visual analog scale (VAS) to assess patient’s compliance to hemodialysis and physician’s instructions. Also, we used the Arabic validated version of the hospital anxiety and depression scale (HAD scale) used mainly for anxiety assessment. Results: The overall response rate was 54%. Respondents included 147 (62.6%) males and 88 (37.4%) females. The prevalence of anxiety among hemodialysis patients is 13.3%. According to visual analog scale, we found that 189 compliant patients and 45 non-compliant patients. For HAD scale, the mean ± standard deviation of the total score for females was (4.44 ± 4.7) and it’s higher than males which was 2.65 ± 3.08 (P-value= 0.002). The mean ± standard deviation of HAD score in the non-compliant group was (5.88  4.88) and it was higher than the compliant group (2.7  3.32) (P-value= 0.004). Among non-complaint group, 33.3% of anxious patients were males and 66.6% were females. There was a negative correlation between HAD score of anxiety and visual analog scale (R= - 0.285). Conclusion: We conclude that there is a high prevalence of anxiety among patients with End Stage Renal Disease that was higher in females with association of non-compliance to physician’s instructions and hemodialysis therapy.

Keywords: anxiety, end-stage renal disease, renal failure, anxiety disorder

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Authors: Christopher Benedikt Jakob

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In our current society, there is no need to take a look at the wristwatch to know the exact time. Smartphones, the watch in the car or the computer watch, inform us about the time too. Over hundreds of years, luxury watches have held a fascination for human beings. Consumers buy watches that cost thousands of euros, although they could buy much cheaper watches which also fulfill the function to indicate the correct time. This shows that the functional value has got a minor meaning with reference to the buying-reasons as regards luxury watches. For a few years, people have an increased demand to track data like their walking distance per day or to track their sleep for example. Smart watches enable consumers to get information about these data. There exists a trend that people intend to optimise parts of their social life, and thus they get the impression that they are able to optimise themselves as human beings. With the help of smart watches, they are able to optimise parts of their productivity and to realise their targets at the same time. These smart watches are also offered as luxury models, and the question is: how will customers of traditional luxury watches react? Therefore this study has the intention to give answers to the question why people are willing to spend an enormous amount of money on the consumption of luxury watches. The self-expression model, the relationship basis model, the functional benefit representation model and the means-end-theory are chosen as an appropriate methodology to find reasons why human beings purchase specific luxury watches and luxury smart watches. This evaluative approach further discusses these strategies concerning for example if consumers buy luxury watches/smart watches to express the current self or the ideal self and if human beings make decisions on expected results. The research critically evaluates that relationships are compared on the basis of their advantages. Luxury brands offer socio-emotional advantages like social functions of identification and that the strong brand personality of luxury watches and luxury smart watches helps customers to structure and retrieve brand awareness which simplifies the process of decision-making. One of the goals is to identify if customers know why they like specific luxury watches and dislike others although they are produced in the same country and cost comparable prices. It is very obvious that the market for luxury watches especially for luxury smart watches is changing way faster than it has been in the past. Therefore the research examines the market changing parameters in detail.

Keywords: buying-behaviour, brand management, consumer, luxury watch, smart watch

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Authors: Matheus Madureira Matos, Alexandre Rodrigues Farias

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Magnetic Resonance Imaging (MRI) is a vital imaging technique used in both clinical and pre-clinical areas to obtain detailed anatomical and functional information. However, MRI scans can be expensive, time-consuming, and often require the use of anesthetics to keep animals still during the imaging process. Anesthetics are commonly administered to animals undergoing MRI scans to ensure they remain still during the imaging process. However, prolonged or repeated exposure to anesthetics can have adverse effects on animals, including physiological alterations and potential toxicity. Minimizing the duration and frequency of anesthesia is, therefore, crucial for the well-being of research animals. In recent years, various sampling trajectories have been investigated to reduce the number of MRI measurements leading to shorter scanning time and minimizing the duration of animal exposure to the effects of anesthetics. Compressed sensing (CS) and sampling trajectories, such as cartesian, spiral, and radial, have emerged as powerful tools to reduce MRI data while preserving diagnostic quality. This work aims to apply CS and cartesian, spiral, and radial sampling trajectories for the reconstruction of MRI of the abdomen of mice sub-sampled at levels below that defined by the Nyquist theorem. The methodology of this work consists of using a fully sampled reference MRI of a female model C57B1/6 mouse acquired experimentally in a 4.7 Tesla MRI scanner for small animals using Spin Echo pulse sequences. The image is down-sampled by cartesian, radial, and spiral sampling paths and then reconstructed by CS. The quality of the reconstructed images is objectively assessed by three quality assessment techniques RMSE (Root mean square error), PSNR (Peak to Signal Noise Ratio), and SSIM (Structural similarity index measure). The utilization of optimized sampling trajectories and CS technique has demonstrated the potential for a significant reduction of up to 70% of image data acquisition. This result translates into shorter scan times, minimizing the duration and frequency of anesthesia administration and reducing the potential risks associated with it.

Keywords: compressed sensing, magnetic resonance, sampling trajectories, small animals

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Authors: Julia A. Ermakova

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This study aimed to investigate the efficacy of a physical rehabilitation program for postpartum women. The program was developed with the purpose of restoring physical performance in women during the postpartum period. The research employed a variety of methods, including an analysis of scientific literature, pedagogical testing and experimentation, mathematical processing of study results, and physical performance assessment using a range of tests. The program recommends refraining from abdominal exercises during the first 6-8 months following a cesarean section and avoiding exercises with weights. Instead, a feasible training regimen that gradually increases in intensity several times a week is recommended, along with moderate cardio exercises such as walking, bodyweight training, and a separate workout component that targets posture improvement. Stretching after strength training is also encouraged. The necessary equipment includes comfortable sports attire with a chest support top, mat, push-ups, resistance band, timer, and clock. The motivational aspect of the program is paramount, and the mentee's positive experience with the workout regimen includes feelings of lightness in the body, increased energy, and positive emotions. The gradual reduction of body size and weight loss due to an improved metabolism also serves as positive reinforcement. The mentee's progress can be measured through various means, including an external assessment of her form, body measurements, weight, BMI, and the presence or absence of slouching in everyday life. The findings of this study reveal that the program is effective in restoring physical performance in postpartum women. The mentee achieved weight loss and almost regained her pre-pregnancy shape while her self-esteem improved. Her waist, shoulder, and hip measurements decreased, and she displayed less slouching in her daily life. In conclusion, the developed physical rehabilitation program for postpartum women is an effective means of restoring physical performance. It is crucial to follow the recommended training regimen and equipment to avoid limitations and ensure safety during the postpartum period. The motivational component of the program is also fundamental in encouraging positive reinforcement and improving self-esteem.

Keywords: physical rehabilitation, postpartum, methodology, postpartum recovery, rehabilitation

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Authors: Saadet Taşyürek Demirel, Halide Sena Koçyiğit, Rümeysa Fatma Çetin

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Celebrity worship, characterized by excessive admiration and devotion towards public figures, often mirrors elements of religious fervor. This study delves into the intricate connection between celebrity worship and religiosity, particularly within the Turkish cultural context, where Islamic values predominantly shape societal norms. The investigation involves the adaptation of the Celebrity Attitude Scale into Turkish and scrutinizes the interplay between young individuals' religiosity and their extreme adulation of celebrities. Additionally, the study explores potential moderating factors, such as age and gender, that might influence this relationship. A cohort of 197 young adults, aged 19 to 30, participated in this research, responding to self-administered questionnaires that assessed their attitudes towards celebrities using the adapted Celebrity Attitude Scale, along with their self-reported religiosity. The anticipated relationship between religiosity and celebrity worship is hypothesized to exhibit a non-linear pattern. Specifically, we expect religiosity to positively predict celebrity worship tendencies among individuals with minimal to moderate religiosity levels. Conversely, a negative association between religiosity and celebrity worship is expected to manifest among participants exhibiting moderate to high levels of religiosity. The findings of this study will contribute to the comprehension of the intricate dynamics between celebrity worship and religiosity, offering insights specifically within the Turkish cultural context. By shedding light on this relationship, the study aims to enhance our understanding of the multifaceted influences that shape individuals' perceptions and behaviors towards both celebrities and religious inclinations. Methodology of the study: A quantitative research will be conducted, where the factor analysis and correlational method will be used. The factor structure of the scale will be determined with exploratory and confirmatory factor analysis. The reliability, internal consistency, Objectives of the study: This study examines the relationship between religiosity and celebrity worship by young adults in the Turkish context. The other aim of the study is to assess the Turkish validity and reliability of the Celebrity Attitude Scale and contribute it to the literature. Main Contributions of the study: The study aims to introduce celebrity worship to Turkish literature, assess the Celebrity Attitude Scale's reliability in a Turkish sample, explore manifestations of celebrity worship, and examine its link to religiosity. This research addresses the lack of Turkish sources on celebrity worship and extends understanding of the concept.

Keywords: celebrity, worship, religiosity, god

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Authors: Allaw Kamel, Bazzi Hasan

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Municipal solid waste (MSW) generation is among the most significant sources which threaten the global environmental health. Solid Waste Management has been an important environmental problem in developing countries because of the difficulties in finding sustainable solutions for solid wastes. Therefore, more efforts are needed to be implemented to overcome this problem. Lebanon has suffered a severe solid waste management problem in 2015, and a new landfill site was proposed to solve the existing problem. The study aims to identify and locate the most suitable area to construct a landfill taking into consideration the sustainable development to overcome the present situation and protect the future demands. Throughout the article, a landfill site selection methodology was discussed using Geographic Information System (GIS) and Multi Criteria Decision Analysis (MCDA). Several environmental, economic and social factors were taken as criterion for selection of a landfill. Soil, geology, and LUC (Land Use and Land Cover) indices with the Sustainable Development Index were main inputs to create the final map of Environmentally Sensitive Area (ESA) for landfill site. Different factors were determined to define each index. Input data of each factor was managed, visualized and analyzed using GIS. GIS was used as an important tool to identify suitable areas for landfill. Spatial Analysis (SA), Analysis and Management GIS tools were implemented to produce input maps capable of identifying suitable areas related to each index. Weight has been assigned to each factor in the same index, and the main weights were assigned to each index used. The combination of the different indices map generates the final output map of ESA. The output map was reclassified into three suitability classes of low, moderate, and high suitability. Results showed different locations suitable for the construction of a landfill. Results also reflected the importance of GIS and MCDA in helping decision makers finding a solution of solid wastes by a sanitary landfill.

Keywords: sustainable development, landfill, municipal solid waste (MSW), geographic information system (GIS), multi criteria decision analysis (MCDA), environmentally sensitive area (ESA)

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Authors: Raluca-Ioana Antonescu

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The field research of the paper stands at the intersection between Linguistics and Sociology, while the problem of the research is the importance of language in the modernization process and in a globalized society. The research objective is to prove that language is a stimulant for modernity, while it defines the tradition and the culture of a specific society. In order to examine the linguistic change of the Korean language due to the modernity and globalization, the paper tries to answer one main question, What are the changes the Korean language underwent from a traditional version of Korean, towards one influenced by modernity?, and two secondary questions, How are explored in specialized literature the relations between globalization (and modernity) and culture (focusing on language)? and What influences the Korean language? For the purpose of answering the research questions, the paper has the main premise that due to modernity and globalization, the Korean language changed its discourse construction, and two secondary hypothesis, first is that in literature there are not much explored the relations between culture and modernity focusing on the language discourse construction, but more about identity issue and commodification problems, and the second hypothesis is that the Korean language is influenced by traditional values (like Confucianism) while receiving influence also of globalization process (especially from English language). In terms of methodology, the paper will analyze the two main influences upon the Korean language, referring to traditionalism (being defined as the influence of Confucianism) and modernism (as the influence of other countries’ language and culture), and how the Korean language it was constructed and modified due to these two elements. The paper will analyze at what level (grammatical, lexical, etc.) the traditionalism help at the construction of the Korean language, and what are the changes at each level that modernism brought along. As for the results of this research, the influence of modernism changed both lexically and grammatically the Korean language. In 60 years the increase of English influence is astonishing, and this paper shows the main changes the Korean language underwent, like the loanwords (Konglish), but also the reduction of the speech levels and the ease of the register variation use. Therefore the grammatical influence of modernity and globalization could be seen at the reduction of the speech level and register variation, while the lexical change comes with the influence of English language especially, where about 10% of the Korean vocabulary is considered to be loanwords. Also the paper presents the interrelation between traditionalism and modernity, with the example of Konglish, but not only (we can consider also the Korean greetings which are translated by Koreans when they speak in other languages, bringing their cultural characteristics in English discourse construction), which makes the Koreans global, since they speak in an international language, but still local since they cannot get rid completely of their culture.

Keywords: Confucianism, globalization, language and linguistic change, modernism, traditionalism

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Authors: Mohamad Musa, Khaldoun Aldiabat, Chelsea McLellan

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In higher education, academic advising and counseling are pivotal for guiding students towards successful academic and professional trajectories. Within this landscape, professors play a critical role as academic advisors, offering guidance and support to students navigating their educational journey. This study endeavors to delve into the effectiveness of professors in this capacity through a comprehensive quantitative survey. Amidst the research objectives lies a profound exploration of students' perceptions regarding professors' effectiveness as academic advisors. Additionally, the study aims to elucidate the nuanced strengths and limitations inherent in professors' advisory roles. Through meticulous examination, the research seeks to uncover the profound impact of professors' engagement on student academic accomplishments and contentment. Moreover, it will scrutinize the requisite qualifications, training, and support mechanisms necessary for professors to excel in advisory roles. Utilizing a quantitative survey methodology, this research will gather invaluable insights into students' perspectives on professors' advisory competencies. Rigorous statistical analysis of survey responses will illuminate the efficacy of professors as academic advisors. The survey instrument will intricately measure diverse dimensions such as students' satisfaction levels with advisory sessions, the perceived efficacy of advice rendered by professors, and the holistic influence of professors' involvement on academic triumphs. Anticipated outcomes encompass a meticulous quantitative evaluation of professors' efficacy in academic advisory roles. Moreover, the research endeavors to delineate areas of proficiency and areas necessitating refinement within professors' advisory practices. Through these efforts, the study aims to provide valuable insights that can inform strategies for enhancing professors' advisory practices and optimizing the support systems available to students in higher education institutions. The study seeks to go beyond surface-level evaluations by delving into the intricate relationship between professors' involvement in academic advising and student academic outcomes. By unraveling this complex interplay, the research endeavors to shed light on the mechanisms through which professors' guidance impacts students' academic success, satisfaction, and overall educational experience.

Keywords: academic advising, professors, effectiveness, quantitative survey, student outcomes

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Authors: Katarzyna Stoklosa

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Introduction: European Public Prosecutor’s Office (EPPO) is an independent office in European Union which was established under the article 86 of the Treaty on the Functioning of the European Union by the Treaty of Lisbon following the method of enhanced cooperation. EPPO is aimed at combating crimes against the EU’s financial interest et fraud against the EU budgets on the one hand, EPPO will give a chance to effective fight with organized criminality, on the other it seems to be a threat for member-states which bound with justice the problem of sovereignty. It is a new institution that will become effective from 2020, which is why it requires prior analysis. Methodology: The author uses statistical and comparative methods by collecting and analyzing the work of current institutions such as Europol, Eurojust, as well as the future impact of EPPO on detection and prosecution of crimes. The author will also conduct questionnaire among students and academic staff involved in the perception of EU institutions and the need to create new entities dealing with inter-agency cooperation in criminal matters. Thanks to these research the author will draw up present ways of cooperation between member-states and changes in fighting with financial crimes which will grow up under new regulation. Major Finding of the Study: Analysis and research show that EPPO is an institution based on the principle of mutual recognition, which often does not work in cooperation between Member States. Distrust and problems with the recognition of judgments of other EU Member States may significantly affect the functioning of EPPO. Poland is not part of the EPPO, because arguments have been raised that the European Public Prosecutor's Office interferes too much with the Member States’ pro-active sovereignty and duplicates competences. The research and analyzes carried out by the author show that EPPO has completely new competences, for example, it may file indictments against perpetrators of financial crimes. However, according to the research carried out by the author, such competences may undermine the sovereignty and the principle of protecting the public order of the EU. Conclusion: After the analysis, it will be possible to set following thesis: EPPO is only possible way to effective fight with organized financial criminality. However in conclusion Polish doubts should not be criticized at all. Institutions as EPPO must properly respect sovereignty of member-states. Even instruments like that cannot provoke political contraventions, because there are no other ways to effective resolving of international criminality problem.

Keywords: criminal trial, economic crimes, European Public Prosecutor's Office, European Union

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Authors: Anu Chandran, Reena Esther Rani

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Background of the Study: Dotted with multiple Unique Destination Prepositions (UDPs), Tamil Nadu is an established tourism brand as regards leisure, MICE, culture, and ecological flavors. Albeit, the enchanting destination possesses distinctive attributes and resources yet to be tapped for better competitive advantage. Being a destination that allures an incredible variety of migratory birds, Tamil Nadu is deemed to be an ornithologist’s paradise. This study primarily explores the prospects of developing Kaliveli, recognized as a bird sanctuary in the Tindivanam forest division of the Villupuram district in the State. Kaliveli is an ideal nesting site for migratory birds and is currently apt for a prospective analysis of regenerative tourism. Objectives of the study: This research lays an accent on avian tourism as part and parcel of sustainable tourism ventures. The impacts of projects like the Ornithological Conservation Centre on tourists have been gauged in the present paper. It maps the futuristic proactive propositions linked to regenerative tourism on the site. How far technological innovations can do a world of good in Kaliveli through Artificial Intelligence, Smart Tourism, and similar latest coinages to entice real eco-tourists, have been conceptualized. The experiential dimensions of resource stewardship as regards facilitating tourists’ relish the offerings in a sustainable manner is at the crux of this work. Methodology: Modeled as a case study, this work tries to deliberate on the impact of existing projects attributed to avian fauna in Kalveli. Conducted in the qualitative research design mode, the case study method was adopted for the processing and presentation of study results drawn by applying thematic content analysis based on the data collected from the field. Result and discussion: One of the key findings relates to the kind of nature trails that can be a regenerative dynamic for eco-friendly tourism in Kaliveli. Field visits have been conducted to assess the niche tourism aspects which could be incorporated with the regenerative tourism model to be framed as part of the study.

Keywords: regenerative tourism, Kaliveli bird sanctuary, sustainable development, resource Stewardship, Ornithology, Avian Fauna

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Authors: Ayotunde Qudus Saka, Xin Zhang

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Purpose: The purpose of this study is to investigate how corporate governance traits affect the financial performance of banks in the sub-Saharan African region from 2008 to 2022. Methodology/Design/Approach: The performance of a few chosen banks in Sub-Saharan Africa is examined in relation to corporate governance using static panel regression analysis. The following variables were used to present corporate governance in the study: board size (BDS), board gender diversity (BGD), board independence (BDI), number of audit committee meetings (NAM), and number of foreign members on the board (SFM). Return on assets (ROA) was employed as the dependent variable. Fixed effect (FE), random effect (RE), and common effect (CE) estimators were used with static panel data. The model estimate procedure is based on the 'Log-Lin' specification. The estimation includes eleven (11) models, ten of which relate to the individual country and one that captures the SSA countries used in this study. Finding: The RE effect estimator seems to be more efficient than the FE estimator overall. Therefore, the selected estimator used for the overall country investigation is the random effect model adopted in evaluating the connection between financial success and corporate governance, and according to the all-country specification in assessing the study's goal, the fixed effect estimator is thus selected for most of the countries except for Malawi and Zambia that common effect model worked well for showing that the banks in the aforementioned countries have similar organisational cultures and management philosophies. Consequently, the selected estimators for every country were used to evaluate the connection between financial success and corporate governance. Originality/Value: Corporate governance and bank performance topics are well grounded in literature with evidence from developed countries. However, there is a darth in developing countries particularly in the sub-Saharan African region. This study presents multi-country empirical evidence within the SSAs which gives the study more samples, this study makes use of balanced data from 2008 to 2022 being the latest data coverage from SSA, and to the best knowledge of the authors, no prior research has examined the impact of corporate governance mechanisms on bank performance in the SSA region through the use of multi-country samples.

Keywords: bank performance, corporate governance, sub-Saharan African (SSA), gender diversity, foreign member of the board, multi-country

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Authors: Bayarmaa Enkhbold, Kenichi Matsui

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Urban parks are important assets to every community in terms of providing space for health, cultural and leisure activities. However, Ulaanbaatar, the capital of Mongolia, faces a shortage of green spaces, particularly urban parks, due to overpopulation and haphazard growth. Therefore, in order to increase green space per person, the city government has planned to increase green space per person up to 20m² by 2020 and 30m² by 2030 by establishing more urban parks throughout the city. But this plan was estimated that it is highly unlikely to reach those goals according to the analysis of the present status of plan implementation because the current amount of green space per person is still 4m². In the past studies globally, city planners and scientists agree that it is highly improbable to develop urban parks and keep maintenance sustainably without reflecting community perceptions and their involvement in the park establishment. Therefore, this research aims to find the challenges which stymie urban park development in Ulaanbaatar city and recommend dealing with the problems. In order to reach the goal, communities’ perceptions about the current challenges and their necessity for urban parks were identified and determined whether they differentiated depending on two different types of residential areas (urban and suburban areas). It also attempted to investigate international good practices on how they deal with similar problems. The research methodology was based on a questionnaire survey among city residents, a document review regarding the involvement of stakeholders, and a literature review of relevant past studies. According to the residents’ perceptions, the biggest challenge was a lack of land availability and followed by a lack of proper policy, planning, management, and maintenance out of seven key challenges identified. The biggest community demand from the urban park was a playground for children and followed by recreation and relaxation out of six types of needs. Based on research findings, the study proposed several recommendations for enhancements as institutional and legal framework, park plan and management, supportive environment and monitoring, evaluation, and reporting.

Keywords: challenges of urban park planning and maintenance, community-based urban park establishment, community perceptions and participation, urban parks in Ulaanbaatar, Mongolia

Procedia PDF Downloads 119

Authors: Ashraf Nawaz Khan, R. Alagirusamy, Apurba Das, Puneet Mahajan

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The thermoplastic-based fibre composites are acquiring a market sector of conventional as well as thermoset composites. However, replacing the thermoset with a thermoplastic composite has never been an easy task. The inherent high viscosity of thermoplastic resin reveals poor interface properties. In this work, a homo-polymer towpreg is produced through an electrostatic powder spray coating methodology. The produced flexible towpreg offers a low melt-flow distance during the consolidation of the laminate. The reduced melt-flow distance demonstrates a homogeneous fibre/matrix distribution (and low void content) on consolidation. The composite laminate has been fabricated with two manufacturing techniques such as conventional film stack (FS) and powder-coated (PC) technique. This helps in understanding the distinct response of produced laminates on applying load since the laminates produced through the two techniques are comprised of the same constituent fibre and matrix (constant fibre volume fraction). The changed behaviour is observed mainly due to the different fibre/matrix configurations within the laminate. The interface adhesion influences the load transfer between the fibre and matrix. Therefore, it influences the elastic, plastic, and failure patterns of the laminates. Moreover, the effect of preform geometries (plain weave and satin weave structure) are also studied for corresponding composite laminates in terms of various mechanical properties. The fracture analysis is carried out to study the effect of resin at the interlacement points through micro-CT analysis. The PC laminate reveals a considerably small matrix-rich and deficient zone in comparison to the FS laminate. The different load tensile, shear, fracture toughness, and drop weight impact test) is applied to the laminates, and corresponding damage behaviour is analysed in the successive stage of failure. The PC composite has shown superior mechanical properties in comparison to the FS composite. The damage that occurs in the laminate is captured through the SEM analysis to identify the prominent mode of failure, such as matrix cracking, fibre breakage, delamination, debonding, and other phenomena.

Keywords: composite, damage, fibre, manufacturing

Procedia PDF Downloads 137

Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

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A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

Procedia PDF Downloads 187

Authors: Rajesh Karki, Safal Bhattarai, Saket Adhikari

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Reliable and economic operation of power systems are becoming extremely challenging with large scale integration of renewable energy sources due to the intermittency and uncertainty associated with renewable power generation. It is, therefore, important to make a quantitative risk assessment and explore the potential resources to mitigate such risks. Probabilistic models for different energy storage systems (ESS), such as the flywheel energy storage system (FESS) and the compressed air energy storage (CAES) incorporating specific charge/discharge performance and failure characteristics suitable for probabilistic risk assessment in power system operation and planning are presented in this paper. The proposed methodology used in FESS modelling offers flexibility to accommodate different configurations of plant topology. It is perceived that CAES has a high potential for grid-scale application, and a hybrid approach is proposed, which embeds a Monte-Carlo simulation (MCS) method in an analytical technique to develop a suitable reliability model of the CAES. The proposed ESS models are applied to a test system to investigate the economic and reliability benefits of the energy storage technologies in system operation and planning, as well as to assess their contributions in facilitating wind integration during different operating scenarios. A comparative study considering various storage system topologies are also presented. The impacts of failure rates of the critical components of ESS on the expected state of charge (SOC) and the performance of the different types of ESS during operation are illustrated with selected studies on the test system. The paper also applies the proposed models on the test system to investigate the economic and reliability benefits of the different ESS technologies and to evaluate their contributions in facilitating wind integration during different operating scenarios and system configurations. The conclusions drawn from the study results provide valuable information to help policymakers, system planners, and operators in arriving at effective and efficient policies, investment decisions, and operating strategies for planning and operation of power systems with large penetrations of renewable energy sources.

Keywords: flywheel energy storage, compressed air energy storage, power system reliability, renewable energy, system planning, system operation

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Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: J. Tirano, H. Zea, C. Luhrs

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It is well known that titanium dioxide is a semiconductor with several applications in photocatalytic process. Its band gap makes it very interesting in the photoelectrodes manufacturing used in photoelectrochemical cells for hydrogen production, a clean and environmentally friendly fuel. The synthesis of 1D titanium dioxide nanostructures, such as nanotubes, makes possible to produce more efficient photoelectrodes for solar energy to hydrogen conversion. In essence, this is because it increases the charge transport rate, decreasing recombination options. However, its principal constraint is to be mainly sensitive to UV range, which represents a very low percentage of solar radiation that reaches earth's surface. One of the alternatives to modifying the TiO2’s band gap and improving its photoactivity under visible light irradiation is to dope the nanotubes with transition metals. This option requires fabricating efficient nanostructured photoelectrodes with controlled morphology and specific properties able to offer a suitable surface area for metallic doping. Hence, currently one of the central challenges in photoelectrochemical cells is the construction of nanomaterials with a proper band position for driving the reaction while absorbing energy over the VIS spectrum. This research focuses on the synthesis and characterization of Nidoped TiO2 nanotubes for improving its photocatalytic activity in solar energy conversion applications. Initially, titanium dioxide nanotubes (TNTs) with controlled morphology were synthesized by two-step potentiostatic anodization of titanium foil. The anodization was carried out at room temperature in an electrolyte composed of ammonium fluoride, deionized water and ethylene glycol. Consequent thermal annealing of as-prepared TNTs was conducted in the air between 450 °C - 550 °C. Afterwards, the nanotubes were superficially modified by nickel deposition. Morphology and crystalline phase of the samples were carried out by SEM, EDS and XRD analysis before and after nickel deposition. Determining the photoelectrochemical performance of photoelectrodes is based on typical electrochemical characterization techniques. Also, the morphological characterization associated electrochemical behavior analysis were discussed to establish the effect of nickel nanoparticles modification on the TiO2 nanotubes. The methodology proposed in this research allows using other transition metal for nanotube surface modification.

Keywords: dimensionally stable electrode, nickel nanoparticles, photo-electrode, TiO₂ nanotubes

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Authors: Shamie Kumar

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Background: Radiologists and radiographers (RR) need to educate themselves and their colleagues to ensure that AI is integrated safely, useful, and in a meaningful way with the direction it always benefits the patients. AI education and training are fundamental to the way RR work and interact with it, such that they feel confident using it as part of their clinical practice in a way they understand it. Methodology: This exploratory research will outline the current educational and training gaps for radiographers and radiologists in AI radiology diagnostics. It will review the status, skills, challenges of educating and teaching. Understanding the use of artificial intelligence within daily clinical practice, why it is fundamental, and justification on why learning about AI is essential for wider adoption. Results: The current knowledge among RR is very sparse, country dependent, and with radiologists being the majority of the end-users for AI, their targeted training and learning AI opportunities surpass the ones available to radiographers. There are many papers that suggest there is a lack of knowledge, understanding, and training of AI in radiology amongst RR, and because of this, they are unable to comprehend exactly how AI works, integrates, benefits of using it, and its limitations. There is an indication they wish to receive specific training; however, both professions need to actively engage in learning about it and develop the skills that enable them to effectively use it. There is expected variability amongst the profession on their degree of commitment to AI as most don’t understand its value; this only adds to the need to train and educate RR. Currently, there is little AI teaching in either undergraduate or postgraduate study programs, and it is not readily available. In addition to this, there are other training programs, courses, workshops, and seminars available; most of these are short and one session rather than a continuation of learning which cover a basic understanding of AI and peripheral topics such as ethics, legal, and potential of AI. There appears to be an obvious gap between the content of what the training program offers and what the RR needs and wants to learn. Due to this, there is a risk of ineffective learning outcomes and attendees feeling a lack of clarity and depth of understanding of the practicality of using AI in a clinical environment. Conclusion: Education, training, and courses need to have defined learning outcomes with relevant concepts, ensuring theory and practice are taught as a continuation of the learning process based on use cases specific to a clinical working environment. Undergraduate and postgraduate courses should be developed robustly, ensuring the delivery of it is with expertise within that field; in addition, training and other programs should be delivered as a way of continued professional development and aligned with accredited institutions for a degree of quality assurance.

Keywords: artificial intelligence, training, radiology, education, learning

Procedia PDF Downloads 87

Authors: Ambika Perisamy, Asyriawati binte Mohd Hamzah

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The focus of this presentation is to discuss teacher professional development (TPD) through the use of technology. TPD is necessary to prepare teachers for future challenges they will face throughout their careers and to develop new skills and good teaching practices. We will also be discussing current issues in embracing technology in the field of early childhood education and the impact on the professional development of teachers. Participants will also learn to apply teaching and learning practices through the use of technology. One major objective of this presentation is to coherently fuse practical, technology and theoretical content. The process begins by concretizing a set of preconceived ideas which need to be joined with theoretical justifications found in the literature. Technology can make observations fairer and more reliable, easier to implement, and more preferable to teachers and principals. Technology will also help principals to improve classroom observations of teachers and ultimately improve teachers’ continuous professional development. Video technology allows the early childhood teachers to record and keep the recorded video for reflection at any time. This will also provide opportunities for her to share with her principals for professional dialogues and continuous professional development plans. A total of 10 early childhood teachers and 4 principals were involved in these efforts which identified and analyze the gaps in the quality of classroom observations and its co relation to developing teachers as reflective practitioners. The methodology used involves active exploration with video technology recordings, conversations, interviews and authentic teacher child interactions which forms the key thrust in improving teaching and learning practice. A qualitative analysis of photographs, videos, transcripts which illustrates teacher’s reflections and classroom observation checklists before and after the use of video technology were adopted. Arguably, although PD support can be magnanimously strong, if teachers could not connect or create meaning out of the opportunities made available to them, they may remain passive or uninvolved. Therefore, teachers must see the value of applying new ideas such as technology and approaches to practice while creating personal meaning out of professional development. These video recordings are transferable, can be shared and edited through social media, emails and common storage between teachers and principals. To conclude the importance of reflective practice among early childhood teachers and addressing the concerns raised before and after the use of video technology, teachers and principals shared the feasibility, practical and relevance use of video technology.

Keywords: early childhood education, reflective, improve teaching and learning, technology

Procedia PDF Downloads 503

Authors: Beaula, M. Kruger, Silindisipho, T. Belot

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Small informal retailers are considered one of the most important features of developing countries around the world. Those small informal retailers form part of the local communities in South African townships and are estimated to be more than 100,000 across the country. The township economic landscape has changed over time in South Africa. The traditional small informal retailers in South African Townships have been faced with numerous challenges of increasing competition; an increase in the number of local retail shops and foreign-owned shops. There is evidence that the South African personal and disposable income has increased amongst black African consumers. Historically, people residing in townships were restricted to informal retail shops; however, this has changed due to the growing number of formal large retail chains entering into the township market. The larger retail chains are aware of the improved income levels of the middle-income townships residence and as a result, larger retailers have followed certain strategies such as; (1) retail format development; (2) diversification growth strategy; (3) market penetration growth strategy and (4) market expansion. This research did a comparative analysis between the different retail models developed by Pick n Pay, Spar and Shoprite. The research methodology employed for this study was of a qualitative nature and made use of a case study to conduct a comparative analysis between larger retailers. A questionnaire was also designed to obtain data from existing smaller retailers. The study found that larger retailers have developed smaller retail formats to compete with the traditional smaller retailers operating in South African townships. Only one out of the two large retailers offers entrepreneurs a franchise model. One of the big retailers offers the opportunity to employ between 15 to 20 employees while the others are subject to the outcome of a feasibility study. The response obtained from the entrepreneurs in the townships were mixed, while some found their presence as having a “negative impact,” which has increased competition; others saw them as a means to obtain a variety of products. This research found that the most beneficial retail model for both bigger retail and existing and new entrepreneurs are from Pick n Pay. The other retail format models are more beneficial for the bigger retailers and not to new and existing entrepreneurs.

Keywords: Pick n Pay, retailers, shoprite, spar, townships

Procedia PDF Downloads 195

Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

Procedia PDF Downloads 122

Authors: Ayat-Allah Bouramdane

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Since 2010, there have been sustained decreases in the unit costs of onshore wind energy and large increases in its deployment, varying widely across regions. In fact, the onshore wind production is affected by air density— because cold air is more dense and therefore more effective at producing wind power— and by wind speed—as wind turbines cannot operate in very low or extreme stormy winds. The wind speed is essentially affected by the surface friction or the roughness and other topographic features of the land, which slow down winds significantly over the continent. Hence, the identification of the most appropriate locations of onshore wind systems is crucial to maximize their energy output and therefore minimize their Levelized Cost of Electricity (LCOE). This study focuses on the preliminary assessment of onshore wind energy potential, in several areas in Morocco with a particular focus on the Dakhla city, by analyzing the diurnal and seasonal variability of wind speed for different hub heights, the frequency distribution of wind speed, the wind rose and the wind performance indicators such as wind power density, capacity factor, and LCOE. In addition to climate criterion, other criteria (i.e., topography, location, environment) were selected fromGeographic Referenced Information (GRI), reflecting different considerations. The impact of each criterion on the suitability map of onshore wind farms was identified using the Analytic Hierarchy Process (AHP). We find that the majority of suitable zones are located along the Atlantic Ocean and the Mediterranean Sea. We discuss the sensitivity of the onshore wind site suitability to different aspects such as the methodology—by comparing the Multi-Criteria Decision-Making (MCDM)-AHP results to the Mean-Variance Portfolio optimization framework—and the potential impact of climate change on this suitability map, and provide the final recommendations to the Moroccan energy strategy by analyzing if the actual Morocco's onshore wind installations are located within areas deemed suitable. This analysis may serve as a decision-making framework for cost-effective investment in onshore wind power in Morocco and to shape the future sustainable development of the Dakhla city.

Keywords: analytic hierarchy process (ahp), dakhla, geographic referenced information, morocco, multi-criteria decision-making, onshore wind, site suitability.

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Authors: Debamitra Chakravorty, Pratap K. Parida

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Cold-adapted proteases enhance wash performance in low-temperature laundry resulting in a reduction in energy consumption and wear of textiles and are also used in the dehairing process in leather industries. Unfortunately, the possible drawbacks of using cold-adapted proteases are their instability at higher temperatures. Therefore, proteases with broad temperature stability are required. Unfortunately, wild-type cold-adapted proteases exhibit instability at higher temperatures and thus have low shelf lives. Therefore, attempts to engineer cold-adapted proteases by protein engineering were made previously by directed evolution and random mutagenesis. The lacuna is the time, capital, and labour involved to obtain these variants are very demanding and challenging. Therefore, rational engineering for cold stability without compromising an enzyme's optimum pH and temperature for activity is the current requirement. In this work, mutations were rationally designed with the aid of high throughput computational methodology of network analysis, evolutionary conservation scores, and molecular dynamics simulations for Savinase from Bacillus lentus with the intention of rendering the mutants cold stable without affecting their temperature and pH optimum for activity. Further, an attempt was made to incorporate a mutation in the most stable mutant rationally obtained by this method to introduce oxidative stability in the mutant. Such enzymes are desired in detergents with bleaching agents. In silico analysis by performing 300 ns molecular dynamics simulations at 5 different temperatures revealed that these three mutants were found to be better in cold stability compared to the wild type Savinase from Bacillus lentus. Conclusively, this work shows that cold adaptation without losing optimum temperature and pH stability and additionally stability from oxidative damage can be rationally designed by in silico enzyme engineering. The key findings of this work were first, the in silico data of H5 (cold stable savinase) used as a control in this work, corroborated with its reported wet lab temperature stability data. Secondly, three cold stable mutants of Savinase from Bacillus lentus were rationally identified. Lastly, a mutation which will stabilize savinase against oxidative damage was additionally identified.

Keywords: cold stability, molecular dynamics simulations, protein engineering, rational design

Procedia PDF Downloads 141

Authors: Satya P. Dubey, Hrushikesh A Abhyankar, Veronica Marchante, James L. Brighton, Björn Bergmann

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Aims: To develop a mathematical model that simulates the ROP of PLA taking into account the effect of alternative energy to be implemented in a continuous reactive extrusion production process of PLA. Introduction: The production of large amount of waste is one of the major challenges at the present time, and polymers represent 70% of global waste. PLA has emerged as a promising polymer as it is compostable, biodegradable thermoplastic polymer made from renewable sources. However, the main limitation for the application of PLA is the traces of toxic metal catalyst in the final product. Thus, a safe and efficient production process needs to be developed to avoid the potential hazards and toxicity. It has been found that alternative energy sources (LASER, ultrasounds, microwaves) could be a prominent option to facilitate the ROP of PLA via continuous reactive extrusion. This process may result in complete extraction of the metal catalysts and facilitate less active organic catalysts. Methodology: Initial investigation were performed using the data available in literature for the reaction mechanism of ROP of PLA based on conventional metal catalyst stannous octoate. A mathematical model has been developed by considering significant parameters such as different initial concentration ratio of catalyst, co-catalyst and impurity. Effects of temperature variation and alternative energies have been implemented in the model. Results: The validation of the mathematical model has been made by using data from literature as well as actual experiments. Validation of the model including alternative energies is in progress based on experimental data for partners of the InnoREX project consortium. Conclusion: The model developed reproduces accurately the polymerisation reaction when applying alternative energy. Alternative energies have a great positive effect to increase the conversion and molecular weight of the PLA. This model could be very useful tool to complement Ludovic® software to predict the large scale production process when using reactive extrusion.

Keywords: polymer, poly-lactic acid (PLA), ring opening polymerization (ROP), metal-catalyst, bio-degradable, renewable source, alternative energy (AE)

Procedia PDF Downloads 362