Search results for: higher learning institutions

Authors: Li Jiuen Ong, Magdalin Cheong, Sri Rahayu, Lek Alexander, Pei Ting Tan

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Background: Previous programme evaluations from the diabetes training programme conducted in Changi General Hospital revealed that healthcare professionals (HCPs) are keen to receive advance diabetes training and education, specifically in medical, nutritional therapy. HCPs also expressed a preference for interactive activities over didactic teaching methods to enhance their learning. Since the War on Diabetes was initiated by MOH in 2016, HCPs are challenged to be actively involved in continuous education to be better equipped to reduce the growing burden of diabetes. Hence, streamlining training to incorporate an element of fun is of utmost importance. Aim: The nutrition programme incorporates game play using an interactive board game that aims to provide a more conducive and less stressful environment for learning. The board game could be adapted for training of community HCPs, health ambassadors or caregivers to cope with the increasing demand of diabetes care in the hospital and community setting. Methodology: Stages for game’s conception (Jaffe, 2001) were adopted in the development of the interactive board game ‘Sweet Score™ ’ Nutrition concepts and topics in diabetes self-management are embedded into the game elements of varying levels of difficulty (‘Easy,’ ‘Medium,’ ‘Hard’) including activities such as a) Drawing/ sculpting (Pictionary-like) b)Facts/ Knowledge (MCQs/ True or False) Word definition) c) Performing/ Charades To study the effects of game play on knowledge acquisition and perceived experiences, participants were randomised into two groups, i.e., lecture group (control) and game group (intervention), to test the difference. Results: Participants in both groups (control group, n= 14; intervention group, n= 13) attempted a pre and post workshop quiz to assess the effectiveness of knowledge acquisition. The scores were analysed using paired T-test. There was an improvement of quiz scores after attending the game play (mean difference: 4.3, SD: 2.0, P<0.001) and the lecture (mean difference: 3.4, SD: 2.1, P<0.001). However, there was no significance difference in the improvement of quiz scores between gameplay and lecture (mean difference: 0.9, 95%CI: -0.8 to 2.5, P=0.280). This suggests that gameplay may be as effective as a lecture in terms of knowledge transfer. All the13 HCPs who participated in the game rated 4 out of 5 on the likert scale for the favourable learning experience and relevance of learning to their job, whereas only 8 out of 14 HCPs in the lecture reported a high rating in both aspects. 16. Conclusion: There is no known board game currently designed for diabetes training for HCPs.Evaluative data from future training can provide insights and direction to improve the game format and cover other aspects of diabetes management such as self-care, exercise, medications and insulin management. Further testing of the board game to ensure learning objectives are met is important and can assist in the development of awell-designed digital game as an alternative training approach during the COVID-19 pandemic. Learning through gameplay increases opportunities for HCPs to bond, interact and learn through games in a relaxed social setting and potentially brings more joy to the workplace.

Keywords: active learning, game, diabetes, nutrition

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Authors: Waqas Ahmed Khan Afridi, Subhas Chandra Mukhopadhyay, Bandita Mainali

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The research paper presents a unique approach to evapotranspiration (ET) prediction using a Support Vector Machine (SVM) learning algorithm. The study leverages real-time sensor node data to develop an accurate and adaptable prediction model, addressing the inherent challenges of traditional ET estimation methods. The integration of the SVM algorithm with real-time sensor node data offers great potential to improve spatial and temporal resolution in ET predictions. In the model development, key input features are measured and computed using mathematical equations such as Penman-Monteith (FAO56) and soil water balance (SWB), which include soil-environmental parameters such as; solar radiation (Rs), air temperature (T), atmospheric pressure (P), relative humidity (RH), wind speed (u2), rain (R), deep percolation (DP), soil temperature (ST), and change in soil moisture (∆SM). The one-year field data are split into combinations of three proportions i.e. train, test, and validation sets. While kernel functions with tuning hyperparameters have been used to train and improve the accuracy of the prediction model with multiple iterations. This paper also outlines the existing methods and the machine learning techniques to determine Evapotranspiration, data collection and preprocessing, model construction, and evaluation metrics, highlighting the significance of SVM in advancing the field of ET prediction. The results demonstrate the robustness and high predictability of the developed model on the basis of performance evaluation metrics (R2, RMSE, MAE). The effectiveness of the proposed model in capturing complex relationships within soil and environmental parameters provide insights into its potential applications for water resource management and hydrological ecosystem.

Keywords: evapotranspiration, FAO56, KNIME, machine learning, RStudio, SVM, sensors

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Authors: T. Yasmin, M. A. Farrelly, B. C. Rogers

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Urban water governance in developing countries faces numerous challenges arising from uncontrolled urban population expansion, water pollution, greater economic push and more recently, climate change impact while undergoing transitioning towards a sustainable system. Sustainability transition requires developing adaptive capacities of the socio-ecological and socio-technical system to be able to deal with complexity. Adaptive capacities deliver strategies to connect individuals, organizations, agencies and institutions at multiple levels for dealing with such complexity. Understanding the level of adaptive capacities for sustainability transformation thus has gained significant research attention within developed countries, much less so in developing countries. Filling this gap, this article develops a conceptual framework for analysing the level of adaptive capacities (if any) within a developing context. This framework then applied to the chronological development of urban water governance strategies in Bangladesh for almost two centuries. The chronological analysis of governance interventions has revealed that crisis (public health, food and natural hazards) became the opportunities and thus opened the windows for experimentation and learning to occur as a deviation from traditional practices. Self-organization and networks thus created the platform for development or disruptions to occur for creating change. Leadership (internal or external) is important for nurturing and upscaling theses development or disruptions towards guiding policy vision and targets as well as championing ground implementation. In the case of Bangladesh, the leadership from the international and national aid organizations and targets have always lead the development whereas more often social capital tools (trust, power relations, cultural norms) act as disruptions. Historically, this has been evident in the development pathways of urban water governance in Bangladesh. Overall this research has shown some level of adaptive capacities is growing for sustainable urban growth in big cities, nevertheless unclear regarding the growth in medium and small cities context.

Keywords: adaptive capacity, Bangladesh, sustainability transformation, water governance

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Authors: Bahieh Mohajeri, Mohamad Sharif Mustaf, Mahani Mokhtar

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Purpose: This paper attempts to set the stage for the exploration of female participation in administrative positions within non-western countries by reviewing the studies on female in administrative positions within non-western countries and suggesting guidelines for future studies in this area in developing countries. Methodology: The paper is based on a systematic review of papers that have been published in journals. Findings: The review focuses on constraints to female’s participation in higher education of developing countries (e.g. strong family responsibility, low levels of women faculty members, social values and gendered cultural factors). Practical Implications: Further guidelines for future examination of this field of study are suggested (e.g. adopting a different theoretical view).Value: The article is an initial attempt to gather knowledge about constraints of female administrators in higher education of developing countries. The subject has received less attention in studies on administration and gender. In addition, the article provides suggestions for future studies in order to understand women administrators’ experiences in different educational and cultural settings.

Keywords: administrative position, female administrator, developing countries, participation

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Authors: Mana Shrestha, Dhruba Khatri, Pralhad Kunwor

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The objective of the study was to explore the vehicle owners’ willingness to pay (WTP) for offsetting carbon that could eventually facilitate local governmental institutions to take further step in environmental conservation. Contingent valuation method was used to find out how much amount people were willing to pay for the carbon service they are getting from providers. Open ended questionnaire was carried out with 181 respondents randomly. The result shows different mean willingness to pay amount depending upon demographic variations like education, occupation, sex and residence but the occupation and the educational status significantly affected the WTP of respondent. Total WTP amount was calculated as 650 NRS.

Keywords: community forest, carbon offset, Kyoto, REDD WTP

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Authors: Nelson Kimeli Kemboi Yego, Juma Kasozi, Joseph Nkruzinza, Francis Kipkogei

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The study investigated the low uptake of health insurance in Kenya despite efforts to achieve universal health coverage through various health insurance schemes. Unsupervised machine learning techniques were employed to identify patterns in health insurance uptake based on sociodemographic factors among Kenyan households. The aim was to identify key demographic groups that are underinsured and to provide insights for the development of effective policies and outreach programs. Using the 2021 FinAccess Survey, the study clustered Kenyan households based on their health insurance uptake and sociodemographic features to reveal patterns in health insurance uptake across the country. The effectiveness of k-prototypes clustering, hierarchical clustering, and agglomerative hierarchical clustering in clustering based on sociodemographic factors was compared. The k-prototypes approach was found to be the most effective at uncovering distinct and well-separated clusters in the Kenyan sociodemographic data related to health insurance uptake based on silhouette, Calinski-Harabasz, Davies-Bouldin, and Rand indices. Hence, it was utilized in uncovering the patterns in uptake. The results of the analysis indicate that inclusivity in health insurance is greatly related to affordability. The findings suggest that targeted policy interventions and outreach programs are necessary to increase health insurance uptake in Kenya, with the ultimate goal of achieving universal health coverage. The study provides important insights for policymakers and stakeholders in the health insurance sector to address the low uptake of health insurance and to ensure that healthcare services are accessible and affordable to all Kenyans, regardless of their socio-demographic status. The study highlights the potential of unsupervised machine learning techniques to provide insights into complex health policy issues and improve decision-making in the health sector.

Keywords: health insurance, unsupervised learning, clustering algorithms, machine learning

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Authors: Chui Ka Shing

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This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed.

Keywords: bar model method, curriculum development, mathematics education, problem solving

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Authors: Canga Mimoza, Irene Malagnino, Giulia Malagnino, Vito Malagnino

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Aim: This study aims at evaluating the impact of total dust (LGS) and mineral dust (PM10), in the cardio vascular and respiratory systems. Also proving that these air polluters are the cause of several diseases, such as bronchopneumonia, pneumonia, bronchitis, angina pectoris and cardiac insufficiency. Material and Method: The study is concentrated in the cities of Fier and Vlora. This is a clinic-epidemiological study conducted during the time period 2014-2019. Some of the data of LGS and PM10 were obtained from the database of the Institute of Public Health. The formula to measure the mean value of LGS and PM10 is ∆X=X (mean)-Xᵢ. Results: Based on the calculations made, we noticed that: The mean value of LGS in the city of Fieri was 227,33, while the mean value of LGS in the city of Vlora was 177,4. Whereas, the mean value of PM10 in the city of Fieri was 105.5 and the mean value of PM10 in the city of Vlore was 77.5. According to, our statistics the values of LGS were 1.2 times higher in Fier than in Vlora and the PM10 values were 1.36 times higher in Fier than in Vlora. Based on the data, in the city of Fier, the incidence of the bronchopneumonia was 56.53 sick patients/1000 inhabitants, but in Vlora, it was 22 sick patients/1000 inhabitants, so the number of the sick patients was 2.5 times higher in the city of Fieri compared with Vlora city, (P=0.001). The number of the patients with bronchitis, in the city of Fier, was 18 patients/1000 inhabitants, whereas, in Vlora, it was 9 patients/1000 inhabitants, (P=0.005). Based on the data, 8 patients/1000 inhabitants in the city of Fier, suffered from the pneumonia disease, while in Vlora city, were 4 patients/1000 inhabitants, (P=0.005). Another disease taken in consideration was angina pectoris. This study can claim that in the city of Fier, 9.5 patients/1000 inhabitants suffered from this disease, while in Vlora city, were only 4 patients /1000 inhabitants, (P=0.001). Findings of the present study proved that 3.7 patients/1000 inhabitants in the city of Fieri, had cardiac insufficiency, whereas in the city of Vlora, were 1.8 patients/1000 inhabitants, (P=0.05). Conclusions: LGS and PM10 have an influential impact on the cardio vascular and respiratory system; that’s why their levels should be kept under control. The pollution levels are 1.2 and 1.4 times higher in Fier than in Vlora; also the incidences of the diseases are 2 times higher in Fier than in Vlora. Recommendations: In order to prevent the cardio vascular and respiratory diseases, we should avoid places where pollution is higher than the norm. This can be achieved by frequenting places where the air pollution is lower, such as parks, gardens, top floors, etc.

Keywords: impact of total dust, LGS, mineral dust, PM 10, cardio vascular pathologies, respiratory disease

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Authors: Cristy Stagnar, Nina Hubig, Diana Ivankovic

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The epigenome is a compelling candidate for mediating long-term responses to environmental effects modifying disease risk. The main goal of this research is to develop a machine learning-based DNA methylation score, which will be valuable in delineating the unique contribution of paternal epigenetic modifications to the germline impacting childhood health outcomes. It will also be a useful tool in validating self-reports of nonsmoking and in adjusting epigenome-wide DNA methylation association studies for this early-life exposure. Using secondary data from two population-based methylation profiling studies, our DNA methylation score is based on CpG DNA methylation measurements from cord blood gathered from children whose fathers smoked pre- and peri-conceptually. Each child’s mother and father fell into one of three class labels in the accompanying questionnaires -never smoker, former smoker, or current smoker. By applying different machine learning algorithms to the accessible resource for integrated epigenomic studies (ARIES) sub-study of the Avon longitudinal study of parents and children (ALSPAC) data set, which we used for training and testing of our model, the best-performing algorithm for classifying the father smoker and mother never smoker was selected based on Cohen’s κ. Error in the model was identified and optimized. The final DNA methylation score was further tested and validated in an independent data set. This resulted in a linear combination of methylation values of selected probes via a logistic link function that accurately classified each group and contributed the most towards classification. The result is a unique, robust DNA methylation score which combines information on DNA methylation and early life exposure of offspring to paternal smoking during pregnancy and which may be used to examine the paternal contribution to offspring health outcomes.

Keywords: epigenome, health outcomes, paternal preconception environmental exposures, supervised machine learning

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Authors: Janet Holland

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Eye tracking is a great way to triangulate multiple data sources for deeper, more complete knowledge of how instructional materials are really being used and emotional connections made. Using sensor based biometrics provides a detailed local analysis in real time expanding our ability to collect science based data for a more comprehensive level of understanding, not previously possible, for teaching and learning. The knowledge gained will be used to make future improvements to instructional materials, tools, and interactions. The literature has been examined and a preliminary pilot test was implemented to develop a methodology for research in Instructional Design and Technology. Eye tracking now offers the addition of objective metrics obtained from eye tracking and other biometric data collection with analysis for a fresh perspective.

Keywords: area of interest, eye tracking, biometrics, fixation, fixation count, fixation sequence, fixation time, gaze points, heat map, saccades, time to first fixation

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Authors: Wahid Sharif

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Germany is a country that is traditionally highly regarded in the countries of South Asia. The German people and German products are valued and generate a positive response in South Asia. The main objective of this research is to evaluate and analyze various dimensions of a Such Comparative Study of Geography (German & Pakistan). Basically, Germany is located in Central Europe; it has common borders with Denmark, the Netherlands, Belgium, Luxembourg, France, Switzerland, Austria, the Czech Republic and Poland, Its total area is around 356,854 sq km. Pakistan has a strategic geo-political location at the corridor of the world's major maritime oil supply lines and has close proximity to the resource and oil-rich Central Asian countries. Germany and Pakistan enjoy intimately cordial relations. Germany has taken large measures to aid the south Asian countries in its economic and governmental hardship. Commercial trade between Berlin and Islamabad has also been essential as Germany is Pakistan’s fourth largest trade partner, also Germany is home to 35,081 Pakistani immigrants overall, and the two nations have almost always had a friendly bond. The aim of this research is to initiate fruitful discussions about appropriate strategies and actions in the face of the economic and geopolitical challenges faced by Pakistan and the role that societies of each country can play in assisting the region in overcoming its problems. The research would aim to serve as a facilitator for developing collaborative research projects between different institutions and disciplines in the Germany and Pakistan institutions. This is important, as the issues of poverty, illiteracy, unemployment and social inequities need to be understood properly. Though geographically far apart from each other and not having gone through the experience that the Asian states had undergone in their relations with the Portuguese, Dutch, French and English. Pakistan and Germany did not have to forget any unpleasant memories of a colonial past. On the contrary, the freedom fighters of the Indo-Pak subcontinent did not make secret of their sympathy-nay-admiration for Germany, which, though defeated in World War I and World War II by Anglo-French and Anglo-American blocs respectively, had shaken the British and French empires to their foundation in the protracted wars.

Keywords: relations, cultural, socio economic, bilateral agreement

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Authors: Meruyert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova, Madina Ermaganbetova

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This research paper explores the process of creating a proctoring system by evaluating the implementation of practical face recognition algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As an outcome, a proctoring system will be created, enabling the conduction of tests and ensuring academic integrity checks within the system. Due to the correct operation of the system, test works are carried out. The result of the creation of the proctoring system will be the basis for the automation of the informational, educational portal developed by machine learning.

Keywords: artificial intelligence, education portal, face recognition, machine learning, proctoring

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Authors: Mahdi Bazarganigilani

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Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

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Authors: Ugur Choban, Aruzhan Zhaksylyk, Assylbek Nurgabdeshov

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In recent years, there has been an increasing understanding of the value of encouraging entrepreneurial attitudes in university students. This is motivated by the belief that stimulating entrepreneurship not only promotes economic growth but also fosters innovation. This study looks at the complex link and addresses critical gaps between psychological capital and entrepreneurial intention among university students, with a specific emphasis on how contextual factors like academic support and past business experience impact this dynamic. Using a quantitative research method, data were gathered from a broad sample of 300 university students drawn from several faculties. The study used a questionnaire that included the Psychological Capital Questionnaire (PCQ) to assess psychological capital and a validated scale for entrepreneurial intention, as well as binary measures of academic support and prior entrepreneurial experience. Statistical investigations, including multigroup analyses performed with SmartPLS software, provided interesting insights into the effect of contextual factors on the relationship between psychological capital and entrepreneurial intention. The findings highlight that psychological capital had a strong favorable influence on university students' entrepreneurial inclinations. Furthermore, the study found that academic support enhances the influence of psychological capital on entrepreneurial intentions, emphasizing the significance of institutional backing in fostering entrepreneurial mindsets. Furthermore, students with prior entrepreneurial experience had a stronger propensity for entrepreneurship, showing a synergistic link between psychological capital and entrepreneurial background. These findings have both theoretical and practical implications. By explaining the mechanisms by which psychological capital promotes entrepreneurial intentions, the study contributes to the establishment of focused entrepreneurship education programs and support activities that are suited to student requirements. Policymakers may use these findings to create policies that encourage student entrepreneurship, ultimately encouraging economic development and innovation.

Keywords: academic support, entrepreneurial intentions, higher education institutions, psychological capital, prior entrepreneurial experience

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Authors: Jabulani Mtshiya, Yasmin Sultana-Muchindu

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Technical and Vocational Education (TVE) is the platform on which developed nations have built their economic foundations, which have led them to attain high standards of living. Zambia has put up educational systems aimed at empowering the citizens and building the economy. Nations such as China, the United States America, and several other European nations are such examples. Despite having programs in Technical and Vocations Education, the Zambian economy still lags, and the industries contributing merger to Gross Domestic Product. This study addresses the significance of Technical and Vocational Education and how it can improve the livelihood of citizens. It addresses aspects of development and productivity and highlights the problems faced by learners in Lusaka and Southern provinces in Zambia. The study employed qualitative research design in data collection and a method of descriptive data analysis was used in order to bring out the description of the prevailing state of affairs in TVE in the perspective of learners. This meant that the respondents indicated their views and thoughts toward TVE. The study collected information through research questionnaires. The findings showed that TVE is regarded important by government and various stakeholders and that it is also regarded important by learners. The findings also showed that stakeholders and society need to pay particular attention to the development of TVE in order to improve the livelihood of citizens and to improve the national economy. Just like any other developed nation that used TVE to develop their industries, Zambia also has the potential to train its youth and to equip them with the necessary skills required for them to contribute positively to the growth of industries and the growth of the economy. Deliberate steps need to be taken by the government and stakeholders to apply and make firm the TVE policies that were laid. At the end of the study recommendations were made; that government should put in the right measures in order to harness the potential at hand. Further on, recommendations were made to carry out this research at the national level and also to conduct it using the quantitative research method, and that government should be consistent to its obligations of funding and maintaining TVE institutions in order for them to be able to operate effectively.

Keywords: education, technical, training, vocational

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Authors: Vaishali Chaurasia

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Ageing is the universal phenomenon that is associated with deteriorating health status. As the human becomes old, certain changes take place in an organism leading to morbidities, disabilities, and event death. Furthermore, older people are more vulnerable for the various kinds of diseases and health problem. Due to the some unhealthy conventions like smoking, drinking and unhealthy foods is the genesis of the lifestyle diseases. These diseases associated with the way a person or group of people lives. The main purpose of the study is to determine the prevalence of lifestyle diseases and its association with physical activity as well as the risk factors associated with it among the adult population in India. Longitudinal Aging Study in India and Study on Global Aging and Adult Health in India were used in the study. We will take population aged 50 and older, began in 1935, and regularly refreshed at younger ages with new birth cohorts. Life style diseases are more prominent in 65+ age group. The study finds an association between prevalence of life style diseases and life style risk factors. The lifestyle disease prevalence is more among higher age group people, female, richest quintile, and doing lesser physical activity. A higher prevalence of lifestyle diseases associated with the multiple risk factors. The occurrence of three and four risk factors was more prevalent in India. The frequency of different type of life style disease is higher among those who hardly or never do any physical activity as compare to those who do physical activity every day. The pattern remains the same in Moderate as well as vigorous physical activity. Those who are regularly doing physical activities have lesser percentage of having any disease and those who hardly ever or never do any physical activities and equally involve with some risk factors have higher percentage of having all type of diseases.

Keywords: lifestyle disease, morbidity, disability, physical activity

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Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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Authors: Shreya Srivastava, Sushovan Ghosh, Sagnik Dey

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Aerosols directly affect Earth’s radiation budget by scattering and absorbing incoming solar radiation and outgoing terrestrial radiation. While the uncertainty in aerosol radiative forcing (ARF) has decreased over the years, it is still higher than that of greenhouse gas forcing, particularly in the South Asian region, due to high heterogeneity in their chemical properties. Understanding the Spatio-temporal heterogeneity of aerosol composition is critical in improving climate prediction. Studies using satellite data, in-situ and aircraft measurements, and models have investigated the Spatio-temporal variability of aerosol characteristics. In this study, we have taken aerosol data from Multi-angle Imaging Spectro-Radiometer (MISR) level-2 version 23 aerosol products retrieved at 4.4 km and radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 21 years (2000-2021) over the Indian subcontinent. MISR aerosol product includes size and shapes segregated aerosol optical depth (AOD), Angstrom exponent (AE), and single scattering albedo (SSA). Additionally, 74 aerosol mixtures are included in version 23 data that is used for aerosol speciation. We have seasonally mapped aerosol optical and microphysical properties from MISR for India at quarter degrees resolution. Results show strong Spatio-temporal variability, with a constant higher value of AOD for the Indo-Gangetic Plain (IGP). The contribution of small-size particles is higher throughout the year, spatially during winter months. SSA is found to be overestimated where absorbing particles are present. The climatological map of short wave (SW) ARF at the top of the atmosphere (TOA) shows a strong cooling except in only a few places (values ranging from +2.5o to -22.5o). Cooling due to aerosols is higher in the absence of clouds. Higher negative values of ARF are found over the IGP region, given the high aerosol concentration above the region. Surface ARF values are everywhere negative for our study domain, with higher values in clear conditions. The results strongly correlate with AOD from MISR and ARF from CERES.

Keywords: aerosol Radiative forcing (ARF), aerosol composition, single scattering albedo (SSA), CERES

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka

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Authors: Kwizera Mireille, Kharesh Ahmed Al-Khadher

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This paper explores the critical issue of girls' and women's right to education, exploring the challenges they face in accessing and benefiting from quality education. Gender disparities in education have persisted globally, hindering social progress and sustainable development. The fundamental importance of education in empowering individuals and promoting gender equality is acknowledged, making it imperative to address the disparities that hinder girls' and women's educational opportunities. The paper discusses various factors contributing to these disparities, including cultural norms(common in third-world countries), socio-economic constraints, and systemic biases. Drawing on a wide range of scholarly sources, empirical studies, and reports from international organizations, this paper highlights the broader societal benefits of educating girls and women, ranging from improved health outcomes to enhanced economic development and greater social and political participation. The paper further outlines strategies and initiatives aimed at overcoming these challenges. These include policy interventions, community-based programs, and international collaborations that work towards eliminating gender-based discrimination in educational settings. The paper emphasizes the significance of not only ensuring access but also fostering an inclusive and safe learning environment that encourages girls and women to thrive academically and personally. By analyzing successful case studies and best practices from around the world, the paper offers insights into effective approaches that can be adopted to enhance girls' and women's right to education globally. Furthermore, it emphasizes the importance of raising awareness of girl's and women's education. In conclusion, this paper underscores the urgency of prioritizing and protecting the educational rights of girls and women's right to education as a fundamental human right and catalyst for gender equality. It calls for a concerted effort from governments, NGOs, educational institutions, and society as a whole to create an equitable and empowering educational landscape that contributes to gender equality and sustainable development.

Keywords: empowerment, gender equality, inclusive education, right to education

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Authors: Usama Shahid

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Be it written documents, news columns, or students' essays, verifying the content can be a time-consuming task. Apart from the spelling and grammar mistakes, the proofreader is also supposed to verify whether the content included in the essay or document is relevant or not. The irrelevant content in any document or essay is referred to as off-topic text and in this paper, we will address the problem of off-topic text detection from a document using machine learning techniques. Our study aims to identify the off-topic content from a document using Echo state network model and we will also compare data with other models. The previous study uses Convolutional Neural Networks and TFIDF to detect off-topic text. We will rearrange the existing datasets and take new classifiers along with new word embeddings and implement them on existing and new datasets in order to compare the results with the previously existing CNN model.

Keywords: off topic, text detection, eco state network, machine learning

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Authors: Tatyana Gavrilova, Vadim Onufriev

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Knowledge-based systems’ design requires the developer’s owning the advanced analytical skills. The efficient development of that skills within university courses needs a deep understanding of main pitfalls and drawbacks, which students usually make during their analytical work in form of visual modeling. Thus, it was necessary to hold an analysis of 5-th year students’ learning exercises within courses of 'Intelligent systems' and 'Knowledge engineering' in Saint-Petersburg Polytechnic University. The analysis shows that both lack of system thinking skills and methodological mistakes in course design cause the errors that are discussed in the paper. The conclusion contains an exploration of the issues and topics necessary and sufficient for the implementation of the improved practices in educational design for future curricula of teaching programs.

Keywords: knowledge based systems, knowledge engineering, students’ errors, visual modeling

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Authors: Sipho Mbatha, Anne Mastament-Mason

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South African manufacturing global competitiveness was ranked 22nd (out of 38 countries), dropped to 24th in 2013 and is expected to drop further to 25th by 2018. These impacts negatively on the industrialisation project of South Africa. For industrialization to be achieved through labour intensive industries like the Apparel Manufacturing Industries of South Africa (AMISA), South Africa needs to identify and respond to factors negatively impacting on the development of competitive advantage This paper applied factor conditions from Porter’s Diamond Model (1990) to understand the various challenges facing the AMISA. Factor conditions highlighted in Porter’s model are grouped into two groups namely, basic and advance factors. Two AMISA associations representing over 10 000 employees were interviewed. The largest Clothing, Textiles and Leather (CTL) apparel retail group was also interviewed with a government department implementing the industrialisation policy were interviewed The paper points out that while AMISA have basic factor conditions necessary for competitive advantage in the clothing and textiles industries, Advance factor coordination has proven to be a challenging task for the AMISA, Higher Education Institutions (HEIs) and government. Poor infrastructural maintenance has contributed to high manufacturing costs and poor quick response as a result of lack of advanced technologies. The use of Porter’s Factor Conditions as a tool to analyse the sector’s competitive advantage challenges and opportunities has increased knowledge regarding factors that limit the AMISA’s competitiveness. It is therefore argued that other studies on Porter’s Diamond model factors like Demand conditions, Firm strategy, structure and rivalry and Related and supporting industries can be used to analyse the situation of the AMISA for the purposes of improving competitive advantage.

Keywords: compliance rule, apparel manufacturing industry, factor conditions, advance skills and South African industrial policy

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Authors: Bartłomiej K. Sołtysik, Agnieszka Guligowska, Łukasz Kroc, Małgorzata Pigłowska, Elizavetta Fife, Tomasz Kostka

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Introduction: Functional capacity is one of the basic determinants of health in older age. Functional capacity may be influenced by multiple disorders, including cardiovascular and metabolic diseases. Nevertheless, there is relatively little evidence regarding the association of functional status and cardiometabolic risk factors. Aim: The aim of this research is to check possible association between functional capacity and cardiovascular risk factor in a group of younger seniors. Materials and Methods: The study group consisted of 300 participants aged 60-65 years (50% were women). Total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), glucose, uric acid, body mass index (BMI), waist-to-height ratio (WHtR) and blood pressure were measured. Smoking status and physical activity level (by Seven Day Physical Activity Recall Questionnaire ) were analysed. Functional status was assessed with the Timed Up and Go (TUG) Test. The data were compared according to gender, and then separately for both sexes regarding prolonged TUG score (>7 s). The limit of significance was set at p≤0.05 for all analyses. Results: Women presented with higher serum lipids and longer TUG. Men had higher blood pressure, glucose, uric acid, the prevalence of hypertension and history of heart infarct. In women group, those with prolonged TUG displayed significantly higher obesity rate (BMI, WHTR), uric acid, hypertension and ischemic heart disease (IHD), but lower physical activity level, TC or LDL-C. Men with prolonged TUG were heavier smokers, had higher TG, lower HDL and presented with higher prevalence of diabetes and IHD. Discussion: This study shows association between functional status and risk profile of cardiometabolic disorders. In women, the relationship of lower functional status to cardiometabolic diseases may be mediated by overweight/obesity. In men, locomotor problems may be related to smoking. Higher education level may be considered as a protective factor regardless of gender.

Keywords: cardiovascular risk factors, functional capacity, TUG test, seniors

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Authors: C. B. Le, V. N. Pham

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In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: Damianos Tzoupis

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In the context of the canon debate, assumptions regarding the place, value, and impact of classical texts have come under increased scrutiny. Factors like the distance of time, the depreciation of tradition, or the increased cultural omnivorousness and eclecticism have allegedly played a part in destabilizing classics’ authority. However, despite all these developments, classics’ position and influence is strong both in contemporary institutions and among readers’ preferences. Within this background of conflicted narratives, the study maps the varied discourses, value grammars, and justifications that lay cultural consumers employ to discuss those texts which have come to be the most consecrated and valuable cultural objects. The study centers on reviews posted on Goodreads. These online reviews offer unique access to unsolicited reception data produced by lay readers themselves, thus providing a clearer picture of lay cultural consumption and lay theories about classics. Moreover, the approach taken relies on the micro-practices of evaluation: the study investigates the evaluation of a specific cultural object, namely Plato’s allegory of the Cave, and treats it as an exemplary case to identify interpretive repertoires and valuation grammars about classical texts in general. The analysis uncovers a wide range of discourses used to construct the concept of the “classical text”. At first sight, lay reviewers seem to adopt interpretive repertoires that highlight qualities such as universality, timelessness, canonicity, cultural impact, and difficulty. These repertoires seem in principle to follow generalized and institutionalized discourses about classical texts, as these are established and circulated by institutions and cultural brokers like schools, academics, critics, etc. However, the study also uncovers important variations of these discourses. Lay readers tend to (re)negotiate the meanings/connotations of the above qualities and also structure their discourses by “modalities” such as necessity or surprise. These variations in interpretive repertoires are important in cultural sociology’s attempt to better grasp the principles informing the grammars of valuation that lay cultural consumers employ and to understand the kinds of impact that consecrated cultural objects have on people’s lives.

Keywords: classics, interpretive repertoires around classicalness, institutionalized discourses, lay readers, online reviews/criticism

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Authors: Shaik Asha Begum, S. Joshna Rani, Shaik Abdul Rahaman

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INTRODUCTION: Breast cancer is a disease that creates in breast cells. "KAP" study estimates the Knowledge, Attitude, and Practices of a local area. More than 1.5 million ladies (25% of all ladies with malignancy) are determined to have bosom disease consistently all through the world. Understanding the degrees of Knowledge, Attitude and Practice will empower a more effective cycle of mindfulness creation as it will permit the program to be custom-made all the more properly to the necessities of the local area. OBJECTIVES: The objective of this study is to assess the knowledge on signs and symptoms, risk factors, provide awareness on the practicing of the early detection techniques of breast cancer and provide knowledge on the overall breast cancer including preventive techniques. METHODOLOGY: This is an expressive cross-sectional investigation. This investigation of KAP was done in the Nirmala Educational Institutions from January to April 2021. A total of 300 participants are included from women students in pharmacy graduates & lecturers, and also from graduates other than the pharmacy. The examiners are taken from the BCAM (Breast Cancer Awareness Measure), tool compartment (Version 2). RESULT: According to the findings of the study, the majority of the participants were not well informed about breast cancer. A lump in the breast was the most commonly mentioned sign of breast cancer, followed by pain in the breast or nipple. The percentage of knowledge related to the breast cancer risk factors was also very less. The correct answers for breast cancer risk factors were radiation exposure (58.20 percent), a positive family history (47.6 percent), obesity (46.9 percent), a lack of physical activity (43.6 percent), and smoking (43.2 percent). Breast cancer screening, on the other hand, was uncommon (only 30 and 11.3 percent practiced clinical breast examination and mammography respectively). CONCLUSION: In this study, the knowledge on the signs and symptoms, risk factors of breast cancer - pharmacy graduates have more knowledge than the non-pharmacy graduates but in the preventive techniques and early detective tools of breast cancer -had poor knowledge in the pharmacy and non-pharmacy graduate. After the awareness program, pharmacy and non-pharmacy graduates got supportive knowledge on the preventive techniques and also practiced the early detective techniques of breast cancer.

Keywords: breast cancer, mammography, KAP study, early detection

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Authors: Jonathan Glazzard

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National student satisfaction data in England demonstrate that undergraduate students are less satisfied overall with assessment and feedback than other aspects of their higher education courses. Given that research findings suggest that high-quality feedback is a critical factor associated with academic achievement, it is important that feedback enables students to demonstrate improved academic achievement in their subsequent assessments. Given the growing importance of staff-student partnerships in higher education, this research examined students’ perceptions of assessment and feedback in one UK university. Students’ perceptions were elicited through the use of a university-wide survey which was completed by undergraduate students. In addition, three focus groups were used to provide qualitative student perception data across the three university Facilities. The data indicate that whilst students valued detailed feedback on their work, less detailed feedback could be compensated for by the development of pre-assessment literacy skills which are front-loaded into courses. Assessment literacy skills valued by students included the use of clear assessment criteria and assignment briefings which enabled students to fully understand the assessment task. Additionally, students valued assessment literacy pre-assessment tasks which enabled them to understand the standards which they were expected to achieve. Students valued opportunities for self and peer assessment prior to the final assessment and formative assessment feedback which matched the summative assessment feedback. Students also valued dialogic face-to-face feedback after receiving written feedback Above all, students valued feedback which was particular to their work and which gave recognition for the effort they had put into completing specific assessments. The data indicate that there is a need for higher education lecturers to receive systematic training in assessment and feedback which provides a comprehensive grounding in pre-assessment literacy skills.

Keywords: formative assessment, summative assessment, feedback, marking

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Authors: Helen Zhang

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Accurate segmentation of the airways from CT scans is crucial for early diagnosis of lung cancer. However, the existing airway segmentation algorithms often rely on thin-slice CT scans, which can be inconvenient and costly. This paper presents a set of machine learning-based 3D super-resolution algorithms along heterogeneous dimensions to improve the resolution of thicker CT scans to reduce the reliance on thin-slice scans. To evaluate the efficacy of the super-resolution algorithms, quantitative assessments using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural SIMilarity index) were performed. The impact of super-resolution on airway segmentation accuracy is also studied. The proposed approach has the potential to make airway segmentation more accessible and affordable, thereby facilitating early diagnosis and treatment of lung cancer.

Keywords: 3D super-resolution, airway segmentation, thin-slice CT scans, machine learning

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Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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