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Poverty is still one of the main problems for developing countries including Indonesia. Poverty is a multidimensional problem not only in terms of income but also in other factors such as health, education, access to goods and services, location, geographical conditions, gender, and environmental conditions. Poverty is not only the responsibility of the central government but also the respective regional governments and all levels of society. Therefore, this study was conducted as a contribution to the government in providing information about the forecasted number of poor people in 2023. This study used a dataset of the number of poor people in Indonesia by province from 2015 to 2022, sourced from the National Socioeconomic Survey. The proposed algorithm was Machine Learning with the Quasi-Newton BFGS technique using Matlab version 2011b. The dataset was analyzed using eleven architectural models: 6-3-1, 6-4-1, 6-5-1, 6-8-1, 6-10-1, 6-11-1, 6-15-1, 6 -20-1, 6-25-1, 6-5-5-1, and 6-11-1. After being analyzed, the best model obtained was 6-5-1 due to the lowest MSE and RMSE values compared to the other models. Therefore, the 6-5-1 architectural model can be used to forecast the number of poor people in Indonesia by the province in 2023. Thus, based on the forecasting results, the poor population in Indonesia in 2023 is expected to decrease compared to 2022. [ABSTRACT FROM AUTHOR]

Economic development improves people's welfare. In improving the welfare of the community, economic growth is needed because economic growth is an indication of the success of economic development. One important indicator that is used to determine economic conditions in a certain period is that GDP is good at the current price and at constant prices. This study performs the modelling of Indonesian GDP using panel regression and dynamic panel data regression with GMM Arellano-Bond estimates. Dynamic panel regression is needed in analyzing economic problems because economic variables are dynamic variables, that is, these variables are not only influenced by other variables but also by those variables at the previous time. By using GMM estimation, it can produce unbiased, consistent and efficient parameters. The data used are panel data from 21 provinces in Indonesia, which are included in the islands of Java, Sumatra, and Kalimantan in 2013–2017. The dependent variable is the GRDP. The independent variables are Government Expenditures, Foreign Investment, Domestic Investment, Human Development Index, Open Unemployment Rate, Number of Poor Population, and Average School Length. The Government Expenditures and the Number of Poor Population variables have a positive effect on GRDP with values of 0.017724 and 64.107. In the dynamic panel model with the estimated GMM Arellano-Bond, the variables that influence GDP are the GRDP-1, Foreign Investment, Poor Population, and Average School Length. School length variables provide the greatest long-term elasticity compared to other variables, which is equal to 0.8292. [ABSTRACT FROM AUTHOR]

In today's modern era, technologies are much developed, and we came far away. Even we are so far from the ancient time and comes under the category of developing country but still we can't say we are developed completely the reason comes out to be not getting proper education to students who actual deserve even the schemes which are made by the government are not in the reach of the poor people, some students couldn't afford the fee of hospital and that lead to severe problems and multiple people are getting died day by day we are losing the gems of India before even having them in our eyes some are dying by filling the loans of banks and other things So I Have made a technology or a model by which we can connect multiple technologies and applications together either by integrating or differentiating them to form a new innovation. In this research I have developed a model with the combination of Internet of Things and cloud computing technologies which can help the people all over the world. We can connect with hospitals, clinics, education, e-business, e-commerce, e-banking, connect with poor people to help them and merge them into a single unit by which a user can have multiple option to buy or pay the things according to his needs without travelling, government can focus on the poor people who couldn't afford the basic needs, one can fulfil his requirement at a very short period of time. [ABSTRACT FROM AUTHOR]

This paper deals with distinct problems of a woman faced in the social hierarchical order. This paper finds the significance of the title "The Inheritance of Loss". The main focus of this paper is to see how a deserted woman is degraded by the husband and predicament status of a widow in the society. It also discusses the elements of terrorism and political issues and a subaltern treated by the judge. This paper discuses on various post-colonial issues like the issues of poverty and subalternity. This paper also discloses people's longing and losses which are essential part of loss. This paper focuses the ordinary life of poor people in the text. [ABSTRACT FROM AUTHOR]

Housing is always critical for all governments in developing countries before providing public housing for low-income people. However, public housing has always been associated with long-term problems and poor value for money. To achieve the Sustainable Development Goals (SDGs) agenda, the globe is presently being encouraged to promote Sustainable Success (SS) in the construction industry, particularly in public housing. The Malaysian government is aware of the situation, and the Ministry of Housing and Local Government recently emphasized the need for long-term improvement in the National Housing Policy (NHP) 2018-2025. The sustainability factor will greatly increase the value of construction projects, particularly public housing projects. As a result, the purpose of this study is to present a thorough review of the SS that contributes to long-term success in public housing projects. To gain a better understanding of the key topics, a systematic literature review was conducted, and the findings were validated using a qualitative method involving semi-structured interviews with five construction key players. As a consequence, economic, social, and environmental factors all play an important role in achieving long-term public housing. The study's findings could be critical for the framework's development, acting as a catalyst for the creation of sustainable public housing. [ABSTRACT FROM AUTHOR]

Nonparametric regression is a statistical method used to determine the pattern of relationship between the predictor variable and the response when the regression function is unknown and only assumed to be smooth. Spline truncated is an approach towards data matching while taking into the smoothness of the curve which has continuous segmented properties so as to provide flexibility to adapt in explaining the local characteristics of the data function. The spline approach has the advantage of overcoming data patterns that indicate how sharply the ups or down with the help of vertices and relatively smooth curves. The supremacy of this method is good to be used for correlated data. In this study, will discuss the selection of optimal knot points using the Generalized Maximum Likelihood (GML) method on tuberculosis case data in East Kalimantan, West Kalimantan and South Kalimantan in 2020 using one knot point, two knot points and three knot points. The results showed that the best spline truncated nonparametric regression model in modeling the number of tuberculosis cases was using one knot points. The model has a minimum GML value of 11.774.487 with an R2value of 90.63%. Based on the results of testing the significance of the model parameters, it can be concluded that the money factors affecting the number of tuberculosis cases in East Kalimantan, West Kalimantan and South Kalimantan in 2020 are the percentage of community malnutrition, the percentage of trained health workers, the percentage of the poor people and the number of health centers. [ABSTRACT FROM AUTHOR]

The article focuses on how dual coping mechanisms impact the well-being of Bottom of the Pyramid (BOP) consumers facing stressors exacerbated by materialistic desires. Topics include the categorization of coping strategies into virtuous and vicious approaches; the role of technological access in these coping mechanisms; the influence of materialistic desires on stress levels and well-being; and study highlights how individuals' coping approaches affect their psychological well-being.

Climate change, marked by rising temperatures, poses significant health risks to indoorbound individuals. This paper stresses the need for proactive public health measures, especially for vulnerable groups like the elderly and economically disadvantaged who lack access to air conditioning. As heatwaves worsen, traditional solutions, like energyintensive air conditioning, are problematic due to increased energy use, greenhouse gas emissions, and cost issues. Instead, this paper proposes an affordable solution: electric fans, natural ventilation, and window shadings to combat heat stress indoors. The study examines the effectiveness of electric fans, window shading, and natural ventilation in mitigating extreme heat's impact. Findings show a notable reduction in heat exposure, even in worst-case scenarios, with electric fans reducing heat strain hours. The methodology employs EnergyPlus and Design Builder software for a comprehensive numerical simulation of a sample building representative of the ones constructed between 1961 and 1975 located in Trieste, Italy. The simulations employ historical weather data, extreme conditions, and future projections to enhance the analysis's depth and relevance. [ABSTRACT FROM AUTHOR]

Zakat is one of the five pillars of Islam that becomes philanthropic to reduce social inequality, increase welfare, and embody faith. There are eight groups of zakat recipients, namely the poor, amil, converts, riqab, gharim, fi sabilillah, and ibnu sabil managed by the Amil Zakat Institute (LAZ) in Indonesia. According to BPS, there has been an increase since September 2019 when the total number of poor people was 24.79 million people to 26.42 million people in March 2020. The increase in the number of poor people (mustahiq) indicates a problem in its management. The solution proposed through this research is the Multi-Factor Evaluation Process (MFEP), a method of evaluating zakat distribution with a priority scale. Six weighting criteria are determined by family status, clothing, food, housing, health, and education. A score of 1 to 10 is given to find the factor weight for each criterion. The value is reached by dividing the subfactor's total value by the subfactor's maximum value. The highest results on this evaluation of the first 10 (ten) priority mustahiq targets 0.74632 on behalf of Ahmad. More studies are needed to obtain more data and the accuracy of prioritizing mustahiq targets. [ABSTRACT FROM AUTHOR]

Poverty is a serious socio-economic problem in Malaysia and all over the world since it is a never-ending vicious cycle. Even though countless tries over decades, Malaysia has been unable to break free from its poverty chains. In peninsular Malaysia, Kelantan and Kedah have been stated as the highest poverty rate because those states have higher than the national poverty rate (8.4%). Since the past research has tended to focus on the country and state-level in Kedah, therefore, this study aimed to determine the most important indicators of poverty by all districts in Kedah by using the Rank Order Centroid weighting method. This study collected opinions by interviewing experts in the poverty field. The results shown the most important indicator of poverty was income followed by the highest education, marital status, living standard, strata, residential and comfortability. In addition, the poverty index was also developed for twelve districts in Kedah by using the Simple Additive Weighting method as it can identify the districts with high poverty index in Kedah. The results shown that Kuala Muda has the highest poverty index (0.9358) for poor group while the lowest index (0.2400)is Bandar Baharu. Meanwhile, for hardcore poor group, the results shown that Sik has the highest poverty index score (0.8135), while Bandar Baharu has the lowest index (0.2105). This research contributes to changes in poverty informationso that these governmental and non-governmental could revise the initiatives which might help poor people to get them out from poverty problem. [ABSTRACT FROM AUTHOR]

Freshwater is an inseparable part of humankind. Clean water is used in domestic as well as in commercial application. Separation of unwanted dirt particle, bacteria, and viruses from water by conventional method of desalination causes expensiveness. Reasonable amount of distilled productivity can be extracted from solar stills. Solar stills are cost effective and easy to design. In rural area poor people can't afford expensive traditional desalination devices. Shortage of clean water could be resolved by creating traditional stills at cheap cost. A solar still overcomes the two main problems of our country that is shortage of fresh water and energy. It basically converts the brackish, saline water to potable water. This review paper describe the importance of solar still, it's working, various factors to affects it's productivity and numerous devices which can be attached to increase the performance and yield. This paper have two objectives : Energy, exergy, economic and enviro-economic analysis of single effect solar still & Energy, exergy, economic and enviro-economic analysis of double effect solar still. In this review, comparisons is done on single effect and double effect stills on the basis of thermo-economic and enviro-economic. This paper also attempts to explain various techniques to improve the overall efficiency and effectiveness of solar still. [ABSTRACT FROM AUTHOR]

Microfinance plays a critical role in alleviating poverty and promoting global economic and social development. This was emphasized in the 2030 Agenda for Development. In fact, one of the Sustainable Development Goals (SDGs) is to improve access to financial services. They also emphasize the importance of women's access to financial possibilities, as well as comprehensive access to financial services for everybody. The concept of microfinance has been promoted with the goal of providing funds to people who were considered to be at the bottom of the socio-economic pyramid so that they might run modest household businesses, but it has now expanded as a means of assisting poor people in improving their socio standards. India is the world's second-most populous country, with more than 60% of the country's people living in rural areas. More than half of this rural population depend on agriculture or related occupations for living which leads to chronic underemployment and poor per capita income. Poor people have limited access to formalized credit from commercial banks. As a result, they are compelled to rely on informal sources of credit, which exploit them by charging high-interest rates, resulting in their long-term indebtedness. In India, microfinance is critical to the nation's development. It serves as an anti-poverty vaccine for rural residents by providing basic financial services to the underserved at low costs. The present study aims to highlight the role of microfinance in achieving the SDGs and its challenges and their solution in the Indian context. [ABSTRACT FROM AUTHOR]

This study aims to see what factors influence the dropout rate for children of compulsory education in the province of South Sulawesi. The factors studied indicated an influence in the region so that in this study the Spatial Error Model (SEM) regression was used. The data used in the study is secondary data from the Central Statistics Agency of South Sulawesi Province in 2018. This study was conducted to determine the spatial error model (SEM) in the dropout rate data that occurred in the province of South Sulawesi, as well as to analyze the factors that influence the dropout rate. school for compulsory school age children. The results of this study obtained a model that is y ^ i j = 0 , 6 ∑ j = 1 , i = 1 24 W i j + y i + 168 , 9 x 2 − 76 , 9 x 4 + 0 , 197 x 5 , so that the factors that significantly influence the dropout rate in South Sulawesi are per capita expenditure, the ratio of students to school and the number of poor people. [ABSTRACT FROM AUTHOR]

Kampung in Indonesia is well known as one of the character urban form, in which it has various condition as well as their way of living. In general, a kampung is sat as an urban informal settlement for low-income people which separate in many locations, such as along the riverbank or railway, around the urban waste disposal, etc. Nevertheless, some kampung are situated in the downtown or around the Malang Square as the most expensive area. Usually, kampung performs as a high density settlement, less of infrastructure, and supported by informal economic activities. Realized that kampung have some problems, develop a concept by themselves and some of them are supported by government, private and university. Various efforts have been made in supported kampung improvement programs, then it become a mass movement, and also supported by public – private – university program using kampung design competitions. The results of improving some programs were vary widely, but in generally it makes better conditions, in terms of increasing environmental quality, better residential infrastructure, better social participation, and increasing family income. Among the various efforts made, it turns out that many have succeeded in changing the stigma of a slum and dense kampung to be more livable and even a tourist destination, then in general it supports the concept of sustainability. In the early 2020, all of the word suffers caused of Covid-19 pandemic, in which almost all of economic and social activities are sharply decreased or even stopped up to the new normal is applied, some activities are to be conducted, but in fact, it was still limited, including tourism. After entering micro-scale social restriction, the number of covid sufferer were decrease, namely between level 3 to 4, various activities can begin to be carried out, including implementation of schools, worship and many activities using the health protocol in various form. Therefore, an adaptive concept is needed as a way out for the Covid-19 problem which aims to develop and restore tourist kampung, as well as sustainability needed. This concept is structured with an approach that combines scaling methods, sustainable concepts and health protocol standards for tourism development. The result of this research can be implemented in kampung tourism than it has the possibility for widespread in many kampung. [ABSTRACT FROM AUTHOR]

This study contributes to the literature in food security and economic growth. The relationship between food securities has been reviewed by variety of the previous studies; it becomes important to explore the problem issues that arise regarding on previous studies. This research is to explore the problems and issues in high income country. Though in the world's wealthiest countries, the poor people frequently survive in substandard housing and struggle to afford basic goods and services such as heating, transportation, and nutritious food for themselves and their families. Understanding of the relationship between multiple measuring poverty and variety of food security factors is therefore critical for program planning and subsequent analysis. People live in poverty in every country on the planet. Therefore, this study aims to examine the relationship between food security and economic growth in two selected high-income countries which is Singapore and Canada. [ABSTRACT FROM AUTHOR]

As of April 30, Vietnam has a total of 270 confirmed cases of the SARS-CoV-2 virus and no death, numbers that are significantly low compared to other neighboring countries. Besides, with no new cases reported in the past few days, and 222 cases have recovered. So far, Vietnam, which borders with China, where the COVID-19 originated, has done an excellent job in fighting the outbreak with limited resources compared to wealthy Western countries. In order to prevent further spread, Vietnamese authorities have enforced social distancing, many restaurants and businesses have shuttered, tourists have left, and many residents are out of work. As a result, the Vietnam economy and residents have been primarily affected. In this paper, the author will review how the Vietnamese Government combat the COVID-19 pandemic successfully, manage socio-economic impact as well as support poor people and workers. Lastly, the author will provide recommendations to Vietnam's Government to reduce the impact of coronavirus in tourist field. [ABSTRACT FROM AUTHOR]

The past decades of the last century and until now have witnessed many crises in the housing sector, and these crises were the result of many problems that led to a weak quality and quantity of housing stock, especially for low-income people, and Goal 11 of the Sustainable Development Goals states, "Make cities and human settlements inclusive, safe, and capable of enduring and being sustainable, we have prepared this research that attempts to answer the following question: Is the current empowerment in the housing sector real and efficient support for people with limited income? The research assumes that empowerment in the housing sector has an important and effective role in reducing housing problems, the research aims to reach the most important indicators of Empowerment in affordable housing And discussed in the light of the study area, the research relied on the descriptive-analytical approach and a questionnaire was made for a random sample of 60 people distributed among experts in the housing sector, local authority, non-governmental organizations, and the local community. The research recommends the need to support the category of low-income citizens and give them flexible and affordable loans to help them own a housing unit and to take into account the conditions of the site to ensure that they do not bear additional transportation costs resulting from moving to the city center, especially for students and workers. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic that hit the country has caused a huge impact, especially on the economic sector. The approach taken by the government in dealing with the pandemic crisis by implementing a movement control order (MCO) have, to some extent, affected the source of income of the community. In order to survive, these underprivileged people are in need of financial assistance from the government, agencies and the kind-hearted people. Islam places great emphasis on welfare, especially in helping the needy with their daily needs. Therefore, this study aims to examine the level of philanthropic behavior of Muslims during the COVID-19 pandemic as well as to analyze the differences in Muslim philanthropies' behavior during the occurrence of this pandemic based on demographic factors, namely gender, age, education level, marital status, area of residence, household income and employment sector. To achieve this goal, a total of 424 respondents had answered a set of questionnaires distributed during the movement control order (MCO) period as a time limit via a simple sampling method. The results of the study found that five out of the seven demographic factors tested, namely age, level of education, area of residence, household income and employment sector showed significant differences in philanthropic behavior among the respondents. These findings also prove that demographic factors do also influence the decision-making process to donate among Muslims in Melaka. Therefore, all parties need to take a role in explaining and providing awareness on the importance of this philanthropic activity so that the burden borne by the community affected by the COVID-19 pandemic can be eased. [ABSTRACT FROM AUTHOR]

The infant Mortality rate (IMR) is an indicator normally used as an index of economic improvement, an indicator of the nice of existence, and the principle aspect figuring out the life expectancy of a society. IMR can be observed as longitudinal data, a combination of cross-section data and time-series data, where the same cross-section unit is observed at different times. When the data is repeatedly observed with a specific interval of time, then the time will correlate or not mutually exclusive. To overcome this, time is used as a random effect, so the appropriate method used is the Generalized Linear Mixed Model (GLMM). This study pursuits to version infant mortality data the use of the GLMM and have a look at the variables that affect the quantity of infant deaths in West Sumatra. Based on the results of the analysis, the quantity of low birth weight babies, the percentage of births assisted by non-medical personnel, the percentage of households that have access to proper sanitation services, the percentage of households that have adequate drinking water sources, the percentage of poor people, the quantity of health workers, and the quantity of health facilities has a very significant influence on infant mortality in the province of West Sumatra. [ABSTRACT FROM AUTHOR]

The article focuses on examining the health consumption patterns of low-income, chronically ill individuals within their daily lived spaces, exploring the spatial ecology and strategies used to navigate those spaces for seeking health. Topics include spatial ecology of health, spatial strategies for health, and the interplay of life factors in selecting health-seeking strategies within impoverished and ill populations.

One of the problems faced by the Province of West Java is poverty. The response data used in this study is the percentage of the poor who have a non-normal distribution. Fixed effects variables consist of life expectancy, school year expectancy, and school enrollment rates aged 16-18 years. Years and clusters variables will be included as independent variables but are random effects. Therefore, for this data case, the appropriate model to be developed is Binomial GLMM and Beta-Binomial HGLM. The modeling performed on the percentage of poor population data gives relatively the same results between the model approaches using Binomial GLMM and Beta-Binomial HGLM with a random effect of years. The random effect in both models shows that there is a variation in the percentage of poor people in years, but the variabilitybetween years cannot be shown by the data. Likewise, the modeling carried out on the percentage of poor population data gives relatively the same results between the model approaches using Binomial GLMM and Beta-Binomial HGLM with clusters random effect. Fixed effects variables and random effects have a significant effect on the percentage of poor people for all models. The model obtained by involving all fixed effects and random effects (clusters) is the best model because itprovides the smallest CAIC value compared to models using random effects (Years). [ABSTRACT FROM AUTHOR]

Bidikmisi scholarships are tuition assistance for prospective students who are economically disadvantaged but have the good academic potential to study at State Universities in Indonesia. With the amount Bidikmisi applicants, there is a need to use a system that can speed up the selection process and avoid human errors. The purpose of this study is to develop a classification system for Bidikmisi scholarship applicants at Universities in Indonesia. This study uses a multilayer perceptron (MLP) neural network to build a classification model. Because MLP has some hidden layers, MLP has advantages to predict or analyze complex problems. The methodology in this study is data collection, data preprocessing, data encoding, data modeling, and evaluation. The results of the classification of bidikmisi scholarship applicants are divided into two classes, namely accepted and rejected. The multilayer perceptron method generates an accuracy value of 72.81%. The Multilayer perceptron is compared with other classification methods, namely Naïve Bayes and K-Nearest Neighbors (KNN). The results of the classification using the Naïve Bayes method obtained an accuracy value of 79.47%, while the accuracy value using KNN was 78.33%. Evaluation using MLP resulted in precision, recall, and F1-measure values of 68.36%, 72.81%, and 66.33%. the results of the evaluation using Naïve Bayes were 75.58%, 79.47%, and 71.24%, while the KNN values were 71.90%, 78.33%, and 72.53%. In order to the conclusion in this research is the MLP method can generate good performance for the classification of bidikmisi scholarship applicants. However, Naïve Bayes' performance is better than MLP for the classification of bidikmisi scholarship applicants. [ABSTRACT FROM AUTHOR]

The development model of the GLM for longitudinal data that has not normally distributed (but still in the exponential family) and correlates with response variables is the Generalized Estimating Equations (GEE) and Generalized Linear Mixed-effects Model (GLMM) models. This study compares the GEE model with the GLMM on longitudinal data in modeling poor people in Indonesia in 2015-2019. The data source used is from the publication of the Central Statistics Agency. Based on the smaller RMSE and AIC criteria, the GLMM model is better than the GEE model in modeling the percentage of poor people in Indonesia. The Gini ratio, the rate of Households in Slums, and the percentage of Informal Workers have a significant positive effect on the percentage of poor people. Meanwhile, the percentage of households having access to HDI, economic growth, domestic and foreign investment value have a significant negative impact on poor people. [ABSTRACT FROM AUTHOR]

Purpose: This research intends to determine the possible effects of alternative growth strategies which including changing tax structures and increasing capital flow to economic movements in order to speed up economic recovery and ensure long-term growth and sustainable development of the state economy. Methodology: The study examines the most recent information on the impact of the tax structure on economic growth, determining which adjustments to the growth-enhancing tax system can help the economy recover faster by safeguarding low-income people. The paper examines the efficacy of short-term measures in several European nations during the crisis, as well as prospective mechanisms for long-term tax policymaking to minimize the crisis' effects on future sustainable development. Results: The study's conclusion is that the country's recovery from the COVID-19 crisis is dependent on the government's response, the speed with which solutions are developed, and all economic participants in the economic circle. Originality: The tax system as a whole must be assessed, not its elements. It is therefore necessary to find a balanced, neutral approach between economic growth, social issues, and environmental impact in order to achieve sustainable development. Such a balanced, neutral approach could be a reduction in labor taxes and consumption taxes for households, offset by an increase in wealth and solidarity payments. [ABSTRACT FROM AUTHOR]

Deep Learning is invading almost all sector of real world. With the rapidly growing demand and need of several industries, a Convolutional neural network (CNN) has become a major driving force in all image based applications. The advances in Computation infrastructures like cloud, GPUs and data science, solution to almost any problem is made simple as ever before. The formidable growth of these technologies aid in the high level understanding of computers resulting in automation and digitization while meeting the extremity of real world applications. In this paper we train the CNN to identify different types of basic skin diseases, source of cause and also attempt to predict the recurrence of the disease in future. Based on the appearance, the neural network is trained to understand the different categories of diseases and analyze the reason for occurrence and also predicts the recurrence of the disease in future. According to "A new Journal of the European Academy of Dermatology and Venereology "states that skin problems are the most commonly caused human illness. But most of the people give poor importance and doesn't consult the physician. Skin problems are often considered to be least important due to various societal and personal factors. While most of the people avoid consulting a physician due to lack of awareness, reluctant and seriousness, diagnosing the problem via images may become a good fortune to many people suffering from various skin problems. Image classification and image captioning, the subfields of computer vision are used for classifying the images and labeling them according to the visual content. In addition to these, Transfer Learning advancement in the field of Deep learning is used to identify the reason for recurrence of skin problems. Automated detection of skin problems, instance segmentation and the subsequent quantification (severity of skin problem) will be able to provide timely help to patients. Experimental results provide greater accuracy in the field of dermatology while detecting the disease, source of occurrence. Further attempts are made to predict the recurrence. [ABSTRACT FROM AUTHOR]

This research aims to propose improvement actions to integrate social innovation in the microfinance sector to promote financial inclusion in Mexico, to provide financial services to low-income people. Since the infrastructure, the supply of financial products and services in Mexico is highly concentrated in urban areas in the center and north of the country, for which there is the challenge of expanding them to a greater part of the population to reduce the income gap coverage in rural areas and in southern Mexico. The research is descriptive, phenomenological, qualitative, and non-experimental. As a result of the investigation, a proposal for improvement actions was designed that integrates social innovation to promote financial inclusion in Mexico. The proposal focuses on the use of technological applications that are being used in the country and is supported by social innovations identified in some successful cases in the microfinance sector worldwide. [ABSTRACT FROM AUTHOR]

Due to the COVID -19 Pandemic, there was a sudden shift from face-to-face to distance education in all schools and universities in Saudi Arabia (SA) starting March 2020. Many instructors and students were not technically prepared for this abrupt transition as some did not have devices and Internet access. On the other hand, some households have high-speed Internet and even a device for each child. This study investigates the digital equity in accessing online courses by students in low-income families, orphanages, and remote areas. A sample of school and university teachers and students from different regions in SA was interviewed. The subjects reported that lack of devices/Internet access was overcome by: (i) Governorates donating thousands of tablets to disadvantaged students; (ii) charity organizations and affluent individuals donate tablets/laptops and financial aid; (iii) some school teachers collect money to buy tablets for needy students; (iv) students who do not have devices and/or Internet go to school few times a week and meet with teachers face-to-face to teach them and help them with homework; (v) needy college students are allowed to use devices and Internet at their college computer laps or library; (vi) some underprivileged students reported borrowing a smart phone/laptop from relatives or neighbours and/or use relatives and neighbours’ Internet; (vii) Saudi mobile companies offer special Internet packages for students and teachers. Sample regions, types of disadvantaged students and help provided to bridge the digital and distance education gap in SA during COVID -19 are given in detail. [ABSTRACT FROM AUTHOR]