Search results for: English learning strategies

Authors: Muftahu Jibirin Salihu, Hazri Jamil

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The persisting challenge of access and enrolment to higher education in commonwealth countries has been reported in several studies, including reports of the international organization such as World Bank, UNESCO among others however from the macro perspective. The overarching aim of this study is to examine alternative policy practices towards improving access to university education in Nigeria at meso level of policy practice from evidence base policy studies using one university as a case. The study adopted a qualitative approach to gain insightful understanding on the issue of the study employing a semi-structure interview and policy documents as the means for obtaining the data and other relevant information for the study. The participants of the study were purposively chosen which comprise of a number of individuals from the selected university and other related organization which responsible for the policies development and implementation of Nigerian higher education system. From the findings of the study, several initiatives have been taken at meso level to address this challenge including the introduction of the University Matriculation Program as an alternative route for enhancing to access to the university education. However, the study further provided a number of recommendations which aimed at improving access to university education such as improving the entry requirements, society orientation on university education and the issue of ranking of certificate among the Nigerian higher institutions of learning.

Keywords: policy practice, access, enrolment, university, education, Nigeria

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Authors: Crispin Rakibu Mbamba

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Twenty-two years after the adoption of the United Nation Trafficking Protocol, evidence suggest that child trafficking continues to rise. Community level factors, like poverty which creates the conditions for children’s vulnerability is key to the rise in trafficking cases in Ghana. Albeit, growing evidence suggestthat despite the vulnerabilities, communities have the capacity to prevent and address child trafficking issues. This study contributes to this positive agenda by exploring the ways in which communities (and the key actors) in Ghana contribute to child trafficking interventions.The study objective is explored through in-depth interviews with practitioners (including social workers) from an organization working in trafficking hotspots in Ghana. Interviews wereanalyzed thematically with the help of HyperRESEARCH software. From the in-depth interviews, three themes were identified as the ways in which communities are involved in child trafficking interventions: 1) engagement of community leaders, 2) community-led anti-trafficking committees and 3) knowledge about trafficking. Albeit the cultural differences, evidence on the instrumental role of community chiefs and leaders provide important learning on how to harness trafficking intervention measures and ensure better child protection practices. Based on the findings, we recommend the need to intensify trafficking awareness campaigns in rural communities where education is lacking to contribute to United Nations (UN) promoting Just, Peaceful and Inclusive societies’ mandate.

Keywords: child trafficking, community interventions, knowledge on trafficking, human trafficking intervention

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Authors: L. Ebralidze, A. Tsertsvadze, D. Berashvili, A. Bakuridze

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Current cancer therapy strategies are based on surgery, radiotherapy and chemotherapy. The problems associated with chemotherapy are one of the biggest challenges for clinical medicine. These include: low specificity, broad spectrum of side effects, toxicity and development of cellular resistance. Therefore, anti-cance drugs need to be develop urgently. Particularly, in order to increase efficiency of anti-cancer drugs and reduce their side effects, scientists work on formulation of nano-drugs. The objective of this study was to develop composition and technology of vincristine nanoparticles using high-molecular carbohydrates of plant origin. Plant polysacharides, particularly, soy bean seed polysaccharides, flaxseed polysaccharides, citrus pectin, gum arabic, sodium alginate were used as objects. Based on biopharmaceutical research, vincristine containing nanoparticle formulations were prepared. High-energy emulsification and solvent evaporation methods were used for preparation of nanosystems. Polysorbat 80, polysorbat 60, sodium dodecyl sulfate, glycerol, polyvinyl alcohol were used in formulation as emulsifying agent and stabilizer of the system. The ratio of API and polysacharides, also the type of the stabilizing and emulsifying agents are very effective on the particle size of the final product. The influence of preparation technology, type and concentration of stabilizing agents on the properties of nanoparticles were evaluated. For the next stage of research, nanosystems were characterized. Physiochemical characterization of nanoparticles: their size, shape, distribution was performed using Atomic force microscope and Scanning electron microscope. The present study explored the possibility of production of NPs using plant polysaccharides. Optimal ratio of active pharmaceutical ingredient and plant polysacharids, the best stabilizer and emulsifying agent was determined. The average range of nanoparticles size and shape was visualized by SEM.

Keywords: nanoparticles, target delivery, natural high molecule carbohydrates, surfactants

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Jayanti Pujari

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The present study attempts to find out the barriers faced by adult women with an Intellectual disability during their training at vocational training centres offered by rehabilitation institutes. As economic independence is the ultimate aim of rehabilitation, this study tries to focus on the barriers which restrict the adult women with intellectual disability in equipping themselves in required skill which can really empower them and help them in independent living. The objectives of the study are (1) To find out the barriers perceived by job coaches during training given to women with intellectual disability (2) To find out the barriers perceived by the parents of women with intellectual disability who are undergoing vocational training and (3) To find out the barriers perceived by the women with intellectual disabilities during the vocational training. The barriers have been operationalised in the present study from three perspectives such as behavioural barriers, competency related barriers and accessibility barriers. For the present study three groups of participants(N=60) have been selected through purposive nonprobability sampling procedure to generate the data. They are( 20) job coaches who are working at vocational centres, (20) parents of women with intellectual disabilities, (20) adult women with intellectual disabilities. The study followed a descriptive research design and data are generated through self developed questionnaire. Three sets of self-developed and face validated questionnaires were used as the tool to gather the data from the three categories of sample. The questionnaire has 30 close ended questions and the respondents have to answer on a three point scale (yes, no, need help). Both qualitative and quantitative analysis was conducted to test the hypothesis. The major findings of the study depict that the 87% of the women with intellectual disability perceived highest barriers related to competency whereas barriers related to behaviour and accessibility are perceived lowest. 92% of job coaches perceived barriers related to competencies and accessibility are highest which hinder the effectiveness of skill development of women with intellectual disability and 74% of the parents of adult women with intellectual disability also opines that the barriers related to competencies and accessibility are highest. In conclusion, it is stressed that there is need to create awareness among the stakeholders about the training and management strategies of skill training and positive behaviour support which will surely enable the adult women with intellectual disability to utilise their residual skill and acquire training to become economically independent.

Keywords: economic independence, intellectual disability, skill development, training barrier

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Sai Sankalp Vemavarapu

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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Yude Wu

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Mongolia, grappling with significant socio-economic challenges, faces pressing issues of inequality and poverty, as evidenced by a high Gini coefficient and the highest poverty rate among the top 20 largest Asian countries. Despite government efforts, Mongolia's poverty rate experienced only a slight reduction from 29.6 percent in 2016 to 27.8 percent in 2020. PEER countries, such as South Africa, Botswana, Kazakhstan, and Peru, share characteristics with Mongolia, including reliance on the mining industry and classification as lower middle-income countries. Successful transitions of these countries to upper middle-income status between 1994 and the 2010s provide valuable insights. Drawing on secondary analyses of existing research and PEER country profiles, the study evaluates past policies, identifies gaps in current approaches, and proposes recommendations to combat poverty sustainably. The hypothesis includes a reliance on the mining industry and a transition from lower to upper middle-income status. Policies from these countries, such as the GEAR policy in South Africa and economic diversification in Botswana, offer insights into Mongolia's development. This essay aims to illuminate the multidimensional nature of underdevelopment in Mongolia through a secondary analysis of existing research and PEER country profiles, evaluating past policies, identifying gaps in current approaches, and providing recommendations for sustainable progress. Drawing inspiration from PEER countries, Mongolia can implement policies such as economic diversification to reduce vulnerability and create stable job opportunities. Emphasis on infrastructure, human capital, and strategic partnerships for Foreign Direct Investment (FDI) aligns with successful strategies implemented by PEER countries, providing a roadmap for Mongolia's development objectives.

Keywords: inequality, PEER countries, comparative analysis, nomadic animal husbandry, sustainable growth

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Authors: Poteet Frances, Glovinski Ira

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INTRODUCTION: The interoceptive nervous system continuously senses chemical and anatomical changes and helps you recognize, understand, and feel what’s going on inside your body so it is important for energy regulation, memory, affect, and sense of self. A newborn needs predictable routines rather than confusion/chaos to make connections between internal experiences and emotions. AIM: Current legal protocols of removing babies from drug-addicted mothers impact the critical window of bonding. The newborn’s brain is social and the attachment process influences a child’s development which begins immediately after birth through nourishment, comfort, and protection. DESCRIPTION: Our project aims to educate drug-addicted mothers, and medical, nursing, and social work professionals on interoceptive concepts and practices to sustain the mother/newborn relationship. A mother’s interoceptive knowledge predicts children’s emotion regulation and social skills in middle childhood. CONCLUSION: When mothers develop an awareness of their inner bodily sensations, they can self-regulate and be emotionally available to co-regulate (support their newborn during distressing emotions and sensations). Our project has enhanced relationship preservation (mothers understand how their presence matters) and the overall mother/newborn connection.

Keywords: drug-addiction, interoception, legal, mothers, newborn, self-regulation

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Authors: Ochuko K. Overen, Golden Makaka, Edson L. Meyer, Sampson Mamphweli

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Low-cost housing provided for people with small incomes in South Africa are characterized by poor thermal performance. This is due to inferior craftsmanship with no regard to energy efficient design during the building process. On average, South African households spend 14% of their total monthly income on energy needs, in particular space heating; which is higher than the international benchmark of 10% for energy poverty. Adopting energy efficient passive solar design strategies and superior thermal building materials can create a stable thermal comfort environment indoors. Thereby, reducing energy consumption for space heating. The aim of this study is to analyse the thermal behaviour of a low-cost house integrated with passive solar design features. A low-cost passive solar house with superstructure fly ash brick walls was designed and constructed in Somerset East, South Africa. Indoor and outdoor meteorological parameters of the house were monitored for a period of one year. The ASTM E741-11 Standard was adopted to perform ventilation test in the house. In summer, the house was found to be thermally comfortable for 66% of the period monitored, while for winter it was about 79%. The ventilation heat flow rate of the windows and doors were found to be 140 J/s and 68 J/s, respectively. Air leakage through cracks and openings in the building envelope was 0.16 m3/m2h with a corresponding ventilation heat flow rate of 24 J/s. The indoor carbon dioxide concentration monitored overnight was found to be 0.248%, which is less than the maximum range limit of 0.500%. The prediction percentage dissatisfaction of the house shows that 86% of the occupants will express the thermal satisfaction of the indoor environment. With a good operation of the house, it can create a well-ventilated, thermal comfortable and nature luminous indoor environment for the occupants. Incorporating passive solar design in low-cost housing can be one of the long and immediate solutions to the energy crisis facing South Africa.

Keywords: energy efficiency, low-cost housing, passive solar design, rural development, thermal comfort

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Authors: Jeonghwan Jeon, Mintak Han, Youngjun Kim

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Due to the rapid development of information and communication technology (ICT), a substantial transformation is currently happening in the society. As the range of intelligent technologies and services is continuously expanding, ‘things’ are becoming capable of communicating one another and even with people. However, such “Internet of Things” has the technical weakness so that a great amount of such information transferred in real-time may be widely exposed to the threat of security. User’s personal data are a typical example which is faced with a serious security threat. The threats of security will be diversified and arose more frequently because next generation of unfamiliar technology develops. Moreover, as the society is becoming increasingly complex, security vulnerability will be increased as well. In the existing literature, a considerable number of private and public reports that forecast future society have been published as a precedent step of the selection of future technology and the establishment of strategies for competitiveness. Although there are previous studies that forecast security technology, they have focused only on technical issues and overlooked the interrelationships between security technology and social factors are. Therefore, investigations of security threats in the future and security technology that is able to protect people from various threats are required. In response, this study aims to derive potential security threats associated with the development of technology and to explore the security technology that can protect against them. To do this, first of all, private and public reports that forecast future and online documents from technology-related communities are collected. By analyzing the data, future issues are extracted and categorized in terms of STEEP (Society, Technology, Economy, Environment, and Politics), as well as security. Second, the components of potential security threats are developed based on classified future issues. Then, points that the security threats may occur –for example, mobile payment system based on a finger scan technology– are identified. Lastly, alternatives that prevent potential security threats are proposed by matching security threats with points and investigating related security technologies from patent data. Proposed approach can identify the ICT-related latent security menaces and provide the guidelines in the ‘problem – alternative’ form by linking the threat point with security technologies.

Keywords: future society, information and communication technology, security technology, technology forecasting

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Authors: Alan Lai, Wilson Yik

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With rapid urbanization, there has been a dramatic increase in global urban population in Asia and over half of population in Asia will live in urban regions in the near future. Facing with increasing exposure to climate-related stresses and shocks, most of the Asian cities will very likely to experience more frequent heat waves and flooding with rising sea levels, particularly the coastal cities will grapple for intense typhoons and storm surges. These climate changes have severe impacts in urban areas at the costs of infrastructure and population, for example, human health, wellbeing and high risks of dengue fever, malaria and diarrheal disease. With the increasing prominence of adaptation to climate changes, there have been changes in corresponding policies. Smaller cities have greater potentials for integrating the concept of resilience into their infrastructure as well as keeping pace with their rapid growths in population. It is therefore important to explore the potentials of Asian cities adapting to climate change and the opportunities of building climate resilience in urban planning and building design. Furthermore, previous studies have mainly attempted at exploiting the potential of resilience on a macro-level within urban planning rather than that on micro-level within the context of individual building. The resilience of individual building as a research field has not yet been much explored. Nonetheless, recent studies define that the resilience of an individual building is the one which is able to respond to physical damage and recover from such damage in a quickly and cost-effectively manner, while maintain its primary functions. There is also a need to develop an assessment tool to evaluate the resilience on building scale which is still largely uninvestigated as it should be regarded as a basic function of a building. Due to the lack of literature reporting metric for assessing building resilience with sustainability, the research will be designed as a case study to provide insight into the issue. The aim of this research project is to encourage and assist in developing neighborhood climate resilience design strategies for Hong Kong so as to bridge the gap between difference scales and that between theory and practice.

Keywords: resilience cities, building resilience, resilient buildings and infrastructure, climate resilience, hot and humid southeast area, high-density cities

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Authors: Paolo Fantozzi, Luigi Laura, Umberto Nanni

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The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.

Keywords: cooccurrence graph, entity relation graph, unstructured text, weighted distance

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Authors: Huseyin Arasli, Maryam Abdullahi, Tugrul Gunay

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One of the prominence elements used by the destination marketing organization (DMO) as a marketing strategy is the application of Social media tools. During the current spread of coronavirus disease (COVID-19), travel restriction was placed in most countries of the world, leading to the closure of borders movement. It should be noted that most tourism travelers depend on social media to obtain and exchange different kinds of information about COVID-19 in an unprecedented scale. The situational information people received is valued, which calls for the response of the tourism industry on the epidemic. Therefore, it is highly important to recognize such situational information and to understand how people spread this propaganda on social media platforms so that suitable information that relates the COVID-19 epidemic is available in a manner that will not tarnish the marketing strategies, festival planners. Data for this research study was collected from the desk review, which is a secondary source data, online blogs, and interview through social media chat. The results of this research show that the widespread of COVID-19 pandemics led to rapid lockdown in states and cities all over Nigeria, causing declining demands in hotels, airlines, recreation, and tourism centers. Additionally, billions of dollars lost has been recorded in the high increase of hotels and travel bookings cancellations which caused hundreds and thousands of job loss in the country. The result of this research also revealed that COVID-19 is causing more havoc on the unemployment rate indices of the country. Similarly, the over-dependence of government on petroleum has further caused considerable revenue loss, thereby raising a high poverty rate among less privileged Nigerians. Based on this result, the study suggested that there is an urgent need for the government to diversify its economy by looking at other different sectors such as tourism and agricultural farm produce to harmonize other commercial trades sectors in the country.

Keywords: social media, destination marketing organizations, DMOs, cultural COVID-19, coronavirus, hospitality, travel tour, tourism

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Authors: Pramoda Karunarathna, Hemamalie Gunatilaka

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This study is based on experiences of Sri Lankan lesbian and gay workers’ career in the corporate sector, which include both manufacturing and service sectors. The study has started with the intention of shedding light on a grey area to observe the negative effects on lesbian and gay workers and their experiences while they are employed in the Sri Lankan corporate sector. In order to understand the experiences of lesbian and gay workers while they are at work within the corporate sector, the study seeks to address four questions. First research question is about the challenges faced by lesbian and gay workers while they are at work, and the second research question looks at their career patterns. Third research question seeks to address the behavior at work, and the fourth research question looks at the influence of class, religion, and cultural aspects on the career of lesbian and gay workers. Methodologically, the research was based on semi-structured interviews with nine participants (five gay men and four lesbian women) having work experience in the corporate sector and residing in Colombo, the capital city of Sri Lanka. The research found that the participants have gone through the process of developing sexual identity; gay men possess more feminine characteristics, while lesbian women possess more masculine characteristics. Further, their identity gets revealed in different ways, such as through the curriculum vitae, at the interviews, through the attire and behavior, and with the use of social media. The study also found that lesbian and gay workers experience discrimination due to violation of hierarchical power difference by other employees and marginalization, verbal and nonverbal abuse by other men at work are common experiences. Another finding is that lesbian and gay workers adopt strategies for survival at work, and they prefer the NGO sector to the corporate sector. In contrast, even within the corporate sector, advertising is preferred by lesbian and gay workers. Some of the Sri Lankan corporate sector organizations, especially multinational organizations, have initiated diversity training, and it might lead to making these organisations lesbian and gay-friendly workplaces in the future. It is also found that nearly 44 percent of the participants do not have a religion, and it is due to the rejection of deviant behaviours by most of the religions. In conclusion, lesbian and gay workers experience discrimination at work in the Sri Lankan corporate sector with an exception to the companies relating to advertising and non-governmental organisations is the sector that these workers prefer the most.

Keywords: lesbian workers, gay workers, Sri Lankan corporate sector, discrimination

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Authors: Sher Mohammed, Purushottam Lal, Pawan K. Kasera

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The Thar Desert of Rajasthan covers a wide geographical area spreading between 23.3° to 30.12°, North latitude and 69.3◦ to 76◦ Eastern latitudes; having a unique spectrum of arid zone vegetation. This desert is spreading over 12 districts having a rich source of economically important/threatened plant diversity interacting and growing with adverse climatic conditions of the area. Due to variable geological, physiographic, climatic, edaphic and biotic factors, the arid zone medicinal flora exhibit a wide collection of angiosperm families. The herbal diversity of this arid region is medicinally important in household remedies among tribal communities as well as in traditional systems. The on-going increasing disturbances in natural ecosystems are due to climatic and biological, including anthropogenic factors. The unique flora and subsequently dependent faunal diversity of the desert ecosystem is losing its biotic potential. A large number of plants have no future unless immediate steps are taken to arrest the causes, leading to their biological improvement. At present the potential loss in ecological amplitude of various genera and species is making several plant species as red listed plants of arid zone vegetation such as Commmiphora wightii, Tribulus rajasthanensis, Calligonum polygonoides, Ephedra foliata, Leptadenia reticulata, Tecomella undulata, Blepharis sindica, Peganum harmala, Sarcostoma vinimale, etc. Mostly arid zone species are under serious pressure against prevailing ecosystem factors to continuation their life cycles. Genetic, molecular, cytological, biochemical, metabolic, reproductive, germination etc. are the several points where the floral diversity of the arid zone area is facing severe ecological influences. So, there is an urgent need to conserve them. There are several opportunities in the field to carry out remarkable work at particular levels to protect the native plants in their natural habitat instead of only their in vitro multiplication.

Keywords: ecology, evaluation, xerophytes, economically, threatened plants, conservation

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Authors: Seyran Naghdi

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Background: Orphan drug development is limited by very high costs attributed to the research and development and small size market. How health policymakers address this challenge to consider both supply and demand sides need to be explored for directing the policies and plans in the right way. The price is an important signal for pharmaceutical companies’ profitability and the patients’ accessibility as well. Objective: This study aims to find out the orphan drugs' price-setting patterns and approaches in health systems through a systematic review of the available evidence. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) approach was used. MedLine, Embase, and Web of Sciences were searched via appropriate search strategies. Through Medical Subject Headings (MeSH), the appropriate terms for pricing were 'cost and cost analysis', and it was 'orphan drug production', and 'orphan drug', for orphan drugs. The critical appraisal was performed by the Joanna-Briggs tool. A Cochrane data extraction form was used to obtain the data about the studies' characteristics, results, and conclusions. Results: Totally, 1,197 records were found. It included 640 hits from Embase, 327 from Web of Sciences, and 230 MedLine. After removing the duplicates, 1,056 studies remained. Of them, 924 studies were removed in the primary screening phase. Of them, 26 studies were included for data extraction. The majority of the studies (>75%) are from developed countries, among them, approximately 80% of the studies are from European countries. Approximately 85% of evidence has been produced in the recent decade. Conclusions: There is a huge variation of price-setting among countries, and this is related to the specific pharmacological market structure and the thresholds that governments want to intervene in the process of pricing. On the other hand, there is some evidence on the availability of spaces to reduce the very high costs of orphan drugs development through an early agreement between pharmacological firms and governments. Further studies need to focus on how the governments could incentivize the companies to agree on providing the drugs at lower prices.

Keywords: orphan drugs, orphan drug production, pricing, costs, cost analysis

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Authors: Rashmi Gupta

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Rewarding stimuli capture attention involuntarily as a result of an association process that develops quickly during value learning, referred to as the reward or value-driven attentional capture. It is essential to compare reward with punishment processing to get a full picture of value-based modulation in visual attention processing. Hence, the present study manipulated both valence/value (reward as well as punishment) and motivational salience (probability of an outcome: high vs. low) together. Series of experiments were conducted, and there were two phases in each experiment. In phase 1, participants were required to learn to associate specific face stimuli with a high or low probability of winning or losing points. In the second phase, these conditioned stimuli then served as a distractor or prime in a speeded letter search task. Faces with high versus low outcome probability, regardless of valence, slowed the search for targets (specifically the left visual field target) and suggesting that the costs to performance on non-emotional cognitive tasks were only driven by motivational salience (high vs. loss) associated with the stimuli rather than the valence (gain vs. loss). It also suggests that the processing of motivationally salient stimuli is right-hemisphere biased. Together, results of these studies strengthen the notion that our visual attention system is more sensitive to affected by motivational saliency rather than valence, which termed here as motivational-driven attentional capture.

Keywords: attention, distractors, motivational salience, valence

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Authors: Hilal Al Shamsi, Abdullah Almutairi

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Introduction: As primary healthcare centres play an important role in implementing Saudi Arabia’s health strategy, this paper offers a review of publications on the quality of the country’s primary health care. With the aim of deciding on solutions for improvement, it provides an overview of healthcare quality in this context and indicates barriers to quality. Method: Using two databases, ProQuest and Scopus, data extracted from published articles were systematically analysed for determining the care quality in Saudi primary health centres and obstacles to achieving higher quality. Results: Twenty-six articles met the criteria for inclusion in this review. The components of healthcare quality were examined in terms of the access to and effectiveness of interpersonal and clinical care. Good access and effective care were identified in such areas as maternal health care and the control of epidemic diseases, whereas poor access and effectiveness of care were shown for chronic disease management programmes, referral patterns (in terms of referral letters and feedback reports), health education and interpersonal care (in terms of language barriers). Several factors were identified as barriers to high-quality care. These included problems with evidence-based practice implementation, professional development, the use of referrals to secondary care and organisational culture. Successful improvements have been implemented by other systems, such as mobile medical units, electronic referrals, online translation tools and mobile devices and their applications; these can be implemented in Saudi Arabia for improving the quality of the primary healthcare system in this country. Conclusion: The quality of primary health care in Saudi Arabia varies among the different services. To improve quality, management programmes and organisational culture must be promoted in primary health care. Professional development strategies are also needed for improving the skills and knowledge of healthcare professionals. Potential improvements can be implemented to improve the quality of the primary health system.

Keywords: quality, primary health care, Saudi Arabia, health centres, general medical

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Authors: Baohua Yu

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In line with wider tends in the expansion of international student mobility, the number of international higher degree research students has grown at a significant rate in recent years. In particular, Australia has become a hub for attracting international higher degree research students from around the world. However, research has identified that international higher degree research students often encounter a wide range of academic and socio-cultural challenges in adapting to their new environment. Moreover, this can have a significant bearing on their levels of satisfaction with their studies. This paper outlines the findings of a mixed method study exploring the experiences and perceptions of international higher degree research students in Australia. Findings revealed that IRHD students’ overall and academic satisfaction in Australia were highly related to each other, and they were strongly influenced by their learning and research, moderately influenced by co-national support and intercultural contact ability. Socio-cultural satisfaction seemed to belong to a different domain from academic satisfaction because it was explained by a different set of variables such as living and adaptation and intercultural contact ability. In addition, the most important issues in terms of satisfaction were not directly related to academic studies. Instead, factors such as integration into the community, interacting with other students, relationships with supervisors, and the provision of adequate desk space were often given the greatest weight. Implications for how university policy can better support international doctoral students are discussed.

Keywords: international higher degree research students, academic adaptation, socio-cultural adaptation, student satisfaction

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Authors: Renee Moten

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Introduction: Knee pain becomes chronic because the therapy used focuses only on the symptoms of knee pain and not the causes of knee pain. Preventing knee injuries is not in the toolbox of the traditional practitioner. This research was done to show that we must reduce the inflammation (holistically), reduce the swelling and regain flexibility before considering any type of exercise. This method of performing the correct exercise stops the bowing of the knee, corrects the walking gait, and starts to relieve knee, hip, back, and shoulder pain. Method: The holistic method that is used to heal knees is called the Knee Pain Recipe. It’s a six step system that only uses alternative medicine methods to reduce, relieve and restore knee joint mobility. The system is low cost, with no hospital bills, no physical therapy, and no painkillers that can cause damage to the kidneys and liver. This method has been tested on 200 women with knee, back, hip, and shoulder pain. Results: All 200 women reduce their knee pain by 50%, some by as much as 90%. Learning about ankle and foot flexibility, along with understanding the kinetic chain, helps improve the walking gait, which takes the pressure off the knee, hip and back. The knee pain recipe also has helped to reduce the need for a cortisone injection, stem cell procedures, to take painkillers, and surgeries. What has also been noted in the research was that if the women's knees were too far gone, the Knee Pain Recipe helped prepare the women for knee replacement surgery. Conclusion: It is believed that the Knee Pain Recipe, when performed by men and women from around the world, will give them a holistic alternative to drugs, injections, and surgeries.

Keywords: knee, surgery, healing, holistic

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Authors: Kamila Troper, Pedro Mestre, Maria Lurdes Menano, Joana Mendonça, Maria João Costa, Sandra Demel

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Introduction: Visual impairment is a problem that has an influence on hundreds of thousands of people all over the world. Although it is possible for a Visually Impaired person to do most jobs, the right training, technological assistance, and emotional support are essential. Ergonomics be able to solve many of the problems/issues with the relative ease of positioning, lighting and design of the workplace. A little forethought can make a tremendous difference to the ease with which a person with an impairment function. Objectives: Review the main ergonomic adaptation measures reported in the literature in order to promote better working conditions and safety measures for the visually impaired. Methodology: This was an exploratory-descriptive, qualitative literature systematic review study. The main databases used were: PubMed, BIREME, LILACS, with articles and studies published between 2000 and 2021. Results: Based on the principles of the theoretical references of ergonomic analysis of work, the main restructuring of the physical space of the workstations were: Accessibility facilities and assistive technologies; A screen reader that captures information from a computer and sends it in real-time to a speech synthesizer or Braille terminal; Installations of software with voice recognition, Monitors with enlarged screens; Magnification software; Adequate lighting, magnifying lenses in addition to recommendations regarding signage and clearance of the places where the visually impaired pass through. Conclusions: Employability rates for people with visual impairments(both those who are blind and those who have low vision)are low and continue to be a concern to the world and for researchers as a topic of international interest. Although numerous authors have identified barriers to employment and proposed strategies to remediate or circumvent those barriers, people with visual impairments continue to experience high rates of unemployment.

Keywords: ergonomic adaptations, visual impairments, ergonomic analysis of work, systematic review

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Authors: Vaiddehi Bansal, Ridhi Sahai, Kareem Kysia

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Overseas labor migration is currently one of the most important contributors to the economy of Bangladesh and is a highly profitable form of labor for Gulf Cooperative Council (GCC) countries. In 2019, 700,159 migrant workers from Bangladeshtraveled abroad for employment. GCC countries are a major destination for Bangladeshi migrant workers, with Saudi Arabia being the most common destination for Bangladeshi migrant workers since 2016. Despite the high rate of migration between these countries every year, the OLR industry remains complex and often leaves migrants susceptible to human trafficking, forced labor, and modern slavery. While the prevalence of forced labor among Bangladeshi migrants in GCC countries is still unknown, the IOM estimates international migrant workers comprise one fourth of the victims of forced labor. Moreover, the onset of the global COVID-19 pandemic has exposed migrant workers to additional adverse situations, making them even more vulnerable to forced labor and health risks. This paper presents findings from a rapid assessment of the impacts of COVID-19 on OLR in Bangladesh, with an emphasis on the increased risk of forced labor among vulnerable migrant worker populations, particularly women.Rapid reviews are a useful approach to swiftly provide actionable evidence for informed decision-making during emergencies, such as the COVID-19 pandemic. The research team conducted semi-structured key information interviews (KIIs) with a range of stakeholders, including government officials, local NGOs, international organizations, migration researchers, and formal and informal recruiting agencies, to obtain insights on the multi-facted impacts of COVID-19 on the OLR sector. The research team also conducted a comprehensive review of available resources, including media articles, blogs, policy briefs, reports, white papers, and other online content, to triangulate findings from the KIIs. After screening for inclusion criteria, a total of 110 grey literature documents were included in the review. A total of 31 KIIs were conducted, data from which was transcribed and translated from Bangla to English, andanalyzed using a detailed codebook. Findings indicate that there was limited reintegration support for returnee migrants. Facing increasing amounts of debt, financial insecurity, and social discrimination, returnee migrants, were extremely vulnerable to forced labor and exploitation. Growing financial debt and limited job opportunities in their home country will likely push migrants to resort to unsafe migration channels. Evidence suggests that women, who are primarily domestic works in GCC countries, were exposed to increased risk of forced labor and workplace violence. Due to stay-at-home measures, women migrant workers were tasked with additional housekeeping working and subjected to longer work hours, wage withholding, and physical abuse. In Bangladesh, returnee women migrant workers also faced an increased risk of domestic violence.

Keywords: forced labor, migration, gender, human trafficking

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Authors: Samrawit Tamrat Gebretsadik

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Recurrent wheezing is a common respiratory symptom among children, often indicative of underlying airway inflammation and hyperreactivity. Understanding the prevalence and associated factors of recurrent wheezing in specific age groups is crucial for targeted interventions and improved respiratory health outcomes. This study aimed to investigate the prevalence and associated factors of recurrent wheezing among 6-year-old children attending Adama Comprehensive Specialized Hospital Medical College in Ethiopia. A cross-sectional study design was employed, involving structured interviews with parents/guardians, medical records review, and clinical examination of children. Data on demographic characteristics, environmental exposures, family history of respiratory diseases, and socioeconomic status were collected. Logistic regression analysis was used to identify factors associated with recurrent wheezing. The study included X 6-year-old children, with a prevalence of recurrent wheezing found to be Y%. Environmental exposures, including tobacco smoke exposure (OR = Z, 95% CI: X-Y), indoor air pollution (OR = Z, 95% CI: X-Y), and presence of pets at home (OR = Z, 95% CI: X-Y), were identified as significant risk factors for recurrent wheezing. Additionally, a family history of asthma or allergies (OR = Z, 95% CI: X-Y) and low socioeconomic status (OR = Z, 95% CI: X-Y) were associated with an increased likelihood of recurrent wheezing. The impact of recurrent wheezing on the quality of life of affected children and their families was also assessed. Children with recurrent wheezing experienced a higher frequency of respiratory symptoms, increased healthcare utilization, and decreased physical activity compared to their non-wheezing counterparts. In conclusion, recurrent wheezing among 6-year-old children attending Adama Comprehensive Specialized Hospital Medical College is associated with various environmental, genetic, and socioeconomic factors. These findings underscore the importance of targeted interventions aimed at reducing exposure to known triggers and improving respiratory health outcomes in this population. Future research should focus on longitudinal studies to further elucidate the causal relationships between risk factors and recurrent wheezing and evaluate the effectiveness of preventive strategies.

Keywords: wheezing, inflammation, respiratory, crucial

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Authors: Fabianna Bacil, Zenathan Hasannundin, Clovis Freire

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The green transition opens green windows of opportunity – temporary moments in which there are lower barriers and shorter learning periods for developing countries to enter emerging technologies and catch-up. However, taking advantage of these windows requires capabilities in national sectoral systems to adopt and develop technologies linked to green sectors as well as strong responses to build the required knowledge, skills, and infrastructure and foster the growth of targeted sectors. This paper uses UNCTAD’s frontier technology readiness index to analyse the current position of Latin America and the Caribbean to use, adopt, and adapt frontier technologies, examining the preconditions in the region to take up windows of opportunity that arise with the green transition. The index highlights the inequality across countries in the region, as well as gaps in capabilities dimensions, especially in terms of R&D. Moving to responses, it highlights industrial policies implemented to foster the growth of green technologies, emphasising the essential role played by the state to build and strengthen capabilities and provide infant industry protection that enables the growth of these sectors. Overall, while there are exceptions, especially in the Brazilian case, countries in Latin America and the Caribbean should focus on strengthening their capabilities to be better positioned, especially in terms of knowledge creation, infrastructure, and financing availability.

Keywords: Green technologies, Industrial policy, Latin America, windows of opportunity

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Authors: Jae-Hyuk Hyun, Dong-Sung Bae, Jea-Sun Lee

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The COVID-19 pandemic emphasized the benefits of natural green space on mental health in pandemic situations. The effects of greenspace on reducing mental health disorder are detected, but limitations impede highlighting the overall effectiveness of greenspace on mental health to be valid and significant. Therefore, this study aims to comprehensively and quantitatively analyze the effectiveness and significance of greenspace in reducing mental disorders after the COVID-19 outbreak. This study adopted a systematic review to select adequate, necessary studies with significant associations between greenspace and mental health after COVID-19. Meta-analysis is performed using the selected studies for calculating and analyzing the combined effect size of greenspace on reducing mental disorder, difference of effect size in various factors of greenspace or mental health, and variables’ effects on greenspace or mental health. Also, a correlation test using MQRS and effect size is performed to determine significant correlations of factors in greenspace and mental health. The analysis confirmed the combined effect size of the association between greenspace and mental health to be interpreted as large enough (medium effect size, 0.565). Various factors consisting of greenspace or mental health had considerable effect sizes, with heterogeneity existing between studies of different greenspace and mental health aspects (subgroups). A significant correlation between factors in greenspace and mental health was identified, with correlations satisfying both reliability and effectiveness used for suggesting necessary greenspace policies with mental health benefits during the pandemic situation. Different variables of the study period, female proportion, and mean age significantly affected certain factors of greenspace or mental health, while the increase in effects of greenspace on mental health was detected as the COVID-19 period continued. Also, the regional heterogeneity of effects on the association between greenspace and mental health is recognized in all factors consisting of greenspace and mental health except for the visitation of greenspace. In conclusion, valid and significant effects were detected in various associations between greenspace and mental health. Based on the results of this study, conducting elaborate research and establishing adequate and necessary greenspace policies and strategies are recommended to effectively benefit the mental health of citizens in future pandemic situations.

Keywords: greenspace, natural environment, mental health, mental disorder, COVID-19, pandemic, systematic review, meta-analysis

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Vincent Mokoka, Kai Behn, Edwin Mudongo, Jan Ruppert, Kingsley Ayisi, Anja Linstädter

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Severe drought may trigger a transition of vegetation composition in dryland grasslands, with productive perennial grasses often being replaced by annual grasses. Grazing pressure is thought to exacerbate drought effects, but little is known on the joint effects of grazing and drought on the functional and taxonomic composition of the herbaceous vegetation in African savannas. This study thus aimed to elucidate which herbaceous species and plant functional types (PFTs) are most resistant to prolonged drought and grazing and whether resting plays a role in this context. Thus, we performed a six-year field experiment in South Africa’s Limpopo province, combining drought and grazing treatments. Aboveground herbaceous biomass was harvested annually and separated into species. We grouped species into five PFTs, i.e. very broad-leaved perennial grasses, broad-leaved perennial grasses, narrow-leaved perennial grasses, annual grasses, and forbs. For all species, we also recorded three-leaf traits (leaf area - LA, specific leaf area – SLA, and leaf dry matter content – LDM) to describe their resource acquisition strategies. We used generalized linear models to test for treatment effects and their interaction. Association indices were used to detect the relationship between species and treatments. We found that there were no absolute winner species or PFTs, as the six-year severe drought had a pronounced negative impact on the biomass production of all species and PFTs. However, we detected relative winners with increases in relative abundances, mainly forbs and less palatable narrow-leafed grasses with comparatively low LA and high LDMC, such as Aristida stipidata Hack. These species and PFTs also tended to be favored by grazing. Although few species profited from resting, for most species, the combination of drought and resting proved to be particularly unfavorable. Winners and losers can indicate ecological transition and may be used to guide management decisions.

Keywords: aboveground net primary production, drought, functional diversity, winner and loser species

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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