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International Journal of Integrative Research (IJIR)
Published by MULTITECH PUBLISHER
ISSN : -     EISSN : 29882184     DOI : https://doi.org/10.59890/ijir.v1i6
Core Subject : Economy, Health, Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions
The International Journal of Integrative Research (IJIR) is published by the Multitech Publisher. IJIR provides a supportive environment for multidisciplinary researchers to publish their contributions to the academy of knowledge and wisdom. The Focus of the journal is on multidisciplinary research which should cover at least two distinct disciplines that aim to solve a real-life problem that contributes to the development of knowledge and wisdom.
Arjuna Subject : Umum - Umum
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 4 (2023): April 2023" : 5 Documents clear
Integrating Menstrual Health Rehan Naqvi
International Journal of Integrative Research Vol. 1 No. 4 (2023): April 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (446.435 KB) | DOI: 10.59890/ijir.v1i4.44

Abstract

Menstruation is a natural and important part of the reproductive cycle, approximately half of the human population has or will experience it. Menstrual health (MH) is an integral part of sexual and reproductive health. Yet shame, stigma and misinformation around the menstrual life cycle undermine the well-being of women, girls, and people who menstruate, leaving them vulnerable to gender-based discrimination, child marriage, exclusion, violence, poverty, and untreated health problems. The Covid-19 pandemic has disrupted health delivery systems on a scale that has ushered in a new world. An estimated 1.8 billion women, girls, and gender non-binary people menstruate despite lockdown, restrictions on social mobility, stock outs, supply chain disruptions, lack of essential menstrual supplies, safe access to bathrooms, soap, water, and privacy. One in ten women in Africa skipped school when they menstruated, and too many girls struggled with chronic poverty. The year 2020 brought unprecedented disruption and change due to the COVID-19 pandemic, impacting various aspects of people's lives worldwide, including MH management. Despite these circumstances, an estimated 1.8 billion menstruating individuals faced difficulties in accessing essential menstrual supplies, safe facilities, and basic hygiene resources like soap and water. This lack of access has particularly affected girls' education and perpetuated chronic poverty.
Mechanized Rice Cultivation Through Smart Farming Using Artificial Intelligence Basis of Rice Farmers in Bongabong, Oriental Mindoro Saguid John Rex; Valdez Kaycee; Magbanua Jonnel; Villaluna Vinz Philip; Nicko A. Magnaye; Jesselle P. Atienza
International Journal of Integrative Research Vol. 1 No. 4 (2023): April 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (404.01 KB) | DOI: 10.59890/ijir.v1i4.52

Abstract

Mechanized rice cultivation through smart farming using artificial intelligence (AI) has gained considerable interest as a means to improve agricultural practices and increase productivity. This study focuses on the application of smart farming technology in Bongabong, Oriental Mindoro, Philippines, with the aim of optimizing rice production. Data were collected through self-administered questionnaires, and statistical analyses using descriptive and inferential statistics were conducted. The findings indicate a gender imbalance among farmers utilizing smart farming technologies, with a higher representation of males. The study identified challenges in terms of limited trained operators, inadequate infrastructure and support facilities, high operational costs, and market limitations. The study also highlighted the environmental implications of smart farming technology, such as improved water management, reduced chemical inputs, and enhanced soil health. Overall, the study underscores the importance of education, training, and collaborative efforts to promote the adoption of smart farming technology in rice cultivation. By leveraging AI and innovative farming techniques, rice farmers in Bongabong, Oriental Mindoro can enhance productivity, sustainability, and economic outcomes.
Endocrine Disorders that Cause Diabetes Rehan Naqvi
International Journal of Integrative Research Vol. 1 No. 4 (2023): April 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (621.774 KB) | DOI: 10.59890/ijir.v1i4.55

Abstract

Endocrine disorders are a scientific group of conditions that affect the day-to-day functioning of the endocrine system, which is responsible for producing and regulating hormones in the body. Many endocrine problems can lead to the development of diabetes, a metabolic disorder characterized by persistently high blood sugar levels. Excess cortisol can cause insulin resistance, which causes an increase in blood sugar levels, and eventually leads to diabetes. Another disease is acromegaly which is caused by an overproduction of increased hormones. An extended hormone boom stage can lead to insulin resistance in the long term, contributing to an increase in diabetes. Polycystic ovary syndrome (PCOS) is an endocrine disease commonly associated with insulin resistance and diabetes. PCOS is characterized by an imbalance of hormones, especially androgens. This imbalance can impair insulin signaling, especially insulin resistance, and the subsequent development of diabetes. Hypothyroidism, which is characterized by low thyroid hormone levels, can lead to insulin resistance and impaired insulin secretion. In contrast, hyperthyroidism, which is characterized by overproduction of thyroid hormone, can increase glucose metabolism and lead to diabetes in susceptible individuals. In addition, tumors of the endocrine system, including insulinomas and glucagonomas, can cause atypical insulin production and release, leading to hypoglycemia and hyperglycemia, respectively.
Causes of Sectarian Extremism in Pakistan: an EMIC Prospective of Religious Scholars Hafiz ur Rehman; Huma Razaq Abbas; Aisha Tahir
International Journal of Integrative Research Vol. 1 No. 4 (2023): April 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (570.227 KB) | DOI: 10.59890/ijir.v1i4.59

Abstract

The purpose for present study is to investigate the reasons of extremism and sectarianism. The Qualitative research design was used to conduct the study. The semi-structured interview guideline was used for data collection. An In-depth analysis of data was done through thematic analysis by [1]. The sample of participants (N=8), male (n=7) & female (n=1) were selected through purposive sampling from different sect scholars. The interview guideline caters the domains opinion about sectarianism, reasons of sectarianism, why Pakistan is unsuccessful to stop it, role of religious extremism in sectarianism, what preventive measures should be taken, role of human cognitions. Further in depth analysis revealed that there are different Islamic views, division of groups, propaganda, lack of faith, use of power, conflicts, cognitions, following the schools of thoughts and force against Islam regarding opinion of sectarianism and the reasons behind the sectarianism are invasion of external factors, lack of control, misuse of religion, emotional propaganda, political influence etc. Results shows revealed that there is positive, negative and neutral opinion about sectarianism like Islamic view, and division of groups.
A New Approach to Most Advanced Technique for Data Mining of the Big Data pooja sharma; B.D. K. Patro
International Journal of Integrative Research Vol. 1 No. 4 (2023): April 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (475.554 KB) | DOI: 10.59890/ijir.v1i4.60

Abstract

Big data mining and analysis requires novel and improved techniques so that mixed types of data can be processed efficiently and effectively. Cluster, factor, regression, crowd-sourcing, and classification analysis are the main methods used in Big data. In the present research work, Big data storage, traditional data mining, Big data mining, Social recommendation, Scalable social recommendation and social recommendation improvement using deep learning are analyzed. The issues such as scalability, sparsity, cold start, data variety etc. are addressed by proposed approaches. 

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