Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.1197
Vanisri. M, Sreesivasakthi. A, MuthuKaviya. M, Roja Jayashankar, Salai Dhivyathai. N, Rajaganapathy. K, Srinivasan.R
Exploring innovative ways to accelerate drug repurposing through in-silico molecular modeling techniques, tools, and databases is paramount in modern pharmaceutical research. Exploring the vast landscape of drug repurposing presents both a challenge and an opportunity in the realm of pharmaceutical research. With the escalating costs and time-consuming nature of developing new drugs from scratch, the urgency to identify novel therapeutic uses for existing compounds has never been more pressing. Readers can expect a detailed exploration of how computational methods are revolutionizing drug repurposing efforts, offering insights into accelerated drug discovery and development timelines. This comprehensive review dives deep into the opportunities and challenges of leveraging computational approaches to identify new therapeutic uses for existing drugs and this article highlights the potential of in-silico methods to revolutionize drug discovery by repurposing existing compounds efficiently and cost-effectively, ultimately leading to faster development timelines and improved patient outcomes and will be focused for In-silico molecular modeling techniques, tools, and databases as powerful allies in expediting this crucial process.
{"title":"Accelerate drug repurposing with in-silico molecular modelling techniques, tools and databases: A comprehensive review","authors":"Vanisri. M, Sreesivasakthi. A, MuthuKaviya. M, Roja Jayashankar, Salai Dhivyathai. N, Rajaganapathy. K, Srinivasan.R","doi":"10.30574/ijsra.2024.12.2.1197","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1197","url":null,"abstract":"Exploring innovative ways to accelerate drug repurposing through in-silico molecular modeling techniques, tools, and databases is paramount in modern pharmaceutical research. Exploring the vast landscape of drug repurposing presents both a challenge and an opportunity in the realm of pharmaceutical research. With the escalating costs and time-consuming nature of developing new drugs from scratch, the urgency to identify novel therapeutic uses for existing compounds has never been more pressing. Readers can expect a detailed exploration of how computational methods are revolutionizing drug repurposing efforts, offering insights into accelerated drug discovery and development timelines. This comprehensive review dives deep into the opportunities and challenges of leveraging computational approaches to identify new therapeutic uses for existing drugs and this article highlights the potential of in-silico methods to revolutionize drug discovery by repurposing existing compounds efficiently and cost-effectively, ultimately leading to faster development timelines and improved patient outcomes and will be focused for In-silico molecular modeling techniques, tools, and databases as powerful allies in expediting this crucial process.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"9 37","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.1251
I Ketut Ginantra, I Ketut Muksin, Martin Joni
The coastal mangroves of Perancak Jembrana Village cover an area of around 177.09 hectares, some of the area (around 10 ha) has been developed into a tourist attraction. The tourism being developed is ecotourism based on ecology, biodiversity, conservation of natural resources, environmental education and economic empowerment of local communities. The aim of the research is to identify and describe the diversity of mangrove flora. Analysis of mangrove vegetation uses the square method, the parameters determined are the number of individuals of each species, the area of canopy cover for each species and the frequency of presence. Diversity was calculated with the Shanon-Wiener index. The research results showed that in the Perancak ecotourism area, 25 mangrove flora were found, consisting of 16 species of true mangrove flora and nine species of associated mangroves. The species that dominate are Rhizophora mucronata (important value 52.63), Rhizophora apiculata (important value 31.93), Avicennia marina (28.70), Rhizophora stylosa (important value 24.81), Avicennia officinalis (important value 17, 73) and Sonneratia alba (important value 16.39). The diversity index (H) is 2.89 and the species evenness index is 0.90. Species diversity in mengrove vegetation with a diversity index >1 and evenness approaching 1 means that the condition of the Perancak mangrove is in the stable/good category. Interpretation of the diversity of mangrove flora, habitus characteristics, fruit morphology, root types, typical substrate types is an interesting attraction for ecotourism activities.
{"title":"Mangrove flora as an ecotourism attraction in the Perancak Mangrove, Jembrana Bali","authors":"I Ketut Ginantra, I Ketut Muksin, Martin Joni","doi":"10.30574/ijsra.2024.12.2.1251","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1251","url":null,"abstract":"The coastal mangroves of Perancak Jembrana Village cover an area of around 177.09 hectares, some of the area (around 10 ha) has been developed into a tourist attraction. The tourism being developed is ecotourism based on ecology, biodiversity, conservation of natural resources, environmental education and economic empowerment of local communities. The aim of the research is to identify and describe the diversity of mangrove flora. Analysis of mangrove vegetation uses the square method, the parameters determined are the number of individuals of each species, the area of canopy cover for each species and the frequency of presence. Diversity was calculated with the Shanon-Wiener index. The research results showed that in the Perancak ecotourism area, 25 mangrove flora were found, consisting of 16 species of true mangrove flora and nine species of associated mangroves. The species that dominate are Rhizophora mucronata (important value 52.63), Rhizophora apiculata (important value 31.93), Avicennia marina (28.70), Rhizophora stylosa (important value 24.81), Avicennia officinalis (important value 17, 73) and Sonneratia alba (important value 16.39). The diversity index (H) is 2.89 and the species evenness index is 0.90. Species diversity in mengrove vegetation with a diversity index >1 and evenness approaching 1 means that the condition of the Perancak mangrove is in the stable/good category. Interpretation of the diversity of mangrove flora, habitus characteristics, fruit morphology, root types, typical substrate types is an interesting attraction for ecotourism activities.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The widespread utilization of AI tools such as ChatGPT has become increasingly prevalent among learners, posing a threat to academic integrity. This study seeks to evaluate capability and efficiency of AI detection tools in distinguishing between human-authored and AI-generated works. Three-paragraph works on “AutoCAD and Architecture” were generated through ChatGPT, and three human-written works were subjected to evaluation. AI detection tools such as GPTZero, Copyleaks and Writer AI were used to evaluate these paragraphs. Parameters such as “Human/Human Text/Human Generated Text” and “AI/AI Content Detected” were used to evaluate the performance of the three AI detection tools in evaluating outputs. Findings indicate that GPT Zero and Copyleaks have higher reliability in determining human-authored work and AI generated work while Writer AI showed a notable content classification of “Human Generated Content” on all tested outputs showing less sensitivity on determining human-authored work and AI generated work. Findings indicate that the use of Artificial Intelligence as an AI detection tool should be accompanied with thorough validation and cross-referencing of results.
人工智能工具（如 ChatGPT）在学习者中的广泛使用日益普遍，对学术诚信构成了威胁。本研究旨在评估人工智能检测工具在区分人类撰写的作品和人工智能生成的作品方面的能力和效率。通过 ChatGPT 生成了三段关于 "AutoCAD 与建筑 "的作品，并对三段人类撰写的作品进行了评估。使用 GPTZero、Copyleaks 和 Writer AI 等人工智能检测工具对这些段落进行评估。使用 "人类/人类文本/人类生成文本 "和 "检测到的人工智能/人工智能内容 "等参数来评估三种人工智能检测工具在评估输出方面的性能。结果表明，GPT Zero 和 Copyleaks 在确定人类撰写的作品和人工智能生成的作品方面具有更高的可靠性，而 Writer AI 在所有测试输出中显示出显著的 "人类生成内容 "内容分类，在确定人类撰写的作品和人工智能生成的作品方面显示出较低的灵敏度。研究结果表明，在使用人工智能作为人工智能检测工具的同时，还应对结果进行彻底验证和交叉引用。
{"title":"Comparing ai detectors: evaluating performance and efficiency","authors":"Jeremie Busio Legaspi, Roan Joyce Ohoy Licuben, Emmanuel Alegado Legaspi, Joven Aguinaldo Tolentino","doi":"10.30574/ijsra.2024.12.2.1276","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1276","url":null,"abstract":"The widespread utilization of AI tools such as ChatGPT has become increasingly prevalent among learners, posing a threat to academic integrity. This study seeks to evaluate capability and efficiency of AI detection tools in distinguishing between human-authored and AI-generated works. Three-paragraph works on “AutoCAD and Architecture” were generated through ChatGPT, and three human-written works were subjected to evaluation. AI detection tools such as GPTZero, Copyleaks and Writer AI were used to evaluate these paragraphs. Parameters such as “Human/Human Text/Human Generated Text” and “AI/AI Content Detected” were used to evaluate the performance of the three AI detection tools in evaluating outputs. Findings indicate that GPT Zero and Copyleaks have higher reliability in determining human-authored work and AI generated work while Writer AI showed a notable content classification of “Human Generated Content” on all tested outputs showing less sensitivity on determining human-authored work and AI generated work. Findings indicate that the use of Artificial Intelligence as an AI detection tool should be accompanied with thorough validation and cross-referencing of results.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"1 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.1237
S. Kalaivanan, S. Showbharnikhaa, T. Thenmozhi, S. Preethi, A. Ayisha Siddiqkha, A. Hema Malini, K. Rajaganapathy, R. Srinivasan
Targeting High Mobility Group Box 1 (HMGB1) in rheumatoid arthritis (RA) holds promise for mitigating inflammation and joint damage. This paper comprehensively overviews In Vitro and In Vivo screening methods for HMGB1 targeting in RA. In Vitro, assays include cell-based assays, ELISA, and Western blotting to assess HMGB1 release, receptor activation, and downstream signalling pathways. In Vivo, models such as collagen-induced arthritis (CIA) in mice and adjuvant-induced arthritis (AIA) in rats mimic RA pathogenesis and enable evaluation of HMGB1 inhibitors' efficacy, safety, and pharmacokinetics. Advanced imaging technologies, including PET and MRI, allow non-invasive visualization of HMGB1 expression In Vivo. Biomarker analyses complement screening methods by correlating HMGB1 levels with disease activity and treatment response. Integration of these screening methods facilitates the development of HMGB1-targeted therapies with the potential to transform RA management. In this review we proposed certain In-vitro and In-vivo screening methods for RA.
靶向类风湿性关节炎（RA）中的高迁移率组框 1（HMGB1）有望减轻炎症和关节损伤。本文全面概述了针对类风湿性关节炎 HMGB1 的体外和体内筛选方法。体外检测包括细胞检测、ELISA 和 Western 印迹法，以评估 HMGB1 的释放、受体激活和下游信号通路。体内，小鼠胶原诱导性关节炎（CIA）和大鼠佐剂诱导性关节炎（AIA）等模型模拟了 RA 的发病机制，可评估 HMGB1 抑制剂的疗效、安全性和药代动力学。包括正电子发射计算机断层显像（PET）和核磁共振成像（MRI）在内的先进成像技术可以对体内 HMGB1 的表达进行无创观察。生物标志物分析可将 HMGB1 水平与疾病活动和治疗反应相关联，从而对筛选方法起到补充作用。整合这些筛查方法有助于开发 HMGB1 靶向疗法，从而有可能改变 RA 的治疗方法。在本综述中，我们提出了一些针对 RA 的体外和体内筛查方法。
{"title":"In-vitro and In-vivo screening methods for targeting HMBG1 in RA: A comprehensive overview","authors":"S. Kalaivanan, S. Showbharnikhaa, T. Thenmozhi, S. Preethi, A. Ayisha Siddiqkha, A. Hema Malini, K. Rajaganapathy, R. Srinivasan","doi":"10.30574/ijsra.2024.12.2.1237","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1237","url":null,"abstract":"Targeting High Mobility Group Box 1 (HMGB1) in rheumatoid arthritis (RA) holds promise for mitigating inflammation and joint damage. This paper comprehensively overviews In Vitro and In Vivo screening methods for HMGB1 targeting in RA. In Vitro, assays include cell-based assays, ELISA, and Western blotting to assess HMGB1 release, receptor activation, and downstream signalling pathways. In Vivo, models such as collagen-induced arthritis (CIA) in mice and adjuvant-induced arthritis (AIA) in rats mimic RA pathogenesis and enable evaluation of HMGB1 inhibitors' efficacy, safety, and pharmacokinetics. Advanced imaging technologies, including PET and MRI, allow non-invasive visualization of HMGB1 expression In Vivo. Biomarker analyses complement screening methods by correlating HMGB1 levels with disease activity and treatment response. Integration of these screening methods facilitates the development of HMGB1-targeted therapies with the potential to transform RA management. In this review we proposed certain In-vitro and In-vivo screening methods for RA.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"10 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.1247
Wenpeng Zhan
The aim of this study is to investigate how psychological capital can predict athletic achievement among Taekwondo athletes. Data was collected using the psychological capital questionnaire and the athletic achievement scale through a survey of Taekwondo athletes. A total of 421 valid responses were collected with a response rate of 81.7%. The data was analyzed using SEM-PLS. The results show that the psychological capital dimensions of self-efficacy, hope, resilience, and optimism have a significant impact on the athletic achievement of Taekwondo athletes. Among these dimensions, self-efficacy has the greatest impact on athletic achievement, while optimism has the least influence. Overall, psychological capital accounts for 79.6% of the variance in athletic achievement. Based on these results, the study suggests several recommendations for future research.
{"title":"A study on the relationship between taekwondo athletes’ psychological capital and athletic achievement","authors":"Wenpeng Zhan","doi":"10.30574/ijsra.2024.12.2.1247","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1247","url":null,"abstract":"The aim of this study is to investigate how psychological capital can predict athletic achievement among Taekwondo athletes. Data was collected using the psychological capital questionnaire and the athletic achievement scale through a survey of Taekwondo athletes. A total of 421 valid responses were collected with a response rate of 81.7%. The data was analyzed using SEM-PLS. The results show that the psychological capital dimensions of self-efficacy, hope, resilience, and optimism have a significant impact on the athletic achievement of Taekwondo athletes. Among these dimensions, self-efficacy has the greatest impact on athletic achievement, while optimism has the least influence. Overall, psychological capital accounts for 79.6% of the variance in athletic achievement. Based on these results, the study suggests several recommendations for future research.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"10 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.1235
Pius David Muzzazzi, Kandi Catherine Muze
WAGR syndrome is a rare genetic disorder characterized by a de novo deletion of 11p 13 (PAX6 and WT1 genes), clinically associated with Wilms’ tumor, aniridia, genitourinary anomalies, and mental retardation. It affects 1 in 500,000 to 1 million people worldwide. Wilms tumor occurs in half of the children with WAGR syndrome. We admitted 3-year-old boy who presented in our institution with the complaints of delay in development milestones and abdomen distension. On thorough examination he was found to have aniridia, Wilms tumor, undescended testis and mental retardation. The observation that aniridia is associated with Wilms tumor led us to believe that the findings were consistent with WAGR syndrome. The diagnosis was confirmed by a genetic testing that revealed loss of 17840kb within the 11p15.1p12 chromosome, confirming the diagnosis of WAGR syndrome.
{"title":"A Tanzanian child with WAGR syndrome: A case report","authors":"Pius David Muzzazzi, Kandi Catherine Muze","doi":"10.30574/ijsra.2024.12.2.1235","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1235","url":null,"abstract":"WAGR syndrome is a rare genetic disorder characterized by a de novo deletion of 11p 13 (PAX6 and WT1 genes), clinically associated with Wilms’ tumor, aniridia, genitourinary anomalies, and mental retardation. It affects 1 in 500,000 to 1 million people worldwide. Wilms tumor occurs in half of the children with WAGR syndrome. We admitted 3-year-old boy who presented in our institution with the complaints of delay in development milestones and abdomen distension. On thorough examination he was found to have aniridia, Wilms tumor, undescended testis and mental retardation. The observation that aniridia is associated with Wilms tumor led us to believe that the findings were consistent with WAGR syndrome. The diagnosis was confirmed by a genetic testing that revealed loss of 17840kb within the 11p15.1p12 chromosome, confirming the diagnosis of WAGR syndrome.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"9 49","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.1245
Mitul Goswami, Shashwat Kumar, Sourav Kaity
This research presents an innovative approach to developing a Tracking Radar Trajectory Simulator by integrating advanced network communication protocols and the GLG toolkit framework. The simulator processes raw real-time coordinate system data, specifically in ECEF, ENV, or LLA formats, and converts this to Radar-specific requirements. It serves as a crucial tool for real-time data transmission and visualization of key parameters such as Azimuth Angle, Elevation Angle, and Range, facilitating the study and analysis of Radar trajectory dynamics. The system employs socket programming to enable seamless communication between the simulator and external devices, allowing efficient data exchange in a networked environment. Additionally, it incorporates optimized algorithms to enhance performance and reliability while reducing the time complexity of the simulation. The proposed system surpasses existing state-of-the-art models in terms of agility and performance. Through rigorous experimentation and evaluation, the effectiveness and efficiency of the proposed approach are demonstrated, highlighting its potential applications in Radar technology research and development. This research advances the field of trajectory simulation by providing a robust and scalable solution for real-time data analysis and visualization, contributing significantly to the development of more agile and high-performing tracking systems.
{"title":"Network protocol-driven real-time tracking radar trajectory simulation using GLG framework for test range applications","authors":"Mitul Goswami, Shashwat Kumar, Sourav Kaity","doi":"10.30574/ijsra.2024.12.2.1245","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1245","url":null,"abstract":"This research presents an innovative approach to developing a Tracking Radar Trajectory Simulator by integrating advanced network communication protocols and the GLG toolkit framework. The simulator processes raw real-time coordinate system data, specifically in ECEF, ENV, or LLA formats, and converts this to Radar-specific requirements. It serves as a crucial tool for real-time data transmission and visualization of key parameters such as Azimuth Angle, Elevation Angle, and Range, facilitating the study and analysis of Radar trajectory dynamics. The system employs socket programming to enable seamless communication between the simulator and external devices, allowing efficient data exchange in a networked environment. Additionally, it incorporates optimized algorithms to enhance performance and reliability while reducing the time complexity of the simulation. The proposed system surpasses existing state-of-the-art models in terms of agility and performance. Through rigorous experimentation and evaluation, the effectiveness and efficiency of the proposed approach are demonstrated, highlighting its potential applications in Radar technology research and development. This research advances the field of trajectory simulation by providing a robust and scalable solution for real-time data analysis and visualization, contributing significantly to the development of more agile and high-performing tracking systems.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"5 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.1308
Madhuri Martis, Subramanya Bhat, Sreenivasa B R
IPMN cysts, a pre-malignant risk to the pancreas, have the potential to develop into pancreatic cancer. Accurately identifying and evaluating the risk level is crucial for planning an efficient treatment strategy. However, this task is immensely challenging due to the varied and irregular shapes, textures, and sizes of IPMN cysts, as well as those of the pancreas itself. In this study, we introduce a new computer-aided diagnostic approach for classifying IPMN risk levels based on multi-contrast MRI scans. The proposed analysis framework comprises an efficient volumetric self-adapting segmentation strategy for delineating the pancreas, followed by a newly developed deep learning-based classification scheme incorporating a radiomics-based predictive approach. To evaluate the proposed decision-fusion model, we use multi-centre datasets and multi-contrast MRI scans, aiming to achieve superior performance compared to the current state of the art in this field. The ablation studies illustrate the importance of both radiomics and deep learning modules in achieving a new state-of-the-art (SOTA) performance compared to international guidelines and published studies (81.9% vs 61.3% in accuracy). These key findings carry significant implications for clinical decision-making, potentially revolutionizing the way IPMN risk levels are classified. Through a series of rigorous experiments on multi-centre datasets (involving more MRI scans from five centers), we attained unprecedented performance levels with moderate accuracy. The code will be made available upon publication.
{"title":"A survey on machine learning system for intraductal papillary mucinous neoplasms detection","authors":"Madhuri Martis, Subramanya Bhat, Sreenivasa B R","doi":"10.30574/ijsra.2024.12.2.1308","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1308","url":null,"abstract":"IPMN cysts, a pre-malignant risk to the pancreas, have the potential to develop into pancreatic cancer. Accurately identifying and evaluating the risk level is crucial for planning an efficient treatment strategy. However, this task is immensely challenging due to the varied and irregular shapes, textures, and sizes of IPMN cysts, as well as those of the pancreas itself. In this study, we introduce a new computer-aided diagnostic approach for classifying IPMN risk levels based on multi-contrast MRI scans. The proposed analysis framework comprises an efficient volumetric self-adapting segmentation strategy for delineating the pancreas, followed by a newly developed deep learning-based classification scheme incorporating a radiomics-based predictive approach. To evaluate the proposed decision-fusion model, we use multi-centre datasets and multi-contrast MRI scans, aiming to achieve superior performance compared to the current state of the art in this field. The ablation studies illustrate the importance of both radiomics and deep learning modules in achieving a new state-of-the-art (SOTA) performance compared to international guidelines and published studies (81.9% vs 61.3% in accuracy). These key findings carry significant implications for clinical decision-making, potentially revolutionizing the way IPMN risk levels are classified. Through a series of rigorous experiments on multi-centre datasets (involving more MRI scans from five centers), we attained unprecedented performance levels with moderate accuracy. The code will be made available upon publication.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"4 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.1273
Mohammad Aniq Bin, Mohammad Aniq, Bin Amdan, Naldo Janius, Mohd Aidil, Hazidi Bin Kasdiah
The concept paper identifies the relationship of Artificial Intelligence (AI) towards teaching and learning in STEM education. AI can really revolutionize STEM education if AI-powered tools are in place to ensure that each of the students receives personalized instructions, intelligent tutoring, and interactive simulations. Not only this, but they even grade assignments or quizzes that are submitted automatically and prove predictions with analytics to create efficiency and effectiveness in STEM pedagogy. However, there is a limited quantity of primary research regarding the actual impacts of such AI technologies. The paper will hence fill this gap by making an in-depth assessment of the application of AI tools in STEM classrooms. If strategically deployed, AI has huge potential to improve student mastery in STEM, increase learner motivation and autonomy, and allow teachers to become more personalized in their support. However, it also identifies challenges of equitable access, bias in algorithms, and wishing that the teachers have robust training programs. It thus proposes, based on the results, key recommendations that include developing ethical guidelines, investing in professional development, and designing AI systems accommodating diverse learning needs. To be precise, this research provides relevant empirical evidence and some practical guidance for education stakeholders to harness the transformative power of AI for STEM learning
{"title":"Concept paper: Efficiency of Artificial Intelligence (AI) tools For STEM Education In Malaysia","authors":"Mohammad Aniq Bin, Mohammad Aniq, Bin Amdan, Naldo Janius, Mohd Aidil, Hazidi Bin Kasdiah","doi":"10.30574/ijsra.2024.12.2.1273","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1273","url":null,"abstract":"The concept paper identifies the relationship of Artificial Intelligence (AI) towards teaching and learning in STEM education. AI can really revolutionize STEM education if AI-powered tools are in place to ensure that each of the students receives personalized instructions, intelligent tutoring, and interactive simulations. Not only this, but they even grade assignments or quizzes that are submitted automatically and prove predictions with analytics to create efficiency and effectiveness in STEM pedagogy. However, there is a limited quantity of primary research regarding the actual impacts of such AI technologies. The paper will hence fill this gap by making an in-depth assessment of the application of AI tools in STEM classrooms. If strategically deployed, AI has huge potential to improve student mastery in STEM, increase learner motivation and autonomy, and allow teachers to become more personalized in their support. However, it also identifies challenges of equitable access, bias in algorithms, and wishing that the teachers have robust training programs. It thus proposes, based on the results, key recommendations that include developing ethical guidelines, investing in professional development, and designing AI systems accommodating diverse learning needs. To be precise, this research provides relevant empirical evidence and some practical guidance for education stakeholders to harness the transformative power of AI for STEM learning","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"3 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.1181
Srishti Bhatt, Saumya Jogy, Amita Puri
The relationship between parenting styles and the severity of attention deficit hyperactivity disorder (ADHD) in children has garnered considerable attention, yet remains complex and multifaceted. This study aims to elucidate this relationship by leveraging advanced artificial intelligence (AI) techniques to analyse a comprehensive dataset of parenting behaviours and ADHD symptomatology. Utilizing machine learning algorithms, we classified parenting styles into authoritative, authoritarian, permissive, and uninvolved categories based on standardized questionnaires. Simultaneously, ADHD severity was quantified using clinically validated scales. The AI-driven analysis revealed significant correlations between specific parenting styles and ADHD severity, with authoritative parenting showing a negative correlation, suggesting a potential mitigating effect on ADHD symptoms. Conversely, authoritarian and permissive styles were positively correlated with higher ADHD severity, indicating potential exacerbation of symptoms. Uninvolved parenting showed the weakest correlation, yet still highlighted notable impacts. Additionally, AI models identified nuanced patterns and interactions between various parenting practices and ADHD characteristics that traditional statistical methods might overlook. These findings underscore the critical role of adaptive parenting strategies in managing ADHD and highlight the potential of AI to uncover intricate behavioural patterns, offering novel insights for clinicians and researchers. The study advocates for the integration of AI in psychological and behavioural research to enhance the understanding of complex developmental disorders and improve intervention strategies. This approach not only deepens our comprehension of ADHD and its environmental influencers but also sets a precedent for future research utilizing AI to explore psychological phenomena.
{"title":"Parenting styles and ADHD severity: Leveraging AI to understand their relationship","authors":"Srishti Bhatt, Saumya Jogy, Amita Puri","doi":"10.30574/ijsra.2024.12.2.1181","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1181","url":null,"abstract":"The relationship between parenting styles and the severity of attention deficit hyperactivity disorder (ADHD) in children has garnered considerable attention, yet remains complex and multifaceted. This study aims to elucidate this relationship by leveraging advanced artificial intelligence (AI) techniques to analyse a comprehensive dataset of parenting behaviours and ADHD symptomatology. Utilizing machine learning algorithms, we classified parenting styles into authoritative, authoritarian, permissive, and uninvolved categories based on standardized questionnaires. Simultaneously, ADHD severity was quantified using clinically validated scales. The AI-driven analysis revealed significant correlations between specific parenting styles and ADHD severity, with authoritative parenting showing a negative correlation, suggesting a potential mitigating effect on ADHD symptoms. Conversely, authoritarian and permissive styles were positively correlated with higher ADHD severity, indicating potential exacerbation of symptoms. Uninvolved parenting showed the weakest correlation, yet still highlighted notable impacts. Additionally, AI models identified nuanced patterns and interactions between various parenting practices and ADHD characteristics that traditional statistical methods might overlook. These findings underscore the critical role of adaptive parenting strategies in managing ADHD and highlight the potential of AI to uncover intricate behavioural patterns, offering novel insights for clinicians and researchers. The study advocates for the integration of AI in psychological and behavioural research to enhance the understanding of complex developmental disorders and improve intervention strategies. This approach not only deepens our comprehension of ADHD and its environmental influencers but also sets a precedent for future research utilizing AI to explore psychological phenomena.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"6 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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