Pub Date : 2023-09-11DOI: 10.52783/tjjpt.v44.i3.916
Trapti Tak , Manish Sharma
Leadership is described as the heart of every organization and it is a process of leading followers/team. To get better outcome from the employees and to achieve the organizational goals, the leader should be able to understand the pulse of the employees and his or her own. The present research will focus on two vital parameters that are spirituality and emotional intelligence. The present research proposes to study the role of spirituality and emotional Intelligence in the development of effective leadership through extensive literature review. Emotional Intelligence includes self- awareness, empathy, self- motivation, emotional stability, managing relationships, integrity, sociability, of spirituality and emotional Intelligence in the development of effective leadership through extensive literature review. Emotional Intelligence includes self- awareness, empathy, self-motivation, emotional stability, managing relationships, integrity, sociability warmth and optimism on the part of the leader reflecting it onto the followers and spirituality comprises the values, attitudes, and behaviors that are reflecting compassion, vision, hope, commitment, satisfaction and happiness that are necessary to intrinsically motivate one and others.
{"title":"Impact of Emotional Intelligence and Spiritual Intelligence on Leadership Effectiveness- A Study Related to Banking Organization in Rajasthan: Analysis Approach","authors":"Trapti Tak , Manish Sharma","doi":"10.52783/tjjpt.v44.i3.916","DOIUrl":"https://doi.org/10.52783/tjjpt.v44.i3.916","url":null,"abstract":"Leadership is described as the heart of every organization and it is a process of leading followers/team. To get better outcome from the employees and to achieve the organizational goals, the leader should be able to understand the pulse of the employees and his or her own. The present research will focus on two vital parameters that are spirituality and emotional intelligence. The present research proposes to study the role of spirituality and emotional Intelligence in the development of effective leadership through extensive literature review. Emotional Intelligence includes self- awareness, empathy, self- motivation, emotional stability, managing relationships, integrity, sociability, of spirituality and emotional Intelligence in the development of effective leadership through extensive literature review. Emotional Intelligence includes self- awareness, empathy, self-motivation, emotional stability, managing relationships, integrity, sociability warmth and optimism on the part of the leader reflecting it onto the followers and spirituality comprises the values, attitudes, and behaviors that are reflecting compassion, vision, hope, commitment, satisfaction and happiness that are necessary to intrinsically motivate one and others.","PeriodicalId":39883,"journal":{"name":"Tuijin Jishu/Journal of Propulsion Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136070419","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 : 2023-09-09DOI: 10.52783/tjjpt.v44.i2.220
Jubber Nadaf Et al.
The primary objective of this research is to develop an innovative and AI-driven automation system that leverages state-of-the-art perceptive technologies for creating an ideal self-regulating video surveillance model. The system will be designed to optimize real-time monitoring and enhance threat detection capabilities through advanced AI algorithms and cutting-edge computer vision techniques. By harnessing machine learning and deep learning methodologies, the model aims to achieve unparalleled accuracy in detecting and analyzing potential security breaches and anomalies. Through continual learning and adaptation, the system seeks to establish a highly efficient and adaptable surveillance framework suitable for various environments, including public spaces, critical infrastructures, and private facilities. The ultimate goal is to revolutionize video surveillance by creating an intelligent, autonomous system that minimizes human intervention, reduces operational costs, and maximizes security effectiveness. The ultimate aim is to revolutionize video surveillance by creating a highly intelligent, self-sufficient system that maximizes security and safety while minimizing human intervention and operational costs.
{"title":"Innovative AI-driven Automation System Leveraging Advanced Perceptive Technologies to Establish an Ideal Self-Regulating Video Surveillance Model","authors":"Jubber Nadaf Et al.","doi":"10.52783/tjjpt.v44.i2.220","DOIUrl":"https://doi.org/10.52783/tjjpt.v44.i2.220","url":null,"abstract":"The primary objective of this research is to develop an innovative and AI-driven automation system that leverages state-of-the-art perceptive technologies for creating an ideal self-regulating video surveillance model. The system will be designed to optimize real-time monitoring and enhance threat detection capabilities through advanced AI algorithms and cutting-edge computer vision techniques. By harnessing machine learning and deep learning methodologies, the model aims to achieve unparalleled accuracy in detecting and analyzing potential security breaches and anomalies. Through continual learning and adaptation, the system seeks to establish a highly efficient and adaptable surveillance framework suitable for various environments, including public spaces, critical infrastructures, and private facilities. The ultimate goal is to revolutionize video surveillance by creating an intelligent, autonomous system that minimizes human intervention, reduces operational costs, and maximizes security effectiveness. The ultimate aim is to revolutionize video surveillance by creating a highly intelligent, self-sufficient system that maximizes security and safety while minimizing human intervention and operational costs.","PeriodicalId":39883,"journal":{"name":"Tuijin Jishu/Journal of Propulsion Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136192329","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 : 2023-09-07DOI: 10.52783/tjjpt.v44.i2.193
Nand Kumar Et al.
Big Data analytics refers to the process of examining, processing, and extracting meaningful insights from large and complex datasets that are too vast and dynamic to be effectively managed and analyzed using traditional data processing tools and methods. It involves the application of various techniques, technologies, and algorithms to uncover patterns, trends, correlations, and valuable information within massive volumes of data. The era of Big Data has ushered in a transformative wave across various industries, offering unprecedented opportunities for organizations to glean valuable insights and drive informed decision-making. However, with this vast potential comes a myriad of challenges that must be addressed to fully harness the power of Big Data analytics. This paper delves into the multifaceted landscape of Big Data analytics, exploring both the challenges that impede its realization and the abundant opportunities it presents.[1] The challenges in harnessing Big Data analytics include issues related to data volume, velocity, variety, and veracity, as well as the complexities of data storage, processing, and privacy. Scalability, data quality, and the need for skilled personnel also pose significant obstacles. Conversely, the paper highlights the vast opportunities that Big Data analytics offers. It discusses the potential for improving business operations, enhancing customer experiences, and enabling data-driven innovation. Additionally, the paper explores the impact of Big Data analytics in diverse fields such as healthcare, finance, marketing, and cybersecurity. The human element in Big Data analytics is also scrutinized, emphasizing the importance of fostering a data-centric culture within organizations. The role of data scientists, analysts, and data stewards is pivotal in extracting meaningful insights from the data deluge. The benefits as well as challenges of Big Data Analytics will be discussed in this paper.
{"title":"Harnessing the Power of Big Data: Challenges and Opportunities in Analytics.","authors":"Nand Kumar Et al.","doi":"10.52783/tjjpt.v44.i2.193","DOIUrl":"https://doi.org/10.52783/tjjpt.v44.i2.193","url":null,"abstract":"Big Data analytics refers to the process of examining, processing, and extracting meaningful insights from large and complex datasets that are too vast and dynamic to be effectively managed and analyzed using traditional data processing tools and methods. It involves the application of various techniques, technologies, and algorithms to uncover patterns, trends, correlations, and valuable information within massive volumes of data. The era of Big Data has ushered in a transformative wave across various industries, offering unprecedented opportunities for organizations to glean valuable insights and drive informed decision-making. However, with this vast potential comes a myriad of challenges that must be addressed to fully harness the power of Big Data analytics. This paper delves into the multifaceted landscape of Big Data analytics, exploring both the challenges that impede its realization and the abundant opportunities it presents.[1] The challenges in harnessing Big Data analytics include issues related to data volume, velocity, variety, and veracity, as well as the complexities of data storage, processing, and privacy. Scalability, data quality, and the need for skilled personnel also pose significant obstacles. Conversely, the paper highlights the vast opportunities that Big Data analytics offers. It discusses the potential for improving business operations, enhancing customer experiences, and enabling data-driven innovation. Additionally, the paper explores the impact of Big Data analytics in diverse fields such as healthcare, finance, marketing, and cybersecurity. The human element in Big Data analytics is also scrutinized, emphasizing the importance of fostering a data-centric culture within organizations. The role of data scientists, analysts, and data stewards is pivotal in extracting meaningful insights from the data deluge. The benefits as well as challenges of Big Data Analytics will be discussed in this paper.","PeriodicalId":39883,"journal":{"name":"Tuijin Jishu/Journal of Propulsion Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135096388","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 : 2023-09-06DOI: 10.52783/tjjpt.v44.i2.177
Anam Ashiq, Zhang Guoxing, Aftab Hussain Tabasam, Muhammad Nad
Purpose: This paper investigates the associations among managerial ability (MA), earnings quality (EQ) and financial performance of the firm (FP) in the context of Pakistani economy. Design/methodology/approach: For testing objectives, the research proposed panel data model based on three earnings quality attributes, such as predictability, smoothness, and conservatism, between the managerial ability and corporate financial performance. For estimation, the study analyzed an unbalanced panel of 219 non-financial listed firms on the Pakistan Stock Exchange (PSX) for 2008-2021. To address the concerns of heteroscedasticity and autocorrelation, the study applied fixed effect regression with robust standard errors clustered at the firm level, as suggested by Newey and West (1987). Findings: -The study provides that overall managerial ability enhances earnings quality and firm performance. In addition, it is observed that earnings quality plays a significant role in enhancing the firm financial performance. Furthermore, the findings also indicate that earnings quality partially mediates the linkage between managerial ability and firm performance. These results support the hypothesis that efficient managers enhance the earnings quality, reduce information asymmetries which translates into higher firm performance. Research limitations/implications: The current research is limited to the non-financial sector; however, the study findings are undeniably beneficial for corporate managers in the context of developing economies where the managerial skills, quality of earnings and regulatory control is poor. Originality/value: -The novelty of the study lies in the managerial ability and performance linkage considering earning quality as a mediator. Standard-setters and regulators can use the study's findings to understand how managerial skills affect corporate practices, accounting standards and behaviour.
{"title":"Indirect Effect of Earnings Quality in the Linkage between Managerial Ability and Firm Performance: Evidence from an Emerging Economy","authors":"Anam Ashiq, Zhang Guoxing, Aftab Hussain Tabasam, Muhammad Nad","doi":"10.52783/tjjpt.v44.i2.177","DOIUrl":"https://doi.org/10.52783/tjjpt.v44.i2.177","url":null,"abstract":"Purpose: This paper investigates the associations among managerial ability (MA), earnings quality (EQ) and financial performance of the firm (FP) in the context of Pakistani economy. \u0000 Design/methodology/approach: For testing objectives, the research proposed panel data model based on three earnings quality attributes, such as predictability, smoothness, and conservatism, between the managerial ability and corporate financial performance. For estimation, the study analyzed an unbalanced panel of 219 non-financial listed firms on the Pakistan Stock Exchange (PSX) for 2008-2021. To address the concerns of heteroscedasticity and autocorrelation, the study applied fixed effect regression with robust standard errors clustered at the firm level, as suggested by Newey and West (1987). \u0000Findings: -The study provides that overall managerial ability enhances earnings quality and firm performance. In addition, it is observed that earnings quality plays a significant role in enhancing the firm financial performance. Furthermore, the findings also indicate that earnings quality partially mediates the linkage between managerial ability and firm performance. These results support the hypothesis that efficient managers enhance the earnings quality, reduce information asymmetries which translates into higher firm performance. \u0000Research limitations/implications: The current research is limited to the non-financial sector; however, the study findings are undeniably beneficial for corporate managers in the context of developing economies where the managerial skills, quality of earnings and regulatory control is poor. \u0000Originality/value: -The novelty of the study lies in the managerial ability and performance linkage considering earning quality as a mediator. Standard-setters and regulators can use the study's findings to understand how managerial skills affect corporate practices, accounting standards and behaviour.","PeriodicalId":39883,"journal":{"name":"Tuijin Jishu/Journal of Propulsion Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85379096","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 : 2023-07-24DOI: 10.52783/tjjpt.v44.i2.148
Gonesh Chandra Saha Et al.
Human-AI collaboration embodies the idea that AI systems and humans work together synergistically, leveraging each other's strengths to achieve more than what either can do in isolation. It's a shift from the traditional notion of AI as a replacement for human labour to a partnership where AI augments human capabilities. This collaboration is founded on trust, where humans rely on AI for data-driven insights, and AI relies on human expertise for nuanced decision-making. In the ever-evolving landscape of technology, one of the most profound transformations is the collaboration between humans and artificial intelligence (AI). This collaboration is further facilitated and enhanced through the interfaces of machine learning (ML), where humans interact with AI algorithms to achieve collective goals. As artificial intelligence (AI) continues to advance, the synergy between humans and machines becomes increasingly significant. This paper delves into the evolving landscape of Human-AI Collaboration, with a particular focus on interactive Machine Learning (iML) interfaces. In a world where AI systems permeate numerous facets of society, understanding how humans can effectively collaborate with AI through intuitive interfaces is paramount. This research comprehensively explores the pivotal role of user interfaces in facilitating collaborative machine learning. It encompasses an analysis of existing iML interfaces, user experience evaluations, and the proposition of innovative design principles to enhance the effectiveness of AI as a collaborative tool. This study contributes to advancing our understanding of harnessing AI's potential to empower users in various domains.
{"title":"Human-AI Collaboration: Exploring interfaces for interactive Machine Learning","authors":"Gonesh Chandra Saha Et al.","doi":"10.52783/tjjpt.v44.i2.148","DOIUrl":"https://doi.org/10.52783/tjjpt.v44.i2.148","url":null,"abstract":"Human-AI collaboration embodies the idea that AI systems and humans work together synergistically, leveraging each other's strengths to achieve more than what either can do in isolation. It's a shift from the traditional notion of AI as a replacement for human labour to a partnership where AI augments human capabilities. This collaboration is founded on trust, where humans rely on AI for data-driven insights, and AI relies on human expertise for nuanced decision-making. In the ever-evolving landscape of technology, one of the most profound transformations is the collaboration between humans and artificial intelligence (AI). This collaboration is further facilitated and enhanced through the interfaces of machine learning (ML), where humans interact with AI algorithms to achieve collective goals. As artificial intelligence (AI) continues to advance, the synergy between humans and machines becomes increasingly significant. This paper delves into the evolving landscape of Human-AI Collaboration, with a particular focus on interactive Machine Learning (iML) interfaces. In a world where AI systems permeate numerous facets of society, understanding how humans can effectively collaborate with AI through intuitive interfaces is paramount. This research comprehensively explores the pivotal role of user interfaces in facilitating collaborative machine learning. It encompasses an analysis of existing iML interfaces, user experience evaluations, and the proposition of innovative design principles to enhance the effectiveness of AI as a collaborative tool. This study contributes to advancing our understanding of harnessing AI's potential to empower users in various domains.","PeriodicalId":39883,"journal":{"name":"Tuijin Jishu/Journal of Propulsion Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84687067","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 : 2023-07-24DOI: 10.52783/tjjpt.v44.i2.127
Anuradha More Et al.
Vaginal candidiasis, a fungal infection estimates that 75 % of women will be suffering at least once during their lifetime. The disorders of this infection might be premature birth, pelvic inflammation, abortion, the transmission of sexual disorders, etc. In the present research, mucoadhesive vaginal tablets containing sertaconazole nitrate-loaded silver nanoparticles formulations were developed which increases the proximity period of the medicine with the vaginal mucosa, showing sustained drug release. The drug-loaded silver nanoparticle was synthesized by the chemical reduction method. There was successful conjugation of sertaconazole nitrate with silver nanoparticles (Ser-AgNP1) therefore, the drug’s solubility is increased by 2.51 folds. The confirmation of silver nanoparticles was accessed by UV-visible spectroscopy. The mucoadhesive vaginal tablets were formulated and evaluated for swelling index, mucoadhesive force, residence time, In vitro dissolution and release kinetics, stability, and antifungal study. Optimized batch F8 was selected based on optimum mucoadhesive force (2.59±0.25N), % swelling index (86.50±0.11%), and sustained drug release (95.63±0.16%) up to 12 hr and showed greater antifungal activity. Overall study reveals that a prepared novel formulation, a mucoadhesive vaginal tablet containing sertaconazole nitrate loaded silver nanoparticles prevail over sertaconazole nitrate poor solubility and delivered drug during an extended period of time and also improved antifungal activity against Candida albicans.
{"title":"Design and Development of Sertaconazole Nitrate Loaded Silver Nanoparticulate Mucoadhesive Tablets for the Treatment of Vaginal Candidiasis","authors":"Anuradha More Et al.","doi":"10.52783/tjjpt.v44.i2.127","DOIUrl":"https://doi.org/10.52783/tjjpt.v44.i2.127","url":null,"abstract":"Vaginal candidiasis, a fungal infection estimates that 75 % of women will be suffering at least once during their lifetime. The disorders of this infection might be premature birth, pelvic inflammation, abortion, the transmission of sexual disorders, etc. In the present research, mucoadhesive vaginal tablets containing sertaconazole nitrate-loaded silver nanoparticles formulations were developed which increases the proximity period of the medicine with the vaginal mucosa, showing sustained drug release. The drug-loaded silver nanoparticle was synthesized by the chemical reduction method. There was successful conjugation of sertaconazole nitrate with silver nanoparticles (Ser-AgNP1) therefore, the drug’s solubility is increased by 2.51 folds. The confirmation of silver nanoparticles was accessed by UV-visible spectroscopy. The mucoadhesive vaginal tablets were formulated and evaluated for swelling index, mucoadhesive force, residence time, In vitro dissolution and release kinetics, stability, and antifungal study. Optimized batch F8 was selected based on optimum mucoadhesive force (2.59±0.25N), % swelling index (86.50±0.11%), and sustained drug release (95.63±0.16%) up to 12 hr and showed greater antifungal activity. Overall study reveals that a prepared novel formulation, a mucoadhesive vaginal tablet containing sertaconazole nitrate loaded silver nanoparticles prevail over sertaconazole nitrate poor solubility and delivered drug during an extended period of time and also improved antifungal activity against Candida albicans.","PeriodicalId":39883,"journal":{"name":"Tuijin Jishu/Journal of Propulsion Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90925636","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}
Deep Learning (DL), a subset of machine learning (ML) based on artificial neural networks, has experienced significant advancements in recent years. While it has demonstrated remarkable capabilities in various domains, the true potential of DL shines when it is applied to real-world problems. This article delves into the fascinating world of deep learning in real-world applications, highlighting its impact, challenges, and future prospects. the translation of DL research into real-world applications presents a unique set of challenges. While DL models exhibit remarkable performance in controlled environments, their practical deployment is often impeded by issues related to data availability, model interpretability, ethical considerations, and computational requirements. This paper aims to provide a comprehensive analysis of the progress and challenges associated with deploying deep learning in real-world scenarios. Deep learning is the subset of man-made intelligence technique where there are number of layers of data which are tended to as neurons and helps with understanding the data gainfully. Computer based intelligence helps the machines and structures to fathom the human exercises themselves and subsequently reply in a way that is controlled successfully close to the end client of that particular application, system, etc. Different significant learning computations are used to complete the thought where the significant acquiring starts the cycle by taking data from one layer and give it to the accompanying layer of data. A lot of information and data is taken care of as layers and moderate framework where they are related with each other by association of neurons which go about as information of interest for each layer. The meaning of significant learning will be gotten a handle on in this paper which will figure out the uses of significant learning thought. The fundamental or low-level layers of significant learning will endeavour to recognize fundamental components and the middle layer will endeavour to perceive the thing and the critical level layers will distinguish the real deal. There are numerous significant learning frameworks which are used across various spaces to basic and work on the task of the business.
{"title":"Analysis of Deep Learning in Real-World Applications: Challenges and Progress","authors":"Vivek Velayutham, Gunjan Chhabra, Sanjay Kumar, Avinash Kumar, Shrinwantu Raha, Gonesh Chandra Sah","doi":"10.52783/tjjpt.v44.i2.150","DOIUrl":"https://doi.org/10.52783/tjjpt.v44.i2.150","url":null,"abstract":"Deep Learning (DL), a subset of machine learning (ML) based on artificial neural networks, has experienced significant advancements in recent years. While it has demonstrated remarkable capabilities in various domains, the true potential of DL shines when it is applied to real-world problems. This article delves into the fascinating world of deep learning in real-world applications, highlighting its impact, challenges, and future prospects. the translation of DL research into real-world applications presents a unique set of challenges. While DL models exhibit remarkable performance in controlled environments, their practical deployment is often impeded by issues related to data availability, model interpretability, ethical considerations, and computational requirements. This paper aims to provide a comprehensive analysis of the progress and challenges associated with deploying deep learning in real-world scenarios. Deep learning is the subset of man-made intelligence technique where there are number of layers of data which are tended to as neurons and helps with understanding the data gainfully. Computer based intelligence helps the machines and structures to fathom the human exercises themselves and subsequently reply in a way that is controlled successfully close to the end client of that particular application, system, etc. Different significant learning computations are used to complete the thought where the significant acquiring starts the cycle by taking data from one layer and give it to the accompanying layer of data. A lot of information and data is taken care of as layers and moderate framework where they are related with each other by association of neurons which go about as information of interest for each layer. The meaning of significant learning will be gotten a handle on in this paper which will figure out the uses of significant learning thought. The fundamental or low-level layers of significant learning will endeavour to recognize fundamental components and the middle layer will endeavour to perceive the thing and the critical level layers will distinguish the real deal. There are numerous significant learning frameworks which are used across various spaces to basic and work on the task of the business.","PeriodicalId":39883,"journal":{"name":"Tuijin Jishu/Journal of Propulsion Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81903681","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 : 2023-07-24DOI: 10.52783/tjjpt.v44.i2.131
Sowmya Dongari, M. Nisarudeen, Joetika Devi, Shahrukh Irfan, Prasanta Kumar Parida, Aakanksha B
The integration of Artificial Intelligence (AI) into the field of medicine has catalysed transformative advancements, revolutionizing the landscape of healthcare. The paper delves into the dynamic intersection of AI and medicine, exploring innovative applications, methodologies, and outcomes that have emerged as a result. By harnessing the power of AI, healthcare systems have experienced enhanced diagnostic accuracy, personalized treatment strategies, and optimized operational efficiency. Through an in-depth analysis of cutting-edge research, technological breakthroughs, and real-world implementations, the paper showcases how AI has propelled healthcare into an era of unprecedented precision and effectiveness. It also addresses the ethical considerations and challenges associated with AI-driven medical interventions. By shedding light on the remarkable potential of AI in healthcare, it contributes to the broader dialogue on the ongoing transformation of medical practices and offers insights into the future trajectory of this dynamic synergy between AI and medicine. The convergence of Artificial Intelligence (AI) and medicine has ushered in a new era of possibilities, revolutionizing the healthcare landscape. It is a comprehensive exploration of the multifaceted intersection between AI and medicine, highlighting the transformative innovations that have emerged and their profound impact on healthcare delivery. The rise of AI in healthcare, elucidating the challenges that the field faces and how AI presents a paradigm shift in addressing them, is also explained in this paper. It delves into the intricate methodologies that underpin AI-driven medical advancements, ranging from machine learning algorithms that process complex medical data to neural networks that mimic human cognitive processes for image analysis and pattern recognition. These methodologies have led to groundbreaking achievements in disease diagnosis, prognosis, and treatment selection, surpassing human capabilities in some instances. The integration of AI also extends beyond clinical settings. The paper investigates how AI-driven predictive analytics have streamlined hospital operations, optimizing resource allocation, staff scheduling, and patient flow. Such innovations enhance cost-effectiveness and patient satisfaction, contributing to the overall efficiency of healthcare institutions.
{"title":"Advancing Healthcare through Artificial Intelligence: Innovations at the Intersection of AI and Medicine","authors":"Sowmya Dongari, M. Nisarudeen, Joetika Devi, Shahrukh Irfan, Prasanta Kumar Parida, Aakanksha B","doi":"10.52783/tjjpt.v44.i2.131","DOIUrl":"https://doi.org/10.52783/tjjpt.v44.i2.131","url":null,"abstract":"The integration of Artificial Intelligence (AI) into the field of medicine has catalysed transformative advancements, revolutionizing the landscape of healthcare. The paper delves into the dynamic intersection of AI and medicine, exploring innovative applications, methodologies, and outcomes that have emerged as a result. By harnessing the power of AI, healthcare systems have experienced enhanced diagnostic accuracy, personalized treatment strategies, and optimized operational efficiency. Through an in-depth analysis of cutting-edge research, technological breakthroughs, and real-world implementations, the paper showcases how AI has propelled healthcare into an era of unprecedented precision and effectiveness. It also addresses the ethical considerations and challenges associated with AI-driven medical interventions. By shedding light on the remarkable potential of AI in healthcare, it contributes to the broader dialogue on the ongoing transformation of medical practices and offers insights into the future trajectory of this dynamic synergy between AI and medicine. The convergence of Artificial Intelligence (AI) and medicine has ushered in a new era of possibilities, revolutionizing the healthcare landscape. It is a comprehensive exploration of the multifaceted intersection between AI and medicine, highlighting the transformative innovations that have emerged and their profound impact on healthcare delivery. The rise of AI in healthcare, elucidating the challenges that the field faces and how AI presents a paradigm shift in addressing them, is also explained in this paper. It delves into the intricate methodologies that underpin AI-driven medical advancements, ranging from machine learning algorithms that process complex medical data to neural networks that mimic human cognitive processes for image analysis and pattern recognition. These methodologies have led to groundbreaking achievements in disease diagnosis, prognosis, and treatment selection, surpassing human capabilities in some instances. The integration of AI also extends beyond clinical settings. The paper investigates how AI-driven predictive analytics have streamlined hospital operations, optimizing resource allocation, staff scheduling, and patient flow. Such innovations enhance cost-effectiveness and patient satisfaction, contributing to the overall efficiency of healthcare institutions.","PeriodicalId":39883,"journal":{"name":"Tuijin Jishu/Journal of Propulsion Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89746195","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 : 2023-07-24DOI: 10.52783/tjjpt.v44.i2.141
Aaqib Nisar Bhat, Saba Tahir, Rajiv Kumar
In the contemporary digital era, the proliferation of smart gadgets has revolutionized the way information is accessed, communicated, and entertained. With the increasing availability and accessibility of smartphones, tablets, and other electronic devices, children are exposed to digital technology at an earlier age than ever before. This abstract delves into the effects of smart gadgets on children in their early developmental years, exploring both the potential benefits and drawbacks. The usage of smart gadgets among young children has raised concerns among parents, educators, and researchers regarding its influence on cognitive, social, and emotional development. This abstract synthesizes current research findings and offers insights into the multifaceted impact of smart gadgets on early age children
{"title":"The Influence of Early Exposure to Smart Gadgets on Children","authors":"Aaqib Nisar Bhat, Saba Tahir, Rajiv Kumar","doi":"10.52783/tjjpt.v44.i2.141","DOIUrl":"https://doi.org/10.52783/tjjpt.v44.i2.141","url":null,"abstract":"In the contemporary digital era, the proliferation of smart gadgets has revolutionized the way information is accessed, communicated, and entertained. With the increasing availability and accessibility of smartphones, tablets, and other electronic devices, children are exposed to digital technology at an earlier age than ever before. This abstract delves into the effects of smart gadgets on children in their early developmental years, exploring both the potential benefits and drawbacks. The usage of smart gadgets among young children has raised concerns among parents, educators, and researchers regarding its influence on cognitive, social, and emotional development. This abstract synthesizes current research findings and offers insights into the multifaceted impact of smart gadgets on early age children","PeriodicalId":39883,"journal":{"name":"Tuijin Jishu/Journal of Propulsion Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82839366","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}
This research is dedicated to outlining the sustainable practices embraced by hotels, gauging their potency in cultivating a competitive edge, and exploring their ramifications for various hotel stakeholders. Focusing on the context of Agra's five-star hotels, this study undertakes an assessment of their sustainable endeavors. A comprehensive survey encompassing 252 employees from the city's 13 five-star hotels was conducted. Through this survey, we endeavored to discern the sustainable practices undertaken across these establishments in the realms of economic, social, and environmental dimensions. Moreover, we aimed to gauge the extent to which these practices have been seamlessly integrated into their operations. Concurrently, we also undertook an exploration of the correlation between employee satisfaction and the implementation of sustainability initiatives.
{"title":"\"Exploring Sustainable Practices in Five-Star Hotels: A Comprehensive Analysis and Implications for Agra's Hospitality Industry\"","authors":"Sanjeev Kumar Saxena, Soumendra Nath Biswas, Vandana Gupta Pradip Kumar","doi":"10.52783/tjjpt.v44.i2.137","DOIUrl":"https://doi.org/10.52783/tjjpt.v44.i2.137","url":null,"abstract":"This research is dedicated to outlining the sustainable practices embraced by hotels, gauging their potency in cultivating a competitive edge, and exploring their ramifications for various hotel stakeholders. Focusing on the context of Agra's five-star hotels, this study undertakes an assessment of their sustainable endeavors. A comprehensive survey encompassing 252 employees from the city's 13 five-star hotels was conducted. Through this survey, we endeavored to discern the sustainable practices undertaken across these establishments in the realms of economic, social, and environmental dimensions. Moreover, we aimed to gauge the extent to which these practices have been seamlessly integrated into their operations. Concurrently, we also undertook an exploration of the correlation between employee satisfaction and the implementation of sustainability initiatives.","PeriodicalId":39883,"journal":{"name":"Tuijin Jishu/Journal of Propulsion Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89158173","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：