Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.0892
S. E. Ezeani, W. I. Bell-Gam
Bioremediation of hydrocarbon contaminated soils is a relatively inexpensive and environmentally friendly technology that is applicable over a large area of contaminated site. The paper is a case study of a successful ex situ bioremediation of a hydrocarbon contaminated site in Ogoni Land, Rivers State. The contaminated soils were excavated, treated in an engineered biocell, and sprinkled with nutrient media to enhance microbial population and biodegradation. The biocell was constructed using laterite material. The floor was lined with High Density Polyethylene material. The treatability study of the contaminated soil was conducted to determine the quantity of nutrient required to boost the microbial population in the affected soil. A PNutrient made up of (Nitrogen, Phosphorus, Potassium) NPK 20-10-10 and urea at a quantity established by the EnviTech Calculator was used for the treatment. Due to varying depths and concentrations of the contaminant, nutrient adjustments necessary to enhance rapid microbial population and degradation were noted and undertaken. Soil sampling and analysis were conducted at the end of every treatment cycle to establish reduction of the Total Petroleum Hydrocarbon to an allowable limit. The project has proven to be successful and beneficial in the clean-up and restoration of Ogoni Land.
{"title":"Bio-remediation of hydrocarbon contaminated site using nitrogen, phosphorus, potassium and urea: A case study of Ogoni clean –Up","authors":"S. E. Ezeani, W. I. Bell-Gam","doi":"10.30574/ijsra.2024.12.2.0892","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.0892","url":null,"abstract":"Bioremediation of hydrocarbon contaminated soils is a relatively inexpensive and environmentally friendly technology that is applicable over a large area of contaminated site. The paper is a case study of a successful ex situ bioremediation of a hydrocarbon contaminated site in Ogoni Land, Rivers State. The contaminated soils were excavated, treated in an engineered biocell, and sprinkled with nutrient media to enhance microbial population and biodegradation. The biocell was constructed using laterite material. The floor was lined with High Density Polyethylene material. The treatability study of the contaminated soil was conducted to determine the quantity of nutrient required to boost the microbial population in the affected soil. A PNutrient made up of (Nitrogen, Phosphorus, Potassium) NPK 20-10-10 and urea at a quantity established by the EnviTech Calculator was used for the treatment. Due to varying depths and concentrations of the contaminant, nutrient adjustments necessary to enhance rapid microbial population and degradation were noted and undertaken. Soil sampling and analysis were conducted at the end of every treatment cycle to establish reduction of the Total Petroleum Hydrocarbon to an allowable limit. The project has proven to be successful and beneficial in the clean-up and restoration of Ogoni Land.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"5 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796086","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}
Precision agriculture leverages data science and technology to optimize farming practices, enhance crop yields, and promote sustainability. This review examines how data-driven approaches are revolutionizing agriculture through improved decision-making, resource efficiency, and environmental stewardship. Key technologies enabling precision agriculture are discussed, including remote sensing, IoT sensors, AI/machine learning, and farm management information systems. The paper explores applications such as variable rate technology, yield mapping, and predictive analytics. Challenges related to data management, interoperability, and adoption barriers are analyzed. The review concludes that precision agriculture, powered by data science, offers significant potential to address food security and sustainability challenges, but requires continued research and interdisciplinary collaboration to realize its full benefits.
{"title":"Precision agriculture: Leveraging data science for sustainable farming","authors":"Adeleye Yusuff Adewuyi, Blessing Anyibama, Kayode Blessing Adebayo, Joseph Moses Kalinzi, Samson Ademola Adeniyi, Ifeoluwa Wada","doi":"10.30574/ijsra.2024.12.2.1371","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1371","url":null,"abstract":"Precision agriculture leverages data science and technology to optimize farming practices, enhance crop yields, and promote sustainability. This review examines how data-driven approaches are revolutionizing agriculture through improved decision-making, resource efficiency, and environmental stewardship. Key technologies enabling precision agriculture are discussed, including remote sensing, IoT sensors, AI/machine learning, and farm management information systems. The paper explores applications such as variable rate technology, yield mapping, and predictive analytics. Challenges related to data management, interoperability, and adoption barriers are analyzed. The review concludes that precision agriculture, powered by data science, offers significant potential to address food security and sustainability challenges, but requires continued research and interdisciplinary collaboration to realize its full benefits.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"2 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796270","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.2024.12.2.1321
Nondon Lal Dey, Shuvasish Chowdhury, Islam Uddin Shipu, Muhammad Ihsan Ibn Rahim, Debangshu Deb, Md Rafid Hasan
The perovskite structure has shown enormous utility in many facets of science in the past 50 years. From applications in high-temperature superconductors to piezoelectric sensors, the perovskite structure has been used in a wide array of cutting-edge areas of solid-state physics and materials science. LaTiO3 has a perovskite type crystal structure. It undergoes three phase transitions. At 50-100 K LaTiO3 undergoes a magnetic phase transition. John –Teller phase transition occurs between 100 K and 300 K. Also, insulator-metal (I-M) transition occurred at 500-550k. On the other hand, YtiO3 also have perovskite type crystal structure. It undergoes I-M phase transition around 750 K. We are interested to know the effect of the electrical and dielectric properties by replacing La with Y (Yttrium). To investigate the electrical and dielectric properties of La1-xYxTiO3 [x = 0.0, 0.2, 0.3 0.4 and 0.6] system, samples have been prepared by solid state reaction method. To confirm the crystal structure, room temperature X-ray diffractions were performed and no extra pack was observed. The measurement of frequency dependence dielectric constant shows that the decreases in dielectric constant observed with increase in frequency and the value of dielectric constant increase with increasing concentration of Y (Yttrium). We also observed that loss tangent decrease with increasing frequency and increase in concentration of Y (Yttrium) results to decrease in the value of loss tangent. The cole-cole plot shows that the grain size decrease with increasing concentration of Y (Yttrium), as a result resistivity decrease while conductivity increases with increasing concentration of Y (Yttrium).
在过去的 50 年中，包晶结构在科学的许多方面都显示出巨大的用途。从高温超导体到压电传感器，透辉石结构被广泛应用于固体物理和材料科学的前沿领域。LaTiO3 具有包晶型晶体结构。它经历了三次相变。在 50-100 K 时，LaTiO3 会发生磁性相变。约翰-泰勒相变发生在 100 K 到 300 K 之间，绝缘体-金属（I-M）相变发生在 500-550 K 之间。另一方面，YtiO3 也具有包晶型晶体结构。我们有兴趣了解用 Y（钇）取代 La 对电气和介电性质的影响。为了研究 La1-xYxTiO3 [x = 0.0、0.2、0.3 0.4 和 0.6] 体系的电学和介电性能，我们采用固态反应法制备了样品。为了确认晶体结构，进行了室温 X 射线衍射，没有观察到额外的包。频率相关介电常数的测量结果表明，介电常数随频率的增加而降低，介电常数值随钇（Y）浓度的增加而增加。我们还观察到，损耗正切随频率增加而减小，钇浓度增加导致损耗正切值减小。科尔-科尔图显示，晶粒尺寸随钇（钇）浓度的增加而减小，因此电阻率随钇（钇）浓度的增加而减小，而电导率随钇（钇）浓度的增加而增大。
{"title":"Electrical properties of Yttrium(Y) doped LaTiO3","authors":"Nondon Lal Dey, Shuvasish Chowdhury, Islam Uddin Shipu, Muhammad Ihsan Ibn Rahim, Debangshu Deb, Md Rafid Hasan","doi":"10.30574/ijsra.2024.12.2.1321","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1321","url":null,"abstract":"The perovskite structure has shown enormous utility in many facets of science in the past 50 years. From applications in high-temperature superconductors to piezoelectric sensors, the perovskite structure has been used in a wide array of cutting-edge areas of solid-state physics and materials science. LaTiO3 has a perovskite type crystal structure. It undergoes three phase transitions. At 50-100 K LaTiO3 undergoes a magnetic phase transition. John –Teller phase transition occurs between 100 K and 300 K. Also, insulator-metal (I-M) transition occurred at 500-550k. On the other hand, YtiO3 also have perovskite type crystal structure. It undergoes I-M phase transition around 750 K. We are interested to know the effect of the electrical and dielectric properties by replacing La with Y (Yttrium). To investigate the electrical and dielectric properties of La1-xYxTiO3 [x = 0.0, 0.2, 0.3 0.4 and 0.6] system, samples have been prepared by solid state reaction method. To confirm the crystal structure, room temperature X-ray diffractions were performed and no extra pack was observed. The measurement of frequency dependence dielectric constant shows that the decreases in dielectric constant observed with increase in frequency and the value of dielectric constant increase with increasing concentration of Y (Yttrium). We also observed that loss tangent decrease with increasing frequency and increase in concentration of Y (Yttrium) results to decrease in the value of loss tangent. The cole-cole plot shows that the grain size decrease with increasing concentration of Y (Yttrium), as a result resistivity decrease while conductivity increases with increasing concentration of Y (Yttrium).","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"8 48","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795687","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.2024.12.2.1370
Edward Muita Mugo, Redempter Nzuma, Emeka Augustine Adibe, Raphael Ekundayo Adesiyan, Oyinlola Esther Obafunsho, Blessing Anyibama
Globalization in the food supply chain presents complex challenges, particularly regarding food safety and security, due to the risks of infectious diseases and outbreaks. These threats impact public health and economic stability, necessitating multifaceted interventions and collaborative efforts within the food industry. This review article explores the importance and challenges of collaboration between public health authorities and the food industry. It examines current partnerships, analyzes successful strategies through case studies, and identifies opportunities for enhancing cooperation. Key areas of focus include improved information exchange, joint training, and the development of standardized practices and policies.
{"title":"Collaborative efforts between public health agencies and the food industry to enhance preparedness","authors":"Edward Muita Mugo, Redempter Nzuma, Emeka Augustine Adibe, Raphael Ekundayo Adesiyan, Oyinlola Esther Obafunsho, Blessing Anyibama","doi":"10.30574/ijsra.2024.12.2.1370","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1370","url":null,"abstract":"Globalization in the food supply chain presents complex challenges, particularly regarding food safety and security, due to the risks of infectious diseases and outbreaks. These threats impact public health and economic stability, necessitating multifaceted interventions and collaborative efforts within the food industry. This review article explores the importance and challenges of collaboration between public health authorities and the food industry. It examines current partnerships, analyzes successful strategies through case studies, and identifies opportunities for enhancing cooperation. Key areas of focus include improved information exchange, joint training, and the development of standardized practices and policies.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"2 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795761","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 advent of artificial intelligence (AI) has dramatically changed the business landscape, providing unprecedented opportunities for organizations to transform, grow and innovate This research paper explores how AI can be used to transform business advanced growth strategies, market research, customer insights and competitive intelligence. Companies can reap many benefits from integrating AI into their operations. AI algorithms can analyze large data sets to identify trends and patterns beyond human capabilities, enabling companies to forecast market demand, streamline distribution, and make data-driven decisions in terms of production and marketing. AI also empowers customers with more personalized experiences by analyzing behaviors and preferences to recommend personalized products and services. This personalization drives greater customer engagement, loyalty and increased sales. The paper highlights the transformative potential of AI through real-world examples and case studies in various industries. These examples illustrate the impact of AI, from predicting customer attendance in mobile communication to optimizing marketing campaigns in retail. However, implementing AI is not without its challenges. Businesses need to address the need for robust data structures and reduce the potential for bias in AI algorithms. Furthermore, ethical considerations such as data privacy and displacement of human workers must be treated with caution. The paper discusses these challenges and highlights the importance of responsible AI implementation strategies. By acknowledging and addressing these obstacles, companies can unlock the full potential of AI. This review paper aims to provide readers with a comprehensive understanding of AI-driven business development strategies, enabling them to harness the potential of AI to drive sustainable growth and success.
{"title":"Leveraging AI for transformative business development: Strategies for market analysis, customer insights, and competitive intelligence","authors":"Temitayo Oluwadamilola Adesoga, Omolara Patricia Olaiya, Omotoyosi Qazeem Obani, Mary-Cynthia Uchenna Orji, Chimezirim Akanu Orji, Oluwabusola Dorcas Olagunju","doi":"10.30574/ijsra.2024.12.2.1291","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1291","url":null,"abstract":"The advent of artificial intelligence (AI) has dramatically changed the business landscape, providing unprecedented opportunities for organizations to transform, grow and innovate This research paper explores how AI can be used to transform business advanced growth strategies, market research, customer insights and competitive intelligence. Companies can reap many benefits from integrating AI into their operations. AI algorithms can analyze large data sets to identify trends and patterns beyond human capabilities, enabling companies to forecast market demand, streamline distribution, and make data-driven decisions in terms of production and marketing. AI also empowers customers with more personalized experiences by analyzing behaviors and preferences to recommend personalized products and services. This personalization drives greater customer engagement, loyalty and increased sales. The paper highlights the transformative potential of AI through real-world examples and case studies in various industries. These examples illustrate the impact of AI, from predicting customer attendance in mobile communication to optimizing marketing campaigns in retail. However, implementing AI is not without its challenges. Businesses need to address the need for robust data structures and reduce the potential for bias in AI algorithms. Furthermore, ethical considerations such as data privacy and displacement of human workers must be treated with caution. The paper discusses these challenges and highlights the importance of responsible AI implementation strategies. By acknowledging and addressing these obstacles, companies can unlock the full potential of AI. This review paper aims to provide readers with a comprehensive understanding of AI-driven business development strategies, enabling them to harness the potential of AI to drive sustainable growth and success.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"10 38","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795843","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.2024.12.2.1246
Suri babu Nuthalapati, Aravind Nuthalapati
This Paper examines the interesting topic of weather forecasting using ML. From kaggle.com, there is an extensive list of daily weather records for a Seattle dataset. In this chapter, gradient boosting outcomes are revealed as a result of careful data preparation and thorough examination of several machine learning models such as K-Nearest Neighbors, Support vector machine, Gradient Boosting, XGBOOST, logistic regression, and random forest class Its 80.95% accuracy was outstanding. ML traverses atmospheric dynamics that form a basis for weather predictions. It uses a highly developed method that enables it to predict the complex trends in the weather. In addition, machine learning algorithms are increasingly important for detecting non-linear relationships and patterns from large sets of complex data with time. It is critical for meteorologists in overcoming uncertainties associated with atmospheric dynamics to improve prediction. Gradient Boosting – a weather forecasting perspective in an interdisciplinary landscape involving weather science and machine learning. The current research on ML for weather forecasting has been very useful.
本文探讨了使用 ML 进行天气预报这一有趣的话题。kaggle.com 提供了西雅图数据集的大量每日天气记录。在本章中，通过对 K-近邻、支持向量机、梯度提升、XGBOOST、逻辑回归和随机森林类等多个机器学习模型进行仔细的数据准备和全面的检查，揭示了梯度提升的结果，其准确率高达 80.95%。ML 追踪大气动力学，是天气预报的基础。它使用一种高度发达的方法，使其能够预测天气的复杂趋势。此外，机器学习算法对于从随时间变化的大量复杂数据中检测非线性关系和模式越来越重要。这对气象学家克服与大气动力学相关的不确定性以改进预测至关重要。梯度提升--涉及气象科学和机器学习的跨学科领域中的天气预报视角。目前有关用于天气预报的机器学习的研究非常有用。
{"title":"Accurate weather forecasting with dominant gradient boosting using machine learning","authors":"Suri babu Nuthalapati, Aravind Nuthalapati","doi":"10.30574/ijsra.2024.12.2.1246","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1246","url":null,"abstract":"This Paper examines the interesting topic of weather forecasting using ML. From kaggle.com, there is an extensive list of daily weather records for a Seattle dataset. In this chapter, gradient boosting outcomes are revealed as a result of careful data preparation and thorough examination of several machine learning models such as K-Nearest Neighbors, Support vector machine, Gradient Boosting, XGBOOST, logistic regression, and random forest class Its 80.95% accuracy was outstanding. ML traverses atmospheric dynamics that form a basis for weather predictions. It uses a highly developed method that enables it to predict the complex trends in the weather. In addition, machine learning algorithms are increasingly important for detecting non-linear relationships and patterns from large sets of complex data with time. It is critical for meteorologists in overcoming uncertainties associated with atmospheric dynamics to improve prediction. Gradient Boosting – a weather forecasting perspective in an interdisciplinary landscape involving weather science and machine learning. The current research on ML for weather forecasting has been very useful.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"9 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795913","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}
In language and communication, multimodality refers to using various modes of signification to convey meaning. These modes transcend language to engage with audiences at multiple sensory levels. Over time, communication has evolved to reflect a paradigm shift towards a multimodal perspective. This leads to a complex interplay between different modes of shaping interpretations and constructing meaning in discourse, which has attracted little research. This paper explores the concept of multimodality as used in the television advertisement discourse of Raha premium maize meal, using the Multimodal Discourse Analysis Theory. The objective is to investigate how viewers interpret and perceive different modes of signification employed in the advertisement. A descriptive research design with a qualitative approach is used in the collection and analysis of data. The findings reveal that each mode of signification has a unique role, some of which television viewers hardly denote their meaning. Further, politics, religion, and culture influence the perception of some modes of signification used in the advertisement. We recommend that the advertisements be tailored with modes of signification that resonate with the expectations of television viewers. The findings of this paper are intended to enrich linguistic theory concerning the analysis of the representation of meaning in a text and perceptions of modes of signification used.
{"title":"Multimodality in the television advertisement of Raha premium maize meal","authors":"Jackton Otieno Midigo, Benard Otieno Kodak, David Ogoti Ongarora, Damaris Gechemba Nyakoe","doi":"10.30574/ijsra.2024.12.2.1368","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1368","url":null,"abstract":"In language and communication, multimodality refers to using various modes of signification to convey meaning. These modes transcend language to engage with audiences at multiple sensory levels. Over time, communication has evolved to reflect a paradigm shift towards a multimodal perspective. This leads to a complex interplay between different modes of shaping interpretations and constructing meaning in discourse, which has attracted little research. This paper explores the concept of multimodality as used in the television advertisement discourse of Raha premium maize meal, using the Multimodal Discourse Analysis Theory. The objective is to investigate how viewers interpret and perceive different modes of signification employed in the advertisement. A descriptive research design with a qualitative approach is used in the collection and analysis of data. The findings reveal that each mode of signification has a unique role, some of which television viewers hardly denote their meaning. Further, politics, religion, and culture influence the perception of some modes of signification used in the advertisement. We recommend that the advertisements be tailored with modes of signification that resonate with the expectations of television viewers. The findings of this paper are intended to enrich linguistic theory concerning the analysis of the representation of meaning in a text and perceptions of modes of signification used.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"1 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795987","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.2024.12.2.1259
Harshit Kumar, Harshit Kumar Taneja
In the world of start-ups, private companies with a valuation exceeding $1bn are called “unicorns.” The term was initially meant to symbolize the uniqueness and remarkable growth trend of these highly valued businesses. Furthermore, unicorns have evolved into representatives of creativity and economic vitality, driving the development of new technologies, the creation of jobs, and the generating of money within their ecosystems. This worldwide trend is reflected in the emerging startup culture in India, which has seen an incredible rise in the country in recent years. Notably, startups like Khan Academy, and BYJU have reached multi-billion revenues in the previous years. The ventures are not just profitable but they offer many opportunities and encourage creativity through the use of advanced apps and technology. This has helped the country to become the third largest global home to unicorns after China and America. Using the data collected between 2020 and 2021, this study seeks to explain why these start-ups were so successful. Moreover, this paper analyzes the latest funding, valuations, and comparison of profit and losses for various unicorn companies in different sectors by utilizing several chart visualizations and showing multiple factors contributing to their success. Furthermore, with this comprehensive analysis of unicorns’ financial characteristics and performance measures, this paper will offer insightful information on their sustainability and obstacles to maintaining their unicorn status and for the new startups to rise in this changing and dynamic industry.
{"title":"Exploring the success of Indian unicorns: A study of growth trends and economic impact","authors":"Harshit Kumar, Harshit Kumar Taneja","doi":"10.30574/ijsra.2024.12.2.1259","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1259","url":null,"abstract":"In the world of start-ups, private companies with a valuation exceeding $1bn are called “unicorns.” The term was initially meant to symbolize the uniqueness and remarkable growth trend of these highly valued businesses. Furthermore, unicorns have evolved into representatives of creativity and economic vitality, driving the development of new technologies, the creation of jobs, and the generating of money within their ecosystems. This worldwide trend is reflected in the emerging startup culture in India, which has seen an incredible rise in the country in recent years. Notably, startups like Khan Academy, and BYJU have reached multi-billion revenues in the previous years. The ventures are not just profitable but they offer many opportunities and encourage creativity through the use of advanced apps and technology. This has helped the country to become the third largest global home to unicorns after China and America. Using the data collected between 2020 and 2021, this study seeks to explain why these start-ups were so successful. Moreover, this paper analyzes the latest funding, valuations, and comparison of profit and losses for various unicorn companies in different sectors by utilizing several chart visualizations and showing multiple factors contributing to their success. Furthermore, with this comprehensive analysis of unicorns’ financial characteristics and performance measures, this paper will offer insightful information on their sustainability and obstacles to maintaining their unicorn status and for the new startups to rise in this changing and dynamic industry.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"4 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796013","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.2024.12.2.1258
Dharani Raja Sree B, Sindhu S
Rising incidence related to gluten illness, have gained significant attention and more demand for gluten free diet. This upsurge can be traced not only from the population that suffered from gluten–related disorders but also people who prioritize healthy lifestyles and practicing gluten free diets. The availability of gluten-free bakery products has increased dramatically in the last five years. Typically, conventional wheat products like pastas, breads, crackers and baked goods contain gluten. Nevertheless, numerous gluten-free alternatives exist, utilizing different flours and grains. However, developing an innovative gluten free product with highly acceptable sensory properties is the most challenging task. In addition to its nutritional advantages over regular wheat flour, gluten-free flours have higher levels of protein, fiber, vitamins and minerals. This can lead to bakery products having reduced levels of harmful fats, refined carbohydrates and sugars, making them a better choice for people trying to adopt a diet with a healthy lifestyle. Those who have celiac disease or gluten sensitivity can find a safe substitute that doesn't cause side effects of gluten. Diverse dietary preferences are catered by the bakery industry's increasing awareness of accessibility to gluten- free choices. The size of the market for gluten-free baking offers potential for innovation, technological improvement and adaptation to shifting consumer preferences. Hence, incorporating a range of gluten-free flours into a diet can enhance dietary diversity, which is beneficial for nutrition and overall health. This article reviews the use of gluten free flours in baking.
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Pub Date : 2024-07-30DOI: 10.30574/ijsra.2024.12.2.1269
Md Norul Amin
This research aims to describe the design and construction of a line-following intelligent automobile using the TM4C123GH6PZ microcontroller as the central processing unit. The vehicle uses two MG310P20_7 motors, one motor driver circuit and a 12-gray sensor for propulsion, motor control and line detection. The sensors made the high-accuracy angler movement in tests, the vehicle is 91.85% stabile to follow the line, taking an average of 3.44 seconds to complete a 3-meter road. Therefore, this concept demonstrates how infrared sensors and sophisticated control algorithms can be used to be more stable in creating driverless vehicles.
{"title":"High accuracy line following intelligent car based on infrared sensor","authors":"Md Norul Amin","doi":"10.30574/ijsra.2024.12.2.1269","DOIUrl":"https://doi.org/10.30574/ijsra.2024.12.2.1269","url":null,"abstract":"This research aims to describe the design and construction of a line-following intelligent automobile using the TM4C123GH6PZ microcontroller as the central processing unit. The vehicle uses two MG310P20_7 motors, one motor driver circuit and a 12-gray sensor for propulsion, motor control and line detection. The sensors made the high-accuracy angler movement in tests, the vehicle is 91.85% stabile to follow the line, taking an average of 3.44 seconds to complete a 3-meter road. Therefore, this concept demonstrates how infrared sensors and sophisticated control algorithms can be used to be more stable in creating driverless vehicles.","PeriodicalId":14366,"journal":{"name":"International Journal of Science and Research Archive","volume":"5 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796190","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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