Panimalar Engineering College
Master of Business Administration
The chilli wastes were considered separately using four bacteria for enhancement, including Fischerella muscicola, Anabaena variabilis, Aulosira fertilissima, and Tolypothrix tenuis, and combined mixture. Inoculated F. muscicola chilli... more
The chilli wastes were considered separately using four bacteria for enhancement, including Fischerella muscicola, Anabaena variabilis, Aulosira fertilissima, and Tolypothrix tenuis, and combined mixture. Inoculated F. muscicola chilli wastes had highest NPK concentration of 0.4 percent (w/w), 0.18 percent (w/w), and 0.15 percent (w/w). For producing the brinjal plant, biomanure is utilised as a replacement for inorganic fertilizers and sprayed to a soil at a rate of 20 t ha-1. The report's findings suggest that enhanced chilli wastes could be utilised as a fertilisers replacement to increase soil quality and enhanced plant.
- by Suresh Kumar k.
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Nowadays, a rising number of individuals use online social networks, e-commerce, and applications to not only socialize and engage, but also to express their ideas. Deep Learning is an area of machine learning dealing with neural... more
Nowadays, a rising number of individuals use online social networks, e-commerce, and applications to not only socialize and engage, but also to express their ideas. Deep Learning is an area of machine learning dealing with neural representations of procedures, most frequently shown as neural networks, neural beliefs, and so on. When evaluating sentiments for a given datasets, it is critical to choose the most practical and precise approach possible because this impacts both buyers and sellers. Deep Learning (DL) approaches have been used to identify important data and make recommendations from enormous data sets. The effectiveness and results of various deep learning techniques may change based on the data sets utilized, as well as the techniques' appropriateness to the information and applications domains under discussion. To meet this demand, a comparative examination of well-known deep learning techniques was conducted. E-commerce was the first business to capitalize on the advantages of Deep Learning (DL). Firms now have whole DL departments, which is not uncommon. Because digital transactions have become the usual means of acquiring products and services, top E-commerce businesses are investigating how DL may improve customer satisfaction and company profitability. The idea is that they contain a massive volume of information, and making use of that information is difficult. E-commerce firms spend a lot of money to automating tedious procedures, enhance the customer experiences, tailor offers for specific customers, and gain a deeper understanding of their customers.
- by Suresh Kumar k. and +1
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In this study, a brief detailed description of the significance of Artificial intelligence (AI) and machine learning (ML) in businesses are described. AI is the emerging trend and technology of the modern world and provides various... more
In this study, a brief detailed description of the significance of Artificial intelligence (AI) and machine learning (ML) in businesses are described. AI is the emerging trend and technology of the modern world and provides various benefits to firms. AI and ML reduce the overall cost of the business operations and save the money of the organization. It also helps the businesses to make smarter decisions in the business processes and also able to provide solutions to the business problems effectively. The chat bots developed on the basis of AI can communicate with the customers anytime 24/7 and solve the queries of the customers regarding any product or business. ML creates opportunities for businesses based on business operations and also makes the process fully automated. In addition to this, the ML also improves the cognitive engagement between customers and employees effectively and provides solutions to problems of customers like password issues and many others. Along with that, the study also contains the methods and techniques used for the completion of the study. The researcher has used the secondary qualitative and quantitative data collection methods in this study. In order to implement AI and ML in business operations, companies need to understand the augmentation and automation process.
- by Suresh Kumar k.
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This paper explores the integration of AI and wireless multimedia communication in supply chain economic risk management. The advancements in technology, specifically AI and wireless multimedia communication, have revolutionized the way... more
This paper explores the integration of AI and wireless multimedia communication in supply chain economic risk management. The advancements in technology, specifically AI and wireless multimedia communication, have revolutionized the way supply chain risks are managed. Economic risks in the supply chain are increasing due to the complexities and uncertainties in global trade. The role of technology, particularly AI, has proven to be a valuable tool in mitigating supply chain risks. Wireless multimedia communication also enhances the efficiency of the supply chain by facilitating real-time communication and collaboration among stakeholders. This paper examines the challenges of implementing AI in supply chain risk management, including data integration and security, as well as the benefits of wireless multimedia communication in improving supply chain visibility and agility. The integration of AI and wireless multimedia communication can provide a powerful toolset for supply chain economic risk management. By leveraging advanced analytics and real-time communication, supply chain managers can reduce their exposure to economic risks and improve overall supply chain efficiency. This paper concludes that the integration of AI and wireless multimedia communication is critical for managing economic risks in the supply chain, and its use will become increasingly important as supply chains continue to become more complex.
- by Suresh Kumar k. and +1
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