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Application of data analytics principles in healthcare
Information technology has transformed the healthcare field worldwide. In many areas of the healthcare industry, implementations of data analytics tools are commonly used recently. Applying data analytics principles in medical sciences appropriately transforms the mere storage of medical records in to discovery of drugs. Data science and analytics are essential tools because they can help make better decisions when it comes to spending and reducing inefficiencies in healthcare. The proposed model of healthcare data analytics provides a framework to accelerate the adoption and implementation of predictive analytics in healthcare. Healthcare data analytics can be applied to prove formulated hypotheses, test those using standard analytics models and predict patient health conditions. It can be used to classify patients at risk of developing diseases such as diabetes, asthma, and other life-long illnesses. In spite of the challenges faced while applying data science predictive analytics in the healthcare environment, there is an enormous opportunity for its usage in providing quality healthcare for patients. BEIESP. -
Application of Corn Oil Derived Carbon Nano-onions Using Flame Pyrolysis as Durable Catalyst Support for Polymer Electrolyte Membrane Fuel Cells
The reliance of carbon black as catalyst support for Pt in PEM fuel cell has posed a major challenge in its durability as carbon blacks are highly prone to corrosion. As an alternative, CNTs, CNFs, and graphene are explored as catalyst support, however at the expense of tedious synthesis procedure and production cost. So to combat this issue, a facile flame pyrolysis route was adopted to produce carbon nano-onions using eco-friendly corn oil. Further modification in the carbon nano-onions exhibited better corrosion resistance in comparison to carbon black (Vulcan XC-72R). Also, a systematic approach was adopted towards developing a durable electrocatalyst which was designed to withstand harsh fuel cell operating conditions. The electrocatalyst was successfully analyzed using stringent standard testing protocols (< 40% ECSA loss). Among all the electrocatalyst studied, Pt/fOC exhibited only 37.1% loss in electrochemical active surface area (ECSA) after 5000 cycles, thus indicating its excellent durability. A full cell was also constructed with Pt/fOC as cathode electrocatalyst which showed a maximum power density of 365 mW cm?2, comparable to commercial Pt/C (367 mW cm?2). To the best of our knowledge, this is the first study on the application of corn oil derived carbon nano-onions as catalyst support for PEM fuel cells. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Application of CNN and Recurrent Neural Network Method for Osteosarcoma Bone Cancer Detection
The outlook for people with metastatic osteosarcoma at an advanced stage is poor. Osteosarcoma is the most frequent form of bone cancer in children and young adults. There is an urgent need for both advances in treatment tactics and the identification of novel therapeutic targets for osteosarcoma since the disease typically develops resistance to existing treatments. Cancer stem cells, also known as tumor stem cells, have been linked to the development and spread of cancer at multiple points in the disease's progression. Cancer stem cells are linked to treatment resistance and carcinogenesis, and recent studies have demonstrated that osteosarcoma shares these properties. The proposed methodology rests on the three pillars of preprocessing, feature extraction, and model training. During preprocessing, that the proposed approach eliminated isolated highlights to help us zero in on the trustworthy region. They use the wavelet transform and the gray level co-occurrence matrix to extract features. A CNN-RNN technique is used to evaluate the models. In terms of output quality, the proposed technique is superior to both CNN and RNN. 2023 IEEE. -
Application of artificial neural networks in optimizing MPPT control for standalone solar PV system
Increasing demand of power supply and the limited nature of fossil fuel has resulted for the world to focus on renewable energy resources. Solar photovoltaic (PV) energy source being the most easily available, it is considered to have the potential to meet the ever increasing energy demand. Developing an intelligent system with Artificial Neural Networks (ANN) to track the Maximum Power Point (MPP) of a PV Array is being proposed in this paper. The system adopts Radial Basis Function Network (RBFN) architecture to optimize the control of Maximum Power Point Tracking (MPPT) for PV Systems. A PV array has non-linear output characteristics due to the insolation, temperature variations and the optimum operating point needs to be tracked in order to draw maximum power from the system. The output of the intelligent MPPT controller can be used to control the DC/DC converters to achieve maximum efficiency. 2014 IEEE. -
Application of Artificial Intelligence on Smart Tourism Eco Space: An Integrated Approach in Post-COVID-19 Era
The AI-integrated approach in recent times has evolved with innovative techniques and gained much importance in the post-COVID-19 scenario. This chapter extends contemporary and exponential research findings for Smart Tourism Practices and the Application of AI-enabled systems for the Tourism Ecosystem. It highlights for various service segments like hotels, motels, resorts, restaurants, cafes, airlines, and destinations under this large umbrella known as the hospitality sector. Smart tourism eco space capacitates an ICT-enabled system consolidates tourism resources and information technologies. Perhaps, with multiple challenges, a successful implementation of smart tourism approaches empowers and supports a smart system in place. The tourism eco space is highly vulnerable, and this situation in the service sector creates an intense requirement of a comprehensive view of digitally enabled smart tourism eco space with innovative mechanisms to remain contact-free with less human intervention. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Application of Artificial Intelligence in the Supply Chain Finance
Artificial intelligence (AI) has numerous applications in supply chain finance, including the ability to streamline processes, improve decision-making, and reduce costs. This abstract will discuss some of the key ways in which AI is being used in supply chain finance. One major Using AI in the Supply Chain finance is in risk management. By analyzing data from a variety of sources, including historical transaction data and external market data, AI can identify potential risks and suggest strategies for managing them. For example, AI can be used to predict which suppliers are at the greatest risk of financial distress, allowing companies to take proactive measures to minimize the impact of any disruptions. Another key Using AI in the Supply Chain finance is in fraud detection. By analyzing large volumes of data in real-time, AI can spot deviations from the norm that may point to fraud. This can help companies to prevent fraud and minimize losses. AI can also be used to optimize working capital management. By analyzing data on inventory levels, order volumes, and payment terms, AI can help companies to optimize their cash flow and improve their working capital position. For example, AI can help companies to identify opportunities to negotiate more favorable payment terms with suppliers or to optimize their inventory levels to minimize the amount of cash tied up in inventory. Finally, AI can be used to improve supply chain efficiency and reduce costs. By analyzing data on order volumes, shipping times, and other factors, A.I. may aid businesses in identify opportunities to their supply network needs improvement processes and reduce costs. For example, AI can aid businesses in determining opportunities to consolidate shipments or to optimize their routes to reduce transportation costs. Now a days AI has numerous applications in supply chain finance, including risk management, fraud detection, working capital management, and supply chain optimization. By leveraging the power of AI, companies can improve their financial performance, reduce costs, and enhance their overall competitiveness. 2023 IEEE. -
APPLICATION OF ARTIFICIAL INTELLIGENCE IN PHARMACEUTICAL INDUSTRY
Artificial Technology is the blockbuster technology today. Pharmaceutical industry is no exception to the technology onslaught. Pharmaceutical industry adapting to the Artificial Intelligence (AI) to improve the overall performance of the industry processes, through improved efficiency in the operations and reduced lead time in the drug discovery. This is done through AIs ability of scanning huge data to speed up the drug discovery stage by identifying prospective drug candidates through technology like Structure-Based Virtual Screening (SBVS) and Fragment-Based Drug Discovery (FBDD). A nascent drug approach called as drug repurposing is very prospective through AI, and AI makes it possible to integrate nanotechnology, targeted drug development and personalised treatment based on genetic and proteomic data. AI has huge applications in the very important drug development stage of clinical trials. Selection of suitable participants, predicting drug responses will have huge cost reduction with the AI technology. In addition to drug trials, AI is transforming the pharmaceutical marketing process. Personalised communication, predictive sales forecasting, automated content generation and sentiment analysis are some of the possible as of now. These applications make the companies offer tailor made marketing strategies specific to physicians and patients and monitor the brand reputation and bring efficiency in the supply chain. Albeit the potential benefits, adoption of AI fully in the pharmaceutical industry has its own challenges. In the areas of data privacy, regulatory compliance and ethics related to drug testing, AI could face serious challenges. As the technology evolves, AI will have its impact on the pharmaceutical industry offering huge growth opportunities. India could emerge as a potential superpower in the pharmaceutical industry if AI is properly harnessed for industry growth. India can be the pharmacy for the entire world in the coming days if industry finds a way to utilize AI properly. 2024, Indian Pharmaceutical Association. All rights reserved. -
Application of AI-Based Learning in Automated Applications and Soft Computing Mechanisms Applicable in Industries
The term artificial intelligence is used to describe a method through which computers may teach themselves new skills and develop themselves, without the help of humans or any predetermined instructions. Machines are fed data and trained to look for patterns; these patterns are then used as templates for further learning. They get the agency to choose their own actions and alter their habits accordingly. The term soft computing refers to a group of computational techniques that draw inspiration from both AI and natural selection. Solutions to difficult real-world situations that have no simple computer solution are provided, and they are both practical and cost-effective. Soft computing is an area of study in mathematics and computer science that has been around since the early 1990s. The idea for this project sprang from the fact that people can think of solutions that are close to the ones in the actual world. It is via the use of approximations that the science of soft computing is able to solve difficult computational challenges. Industrial automation is used by a diverse variety of industries and companies to improve the effectiveness of their processes by leveraging a number of technology developments. Many routine tasks are being changed by industrial applications. Industrial automation that reduces breakdowns and repairs quickly might help a business save money. 2024 selection and editorial matter, Nidhi Sindhwani, Rohit Anand, A. Shaji George and Digvijay Pandey; individual chapters, the contributors. -
Application of AI in video games to improve game building
Video Games Industry has been welcoming AI like any other industry for various tasks, AI in gaming helps to convey a much more realistic gaming experience, amplify player interaction and satisfaction over extensive periods. Additionally, the gaming industry is utilizing Artificial Intelligence to liberate its staff by making game development automated, quicker, and less expensive. In this work an experiment is described using Deep Neural Network and Statistical techniques for forecasting the location of an object in future frames of a video, it focuses on the engineering phase of the game, the proposed model combines future prediction of object location which helps to build the infinite universe in the videogame without any additional videos frames of the input video or hard coding any scenes to build the scenes further. 2021 IEEE. -
Application of AI in Determining the Strategies for the Startups
Startups face unique challenges in developing viable strategies to create a competitive advantage and achieve long-term success in today's rapid and global business climate. Using tools powered by AI and algorithms, startups may harness massive amounts of data, generate relevant insights, and make intelligent choices across a variety of business processes. The research begins with an examination of the fundamental concepts beneath AI and how they are used in the business sector. It illustrates how organizations may simplify and improve important activities such as market research, customer segmentation, and trend analysis using artificial intelligence (AI), natural language understanding (NLU), as well as predictive analytics. The report also delves into extensive case studies and real-world examples of businesses that have effectively integrated AI into their business decision-making processes. These examples highlight the practical benefits of AI-driven insights that include enhanced resource allocation, customer targeting, as well as operational performance. It highlights the importance of ethical AI methodologies, transparency, and safeguards to ensure unbiased and fair decision-making. Finally, this study demonstrates how AI has the potential to profoundly transform how entrepreneurs design and implement their strategies. By leveraging AI-driven perspectives, startups may handle complex market dynamics with more precision and agility, increasing their chances of enduring and succeeding in a competitive business climate. The study's findings provide a road map for organizations wishing to apply AI in strategic decision-making processes. 2024 IEEE. -
Application Areas, Benefits, and Research Challenges of Converging Blockchain and Machine Learning Techniques
In recent years, machine learning (ML) has become a hot topic of research and application. ML model and huge amount of data growth difficulties still follow ML development. With the lack of new data and constant training, published ML models may soon become obsolete; unscrupulous data contributors may upload incorrectly labelled data, leading to poor training results; and data leakage and abuse are all possible outcomes. These issues can be effectively addressed by using blockchain, a new and rapidly evolving technology. With the advancement of various smart devices and the field of artificial intelligence and machine learning, interdisciplinary collaboration with blockchain technology may be incredibly valuable for future investigations. Collaborative ML and blockchain convergence can be studied here, with emphasis on how these two technologies can be combined and their application areas. On the other hand, look at the existing researchs shortcomings and future enhancements. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. -
Application and challenges of optimization in Internet of Things (IoT)
[No abstract available] -
Applicability of Search Engine Optimization for WordPress (WP) Website
91 percent of online experiences begin with a search, according to the Content Marketing Institute. That is the hunt for an explanation. As a result, search marketing is a critical practice for any businesses looking to grow and improve. Marketers and clients that paid for adverts began researching SEO and SEM at that time. This pursuit plans to give knowledge into the paid and unpaid procedures of search engine marketing (SEM) and what falls under its umbrella including search engine optimization (SEO) and pay per click (PPC). So in this exploration work, we feel the most ideal approach to utilize a web search tool SEM, is such a method of Internet showcasing that incorporates the utilization of web crawler result pages to advance business sites. SEM was earlier used as a protective gadget for anything to be done with the online search marketing field and it was girdled along with SEO. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Apparel shopping styles of young adult consumers in Bangalore /
Indian Journal Of Marketing, Vol.46, Issue 2, pp.267-279, ISSN No: 0973-8703. -
Apparel shopping styles of young adult consumers in Bangalore
Apparels are one of the most frequently purchased product categories where young adults have the authority to make independent buying decisions, and they also become trendsetters and opinion leaders. Understanding this large segment appropriately is crucial for apparel manufacturers and marketers as they promise longevity of market and exert substantial influence on their parents, peers, as well as their own spending. The present study segmented young adult consumers based on their shopping styles towards purchase of apparels and explored the differences in the shopping styles across demographics such as gender, educational levels, and regional background. The respondents for the study were young adults who belonged to the age group of 18 - 25 years residing in Bangalore, India. The variables under study were eight shopping styles adapted from Sproles and Kendall Consumer Style Inventory- CSI (1986). The study revealed that all the eight shopping styles of the CSI were manifested among young adults in Bangalore; however, the predominant shopping style was the Perfectionist/ High Quality Conscious shopping style. Furthermore, significant differences in the shopping styles of young adults across gender, educational levels, and regional background were found. -
Aplicaci obligatoria de las NIIF y relevancia del valor de la informaci contable en la India; [Mandatory IFRS enforcement and value relevance of accounting information in India]
This study investigates the influence of IFRS enforcement on the explanatory power of earnings and book value on the market price in an emerging economy, India over five years that is two years before mandatory IFRS enforcement for 2014-2015 and three years after IFRS enforcement for 2016- 2018. Total 3470 firm-year observations were examined by assembling data from the BSE website and the annual reports of the firms for this purpose. The findings of the study conclude that the financial reporting environment has improved after introducing the IFRS, which was reflected through a strong and significant association between market price and its two dominating variables earnings and book values. However, the findings also suggest that earnings have been stronger and more significant predictors of market price post-IFRS enforcement than book values, which showed a negative association with market price and declined after IFRS enforcement. The study also suffers from diverse constraints similar to previous studies such as limited data sets and years coupled with only two variables and suggests future scope for research in diverse angles where researchers can employ the return model, and add more control variables such as cash flows, leverage, size, growth... 2019 Universidad Nacional Automa de Mico, -
Antiwear performance evaluation of halloysite nanotube (HNT) filled polymer nanocomposites
Polymer nanocomposites containing various types of reinforcements and fillers are oftenly used in applications such as sliding elements in the machine and automotive parts, gear assemblies etc., in which tribological performance parameters viz. friction and wear are the major issues. In this work, the specific wear rate of HNT filler loading (0-4wt %) in Glass-Epoxy nanocomposites fabricated by vacuum bagging technique are evaluated experimentally. For this purpose, the specimens are prepared and tests are conducted as per the ASTM G-99 standard for a number of trials with the assistance of a pin-on-disc machine by varying load and speed values, keeping time and track diameter constant. The results obtained from experiments reveals that reduction in specific wear rate and the amount of material loss is quite significant for HNT loaded specimens when compared with neat sample even at higher operating conditions. This indicates that HNT comprises of hard ceramic elements viz. SiO2 and Al2O3 which eventually enhances the antiwear behaviour of prepared nanocomposites. Finally, a study on wear mechanisms and morphologies are carried out by analyzing the worn surfaces through SEM micrographs. BEIESP. -
Antioxidant Phenolics of Justicia adhatoda L. and Cordia dichotoma Frost. Promote Thrombolytic Activity through Binding to a Serine Protease, Tissue Plasminogen Activator Protein
Background: The tissue plasminogen activator (tPA) protein dissolutes fibrin clots and prevents the disease like thrombosis. The current study aimed to study the tPA-promoting activity of bioactive molecules of Justicia adhatoda L (JA) and Cordia dichotoma Frost (CD). Methods: The phytochemical characterization of methanolic and aqueous extracts of JA and CD stems was performed through qualitative analysis, Fourier-transform infrared spectroscopy (FTIR), and biochemical tests (total phenolic and total flavonoid content [TPC and TFC]). The bioactivity of the extracts was studied through total antioxidant capacity (TAC) and ferric-reducing antioxidant potential (FRAP) assays. Finally, forty phytocompounds from JA and CD were identified from the literature, and in silico molecular docking study was performed to target tPA protein (PDB id 1A5H, Chain A, X-ray diffraction, resolution 2.90 . Results: Various phytochemical classes were identified from extracts, through qualitative and FTIR analysis. TPC and TFC were estimated from the JA and CD extracts within the range of 9.3428.67 mg gallic acid equivalent/100 g of extract weight (EW) and 2.4816.17 mg quercetin equivalent/100 g of EW, respectively. The aqueous extract of CD showed the highest TAC of 14.90 ascorbic acid equivalent (AAE)/100 g of EW, and the methanolic extract of JA had the highest FRAP activity of 27.77 mg AAE/100 g EW. The molecular docking study showed that apigenin 6,8-di-glucopyranoside had the highest binding potential toward the tPA (?9.380 kcal/mol). Conclusion: It can be concluded that antioxidant phytochemicals of JA and CD could promote the tPA activity, thereby promoting thrombolytic activity. Copyright: 2023 Biomedical and Biotechnology Research Journal (BBRJ) -
Antioxidant and antigenotoxic properties of Alpinia galanga, Curcuma amada, and Curcuma caesia
Objective: To compare the antioxidant and anti-genotoxic properties of Alpinia (A.) galanga, Curcuma (C.) amada, and C. caesia. Methods: Cytotoxicity of ethanolic extracts of A. galanga, C. amada, and C. caesia at selected doses was evaluated by trypan blue, MTT, and flow cytometry-based assays. Genotoxicity and anti-genotoxicity (against methyl methanesulfonate, 35 ?M and H2O2, 250 ?M) of these plants were studied by comet assay in human lymphocytes in vitro. Furthermore, DPPH, ABTS, FRAP, lipid peroxidation, and hydroxyl radical scavenging assays were performed to study the antioxidant potentials of the plants. Finally, anti-genotoxic potential of C. amada was validated in Swiss albino mice using comet assay. Phytochemical composition of C. amada was determined by GC/MS and HPLC. Results: The selected doses (2.5, 5, and 10 ?g/mL) of A. galanga, C. amada, and C. caesia were non-toxic by cytotoxicity tests. All three ethanolic extracts of plant rhizomes demonstrated antioxidant and anti-genotoxic properties against methyl methanesulfonate-and H2O2-induced oxidative stress in human peripheral blood lymphocytes in vitro. Multivariate analysis revealed that various antioxidant properties of these extracts in DPPH, ABTS, and FRAP assays were strongly correlated with their total phenolic constituents. C. amada extract conferred protection against cyclophosphamide-induced DNA damage in the bone marrow cells of mice and DNA damage was significantly inhibited by 2.5 mg/kg C. amada extract. Conclusions: C. amada is rich in potentially bioactive molecules and exhibits potent antioxidant activities. Its anti-genotoxicity against cyclophosphamide-induced oxidative stress is also confirmed in this study. 2021 Asian Pacific Journal of Tropical Biomedicine Produced by Wolters Kluwer-Medknow. All rights reserved. -
Antioxidant activities of leaves and fruits of piper nigrum and piper longum
Background and Objectives: Herbs and spices have been used to enhance flavors of food, as well as for their medicinal purposes. Herbs usually contain antioxidant properties. The present study was focused on the importance of the antioxidants present in Piper nigrum and Piper longum widely used by the people of India in their food. Materials and Methods: The methanolic extracts of the leaves and fruits of both Piper nigrum and Piper longum were prepared using soxhlet extraction method. The total phenolic content (TPC) of the plant samples were determined by the Folin-Ciocalteu method. The total flavonoid content (TFC) of the plant was determined. The inhibitory effect of the plant against oxidation by peroxides was evaluated by ferric thiocyanate assay. Results: The highest concentration of phenol was obtained from Piper nigrum leaves. The highest flavonoid content was observed in the Piper nigrum leaves (0.15 mg). The higher reducing potency of the antioxidants was present in the leaves and fruit of Piper nigrum and Piper longum exhibiting their antioxidant properties. The ability of the plant extracts of Piper nigrum and Piper longum against lipid peroxidation was revealed through the efficiency of inhibiting the radicals at a percentage of 58.33, 77.77, 66.66 and 22.22, respectively. Conclusion: From the study it was concluded that leaves and fruits of Piper nigrum and Piper longum have shown high antioxidant properties. So, they are considered to be rich sources of natural antioxidants for food, cosmetic and pharmaceutical industries. 2020 Jobi Xavier and Seju Thomas.