Volume 11 | Issue 4 |

 Abstract

Machine learning has a lot of potential for automated disease diagnosis. The liver is vital to life and promotes the body's ability to rid itself of poisons. Given the increasing increase in numerous chronic liver diseases, a preliminary diagnosis of chronic liver disease is required. With a population of 1.33 billion, India is the second most populous nation in the world, and millions of people are diagnosed with chronic liver disease each year. Jaundice, hepatitis (A, B, C), and non-alcoholic liver disease are a few examples of chronic liver diseases (NAFLD). They are brought on by drinking alcohol, eating tainted food, and other things including obesity. As a result, we would want a system that is trustworthy and capable of forecasting the signs of chronic liver disease. By utilising machine learning algorithms and patient data, this method forecasts Chronic Liver Diseases. Experiments and comparison analyses show that it improves classification accuracy, reduces classification time, and hence contributes in the more accurate prognosis of chronic liver disease. Accuracy, auc score, precision, recall, and f-measure are used to evaluate performance. To categorise liver patients, a variety of classification algorithms are used, and the best model is selected and applied based on the classification report and performance (Liver patient or not liver patient).

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 Keywords

Liver disease, Machine learning algorithm, NAFLD, disease diagnose.

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Microfinance is widely acknowledged as a potent instrument for eradicating poverty and empowering women. This study investigates the effects of microfinance on women's empowerment and poverty reduction in Uttarakhand, a state in northern India. Several sources, including academic publications, internet databases, reports, and governmental websites, were used to gather secondary data. The current study is descriptive in form and offers a critical assessment of several empirical investigations carried out in the Indian state of Uttarakhand. The results imply that microfinance benefits women's empowerment and poverty reduction in Uttarakhand. The microfinance consumers reported higher incomes, better living conditions, and easier access to healthcare and education. Microfinance has also significantly contributed to the empowerment of women by granting them financial independence, enhancing their ability to make decisions, and decreasing gender inequities. The report emphasizes the necessity of maintaining assistance for microfinance organizations to increase their influence on eradicating poverty and empowering women in Uttarakhand.

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 Keywords

microfinance, eradicating poverty, empowering women, and Uttarakhand.

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One of the main reasons for cancer-related fatalities worldwide is lung cancer. For a lung cancer patient to receive a good therapy and have better outcomes, early identification is essential. Lung cancer diagnosis frequently makes use of histopathological pictures of lung tissue. However using histopathological pictures to diagnose lung cancer is difficult since it takes a lot of training and experience. Convolutional Neural Networks (CNNs) are a viable method for spotting lung cancer in histopathology pictures since they have demonstrated great effectiveness in image classification tasks. In this study, we suggest a CNN-based method for detecting lung cancer using the architecture of histopathology images. Our suggested method achieves good accuracy and shows promise for enhancing the precision of lung cancer diagnosis. One of the cancers that claims the most lives globally is lung cancer. For a patient to recover, early detection and treatment are essential. Histopathological images of biopsied tissue from potentially infected lung regions are used by medical practitioners to make diagnoses. The diagnosis of different kinds of lung cancer is frequently laborious and prone to inaccuracy. Convolutional Neural Networks can more accurately identify and categorise different types of lung cancer in a shorter amount of time, which is essential for establishing the best course of treatment for patients and their chance of survival. This study takes into account benign tissue, adenocarcinoma, and squamous cell carcinoma. The accuracy of the CNN model during training and validation is 96.11 and 97.2 percent, respectively.

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Keywords: - Convolutional Neural Network (CNN), Machine Learning, Lung cancer, Histopathological Image

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UWSN faces many challenges in terms of energy consumption and routing. In recent years, energy harvesting has emerged as a promising solution to address the energy consumption issues in the UWSN. It faces many challenges in terms of energy consumption and routing. In recent years, energy harvesting has emerged as a promising solution to address the energy consumption issues in the UWSN. Routing protocols play a crucial role in ensuring efficient communication in the UWSN. In this context, the implementation of a routing protocol that takes into account the energy harvesting capabilities of UWSN nodes is essential to maximizing network lifetime. In general, localized or non-localized deployment techniques can be used to place the sensor nodes in the UWSN and WSN. So far, balancing energy usage has been a difficult problem in both networks. When it comes to UWSN and WSN, inefficient energy use has an impact on network metrics like stability period, node mobility, transmission rate, end-to-end latency,and packet delivery ratio. Most previous routing protocols are based on cooperation and clustering but do not implement an energy harvesting technique at Sensor nodes. Therefore, this research suggests an Analytical Approach towards Reliability with Cooperation for the UWSN's Energy Harvesting (ARCUNEH) Protocol. A modification of the already-proposed ARCUN protocol is called ARCUNEH. The suggested method selects relay nodes from one of their surrounding nodes based on the sensor node's collected vitality level. In UWSN, we directly implement ARCUNEH, while at WSN, we implement the modified EH based on environmental conditions. The ARCUNEH approach combines Piezoelectric Energy Harvesting and the amplifying forwarding (AF) technique at sensor nodes in order to increase the stability and lifetime of sensor nodes at UWSN and WSN. Finally, in this proposed method's simulation, It is compared to both network metrics, including the lifetime of the network, packet delivery ratio, energy consumption, and throughput. According to our simulation study, ARCUNEH performs better than LEACH. According to our simulation study, ARCUNEH performs better than LEACH, ARCUN, and RACE. Hence, both WSN and UWSN network sensor nodes can use the ARCUNEH Energy Harvesting Protocol to collect energy.

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 Keywords

Energy harvesting Algorithms,Energy Efficiency,WSN,UWSN,ARCUNEH

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Cryptography is a process to secure data transmission using Encryption and decryption over the internet. This paper proposed concept to enhance the data encryption and decryption security by using combination of both Cryptography and Steganography techniques. In Cryptography there is used Rivest-Shamir-Adleman (RSA) Algorithm. In Steganography there is used Image Steganography for hiding the data. Through using combination of both cryptography and steganography security of data is increased which is also known as CRYPTO-STEGO Approach. This satisfies all services in Cryptography i.e., Access Control, Confidentiality, Integrity, Authentication. And data can be maintained more securely. There can used RSA for encryption of data and Steganography approach to hide the data in an image so that data can not be accessed by anybody in network and only sender and receiver can retrieve the data from message file.

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 Keywords

RSA Algorithm, Cryptography, Steganography

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Background of the Study: COVID-19 has overwhelmed healthcare services in various nations. Prolonged hypoxemia is a common presentation in patients with severe COVID-19. Several hospitalised COVID-19 patients had ARDS, which requires invasive mechanical breathing and intensive care. Prone position enhances the ventilation/perfusion ratio and recruitment of the dorsal lung segments, resulting in the opening of collapsed dorsal alveoli with enhanced gas exchange and oxygenation. Aim of the study: To examine the effect of prone versus semi-fowler's positions on peak expiratory flow rate and respiratory rate among Post Covid patients treated in LHDM & Dr Prem Hospital, Panipat. Haryana. Research Methodology: This study used true quasi-experimental design. Group 1 was given prone position, while Group 2 was given semi-position. fowler's This study used non-probability purposive sampling. LHDM & Dr Prem Hospital, Panipat post-covid patients provided data. Group 1 received prone positioning, whereas Group 2 received semi-position. fowler's Before situating the individuals in both groups, the researcher examined peak expiratory flow rate and respiratory rate and gave them the prescribed position for 30 minutes. The subjects were asked to maintain the position for 12 hours per day as comfortable. Post-test assessment occurred seven days after positioning. Descriptive and inferential statistics analysed data. Results: Experimental group PEFR values were 525.27 + 38.868 post-test. Control group mean and standard deviation values were 498.87 + 82.582 at post-test. Their mean difference was 428.6 and their paired "t" test value was 26.4 for 58 degrees of freedom. This is substantial at 0.003. Hence, experimental and control group post-test PEFR levels differed. Conclusion: Post-covid patients' PEFR was higher in prone position than semi- fowler's. The researcher recommends prone and semi-for fowler's post-covid patients' respiratory characteristics.

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Prone, Semi-fowler, Post Covid, PEFR,

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Aim of the Study: To assess the effectiveness of modified ABCD bundle on level of ICU psychosis among cardiac post-operative patients in the experimental and control group. Methodology: The research design used in this study was true experimental post-test only design with 60 sample using simple random sampling technique, with 30 each in the experimental and control group. The informed consent was obtained after collecting the demographic data. The patients in the experimental group were administered the modified ABCD bundle. Awakening aspect of orientation was given to the patients during the pre-operative day, whereas the other components were given during the post-operative period. The patients in the control group were administered with hospital routine care.The post-test level of ICU psychosis was assessed using the Intensive care delirium screening checklist. The post-test I was conducted on the 3rd POD and the post-test II was conducted on the 4th POD. Both the post-test levels of ICU psychosis were measured using ICDSC. The data were coded and entered in the main coding sheet. Results: The experimental group's post-test I level of ICU psychosis was 1.20 with SD 1.09. The control group scored 3.23 with SD 1.67. The experimental group had a mean post-test II ICU psychosis score of 0.63 with SD of 0.81, while the control group had 3.06 with SD of 1.74. The student's unpaired t-test showed great statistical significance between the experimental and control groups in post-test I (t = 5.565 at p<0.001), proving that modified ABCD bundle reduced ICU psychos in cardiac post-operative patients. The student's unpaired t test (t=6.944atp<0.001) showed that modified ABCD bundle had sustained substantial impact on ICU psychosis in cardiac post-operative patients. The paired 't' test showed that the experimental group's post-test I and II ICU psychos levels were statistically significant at p<0.001 with t=2.984. The modified ABCD bundle reduced cardiac post-operative ICU psychosis immediately and permanently. The results also showed that the post-test I level of ICU psychosis in the experimental group was associated with gender, marital status, and occupation (p<0.05, p<0.001, and p<0.05, respectively). Male married and skilled employees had sub-syndromal delirium. Conclusion: The findings verified that modified ABCD bundle was very effective in reducing the level of ICU psychos is of patients who under went cardiac surgery and can be used as a non-pharmacological measure to reduce ICU psychos is during ICU stay.

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 Keywords

Assess, Effectiveness, Modified ABCD Bundle, ICU Psychosis, Post Operative Cardiac Patients.

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In this paper, the design and perpetration of SENSEPACK- a smart system to cover room terrain of mushroom civilization ranch is reported. The system measures the temperature, moisture, light and CO2 position with applicable detectors. The attained data can be employed to control the terrain of the nursing room with the help of external bias similar as water pump, exhaust addict, light bulb and air conditioner. An android/ web- grounded operation has been developed for the ease of covering the system. The software operation allows robotization and remote operation of the external bias to maintain and control the optimum environment.

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Mushroom, Cultivation, Android, Raspberry pi, Wireless sensor networks, Sensors, IOT,Monitoring.

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Warehouse management is a critical aspect of logistics operations, and businesses must address various issues to ensure efficient warehouse operations. This research paper examines the key issues faced by warehousing department, including inventory control, space utilization, personnel management, and technology integration. The paper explores the challenges and strategies associated with managing inventory levels, including the use of forecasting and inventory optimization tools. The importance of effective space utilization is discussed, along with strategies for organizing and optimizing warehouse layout. Personnel management is also examined, highlighting the significance of staff training and development to ensure efficient and productive operations. Lastly, the paper explores the impact of technology on warehouse management, including the use of automation and data analytics to improve efficiency and reduce costs. The research concludes that effective warehouse management requires a comprehensive approach that addresses these issues and leverages the latest technologies to optimize operations.

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Inventory control, warehousing department, automation.

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This research paper examines the customer preferences on coupon code based promotional activities in Coimbatore city. This study used primary data collected from survey respondents in Coimbatore city. The survey was conducted by interviewing a total of 100 respondents from the local population. The objective of the study is to analyze the customer preferences on coupon code based promotional activities in the city. The survey results showed that customers are willing to use coupon codes for promotional activities, but they prefer to use them for discounts on products and services. Furthermore, the survey results also showed that customers are more likely to use coupon codes for online purchases, as opposed to offline purchases. In conclusion, the study found that coupon codes are an effective way of increasing sales and customer loyalty, and thus should be incorporated into promotional activities.

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Coupon code, promotional activities, customer preferences, discount.

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