Volume 14, Issue 12, 12 2023 Edition - IJSER Journal Publication

Publication for Volume 14, Issue 12, 12 2023 Edition - IJSER Journal Publication

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Using Technology as an Enabler of Healthcare Facilities []

Currently, pharmacy management systems are focused mainly on receiving electronic prescriptions, documenting prescription dispensing functions, and exchanging claims-based information. As pharmacists provide more clinically based services, pharmacy management systems need to adopt functionality to collect, document, and exchange clinical information. Increasing access to new health technologies leverages the power of mobile communications both in emerging and developed countries, and promises to deliver better health solutions around the globe. This study examines how mobile solutions can help address drugs accessibility challenges so that patients can access drugs without travelling long distances. The World Health Organization’s (WHO) defines health as “a state of complete physical, mental, and social well-being, not merely the absence of disease or infirmity” and it should inform approaches to healthcare as good health largely impacts individuals and the society. For individuals, good health leads to a better quality of life and education, enhancing their ability to find a job and to secure a higher lifetime income. In addition, healthier workers are less frequently absent from the workplace, and lower levels of absenteeism lead to cost savings for companies. For the society as a whole, a healthier citizen reduces pressure on overburdened hospitals, clinics, and medical professionals. By introducing technologies such as mobile health to improve the pharmacy process, the drug accessibility challenges are greatly reduced. A patient will be able to collect their medication without the stress of long distance drives or taking days off from work. An effective, accessible healthcare system is a prerequisite for economic growth and has clear benefits across society. Technology is an increasingly important element in operations management. It may be defined as “anything that replaces routine or repetitive tasks that were previously per-formed by people or which extends (or enhances) the capability of people to do their work”. Merriam-Webster (2016) defines technology as “the practical application of knowledge especially in a particular area” and “a capability given by the practical application of knowledge”.

An integrated MCDM approach for drought vulnerability Assessment in semi-Arid region- Ranipet, Tamil Nadu, India []

Major part of the city of ranipet is used for agricultural purposed and drought can adversely affect it and hence Drought vulnerability assessment is very important for the area. For this past 35 years of rainfall data is used for six stations found for the study area using theissen polygon method. Then three drought index that is SPI (standard precipitation index), RAI (Rainfall anomaly index) and PNPI (percent normal precipitation index) is calculated. Spatial variation maps of the index is prepared in ArcGIS. The next set of data is downloaded from CRU (climatic research unit) website. Potential evapotranspiration, precipitation, wet days and temperature of past 10 years is downloaded and is extracted for our study area in ArcGIS. Now the data calculated is extracted for MCDA ( multi criteria decision analysis) decision matrix for this RAI, PNPI and CRU data maps is placed in a single layer of ArcGIS and with spreading random points the data is extracted in the form of attribute table .In the decision matrix nine parameters are present and for MCDA we have to assign weight to each category this is done with entropy weight now, In MCDM two models is used WPM (weighted product method) WSM (weighted sum method).spatial variation map is prepared from both the models and then with goodness-of-fit statistics the models are validated. The results shows WSM has less percentage error and shows the final drought vulnerability map of the study area.

Big Data Analytics; Prospects in Nigerian Oil and Gas Operations, through Linearized Non-Linear Method by Python Programming Language. []

Nigeria is a significant oil-producing nation whose economy relies significantly on the oil and gas industry. Optimising crude oil profits in Nigeria is essential for the country's continued economic growth and development. The optimisation process analyses the factors influencing crude oil’s revenue, production, and pricing. To maximise crude oil profits in Nigeria, a multifaceted strategy that balances revenue generation and cost management is required. This includes investing in the appropriate areas to maximise profit margins, implementing new technologies and production techniques, and exploring new crude oil export markets. In addition, devising effective optimisation strategies requires comprehending the relationship between revenue, production, oil price, petrol price, gold price, and other pertinent factors. The optimisation process entails a comprehensive analysis of numerous economic and market factors, which necessitated data gathering. These analysis aids were Linear Programming, Design Expert Statistical software and Machine Learning, identifying and analysing data to increase production and pricing efficiency. Nigeria must adopt cost-effective strategies and solutions to enhance production and ensure investments are made in the appropriate areas to maximise profit margins. Optimised revenue was obtained. 21.3Billion Dollars at an optimised crude oil price of $229. The optimal quantity for crude Oil export is 3.016Million barrels per day, optimal oil price should be $ 229.26 per barrel and optimal exchange rate should be Optimal Exchange Rate: 10.95 =N=/$. Of these parameters, increasing oil production is key to Nigerian revenue plans and exchange rate stabilisation. In conclusion, optimising crude oil profit in Nigeria is a crucial process that necessitates a comprehensive analysis of various revenue, production, and pricing influencing factors. Nigeria can leverage its oil and gas resources for economic growth and development by employing a multifaceted strategy and investing in the right areas. The participation of experts and interested parties is crucial to the success of this process.

An Educational Training PowerPoint for Nurses to Assess Increased Anxiety and Depression in Adolescents who Engage in High Usage of Social Media. []

This project was developed using Peplau’s Interpersonal Relations Theory as the theoretical framework to help guide pediatric and pediatric psychiatric nurses on how to assess for increased Anxiety and Depression in Adolescents who engage in high usage of social media use. Social Media has become problematic for adolescents who indulge in content that exposes them to images of unattainable and unhealthy body goals, aggression, sexual content, and violence, to name a few. Adolescence is one of the most impressionable developmental periods, and this content can lead to mental illness into adulthood, leading to poor quality of life.

Privacy-Preserving Techniques for Healthcare Bot Communication: Evaluating Cryptographic Protocols and Data Sharing Mechanisms []

In recent years, there has been a significant surge in the adoption of healthcare bots, driven by the advancements in artificial intelligence, natural language processing, and the Internet of Things (IoT). Healthcare bots have proven to be valuable tools in improving patient engagement, offering personalized medical advice, and optimizing healthcare delivery. However, with this growing reliance on healthcare bots, concerns over data privacy and security have also escalated. Protecting sensitive patient information is paramount to ensure patient trust, regulatory compliance, and the prevention of data breaches. To address these challenges, privacy-preserving techniques are being implemented to safeguard patient data while enabling seamless communication between healthcare bots and relevant data sources. In this article, we delve deeper into privacy-preserving techniques, with a specific focus on cryptographic protocols and data sharing mechanisms, evaluating their significance in the context of healthcare bot communication.

Wall Street – A Gambler’s Paradise; Can Application of Analytical Principles of ‘Turbulence’ Completely Disrupt Wall-Street Trading? []

‘Turbulence’ is a commonly used and easily understood English word. It has universal application in all branches of science and engineering and usage in societal dynamics for its advancement. However, its simplicity vanishes when used in Fluid Science and applied particularly to Aerospace Technology (Ref: Shiva Prasad, B. G., 2012). One could broadly define ‘turbulence’ as fluctuation/s of any dependent parameter/s or variable/s in any system irrespective of its scale (subatomic to cosmic) with respect to its relevant independent variables like space/time. Share price fluctuations seen every day in Wall-Street is a good example of Turbulence (phenomena) signal vary-ing with time. This paper is meant to demonstrate how the physics of fluid turbulence employing signal processing and statistical analysis could be transplanted to other areas like “Wall-Street” Stock Trading for disrupting High Frequency, Programmed and/or Internet Trading.

Breast Cancer Detection & Prediction through Machine Learning []

Data mining play vital role in the prediction and treatment of breast cancer. To enable practitioner decision-making, huge volumes of data is processed with machine learning techniques to produce tools for prediction and accuracy. In this paper, I proposed a prediction model, which is specifically designed for detection and prediction of breast cancer using machine learning algorithms like decision tree classifier, Logistic Regression, Random Forest and SVM algorithms. Machine learning algorithms improves the accuracy and enhances the performance. This paper is an attempt to identify the type of tumour (i.e., benign or malignant), visualise, correlate and categorize different characteristic of data, split the dataset into dependent and independent dataset and eventually split the data into training and testing set thereby increasing the prediction accuracy. With the help of feature scaling and with the use of different models like logistic regression, decision tree, random forest classifier, metrics model an attempt is made to improve the accuracy of training data.

Recent Advances in Reformatsky Reaction and Grignard Reaction on Coumarins and other Uncommon Electrophilic Centre []

The ever increasing large scale isolation of naturally occurring coumarin having diversified skeleton pattern with manifold biological and industrial application throws a challenge for their synthesis. Recent advancement for the synthesis of various derivatives of coumarin through the application of organozinc and organomagnesium reagents well reputed for their high stereo and chemoselectivity are presented in this review

Shortest Path Planning for Wheeled Mobile Robot using Dummy Targets and MATLAB simulations []

In robot navigation, obstacle avoidance is major issue of consideration and if not handled properly can result in enormous losses and permanent damages. This paper presents simple algorithm, with a different technique in obstacle avoidance, for devising the shortest path for the robot navigation, while ensuring utmost safety and task competency in reaching the target. The proposed algorithm assumes the obstacles are 2D, stationary and of different shapes and sizes, embedded by virtual, secure elliptical surrounding. This approach combined with the conventional methodology of employing tangential approach in clockwise/counter clock wise directions and Virtual Force Field (VFF), projects it as hybrid model. The novelty of this method is the introduction of intermittent dummy targets to determine the straight-line segments of the shortest path to the goal.


in a country which continues to increase is directly proportional to the growth in energy needs required by society. Indonesia is the largest energy user in Southeast Asia, namely more than 36% of Southeast Asia's primary energy use. Utilization of the energy used will reduce the increase in production costs for an industry. The use of energy is better known as energy conservation. Energy and exergy analysis based on the first and second laws of thermodynamics is used to analyze the thermal system of industrial units. This can be applied to equipment units in the fertilizer industry to identify sources of inefficiency, determine their location and the amount of exergy destruction that occur. To reduce exergy destruction, this can be done by modifying the operating conditions of the package boiler. The results show that 94.3% of the total exergy destruction from the boiler package is obtained from the evaporator component with a value of 2.7 x 108 kJ/hr Modification of the operating conditions of the evaporator is carried out by reducing Boiler Feed Water (BFW) inlet temperature with ΔT 100C (196 – 116oC). The decrease BFW temperature will increase the amount of required latent heat and reduce the convection heat that will be carried by the flue gas to generate superheated steam. Optimization of the BFW temperature is performed be calculating the flue gas temperature and exergoeconomic analysis. Exergoeconomic analysis is performed by calculating the cost rate of exergy destruction (ĊD,k) and exergoeconomic factor (fk). The results obtained were that the temperature was optimum of BFW is at 161°C which resulted the reduction of exergy destruction of 6,2x106 kJ/hr and resulting difference cost losses based on actual data (196°C) of Rp 1,370,354,743/hr. Exergetic Sustainability Index (ESI) used to demonstrate how reducing a system's environmental impact can be achieved by reducing its exergy consumption (destruction and losses) or increasing its exergetic efficiency. In this research, ESI Value was achieved at 0,918

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