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Magnetic property applications of microwave method prepared zinc ion modified CoAl2O4 nanoparticles
Employing Microwave combustion technique and utilizing L-arginine as fuel pure Cobalt Aluminate and Zn doped Cobalt Aluminate nanoparticles (NPs) were prepared. XRD, DRS-UV, HRSEM and VSM techniques were used to investigate the structural, optical, morphological, and magnetic properties. The average crystallite size is found in the range of 15-24 nm. Elemental confirmation is done by aid of EDX spectra. The band gap values of the produced samples were discovered to be between 2.57 and 2.45 eV. At room temperature, the prepared samples showed diamagnetic magnetic characteristics, which were corroborated by MagnetizationField (MH) hysteresis curves. 2021, S.C. Virtual Company of Phisics S.R.L. All rights reserved. -
The changing paradigm - Gender dimensions of watershed management in Hosadurga Taluk, Chitradurga District, Karnataka, India /
Intenational Journal Of Science And Research, Vol.4, Issue 7, pp.280-285, ISSN No: 2319-7064 (Online). -
Evaluating the performance of machine learning using feature selection methods on dengue dataset
Dengue fever is a mosquito-borne disease transmitted by the bite of an Aedes mosquito infected with a dengue virus. The bites of an infected female Aedes mosquito which gets the virus while feeding on the infected persons blood, transmits the virus to others. Dengue transmission is climate sensitive for several reasons such as temperature, humidity, rainfall, etc. Areas having higher vapor pressure and rainfall rate are most vulnerable to the spreading of the dengue disease. So to find the important features responsible for spreading the dengue we have used the classification algorithms. Machine learning is one of the key methods used in modern day analysis. Many algorithms have been used for medical purposes. Dengue disease is one of the serious contagious diseases. To find the features related to spreading of dengue disease, we have used popular machine learning algorithms. This proposed work focuses on evaluating the performances of the various machine learning techniques like-Random Forest Classifier (RFC), Decision Tree Classifier (DTC) and Linear Support Vector Machine (LSVM). Predictive Mean Matching is applied for preprocessing of the data and percentage split is applied for resampling of the data. Information gain values for each of the attributes are calculated. The attributes are sorted on the basis of information gain values. Feature selection methods (FSMs) such as Forward Selection (FS) and Backward Elimination (BE) are applied to choose the finest subset of the attributes, so that the algorithm runs more efficiently with a lower run time. It also results in the improvement of the accuracy. The attributes selected by the Feature Selection Methods are the main attributes which results in the probable effects of global weather change on human healthiness. BEIESP. -
Exact prediction and consumption of residential electricity power cost hours, daily, weekly, monthly using ant, ML and DL techniques /
Patent Number: 202241055650, Applicant: Dr. S Perumal.
This research describes an unique method for predicting energy consumption based on deep neural networks that can accurately estimate the hourly energy consumption profile of a residential building one day in advance, taking occupancy into account. Providers of energy and utilities can determine the most efficient generation schedule if they have an accurate evaluation of the quantity of energy utilised by houses. A comprehensive review of a number of criteria was undertaken in order to initiate an investigation into the various energy estimation techniques that employ machine learning. -
Artificial intelligence and deep learning based driverless cars to reduce the road accident, death rate using python /
Patent Number: 202221047470, Applicant: Rashel Sarkar.
2% of global deaths each year are caused by automobile accidents. This corresponds to around 3,287 each day, or 1,300,000 per year. 20 million to 50 million people are seriously injured in automobile accidents annually. Why do these recurring problems persist People do make errors. One careless or foolish action is all it takes to transform a safe drive into one that could kill someone. This holds true regardless of whether the driver is preoccupied, intoxicated, or simply careless or irresponsible. In terms of technology, Artificial Intelligence (AI) has always been ahead of the curve. -
Credit card fraud detection using python and machine learning /
Patent Number: 202221047470. Applicant: Pankaj Shambunath Mishra.
Credit Card Fraud Detection Using Python and Machine Learning Abstract: As we are heading towards the digital world cyber security is becoming an essential element of our life. When we talk about security in digital life then the major challenge is to discover the anomalous activities. When we make any transaction while purchasing any product online a big proportion of consumers choose credit cards. The credit limit in credit cards often helps us to making purchases even if we don’t have the funds at that time. But, on the other hand, these features are utilised by cyber attackers. -
Stock market prediction using artificial neural networks in python /
Patent Number: 202231052415, Applicant: Dr. Rashel Sarkar.
When the issue of forecasting time series is mentioned, the reader, listener, or observer instantly considers forecasting stock prices. This should help individuals determine when to sell and when to purchase more. On occasion, we encounter resources that explain how this is possible. Throughout Deep Learning with Python, Chollet cautions against using time series prediction algorithms to estimate market values. You should not attempt to predict how the stock market will behave in the future based on past performance. Due to the design of the martingale system, the present price of a share of stock is the most accurate indicator of its future price (in terms of the error associated with estimation). -
Method of enhancing quality of services in cloud computing environment using load balancer /
Patent Number: 202211006218, Applicant: Dr. Pratibha Giri. -
A smart attendance system and method for permission inventory during the class /
Patent Number: 202111060922, Applicant: Shivani Chaudhry.
A smart attendance system (1). The system (1) comprises a smart lecture stand (2), which having an electronic unit (2A) which is connected to the other smart door, smart bench, and smart chair of the system; a smart bench (3), which having an electronic unit (3A), which is connected to the other smart door, smart stand, and smart chair of the system; a smart chair (4) comprises which having an electronic unit (4A); which is connected to the other smart door, smart bench, and smart stand of the system; a smart door (5) comprises a electronic unit (5A), which is connected to the other smart door, smart bench, and smart chair of the system. -
Credit card fraud detection using python and machine learning /
Patent Number: 202221047470. Applicant: Pankaj Shambunath Mishra.
Credit Card Fraud Detection Using Python and Machine Learning Abstract: As we are heading towards the digital world cyber security is becoming an essential element of our life. When we talk about security in digital life then the major challenge is to discover the anomalous activities. When we make any transaction while purchasing any product online a big proportion of consumers choose credit cards. The credit limit in credit cards often helps us to making purchases even if we don’t have the funds at that time. But, on the other hand, these features are utilised by cyber attackers. -
Stock market prediction using artificial neural networks in python /
Patent Number: 202231052415, Applicant: Dr. Rashel Sarkar.
When the issue of forecasting time series is mentioned, the reader, listener, or observer instantly considers forecasting stock prices. This should help individuals determine when to sell and when to purchase more. On occasion, we encounter resources that explain how this is possible. Throughout Deep Learning with Python, Chollet cautions against using time series prediction algorithms to estimate market values. You should not attempt to predict how the stock market will behave in the future based on past performance. Due to the design of the martingale system, the present price of a share of stock is the most accurate indicator of its future price (in terms of the error associated with estimation). -
Method of enhancing quality of services in cloud computing environment using load balancer /
Patent Number: 202211006218, Applicant: Dr. Pratibha Giri. -
A smart attendance system and method for permission inventory during the class /
Patent Number: 202111060922, Applicant: Shivani Chaudhry.
A smart attendance system (1). The system (1) comprises a smart lecture stand (2), which having an electronic unit (2A) which is connected to the other smart door, smart bench, and smart chair of the system; a smart bench (3), which having an electronic unit (3A), which is connected to the other smart door, smart stand, and smart chair of the system; a smart chair (4) comprises which having an electronic unit (4A); which is connected to the other smart door, smart bench, and smart stand of the system; a smart door (5) comprises a electronic unit (5A), which is connected to the other smart door, smart bench, and smart chair of the system. -
Vehicular Propagation Velocity Forecasting Using Open CV
This work presents a predictive learning driven methodology for recognizing the vehicular velocity. The developed model uses machine vision models to trace and detect vehicular movement in timely manner. It further deploys a machine tested framework for estimation of its velocity on basis of the accumulated information. The technique depends upon a CNN model that is validated with a standardized instances of vehicular scans and corresponding velocity parameters. The proposed model generates good efficiency and robustness in determining velocities across test conditions which encompass various kinds of vehicles and lighting scenarios. An optimal vehicular frequency is noted with heavy-weight vehicles in place in comparison to other vehicles. A mean latency period of 1.25 seconds and an error rate of 0.05 is observed with less road traffic in place. The suggested approach can be of great help in transportation systems, traffic monitoring and enhancing road safety. 2023 IEEE. -
Deprotection induced modulation of excited state intramolecular proton transfer for selective detection of perborate and ammonia
Acetate protected Naphthalene Coupled Benzothiazole (NCB) has been designed and synthesized for selective detection of perborate (BO3) and ammonia (NH3) based on modulation of excited-state intramolecular proton transfer (ESIPT) process by chemodosimetric deacetylation pathway. In presence of nucleophilic species like BO3 and NH3, acetyl group deprotection of NCB resulted ESIPT within the molecule exhibiting a significant enhancement of absorption and emission signals at 425 nm and 472 nm respectively. The emission enhancement of NCB has been observed by 31-folds and 14-folds in presence of BO3 and NH3 respectively. The selectivity and fast sensitivity of NCB have been shown by the lower detection limit (1.32 M for BO3, 1.74 M for NH3 in UVvis study and 0.60 M for BO3 and 4.39 M for NH3 in fluorescence study) and fast response (rate constants: 12.36 s?1 and 5.54 s?1 for BO3 and NH3 respectively). Analytes induced deacetylation pathway of NCB followed by ESIPT has been clearly demonstrated by theoretical calculation. The test strips based on NCB with BO3 and NH3 are fabricated, which can act as a convenient and efficient test kits for both these analytes. In the practical applications, the sensor NCB can be utilized as low cost food spoilage indicator and soil analysis by fluorometric method. 2024 Elsevier B.V. -
Recent Progress on the Development of Chemosensors
Chemosensors are the chemical structures which convert chemical stimuli into responsive form that can be easily detected, such as change of colour, fluorescence, and other electronic signal. Recently, chemosensors development for detection and monitoring of gases has been growing interest due to the significant importance in environmental and biological systems. Subsequently, the development of chemosensors for detection of various gases is considered to be a significant goal in science and among the all gases, carbon dioxide (CO2) is a major public concern due to its role in global greenhouse warming with environmental pollution. Moreover, quite critical level of CO2 in the modern agricultural, food, environmental, oil and chemical industries is dangerous for living beings to survive such high concentration levels of CO2. Therefore, rapid and selective detection and monitoring of CO2 in the gaseous as well as in the liquid phases provides an incentive for development of new methods. The coverage of this book chapter is divided into different sections according to the use of different types of molecular backbones and the detection pathways. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Web Platforms for Fintech Products
Internet marketing and digital marketing are not synonymous in the minds of the majority of the population, yet this may not be true. Given the rise in popularity of digital marketing as a marketing tactic, it is critical to comprehend the distinctions between the two methods. Even while it should be evident that they might be connected, there is very little difference between them. Internet marketing is merely a subclass of digital marketing, as well as the extent of digital marketing encompasses much more than internet marketing. This paper discussed digital marketing technologies, as well as the advantages and disadvantages of employing digital marketing and digital finance tools in general. In order to remain competitive, businesses must overcome obstacles and seize possibilities presented by digital marketing technologies. Lastly, it's critical to prioritise digital marketing and make use of digital finance techniques in order to maintain a good performance without wasting time or money. 2022 IEEE. -
Meta-analysis of EMF-induced pollution by COVID-19 in virtual teaching and learning with an artificial intelligence perspective
Concerns about the health effects of frequent exposure to electromagnetic fields (EMF) emitted from mobile towers and handsets have been raised because of the gradual increase in usage of cell phones and frequent setting up of mobile towers. The present study is targeted to detrimental effects of EMF radiation on various biological systems mainly due to online teaching and learning processes by suppressing the immune system. During the COVID-19 pandemic, the increased usage of internet due to online education and online office leads to more detrimental effects of EMF radiation. Further inculcation of soft computing techniques in EMF radiation has been presented. A literature review focusing on the usage of soft computing techniques in the domain of EMF radiation has been presented in the article. An online survey has been conducted targeting Indian academic stakeholders (specially teachers, students, and parents termed as population in the paper) for analyzing the awareness towards the biohazards of EMF exposure. 2022 IGI Global. All rights reserved. -
An Effecient Approach to Detect Fraud Instagram Accounts Using Supervised ML Algorithms
Nowadays social media plays a vital role in different fields including business, economic communication and personal. Many person get profit from the different origins of availability of data from these social media, but cyber-crimes are increasing day by day. A person can generate many fake accounts and hence pretenders can easily be made. Instagram, as one of the popular types of online social media site, carries big information and messages through the posts. Most of the person use Instagram as a digital life marketing place because it is a one of the big social media site. The goal of the research paper is to recognize and stop fake IDs and pages. Because through the professional pages of Instagram, many fake cases and things are occurring present days. So the main thing is to recognize fake pages and fake accounts also. In this paper, we work on various IDs of Instagram. We want to observe an ID is real or not using Machine Learning techniques namely Logistic Regression, Naive Bayes, Support vector machine, Decision tree, Random Forest. 2022 IEEE. -
ICT Policy Reforms for Innovation and Economic Development: A Comparative Study of India and China
The widespread adoption of Information and Communication Technologies (ICTs) has become essential for economic and social growth across the world. This paper aims to examine the impact of ICT policies and reforms on the level of economic development and adoption of ICTs in two countries, India and China. Previous studies have shown the positive impact of ICT adoption on economic growth, productivity, and innovation. However, the effectiveness of specific policy measures in promoting ICT adoption and economic development remains ambiguous to the users of ICT. This paper presents a comparative analysis of the ICT policies and reforms implemented in India and China from 2010 to 2021 and their impact on GDP per capita and internet usage. The study aims to identify and analyze the key ICT policies and reforms implemented in the two countries and examine their impact on economic development. The data for this study have been collected from the World Bank indicators database. The sample consists of the two fastest-growing economies in the world, India and China. The data analysis involves conducting descriptive statistics, correlation, and regression analysis to examine the relationship between ICT policies and reforms and their impact on GDP per capita, internet usage, and research and development expenditure. The findings of this study will contribute to the existing literature on the relationship between ICTs and economic development and provide insights into the policy measures that can promote ICT adoption and economic growth in different contexts. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.