Volume 9 | Issue 8 |

 Abstract

Fuzzy logic controller is a multiple valued logic in which input space is mapped with output space with help of rules. In this study, semi-active suspension is developed using Fuzzy Logic. The proposed system is simulated using MATLAB/Simulink. A 4 degree of freedom half car model is formulated. Two road inputs are used to simulate the system. A Fuzzy Logic controller is designed to vary the damping coefficient of the system in real time. Body acceleration, tyre load variation and suspension deflection are assessed in the simulation. The results simulated with fuzzy logic controller are compared with the passive suspension. According to the comparison, it is noted that semi active system gives better results than the conventional system.

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 Keywords

Half car Model, Semi-active Suspension, Fuzzy Logic Controller, Mathematical Model

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The world is reworking in a digital era. However, the field of medicine was quite repulsive to technology. Recently, the advent of newer technologies like machine learning has catalyzed its adoption into healthcare. The blending of technology and medicine is facilitating a wealth of innovation that continues to improve lives. With the realm of possibility, machine learning is discovering various trends in a dataset and it is globally practiced in various medical conditions to predict the results, diagnose, analyze, treat, and recover. Machine Learning is aiding a lot to fight the battle against Covid-19. For instance, a face scanner that uses ML is used to detect whether a person has a fever or not. Similarly, the data from wearable technology like Apple Watch and Fit bit can be used to detect the changes in resting heart rate patterns which help in detecting corona virus. According to a study by the Hindustan Times, the number of cases is rapidly increasing. Careful risk assessments should identify hotspots and clusters, and continued efforts should be made to further strengthen capacities to respond, especially at sub-national levels. The core public health measures for the Covid-19 response remain, rapidly detect, test, isolate, treat, and trace all contacts. The work presented in this paper represents the system that predicts the number of corona virus cases in the upcoming days as well as the possibility of the infection in a particular person based on the symptoms. The work focuses on Linear Regression and SVM models for predicting the curve of active cases. SVM is least affected by noisy data, and it is not prone to over fitting. To diagnose a person our application has a certain question that needs to be answered. Based on this, the KNN model provides the maximum likelihood result of a person being infected or not. Tracking and monitoring in the course of such pandemic help us to be prepared.

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 Keywords

Covid-19 Symptoms, Plasma Recommendation, SVM, KNN, Linear Regression Algorithms.

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 Abstract

Lactobacillus in Amla drinks with the aim of formulation of probiotic drink and to analyse the nutritive value and self life of the product.Lactobacillus was capable of growing 15 percentage Amla drink at natural pH 30 degree Celsius . Microbial population pH and organic acid metabolism were measured during the fermentation period and the viability of all strains was also determined during the storage 4 degree Celsius with 4 weeks.The result indicated that Lactobacillus increased the pH at the initial stage .Amla drink could be stored at refrigerated condition for 30 days.Amla juice proved to be a suitable media for production of a fermented probiotic drink.

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 Keywords

Lactobacillus,Amla, fermentation, probiotic, microbial activity .

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 Abstract

Recent years have witnessed the rapidly-growing business of ride-on-demand (RoD) services such as Uber, Lyft, and Didi. Unlike taxi services, these emerging transportation services use dynamic pricing to manipulate the supply and demand and to improve service responsiveness and quality. Despite this, on the drivers' side, dynamic pricing creates a new problem: how to seek passengers in order to earn more under the new pricing scheme. Seeking strategies have been studied extensively in traditional taxi service, but in RoD service such studies are still rare and require the consideration of more factors such as dynamic prices, the status of other transportation services, etc. We develop ROD-Revenue, aiming to mine the relationship between driver revenue and factors relevant to seeking strategies and to predict driver revenue given features extracted from multi-source urban data. We extract basic features from multiple datasets, including RoD service, taxi service, POI information, and the availability of public transportation services, and then construct composite features from basic features in a product form. The desired relationship is learned from a linear regression model with basic features and high-dimensional composite features. The linear model is chosen for its interpretability to quantitatively explain the desired relationship. Finally, we evaluate our model by predicting drivers' revenue.

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 Keywords

Taxi Revenue Prediction, Forecasting, SVM, KNN, CNN Algorithm

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Title: A study to assess the effectiveness of structured teaching programme on knowledge of mothers regarding behavioural problems among pre-schoolers in Anganwadi centres of district Ganderbal, Kashmir. Objectives: To assess the effectiveness of structured teaching programme on knowledge of mothers regarding behavioural problems among preschoolers. Materials and Methods: A Quantitative approach with one group pre-test and post-test pre-experimental design was used. With the purposive sampling 50 study participants were selected. Tool used in this study included two sections, Section-I including demographic Performa of mothers such as age, occupation, education, monthly income, type of family and number of children. Section-II including Structured Interview schedule consisted of 40 items/questions. It was further divided into six parts to assess the knowledge of mothers regarding behavioural problems among preschoolers such as temper tantrum, thumb sucking, pica, bed-wetting and school phobia. STP was administered after conducting pre-test and post-test was conducted on 7th day of intervention. Data was analyzed by using descriptive and inferential statistical technique. Result: The data analysis revealed that majority of the study subjects 56% had moderate knowledge in post-test whereas in pre-test majority of study subjects 88% had inadequate knowledge. Conclusion: The study concluded that the structured teaching programme(STP) was effective in increasing the knowledge of mothers regarding behavioural problems among preschoolers.

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 Keywords

Effectiveness, STP, Knowledge, Preschooler, Behavioural Problem.

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 Abstract

Embedded systems help humans to live a convenient life. Most of the devices employed are altered to work smart for the requirements of humans. Embedded systems are most popularly used in the field of electronics, aviation, communication, health care, home appliances, and many more. With the increasing use of the embedded system devices in our day-to-day lives, security threats have also risen at a corresponding rate. However, assuring security in the embedded systems has become an extreme challenge for the embedded device professionals and the manufacturers of products. Security is always becoming a huge concern to the embedded system due to its drawbacks like power constraint, processing power, and cost. The latest trend of integrating the embedded systems with the internet introduces various vulnerabilities and exposes the attack surface of the embedded system. Incorporating networking capabilities may raise multiple attacks such as packet injection, Man In The Middle (MITM) attacks, and replay attacks. Hence, the security of these systems is very crucial to the sellers and consumers. Internet of Things (IoT) technology helps humans to live a life with quality and comfort. IoT has contributed significantly to various application areas. The extensive development of smart electronic devices and their data transmission protocol using wireless mechanics boost their vulnerability to various cybercrime and attacks. Consequently, the rate of cybercrime is rising every day. Hence, the study of embedded and IoT system security threats and respective counteractive measures can benefit security researchers in identifying proper solutions to face the enormous challenges in cybercrime investigation. IoT forensics plays a vital role in the investigation of cybercrimes. Numerous security issues at each layer in the embedded systems and internet of things (IoT) are also discussed briefly. In this paper, the vulnerabilities and threats present in the embedded systems and internet of things (IoT) are discussed, along with the countermeasures for mitigating those attacks.

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 Keywords

Embedded systems, Internet of Things (IoT), Cybercrime, Cyberattack, Security Threats, Countermeasures.

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 Abstract

The increasing usage of digitally enabled frames and the Internet of Things has resulted in a wealth of knowledge and a diversity of structures. The environment or document frameworks presented by Hadoop are utilised in most enormous data arrangements (HDFS). In any case, the reflectors showed weaknesses in such frameworks in the maintenance of current data. While some research has resolved these concerns for explicit diagram data variants, existing data are based on reasonable data. Studies show that productivity concerns lead to significant scope problems, such as increased space in server farms and waste in assets (such as the use of force), leading to ecological problems (such as more fuel byproduct) [1]. We propose a Hadoop Eco-Focus module that is information-rich. Also, we propose a genetic algorithm encoding strategy that uses circulating encoding. Our architecture enables Hadoop to manage data distribution and organization, as well as conduct group analysis on subsets of data. Even when improvement time and use of assets are involved, we can manage a wide range of data types. We have tested our assumptions on a number of LUBM datasets.

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 Keywords

Strategies for clustering, Distributed computing, Information Management and Management, Optimization and Scalability

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The extreme flexibility of digital imaging supports a wide range of linear and non-linear processes. The results of this processing are displayed as visualization, intensity and geometric processing, spatial frequency processing, and image analysis. Briefly explained how to perform image processing effectively. Vision is an important source of human information. It was impossible before, but because of the development of new technologies, it has become possible. The image processing also affects communication equipment. Through digital image processing, we can enhance the image, extract text from the image, define the edges of the image, and apply other effects. There are many digital imaging applications. In practice, this method is used in all fields, including investigations in medicine, robotics, neural networks, and criminal industries.

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 Keywords

Digital, Image, Information, Process, Technology, Recognition

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Religion biological

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition