Advancement in filtration techniques of air purifier
The air purifier industry has seen growth in terms of demand and sales. All credit goes to massive industrialization in developing and developed countries. As a result, a lot of research has been focused on the various methods of purifying the air. The effect of air pollution on health is complex and their individual impact varies from one another. It is not only the ambient air quality in the cities but also the indoor air quality in the rural and urban areas that are causing concern. In fact, in the developing world, the highest air pollution explosion occurs in an indoor environment. This paper deals with a sterilizer that integrates multiple layers of filtration, purification, sterilization, and air freshening. This air sterilizer consists of multiple layers of filters. It is capable of purifying indoor pollutants like particulate matter PM1.0, PM2.5, microparticles, smoke, the peculiar smell in the air and reduces hazardous materials such as benzene, amici, fungi, molds, and formaldehyde, etc. also at the same time it can kill bacilli and organic substances in the air. It also destroys air-borne viruses and infecting germs like TB, Influenza, Dengue, Allergies, etc.
Published by: Rima Nandurkar, Pallav Kumar Gopal
Author: Rima Nandurkar
Paper ID: V7I4-1685
Paper Status: published
Published: August 9, 2021
Forensic podiatry evidence and admissibility in court
Daubert standard is a set of criteria used to determine whether expert testimony is admissibility in Court. Under the Daubert standard, the trial judge serves a role as the “gatekeeper” who determines whether expert testimony is considered reputable and relevant. Similarly, the judge employs a Dubert test to verify whether the testimony of the expert is based on scientifically valid reasoning and whether it has been properly applied to the facts of the issue [1][2]. The procedure of scientific examination that fails to comply with the Daubert standard may result in the rejection of any expert testimony in the court. In the matter of footwear impression evidence examination, the evidence of footwear impression identification was first accepted in court in 1786 in the Richardson case at Kirkcudbright in Scotland [3]. Footwear impression evidence has been accepted in the US Court since the 1930s. The techniques and methods used in footwear evidence examination are widely accepted in several forensic science communities and the ACE-V methods have been described in numerous forensic journals, books, and seminars around the world. Evidence of footwear impression is regularly accepted in courts in the United States, Canada, and Europe as well as other many countries in the world but so far several Indian courts have ruled that the footprint and footwear impression evidence is a “rudimentary science” and they cannot be safely relied upon. [4][5][6]
Published by: Harendra Nath Singh
Author: Harendra Nath Singh
Paper ID: V7I4-1721
Paper Status: published
Published: August 9, 2021
A speculation technique for the stock market using time series
Using ARIMA (Auto-Regressive Integrated Moving Average) which is a model, this research study presents a method for anticipating stock market values. To begin, historical stock price data is gathered and pre-processed. Pre-processing is a subcategory of Data Mining in which raw original data is processed into a specified format so that the model can use it. Pre-processing is done to fill in the missing values and arrange the data based on the qualities required for developing the prediction model because the raw data to be processed is partly partial or inconsistent with certain errors and missing values. After the data has been filtered and classified, it is standardized by transforming it into a common format that can be used to train the prediction model. The obtained data is then divided into two data - training and testing data, with the majority of the data being used to train the model. And using the variables linked with the stock price, the testing data is fed to the ARIMA model to predict the corresponding stock price on a particular date. The results are used to determine the model's accuracy.
Published by: Rajesh K. S., B. S. Darshith, Amaresh A. Channad, Amaresh R. Vasisth, G. Jayavardhan
Author: Rajesh K. S.
Paper ID: V7I4-1715
Paper Status: published
Published: August 9, 2021
Anomaly detection in pharmaceutical pills using image processing
There are various kinds of technologies available in the market for categorizing and packaging in the production line. Our project here discusses various image processing techniques and their shortcomings in the process. Our aim is to categorize the defective tablets based on their color shape missing tablets, color changes due to oxidation. The images of the tablet strip are captured using the camera. The features are extracted for a defect-less tablet strip. The input image is compared with the reference image present in the database, the amount of features that can be compared with the pre-loaded reference image is compared for a threshold value and is discarded if found to be less by separating them, and rest are allowed to pass for packaging.
Published by: Kaushik T. S., Chandan Prasad, Prajwal V., Dr. Manjula A. V.
Author: Kaushik T. S.
Paper ID: V7I4-1717
Paper Status: published
Published: August 9, 2021
Asthma prediction using Machine Learning
Patient telemonitoring brings about a conglomeration of huge measures of data about quiet illness direction. Notwithstanding, the possible utilization of this data for the early expectation of asthma in grown-ups has not been methodically assessed. The point of this examination was to investigate the information for building AI calculations that anticipate asthma before they happen. The investigation dataset involved 278847 records presented by grown-up asthma patients. Prescient displaying included readiness of preparing informational indexes, prescient component choice, and assessment of coming about classifiers. AI classifiers are utilized to foster these prescient models; including Random Forest, Logistic Regression, Decision Tree, and Naïve Bayes strategy. Of the multitude of classifiers carried out, strategic relapse classifier brought about the most elevated expectation precision. Our investigation showed that AI methods have huge potential in creating customized choice help for ongoing illness telemonitoring frameworks. Future examinations may profit with a far-reaching prescient system that consolidates information with different elements influencing the probability of creating asthma. Approaches carried out for cutting edge asthma expectations might be stretched out to early mediation of persistent ailments in patients
Published by: Manasa G. V. Kumar, Yogesh R, Soumya ranjan nayak, Vinod R, Shreyas M S
Author: Manasa G. V. Kumar
Paper ID: V7I4-1680
Paper Status: published
Published: August 9, 2021
Electronic Voting Machine Based on IRIS Authentication
In every election, the commission is facing plenty of troubles and problems throughout the election. The foremost and familiar issue faced by the commission is inappropriate confirmation with relevance to the arrangement of casting the votes, duplication or illegal casting of votes. In this paper, a secure and new electoral system is developed to enhance the present legal system using iris recognition. Iris, one amongst the foremost secure biometric of person identification. The counting of vote is going to be immediately which makes voting process efficient, fast, and secure. There by can reduce the proxies drained the election system or electoral system and elect the right candidates as rulers. All details are updated to web server through IOT. The main goal of this article is to avoid duplication of casting votes.
Published by: M. K. Sivaranjani, S.Santhiya, S.Swathika, P.Ramya, G.Mohanavel
Author: M. K. Sivaranjani
Paper ID: V7I4-1700
Paper Status: published
Published: August 9, 2021
