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Archives of International Journal of Advanced Innovative Technology in Engineering(IJAITE)

Volume 6 Issue 5 September 2021



1. Intrusion Detection System over Big Data

AUTHOR NAME : Ashish Kokate, Prof. M. K. Nichat

ABSTRACT : Network security is a paramount concern for the organization. To secure the network, we have traditional network intrusion detection systems and firewalls but they have limitations like the size of training data sets. With the inception of Hadoop technology, in industry, recently researchers have started using this new technology with traditional machine learning algorithms which generally uses pattern matching, to design and develop network intrusion detection system based on streaming of big-data using Hadoop that checks for intrusions in a massive amount of data that flows in and out. In this paper, we are presenting a study and analysis of various Hadoop-based network intrusion systems. Here the parameters used for comparison are detection rate and false-positive alarm rate.

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2. Design & Implementation of IoT Based Digital Notice Board using HD-W03 Wi-Fi Series Control Card

AUTHOR NAME : Prof. Pravin Balbudhe, Arti Patle, Sujata Rahangdale, Arti Waghmare, Arti Nandekar, Vishakha Katole, Mayuri Meshram, Roshani Raseker, Nikita Dandekar, Bharti Dhore

ABSTRACT : Now a days the notice board is used widely in an extreme way. These notice boards can be used in many places like educational institutions, stations, etc. to display notices or some information to the people who need it. As technology was increasing day by day, its use was also increasing. So, a traditional notice board can be replaced with a digital notice board that means the conversion of analog to digital systems including Wi-Fi systems. Our project is mainly based on the Wi-Fi module. The objective of our project is to design a dot-matrix moving message display using controller and IOT where the characters shift from left to write continuously. In this project we have used One controller HD-W03 WI-FI Series control card, which is a low cost, high cost-effective single color Wi-Fi controller, easy to operate, better display information, supports various kinds of single-color display. For the door lintel screen, store screen and other places information display. FRC Cable - 16 Pin (16 Wire) - 12 inches (Flat Ribbon Cable)- FRC is an ideal way to connect two devices digitally, Two Power Supply- The purpose of a power supply is to convert the power delivered to its input by the sinusoidally alternating mains electricity supply into the power available at its output in the form of a smooth and constant direct voltage, and finally, we used Four 16*32 LED dot matrix display module -which is also known as P10 LED Display Module to display a scrolling text by using HD-W03 Wi-Fi series control card. This project is regarding an advanced wireless notice board. The main objective of the project is to develop a wireless notice board that displays messages sent from the users mobile application.

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3. Study of Mental Disorder Detection Based on Machine Learning Techniques

AUTHOR NAME : Pramod Shirbhau, Prof. A. A. Bhuyar

ABSTRACT : The explosive growth in popularity of social networking leads to problematic usage. An increasing number of social network mental disorders (SNMDs), such as Cyber-Relationship Addiction, Information Overload, and Net Compulsion, have been recently noted. Symptoms of these mental disorders are usually observed passively today, resulting in delayed clinical intervention. In this paper, we argue that mining online social behavior provides an opportunity to actively identify SNMDs at an early stage. It is challenging to detect SNMDs because the mental status cannot be directly observed from online social activity logs. This paper presented the latest studies that indicate a relationship between mental health and the actions of the social network and how mental illness and social networks respond to each other is still unclear. This paper attempts to use the data analysis of social network research to find a pattern for mental disorders without consulting the patient based on machine learning algorithms.

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4. Study on Online Examination System based on Text Mining

AUTHOR NAME : Pooja J. Shinde, Prof. P. V. Kale

ABSTRACT : In a traditional Online Examination System, only objective-type questions are assessed and according to those marks are given to the student. However, this technique lacks the capability of evaluating descriptive answers. In university examinations, there are many types of questions included for the evaluation of the students. Therefore, the automated system must be capable of evaluating the descriptive answers. The online examination system checks the students answer by matching the answer with a predefined set of answers. The predefined answers are saved on the server and evaluation is done automatically using the automatic assessment tools. Here the machine learning approach is used to solve this problem using text mining. Measuring the similarity between, sentences, words, documents, and paragraphs is an important component in various tasks such as text summarization, information retrieval, automatic essay scoring, document clustering, and machine translation, and word-sense disambiguation. In this system JSON is used for transferring data between web application and server, serving as an alternative to XML.

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5. Detection of Diabetic Retinopathy Using Machine Learning

AUTHOR NAME : Akshara Mehere, Prof. P. P. Pawade

ABSTRACT : The objective of this paper is to perform a survey of different kinds of literature where a comprehensive study on Diabetic Retinopathy (DR) is done and different Machine learning techniques are used to detect DR. Diabetic Retinopathy (DR) is an eye disease in humans with diabetes which may harm the retina of the eye and may cause total visual impairment. Therefore, it is critical to detect diabetic retinopathy in the early phase to avoid blindness in humans. Our aim is to detect the presence of diabetic retinopathy by applying machine learning classifying algorithms. Hence, we try and summarize the various models and techniques used along with methodologies used by them and analyze the accuracies and results. It will give us the exactness of which algorithm will be appropriate and more accurate for prediction.

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6. Review on Motorcycle Helmet & Its Material

AUTHOR NAME : Milind A. Wahile, Prof. M. J. Watane

ABSTRACT : Helmet attempt to protect the user’s head by absorbing mechanical energy and protecting against penetration. Every year many people or riders are killed or seriously injured in accidents as a result of head injuries. Wearing an appropriate safety helmet significantly reduces the risk of injury or even death. Protective headwear could save your life. In this paper, a review of different materials used for designing a motorcycle helmet for improved thermal comfort, visibility, safety with adjustable interior form considering rider’s ergonomics with various materials has been studied.

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7. Study On Prediction of Skin Cancer Based on Machine Learning Techniques

AUTHOR NAME : Mohini G. Muthal, Dr. A. B. Gadicha

ABSTRACT : Skin cancers are the most common forms of human malignancies in fair-skinned populations. Although malignant melanoma is the form of skin cancer with the highest mortality, non-melanoma skin cancers (basal cell carcinomas and squamous cell carcinomas, etc.) are far more common. The incidence of both melanoma and non-melanoma skin cancers is increasing, with the number of cases being diagnosed doubling approximately every 15 years. In this manner, the early finding of skin cancer can diminish the mortality and dreariness of patients. In this paper, we are investigating various machine learning techniques for early-stage skin cancer detection.

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