IJSRET Volume 9 Issue 2, Mar-Apr-2023


Review of Improvement and Prevent Bridges from Contributing to the Nation’s Supply Chain Problem
Authors:- Kailash Nath Bhagat, Prof. Shashikant B. Dhobale

Abstract- Successful highway transportation must address three areas of consideration: (1) creative and aesthetic, (2) analytical, and (3) technical and practical considerations. Given that most bridge transportation today are performed by multidisciplinary teams, addressing the first two considerations is fairly easy to achieve. The last is often the most challenging. This WORK discusses the practical challenges associated in the selection of Highway Bridge, the bridge types that are available for use and their range of applicability, the methods of analysis used, the dominant Supply in use today, and, finally, an example based on the AI of a bridge design following the practical considerations given here.

Image Classification for Dogs and Cats Using CNN
Authors:- Arnav Bhargava, Kunal Paliwal, Komarsamy.G

Abstract- Image classification is an important task in computer vision and has a wide range of applications. In this project, we have developed a deep learning model using Convolutional Neural Networks (CNN) to classify images of dogs and cats. The model was trained on the Cats and Dogs dataset available on Kaggle, which consists of 25,000 images of cats and dogs.

Secured Sim Ejection
Authors:- Sahaya Joseph Rohan.A, Sengodan.D, Kavin Kumar.S, Eswanth Raj.S

Abstract- A SIM card, also known as a subscriber identity module, is a smart card that stores identification information that pinpoints a smartphone to a specific mobile network. Data that SIM cards contain include user identity, location and phone number, network authorization data, personal security keys, contact lists and stored text messages. SIM cards allow a mobile user to use this data and the features that come with them. We all use sim card but without the knowledge about the consequences of losing a sim card. Once we lose a sim card, we let it free and move on to another sim card. Have you ever wondered that our sim stores a lot of data but what if it goes to someone’s hand, all our personal details are leaked and there are even chances of selling them in the dark web? By applying this project, it is easy to avoid the circumstances of losing a sim card. We don’t have a proper protection for our sim card. It can be easily inserted and also easily ejected. Understand that you are in a danger if you have lost your sim card. But this is not going to happen again. This project fully focusses on securing the sim card by giving utmost protection to the sim card. This involves a security page to be authenticated if someone needs to eject the sim. Sim Ejection wouldn’t be easier after the implementation of this project.

A Review of Facial Expression Recognition using Machine Learning
Authors:- M.Tech. Scholar Poonam Gujre, Asst. Prof. Sudha Sharma, HOD. Trapti Sharma,Director Durgesh Mishra

Abstract-How a person seems to be feeling In interpersonal communication, one of the most difficult and vital skills to master is the ability to give and receive acknowledgement. It is easy to tell how people feel and what they aim to accomplish by their facial expressions. Nonverbal communication relies heavily on facial expressions. Automated facial expression identification is becoming more dependent on deep neural networks. In part, this is because FER has gone from lab-controlled to real-world situations, where deep learning methods have proven useful in a variety of industries. Two major issues have been addressed in recent deep FER systems: overfitting, which occurs when there isn’t enough training data, and elements that don’t have anything to do with the expression of the subject, such as illumination, head position, and identification bias. This study provides an in-depth examination of deep FER, which includes datasets and approaches that shed light on the issues at hand. To begin, we’ll go through the datasets that the general public has access to. These datasets have been extensively studied in the scientific literature, and a variety of data selection and assessment techniques have been used. This is followed by an explanation of the standard deep FER system pipeline, as well as background information and recommendations for successful implementations at each level. For deep FER, we look at the most cutting-edge deep neural networks and training approaches for FER based on static photographs and dynamic image sequences, as well as advantages and drawbacks. Other commonly used benchmarks are included in this section as well. Then, in order to make our poll even more helpful, we add more topics and purposes to it. Last but not least, we examine the challenges and opportunities that remain in this sector and how to construct robust deep FER systems in the near future.

A Study of Multiserver Retrial Queues with Different Stages of Homogeneous Service
Authors:- M. Renisagayaraj, R.Roja, S.Bhuvaneswari

Abstract- We discuss a queuing system with retrial of customers. Two models are discussed. First, we investigate single server queues in parallel, when the customer going to search and join the shorter of the two queues and in the second model we introduce the multiserver queue to multiserver retrial queue system. Multiserver provides different stages of homogeneous service in succession.

Authors:- Tejas Shinde, Binit Shirsath, Pranali Vekhande, Varun Margam, Professor Priya Gupta

Abstract-As long as they have the necessary device, such a smart phone, users may now locate and track the locations of other people, objects, machines, cars, and resources from the comfort of their own homes. Location-sensitive information requests are often made by a user known as the client or network provider. Today’s most popular applications employ the Global Positioning System (GPS) to give position data.

Authors:- Tejas Shinde, Binit Shirsath, Pranali Vekhande, Varun Margam, Professor Priya Gupta

Abstract-As long as they have the necessary device, such a smart phone, users may now locate and track the locations of other people, objects, machines, cars, and resources from the comfort of their own homes. Location-sensitive information requests are often made by a user known as the client or network provider. Today’s most popular applications employ the Global Positioning System (GPS) to give position data.

A Review of Human Facial Expressions Recognition Using Artificial Intelligence K-Nearest Neighbor (KNN) Algorithm
Authors:-P.G. Scholor Shivam Sharma, Asst. Prof. Hemant Amhia

Abstract- Facial expression is one of the most important form of non-verbal communication. Facial expressions emit the feelings of a person, and it allows judging that person by others. Some can understand facial expressions of underlying emotions to some extent, whereas many of us cannot. Facial Expression recognition (FER) system is a system to recognize expressions from a person’s face. It plays an important part in today’s world in fields of mental disease diagnosis, and human social/physiological interaction detection. Various methods of FER exist. This paper provides a summary of various processes involved in FER.

Analysis of Multiserver Retrial Queue of Homogeneous with Simple Death Process
Authors:- M. Renisagayaraj, P Suganthi, R. Sujatha

Abstract-We analyzed an M /M /2 retrial queueing model with vacation taken by the server. Then server providing service one by one, also provides the second server with a fixed size 𝑘 ≥ 1. The customers are queued up for the first service, which is essential for all customers and the second server gives an optional service when there is a demand for some of the customer where as the others leave the system after the first server provide the service.

Computer Aided Diagnosis System for Brain Tumor Detection
Authors:- Konda Shiva Teja Ravinder, Devaraju Sai Vandith, Dr. A Venkataramana, AkkepallyAvanthika, A Jaya Krishna Murthy

Abstract- A brain tumor is a mass of abnormal cells in the brain. A brain tumor occurs when abnormal cells form within the brain.This paper presents a brief review of brain tumor detection methods. The computer aided diagnosis system for brain tumor detection consists of step by step procedures namely input of brain images, filtering, thresholding, morphological operations, bounding box, getting tumor outline encoding, inserting the outline in filtered image and displaying images. Simulation results are carried out by considering standard brain images and found that this algorithm works well in detecting the brain tumor.

Drive Assist
Authors:- Pratik Patil, Harshal Bhangale, Janavi Kadam, Vaishnavi Konduru, Co-Ordinator Mrs. V.T. Thakare

Abstract- Contemporary solutions are needed for modern issues. There’s no need to postpone your trip due to vehicle troubles or getting troubles at remote locations because DRIVE ASSIST will guide you how to fix it. User will be able to smoothly use the website with no problems as it is a user- friendly website. If there is sudden destruction of the vehicle, DRIVE ASSIST provides users with the closest garage, serviceman, hotels for resting and even the opportunity to rent automobiles to continue their journey in the event of an unexpected vehicle breakdown. The website also lists the closest gas stations and charging facilities for electric vehicles. DRIVE ASSIST was developed to provide users with support. To use the services they require, users only need to register on the website. Contact information will be available on the website so that customers can speak with service providers directly to ask questions and to discuss pricing. The supervisor will keep track of all customers and service provider information.

Sign Language Translator
Authors:- Asst. Prof. Ms. Pragati V. Thawani, Ms.Kaanchi Mukati, Ms.Shreya Jaiswal

Abstract- Individuals who have trouble hearing can communicate by using sign language. Since it might be difficult for regular people to communicate with deaf people, this technique is beneficial for helping them. The system suggested in this research seeks to partially address this issue. In order to create a real-time sign language dataset using a computer or laptop web camera and then use the Tensor Flow model and LSTM Deep Learning Model, along with many other technologies, to create a real-time sign language recognition system and aid in closing the gap between signers and non-signers, the authors proposed a method. Four modules—image capture, pre-processing, classification, and prediction—make up the proposed system.

The Impact of Fiscal Policy on Unemployment in Indonesia
Authors:- Siti Mewah Siregar, Muhammad Findi, Wiwiek Rindayantil

Abstract- This research investigates fiscal policy’s role in influencing Indonesia’s unemployment rate. This study uses secondary data with the Vector Error Correction Model (VECM) analysis method from 1970-2021. The study results a show that foreign debt, government expenditure, and government revenue do not significantly affect unemployment in Indonesia in the short term. However, in the long term, foreign debt and government expenditurehave a significant positive effect on unemployment, while government revenue has a significant negative effect on unemployment. The IRF test results show that the unemployment variable responds negatively if there is a shock to government expenditureand positively if there is a shock to foreign debt and government revenue. The FEVD test shows that government expenditureis the most effective fiscal policy in reducing the unemployment rate in the short term.

OCTA X – Analysis and Extermination of Space Debris
Authors:- Yash Nigam, Ayush Gupta, Mohd. Aaqib

Abstract- As we are heading towards the age of communication and advanced space exploration for the betterment of life and in the search for life on other planets in the universe. As we head towards the age of this modernisation spacecraft and satellites are being launched into free space as well as into the orbit of the earth and other planets too, for various purposes, as all machines have a life cycle so do the spacecraft and satellites have, as we know the fundamental law that material can’t be created nor be destroyed so, all the junk satellites and spacecraft just revolve around the orbit or in the free space creating the junk debris of the dead spacecraft which causes functional difficulties for the other space operations for the other spacecraft. Day by Day the problem is increasing and creating a major concern of the junk that envelops the planet hence creating hindrances for further space missions. And by OCTA-X is a robotic octopus-shaped debris cleaner and eliminator, the robotic AI Arms have big claws with a big cavity that can collect junk material and suck inside the main body of the robot, pack it throws it in the direction of the star (sun) which will culminate the junk material, hence cleaning the space debris with help of an AI Octopus Shaped Robot.

Analysis of New Computational Models in Analysis of Time Series Data for Rainfall Forecasting of Indian city
Authors:- Prashant Shivhare, Shivank Sonia

Abstract- Autoregressive integrated moving average (ARIMA) is a data mining technique that is generally used for time series analysis and future forecasting. Climate change forecasting is essential for preventing the world from unexpected natural hazards like floods, frost, forest fires and droughts. It is a challenging task to forecast weather data accurately. In this paper, the ARIMA based weather forecasting tool has been developed by implementing the ARIMAalgorithm in R. Sixty-five years of daily meteorological data (1951-2015) was procured from the Indian Meteorological Department. The data were then divided into three datasets- (i)1951 to 1975 was used as the training set for analysis and forecasting, (ii)1975 to 1995 was used as monitoring set and (iii)1995 to 2015 data was used as validating set. As the ARIMA model works only on stationary data, therefore the data should be trend and seasonality free. Hence as the first step of R analysis, the acquired data sets were checked for trend and seasonality. For removing the identified trend and seasonality, the data sets were transformed and the removal of irregularities was done using the Simple Moving Average (SMA) filter and Exponential Moving Average (EMA) filter. ARIMA is based on method ARIMA (p,d,q) where p is a value of partial autocorrelation, d is lagged difference between current and previous values and q is a value from autocorrelation. In the present study, we worked on ARIMA (2,0,2) for rainfall data and ARIMA (2,1,3) fortemperature data. As a result, it estimated the future values for the next fifteen years. The root means square error values were 0.0948 and 0.085 for rainfall data and temperature data respectively which show that the algorithm worked accurately. The resulted data can be further utilized for the management of solar cell station, agriculture, natural resources and tourism.

A Review On Analysis Of Connecting Rod Using Finite Element Method
Authors:- Pradeep Kumar Dwivedi, Prakash Kumar Pandey

Abstract- The connecting rod belongs to the group of critical components of piston engines. The connecting rod transfers loads from the piston onto crankshaft. In modern diesel engines the large value of torque achieved at low speed of rotation causes high stresses in pistons, crankshafts, connecting rods and another engine components. Amplitude of operational stresses has significant in- fluence on the fatigue life of the connecting rod. Additional factors which limit its fatigue strength are: incorrect shape (design), material defects or technological errors (defects created during the production process).The failure analysis of the connecting rods of piston engines was described in many publications. Several typical and uncommon failure modes in connecting rods of combustion engines were reported in work. The author’s attention is focused on description of failure mode and the stress analysis of investigated connecting rod.

Assessment on Manpower Training Practice (The Case of Nib International Bank, Ethiopia)
Authors:- Abreham Tesfaye Abebe (PhD)

Abstract- The document assesses the manpower or workforce training practices of Nib International Bank. The Bank that operates in Ethiopia, a country in the horn of Africa. The researcher deployed a research methodology that fits for the purpose of the research and come up with a recommendation. Training and development has impact on the performance of individual employees, which in turn affects the organization’s performance at large.

A Survey On Heat Pipe Heat Recovery Systems
Authors:- M.Tech.Scholar Babli Lodhi , Prof. Shrihar Pandey

Abstract- Abstrct- The development of heat pipe arrangements has been accelerated by advances in computer research, which have shown multiphase flow regimes and highlighted the vast potential of the respective technology for passive and active applications. This analysis aims to assess the utility of contemporary heat pipe systems for heat recovery and renewable applications. Regarding the operational temperature profiles of the evaluated industrial systems, fundamental characteristics and constraints are explained together with theoretical comparisons. Working fluids are compared using the figure of merit for the temperature range. The analysis determined that typical tubular heat pipe systems offer the broadest operational temperature range compared to other systems and, as a result, offer optimization and integration opportunities for renewable energy systems..

Music Recommendation System Using Facial Features
Authors:- Chandani Mourya, Rugved Patil,Siddhi dorage, Shweta Saindane,Priyanka Sherkhane

Abstract- One of the most challenging and complex processes ever attempted in the paradigm of image processing is the analysis of facial expressions. Since humans express most of their emotions through facial expressions, other uses for facial expressions include determining a person’s mood. The ability to recognize a person’s mood is one of the most beneficial implementations since it may be put to use in a variety of ways to enhance a person’s quality of life.For many people, listening to music is a crucial part of their existence. Numerous studies and advancements have been made in the field of music organizing and search, which directly relates to the issue of locating or streamlining the process of choosing a certain song to listen to. One option is the song’s recommendation, which is becoming more and more popular in modern times as it aids in choosing music for a range of events. Because music is a fantastic form of entertainment for people and may be used to unwind, concentrate, manage stress, and maintain a balance between mental and physical tasks. This paper will discuss the recommendation system which will enable users to receive song recommendations merely by looking at their facial expressions when we combine artificial intelligence technology with a generalized music approach.

A Novel Approach in Power gated Adiabatic Logic for Ultra Low Power Applications
Authors:- Rishabh Singh, Uday Panwar

Abstract-With the continuous scaling down of device technology in the field of VLSI circuit design, low power dissipation has become one of the primary concern of the research field. With the increasing demand of low power portable devices, adiabatic logic gates prove to be an effective solution. This paper presents different types of adiabatic logic families such as 2N-2N2P, PFAL (Positive Feedback Adiabatic Logic), DCPAL (Differential Cascode and Pre-resolved Adiabatic Logic) and a proposed circuit based on the PFAL logic circuit. In this paper, various adiabatic logic approaches have studied and compared with a proposed adiabatic logic based on PFAL logic circuit. Adiabatic logic styles such as 2N-2P, 2N2N-2P, DCPAL and PFAL are considered and their average power dissipation and delay at different frequencies are compared with the proposed circuit. Simulations are done by using HSPICE 32nm technology. Finally results of Power Delay Product obtained from simulations are plotted on bar graphs at various frequencies.

An Investigate on Cyber Security in the Digital Banking Industry
Authors:- Asst. Prof. Mr. S. Kirubakaran

Abstract-Online technology is modernized with excellent performance and is widely used by all users in the twenty-first century. The top five industries that often utilize online technology include the digital banking sector. Despite the increased use of online banking, cybercrime in the banking industry has been rising. According to reports, 50 percent of cybercrime involves ATMs, debit cards, and online banking. Compared to other industries, the banking industry is more frequently the target of cyberattacks. This article examines cyber assaults on the banking industry and methods for defending against them.

MNIST Digital Classification and Handwritten Digit Recognition
Authors:- P Masthan, M Vinay Kumar, P Akhil, P Dileep Kumar, Asst. Prof. Mrs K Anuranjani

Abstract- One of the most well-known issues in computer vision and machine literacy operations is the handwritten digit recognition challenge. There are several machine literacy techniques that have been used to solve the handwritten number recognition issue. In this paper, neural network methods are the main topic. Deep neural networks, deep belief networks, and convolutional neural networks are the three most widely used Neural Network techniques. In this paper, the three neural network approaches are compared and estimated in terms of numerous factors similar to delicacy and performance. Recognition, delicacy rate and performance, still, isn’t the only criterion in the evaluation process, but there are intriguing criteria similar to prosecution time. Random and standard dataset of handwritten numbers have been used for conducting the trials. The results show that among the three neural network approaches, convolutional neural network is the most accurate algorithm; it has a 98.08 delicacy rate. Still, the prosecution time of convolutional neural networks is similar to the other two algorithms.

I Draw Hand Writing Robot
Authors:- Bhairavi P.Chamate, Komal Meshram, Nimisha Ghatole, Raviksha Dhomne, Prof. Swati Dhabarde

Abstract- In industrial use, most of the chunks are obtained from accomplish to make it understandable, In this system, we have understood and formed I draw handwriting robot The main idea is to develop an I- draw handwriting robot that can be taken to any place with comfort. So the controller. This robot can draw both parallel and upstanding. Its single design structures a writing head that spreads beyond the machine, making it possible to draw on objects greater than the machine itself. The major benefit of the machine is that it can be located over the hardcover because the core XY extends the design of the machine.

Design of Chilled Water Distribution Systems
Authors:- Suhasini Pyarasani

Abstract- A chilled water plant can be conceptually well designed but implemented in a manner that unnecessarily increase first costs. This paper evaluates different chilled water distribution systems configurations, for chilled water plant. These chilled water distribution systems configurations include Primary-only-variable flow, and Primary-Secondary, Primary-distributed secondary, and Primary -coil secondary.Different analyses are performed in a model, and results are tabulated and plotted to compare energy costs. This paper offers recommendation to assist designers and engineers to select the chilled water distribution systems, without significant effort on designing.

Wearable Health Monitoring System using IOT
Authors:- Jagruti Kotkar, Pooja Sonawane, Saurabh Kothawale, Prof- Megha Beedkar (Guide)

Abstract- IoT is one of the emerging technologies which is leading to smart health monitoring. IoT helps in connecting the people by empowering their health and wealth in a smart way through wearable gadgets. IoT is the network of physical objects that are embedded with sensors, software and other technologies for exchanging of data over the network. Now a day’s people are suffering from a lot of acute and chronic diseases, and they do not acknowledge it earlier and due to lack of immediate treatment the death rates among these patients are increasing. This type of problems can be encountered through wearable gadgets that continuously monitor the activity and condition of the patient in a predictable method. The main aim of this work is to provide an extensive research in capturing the sensor data’s, analyzing the data and providing a feedback to patients based on different health parameters.

Online Examinaton System
Authors:- Shital Ghodake,Sakshi Nikam, Madhuri Paithankar, Sakshi Mokal, S.A Bhad

Abstract- The Online Exam System is a web-based platform that allows you to manage and conduct exams on the Internet. It provides a convenient, cost-effective and efficient means of assessing candidates’ knowledge and skills regardless of their geographic location. Systems typically include a user interface that allows students to log in, access test materials, and complete their exams online. Tests can be taken in a variety of formats, including multiple-choice, essay, and open-ended questions. The system also includes features for evaluating, reporting and analyzing test results. Online testing systems have several advantages over traditional paper-based testing. It saves time and money because there is no need to print and distribute test papers and no physical space is required to conduct the exam. The system is more secure because it can prevent cheating and protect the integrity of the exam. In addition, the system allows for more efficient examination administration, such as scheduling examinations, appointing examinees and communicating with students. Overall, online testing systems provide a flexible and efficient way to conduct testing in a digital environment.

Review of Gender identification using Machine Learning Techniques
Authors:- Lecturer Md. Arifuzzaman , Lecturer Jannatul Afroj Akhi, Lecturer Tamim Hossain , Lecturer Md. Rezaur Rahman Shipon , Lecturer Shamima Yasmin Sejuti, Prof. Dr. Muhammad Abdul Goffar Khan

Abstract- This paper is about the “Thermal sensor based Temperature Measuring Robot” using Arduino Uno circuits. In this technology, Temperature Measuring Robot measured the temperature of the human body and the temperature of any object. The MLX90614 infrared thermometer is a contactless temperature sensor module for Arduino compatible device. An infrared thermometer works to measure the object temperature by the infrared radiation in the form of an electromagnetic wave through the light emitted on the object. MLX90614 is a powerful infrared sensing device with a very low noise amplifier with a 17 bit ADC. It utilizes non-contact temperature sensing to collect the temperature info without touching any surface of the object. The construction is equipped with many sensors. Hardware and software architecture and integration with Robot operating system is described in details. In the last part of the paper we presented the results of implemented measurement technologies and draw conclusions.

Design and Implementation of Thermal Sensor Based Temperature Measuring Robot Using Arduino Uno
Authors:- M.Tech. Scholar Chahat Vaishnav, Assistant Professor Aditi Khemariya

Abstract- Gender classification has recently received a lot of interest because genders include a lot of information about male and female social activities. It’s difficult to extract discriminating visual representations for gender classification, especially with faces. Gender classification is the process of determining a person’s gender based on their appearance. Automatic gender classification is gaining popularity due to the fact that genders contain a wealth of information about male and female social activities. In recent years, such classification has become increasingly significant in a variety of fields. In a conservative society, a gender classification system can be utilised for a variety of objectives, such as in secure settings. Identifying the gender type is critical, especially in sensitive areas, to keep extremists out of safe areas. Furthermore, such a system is used in situations where women are segregated, such as female railway cabins, gender-specific marketing, and temples.

An Analysis of the Use of Machine Learning Models in the Detection of Skin Cancer
Authors:- M. Tech. Scholar Payal Yadav, Assistant Professor Aditi Khemariya

Abstract- Skin cancer, sometimes referred to as cancer of the skin or SC for short, is one of the most common forms of cancer in the world. Even while a clinical examination of skin lesions is essential for determining the features of the illness, it is constrained by the amount of time it takes to complete and the many different interpretations it might lead to. approaches such as machine learning (ML) and deep learning (DL) have been created to aid dermatologists in establishing an early and correct diagnosis of SC. This is essential for boosting the patient’s chance of survival, hence the approaches have been developed. In this article, we conduct a comprehensive analysis of the published research on the categorization of skin lesions using machine learning. Our intention is to provide those who are new to the topic a firm foundation upon which they may build the studies and contributions they make in the future. Searches were conducted across a number of different internet databases using inclusion/exclusion criteria. Documents were chosen for this evaluation based on their capacity to offer an accurate description of the processes that were carried out as well as an exhaustive explanation of the results that were obtained. A total of 68 papers were chosen, the great majority of which depend on DL methods for detecting and classifying skin cancer, in particular convolutional neural networks (CNN), with a smaller number of research relying on ML techniques or hybrid ML/DL approaches. The articles were selected because of the value they provide to the process of diagnosing and classifying skin cancer. In order to classify skin lesions, many ML and DL algorithms provide findings that are considered to be state-of-the-art. The encouraging results that have been obtained up to this point give hope that these methods will eventually be used in clinical practice.

Literature survey on Different Technique used for Detection of Depression using EEG Signal
Authors:- Research Scholar Pritam Prabhat, Associate Professor & HOD Dr. Bharti Chourasia

Abstract- Electroencephalogram (EEG) plays an important role in E-healthcare systems, especially in the mental healthcare area, where constant and unobtrusive monitoring is desirable. EEG signals can reflect activities of the human brain and represent different emotional states. Stress is a feeling of emotional or physical tension. It can come from any event or thought that makes you feel frustrated, angry, or nervous. Mental stress has become a social issue and could become a cause of functional disability during routine work. A machine learning (ML) framework is effective for electroencephalogram (EEG) signal analysis. This paper reviews of depression emotion recognition from EEG for e-healthcare applications.

Smart Helmet Using IOT Technique
Authors:-Rai Abhishek, Kamisetty Bindusri Laxmi, Machkuri Venkatesh, Dr. A Venkataramana, M Rajamouli

Abstract- Smart Helmet is system used to design a helmet that provides safety to bike riders. It detects whether the rider met with an accident. A smart system can help to decrease death rates on road accidents. This smart system turns on the ignition only when the helmet is worn and no alcohol is consumed by rider. A smart system also helps to detect the obstacle and responds through automatic brake system. The system provides an alert and inform to the family or friends about the accident faced by the rider. Smart helmet system is developed using Arduino Uno for controlling the entire process, RF module to provide communication between helmet and bike unit, ultrasonic sensor for automatic break system, GSM and GPS module for SMS and current location identification, vibrating sensor for accident detection and node MCU to store the data of alcohol consumed by rider. The developed system is tested and works well.

Sales force E-commerce Microservice
Authors:- A Pravin

Abstract- To develop an exclusive e-commerce platform for artisans to sell their products. The demand forecast of the items required, automatic quality checks on the items as well as Sentiment analysis with next recommendation actions for the artist shall be added. To promote the Indian handicraft industry globally. Providing a common platform to make, market, and sell highquality handicrafts and goods. The micro service approach encourages enterprises to become more agile, with crossfunctional teams responsible for each service. Micro service architecture structures the application as a set of loosely coupled,collaborating services. Micro services are inherently distributed systems. Implementing such a company structure, as inSpotify or Netflix, can allow you to adapt and test new ideas quickly, and build strong ownership feelings across the teams.

Home Service Provider Application
Authors:- Shital Mohite, Alisha Pathan, Bhumi Lohar, Atharva Pisal, Riyaan Chatterjee

Abstract- We are building an web application for all the web users. The project “Home service provider” is used to automate all processes of the booking service Which deals with booking of services, providing it confirmation and user details. This will help you to get service from anywhere at any time. This webpage will take input from the user and provide suitable options for you. You can also provide your service here on our platform.Which would save the customers time and efforts significantly.

Brain Tumour Detection using Deep Learning
Authors:-Rohit Chahal

Abstract-The fragmentation of human-assisted manual categories can lead to inaccurate predictions and diagnoses, so classification of the brain tumor is one of the most important and difficult challenges in the field of medical imaging. Moreover, if there is big data that should be national, it is a frustrating task. Because tumors in the brain have a wide range of appearance and because normal tissue and tissue are very similar, it is difficult to distinguish tumor regions from images. We suggested how to remove brain tumor from 2D magnetic resonance brain imaging (MRI) using the Fuzzy C-Means clustering algorithm, followed by classification classification and convolutional emotional networks in this study. Tests were performed on real-time databases with tumors of various sizes, locations, forms, and firmness. In the traditional classification category, we used six classical dividers used in scikit-learn: Vector Support Machine (SVM), K-Nearest Neighborhood (KNN), Multilayer Perceptron (MLP), Logistic Retreat, Naive Bayes, and -Random Forest. After that, we moved on to Convolutional Neural Networks (CNNs), which were built using Keras and Tensorflow and produced much better results than the ancient neural networks. CNN achieved a 97.87 percent accuracy rate in our study, which is surprising. The main purpose of this study was to use textual and mathematical knowledge to discriminate between normal and aberrant pixels.

Secured Routing Energy Efficient Protocol (Sreep)
Authors:-Research Scholar R.S.Karthik, Dr.M. Nagarajan

Abstract-The routing mechanism in wireless sensor networks (WSNs) is crucial for a variety of monitoring applications, such as those focusing on the environment and traffic. In this section, the comprehensive contributions made to routing in WSN are examined. This study concentrates mainly on the challenges that WSN confronts as well as the various protocols that are employed. The SREEP algorithm is a brand-new proposal for assuring the secure transmission of data packets. The proposed technique reduces energy consumption while preserving a high level of security. The efficacy of the algorithm is assessed based on energy consumption, transmission duration, latency, and throughput.

Review: Cloud Computing and Internet of Things Plays Vital Role in Smart Stadium
Authors:-Asst. Prof. Shubham Gangrade, Associate Prof. Dr.Kapil Chaturvedi, Asst. Prof. Ankita Awasthi, Asst. Prof. Brij Mohan Sharma, Asst. Prof. Ashutosh Pandey, Associate Prof. Dr.Vijay Bhandari

Abstract-As we see in daily life how technology plays important role in routine life. There are few technologies are based on cloud computing like azure Microsoft server and the IoT and both are very important part in our lives. In our working life and the follow-up of all operations that we must follow before any match is held on any stadium in the world. An aspect of precautionary measures is discussed here before every match. In this research, based on discussion as per the understanding we will conduct on how to integrate cloud computing and the IoT and use them to work in developing stadiums in the word and made it smart. Several existing and new models of smart stadium are although explained.in this paper we are seeing cloud computing techniques which helps to iot applications.

Data Privacy using Block Chain and AI
Authors:-Asst. Prof. G. Kiran Kumar, A.Hari Prasad, B. Balaraju, N. Mehamood Hussain, B. Guna Sai Reddy, M. Jaya Kishore

Abstract-While data is the fuel that drives AI algorithms, it is difficult to approve or authenticate its use in the complex internet where it resides because of its dispersed nature and the fact that its diverse stakeholders do not trust one another’s stewardship. Due to this, it is challenging to facilitate data exchange in cyberspace for true big data and true powerful AI. In this paper, we propose the SecNet, an architecture that integrates three key components to enable secure data storage, computing, and sharing in the large-scale Internet environment, with the goal of creating a safer online environment rich in authentic big data and, by extension, a more robust artificial intelligence thanks to a larger pool of relevant information from which to draw. 1) Blockchain-based data sharing with ownership guarantee, allowing trustworthy data sharing in the large-scale environment to produce genuine big data. 2) An AI- based safe computing platform that may generate smarter security rules and so contribute to the development of a more reliable digital environment. As a result, greater AI performance may be attained by promoting data sharing and using a trusted value-exchange system for buying security services, which gives participants a chance to earn monetary benefits for supplying their data or service. In addition, we cover the usual deployment of SecNet and its applications.

Spammer Detection and Fake User Identification on Social Networks

Authors:-B.Sekhar, P.Shiva Prasad, J.Bharath Kumar, J.Mahesh, A.Pradeep, B.S.Muzammil

Abstract-Thousands of people across the globe utilize online services. Certain social media platforms, like as Face book and Twitter, get a profound impacts on people’s lives of their consumers, although they can also have unwanted consequences. Hackers are using the most popular social media websites as a distribution service for their unwanted as harmful content. When it comes to spammers, Face book, for examples, became one of the greatest widely utilized websites of any and all time. To responsible for the greater or companies, fraudulent start sending out unwanted messages to authenticated traffic, which not only affects the legitimate customers and also disrupts the usage of resources. In addition, the ability of spreading damaging content to consumers via the use of fictitious accounts has grown[10]. It is becoming increasingly customary in the field of online social networks to study fraudsters and false accounts on Tweets (OSNs). In this study, we start with a review of methods to determine scammers using Tweets as a test bed for their activity. Also included in this paper is a taxonomy of Twitter spam detection algorithms which categorizes the strategies that focus on their capacity to detect: 1 false contents, 2 is spamming depending upon Urls, (3) spamming within hot topics, and (iv) fraudulent accounts. All of these aspects are taken into consideration as well as schedule and user actions. We believe that this research will serve as useful resources for scholars looking for the most cur The y-axis in the above graph reflects the number of tweets containing either a false account or spam terms, while the x- axis represents the total number of tweets. Rent achievements in Twitter malware detection.

Automated Product Identification System For Visually Impaired

Authors:-Subhadip Ghosh, Soumen Maity, Sourav Chowdhury, Sudip Kumar Ghosh, Debmitra Ghosh

Abstract-This model intends to create a speech recognition system. A novel dataset is created, which consists of spoken words. The dataset is to train our system as well as to test the performance of the system. This dataset is not the same as the other conventional datasets generally used for this recognition system. The exciting and challenging aspects of this project are discussed. The content of the dataset and its collection and verification process are also discussed. Along with the system details, a methodology is used to reproduce and compare metrics to check the accuracy of this task. In the end, the performance result of the model is shown.

Land Registry Management System Using Blockchain
Authors:-Sanjana Gate, Rohan Temgire, Atharva Bankar, Rohit Chavan, Prof. Priyanka Sherkhane

Abstract-The present Land Registration System is a time consuming process and it involves a lot of vulnerabilities and fraudsters use it to cheat the common people and the government. The incomplete/improper registration leads to dispute of ownership and litigations of the land. In this project we make use of blockchain technology to overcome some vulnerability in the existing system. We use Metamask to proceed with the transactions and for verifying the users on our system. This application provides a simple and intuitive user interface, where users buy and sell their lands. The Land Inspector is the one who verifies and approves all the transactions and user accounts. With this system, users can ensure enhanced security.

Smart Wheelchair to Disability person Using Arudino UNO
Authors:-Lecturer S.Senthil, Lecturer E.Nambirani

Abstract-In the design of a smart, motorized, voice and app-controlled wheelchair using embedded system. Proposed design supports voice activation system for physically differently abled persons incorporating manual operation. The “Voice-controlled Wheel chair” for the physically differently abled person where the voice command controls the movements of the wheelchair. The voice command is given through a cellular device having Bluetooth and the command is transferred and converted to string by the BT Voice Control for Arduino and is transferred to the Bluetooth Module HC -05 connected to the Arduino board for the control of the Wheelchair. For example, when the user says „Go‟ then chair will move in forward direction and when he says „Back‟ then the chair will move in backward direction and similarly „Left‟, „Right‟ for rotating it in left and right directions respectively and „Stop‟ for making it stop. This system was designed and developed to save cost, time and energy of the patient. Ultrasonic sensor is also made a part of the design and it helps to detect obstacles lying ahead in the way of the wheelchair that can hinder the passage of the wheelchair. On addition to this an IOT device was integrated using NodeMCU where relay was connected to the microcontroller, using the application we can control the device using web application anywhere around the world.

Agriculture That Makes Use of the IOT
Authors:-Assistant Prof. Mr. N.V.S. Prasad, S.Zakeer Hussain, G.Anil Kumar, K.Bala Kumar,
K.Charan Kumar Reddy, S.Mahammed

Abstract-The widespread adoption of IoT technology has resulted in revolutionary changes across all walks of the average person’s life. The Internet of Things, or IoT, is a system where devices create their own network topology. Intelligent Smart Farming Internet of Things (IoT) based devices are changing the game in agriculture by improving yields, cutting costs, and maximaising efficiency. The purpose of this report is to propose an Internet of Things (IoT) based Smart Farming System that will help farmers get Live Data (Temperature, Soil Moisture) for efficient environment monitoring, thereby boosting both yield and product quality. This report proposes an IOT- based Smart Farming System that utilities Arduino technology combined with various Sensors and a Wi-fi module to generate a live data feed that can be accessed online via Thingsspeak.com. The proposed product has been tried and tested in real agricultural fields, yielding data feed accuracy rates of 98% or higher.

Experimental Investigation of Machine Learning Techniques for Predicting Software Quality
Authors:-Asst. Prof. V.Lakshmi Chaitanya, Nikhitha Sutraye, A.Sai Praveeena,U.Naga Niharika,
P.Ulfath, D.P.Rani

Abstract-There are several points in the software development process when estimating software quality is useful. Quality assurance planning and benchmarking are two potential applications. Multiple criterion linear programming and quadratic programming are two approaches that have been utilised in prior research to estimate software quality. In addition, we tested out C5.0, SVM, and a Neutral network to determine how best to estimate quality. The precision of these research is rather poor. The purpose of this research was to enhance estimate precision by using important properties of a large dataset. In order to improve accuracy, we used a feature selection technique and a correlation matrix. We have also tried our hands at several newer techniques that have proven effective in other prediction challenges. Xgboost, Random Forest, and Decision Tree are only few of the machine learning algorithms used to analyse the data and draw conclusions about the software’s quality and its relationship to its development qualities. Results from experiments demonstrate that machine learning algorithms can accurately predict the quality of software.

Predictive Analysis of Aged and Faulty Electronic Appliances in Smart Home
Authors:-Asst. Prof. Sathess Lingam. P, UG Scholar Krithik Gokul. S, UG Scholar Sagar.T.N, UG Scholar Prasanna Venkatachalapathi.B

Abstract-The use of smart homes and Internet of Things (IOT) devices has become increasingly common in recent years. As a result, there is growing interest in using predictive analytics to detect failures in electronic devices and managing medications in smart homes, especially smart homes used by sensors. The purpose of this study is to explore the use of predictive analytics in smart homes to detect errors in electronic devices and improve medication management. To do this, it uses data from a variety of sensors and devices to identify patterns and anomalies that indicate possible errors or problems in devices and medicines. The research focuses on using machine learning algorithms to analyze data from sensors such as temperature, humidity, motion and light to identify patterns of device use and medication administration. Algorithms then use this data to predict the likelihood of failure or problems with devices and medicines. The study also explores how natural language processing (NLP) techniques can be used to analyze text-based data such as drug labels and instructions for use. This allows us to better understand how medicines are used and administered correctly. Overall, this research contributes to the development of predictive analytics techniques that can improve the management of smart homes, especially electronics and medicines used by the elderly.

Need of Technology in Trade Andbusiness
Authors:-Research Scholar Seelesh Sharma

Abstract-The old order changeth yielding place to new and God fulfills himself in many ways lest one good custom should corrupt the world.”Alfred Lord TennysonMeans old policies, methods changed and new policies, methods take their place because along with the old methods some defects arise in those systems, which start causing damage.Exactly the same thing we can do in the context of technology, the techniques which were used for trade and business in ancient times, if compared to the present, all those methods have become very old, and very time consuming.At present, where cut-throat competition is going on, doing work smartly and doing it quickly and accurately has become an essential requirement of business and business, so to fulfill this need, technology has taken birth has become an integral part of business.Technology has transformed all business and business processes from complexity to organization whether it is a matter of information technology or other means of technology, every means of business and business seems to be closely related.The importance of information technology in business has grown impressively over the past two decades. The modern economy places a premium on the acquisition, processing and fair use of information in all its forms and formats. IT helps companies innovate, grow and reach new customers.The most important means of technology in trade include electronic communication such as email, text, fax and virtual conferences. Tracking methods for shipping and purchasing is another huge technological innovation, as it allows businesses to verify the delivery of goods and the amount of inventory purchased. Electronic spreadsheets and databases are other inventions that allow international companies to more easily manage and store their information. Technology has revolutionized the lives of consumers and businesses alike. The increased array of products on the shelves, lower costs of goods and services, and ease of access to information are just a few of the ways technology has enhanced society. The field of international trade is particularly sensitive to technological innovations. Technology used to protect confidential business information using quality. The birth of the Internet and online social networking sites has brought down the cost of conducting business. This gives companies an easy to use Six Sigma management approach. The level of technology is an important determinant of economic growth. Rapid rate of growth can be achieved by high level of technology. Schumpeter is of the view that only innovation or technological advancement is the determinant of economic progress, but if the level of technology stagnates then the process of development stops.At present, there has been an amazing increase in the production and distribution of goods and services through technology. This technology has made business world-wide. We can do shopping from any place in the whole world by simply pressing a few buttons while sitting at our home and can buy the things we want.Through technology, the level of efficiencies of products and services, and when the level of capabilities, comes down costsAnd when there is a reduction in the cost, there is definitely an increase in the profits and the growth of the systems is moreRemember those days when we were born, would technology have developed so much at that time, anyway, it is said that necessity is the mother of invention, so as we need great new inventions were born and technology is also such a thing. It is the invention that replaces our need. Talking about business, any person sitting at home can inquire about any particular service in the whole world, can get any information about it and can also order online after being satisfied.Technology has made business so easy that if any person wants to do business to become self-reliant, then being free from complications, one can easily think about business. Technology is no less than a miracle word for business and business.Just as finance is said to be the lifeblood of business, in the same way if we call technology the heartbeat of business in the present context, then it will not be an exaggeration. Internet has become such a system that has erased all the distances of the world, whether it is family or business or business, no matter how far away we can operate the system and business activities.

Predictive Analysis of Aged and Faulty Electronic Appliances in Smart Home
Authors:-Asst. Prof. Sathess Lingam. P, UG Scholar Krithik Gokul. S, UG Scholar Sagar.T.N, UG Scholar Prasanna Venkatachalapathi.B

Abstract-The use of smart homes and Internet of Things (IOT) devices has become increasingly common in recent years. As a result, there is growing interest in using predictive analytics to detect failures in electronic devices and managing medications in smart homes, especially smart homes used by sensors. The purpose of this study is to explore the use of predictive analytics in smart homes to detect errors in electronic devices and improve medication management. To do this, it uses data from a variety of sensors and devices to identify patterns and anomalies that indicate possible errors or problems in devices and medicines. The research focuses on using machine learning algorithms to analyze data from sensors such as temperature, humidity, motion and light to identify patterns of device use and medication administration. Algorithms then use this data to predict the likelihood of failure or problems with devices and medicines. The study also explores how natural language processing (NLP) techniques can be used to analyze text-based data such as drug labels and instructions for use. This allows us to better understand how medicines are used and administered correctly. Overall, this research contributes to the development of predictive analytics techniques that can improve the management of smart homes, especially electronics and medicines used by the elderly.

A Cloud Computing
Authors:- Ms. Rashmi. R.Kamat

Abstract-Cloud computing is the practice of using a network of remote servers hosted on internet to store, manage and process data on demand and pay as per use. It provides access to a pool of shared resources instead of local servers or personal computers. As it do not acquire the things physically, it saves managing cost and time for organizations. Cloud computing is a completely internet dependent technology where client data is stored and maintain in the data center of a cloud provider like Google, Amazon, Microsoft etc. Cloud computing is an emerging domain and is acclaimed throughout the world. There are some security issues creeping in while using services over the cloud. This research paper presents a review on the cloud computing concepts as well as security issues inherent within the context of cloud computing and cloud infrastructure. This paper also analyzes the key research and challenges that presents in cloud computing and offers best practices to service providers as well as enterprises hoping to leverage cloud service to improve their bottom line in this severe economic climate and boost up its usage. The main emphasis of our study based on existing literature and to understand the concept of multi- tenancy securityissue.

A High Grade Type Light Weights Concrete Design Using Epoxy Material
Authors:- Ajay Bhardwaj, Asst. Prof.Kishor Patil

Abstract-The aim of this study is to determine the performance of concrete by adding the fly ash and silica fume in concrete by the partial replacement of cement and fine aggregate by some percentage and this will be done by different percentage at the gap of some percent and what will be effect on basic properties of concrete as from the other research paper it is noted silica fume and fly ash both are added separately in concrete by some partial replacement so result will be tremendous so here in this study by considering or reading all the previous data from the research paper the new work should also be positive fly ash is the waste product of coal combustion product also known as the fuel ash and silica fume is also known as the micro silica fume is nonmetallic and nonhazardous material.

A Modelling and Analysis Multistory Building Load Analysis Using Staad Pro Software
Authors:- Sumit Kanade, Associate Professor Rahul Yadav

Abstract-In order to compete in the ever growing competent market it is very important for a structural engineer to save time. As a sequel to this an attempt is made to analyze and design a multistoried building by using a software package staad pro. For analyzing a multi storied building one has to consider all the possible loadings and see that the structure is safe against all possible loading conditions. There are several methods for analysis of different frames like FEM method, cantilever method, portal method, and Matrix method. The present project deals with the design & analysis of a multi storied residential building of consisting each floor. The dead load &live loads are applied and the design for beams, columns, footing is obtained STAAD Pro with its new features surpassed its predecessors and compotators with its data sharing capabilities with other major software. We conclude that staad pro is a very powerful tool which can save much time and is very accurate in Designs. Thus it is concluded that staad pro package is suitable for the design of a multistoried building.

A Review On Solar, Wind & Grid Connected Fact Device Design And Noise Estimation
Authors:- Shubhanshu khare, Prof. A. K. Sharma

Abstract-The world is witnessing a change-over from its present centralized generation to a future with greater share of distributed generation. Hybrid energy systems are inter-connected with wind power, photovoltaic power, fuel cell and micro-turbine generator to generate power to local load and connecting to grid/micro-grids that decrease the dependence on fossil fuels. The hybrid system is a better option for construction of modern electrical grids that includes economic, environmental and social benefits. An overview of different distributed generation technologies has been presented. This paper puts forward a comprehensive review of optimal sizing, energy management, operating and control strategies and integration of different renewable energy sources to constitute a hybrid system. The feasibility of the different controllers such as microcontroller, proportional integral controller, hysteresis controller and fuzzy controller are presented. The controller is a closed loop feedback mechanism used for power regulation which achieves zero steady state error and the output signal generated from the controller produces desired output response.

Tribological Behaviour Of Aluminium Metal Matrix Composite Reinforced With Boron Nitride And Carbon Fibre
Authors:- Assistant Professor Sugan V, Manimuthu R, Professor & Head Subramaniam D

Abstract-The increasing need for low weight alloys and composites for engineering and structural applications motivates researchers to investigate the prospect of developing novel processes to generate high-performance materials. The current study addresses the manufacturing of metal matrix composites (MMCs) employing Stir casting procedures with aluminium as the base metal and carbon fibre and boron nitride as reinforcements. The primary goal of incorporating reinforcement into a metal matrix is to improve thermal, structural, and tribological qualities by increasing yield strength, tensile strength, and hardness at ambient temperatures. A hardness test will be performed to investigate the tribological and mechanical properties of the AMMCs, and a SEM image will be captured to investigate the microstructure.

Turtlebot Maze Solving With ROS
Authors:- N Harshavardhan Reddy, G Vamshi Krishna, Shaik Shahid Ali

Abstract-In this project, we are building a maze solver using Turtlebot. It is predicted that usage of automated robotic systems will increase tremendously in both industrial and domestic applications such as path planning bot, robot-based room cleaning system, robot-based waiter, etc. Currently, during the pandemic, it has become important to minimize human-to-human contact to stop transmission of disease hence there is a necessity to use them for pathfinders such as in restaurants. As a result, there is a need for robots to be equipped with this technology. Due to this, we have decided to find an approach for a bot to find to navigate and move the bot from one place to another automatically. For this approach, we have used ROS, modified Turtlebot package, and Gazebo. After compiling and integrating various nodes using ROS we were successfully able to simulate bot which could solve a maze and avoid obstacles in it’s path.

Criminal Face Detection Using Machine Learning
Authors:- Prof. Anup Ganji, Rashmi Kamat, Swapnali Chougule Pooja Biradar, Srushti Gadivaddar

Abstract-In practice, identification of criminal in Malaysia is done through thumbprint identification. However, this type of identification is constrained as most of criminal nowadays getting cleverer not to leave their thumbprint on the scene with the advent of security technology, cameras especially CCTV have been installed in many public and private areas to provide surveillance activities. The footage of the CCTV can be used to identify suspects on scene. However, because of limited software developed to automatically detect the similarity between photo in the footage and recorded photo of criminals, the law enforces thumbprint identification. In this paper, an automated facial recognition system for criminal database was proposed using known Principal Component Analysis approach. This system will be able to detect face and recognize face automatically. This will help the law enforcements to detect or recognize suspect of the case if no thumbprint present on the scene. The results show that about 80% of input photo can be matched with the template data.

An Investigation on the Diagnostic Potential of Machine Learning for Glaucoma
Authors:- Tasneem Shaikh, Sudha Sharma, Durgesh Mishra

Abstract-This review article will study the application of a range of image processing algorithms with the goal of providing an automated diagnosis of glaucoma. The objective of the paper is to fulfill this goal. Glaucoma is a degenerative illness that affects the visual nerve and is brought on by trauma to the neurological system. If the problem is not treated and is allowed to continue without being monitored, it is possible for a person to gradually lose all or part of their vision if the issue is not handled. It is a fact that a large percentage of people residing in the world’s rural and semi-urban areas suffer from eye difficulties; nevertheless, the exact same can be stated for every other location as well. At this point in time, the diagnosis of retinal illnesses is nearly totally completed via the processing of images that are obtained by the study of photographs of the fundus of the retina. Some of the essential image processing methods for detecting eye illnesses include image registration, picture fusion, image segmentation, feature extraction, image enhancement, morphology, pattern matching, image classification, analysis, and statistical measures. Image enhancement, morphology, and pattern matching are some examples of other methods.

Factors Influencing the Process of Internationalization of Small and Medium Enterprises (SME’S)
Authors:- Research Scholar Manish Ranjan, Professor Dr. Ashok Kumar

Abstract-The internationalization process of small and medium-sized enterprises (SMEs) is influenced by a variety of factors. A growing economy creates more opportunities for SMEs to expand their businesses internationally, as it indicates a higher demand for goods and services in international markets. SMEs need to consider the political and economic stability of their target markets before entering them. They need to have a thorough understanding of the political situation, economic growth prospects, and exchange rates of the target country to ensure their success in the international market. The present study aims to study the factors influencing the process of internationalization of SMEs. In the present research study, the researcher has used descriptive research design.To develop stable item attributes, adequate sample sizes are required. The sampling population include 473 SMEs.

Train Car Auto-Pilot to Traffic Sign Detection and Recognition Using Deep Learning
Authors:-Jadhav Sakshi Chhabu, Wakhare Nisha Maruti, Kamble Snehal Govind, Kaitake Jijabai Baban

Abstract-Traffic Sign Detection and Recognition is a crucial task for enhancing the safety of autonomous driving systems. Deep Learning has been proven to be a powerful tool for solving this problem. In recent years, Convolutional Neural Networks (CNNs) have been widely used for Traffic Sign Detection and Recognition due to their ability to automatically learn and extract features from images. This approach has achieved high accuracy rates in detecting and recognizing traffic signs under different weather and lighting conditions. This paper proposes a comprehensive review of recent advances in Traffic Sign Detection and Recognition using Deep Learning. We discuss the challenges of Traffic Sign Detection and Recognition, the state-of-the-art methods, and the datasets commonly used for evaluation. Furthermore, we analyse the limitations of current approaches and highlight the future research directions in this field.

Developments in Forensic Science Technology, Such As New Methods for Analyzing Evidence or New Tools for Gathering Evidence
Authors:-Andrew Roy

Abstract-Forensic technology has undergone significant advances in recent years, resulting in new methods for analyzing evidence and new tools for gathering it. These advancements have revolutionized the way forensic science is conducted and have led to increased accuracy and efficiency in criminal investigations. This research paper aims to explore the latest developments in forensic science technology, including the various methods for analyzing evidence and tools for gathering it. The paper will also discuss the benefits and drawbacks of these new technologies and their potential impact on the field of forensic science.

Analyzing the Impact of Mobile Commerce on Consumer Behavior and E-Commerce Sales
Authors:-Pawan Dadoria

Abstract-The advent of mobile commerce (m-commerce) has transformed the way consumers shop online, creating new opportunities and challenges for e-commerce retailers. The studies is analyze effect in m-commerce in consumers behavior and e-commerce sales, using a mixed-methods approach that combines a literature review, survey data, and secondary data analysis. The literature review covers the definition and evolution of m-commerce, as well as theoretical frameworks for analyzing the relationship between m-commerce and consumer behavior. The survey data is collected from a sample of online shoppers in the United States, and includes measures mobile commerce consumer impact in m-commerce, and shopping behavior across different channels (desktop, mobile, and in-store). The secondary data analysis draws on publicly available data from leading e-commerce retailers and industry reports, and includes measures of e-commerce sales growth, channel mix, and mobile traffic and conversion rates. The results show that m-commerce has a significant positive impact on e-commerce sales, especially for retailers that invest in mobile-friendly websites and apps, personalized promotions, and convenient payment and delivery options. Moreover, the findings suggest that m-commerce adoption is associated with changes in consumer shopping behavior, such as increased frequency and convenience of purchases, reduced search and decision-making costs, and greater reliance on social proof and mobile reviews. The implications of these findings for e-commerce retailers and mobile commerce developers are discussed, along with limitations and future research directions.

A Cinema – Online Movie Ticket Booking System
Authors:-Aarya Nanndaann Singh M N, Akash Hegde P, Abhilash R, Akash Kumar, Prof. Priyadarshini R

Abstract-This paper presents the design and implementation of an online movie ticket booking system. The system is designed to provide a convenient and user-friendly platform for customers to purchase movie tickets online, eliminating the need to wait in long lines or visit physical ticket counters. The system includes features such as movie selection, seat selection, payment processing, ticket confirmation, ticket rescheduling, ticket transferring. The system also employs various recommendation algorithms to suggest movies to users based on their previous selections and browsing history. Additionally, the system includes security features such as user authentication, data encryption, and secure payment processing to ensure the protection of customer information. The implementation of the system involved the use of various programming languages, frameworks, and databases. Overall, the system offers an efficient and streamlined approach to movie ticket booking, enhancing the overall movie going experience for customers.

Emotion Based Music Player
Authors:-Prof. R. K. Sahare, Isha Bhoyar, Diksha Borkar, Amruta Shedame, Achal Deotale, Sheetal Mistry

Abstract-Everyone wants to listen music of their individual taste, mostly based on their mood. Average person spends more time to listen music. Music has high impact on person brain activity. User always faces the task to manually browse the music and to create a playlist based on the current mood. This project is efficient which generate a music playlist based on the current mood of user. How ever the proposed existing algorithms in use are comparably slow, less accurate and sometimes even require use of additional hardware like EEG or sensors. Facial expression is a easy way and most ancient way of expressing emotion, feelings and ongoing mood of the person. This model based on real time extraction of facial expression and identifies the mood. In this project we are using HAAR cascade classifier to extract the facial features based on the extracted features from HAAR cascade, we are using COHN KANADE dataset to identify the emotion of user. If the user’s detected emotion is neutral then the background will be detected and the music will play according to the background. For example. If it detects gym equipment, the algorithm will automatically create a workout song playlist from the captured image of the background.

Survey on Healthcare Image Steganography Techniques and Features
Authors:-Ph.d. Scholar Arun Kumar Sonaniya, Prof. Laxmi Singh

Abstract-One of important part of human life is health and some of information storage provide such valuable data. In order to increase the trust on such type of stored data steganography technique was applied by various researchers. This paper has summarized the features of image processing and its application in different areas. This paper has detailed various models proposed by scholars of image steganography processing. It was obtained that image may undergo some set of attacks that may disturb geometrical and spatial information, so list of such attacks was also summarized in the paper. Some of algorithm measuring parameters were also mentioned in the paper.

Integrating Green/Sustainability concept in Nigeria’s Property Market
Authors:-Habibu Sani, Ibrahim Bashir Bello

Abstract-The study was conducted to explore the need for integrating green sustainability concept into property development and valuation with a view to improving compliance to green sustainability concept and practice into real property market indices. The study was conceived on a survey design to appraise the need of integrating green issues/sustainability into property valuation process. The study used literature analysis approach to review real estate surveyors practices/approach to value indices perception using questionnaires to scope the importance of a range of sustainability features on market value for a hypothetical property, based on social, economic and environmental features constituting the triple bottom line of sustainability. Finding srevealed that energy waste and water management, preservation of biodiversity and environmental indoor/health quality are breakpoints for the integration of green issues into property valuation practice in developing country like Nigeria. There are already growing awareness of the need to integrate sustainability into real estate valuation practice. The study therefore concludes by establishing the significance of integrating green concept/sustainability into real estate valuation and its effect on the general perception of the Nigerian property market players.

Sustainable Investment Appraisal of Latent Values in Undeveloped Sites in Barnawa Kaduna, Nigeria
Authors:-Habibu Sani, Ibrahim Bashir Bello

Abstract-Real estate investment is considered the most complex and sophisticated form of investment compared with stocks, bonds and other finance sector investment, due to the influence of such factors as location and social trends as well as obsolescence (functional/physical) on its performance. Real estate investment decisions must be guided on intuition to avoid colossal loss thus the need for employing appraisal techniques as highest and best use technique to justify resource allocation to productive and best use among competing opportunities. Comparative analysis technique of yields from investment potentials of some selected sites was adopted.The study revealed there exist some vacant plots along AliyuMakama Road Barnawa Kaduna, having untapped latent value for investment but were left vacant thus termed vacant for speculation even though speculation is statutorily discouraged in the land use act 1978 with no visible machinery of enforcement to deter offenders. This has not only thwarted the aesthetics of the area but breaded security threat as being a rearing ground for criminals, rodents and reptiles thus jeopardizing sustainable city growth enshrined in the city master plan.

Sustainable Low Income Housing Delivery in Nigeria: Rent to Own Model.
Authors:-Habibu Sani, Ibrahim Bashir Bello

Abstract-Nigeria being the most populated country in West Africa region is faced with numerous challenges including housing delivery. Existing housing stock are by far short of expected number while the population of the country is geometrically increasing without a corresponding increase in housing delivery even though there are deliberate policies instituted to ameliorate housing problems. This article is predicated on the overview on Nigeria’s housing delivery journey using a policy and document review technique. The research concluded that a rent-to-own model is a workable strategy to adopt by Nigerian government whose interest to improve low income housing is objective and resolute to alleviate sufferings of the low income earners whose savings could hardly grow within a reasonable time frame to purchase a property from the open market on a cash and carry basis as is the tradition in the country.