The changing trends in corporate culture
The pandemic continues to dominate global economic sentiments as the coronavirus also known as COVID-19 continues to spread globally. The Business Insider Intelligence and several eMarketer’s are continuing to work in order to analyze the impact of the virus on businesses across the world. Through this article, readers can have a better understanding of the current situation of businesses and their recent operation trends like remote working, employee motivation, and consumer behavior. The article further proceeds by evaluating the case study of few companies with a high growth perspective and profitability index. And seeks the relevance through checking the feasibility of business models and planning policies for the next consecutive quarters to combat the situation.
Published by: Aryan Dogra
Author: Aryan Dogra
Paper ID: V7I1-1262
Paper Status: published
Published: February 16, 2021
Smart traffic manager: Computer vision and deep learning-based approach
In the last couple of decades, the number of vehicles has been on the road increased drastically. Hence it has become very difficult to keep track of every vehicle for traffic management and law enforcement. With the increasing number of vehicles on roads, it is getting difficult to manually enforce laws and traffic rules for smooth traffic flow. Traffic Management systems are installed on traffic signals to check for vehicles breaking the traffic rules. To automate all these processes a system is required to easily identify a vehicle. The main aim to design this system is to reduce the mishaps which occur due to reckless driving and violations of the traffic rules. The important question here is how to identify a particular vehicle, The obvious answer to this question is by using the vehicle’s registered license plate as every vehicle has a unique number through which it is easily differentiated from all the other vehicles. Vehicles in each country have a unique license number, which is written on their registered number plate. This number distinguishes one vehicle from the other, which is useful especially when both are of the same make and model. So, the basic idea will be identifying whether the two-wheeler rider is wearing a helmet or not, over speeding vehicles, zebra crossing violators, etc. Most of the tasks in this will require machine learning/deep learning models for image processing tasks. In the end, this system would be very effective to automate the hectic task of the traffic police and can be very efficient in terms to reduce the workload and manage the different tasks autonomously.
Published by: Sahil Shaikh, Swapnil Patil, Niranjan Patil, Purushottam Kulkarni, J. K. Kamble
Author: Sahil Shaikh
Paper ID: V7I1-1236
Paper Status: published
Published: February 15, 2021
Studies on the compatibility of Ordinary Portland Cement with Polycarboxylate Superplasticisers
The addition of superplasticisers along with mineral admixtures like fly ash and slag in concrete improves the strength and workability of concrete at lesser water cement ratios. To get this benefit, the compatibility between cement and admixtures must be studied. SP’s are normally adsorbed on the cement particles and sometimes the adsorption will not be even and slightly unreliable. This is due to the clinker composition of cement and the type of SP’s used. Various combinations of materials including mineral admixtures affect the behaviour of the cement–based system and become incompatible like slump loss, delayed setting of concrete etc. In the present work, four brands of Ordinary Portland Cements are selected and is checked for its compatibility with 4 types of PCE superplasticisers available in the market using Marsh cone test. The results of these tests conducted on the cement paste is analyzed to find out the optimum dosage of superplasticiser for all the four brands. Chemical analysis and XRD analysis is done for the 4 types of cements to study the behaviour. The work concludes that the presence of MgO in ordinary portland cement affects the cement superplasticiser compatibility to greater extent.
Published by: Lelin Das, Asis Kumar K., Dinesh Kumar T.
Author: Lelin Das
Paper ID: V7I1-1207
Paper Status: published
Published: February 15, 2021
Driver assistance system based on traffic sign recognition
Programmed discovery and acknowledgment of traffic signs assume a pivotal function in the administration of the traffic-sign stock. It gives an exact and opportune approach to oversee traffic-sign stock with insignificant human exertion. In the Computer Vision network, the acknowledgment and recognition of traffic signs is a well-informed issue. A larger part of existing methodologies performs well on traffic signs required for cutting edge drivers assistance and self-ruling frameworks. In any case, this speaks to a generally modest number of all traffic signs (around 50 classes out of a few hundred) and execution on the excess set of traffic signs, which are needed to take out the manual work in rush hour gridlock sign stock administration, stays an open question. In this paper, we address the issue of perceiving constantly a colossal number of traffic-sign arrangements sensible for automating traffic-sign stock organization. We receive a convolutional neural organization (CNN) approach, the Mask R-CNN, to address the full pipeline of discovery and acknowledgment with programmed start to finish learning. We propose a few upgrades that are assessed on the discovery of traffic signs and result in an improved generally speaking execution. This methodology is applied to the discovery of 200 traffic-sign classifications spoke to in our novel dataset. Results are accounted for on exceptionally testing traffic sign classifications that have not yet been considered in past works. We give a far-reaching investigation of the profound learning technique for the location of traffic signs with huge intra-class appearance variety and show beneath 3% mistake rates with the proposed approach, which is adequate for arrangement in useful uses of traffic-sign stock administration.
Published by: Prajakta Udaram Lanje, Srishti Sunil Bankar, Siddhant Vinay Nikumbh, Pallavi Dhananjay Dadape
Author: Prajakta Udaram Lanje
Paper ID: V7I1-1261
Paper Status: published
Published: February 15, 2021
Smart centralized attendance management system
The management of the attendance can often be a good burden on the lecturers if it is done manually. To resolve this problem, a smart and auto attendance management system is being utilized. But authentication is a crucial issue in this system. Biometrics are generally used to execute a smart attendance system. Face recognition is one of the biometric to be used. The human face is a vital authentication parameter, it has many applications in other fields such as video monitoring and CCTV footage system, access systems present indoors and network security, identification of people, electronics, and validation of identities. By using a similar framework, the problem of proxies and students being marked present even though they are not physically present can easily be solved. The important implementation steps used in this type of system are face detection and recognizing the detected face. This paper proposes a model for implementing an automated attendance management system for students of a class by making use of face recognition technique, by using Convolutional Neural Network (CNN). After these, the connection of recognized faces ought to be conceivable by comparing with the database containing student's faces. This model will be a successful technique to manage the attendance and records of students.
Published by: Vaibhav Ghadiali, Jevin Jain, Meet Nandu
Author: Vaibhav Ghadiali
Paper ID: V7I1-1231
Paper Status: published
Published: February 12, 2021
Role of IoT to make a smart city
IoT plays a very beneficial role to make the city SMART. IoT is a concept that is rapidly used in this IT sector. Nowadays IoT is the most useful field in the IT sector. IoT- Internet of Things is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity which enable these objects to connect and exchange data. Here we study articles to analyze what is the role of IoT to make a smart city. So we identify that the major role of IoT to make a smart city. The smart city always uses a very efficient environment to establish a network to connect the devices into a system. To make a city smart we use sensors or attached sensors to detect the devices. Arun Kumar says that Nowadays, IoT is rapidly used in this time and have been enormous discussions around building smart cities in India. Sometimes, one questions always in my mind i.e. what really defines a smart city? Imagine a city that acts likes a smart city like a living organism, interacts with you, and continuously fulfilled our needs. A smart city is smart due to its inherent intelligence in dealing with its resources and environment. It makes the effective use of available “ICT”, especially the “IoT”. Here one keyword used-“inherent intelligence”, which means sensors.
Published by: Heena Gupta
Author: Heena Gupta
Paper ID: V7I1-1257
Paper Status: published
Published: February 12, 2021
