Christ University

About: Christ University is a education organization based out in Bengaluru, India. It is known for research contribution in the topics: Computer science & Convection. The organization has 2267 authors who have published 2715 publications receiving 14575 citations. The organization is also known as: Christ College & Christ University.

A Novel Approach for Detection and Recognition of Traffic Signs for Automatic Driver Assistance System Under Cluttered Background

Abstract: Traffic sign detection and recognition is a core phase of Driver Assistance and Monitoring System. This paper focuses on the development of an intelligent driver assistance system there by achieving road safty. In this paper a novel system is proposed to detect and classify traffic signs such as warning and compulsory signs even for occluded and angular tilt images using Support Vector Machines. Exhaustive experiments are performed in order to demonstrate the efficiency of proposed method.

Interactive multimedia in efl classroom: a study of teaching reading comprehension at junior high school in indonesia

Abstract: The objectives of the research were to find out: (1) whether or not the use of interactive multimedia improve students reading comprehension in the Eighth-Grade of SMP Negeri 4 Panca Rijang and (2) whether or not the use of interactive multimedia interest students’ in learning reading comprehension in the Eighth-Grade of SMP Negeri 4 Panca Rijang. This research employed mixed method design that applied experimental and control group. The population of the research was the Eighth-Grade students of SMP Negeri 4 Panca Rijang. The result of data analysis showed that there was significant difference between achievement of the students who used interactive multimedia and those who did not use interactive multimedia (conventional technique) in reading comprehension. It was proved by the mean score of experimental group was higher than control group in post-test (59.35 > 46.75). Furthermore, the result of the t-test value (3.581) was greater than t-table (α = 0.05; df = 38; t-table = 2.021) which means that H1 was accepted. The data analysis of questionnaire showed that the students had high interest toward the use of interactive multimedia in reading comprehension. It was supported by 4 students (20%) who were strongly interested, 14 students (70%) who were interested and 2 students (10%) who were moderate. The mean score of students’ answers in questionnaire (79.55) was classified as interested category. Based on the data analysis, the researcher concluded that: (1) the application of interactive multimedia enhanced the students’ ability in reading comprehension; (2) the application of interactive multimedia strategy in reading comprehension was interesting for the students.

Enhanced encryption technique for secure iot data transmission

Abstract: Internet of things is the latest booming innovation in the current period, which lets the physical entity to process and intervene with the virtual entities. As all the entities are connected with each other, it generates load of data, which lacks proper security and privacy standards. Cryptography is one of the domains of Network Security, which is one such mechanism that helps the data transmission process to be secure enough over the wireless or wired channel and along with that, it provides authenticity, confidentiality, integrity of data and prevents repudiation. In this paper, we have proposed an alternate enhanced cryptographic solution combing the characteristic of symmetric, asymmetric encryption algorithms and Public Key Server. Here, the key pairs of end points (User’s Device and IoT device) are generated using Elliptic Curve Cryptography and the respective public keys are registered in Public Key Server along with their unique MAC address. Thereafter, both the ends will agree on one common private secret key, which will be the base for further cryptographic process using AES algorithm. This model can be called as multi-phase protection mechanism. It will make the process of data transmission secure enough that no intermediate can tamper the data.

Human Activity Recognition Using Wearable Sensors

Abstract: The advancement of the internet coined a new era for inventions. Internet of Things (IoT) is one such example. IoT is being applied in all sectors such as healthcare, automobile, retail industry etc. Out of these, Human Activity Recognition (HAR) has taken much attention in IoT applications. The prediction of human activity efficiently adds multiple advantages in many fields. This research paper proposes a HAR system using the wearable sensor. The performance of this system is analyzed using four publicly available datasets that are collected in a real-time environment. Five machine learning algorithms namely Decision tree (DT), Random Forest (RF), Logistics Regression (LR), K-Nearest Neighbor (kNN), and Support Vector Machine (SVM) are compared in terms of recognition of human activities. Out of this SVM responded well on all four datasets with the accuracy of 77%, 99%, 98%, and 99% respectively. With the support of four datasets, the obtained results proved that the performance of the proposed method is better for human activity recognition.