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International Journal of Computer Science and Technology
IJCST Vol 10 Issue 1 (Jan-March 2019)

S.No. Research Topic Paper ID Download
01

Class Room Attendance System Using KNN

S. Sai Kumar, S. Adithya Varun, Dr. P. K. Sahoo, K. Eswaran

Abstract

Marking the attendance in schools and colleges is a key activity by the teachers. They face problems when there are a large number of students in a class. These difficulties can be overcome by using computer aided face recognition techniques. In this paper we use the KNN algorithm and compare our results with the LDA (linear discriminant analysis).
Full Paper

IJCST/101/1/A-0938
02

Efficient System for Heart Disease Prediction by applying Logistic Regression

S.Adithya Varun, G.Mounika, Dr. P.K. Sahoo, K. Eswaran

Abstract

In today’s modern lifestyle people are effecting by different health issues, one among them is heart disease which may be incipient from a very early age. Cardiovascular disease remains as the number one cause of death globally. The main objective of this paper is to identify the presence or absence of heart disease for an individual. In the healthcare industry, it is very difficult to discover whether an individual is affected by heart disease or not by a physician. It requires a careful understanding of patient’s data, and the identification of those parameters which cause the disease all of this is considered as a difficult task. Additional tools are required for making the clinical decision of heart disease. For the implementation of this work we referred to the Kaggle dataset1, which comprises 14 features (attributes) with class label, are identified as a cause for heart disease. In this paper logistic regression algorithm is applied for the Heart Disease prediction in order to improve the system’s efficiency when compared with Naïve Bayes (NB) and Random Forest (RF).
Full Paper

IJCST/101/1/A-0939
03

Sensor Occupancy Detection Using XG Boost Algorithm

G. Mounika, S. Sai Kumar, Dr. P. K. Sahoo, K. Eswaran

Abstract

A room in a smart home is fixed with environmental sensors for sensing of the indoor air quality. Environmental sensors can be any sensor from simple air temperature sensor to an indoor air quality measurement system, which holds different types of sensors or a networked sensor. Purpose of these sensors is to determine the indoor air quality and their potential in incorporating occupancy detection is largely unused. Occupancy detection is a technique used to detect the presence of living and non-living things. There are many environmental sensors which are used to detect different kinds of gases, namely CO2 (carbon dioxide) and TVOC (total volatile organic compounds) sensors which are used here to detect the gases that resides in a room. By detecting the indoor gases we can improve the quality of the air. CO2 sensor is used for detection of carbon dioxide composition, where as TVOC is internally built with CO2 sensor and it will detect other gases too. There are many machine learning algorithms that are used to classify the occupancy detection. In previous studies, naive Bayes classifier is used for detecting occupants using Weka tool. Now In this paper XGBoost, a machine learning algorithm is used for detecting occupants.
Full Paper

IJCST/101/1/A-0940
04

SIFT: Scale Invarient Feature Transforms for Efficient Iris Recognition

Payal Garg, Deepika Arora

Abstract

Iris recognition is an automated method of biometric identification that uses mathematical pattern-recognition techniques. The purpose of ‘Iris Recognition’, a biometrical based technology for personal identification and verification, is to recognize a person from his/her iris prints. In fact, iris patterns are characterized by high level of stability and distinctiveness. Each individual has a unique iris. Not even one egged twins or a future clone of a person will have the same iris patterns. It is stable over time even though the person ages. Iris recognition is the most precise and fastest of the biometric authentication methods. The iris is an externally visible, yet protected organ whose unique epigenetic pattern remains stable throughout adult life. These characteristics make it very attractive for use as a biometric for identifying individuals. The purpose of ‘Iris Recognition’, a biometrical based technology for personal identification and verification, is to recognize a person from his/her iris prints. Image matching is a fundamental aspect of many problems in computer vision, including object or scene recognition, solving for structure from multiple images, stereo correspondence, and motion tracking. The features are invariant to image scaling and rotation, and partially invariant to change in illumination and camera viewpoint. They are well localized in both the spatial and frequency domains, reducing the probability of disruption by occlusion, clutter, or noise. Large numbers of features can be extracted from typical images with efficient algorithms. In addition, the features are highly distinctive, which allows a single feature to be correctly matched with high probability against a large database of features, providing a basis for object and scene recognition. In this paper we propose SIFT based iris recognition method, For iris matching and recognition, SIFT features are first extracted from a set of reference images and stored in a database. A new image is matched by individually comparing each feature from the new image to this previous database and finding candidate matching features based on Euclidean distance of their feature vectors. The keypoint descriptors are highly distinctive, which allows a single feature to find its correct match with good probability in a large database of features. However, in a clutteredimage, many features from the background will not have any correct match in the database, giving rise to many false matches in addition to the correct ones. The correct matches can be filtered from the full set of matches by identifying subsets of keypoints that agree on the object and its location, scale, and orientation in the new image.
Full Paper

IJCST/101/1/A-0941
05

Cloud Computing Security

Pedro Ramos Brandao

Abstract

This work approaches security in Cloud Computing. Key aspects of cloud computing are developed. One will initially review the core concepts inherent in Cloud Computing, then the issues of security and privacy will be addressed. The relevant risks in Cloud Computing environments will be analysed, and some solutions for problem mitigation will be presented.
Full Paper

IJCST/101/1/A-0942
06

Android App as a Platform for the Newly Created Products from Unused Material

Radha Nakhate, Shweta Tareker, Priya Chintalwar, Gayatri Sarode, Kshma, Amit Kumar

Abstract

Information and Communication Technology (ICT) in daily life is an emerging field focusing on the enhancement of recycled product and rural development in India. It involves innovative applications using ICT in the rural domain. The advancement of ICT can be utilized for providing accurate and timely relevant information and services to the artist, thereby facilitating an environment for remunerative business. This paper describes a mobile based application for recycled product business which would help them in their business activities. We propose an android based mobile application Recycled craft which would take care of the updates of the different reusable product, product forecast updates, product news updates. The application has been designed taking Indian recycled craft business in consideration.
Full Paper

IJCST/101/1/A-0943
07

A Novel Block Toeplitz Matrix for DCT-based, Perceptually Enhanced Image Fusion

Fayadh Alenezi, Ezzatollah Salari

Abstract

Image fusion aims at increasing the information content of the composite image. However, many existing transform-domain image fusion methods have failed to properly enhance the finer details in the input images, and the perceptual quality of the fused image often suffersas a result of fusion process. This paper describes and evaluates a novel image pre-processing technique based on the application of a block Toeplitz matrix as a part of a Discrete Cosine Transform (DCT) -based fusion method. The proposed DCT implementation seeks to enhance the finer details of all input images prior to fusion. A post-fusion stage aimed at adjusting image contrast and improving smoothness is then added in order to improve quality of fused image. The proposed method is applied to a set of medical images, and its results are evaluated based on objective performance measures such as entropy, standard deviation, and root-mean-squared error. These indicators are then compared to values obtained from other existing transform-based fusion methods, showing a significant performance improvement across all experiments.
Full Paper

IJCST/101/1/A-0944
08

Web GIS Development using Portal for ArcGIS, ArcGIS Server and Web AppBuilder for ArcGIS

Taranjot Singh Bhatia, Harpinder Singh, P.K Litoria, Brijendra Pateriya

Abstract

Sharing and organization of GIS (Geographic Information System) datasets and applications on the internet and the local network can be a challenging job as it requires specialized software. ArcGIS Enterprise is one such commercial platform. ArcGIS Enterprise is a full-featured mapping and analytics platform that includes a powerful GIS server plus dedicated web-based GIS infrastructure to organize and share your work on the cloud and also on the local infrastructure. This paper reviews a simple and easy to use methodology to create a web GIS application using various ArcGIS Enterprise tools like Portal, Server and Web AppBuilder. Web AppBuilder for ArcGIS has been used to create the GUI (Graphical User Interface), ArcGIS Portal and Server acts as the middleware and PostgreSQL has been used as a backend database. The web GIS has functionalities like pan, zoom, home, info window, legend, search options, layer selection etc.
Full Paper

IJCST/101/1/A-0945
09

Research Analysis of Different Routing Protocols of Mobile Ad Hoc Network (MANET)

Gunjan Bahl, Amit Dawar, Mandeep Singh

Abstract

Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile hosts forming a temporary network without the aid of any stand-alone infrastructure or centralized administration. Due to the mobility of the nodes in the network, these nodes are selforganizing and self-configuring. Not only they act as hosts, but also they function as routers. They direct data to or from other nodes in the network. Currently, it is one of the most attractive research topics in the wireless communication. These mobile nodes dynamically create temporary network and transferring messages from one mobile node to others in peer-to-peer fashion. A routing protocol runs on every mobile host and therefore subjected to the limitation of resources on every node. Therefore, to guarantee communication an efficient routing technique is desirable to that allow nodes to communicate in a timely manner. The primary goal of any ad-hoc network routing protocol is to meet the challenges of the dynamically changing topology. Therefore, an efficient route between any two nodes with minimum routing overhead and bandwidth consumption should be established. In this paper, the MANET characteristics and attacks are highlighted .In addition, the previously mentioned categories of routing protocols, proactive and reactive are explored. Moreover, a comparison is conducted between different protocols; namely, DSDV, AODV ,DSR and AOMDV in terms of both properties and performance.
Full Paper

IJCST/101/1/A-0946
10

Application of Artificial Intelligence in Internet of Things

Goddeti Mallikarjun

Abstract

Artificial intelligence is the best solution to manage huge data flows and storage in the IoT network. IoT nowadays becoming more and more popular with the inventions of high-speed internet networks and many advanced sensors that can be integrated into a microcontroller. The data flows internets now will have sensors data and user data that send and receive from the workstations. With the increase in the number of workstation and more and more sensors, some data may be facing problems on the storage, delay, channels limitation and congestion in the networks. To avoid all these problems, there were many algorithms were proposed in the past of 10 years. Among all the algorithms, Artificial Intelligence still being the best solution to the data mining, manage and control of congestion in the network. The aim of this paper is to present the application of artificial intelligence system in the IoT. The importance of data mining and management will be highlighted in the paper. Also, the method used in the Artificial Intelligence like fuzzy logics and neural network also will be discussed in this paper in conjunction with IoT network.
Full Paper

IJCST/101/1/A-0947