RGB Method to Spot Hemorrhages and Microaneurysms Using Colors in Severe Stage of Non-Proliferative Diabetic Retinopathy

K.Saraswathi and Dr.V.Ganesh Babu, JECET; September 2017- November 2017; Sec. B; Vol.6. No.4, 240-245., [DOI: 10.24214/jecet.B.6.4.24045.]


Diabetic retinopathy (DR) is a diabetes related eye disease which occurs when blood vessels in the retina become swelled and leaks fluid which ultimately leads to vision loss. Several image processing techniques including Image Enhancement, Segmentation, Image Fusion, Morphology, Classification, and registration has been developed for the early detection of DR on the basis of features such as blood vessels, exudes, hemorrhages and microaneurysms. The damage caused by diabetic retinopathy can be prevented by the early detection of microaneurysms, exudates and hemorrhages in the retina. Hemorrhages are medical sign of DR and they seem like large red dots in fundus image. Presence of hemorrhages described the levels of DR. Timely recognition of hemorrhages can reduce the risks of loss of sight. The proposed paper has discussed about the identification of hemorrhages using colors in digital image of fundus using different preprocessing and feature extraction technique.

Rainfall Prediction Based on Decision Tree Classification Algorithm

K.Prabha and R.Sukanya, JECET; September 2017- November 2017; Sec. B; Vol.6. No.4, 230-239,[DOI: 10.24214/jecet.B.6.4.23039.]


Rainfall Prediction is one of the most significant and difficult task for the researchers in the recent years. In Data mining, classification algorithms are mainly used to predict rainfall, temperature, cloud burst, thunderstorm, sea level pressure etc. In this paper the prediction is done by using Decision Tree C5.0 algorithm. The Meteorological data studied is from the year 2012 to 2016 over New Delhi in India. In general, Maximum and Minimum temperature are one of the key factors responsible for Rainfall Prediction. This paper presents a Model to predict Rainfall using Decision Tree Algorithm and the data is implemented in C5 classifier using R.

The Nature of Mobile Money Transfer Transactions in Harare: Zimbabwe

Tinashe Chingoriwoand Dr Farai Choga,JECET; September 2017- November 2017; Sec. B; Vol.6. No.4, 222-229.,[DOI: 10.24214/jecet.B.6.4.22229.]


This research was on the mobile money transfer transactions in Harare in Zimbabwe. Of late, there has been unending queues in banking halls of most banks in Zimbabwe. Most of the people spent their valuable time in banking queues yet they are registered on mobile money transfer systems. The transactions that they use the hard cash for are also available on the mobile money transfer platforms. This research was carried out in order to find out the nature of transactions done by the Zimbabwean people. The researchers used a descriptive survey in a bid to analyse the research problem. A mixed research methodology was used and the researchers collected and analysed both qualitative and quantitative data based on the research question. In this research judgemental sampling was used by the researchers to select the respondents on the basis of their knowledge on mobile money transfer systems. The data was gathered using interviews and questionnaires. The findings revealed that transactions such as send money, cash in, cash out, buy airtime and bill payment were done more frequently on mobile money transfer platforms. On the other hand bank to wallet and wallet to bank transactions were not frequently done as some of the financial institutions were not linked to mobile money transfer systems. The researchers recommended that regulations should be put in place to ensure that all financial institutions are linked to all the mobile money transfer systems in Zimbabwe so as to promote the funding of customer mobile wallets as well as the bank to wallet and wallet to bank transactions.

IoT Sensing in Health Monitoring Platform

Hooman Kashanian and Sahar Rezazadeh, JECET; September 2017- November 2017; Sec. B; Vol.6. No.4, 208-221,,[DOI: 10.24214/jecet.B.6.4.20821.]


IoT industry is composed of big data, Internet of Things, Machine to Machine (M2M) communications, cloud computing, and real-time analysis of data from continuous sensor devices. Internet of Things (IoT) has recently received a great attention due to its potential and capacity to be integrated into any complex system. Due to common advantages through complement between IoT and Cloud technologies, there is apparent interest in integration of Internet of Things (IoT) with cloud computing. The current paper proposes a review on Cloud-IoT approaches with specific emerging services based on which this integration has been provided. The health industry is one of the venues that can benefit from IoT–Cloud technology, because of the scarcity of specialized doctors and the physical movement restrictions of patients, among other factors. This paper introduces platforms for health monitoring using IoT technologies on intelligent and reliable monitoring. The sensing model is presented as a service and main architectural decision are briefly proposed as health monitoring in development of IoT platform. Finally, the paper describes requirements for the model in terms of major roles and operational rules as well as assumes for subsequent phases of developing project.

Cryptanalysis of a Remote User Authentication Scheme

Manoj Kumar, JECET; September 2017- November 2017; Sec. B; Vol.6. No.4, 201-207.,[DOI: 10.24214/jecet.B.6.4.20107.]


Password based remote user authentication schemes are used to authenticate a remote user. E. J. Yoon et al. proposed a new efficient remote user authentication scheme using smart cards to solve the security problems of W. C. Ku and S. M. Chen’s scheme. This paper is about the cryptanalytic study of the security of Yoon et al.’s scheme and then proves that the there is a lot of vulnerabilities in this scheme. The password change phase of Yoon et al’s scheme is still insecure. This paper also proves that the Yoon et al. scheme is still vulnerable to parallel session attack.