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Abstract-This paper focuses on identifying the important aspects of Agile adoption from software practitioners in Malaysia. We analyse 27 Agile adoption variables from a survey of early Agile users in Malaysia. Factor analysis is conducted to identify the clusters of the variables (or items) and how they are inter-related to produce factors. Most of the respondents are from software organisations in Kuala Lumpur and Selangor; in which most of the companies are located in Malaysia. The clusters of variables resulting from this analysis can serve as a reference to the practitioners planning to adopt the methodology. The top factors identified from this study are shown in terms of (i) developer involvement and organisation-related aspects, (ii) cultural and people related aspects and (iii) customer collaboration and the need for professional skills when using Agile methods. In addition, factor analysis discovered that practitioners disagreed about the importance of the technical aspects of Agile. While we believe that these findings are particularly important from the Malaysian perspective, however, they also help add to the body of evidence in the field of software engineering and software process particularly in terms of Agile methods adoption. Moreover, the study also can help adopters from the nearby geographical regions to understand and see the suitability of Agile methods for their organisations.

Water supplied to residential areas is prone to contaminants due to pipe residues and silt, and therefore resulted in cloudiness, unfavorable taste, and odor in water. Turbidity, a measure of water cloudiness, is one of the important factors for assessing water quality. This paper proposes a low-cost turbidity system based on a light detection unit to measure the cloudiness in water. The automated system uses Intel Galileo 2 as the microprocessor and a server for a web-based monitoring system. The turbidity detection unit consists of a Light Dependent Resistor (LDR) and a Light Emitting Diode (LED) inside a polyvinyl chloride (PVC) pipe. Turbidity readings were recorded for two different positionings; 90° and 180° between the detector (LDR) and the incident light (LED). Once the turbidity level reached a threshold level, the system will trigger the filtration process to clean the water. The voltage output captured from the designed system versus total suspended solid (TSS) in sample water is graphed and analyzed in two different conditions; in total darkness and in the present of ambient light. This paper also discusses and compares the results from the above-mentioned conditions when the system is submerged in still and flowing water. It was found that the trends of the plotted graph decline when the total suspended solid increased for both 90° and 180° detector turbidimeter in all conditions which imitate the trends of a commercial turbidimeter. By taking the consideration of the above findings, the design can be recommended for a low-cost real-time web-based monitoring system of the water quality in an IOT environment.

Abstract-Agile methods are an established process for developing software nowadays. There is, however, less evidence on their usage among software practitioners in Malaysia. While the methods have become mainstream in other regions, that is not the case in this country. This paper empirically investigates the perceptions of Agile methods usage from seven organisations involving 14 software practitioners in Malaysia. Our participants are using Scrum and have a maximum of five years experience. We categorised our findings in terms of awareness, introduction, and challenges they are facing, together with the suggested and practiced solution from them. Interestingly, a change in mind set when practicing Agile was identified to be helpful in reducing the challenges. Lastly we present the practices in Agile they perceived to deliver the most benefits. We found that the use of Agile is still emerging in the country, and awareness is still lacking especially within the government sector. Although several challenges have been encountered when introducing Agile in their organisations, the benefits of Agile are reported to be in Agile practices such as: the involvement from all parties from the beginning, daily stand-up meeting, iterative and incremental, applying burn down chart, sprint and continuous integration. We aim to provide awareness and knowledge about Agile methods to the practitioners in the country and the nearby region. This paper can serve as a reference to the early adopters who intend to use Agile methods in the future.

According to World Health Organization (WHO) report an estimated 17.9 million lives are being lost each year due to cardiovascular diseases (CVDs) and is the top contributor to the death causes. 80% of the cardiovascular cases include heart attacks and strokes. This work is an effort to accurately predict the common heart diseases such as arrhythmia (ARR) and congestive heart failure (CHF) along with the normal sinus rhythm (NSR) based on the integrated model developed using continuous wavelet transform (CWT) and deep neural networks. The proposed method used in this research analyses the time-frequency features of an electrocardiogram (ECG) signal by first converting the 1D ECG signals to the 2D Scalogram images and subsequently the 2D images are being used as an input to the 2D deep neural network model-AlexNet. The reason behind converting the ECG signals to 2D images is that it is easier to extract deep features from images rather than from the raw data for training purposes in AlexNet. The dataset used for this research was obtained from Massachusetts Institute of Technology-Boston's Beth Israel Hospital (MIT-BIH) arrhythmia database, MIT-BIH normal sinus rhythm database and Beth Israel Deaconess Medical Center (BIDMC) congestive heart failure database. In this work, we have identified the best fit parameters for the AlexNet model that could successfully predict the common heart diseases with an accuracy of 98.7%. This work is also being compared with the recent research done in the field of ECG Classification for detection of heart conditions and proves to be an effective technique for the classification.