Ensemble prediction model with expert selection for electricity price forecasting

Forecasting of electricity prices is important in deregulated electricity markets for all of the stakeholders: energy wholesalers, traders, retailers and consumers. Electricity price forecasting is an inherently difficult problem due to its special characteristic of dynamicity and non-stationarity. In this paper, we present a robust price forecasting mechanism that shows resilience towards the aggregate demand response effect and provides highly accurate forecasted electricity prices to the stakeholders in a dynamic environment. We employ an ensemble prediction model in which a group of different algorithms participates in forecasting 1-h ahead the price for each hour of a day. We propose two different strategies, namely, the Fixed Weight Method (FWM) and the Varying Weight Method (VWM), for selecting each hour’s expert algorithm from the set of participating algorithms. In addition, we utilize a carefully engineered set of features selected from a pool of features extracted from the past electricity price data, weather data and calendar data. The proposed ensemble model offers better results than the Autoregressive Integrated Moving Average (ARIMA) method, the Pattern Sequence-based Forecasting (PSF) method and our previous work using Artificial Neural Networks (ANN) alone on the datasets for New York, Australian and Spanish electricity markets

A Global Collaboration to Develop and Pilot Test a Mobile Application to Improve Cancer Pain Management in Nepal

INTRODUCTION: Quality palliative care, which prioritizes comfort and symptom control, can reduce global suffering from non-communicable diseases, such as cancer. To address this need, the Nepalese Association of Palliative Care (NAPCare) created pain management guidelines (PMG) to support healthcare providers in assessing and treating serious pain. The NAPCare PMG are grounded in World Health Organization best practices but adapted for the cultural and resource context of Nepal. Wider adoption of the NAPCare PMG has been limited due to distribution of the guidelines as paper booklets. METHODS: Building on a long-standing partnership between clinicians and researchers in the US and Nepal, the NAPCare PMG mobile application (“app”) was collaboratively designed. Healthcare providers in Nepal were recruited to pilot test the app using patient case studies. Then, participants completed a Qualtrics survey to evaluate the app which included the System Usability Scale (SUS) and selected items from the Mobile App Rating Scale (MARS). Descriptive and summary statistics were calculated and compared across institutions and roles. Regression analyses to explore relationships (α = 0.05) between selected demographic variables and SUS and MARS scores were also conducted. RESULTS: Ninety eight healthcare providers (n = 98) pilot tested the NAPCare PMG app. Overall, across institutions and roles, the app received an SUS score of 76.0 (a score > 68 is considered above average) and a MARS score of 4.10 (on a scale of 1 = poor, 5 = excellent). 89.8% (n = 88) “agreed” or “strongly agreed” that the app will help them better manage cancer pain. Age, years of experience, and training in palliative care were significant in predicting SUS scores (p-values, 0.0124, 0.0371, and 0.0189, respectively); institution was significant in predicting MARS scores (p = 0.0030). CONCLUSION: The NAPCare PMG mobile app was well-received, and participants rated it highly on both the SUS and MARS. Regression analyses suggest end-user variables important to consider in designing and evaluating mobile apps in lower resourced settings. Our app design and pilot testing process illustrate the benefits of cross global collaborations to build research capacity and generate knowledge within the local context

Detecting click fraud in online advertising: A data mining approach

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding InitiativeSubmit request for dataset at https://larc.smu.edu.sg/buzzcity-mobile-advertisement-dataset</p

Impact of mobile technology on digital libraries

With the rapid advancement in technology in last two decades, mainly because of the advent of internet, the world no longer works the same. The advent of wireless networks and more recently mobile devices such as smart phones, tablets etc following the internet, contributed a lot to make mobile technology come into existence. The technology has gone on miles since then and there has been no looking back. Mobile devices, which were initially devised with an intention to replace telephones using wireless technology, have now become a very important part of daily communication not only for telephone service users but also for the internet users. Recent studies conducted at different places reveal that the volume of usage of internet using mobile devices is increasing at a very rapid pace. The two main reasons behind success of mobile technology is the benefits such as mobility and ubiquity served by mobile devices. The existing technology is obviously expected to improve rather more in future. These are the reasons why mobile technology is seen as future of communication by many. Mobile devices need an underlying support from Operating System and also need hardware and software support to communicate properly. The devices communicate across different platforms using a communication channel so they also need a defined set of protocols and network support in order to communicate and as mentioned earlier they need internet connection to communicate