Considering the Smartphone Learner: developing innovation to investigate the opportunities for students and their interest

Ownership of mobile smartphones amongst the general consumer, professionals and students is growing exponentially. The potential for smartphones in education builds upon experience described in the extensive literature on mobile learning from the previous decade which suggests that the ubiquity, multi-functionality and connectivity of mobile devices offers a new and potentially powerful networked learning environment. This paper reports on a collaborative study conducted by an undergraduate student with the support of two members of academic staff. The research sought to establish the extent to which students are autonomously harnessing smartphone technology to support their learning and the nature of this use. Initial findings were explored through student interviews. The study found that students who own smartphones are largely unaware of their potential to support learning and, in general, do not install smartphone applications for that purpose. They are, however, interested in and open to the potential as they become familiar with the possibilities for a range of purposes. The paper proposes that more consideration needs to be given to smartphones as platforms to support formal, informal and autonomous learner engagement. The study also reflects on its collaborative methodology and the challenges associated with academic innovation

Predicting the Number of Passengers of MRT Jakarta Based on the Use of the QR-Code Payment Method during the Covid-19 Pandemic Using Long Short-Term Memory

The trend of using public transportation has been rising over the last several decades. Because of increased mobility, public transportation has now become more crucial. In modern environments, public transportation is not only used to carry people and products from one location to another but has also evolved into a service company. In Jakarta, Mass Rapid Transit Jakarta (MRTJ) started to operate in late 2019. Recently, they updated their payment gateway system with QR codes. In this study, we predicted the hourly influx of passengers who used QR codes as their preferred payment method. This research applied machine learning to perform a prediction methodology, which is proposed to predict the number of passengers using time-series analysis. The dataset contained 7760 instances across different hours and days in June 2020 and was reshaped to display the total number of passengers each hour. Next, we incorporated time-series regression alongside LSTM frameworks with variations in architecture. One architecture, the 1D CNN-LSTM, yielded a promising prediction error of only one to two passengers for every hour

Sixth Sense Transport : Challenges in Supporting Flexible Time Travel

In this paper, we consider the challenges associated with providing a mobile computing system that helps users enjoy a more flexible relationship between time and travel. Current travel plans, especially in Western cultures, are dominated by a strict notion of time. The need to conform to schedules leads to increased pressures for travellers and inefficiencies when these schedules cannot be met. We are interested in exploring the extent to which mobile computing can be used to help travellers relax these schedules and adopt a more opportunistic approach to travel – potentially helping to reduce the environmental, financial and societal costs of modern travel

Tiny Codes for Guaranteeable Delay

Future 5G systems will need to support ultra-reliable low-latency communications scenarios. From a latency-reliability viewpoint, it is inefficient to rely on average utility-based system design. Therefore, we introduce the notion of guaranteeable delay which is the average delay plus three standard deviations of the mean. We investigate the trade-off between guaranteeable delay and throughput for point-to-point wireless erasure links with unreliable and delayed feedback, by bringing together signal flow techniques to the area of coding. We use tiny codes, i.e. sliding window by coding with just 2 packets, and design three variations of selective-repeat ARQ protocols, by building on the baseline scheme, i.e. uncoded ARQ, developed by Ausavapattanakun and Nosratinia: (i) Hybrid ARQ with soft combining at the receiver; (ii) cumulative feedback-based ARQ without rate adaptation; and (iii) Coded ARQ with rate adaptation based on the cumulative feedback. Contrasting the performance of these protocols with uncoded ARQ, we demonstrate that HARQ performs only slightly better, cumulative feedback-based ARQ does not provide significant throughput while it has better average delay, and Coded ARQ can provide gains up to about 40% in terms of throughput. Coded ARQ also provides delay guarantees, and is robust to various challenges such as imperfect and delayed feedback, burst erasures, and round-trip time fluctuations. This feature may be preferable for meeting the strict end-to-end latency and reliability requirements of future use cases of ultra-reliable low-latency communications in 5G, such as mission-critical communications and industrial control for critical control messaging.Comment: to appear in IEEE JSAC Special Issue on URLLC in Wireless Network