All Outputs (10)

Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction (2024)
Journal Article
Mishra, B. K., Preniqi, V., Thakker, D., & Feigl, E. (2024). Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction. Discover Internet of Things, 4(1), Article 24. https://doi.org/10.1007/s43926-024-00075-4

Electricity price prediction has an imperative role in the UK energy market among energy trading organisations. The price prediction directly impacts organisational policy for profitable electricity trading, better bidding plans, and the optimisation... Read More about Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction.

A comparative analysis of machine learning algorithms for detecting COVID-19 using lung X-ray images (2024)
Journal Article
Hamal, S., Mishra, B. K., Baldock, R., Sayers, W., Adhikari, T. N., & Gibson, R. M. (2024). A comparative analysis of machine learning algorithms for detecting COVID-19 using lung X-ray images. Decision Analytics Journal, 11, Article 100460. https://doi.org/10.1016/j.dajour.2024.100460

Machine intelligence has the potential to play a significant role in diagnosing, managing, and guiding the treatment of disease, which supports the rising demands on healthcare to provide rapid and accurate interpretation of clinical data. The global... Read More about A comparative analysis of machine learning algorithms for detecting COVID-19 using lung X-ray images.

Tailored risk assessment and forecasting in intermittent claudication (2024)
Journal Article
Ravindhran, B., Prosser, J., Lim, A., Lathan, R., Mishra, B., Hitchman, L., Smith, G. E., Carradice, D., Thakker, D., Chetter, I. C., & Pymer, S. (2024). Tailored risk assessment and forecasting in intermittent claudication. BJS Open, 8(1), Article zrad166. https://doi.org/10.1093/bjsopen/zrad166

Background: Guidelines recommend cardiovascular risk reduction and supervised exercise therapy as the first line of treatment in intermittent claudication, but implementation challenges and poor patient compliance lead to significant variation in man... Read More about Tailored risk assessment and forecasting in intermittent claudication.

A two-phase confirmatory factor analysis and structural equation modelling for customer-based brand equity framework in the smartphone industry (2023)
Journal Article
Shrestha, R., Kadel, R., & Mishra, B. K. (2023). A two-phase confirmatory factor analysis and structural equation modelling for customer-based brand equity framework in the smartphone industry. Decision Analytics Journal, 8, Article 100306. https://doi.org/10.1016/j.dajour.2023.100306

The emergence of smartphones has brought a transformative change in the smartphone industry in terms of technological innovations and business decision-making dynamics. Smartphones have appeared in the market as the standard configuration and current... Read More about A two-phase confirmatory factor analysis and structural equation modelling for customer-based brand equity framework in the smartphone industry.

From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model (2023)
Journal Article
Kureshi, R. R., Thakker, D., Mishra, B. K., & Barnes, J. (2023). From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model. Sensors, 23(7), Article 3613. https://doi.org/10.3390/s23073613

The topic of indoor air pollution has yet to receive the same level of attention as ambient pollution. We spend considerable time indoors, and poorer indoor air quality affects most of us, particularly people with respiratory and other health conditi... Read More about From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model.

A multi-objective evolutionary optimisation model for heterogeneous vehicles routing and relief items scheduling in humanitarian crises (2022)
Journal Article
Mishra, B. K., Dahal, K., Pervez, Z., & Bhattarai, S. (2022). A multi-objective evolutionary optimisation model for heterogeneous vehicles routing and relief items scheduling in humanitarian crises. Decision Analytics Journal, 5, Article 100128. https://doi.org/10.1016/j.dajour.2022.100128

In a disaster scenario, relief items distribution is required as early as possible for the disaster victims to reduce the associated risks. For the distribution tasks, an effective and efficient relief items distribution model is essential to generat... Read More about A multi-objective evolutionary optimisation model for heterogeneous vehicles routing and relief items scheduling in humanitarian crises.

Dynamic Relief Items Distribution Model with Sliding Time Window in the Post-Disaster Environment (2022)
Journal Article
Mishra, B. K., Dahal, K., & Pervez, Z. (2022). Dynamic Relief Items Distribution Model with Sliding Time Window in the Post-Disaster Environment. Applied Sciences, 12(16), Article 8358. https://doi.org/10.3390/app12168358

In smart cities, relief items distribution is a complex task due to the factors such as incomplete information, unpredictable exact demand, lack of resources, and causality levels, to name a few. With the development of Internet of Things (IoT) techn... Read More about Dynamic Relief Items Distribution Model with Sliding Time Window in the Post-Disaster Environment.

Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring (2022)
Journal Article
Kureshi, R., Mishra, B., Thakker, D., John, R., Walker, A., Simpson, S., Thakkar, N., & Wante, A. (2022). Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring. Sensors, 22(3), Article 1093. https://doi.org/10.3390/s22031093

With the emergence of Low-Cost Sensor (LCS) devices, measuring real-time data on a large scale has become a feasible alternative approach to more costly devices. Over the years, sensor technologies have evolved which has provided the opportunity to h... Read More about Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring.

Using Citizen Science to Complement IoT Data Collection: A Survey of Motivational and Engagement Factors in Technology-Centric Citizen Science Projects (2021)
Journal Article
Ali, M. U., Mishra, B. K., Thakker, D., Mazumdar, S., & Simpson, S. (2021). Using Citizen Science to Complement IoT Data Collection: A Survey of Motivational and Engagement Factors in Technology-Centric Citizen Science Projects. IoT, 2(2), 275-309. https://doi.org/10.3390/iot2020015

A key aspect of the development of Smart Cities involves the efficient and effective management of resources to improve liveability. Achieving this requires large volumes of sensors strategically deployed across urban areas. In many cases, however, i... Read More about Using Citizen Science to Complement IoT Data Collection: A Survey of Motivational and Engagement Factors in Technology-Centric Citizen Science Projects.

Explainable artificial intelligence for developing smart cities solutions (2020)
Journal Article
Thakker, D., Mishra, B. K., Abdullatif, A., Mazumdar, S., & Simpson, S. (2020). Explainable artificial intelligence for developing smart cities solutions. Smart Cities, 3(4), 1353-1382. https://doi.org/10.3390/smartcities3040065

Traditional Artificial Intelligence (AI) technologies used in developing smart cities solutions, Machine Learning (ML) and recently Deep Learning (DL), rely more on utilising best representative training datasets and features engineering and less on... Read More about Explainable artificial intelligence for developing smart cities solutions.