| The elderly’s independent living in smart homes: A characterization of activities and sensing infrastructure survey to facilitate services development Q Ni, AB Garcia Hernando, IP De la Cruz Sensors 15 (5), 11312-11362, 2015 | 323 | 2015 |
| A foundational ontology-based model for human activity representation in smart homes Q Ni, I Pau de la Cruz, AB Garcia Hernando Journal of Ambient Intelligence and Smart Environments 8 (1), 47-61, 2016 | 63 | 2016 |
| Dynamic detection of window starting positions and its implementation within an activity recognition framework Q Ni, T Patterson, I Cleland, C Nugent Journal of biomedical informatics 62, 171-180, 2016 | 62 | 2016 |
| A context-aware system infrastructure for monitoring activities of daily living in smart home Q Ni, AB García Hernando, I Pau de la Cruz Journal of Sensors 2016, 2016 | 49 | 2016 |
| RCL-Learning: ResNet and convolutional long short-term memory-based spatiotemporal air pollutant concentration prediction model B Zhang, G Zou, D Qin, Q Ni, H Mao, M Li Expert Systems with Applications 207, 118017, 2022 | 28 | 2022 |
| Body temperature monitoring for regular COVID-19 prevention based on human daily activity recognition L Zhang, Y Zhu, M Jiang, Y Wu, K Deng, Q Ni Sensors 21 (22), 7540, 2021 | 27 | 2021 |
| A heterogeneous ensemble approach for activity recognition with integration of change point-based data segmentation Q Ni, L Zhang, L Li Applied Sciences 8 (9), 1695, 2018 | 26 | 2018 |
| Leveraging wearable sensors for human daily activity recognition with stacked denoising autoencoders Q Ni, Z Fan, L Zhang, CD Nugent, I Cleland, Y Zhang, N Zhou Sensors 20 (18), 5114, 2020 | 24 | 2020 |
| HHSKT: A learner–question interactions based heterogeneous graph neural network model for knowledge tracing Q Ni, T Wei, J Zhao, L He, C Zheng Expert Systems with Applications 215, 119334, 2023 | 18 | 2023 |
| Prediction of snp sequences via gini impurity based gradient boosting method L Jiang, B Zhang, Q Ni, X Sun, P Dong IEEE Access 7, 12647-12657, 2019 | 18 | 2019 |
| An ensemble learning scheme for indoor-outdoor classification based on KPIs of LTE network L Zhang, Q Ni, M Zhai, J Moreno, C Briso IEEE Access 7, 63057-63065, 2019 | 16 | 2019 |
| Sensor-based change detection for timely solicitation of user engagement T Patterson, N Khan, S McClean, C Nugent, S Zhang, I Cleland, Q Ni IEEE Transactions on Mobile Computing 16 (10), 2889-2900, 2016 | 13 | 2016 |
| Design and assessment of the data analysis process for a wrist-worn smart object to detect atomic activities in the smart home Q Ni, I Cleland, C Nugent, ABG Hernando, IP de la Cruz Pervasive and Mobile Computing 56, 57-70, 2019 | 9 | 2019 |
| Random forests‐enabled context detections for long‐term evolution network forrailway L Zhang, Q Ni, G Zhang, M Zhai, J Moreno, C Briso IET Microwaves, Antennas & Propagation 13 (8), 1080-1086, 2019 | 8 | 2019 |
| De la Cruz, and Iván Pau,“ Q Ni, ABG Hernando The elderly’s independent living in smart homes: A characterization of …, 2015 | 7 | 2015 |
| Learning Style Integrated Deep Reinforcement Learning Framework for Programming Problem Recommendation in Online Judge System Y Xu, Q Ni, S Liu, Y Mi, Y Yu, Y Hao International Journal of Computational Intelligence Systems 15 (1), 114, 2022 | 6 | 2022 |
| Daily activity recognition and tremor quantification from accelerometer data for patients with essential tremor using stacked denoising autoencoders Q Ni, Z Fan, L Zhang, B Zhang, X Zheng, Y Zhang International Journal of Computational Intelligence Systems 15 (1), 1, 2022 | 5 | 2022 |
| Interdisciplinary method for assessing students’ ability based on stem projects Q Ni, L Zhang, Z Bo, FK Chiang The International journal of engineering education 35 (2), 698-709, 2019 | 4 | 2019 |
| Bayesian Knowledge Tracing based on Transformer T Wei, B Hu, Q Ni 2022 IEEE 5th International Conference on Electronic Information and …, 2022 | 2 | 2022 |
| A Review on Machine Theory of Mind Y Mao, S Liu, P Zhao, Q Ni, X Lin, L He arXiv preprint arXiv:2303.11594, 2023 | 1 | 2023 |
