File photo of Mustafizur Rahman. The BCCI has asked Kolkata Knight Riders to release the fast bowler due to recent developments in Bangladesh.
| Photo Credit: Emmanual Yogini
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KKR confirms exclusion of Mustafizur Rahman from squad after BCCI directive
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Short-Handed Warriors Fall to Defending Champion Thunder – NBA
- Short-Handed Warriors Fall to Defending Champion Thunder NBA
- Thunder send depleted Warriors to worst loss of season Reuters
- Will Richard: “ball movement, making the simple play, playing off two (feet)” letsgowarriors.com
- Steve Kerr Gives…
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Oppo India Introduces ‘Live It Your Way’ Film As Part Of Reno15 Series Promotions – BW Marketing World
- Oppo India Introduces ‘Live It Your Way’ Film As Part Of Reno15 Series Promotions BW Marketing World
- OPPO Reno 15 Series 5G Coming to India Sooner Than Expected with Exciting Pre-Launch Offers Techgenyz
- Oppo Reno15 Pro Max and Reno15 Pro…
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Research on multi-stage on-board detection algorithm of track defects of high-speed railway based on the influence mechanism of track defects
Liu, X. Z. et al. Correlation analysis between rail track geometry and car-body vibration based on fractal theory[J]. Fractal Fract. 6 (12), 727 (2022).
Xiao, X. et al. A bayesian Kalman filter…
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Electric vehicles charging stations load forecasting based on hybrid XGBoost-BiLSTM model
Ahmad, N., Ghadi, Y., Adnan, M. & Ali, M. Load forecasting techniques for power system: research challenges and survey. IEEE Access 10, 71054–71090. https://doi.org/10.1109/ACCESS.2022.3187839 (2022).
Khan, S. Short-term electricity load forecasting using a new intelligence-based application. Sustainability https://doi.org/10.3390/su151612311 (2023).
Udendhran, R. et al. Transitioning to sustainable E-vehicle systems – Global perspectives on the challenges, policies, and opportunities. J. Hazard. Mater. Adv. 17, 100619. https://doi.org/10.1016/J.HAZADV.2025.100619 (2025).
Elahe, M. F., Kabir, M. A., Mahmud, S. M. H. & Azim, R. Factors impacting short-term load forecasting of charging station to electric vehicle. Electronics (Switzerland) https://doi.org/10.3390/electronics12010055 (2023).
Ran, J., Gong, Y., Hu, Y. & Cai, J. L. EV load forecasting using a refined CNN-LSTM-AM. Electr. Power Syst. Res. 238(August), 2025. https://doi.org/10.1016/j.epsr.2024.111091 (2024).
Van Kriekinge, G., De Cauwer, C., Sapountzoglou, N., Coosemans, T. & Messagie, M. Day-ahead forecast of electric vehicle charging demand with deep neural networks. World Electric Veh. J. https://doi.org/10.3390/wevj12040178 (2021).
Cheng, S., Wei, Z., Shang, D., Zhao, Z. & Chen, H. Charging load prediction and distribution network reliability evaluation considering electric vehicles’ spatial-temporal transfer randomness. IEEE Access 8, 124084–124096. https://doi.org/10.1109/ACCESS.2020.3006093 (2020).
S. Su, H. Zhao, H. Zhang, X. Lin, F. Yang, and Z. Li, Forecast of electric vehicle charging demand based on traffic flow model and optimal path planning. In: 2017 19th International Conference on Intelligent System Application to Power Systems, ISAP 2017. https://doi.org/10.1109/ISAP.2017.8071382. (2017).
Tang, D. & Wang, P. Probabilistic modeling of nodal charging demand based on spatial-temporal dynamics of moving electric vehicles. IEEE Trans. Smart Grid 7(2), 627–636. https://doi.org/10.1109/TSG.2015.2437415 (2016).
Zhang, Q., Chen, J., Xiao, G., He, S. & Deng, K. TransformGraph: A novel short-term electricity net load forecasting model. Energy Rep. 9, 2705–2717. https://doi.org/10.1016/j.egyr.2023.01.050 (2023).
Gao, S. X., Liu, H. & Ota, J. Energy-efficient buffer and service rate allocation in manufacturing systems using hybrid machine learning and evolutionary algorithms. Adv. Manuf 12(2), 227–251. https://doi.org/10.1007/S40436-023-00461-1/FIGURES/9 (2024).
Amini, M. H., Kargarian, A. & Karabasoglu, O. ARIMA-based decoupled time series forecasting of electric vehicle charging demand for stochastic power system operation. Electr. Power Syst. Res. 140, 378–390. https://doi.org/10.1016/J.EPSR.2016.06.003 (2016).
Louie, H. M. Time-series modeling of aggregated electric vehicle charging station load. Electr. Power Compon. Syst. 45(14), 1498–1511. https://doi.org/10.1080/15325008.2017.1336583 (2017).
A. Gautam, A. K. Verma, and M. Srivastava. A novel algorithm for scheduling of electric vehicle using adaptive load forecasting with vehicle-to-grid integration. In: 2019 8th International Conference on Power Systems: Transition towards Sustainable, Smart and Flexible Grids, ICPS 2019. https://doi.org/10.1109/ICPS48983.2019.9067702. (2019).
Almaghrebi, A., Aljuheshi, F., Rafaie, M., James, K. & Alahmad, M. Data-driven charging demand prediction at public charging stations using supervised machine learning regression methods. Energies (Basel) https://doi.org/10.3390/en13164231 (2020).
Peng, Y. & Unluer, C. Modeling the mechanical properties of recycled aggregate concrete using hybrid machine learning algorithms. Resour. Conserv. Recycl. 190, 106812. https://doi.org/10.1016/j.resconrec.2022.106812 (2022).
Zhu, J., Yang, Z., Guo, Y., Zhang, J. & Yang, H. Short-term load forecasting for electric vehicle charging stations based on deep learning approaches. Appl. Sci. (Switzerland) https://doi.org/10.3390/app9091723 (2019).
Aduama, P., Zhang, Z. & Al-Sumaiti, A. S. Multi-feature data fusion-based load forecasting of electric vehicle charging stations using a deep learning model. Energies (Basel) https://doi.org/10.3390/en16031309 (2023).
Van Kriekinge, G., De Cauwer, C., Sapountzoglou, N., Coosemans, T. & Messagie, M. Day-ahead forecast of electric vehicle charging demand with deep neural networks. World Electr. Veh. J. 12(4), 178. https://doi.org/10.3390/WEVJ12040178 (2021).
Li, Y. et al. Probabilistic charging power forecast of EVCS: reinforcement learning assisted deep learning approach. IEEE Trans. Intell. Veh. 8(1), 344–357. https://doi.org/10.1109/TIV.2022.3168577 (2023).
Zhou, D. et al. Using Bayesian deep learning for electric vehicle charging station load forecasting. Energies 15(17), 6195. https://doi.org/10.3390/EN15176195 (2022).
Mohammad, F., Kang, D. K., Ahmed, M. A. & Kim, Y. C. Energy demand load forecasting for electric vehicle charging stations network based on ConvLSTM and BiConvLSTM architectures. IEEE Access 11, 67350–67369. https://doi.org/10.1109/ACCESS.2023.3274657 (2023).
Naveed, M. S. et al. Enhanced accuracy in solar irradiance forecasting through machine learning stack-based ensemble approach. Int. J. Green Energy https://doi.org/10.1080/15435075.2025.2450468 (2025).
Naveed, M. S. et al. Leveraging advanced AI algorithms with transformer-infused recurrent neural networks to optimize solar irradiance forecasting. Front. Energy Res. https://doi.org/10.3389/fenrg.2024.1485690 (2024).
Hanif, J. M. M. F. et al. The Solar AI Nexus: Reinforcement Learning Shaping the Future of Energy Management (Wiley, 2025).
D.-E. L. Yuvaraj Natarajan, Sri Preethaa K. R, Gitanjali Wadhwa, Young Choi, Zengshun Chen, D.-E. Lee, and Y. M. Scholar, SciProfilesScilitPreprints.orgGoogle. Enhancing building energy efficiency with IoT-driven hybrid deep learning models for accurate energy consumption prediction. Coimbatore 641407, India. https://www.mdpi.com/2071-1050/16/5/1925.
ACN-Dataset. https://ev.caltech.edu/dataset.
T. Chen, C. G.-P. of the 22nd acm sigkdd international, and undefined 2016. Xgboost: A scalable tree boosting system. dl.acm.orgT Chen, C GuestrinProceedings of the 22nd acm sigkdd international conference on knowledge, 2016•dl.acm.org, 13–17, 785–794. https://doi.org/10.1145/2939672.2939785. (2016).
Z. Huang, W. Xu, and K. Yu. Bidirectional LSTM-CRF Models for Sequence Tagging. http://arxiv.org/abs/1508.01991. (2015).
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Beavers Fall at Pacific – Oregon State University Athletics
Stockton, Calif. – The Oregon State men’s basketball team fell to Pacific 84-53 Friday evening in Stockton, Calif.
Johan Munch led the Beavers with 12 points and five rebounds on 5-for-10 shooting. Keziah Ekissi also finished with 12 points…Continue Reading
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UND on the International Stage: Jan. 2, 2026
GRAND FORKS, N.D. – It was do-or-die time at the 2026 IIHF World Junior Championships on Friday, as the quarterfinal round took place…
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Weather Forces Location Change For January 3, January 4
LONG BEACH, Calif. – Southern California rains have caused Long Beach State Athletics to make the decision to move both the January 3 Men’s Basketball game against Cal Poly and the second day of the Men’s Volleyball North American Challenge…
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