Toward Sustainability: Interventions for Implementing Energy-Efficient Systems into Hotel Buildings by Alok Bihari Singh, Yogesh Mishra, Surjeet Yadav

“…The study begins by assessing the energy consumption patterns of hotels and the environmental implications of reliance on conventional energy sources. …”
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Neuromorphic Digital-Twin-Based Controller for Indoor Multi-UAV Systems Deployment by Reza Ahmadvand, Sarah Safura Sharif, Yaser Mike Banad

“…The distributed architecture leverages cloud computing for complex calculations while maintaining local autonomy through edge-based SNNs, significantly reducing energy consumption and computational overhead compared to traditional centralized approaches. …”
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MetaStackD A robust meta learning based deep ensemble model for prediction of sensors battery life in IoE environment by D. Gayathri, S. P. Shantharajah

“…This work focuses on proposing a novel framework integrating pre-processing, standardization, encoding scheme, and predictive modeling that includes two algorithms, RFRImpute and MetaStackD, for predicting the RBL of sensors in any IoE device using a meta-learning-based deep ensemble approach blue for analyzing factors such as power consumption, environmental conditions, operational frequency, and workload patterns. …”
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Efficient and Accurate Zero-Day Electricity Theft Detection from Smart Meter Sensor Data Using Prototype and Ensemble Learning by Alyaman H. Massarani, Mahmoud M. Badr, Mohamed Baza, Hani Alshahrani, Ali Alshehri

“…Smart meter data is compressed using Principal Component Analysis (PCA) and K-means clustering to extract representative consumption patterns, i.e., prototypes, achieving a 92% reduction in dataset size while preserving critical anomaly-relevant features. …”
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Empiric Results from the Successful Implementation of Data-Driven Innovative Energy Services in Buildings by Juan Aranda, Boniface Dominick Mselle, Juliana Cruz, Yassine Rqiq, Jose Manuel Longares

“…We conducted empirical tests in three distinct building typologies: a multi-apartment residential building in Spain, detached dwellings in Croatia, and a hotel bungalow in Greece, to measure self-consumption savings, occupant-driven energy use behaviour changes, and the potential for explicit demand response. …”
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Enhancing LoRa-Based Outdoor Localization Accuracy Using Machine Learning by Nur Kelesoglu, Marzena Halama, Anna Strzoda

“…LoRa (Long Range), together with LoRaWAN, is a prominent LPWAN standard that provides long-range connectivity and low energy consumption, making it viable for IoT-based positioning systems in smart cities. …”
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FedPark: A Federated Learning Crowdsensing Solution for On-Street Parking Availability by Afraa Attiah, Shatha Alahmadi, Abeer Hakeem, Linda Mohaisen, Abeer Almakky, Reemah M. Alhebshi

“…Each local model learns from a user’s driving patterns without sharing personal data, ensuring enhanced privacy protection. …”
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Multi-objective stochastic model optimal operation of smart microgrids coalition with penetration renewable energy resources with demand responses by Ali Abdolahzadeh, Amir Hassannia, Farhoud Mousavizadeh, Mohammad Tolou Askari

“…The integration of EV-based storage and demand response strategies further enhances system resilience and economic performance by dynamically adjusting energy consumption patterns and mitigating the intermittency of renewables. …”
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Optimizing Reservoir Separability in Liquid State Machines for Spatio-Temporal Classification in Neuromorphic Hardware by Oscar I. Alvarez-Canchila, Andres Espinal, Alberto Patiño-Saucedo, Horacio Rostro-Gonzalez

“…In this paper, we propose an optimization approach using Particle Swarm Optimization (PSO) to enhance reservoir separability in Liquid State Machines (LSMs) for spatio-temporal classification in neuromorphic systems. By leveraging PSO, our method fine-tunes reservoir parameters, neuron dynamics, and connectivity patterns, maximizing separability while aligning with the resource constraints typical of neuromorphic hardware. …”
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Comprehensive Performance Evaluation of Steel Slag–Slag–Desulfurization Gypsum Ternary Solid Waste Cementitious Material Based on Principal Component Analysis by Mengqi Wang, Jian Xu, Tao Li, Hui Liu, Lei Qu

“…Leveraging industrial solid waste for the production of cementitious materials holds the potential to curtail the consumption of traditional cement. …”
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Water conservation strategies reduce greenhouse gas emission from wastewater treatment plants: A domino effect by Zixiang He, Rupeng Wang, Jifeng Wang, Honglin Chen, Shiyu Zhang, Ke Wang, Junjiang Lai, Nanqi Ren, Shih-Hsin Ho

“…Here we show a domino-effect feedback between urban water-use patterns with WWTP carbon emissions. Our analysis demonstrates that optimized water management can improve average WWTP eco-efficiency by up to 189 %, leading to an annual reduction in water consumption of 48.3 billion m3 and a decrease in GHG emissions by 1.67 million tons CO2-equivalent. …”
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BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices by Emre Şafak, İbrahim Alper Doğru, Necaattin Barışçı, İsmail Atacak

“…By converting Android DEX files into image data, BlockDroid leverages the superior image analysis capabilities of CNN models to discern patterns indicative of malware. …”
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Contactless Triboelectric Sensing for Real‐Time 3D Motion Recognition in Human‐Computer Interaction by Qinghao Xu, Junhao Gong, Jiayi Chen, Yimeng Zhang, Hongfa Zhao, Jiaqi Yin, Runze Zhao, Chuqiao Lyu, Wenbo Ding, Changsheng Wu

“…This study introduces an HCI system that leverages a contactless triboelectric detector (CTD) to classify complex motion patterns in 3D space. …”
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Comparative Lifecycle Assessment of Renewable Energy Investments in Public Buildings: A Case Study of an Austrian Kindergarten Under Atypical Operational Conditions by Georgia Kousovista, Giannis Iakovides, Stefanos Petridis, Nikolaos-Charalampos Chairopoulos, Angelos Skembris, Maria Fotopoulou, Despina Antipa, Nikolaos Nikolopoulos, Dimitrios Rakopoulos

“…The pandemic-induced occupancy reduction led to atypical energy demand patterns, with lower self-consumption and increased electricity exports to the grid, affecting the financial viability of PV investments. …”
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Scalability analysis of heavy-duty gas turbines using data-driven machine learning by Shubhasmita Pati, Julian D. Osorio, Mayank Panwar, Rob Hovsapian

“…The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). …”
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Pretraining-improved Spatiotemporal graph network for the generalization performance enhancement of traffic forecasting by Xiangyue Zhang, Chao Li, Ling Ji, Yuyun Kang, Mingming Pan, Zhuo Liu, Qiang Qi

“…This module enables more efficient processing of long sequences, extracting essential patterns while minimizing computational resource consumption. …”
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Reconfigurable optoelectronic neuromorphic properties of MoS2-based memristors decorated with Pt nanoparticles for low power spiking neural network applications by Chrysi Panagopoulou, Panagiotis Bousoulas, Georgia Iliani Papouli, Maria Kainourgiaki, Charalampos Tsioustas, Maria Karnachoriti, Athanassios G Kontos, Dimitris Tsoukalas

“…In parallel, their layered structure can be leveraged to optically program the device and further reduce power consumption. …”
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Heterogeneous integration of 2D memristor arrays and silicon selectors for compute-in-memory hardware in convolutional neural networks by Samarth Jain, Sifan Li, Haofei Zheng, Lingqi Li, Xuanyao Fong, Kah-Wee Ang

“…Abstract Memristor crossbar arrays (CBAs) based on two-dimensional (2D) materials have emerged as a potential solution to overcome the limitations of energy consumption and latency associated with conventional von Neumann architectures. …”
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Food digital marketing on social media: trends and strategies of Brazil’s leading meal delivery app by Paloma Aparecida Anastacio Barros, Juliana de Paula Matos, Michele Bittencourt Rodrigues, Renata Júlia da Costa, Paula Martins Horta

“…These practices may hinder public health efforts to reduce the consumption of unhealthy foods.…”
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Spatiotemporal differences and influencing factors of the dietary structure index in Chinese urban residents by Tianyang Chen, Zheng Guo, Zheng Guo, Sophia Shuang Chen, Sophia Shuang Chen, Giri Raj Kattel, Giri Raj Kattel, Giri Raj Kattel, Shimou Yao

“…We propose promoting plant-based diets and reducing excessive meat consumption in high-DSI regions, while leveraging urban infrastructure to deliver nutrition education and providing subsidies for healthier food options in markets. …”
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