Review on the Pre-treatment Advancements of Biogas Production Barriers by Amoo, A.O., Ijanu, E.M., Haruna, A., Adeleye, A.O, Sabo, A.

“… Biogas production is a promising renewable energy source that can reduce greenhouse gas emissions and improve environmental health. …”
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Deep learning-based improved transformer model on android malware detection and classification in internet of vehicles by Naif Almakayeel

“…To efficiently counter new malware variants, novel techniques distinct from conventional methods must be utilized. …”
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Study of a Remote Wind Resource Assessment System Integrated with Internet of Things by Filian Arbiyani, Filbert Filbert, Anthony Nathanael Theo

“…Wind energy is an emerging and popular source of clean energy due to its non-polluting nature and low cost. …”
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A Multiscale CNN-Based Intrinsic Permeability Prediction in Deformable Porous Media by Yousef Heider, Fadi Aldakheel, Wolfgang Ehlers

“…Examples demonstrate the CNN’s ability to accurately predict the permeability tensor in connection with the deformation state through the porosity parameter. A source code has been made available as open access.…”
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Knowledge-Grounded Attention-Based Neural Machine Translation Model by Huma Israr, Safdar Abbas Khan, Muhammad Ali Tahir, Muhammad Khuram Shahzad, Muneer Ahmad, Jasni Mohamad Zain

“…Side information related to either source or target side is helpful in the context of NMT. …”
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Vibration Signal-Based Fault Diagnosis of Rotary Machinery Through Convolutional Neural Network and Transfer Learning Method by Chirag Mongia, Shankar Sehgal

“…To address this limitation, a transfer learning (TL)-based methodology has been developed for bearing fault detection, so that the model trained under some specific training conditions can perform accurately under significantly different real-time working conditions, thereby significantly improving diagnostic efficiency while reducing training time. Initially, a deep learning approach utilizing convolutional neural networks (CNNs) has been employed to diagnose faults based on vibration data. …”
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TSMixer- and Transfer Learning-Based Highly Reliable Prediction with Short-Term Time Series Data in Small-Scale Solar Power Generation Systems by Younjeong Lee, Jongpil Jeong

“…In the process of developing a prediction model suitable for the target domain by utilizing multi-source data, we propose a data similarity evaluation method using DTW, which demonstrates excellent performance with low error rates in the MSE and MAE metrics compared with conventional long short-term memory (LSTM) and Transformer models. …”
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Recent Progress in Designing Nanomaterial Biohybrids for Artificial Photosynthesis by Sampathkumar Jeevanandham, Subramaniyan Ramasundaram, Natarajan Vijay, Tae Hwan Oh, Subramanian Tamil Selvan

“…In natural photosynthesis, solar energy is utilized to convert water and CO₂ into energy-rich compounds. …”
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Central composite design in predicting heat transfer rate on the time-dependent flow of Williamson nanofluid with chemical reaction: A response surface methodology by B.C. Rout, Subhajit Panda, S.R. Mishra, Rupa Baithalu

“…Further, a statistical approach embedding central composite design is executed for the efficient heat transfer rate utilizing various influencing terms. …”
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The Significance of Probiotics in Aquaculture: A Review of Research Trend and Latest Scientific Findings by Elshafia Ali Hamid Mohammed, Abdelhakam Esmaeil Mohamed Ahmed, Béla Kovács, Károly Pál

“…In addition, an extensive review of the recent literature showed that probiotics have demonstrated a remarkable efficacy in improving the growth performance, feed utilization efficiency, disease prevention, and water quality management in various aquaculture species under different aquaculture systems when used as feed or water additives for 30–90 days. …”
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A Full Chain of Applying Struvite Recovered from Biogas Slurry to Promote Vegetable Growth by Yunhan Li, Wei Wang, Linhe Sun, Jian Cui, Xiaojing Liu, Jixiang Liu, Yajun Chang, Dongrui Yao

“…The N and P recovery efficiency was higher when magnesium chloride (MgCl₂) was used as a magnesium (Mg) source compared with magnesium oxide (MgO), and the optimal reaction conditions were pH 10, a reaction time of 20 min, a stirring rate of 200 rpm, and a Mg/P/N ratio of 1.2:1.0:1.0, which achieved N and P recovery rates of 81.83% and 99.67%, respectively. …”
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Performance and Applicability Analysis of Indirect Evaporative Cooling Units in Data Centers Across Various Humidity Regions by Qian Wei, Jun Lu, Xiaoping Xia, Bin Zhang, Xiang Ying, Leihong Li

“…Indirect evaporative cooling (IEC), which utilizes natural cooling sources, is an advanced and promising technology to reduce the energy consumption of cooling systems in a data center (DC). …”
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Advancements in Integrated Thermoelectric Power Generation and Water Desalination Technologies: A Comprehensive Review by Oranit Traisak, Pranjal Kumar, Sara Vahaji, Yihe Zhang, Abhijit Date

“…The growing population and reliance on fossil fuels for electricity generation pose challenges related to environmental pollution and resource depletion, necessitating the exploration of alternative energy sources and desalination techniques. While thermoelectric generators are capable of converting low-temperature thermal energy into electricity and desalination processes that can utilize low-temperature thermal energy, their effective integration remains largely unexplored. …”
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Enhanced electrochemical performance of activated carbon derived from Acacia catechu bark by KOH activation for supercapacitor application by Mishra Pawan Kumar, Aryal Sabin, Bhakta Oli Hari, Shrestha Timila, Sapkota Thakur, Shrestha Ram Lal Swagat, Prasad Bhattarai Deval

“…Conventional carbon materials derived from fossils sources cause the limitations of being high rate, processing challenges, and potential harm. …”
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Distributionally robust microgrid formation for service restoration in distribution systems against extended extreme events by Ran Zhu, Hongzhe Liu, Wenwu Yu, Wei Gu, Jin Zhao

“…Microgrid formation (MF) has emerged as a crucial approach for service restoration (SR) under such circumstances since local resources can be utilized to provide temporary power supplies. This paper proposes a novel MF-based SR approach for the DS to maximize the expected weighted load served ratio (WLSR) by allocating mobile power sources and dynamic MF scheduling in the worst case against extended extreme events. …”
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Design of a Portable Integrated Fluid–Structure Interaction-Based Piezoelectric Flag Energy-Harvesting System by Haochen Wang, Xingrong Huang, Zhe Li, Le Fang

“…Charge–discharge experiments on the energy storage unit enable a comprehensive evaluation of system performance, marking the first efficiency measurement of a fully integrated energy-harvesting system. …”
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Microplastic removal in aquatic systems using extracellular polymeric substances (EPS) of microalgae by H. Hadiyanto, Adian Khoironi, Inggar Dianratri, Falvocha Alifsmara Joelyna, Marcelinus Christwardana, Adhelia Intan Sabhira, Rifqi Ahmad Baihaqi

“…Microplastic contamination in clean water sources and household wastewater is a significant environmental issue that requires sustainable remediation solutions. …”
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Human Behavior Analysis Using Radar Data: A Survey by Patrycja Miazek, Alicja Zmudzinska, Pawel karczmarek, Adam Kiersztyn

“…Transfer learning addresses issues related to data scarcity, while data fusion models integrate information from multiple sources. Advances in machine learning, data processing, and GPU speed contribute to the increased efficiency of radar technology for indoor monitoring, opening possibilities for more advanced applications. …”
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Carbon Footprint of Polypropylene Product in Iranian Petrochemical Industry by Sara Safi Jahanshahi, Ahmad Sherafati, Hossein Vahidi

“…By identifying these critical areas, the research not only advances our understanding of polypropylene's environmental profile but also suggests targeted interventions such as the adoption of renewable energy sources and efficiency improvements. This analysis not only sets a benchmark for future environmental assessments within the industry but also serves as a crucial tool for policymakers and industry leaders aiming to implement more sustainable manufacturing practices. …”
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Comparative analysis of machine learning models for detecting water quality anomalies in treatment plants by P. Prabu, Ala Saleh Alluhaidan, Romana Aziz, Shakila Basheer

“…These results highlight the model’s strong predictive capability and its practical utility in improving water treatment plant efficiency. …”
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