Engineering Synthetic Microbial Communities: Diversity and Applications in Soil for Plant Resilience by Arneeb Tariq, Shengzhi Guo, Fozia Farhat, Xihui Shen

“…We also discuss the barriers to the implementation of these technologies in SynCom engineering. …”
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Optimizing Energy Efficiency in UPA-Assisted SWIPT Massive MIMO Systems Over Rician Fading Channels by Mohammad Hassan Adeli, Dariush Abbasi-Moghadam, Hossein Fotouhi, S. Mohammad Razavizadeh

“…The Results also indicate a considerably higher growth rate on EE by increasing the number of antennas and Rician factors compared to the two other methods.…”
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Integrating artificial intelligence for sustainable waste management: Insights from machine learning and deep learning by Son V.T. Dao, Tuan M. Le, Hieu M. Tran, Hung V. Pham, Minh T. Vu, Tuan Chu

“…Then these selected features are fed into Machine Learning algorithms such as Decision Tree (DT), Logistic Regression (LR), and Random Forest (RF). …”
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Livestock Biometrics Identification Using Computer Vision Approaches: A Review by Hua Meng, Lina Zhang, Fan Yang, Lan Hai, Yuxing Wei, Lin Zhu, Jue Zhang

“…Then, the review delves into the analysis and explication of livestock identification methods, based on extant research outcomes, with a focus on the application and trends of advanced technologies such as deep learning. We also highlight the challenges faced in this field, such as data quality and algorithmic efficiency, and introduce the baseline models and innovative solutions developed to address these issues. …”
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Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data by Chien Wei Oei, Eddie Yin Kwee Ng, Matthew Hok Shan Ng, Yam Meng Chan, Vinithasree Subbhuraam, Lai Gwen Chan, U. Rajendra Acharya

“…In addition, sequential data such as daily lab results taken seven consecutive days after admission are also collected. The combination of using DL algorithms, such as multi-layer perceptron (MLP) and long short-term memory (LSTM), which can process complex patterns in the data, and the inclusion of new data types, such as sequential data, helped to improve model performance. …”
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EFFECTS OF COVID-19 PANDEMIC ON DENTISTRY SERVICES AND ETHIC by Gülsüm Ak, Sabire Değer İşler, Kadriye Peker, Özen Doğan Onur, Mustafa Mert Açıkgöz

“…Countries have created various guidelines and algorithms for the implementation of dental services in line with their own health policies. …”
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An Ultrafast Optical Imaging System with Anamorphic Transformation Based on STEAM Structure by Guoqing Wang, Yuan Zhou, Rui Min, Fang Zhao, E Du, Xingquan Li, Cong Qiu, Dongrui Xiao, Chao Wang

“…Furthermore, the AT in our proposal could also be applied to data compression algorithms to mitigate the data issue in ultrafast optical imaging systems.…”
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LRD-RB: The First Large-Scale Dataset With Rotated Bounding Boxes for Automated Lunar Rockfall Detection by Dingruibo Miao, Jianguo Yan, Zhigang Tu, Jean-Pierre Barriot

“…The dataset not only facilitates the development and testing of lunar rockfall detection algorithms but also has the potential to serve as a challenging benchmark for rotated small object detection tasks in remote sensing applications.…”
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Local Diversity-Guided Weakly Supervised Fine-Grained Image Classification Method by Yuebo Meng, Xianglong Luo, Hua Zhan, Bo Wang, Shilong Su, Guanghui Liu

“…Extensive experiments conducted on four fine-grained datasets and explainable visualization demonstrate that the LDGNet can effectively enhance discriminative region localization and detailed feature acquisition for fine-grained objects, achieving competitive performance over other state-of-the-art algorithms.…”
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The Impact of AI-Driven Application Programming Interfaces (APIs) on Educational Information Management by David Pérez-Jorge, Miriam Catalina González-Afonso, Anthea Gara Santos-Álvarez, Zeus Plasencia-Carballo, Carmen de los Ángeles Perdomo-López

“…Reported outcomes include improvements in engagement (63%), comprehension (55.6%), and academic achievement (48.1%). However, the review also identifies concerns about privacy, algorithmic bias, and limited methodological rigor in existing research. …”
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Machine Learning Adoption in Blockchain-Based Smart Applications: The Challenges, and a Way Forward by Sudeep Tanwar, Qasim Bhatia, Pruthvi Patel, Aparna Kumari, Pradeep Kumar Singh, Wei-Chiang Hong

“…The decentralized database in BT emphasizes data security and privacy. Also, the consensus mechanism in it makes sure that data is secured and legitimate. …”
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Insights into landslide susceptibility: a comparative evaluation of multi-criteria analysis and machine learning techniques by Zuleide Ferreira, Bruna Almeida, Ana Cristina Costa, Manoel do Couto Fernandes, Pedro Cabral

“…RF achieved the highest performance, with an accuracy of 0.94, ROC AUC of 0.98, and F1 score of 0.94. SVM and LR also performed well, with ROC AUCs of 0.96 and 0.95 and F1 scores of 0.92 and 0.89, respectively. …”
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Predictive modelling employing machine learning, convolutional neural networks (CNNs), and smartphone RGB images for non-destructive biomass estimation of pearl millet (Pennisetum... by Faten Dhawi, Abdul Ghafoor, Norah Almousa, Sakinah Ali, Sara Alqanbar

“…This study employed a transfer learning approach using pre-trained convolutional neural networks (CNNs) alongside shallow machine learning algorithms (Support Vector Regression, XGBoost, Random Forest Regression) to estimate AGB. …”
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Deep Reinforcement Learning of Mobile Robot Navigation in Dynamic Environment: A Review by Yingjie Zhu, Wan Zuha Wan Hasan, Hafiz Rashidi Harun Ramli, Nor Mohd Haziq Norsahperi, Muhamad Saufi Mohd Kassim, Yiduo Yao

“…Through a comparative analysis of classical DRL algorithms, this study highlights their advantages and limitations in handling real-time navigation tasks under dynamic environmental conditions. …”
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Hover Flight Improvement of a Quadrotor Unmanned Aerial Vehicle Using PID Controllers with an Integral Effect Based on the Riemann–Liouville Fractional-Order Operator: A Determinis... by Gustavo Delgado-Reyes, Jorge Salvador Valdez-Martínez, Pedro Guevara-López, Miguel Angel Hernández-Pérez

“…The hovering flight of a quadrotor Unmanned Aerial Vehicle (UAV) refers to maintaining the aircraft in a fixed position in the air, without lateral, vertical, or rotational movements, using only the vehicle’s control systems to maintain proper balance in all spatial dimensions. Algorithms and control systems have been developed to continuously adjust motor speeds to counteract deviations from the desired position and achieve effective hovering flight. …”
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Strengthening Collaboration via Interlinked Skew Assessment and Rectification (ISAR) in Swarm Robotics by Muhammad Usman Hashmi, Anas Bilal, Muhammad Khurram Ehsan, Monir Abdullah, Abdulbasit A. Darem, Sahraoui Dhelim

“…This synchronization enables distributed data logging, coordination of algorithms, and synchronized event-driven interactions, which would be impossible without a shared time reference. …”
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CAREUP: An Integrated Care Platform with Intrinsic Capacity Monitoring and Prediction Capabilities by Marcin Kolakowski, Andrea Lupica, Seif Ben Bader, Vitomir Djaja-Josko, Jerzy Kolakowski, Jacek Cichocki, Jaouhar Ayadi, Luca Gilardi, Angelo Consoli, Irina Georgiana Mocanu, Oana Cramariuc, Lionello Ferrazzini, Eva Reithner, Magdalena Velciu, Barbara Borgogni, Sofia Rivaira, Sara Leonzi, Giacomo Cucchieri, Vera Stara

“…The users are also presented with a machine learning-based prediction of how their intrinsic capacity might change over the following years. …”
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Water vapor density field estimation using commercial microwave link attenuation combined with temperature measurements by Itay Bragin, Yoav Rubin, Pinhas Alpert, Jonatan Ostrometzky

“…A number of machine-learning based algorithms (e.g. support vector machine) for estimating water vapor density at a reference weather station using the received signal level values measured at a commercial microwave link has been proposed in the past, and also was expanded to include a combination of three commercial microwave links with temperature measurements to achieve a higher estimation accuracy (with respect to the root mean square error at a given location). …”
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Continuous Speech for Improved Learning Pathological Voice Disorders by Syu-Siang Wang, Chi-Te Wang, Chih-Chung Lai, Yu Tsao, Shih-Hau Fang

“…<italic>Conclusions:</italic> The results are consistent with other machine learning algorithms, including gated recurrent units, random forest, deep neural networks, and LSTM.The sensitivities for each disorder were also analyzed, and the model capabilities were visualized via principal component analysis. …”
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Maximizing Energy Output of Photovoltaic Systems: Hybrid PSO-GWO-CS Optimization Approach by Hassan S. Ahmed, Ahmed J. Abid, Adel A. Obed, Ameer L. Saleh, Reheel J. Hassoon

“…Based on these results, a hybrid mode of merging algorithms based on weather radiation conditions is proposed. …”
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