Thermal-aware resource allocation in earliest deadline first using fluid scheduling by Muhammad Naeem Shehzad, Qaisar Bashir, Ghufran Ahmad, Adeel Anjum, Muhammad Naeem Awais, Umar Manzoor, Zeeshan Azmat Shaikh, Muhammad A Balubaid, Tanzila Saba

“…This article proposes an improvement in earliest deadline first, a uni-processor scheduling algorithm, without compromising its optimality in order to reduce the thermal peaks and variations. …”
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Time series segmentation for recognition of epileptiform patterns recorded via microelectrode arrays in vitro. by Gabriel Galeote-Checa, Gabriella Panuccio, Angel Canal-Alonso, Bernabe Linares-Barranco, Teresa Serrano-Gotarredona

“…While initially trained specifically for detecting ictal activity, these algorithms can be fine-tuned for improved interictal detection, aiming at seizure prediction. …”
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Hybrid multi-objective node deployment for energy-coverage problem in mobile underwater wireless sensor networks by Salmah Fattah, Ismail Ahmedy, Mohd Yamani Idna Idris, Abdullah Gani

“…The system faces internal and external environment problems that must be addressed for maximum coverage in the deployment region while minimizing energy consumption. In addition, the existing traditional approaches have limitations of improving simultaneously the objective function of network coverage and the dissipated energy in mobility, sensing and redundant coverage. …”
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The use of artificial intelligence in the HR processes of logistics companies by Adam Panek

“…Personalization of AI-based training improves employee engagement and productivity, while optimization of work schedules and accurate forecasting of staffing needs allow for better human resource management. …”
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Facial emotion based smartphone addiction detection and prevention using deep learning and video based learning by C. Joseph, P. Uma Maheswari

“…Additionally, face emotion detection algorithms tuned with MnasNet-Teaching Learning Based Optimization (TLBO) and Convolution Neural Networks (CNN)-Cuckoo Search Optimization (CSO) are employed for accurate emotion recognition. …”
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YOLO-SMUG: An Efficient and Lightweight Infrared Object Detection Model for Unmanned Aerial Vehicles by Xinzhe Luo, Xiaogang Zhu

“…To tackle the high computational demands and accuracy limitations in UAV-based infrared object detection, this study proposes YOLO-SMUG, a lightweight detection algorithm optimized for small object identification. …”
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Identification of green leafhoppers (cicadellidae) in vineyards through an automatic image acquisition system from yellow sticky traps associated with deep-learning by Proença Maria da Conceição, Rebelo Maria Teresa, Valent Riccardo, Mateus Rebeca, Gaspar Pedro Diniz, Lopes Carlos Manuel, Franco José Carlos

“…The results demonstrated the algorithm’s capability to accurately identify green leafhopper species, improving the speed of identification compared to conventional methods while maintaining a high level of precision (80%), and a harmonic mean of the precision and recall (F1) of 0.85. …”
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SpecPCM: A Low-Power PCM-Based In-Memory Computing Accelerator for Full-Stack Mass Spectrometry Analysis by Keming Fan, Ashkan Moradifirouzabadi, Xiangjin Wu, Zheyu Li, Flavio Ponzina, Anton Persson, Eric Pop, Tajana Rosing, Mingu Kang

“…We also perform a comprehensive design exploration to improve energy and delay efficiency while maintaining accuracy, exploring various combinations of hardware and software parameters controlled by the instruction set architecture (ISA). …”
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Evaluation of Shelf Life Prediction for Broccoli Based on Multispectral Imaging and Multi-Feature Data Fusion by Xiaoshuo Cui, Xiaoxue Sun, Shuxin Xuan, Jinyu Liu, Dongfang Zhang, Jun Zhang, Xiaofei Fan, Xuesong Suo

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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…The particle swarm optimization (PSO) algorithm is refined with enhanced termination criteria and integrated with the 3D Bishop method to search for the minimum factor of safety (F). …”
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Bidirectional Relationship Between Hypoalbuminemia and Postoperative Pneumonia in Elderly Hip Fracture Patients: A Retrospective Cohort Study by Wang J, Yu H, Xu X, Guo J

“…After predefined participants selection inclusion and exclusion criteria, 1661 surgically treated HF patients were included and analyzed utilizing multiple statistical models, including univariate logistic regression, Lasso regression, and Boruta algorithm for variable selection, while multivariate logistic regression and propensity score matching (PSM) for assess the bidirectional relationship between hypoalbuminemia and postoperative pneumonia. …”
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Efficient automated detection of power quality disturbances using nonsubsampled contourlet transform & PCA-SVM by Pampa Sinha, Kaushik Paul, Asit Mohanty, IM Elzein, Chandra Sekhar Mishra, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Ahmed Althobaiti, Hany S Hussein, Thamer AH Alghamdi, Ahmed M Ewais

“…Morphological component analysis (MCA) and the split-augmented Lagrangian shrinkage algorithm (SALSA) optimize this process. Principal component analysis (PCA) is applied to the extracted features to reduce dimensionality and improve feature separability. …”
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A DSP–FPGA Heterogeneous Accelerator for On-Board Pose Estimation of Non-Cooperative Targets by Qiuyu Song, Kai Liu, Shangrong Li, Mengyuan Wang, Junyi Wang

“…Instruction-level control supports model generalization, while a weight concatenation strategy improves resource utilization during convolution. …”
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MED-AGNeT: An attention-guided network of customized augmentation of samples based on conditional diffusion for textile defect detection by Jun Liu, Haolin Li, Hao Liu, Jiuzhen Liang

“…Its feature extraction module employs a dual-branch information residual unit (DIRU) as a substitute for the conventional convolution block, which combines the feature extraction capabilities of global pooling and max pooling, reducing the number of parameters while also achieving a certain improvement in detection results. …”
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Impact of occupancy behavior on building energy efficiency: What’s next in detection and monitoring technologies? by Wenjie Song, John Calautit

“…Personalization and adaptability emerge as key themes, particularly in multi-occupant contexts, while multi-sensor data fusion promises to enhance detection stability and reduce false positives. …”
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Design and Analysis of a Serial Manipulator for Pick and Drop Objects for Material Handling at Uiri Metal Forming Workshop. by Behangana, Abert

“…This analysis enhanced the understanding of motion control and trajectory optimization. Future recommendations include refining control algorithms, integrating advanced safety features, and exploring innovative materials to improve performance. …”
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Finding a suitable chest x-ray image size for the process of Machine learning to build a model for predicting Pneumonia by Kriengsak Yothapakdee, Yosawaj Pugtao, Sarawoot Charoenkhun, Tanunchai Boonnuk, Kreangsak Tamee

“…Our results indicate a balance between efficiency, as larger images slightly improved accuracy but slowed down speed, while smaller images negatively impacted precision and effectiveness. …”
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The Role of Artificial Intelligence (AI) in the Future of Forestry Sector Logistics by Leonel J. R. Nunes

“…Results: The results demonstrated that optimization algorithms reduced transportation costs and carbon emissions. …”
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A Composite Network for CS ISAR Integrating Deep Adaptive Sampling and Imaging by Lianzi Wang, Ling Wang, Miguel Heredia Conde, DaiYin Zhu

“…However, the existing CS ISAR imaging methods based on deep learning (DL) mainly focus on improving the performance of the reconstruction algorithm while ignoring the potential room for improvement given by the design of the measurement matrix. …”
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Unsupervised Learning for Distributed Downlink Power Allocation in Cell-Free mMIMO Networks by Mattia Fabiani, Asmaa Abdallah, Abdulkadir Celik, Omer Haliloglu, Ahmed M. Eltawil

“…The proposed unsupervised learning approach circumvents the arduous task of training data computations, typically required in supervised learning methods, bypassing the use of conventional complex optimization methods and heuristic methodologies. Furthermore, an LSF-based radio unit (RU) selection algorithm is employed to activate only the contributing RUs, allowing efficient utilization of network resources. …”
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