Evaluation of Knowledge Management Maturity Level in Iranian Audiovisual Archives Based on the APQC Model by Sepideh Ciruskabiri, Atefeh Sharif, Saeed Rezaei Sharifabadi, Mohammad Hassanzadeh

“…In implementing KM, understanding the organization’s current status from the perspective of KM maturity is of paramount importance, since KM maturity models describe the expected steps for organizational improvement in terms of knowledge management.Methodology: In this study, five knowledge management maturity models were analyzed, including the Capability Maturity Model (CMM); the Capability Maturity Model Integration (CMMI); the General Knowledge Management Maturity Model (G-KMMM); the Asian Productivity Organization (APO) model; and finally, the APQC Knowledge Management Maturity Model. …”
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A Systematic Integration of Artificial Intelligence Models in Appendicitis Management: A Comprehensive Review by Ivan Maleš, Marko Kumrić, Andrea Huić Maleš, Ivan Cvitković, Roko Šantić, Zenon Pogorelić, Joško Božić

“…Artificial intelligence (AI) and machine learning (ML) are transforming the management of acute appendicitis by enhancing diagnostic accuracy, optimizing treatment strategies, and improving patient outcomes. …”
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Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline by HongYi Li, Jun-Fen Fu, Andre Python

“…General-purpose LLMs may not perform well in specialized areas as they often require lightweight prompt engineering methods or fine-tuning techniques based on specific datasets to improve model performance. Most LLMs with multimodal abilities are closed-source models and, therefore, lack of transparency, model customization, and fine-tuning for specific clinical tasks and may also pose challenges regarding data protection and privacy, which are common requirements in clinical settings. …”
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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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Coordinated multi-level scheduling method considering uncertainty of renewable energy and load by Bingbing Song, Kangping Qin, Min Wen, Moyan Zhu, Kaiming Zou, Guangyu He

“…At the provincial level, a two-stage robust optimization dispatch model is constructed based on regional grid dispatch, and it is solved using the Karush-Kuhn-Tucker conditions and the Column-and-Constraint Generation (C&CG) algorithm. …”
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A Detection Line Counting Method Based on Multi-Target Detection and Tracking for Precision Rearing and High-Quality Breeding of Young Silkworm (<i>Bombyx mori</i>) by Zhenghao Li, Hao Chang, Mingrui Shang, Zhanhua Song, Fuyang Tian, Fade Li, Guizheng Zhang, Tingju Sun, Yinfa Yan, Mochen Liu

“…This method combines an improved detector, incorporating an optimized multi-scale feature fusion module and the Efficient Multi-Scale Attention Fusion Cross Stage Partial (EMA-CSP) mechanism, with an optimized tracker (based on ByteTrack with improved detection box matching), alongside the implementation of a ‘detection line’ approach. …”
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Power supply vehicle routing problem: formulation and solution by Lizhe You, Shengjun Huang, Haowei Zhang, Rui Wang, Tao Zhang

“…Building on this definition, this problem is formulated as a two-stage mixed-integer nonlinear programming model. To solve this model, we adopted a genetic algorithm as the main algorithm framework. …”
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A Tri-Level Transaction Method for Microgrid Clusters Considering Uncertainties and Dynamic Hydrogen Prices by Hui Xiang, Xiao Liao, Yanjie Wang, Hui Cao, Xianjing Zhong, Qingshu Guan, Weiyun Ru

“…A polygonal uncertainty set method quantifies wind and solar energy uncertainties, while an enhanced interval optimization technique refines the model. We integrate a sophisticated demand response model for hydrogen loading, capturing users’ behavior in response to price changes, thereby improving renewable energy utilization and supporting economically viable management practices. …”
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Vehicle routing problem in waste collection: a case study in Son Tra, Da Nang by Le Hoang Son, Truong Nguyen Song Ha, Nguyen Ngoc Phuong, Phan Bao An

“…By employing the Dijkstra algorithm, route optimization resulted in a significant reduction in average route length, from 12.94 ± 3.5 km to 9.42 ± 2.67 km, representing a 9-42% improvement. …”
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Methodology of statistical synthesis and analysis methods for stochastic signal processing in multi-antenna radio direction finders by Eduard Tserne, Yevhen Holovynskyi, Olha Zhyla

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Enhanced early detection of dysarthric speech disabilities using stacking ensemble deep learning model by Jagat Chaitanya Prabhala, Ravi Ragoju, Venkatanareshbabu Kuppili, Christophe Chesneau

“…Unlike conventional stacking methods that use fixed meta-classifiers, this study employs a Genetic Algorithm (GA)-based optimization strategy to dynamically determine optimal weight contributions of the base models, enhancing classification robustness and adaptability.The preprocessing pipeline converts speech signals from the time domain to the frequency domain by using a Short-Time Fourier Transform (STFT). …”
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Research Progress and Prospect of Multi-robot Collaborative SLAM in Complex Agricultural Scenarios by MA Nan, CAO Shanshan, BAI Tao, KONG Fantao, SUN Wei

“…Thirdly, large language models will enhance human-robot interaction by enabling natural language commands, improving collaborative operations. …”
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Enhancing Fault Detection in AUV-Integrated Navigation Systems: Analytical Models and Deep Learning Methods by Huibao Yang, Bangshuai Li, Xiujing Gao, Bo Xiao, Hongwu Huang

“…Specifically, the particle swarm optimization (PSO) algorithm was employed to optimize the hyperparameters of a long short-term memory (LSTM) neural network, leading to the development of a PSO-LSTM fault detection model. …”
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Microgrid Energy Management Considering Energy Storage Degradation Cost by Yiming Zhao, Hongrui Li, Changsheng Wan, Dong Du, Bo Chen

“…The improved sine cosine algorithm (SCA) is used to simulate the energy output optimization of various distributed generators in the microgrid. …”
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Machine learning-based prediction method for open-pit mining truck speed distribution in manned operation by Changyou XU, Gang CHEN, Qiuxia ZHANG, Bo WANG, Hongwang ZHANG, Hongrui LI, Weiwei QIN, Muyang LI

“…Among these models, the Random Forest-based model exhibited lower mean squared error and a higher coefficient of determination, outperforming the XGBoost-based model. …”
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Enhanced Conformer-Based Speech Recognition via Model Fusion and Adaptive Decoding with Dynamic Rescoring by Junhao Geng, Dongyao Jia, Zihao He, Nengkai Wu, Ziqi Li

“…In this paper, we propose improvements to the model structure fusion and decoding algorithms. …”
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A systematic review on the integration of explainable artificial intelligence in intrusion detection systems to enhancing transparency and interpretability in cybersecurity by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…Explainable Artificial Intelligence (XAI) offers a promising solution by providing interpretability and transparency, enabling security professionals to understand better, trust, and optimize IDS models. This paper presents a systematic review of the integration of XAI in IDS, focusing on enhancing transparency and interpretability in cybersecurity. …”
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Non-destructive identification of commercial jerky types based on multi-band hyperspectral imaging with machine learning by Yuanxi Han, Liang Li, Siyuan Jiang, Pengpeng Sun, Wenliang Wu, Zhendong Liu

“…After data preprocessing, all models' accuracies and stability improved. Specifically, the logistic regression model was best for jerky identification, with 85.78 %–100.00 % accuracy. …”
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Hybrid A*-Guided Model Predictive Path Integral Control for Robust Navigation in Rough Terrains by Joonyeol Yang , Minhyeong Kang , Seulchan Lee, Sanghyun Kim

“…This article proposes the Hybrid A*-guided Model Predictive Path Integral (MPPI) algorithm augmented with traversability estimation to address the challenges of path planning on uneven terrains. …”
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