Reliable Graph Routing in Industrial Wireless Sensor Networks by Jing Zhao, Yajuan Qin, Dong Yang, Junqi Duan

“…Our design is evaluated using simulation where we show that our algorithm could achieve a balance between routing reliability and overhead.…”
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Construction of a sugar and acid content estimation model for Miliang-1 kiwifruit during storage by LIU Li, YANG Tianyi, DONG Congying, SHI Caiyun, SI Peng, WEI Zhifeng, GAO Dengtao

“…To select the optimal hyperspectral wavelengths for predicting kiwifruit quality, Genetic Algorithm (GA) and Random Frog (RF) methods were employed. …”
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Machine Learning Approaches to Code Similarity Measurement: A Systematic Review by Zixian Zhang, Takfarinas Saber

“…Following a rigorous systematic review protocol, we identified and analyzed 84 primary studies on a broad spectrum of dimensions covering application type, devised Machine Learning algorithms, used code representations, datasets, and performance metrics, as well as performance evaluations. …”
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QoS-Aware Fault Detection in Wireless Sensor Networks by Alessandra De Paola, Giuseppe Lo Re, Fabrizio Milazzo, Marco Ortolani

“…The experimental evaluation produced good results, showing that our algorithm is able to greatly reduce the response time at the cost of a small reduction in classification accuracy.…”
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Data augmentation of time-series data in human movement biomechanics: A scoping review. by Christina Halmich, Lucas Höschler, Christoph Schranz, Christian Borgelt

“…This understanding is crucial for assessing the impact of the augmented data set on downstream models and evaluating the quality of the data augmentation process.…”
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An Efficient Biobjective Heuristic for Scheduling Workflows on Heterogeneous DVS-Enabled Processors by Pengji Zhou, Wei Zheng

“…Energy consumption has recently become a major concern to multiprocessor computing systems, of which the primary performance goal has traditionally been reducing execution time of applications. In the context of scheduling, there have been increasing research interests on algorithms using dynamic voltage scaling (DVS), which allows processors to operate at lower voltage supply levels at the expense of sacrificing processing speed, to acquire a satisfactory trade-off between quality of schedule and energy consumption. …”
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Improvement of Methodological Tools for Business Analysis of the Effective Company’s Performance by N. S . Plaskova

“…The practical application of the proposed adjusted procedures for calculating indicators contributes to getting a reliable and aimed assessment of the quality of the management system of organizations in the real sector of the economy. …”
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Investigation with Bluetooth Sensors of Bicycle Travel Time Estimation on a Short Corridor by Zhenyu Mei, Dianhai Wang, Jun Chen

“…Test data are used to measure the quality of bicycle travel time data collected by the Bluetooth sensors, and the results show that the new technology is a promising method for collecting high-quality travel time data that can be used as ground truth for evaluating other sources of travel time and other intelligent transportation system applications.…”
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Fishing for biomarkers: analyzing mass spectrometry data with the new ClinProTools™ software by Ralf Ketterlinus, Sen-Yung Hsieh, Shih-Hua Teng, Helen Lee, Wolfgang Pusch

“…For this purpose, efficient visualization of large data sets derived from patient cohorts is crucial to provide clinical experts an interactive impression of the data quality. Additionally, it is necessary to apply statistical analysis and pattern matching algorithms to attain validated signal patterns that may allow for later applications in sample classification. …”
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A Summary of Recent Advances in the Literature on Machine Learning Techniques for Remote Sensing of Groundwater Dependent Ecosystems (GDEs) from Space by Chantel Nthabiseng Chiloane, Timothy Dube, Mbulisi Sibanda, Tatenda Dalu, Cletah Shoko

“…It begins with a systematic literature review following the PRISMA framework, followed by an analysis of temporal and geographic trends in ML applications for GDE research. Additionally, it explores different advanced ML algorithms and their applications across various GDE types. …”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…This study synthesizes findings from 39 high-quality articles published between 2016 and 2024, evaluating various machine learning (ML), deep learning (DL), regression, and hybrid models in sectors such as construction, healthcare, manufacturing, and real estate. …”
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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…Extensive simulations are conducted to evaluate the performance of the proposed method against state-of-the-art algorithms in terms of coverage quality and node count. …”
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Using the power of artificial intelligence to improve the diagnosis and management of nonmelanoma skin cancer by Fahimeh Abdollahimajd, Fatemeh Abbasi, Alireza Motamedi, Narges Koohi, Reza Mohamoud Robati, Mona Gorji

“…Building patient trust is also essential for the successful implementation of AI in the clinical settings. AI algorithms may outperform experts in controlled environments but can fall short in the real-world clinical applications, indicating a need for more prospective studies to evaluate their effectiveness in the practical scenarios. …”
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Semantic Segmentation-Driven Knowledge Distillation-Based Infrared Visible Image Fusion Framework by Xingshuo Wang

“…However, many existing fusion algorithms overly emphasize visual quality and traditional statistical evaluation metrics while neglecting the requirements of real-world applications, especially in high-level vision tasks. …”
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Dataset of apples for grading by sweetness, ripeness and varietyMendeley Data by Shilpa Gaikwad, Sonali Kothari, Ignisha Rajathi G

“…The resulting annotated database includes such quantitative reference points, which can be used to train supervised learning classifiers in computational classification systems.The reuse value of the dataset covers a wide range of applications such as machine learning-based fruit quality evaluation, agricultural automation and food industry examination. …”
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Machine Learning in Ambient Assisted Living for Enhanced Elderly Healthcare: A Systematic Literature Review by Aabid A. Mir, Ahmad S. Khalid, Shahrulniza Musa, Mohammad Faizal Ahmad Fauzi, Normy Norfiza Abdul Razak, Tong Boon Tang

“…This systematic literature review (SLR) explores the current state and advancements in AAL technologies, with a specific focus on their applications in elderly care. It synthesizes current methodologies, including predictive analytics, Explainable AI (XAI), and Generative AI (GenAI), while also evaluating the role of vision-based systems and multi-modal data fusion. …”
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SCHEDULING PROBLEMS OF STATIONARY OBJECTS WITH THE PROCESSOR IN ONE-DIMENSIONAL ZONE by N. A. Dunichkina, D. I. Kogan, Yu. S. Fedosenko

“…Correspondingly, the bicriteria problem with the mentioned evaluation criteria is fundamentally intractable, computational complexity of the schedule structure algorithm is exponential. …”
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Hybrid POF-VLC Systems: Recent Advances, Challenges, Opportunities, and Future Directions by Rola Abdallah, Mohamed Atef, Nasir Saeed

“…Furthermore, the application of machine learning, particularly neural network-based equalizers like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), is highlighted for their potential to enhance signal quality and system performance. …”
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An Efficient and Low-Complexity Transformer-Based Deep Learning Framework for High-Dynamic-Range Image Reconstruction by Josue Lopez-Cabrejos, Thuanne Paixão, Ana Beatriz Alvarez, Diodomiro Baldomero Luque

“…The proposed architecture was evaluated on two datasets, achieving the best results on Tel’s dataset in terms of quality metrics. …”
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Develop Approach to Predicate Software Reliability Growth Model Parameters Based on Machine learning by anfal A. Fadhil, Asmaa’ H. AL_Bayati, Ibrahim Ahmed Saleh

“…This goal is accomplished by calculating the parameters of software reliability growth models (SRGMs). The parameters are evaluated using three algorithms: machine learning decision tree (DT), support vector machine (SVM), and K-nearest neighbors (K-NN). …”
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