The Potential of Unsupervised Induction of Harmonic Syntax for Jazz by Ruben Cartuyvels, John Koslovsky, Marie-Francine Moens

“…Hierarchical structures describing a syntax of harmony have long been studied and proposed by music theorists, but algorithms that model these structures either require costly expert annotations for training or are based on music theorists' predispositions about harmonic syntax. …”
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Smart Thermostat Development and Validation on an Environmental Chamber Using Surrogate Modelling by Leonidas Zouloumis, Nikolaos Ploskas, Nikolaos Taousanidis, Giorgos Panaras

“…Although dynamic simulation tools and decision-making algorithms are core components of energy management methodologies, they are often accompanied by excessive computational cost. …”
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A Review of Embodied Grasping by Jianghao Sun, Pengjun Mao, Lingju Kong, Jun Wang

“…Then, the embodied algorithms are introduced, starting from pre-trained models, with three main research goals: (1) embodied perception, using data captured by visual sensors to perform point cloud extraction or 3D reconstruction, combined with pre-trained models, to understand the target object and external environment and directly predict the execution of actions; (2) embodied strategy: In imitation learning, the pre-trained model is used to enhance data or as a feature extractor to enhance the generalization ability of the model. …”
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Comprehensive multi-omics analysis of histone acetylation modulators identifies ASH1L as a novel aggressive marker for osteosarcoma by Chenlie Ni, Qiwen Sun, Haibo Yin

“…The effectiveness of HAMRPs in predicting the immune landscape of osteosarcoma was confirmed using CIBERSORT, ssGSEA, and ESTIMATE algorithms. …”
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The role of artificial intelligence in enhancing disaster preparedness and trauma care by Mohamad Sorani

“…Furthermore, ethical considerations such as data privacy, algorithmic bias, and equitable access are crucial to ensuring that AI-driven solutions are implemented responsibly and inclusively.This review also explores future directions for AI, including the development of sophisticated predictive models, autonomous systems for high-risk tasks, immersive training programs utilizing virtual and augmented reality, and global collaboration aimed at standardizing AI tools and practices. …”
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ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture by Ju He, Yang Yu, Hongyu Wei, Hu Xu

“…Therefore, existing tracking algorithms face difficulty in direct application to underwater object tracking. …”
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A comprehensive review of flood damage in mountainous regions: challenges, solutions, and advanced management technologies by Mohammad Roohi, Jila Dehghani, Maryam Irani, Paramiss Mina

“…Modern technologies, early warning systems, predictive models, and international collaboration are key to reducing flood losses and informing sustainable flood management.…”
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Estimate Programmatic Effort using the Traditional COCOMO Model and Neural Networks by Jamal Al-Din Sayed Majeed, Isra Majeed Qabaa

“…Estimation models in software engineering are used to predict some important and future features for software project such as effort estimation for developing software projects. …”
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Climate risk and low-carbon policies: implications for sports economics and global events by Siyu Fu, Chen Kong

“…ICSF, on the other hand, leverages game theory and optimization algorithms to enhance decision-making in areas such as resource allocation, salary cap management, and sustainability-oriented strategic planning.ResultsEmpirical results from multiple datasets and experiments confirm that the integration of climate risk and low-carbon policy variables significantly improves the predictive accuracy and resilience of economic planning in the sports sector.DiscussionThis research provides theoretical advancements and practical insights for policymakers, sports managers, and investors seeking to navigate the complex interplay between sustainability and profitability in a rapidly changing global environment.…”
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Achieving Equity via Transfer Learning With Fairness Optimization by Xiaoyang Wang, Chia-Hsuan Chang, Christopher C. Yang

“…Machine learning algorithms are increasingly used in real-world decision-making systems, raising concerns about potential biases and unfairness. …”
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Fusion of Masked Autoencoder for Adaptive Augmentation Sequential Recommendation by SUN Xiujuan, SUN Fuzhen, LI Pengcheng, WANG Aofei, WANG Shaoqing

“…Experimental results on the Books, Toys, and Retailrocket datasets show that the recommendation accuracy of the proposed model is superior to the most advanced baseline algorithms in terms of hit ratio (HR) and normalized discounted cumulative gain (NDCG) metrics. …”
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AI-driven energy management system based on hesitant bipolar complex fuzzy Hamacher power aggregation operators and their applications in MADM by Walid Emam, Hafiz Muhammad Waqas, Tahir Mahmood, Ubaid ur Rehman, Dragan Pamucar

“…Abstract Artificial Intelligence (AI) based energy management systems utilize sophisticated AI algorithms to improve and control the consumption of energy in various sectors, such as power utilities, industrial systems, and smart buildings. …”
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Connectivity and community structure of online and register-based social networks by Márton Menyhért, Eszter Bokányi, Rense Corten, Eelke M. Heemskerk, Yuliia Kazmina, Frank W. Takes

“…Second, we show using multiple algorithms that the community structure of the two networks is similar and that neither follows strict administrative geographical delineations (e.g., provinces). …”
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Privacy, ethics, transparency, and accountability in AI systems for wearable devices by Petar Radanliev, Petar Radanliev

“…The integration of artificial intelligence (AI) and machine learning (ML) into wearable sensor technologies has substantially advanced health data science, enabling continuous monitoring, personalised interventions, and predictive analytics. However, the fast advancement of these technologies has raised critical ethical and regulatory concerns, particularly around data privacy, algorithmic bias, informed consent, and the opacity of automated decision-making. …”
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IDENTIFYING IMPORTANT GENES IN OVARIAN CANCER FROM HIGH-DIMENSIONAL MICROARRAY DATA USING SIFS-CART METHOD by Ni Kadek Emik Sapitri, Umu Sa'adah, Nur Shofianah

“…Many studies only focus on improving the machine learning classification algorithms to achieve higher performance. The purpose of classification is not only to obtain high performance but also to seek new knowledge from the results. …”
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Unlocking biological complexity: the role of machine learning in integrative multi-omics by Ravindra Kumar, Rajrani Ruhel, Andre J. van Wijnen

“…It offers sophisticated algorithms that can identify and discover hidden patterns and provide insights into complex biological networks. …”
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A New High-Performance Photovoltaic Emulator Suitable for Simulating and Validating Maximum Power Point Tracking Controllers by Ambe Harrison, Njimboh Henry Alombah

“…Currently, researchers face several challenges in testing MPPT algorithms due to the unpredictable nature of solar PV power generation. …”
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An Interpretable Machine Learning-Based Hurdle Model for Zero-Inflated Road Crash Frequency Data Analysis: Real-World Assessment and Validation by Moataz Bellah Ben Khedher, Dukgeun Yun

“…The first stage uses binary classification to identify road segments with potential crash occurrences, applying a customized loss function to tackle data imbalance. The second stage predicts crash frequency, also utilizing a customized loss function for count data. …”
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COMPARATIVE EVALUATION OF INDICATORS OF STRUCTURAL AND MECHANICAL PROPERTIES OF WHEAT GRAIN by P. V. Medvedev, V. A. Fedotov, E. S. Lukyanova

“…The vitreous nature of wheat allows us to predict the bakery and pasta advantages of flour from this grain. …”
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A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving Precision Agriculture with IoT-Driven Sensor Networks and Data Analytics by Shnain Ammar H., Mohammed G., Kumar Yalla Jeevan Nagendra

“…To solve these challenges, CM-IoT-SN combines a network of IoT-enabled sensors continuously monitoring key environmental factors such as soil moisture, temperature, and nutrient levels. Advanced algorithms then utilize the realtime data acquired to provide farmers expected insights and quick advise.CM-IoT-SNs adoption across many test locations has proved its effectiveness in producing superior decision-making in crop management by means of exact, real-time monitoring and predictive analytics. …”
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