Cross-Layer Optimization Scheme Using Cooperative Diversity for Reliable Data Transfer in Wireless Sensor Networks by Yongrui Chen, Fei Qin, Yulong Xing, Dujdow Buranapanichkit

“…By utilizing a cross-layer optimization scheme, distributive algorithms which jointly consider routing, relay selection, and power allocation strategies are proposed for the reliability constraint wireless sensor networks. …”
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MEL-IRIS: An Online Tool for Audio Analysis and Music Indexing by Dimitrios Margounakis, Dionysios Politis, Konstantinos Mokos

“…The tool implements specially designed algorithms and a unique way of visualization of the results. …”
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Optimizing Convolution Operations for YOLOv4-based Object Detection on GPU by Guerrouj Fatima Zahra, Rodríguez Flórez Sergio, El Ouardi Abdelhafid, Abouzahir Mohamed, Ramzi Mustapha

“…Real-time object detection is crucial for autonomous vehicles, and YOLO (You Only Look Once) algorithms have demonstrated their effectiveness for this purpose. …”
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Deep neural networks have an inbuilt Occam’s razor by Chris Mingard, Henry Rees, Guillermo Valle-Pérez, Ard A. Louis

“…Abstract The remarkable performance of overparameterized deep neural networks (DNNs) must arise from an interplay between network architecture, training algorithms, and structure in the data. To disentangle these three components for supervised learning, we apply a Bayesian picture based on the functions expressed by a DNN. …”
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Mapping Pituitary Neuroendocrine Tumors: An Annotated MRI Dataset Profiling Tumor and Carotid Characteristics by A. S. Pandit, A. Keenlyside, D. Z. Khan, G. Reischer, M. A. Kamal, N. Yoh, Z. Jaunmuktane, A. Borg, N. L. Dorward, S. E. Baldeweg, I. Davagnanam, H. Hyare, P. Nachev, H. J. Marcus

“…Expert annotations of both the tumor and adjacent carotid arteries ensure precise delineation, facilitating the development of automated segmentation algorithms. Our initiative addresses the need for standardized data in pituitary oncology, fosters collaboration and innovation, and enables the development and benchmarking of workflows that utilize pituitary radiomics for treatment planning and outcome prediction.…”
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Research on How Human Intelligence, Consciousness, and Cognitive Computing Affect the Development of Artificial Intelligence by Yanyan Dong, Jie Hou, Ning Zhang, Maocong Zhang

“…In the future, the research and development of cutting-edge technologies such as brain-computer interface (BCI) together with the development of the human brain will eventually usher in a strong AI era, when AI can simulate and replace human’s imagination, emotion, intuition, potential, tacit knowledge, and other kinds of personalized intelligence. Breakthroughs in algorithms represented by cognitive computing promote the continuous penetration of AI into fields such as education, commerce, and medical treatment to build up AI service space. …”
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Measuring. Monitoring. Management. Control by M.V. Sprindzuk, V.I. Bernik, A.P. Konchits

“…The emergence and importance of the research topic is substantiated by the colossal growth in the volume of accumulated and underprocessed medical information, the evolution of mathematical and algorithmic apparatus, and the need to improve existing data processing pipelines. …”

Methodology for the Automatic Generation of Optimization Models of Systems of Flexible Energy Resources by Lukas Peter Wagner, Felix Gehlhoff, Lasse Matthias Reinpold, Georg Frey, Julian Jepsen, Alexander Fay

“…This methodology utilizes a modular, generic model structure designed to depict systems of flexible energy resources. It incorporates algorithms for model parameter derivation from operational data and an information model that represents the system’s structure and dependencies of resources. …”
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A critical assessment of ionic liquid-based aqueous biphasic systems for biomolecules extraction and CO2 absorption by Viggy Wee Gee Tan, Yazan Abuhasheesh, Doris Ying Ying Tang, Yongyu Zhang, Zengling Ma, Lin Chen, Rambabu Krishnamoorthy, Pau Loke Show

“…The incorporation of machine learning (ML) algorithms to predict the toxicity and CO2 capture properties, as well as the scaling up of IL-ABSs, is also explored.…”
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A Decomposition-Based Approach for the Multiperiod Multiproduct Distribution Planning Problem by S. Ahmad Hosseini, Güvenç Şahin, Tonguç Ünlüyurt

“…Knowing that computational expenses of solving such a large-scale planning problem can be decreased by using decomposition techniques, the special structure of polyhedrals is utilized to develop algorithmic approaches based on decomposition techniques to handle the global problem aiming to save computational resources.…”
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Developing an IoT and ML-driven platform for fruit ripeness evaluation and spoilage detection: A case study on bananas by Rajini M, Persis Voola

“…This framework employed various machine learning algorithms to detect ripeness stages, with the CatBoost classifier exhibiting exceptional performance, demonstrating its dependability and effectiveness in assessing fruit quality. …”
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Rule Acquisition in Formal Decision Contexts Based on Formal, Object-Oriented and Property-Oriented Concept Lattices by Yue Ren, Jinhai Li, Cherukuri Aswani Kumar, Wenqi Liu

“…Finally, some real examples and numerical experiments are conducted to compare the proposed rule acquisition algorithms with the existing one in terms of the running efficiency.…”
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A Survey of Machine Learning Innovations in Ambulance Services: Allocation, Routing, and Demand Estimation by Reem Tluli, Ahmed Badawy, Saeed Salem, Mahmoud Barhamgi, Amr Mohamed

“…In the realm of Emergency Medical Services (EMS), the integration of Machine Learning (ML) techniques has emerged as a catalyst for revolutionizing ambulance operations. ML algorithms could play a pivotal role in dynamically allocating resources, devising efficient routes, and predicting demand patterns. …”
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P-LEACH: An Efficient Cluster-Based Technique to Track Mobile Sinks in Wireless Sensor Networks by Sungchol Cho, Li Han, Bokgyu Joo, Sunyoung Han

“…For a wireless sensor network (WSN) with a large number of inexpensive sensor nodes, energy efficiency is the major concern in designing network structure and related algorithms. If network collects sensor data using mobile sinks, object tracking mechanism must consider the energy efficiency of sensor nodes in the networks as a whole. …”
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Applied of Classification Technique in Data Mining For Credit Scoring by Heriyanto Heriyanto, Ika Kurniawati, Fachri Amsury, Muhammad Rizki Fahdia, Irwansyah Saputra, Nanang Ruhyana, Asrul

“…In this study, a comparison of the Naive Bayes, C4.5 and KNN algorithms was carried out which was applied to consumer data that received credit eligibility for good and bad customers. …”
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Vibration dataset of main journal bearings in internal combustion engines under diverse climatic and varying operating conditionsMendeley Data by Muhammad Noman Riaz, Amir Hamza, Hamid Jabbar, Manzar Abbas, Mohsin Islam Tiwana

“…This dataset provides a valuable and reliable benchmark for researchers and practitioners to validate their diagnostic algorithms and models against real engine conditions, as no such dataset is publicly available.…”
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On the Problem of Energy Balanced Relay Sensor Placement in Wireless Sensor Networks by Jie Jia, Guiyuan Zhang, Xueli Wu, Jian Chen, Xingwei Wang, Xiaolei Yan

“…Balanced energy depletion is an important way to prolong network lifetime for wireless sensor networks. Traditional algorithms mainly aim at maximizing network coverage rate with uniform sensor node distribution. …”
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Intelligent Injection Molding on Sensing, Optimization, and Control by Peng Zhao, Jianfeng Zhang, Zhengyang Dong, Junye Huang, Hongwei Zhou, Jianzhong Fu, Lih-Sheng Turng

“…Finally, conclusions are drawn to discuss future research directions and technologies, as well as algorithms worthy of being explored and developed.…”
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A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural Networks by Shubin Zheng, Qianwen Zhong, Xiaodong Chai, Xingjie Chen, Lele Peng

“…Taking the selected parameters and previous car body vibration acceleration as the inputs, a prediction model for car body vibration acceleration was established based on several training algorithms and neural network structures. Then, the model was successfully applied to predict the car body vibration acceleration of test datasets on different segments of the same railway. …”
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Scilab-RL: A software framework for efficient reinforcement learning and cognitive modeling research by Jan Benad, Frank Röder, Manfred Eppe

“…Many open source implementations of current RL algorithms exist, but there is a lack of a modular suite of tools combining different robotic simulators and platforms, data visualization, hyperparameter optimization, and baseline experiments. …”
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