Enhancing radiomics robustness using bayesian penalized likelihood PET reconstruction: application to Phantom and non-small cell lung cancer patient studies by Zahra Valibeiglou, Jalil Pirayesh Islamian, Yunus Soleymani, Saeed Farzanehfar, Farahnaz Aghahosseini, Neda Gilani, Arman Rahmim, Peyman Sheikhzadeh

“…Abstract Purpose This study aims to enhance the diagnostic and prognostic capabilities of PET imaging through improved robustness of radiomics features, utilizing the Bayesian penalized likelihood (BPL) reconstruction algorithm. …”
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Learning by precedents based on the analysis of the features properties by V. V. Krasnoproshin, V. G. Rodchanka

“…A method of learning based on the analysis of the properties of feature combinations and building feature subspaces where classes do not intersect is proposed. …”
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Deep learning-based crop health enhancement through early disease prediction by Venkata Santhosh Yakkala, Krishna Vamsi Nusimala, Badisa Gayathri, Sriya Kanamarlapudi, S. S. Aravinth, Ayodeji Olalekan Salau, S. Srithar

“…Leveraging the power of machine learning algorithms, particularly Convolutional Neural Networks (CNNs) and ResNet-9 architecture, this research seeks to transform the process of detecting plant diseases. …”
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Early Parkinson’s disease identification via hybrid feature selection from multi-feature subsets and optimized CatBoost with SMOTE by Subhashree Mohapatra, Bhanja Kishor Swain, Manohar Mishra

“…Given the critical role of precise PD classification in medical diagnostics, this study proposes a novel framework to enhance detection accuracy. The proposed framework leverages a strong categorical boosting (CatBoost) algorithm optimized using Grid Search Optimization (GSO). …”
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WSNetDefender: Securing Wireless Sensor Networks Using BBIDNet and Fuzzy-DQN Threat Mitigation System (FD-TMS) by Mohammed A. Aleisa

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Detecting Anomalies in Hydraulically Adjusted Servomotors Based on a Multi-Scale One-Dimensional Residual Neural Network and GA-SVDD by Xukang Yang, Anqi Jiang, Wanlu Jiang, Yonghui Zhao, Enyu Tang, Zhiqian Qi

“…Finally, an abnormal detection model for the hydraulically adjusted servomotor was constructed by optimizing the support vector data domain based on this feature set using a genetic algorithm. …”
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Perbandingan Kinerja Naïve Bayes dan Random Forest dalam Mendeteksi Berita Palsu by William William, Teny Handhayani

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Improved Deviation Sparse Fuzzy C-Means-2D Cumulative Sum Average Filter and Modified Sine Cosine Crow Search Algorithm-Wavelet Extreme Learning Machine for Brain Tumor Detection a... by Suvashisa Dash, Satyasis Mishra, Mohammed Siddique, Demissie J. Gelmecha, Ram Sewak Singh

“…The hybrid modified sine cosine algorithm-crow search algorithm (MSCA-CSA)–based WELM model is proposed to classify the brain tumor. …”
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An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets by Ahmad Salehiyan, Pardis Sadatian Moghaddam, Masoud Kaveh

“…In this study, we propose an optimized hybrid DL framework that combines a transformer, generative adversarial network (GAN), and autoencoder (AE) components, referred to as Transformer–GAN–AE, for robust intrusion detection in Edge and IIoT environments. To enhance the training and convergence of the GAN component, we integrate an improved chimp optimization algorithm (IChOA) for hyperparameter tuning and feature refinement. …”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…This paper addresses this gap by proposing a novel IDS that utilizes hybrid feature selection and deep learning classifiers to detect FDIAs in smart grids. …”
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Visual information perception system of coal mine comprehensive excavation working face for edge computing terminal by Dongyang Zhao, Guoyong Su, Pengyu Wang

“…Firstly, the C3‐Fast feature extraction module, spatial pyramid pooling with cross‐stage partial connection (SPPCSPC) pooling module, bi‐directional feature pyramid network and lightweight decoupled detection head are used to optimize the YOLOv5s model, so as to construct the FSBD‐YOLOv5s multi‐object detection model. …”
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Multifactor Algorithm for Test Case Selection and Ordering by Atulya Gupta, Rajendra Prasad Mahapatra

“…The current research is motivated by this concept and proposes a multifactor algorithm incorporated with genetic operators and powerful features. …”
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Enhanced YOLOv8 with lightweight and efficient detection head for for detecting rice leaf diseases by Bo Gan, Guolin Pu, Weiyin Xing, Lianfang Wang, Shu Liang

“…However, the diversity of these diseases, their uneven distribution, and complex field environments create challenges for precise, multi-scale detection. While YOLO object detection algorithms show strong performance in automated detection, their feature extraction capabilities remain limited in complex agricultural settings. …”
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Machine learning based intrusion detection framework for detecting security attacks in internet of things by V. Kantharaju, H. Suresh, M. Niranjanamurthy, Syed Immamul Ansarullah, Farhan Amin, Amerah Alabrah

“…Then the preprocessing output is fed to feature selection. At feature selection, the optimum features are compiled using a modified War Strategy Optimization Algorithm (WSOA). …”
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Algorithmic bias and the Value Sensitive Design approach by Judith Simon, Pak-Hang Wong, Gernot Rieder

“…Recently, amid growing awareness that computer algorithms are not neutral tools but can cause harm by reproducing and amplifying bias, attempts to detect and prevent such biases have intensified. …”
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Mathematical algorithm for the automatic recognition of intestinal parasites. by Alicia Alva, Carla Cangalaya, Miguel Quiliano, Casey Krebs, Robert H Gilman, Patricia Sheen, Mirko Zimic

“…The principal result showed that our algorithm reached sensitivities between 99.10%-100% and specificities between 98.13%- 98.38% to detect each parasite separately. …”
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Dry-Type Air-Core Series Reactor Turn-to-Turn Short Circuit Fault Detection Method Based on Multi-Parameter Data Fusion by WANG Yin, WANG Yuanyuan, CAO Chengjun, ZHANG Lizhi, YIN Youpeng, JI Hongzhen, DOU Di

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Online clustering with interpretable drift adaptation to mixed features by Flavio Corradini, Vincenzo Nucci, Marco Piangerelli, Barbara Re

“…In our research, we introduce FURAKI, an innovative online clustering algorithm that incorporates drift detection. It employs a binary tree structure and is capable of handling both single-feature and mixed-feature data from unbounded streams. …”
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Retinopathy Disease Detection and Classification Using a Coordinate Attention Module-Based Convolutional Neural Network with Leaky Rectified Linear Unit by Pravin Balaso Chopade, Prabhakar N. Kota, Bhagvat D. Jadhav, Pravin Marotrao Ghate, Shriram Sadashiv Kulkarni

“…The extracted features are given to CAM-based CNN with LReLU to detect DR, which overcomes the dead issues of neurons and minimizes the probability of inactive neurons. …”
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A human visual cognitive mechanism based network for surface defect detection(基于人类视觉认知机制的表面缺陷检测) by 崔丽莎(CUI Lisha), 代润鹏(DAI Runpeng), 姜晓恒(JIANG Xiaoheng), 李飞蝶(LI Feidie), 陈恩庆(CHEN Enqing), 徐明亮(XU Mingliang)

“…HVCM-Net achieves superior detection performance on defect datasets GB-DET, NEU-DET, and DAGM2007 compared to other algorithms, demonstrating the effectiveness of the proposed method.…”
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