Hybrid IoT-CAD system: optimized feature selection based gated recurrent residual deep learning for cyber attack detection in IoT networks by Susheela Vishnoi, Sunil Kumar, Saikat Samanta

“…Next, to solve the data imbalance problem, Conditional Generative Adversarial Networks (CGAN) are employed. After that, the Binary Genetic Dung Beetle Optimization (B-GDBO) method is utilized for optimal feature selection and also reduces the risk of overfitting. …”
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Validation of the Distress Thermometer for detecting psychological distress in patients with stable chronic obstructive pulmonary disease: optimal cut-off score and influencing fac... by Xu Tian, Xiaoling Liu, Xiuni Gan, Maria F. Jimenez-Herrera, Hongcai Shang, Yi Ren

“…The Distress Thermometer (DT), originally developed for cancer patients, is a brief screening tool for detecting psychological distress. However, the optimal cut-off in COPD patients remains unclear. …”
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Highly Versatile FPGA-Implemented Cyber Coherent Ising Machine by Toru Aonishi, Tatsuya Nagasawa, Toshiyuki Koizumi, Mastiyage Don Sudeera Hasaranga Gunathilaka, Kazushi Mimura, Masato Okada, Satoshi Kako, Yoshihisa Yamamoto

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Theoretical investigation of photonic spin Hall effect based on layered metastructure with graphene regulation by WOA for encoding and encryption by Na Pei, Ye Zheng, Yue-Qi Tang, Xing-Zhou Tang, Hai-Feng Zhang

“…To further optimize coding performance, the Beluga optimization algorithm is employed to optimize the PSHE displacement. …”
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PARAMETRIC SYNTHESIS OF MODELS FOR MULTICRITERIAL ESTIMATION OF TECHNOLOGICAL SYSTEMS by Vladimir Beskorovainyi

“…The methods used are: system analysis, decision theory, identification theory, multicriteria optimization methods. The following results are obtained: to increase the adequacy of the models of TS multifactor estimation, it is suggested to use the utility function of partial criteria that makes it possible to realize not only linear, convex or concave, but also S (Z)-like dependencies on their values. …”
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Multi-user joint task offloading and resource allocation based on mobile edge computing in mining scenarios by Siqi Li, Weidong Li, Wanbo Zheng, Yunni Xia, Kunyin Guo, Qinglan Peng, Xu Li, Jiaxin Ren

“…To evaluate the effectiveness of the proposed method, we compare it with five baseline algorithms: the improved grey wolf optimizer metaheuristic algorithm, the traditional genetic algorithm, the binary offloading decision mechanism, the partial non-cooperative mechanism, and the fully local execution mechanism. …”
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Application of decision diagrams of incompletely specified of k-valued logic functions in the synthesis of logical circuits by P. N. Bibilo

“…Encoding of multi-valued values of arguments and values of functions of k-valued logic by binary codes leads to systems of partial Boolean functions, which are also further defined in order to minimize their multi-level BDD representations.Conclusion. …”
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Cross-Modal Hashing Retrieval Based on Density Clustering by Xiaojun Qi, Xianhua Zeng, Hongmei Tang

“…However, most of the existing hashing methods have the problem of how to precisely learn potential correlations between different modalities from binary codes with minimal loss. In addition, solving binary codes in different modalities is an NP-hard problem. …”
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Information-extremе machine learning for object identification on the terrain by V. V. Moskalenko, A. H. Korobov

“…The offered algorithm of information-extreme machine learning implements the adaptive coding of values of primary features using multilevel system of control permits, and creation of hyperspherical containers of classes in binary space of secondary features with sequential optimization procedures. …”
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Exploration of Machine Learning Models for Prediction of Gene Electrotransfer Treatment Outcomes by Alex Otten, Michael Francis, Anna Bulysheva

“…Tissue heterogeneity complicates the delivery process, requiring the extensive optimization of pulsing protocols currently empirically optimized. …”
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Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Framework by Nidhi Simmons, David E. Simmons, Michel Daoud Yacoub

“…They also reveal that focusing on standard metrics, like precision, false-positive rate, or recall, may not produce optimal predictors. …”
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Solving the Control Synthesis Problem Through Supervised Machine Learning of Symbolic Regression by Askhat Diveev, Elena Sofronova, Nurbek Konyrbaev

“…The optimization criterion for solving the synthesis problem is the accuracy of the object’s movement along the optimal trajectory. …”
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Evolutionary Synthesis of High-Capacity Reconfigurable Multilayer Road Networks Using a Multiagent Hybrid Clustering-Assisted Genetic Algorithm by Andranik S. Akopov, Levon A. Beklaryan

“…The proposed algorithm combines the use of binary-coded crossovers and mutations as genetic operators, and biobjective discrete particle swarm optimization (BODPSO) techniques to improve the evolutionary search process. …”
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D-BADGE: Decision-Based Adversarial Batch Attack With Directional Gradient Estimation by Geunhyeok Yu, Minwoo Jeon, Hyoseok Hwang

“…Image-agnostic universal adversarial perturbations (UAPs) are much more threatening, but many limitations exist to implementing UAPs in real-world scenarios where only binary decisions are returned. In this research, we propose D-BADGE, a novel method to craft universal adversarial perturbations for executing decision- To primarily optimize perturbation by focusing on decisions, we consider the direction of these updates as the primary factor and the magnitude of updates as the secondary factor. …”
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Applying a logistic regression-clustering joint model to analyze the causes of prolonged pre-analytic turnaround time for urine culture testing in hospital wards by Shuangshuang Lv, Huan Ye, Yuan Li, Jian Zhang

“…Post-intervention data (May 2024–July 2024, *n* = 1,456) was also analyzed to assess the impact.ResultsAnalysis of the critical risk factors revealed that specimens collected between 04:00–05:59/10:00–11:59 had 142.92-fold higher delay odds (95% CI: 58.81–347.37). …”
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Prediction of Thyroid Classes Using Feature Selection of AEHOA Based CNN Model for Healthy Lifestyle by Rachappa Jopate, Piyush Kumar Pareek, DivyaJyothi M. G, Ariam Saleh Zuwayid Juma Al Hasani

“…Although diagnostic techniques exist, they frequently seek binary categorization, use insufficiently big datasets, and lack confirmation of their conclusions. …”
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XAIEnsembleTL-IoV: A new eXplainable Artificial Intelligence ensemble transfer learning for zero-day botnet attack detection in the Internet of Vehicles by Yakub Kayode Saheed, Joshua Ebere Chukwuere

“…Additionally, the model employs hybrid bidirectional long-short-term memory with autoencoders (BiLAE) to reduce the dimensionality of IoV network traffic, improving computational efficiency. It also uses Barnacle Mating Optimizer (BMO) to optimize the hyper-parameters of deep learning models such as ResNet, Inception, Inception ResNet, and MobileNet Convolution neural network-transfer learning architecture (CNN-TL), enhancing detection capabilities without needing vast amounts of labeled data. …”
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Securing the economic management and service infrastructure of banks via the use of artificial intelligence (MO-ILSTM) by Xintong Wu

“…This study explores the use of Mothfly Optimized Improved Long Short-Term Memory (MO-ILSTM) as a data classification technique to improve data sharing and processing effectiveness. …”
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NLP for computational insights into nutritional impacts on colorectal cancer care by Shengnan Gong, Xiaohong Jin, Yujie Guo, Jie Yu

“…Relevant terms are then extracted and visualized in a word cloud. The dataset also contained an imbalanced binary CRC outcome, which is rebalanced utilizing the random oversampling. …”
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Quantum global minimum finder based on variational quantum search by Mohammadreza Soltaninia, Junpeng Zhan

“…Designed with a O(n)-depth circuit architecture, QGMF also utilize the logarithmic benefits of binary search to enhance scalability and efficiency. …”
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