A Novel Diagnostic Framework with an Optimized Ensemble of Vision Transformers and Convolutional Neural Networks for Enhanced Alzheimer’s Disease Detection in Medical Imaging by Joy Chakra Bortty, Gouri Shankar Chakraborty, Inshad Rahman Noman, Salil Batra, Joy Das, Kanchon Kumar Bishnu, Md Tanvir Rahman Tarafder, Araf Islam

“…Artificial intelligence-based solutions are putting great importance on identifying the disease efficiently, where deep learning with medical imaging is highly being utilized to develop disease detection frameworks. In this work, a novel and optimized detection framework has been proposed that comes with remarkable performance that can classify the level of Alzheimer’s accurately and efficiently. …”
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A Hybrid Ensemble Learning Framework for Predicting Lumbar Disc Herniation Recurrence: Integrating Supervised Models, Anomaly Detection, and Threshold Optimization by Mădălina Duceac (Covrig), Călin Gheorghe Buzea, Alina Pleșea-Condratovici, Lucian Eva, Letiția Doina Duceac, Marius Gabriel Dabija, Bogdan Costăchescu, Eva Maria Elkan, Cristian Guțu, Doina Carina Voinescu

“…<b>Methods:</b> A dataset of 977 patients from a Romanian neurosurgical center was used. …”
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Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

“…To solve the problem that the parameter of silicon content ([Si]) in hot mental is difficult to be directly detected and obtained by manual analysis with large time delay, a method of sparse and robust least squares support vector regression (R-S-LS-SVR) was proposed to establish a dynamic model of[Si] with the help of the multi-objective genetic optimization of model parame-ters. …”
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A green and robust LC–MS/MS bioanalytical method for sulopenem etzadroxil and probenecid: Optimization, validation, and pharmacokinetic application by Niloufer Tasnim Khazi, Kumaraswamy Gandla, Lalitha Repudi

“…The method exhibited excellent linearity (10–400 ng/mL), low limits of detection (LOD: ∼3 ng/mL), and quantification (LOQ: ∼9 ng/mL) for both analytes, with recovery rates > 93 % and %CVs < 15 %. …”
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An Optimized Real-Time PCR to Avoid Species-/Tissue-Associated Inhibition for H5N1 Detection in Ferret and Monkey Tissues by LingJun Zhan, LinLin Bao, FengDi Li, Qi Lv, LiLi Xu, Chuan Qin

“…No statistically significant differences were found between the Ct values from the isolation methods. So the optimized SYBR Green real-time PCR could avoid species- or tissue-associated PCR inhibition in detecting H5N1 in ferret and monkey tissues, including lung and small intestine.…”
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A New Meta-heuristic Algorithm based on Multi-criteria Decision Making to Solve Community Detection Problem by Vahid Baradaran, Amir Hossein Hosseinian, Reza Derakhshani

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Optimization and modeling of Zn2SnO4 sensitivity as gas sensor for detection benzene in the air by using the response surface methodology by Hassan Hosseinzadeh asl, Ghasem Tohidi, F. Movahedi, E. Hassannayebi

“…In this paper, the performance of the benzene gas detection sensor in the air is optimized by an experimental design method. …”
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MRI based early Temporal Lobe Epilepsy detection using DGWO based optimized HAETN and Fuzzy-AAL Segmentation Framework (FASF). by Hasim Khan, Ahmed Ibrahim Alutaibi, Ghanshyam G Tejani, Sunil Kumar Sharma, Ahmad Raza Khan, Fuzail Ahmad, Seyed Jalaleddin Mousavirad

“…Furthermore, an effective feature selection method is proposed using the Dipper- grey wolf optimization (DGWO) algorithm to improve the performance of the proposed model. …”
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Hybrid Feature-Based Disease Detection in Plant Leaf Using Convolutional Neural Network, Bayesian Optimized SVM, and Random Forest Classifier by Ashutosh Kumar Singh, SVN Sreenivasu, U.S.B. K. Mahalaxmi, Himanshu Sharma, Dinesh D. Patil, Evans Asenso

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iYOLOV7-TPE-SS: Leveraging Improved YOLO Model With Multilevel Hyperparameter Optimization for Road Damage Detection on Edge Devices by Haniah Mahmudah, Aulia Siti Aisjah, Syamsul Arifin, Catur Arif Prastyantyo

“…The research investigates how leveraging multilevel hyperparameter optimization using the TPE-SS model improves system performance where road damage is detected. …”
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Optimization of Sensor Positions and Orientations for Multiple Load Case Scenarios by Wacław Kuś, Waldemar Mucha, Iyasu Tafese Jiregna

“…This paper focuses on optimizing sensor placement in structures for load monitoring applications. …”
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Research on Anti-Submarine Warfare Method of Unmanned Aerial Vehicle Cluster Based on Area Coverage and Distributed Optimization Control by Yongzhao Yan, Yi Liu, Ying Bi, Qian Wang, Huazhen Cao, Ziping Yu, Kangkang Li, Bo Wang, Xiaoping Ma

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Development of paper based colorimetric method using pigment from red dragon fruit for determination of Cu and Fe by Rimadani Pratiwi, Raspati Dewi Mulyaningsih, Aliya Nur Hasanah

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Noise Analysis and Suppression Methods for the Front-End Readout Circuit of a Microelectromechanical Systems Gyroscope by Chunhua He, Yingyu Xu, Xiaoman Wang, Heng Wu, Lianglun Cheng, Guizhen Yan, Qinwen Huang

“…This study presents an optimized front-end readout circuit and noise suppression methods. …”
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GC-Faster RCNN: The Object Detection Algorithm for Agricultural Pests Based on Improved Hybrid Attention Mechanism by Bolun Guan, Yaqian Wu, Jingbo Zhu, Juanjuan Kong, Wei Dong

“…In addition, experiments have also shown that the GC-Faster RCNN detection method can reduce interference from multiple scales and high similarity between categories, improving detection performance.…”
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Encrypted traffic classification method based on convolutional neural network by Rongna XIE, Zhuhong MA, Zongyu LI, Ye TIAN

“…Aiming at the problems of low accuracy, weak generality, and easy privacy violation of traditional encrypted network traffic classification methods, an encrypted traffic classification method based on convolutional neural network was proposed, which avoided relying on original traffic data and prevented overfitting of specific byte structure of the application.According to the data packet size and arrival time information of network traffic, a method to convert the original traffic into a two-dimensional picture was designed.Each cell in the histogram represented the number of packets with corresponding size that arrive at the corresponding time interval, avoiding reliance on packet payloads and privacy violations.The LeNet-5 convolutional neural network model was optimized to improve the classification accuracy.The inception module was embedded for multi-dimensional feature extraction and feature fusion.And the 1*1 convolution was used to control the feature dimension of the output.Besides, the average pooling layer and the convolutional layer were used to replace the fully connected layer to increase the calculation speed and avoid overfitting.The sliding window method was used in the object detection task, and each network unidirectional flow was divided into equal-sized blocks, ensuring that the blocks in the training set and the blocks in the test set in a single session do not overlap and expanding the dataset samples.The classification experiment results on the ISCX dataset show that for the application traffic classification task, the average accuracy rate reaches more than 95%.The comparative experimental results show that the traditional classification method has a significant decrease in accuracy or even fails when the types of training set and test set are different.However, the accuracy rate of the proposed method still reaches 89.2%, which proves that the method is universally suitable for encrypted traffic and non-encrypted traffic.All experiments are based on imbalanced datasets, and the experimental results may be further improved if balanced processing is performed.…”
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On Optimally Selecting Candidate Detectors with High Predicted Radio Signals from Energetic Cosmic Ray-Induced Extensive Air Showers by Tudor Alexandru Calafeteanu, Paula Gina Isar, Emil Ioan Slușanschi

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Comparative Analysis and Optimal Selection of Calibration Functions in Pure Rotational Raman Lidar Technique by Yinghong Yu, Siying Chen, Wangshu Tan, Rongzheng Cao, Yixuan Xie, He Chen, Pan Guo, Jie Yu, Rui Hu, Haokai Yang, Xin Li

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Investigation of Effects of Thermal Radiation, Magnetic Field, Eckert Number, and Thermal Slip on MHD Hiemenz Flow by Optimal Homotopy Asymptotic Method by Solomon Bati Kejela, Mitiku Daba, Abebe Girum

“…Similarity variable conversion method has been applied to transmute the fundamental governing equations of the fluid dynamics in flow into a pair of nonlinear third-order ordinary differential equations and is analytically solved by the optimal homotopy asymptotic method (OHAM). …”
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Improved Isolation Optimizes Downstream Application of Extracellular Vesicles Derived from <i>Mycobacterium tuberculosis</i> by Wenjing Wang, Yue Hou, Jingfang Zhang, Zhaogang Sun, Hong Sun

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