Music Emotion Detection Using Hierarchical Sparse Kernel Machines by Yu-Hao Chin, Chang-Hong Lin, Ernestasia Siahaan, Jia-Ching Wang

“…In the first level, a set of acoustical features are extracted, and principle component analysis (PCA) is implemented to reduce the dimension. …”
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Epidemiological, demographic, social, clinical features of manifestations of system red lupus in patients in Kazakhstan by B. G. Issayeva, E. A. Aseeva, M. M. Saparbayeva, S. M. Issayeva, M. M. Kulshymanova, S. M. Kaiyrgali, M. P. Bizhanova, K. Zh. Nurgaliyev, N. S. Akhtaeva, B. A. Kulymbetova, K. K. Rysbekova, S. K. Solovyev

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Unmasking the Fake: Machine Learning Approach for Deepfake Voice Detection by Muhammad Usama Tanveer Gujjar, Kashif Munir, Madiha Amjad, Atiq Ur Rehman, Amine Bermak

“…By extracting Mel-Frequency Cepstral Coefficients (MFCC) from audio samples which serve as the foundational features for identifying genuine and fake voices. These MFCC features are then enhanced through a transformation process that employs a Gaussian Naive Bayes (GNB) model in conjunction with Non-Negative Factorization, creating a more discriminative feature set for subsequent analysis. …”
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An explainable EEG epilepsy detection model using friend pattern by Turker Tuncer, Sengul Dogan

“…EEG signals have commonly been used to detect epilepsy. Therefore, the main objective of this research is to demonstrate the epilepsy detection capability of the presented new-generation relation-centric feature extraction function. …”
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Surface roughness detection based on spindle motor current signal by Liu Xuejie, Li Guofu, Ren Lu

“…The total harmonic distortion feature achieves built-up edge detection during the machining process. …”
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Chronic lymphocytic leukemia in combination with COVID-19: clinical features and unfavorable prognosis factors by O. L. Kochneva, E. A. Baryakh, E. N. Misyurina, E. I. Zhelnova, K. V. Yatskov, T. S. Chudnova, Yu. Yu. Polyakov, A. B. Makeshova, M. A. Mingalimov, D. D. Ivanova, L. T. Shimanovskaya, E. N. Zotina, T. N. Tolstykh, E. Yu. Grishina, D. E. Gagloeva, V. N. Yakimets, A. I. Koneva, E. A. Karimova

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Contactless Detection of pH Change in a Liquid Analyte by Dylan Gustafson, Dominic Klyve

“…Second, the change is detected using a Linear Discriminant Analysis model using values from an inverse Fourier transform of the frequency data as its features. …”
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Rumor Detection Based on Knowledge Enhancement and Graph Attention Network by Wanru Wang, Yuwei Lv, Yonggang Wen, Xuemei Sun

“…Presently, most of the existing rumor detection methods focus on learning and integrating various features for detection, but due to the complexity of the language, these models often rarely consider the relationship between the parts of speech. …”
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Using pseudo-AI submissions for detecting AI-generated code by Shariq Bashir

“…Previous studies have explored ways to detect AI-generated text, such as analyzing structural differences, embedding watermarks, examining specific features, or using fine-tuned language models. …”
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Detection of axonal synapses in 3D two-photon images. by Cher Bass, Pyry Helkkula, Vincenzo De Paola, Claudia Clopath, Anil Anthony Bharath

“…Studies of structural plasticity in the brain often require the detection and analysis of axonal synapses (boutons). …”
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An Object Detection Model based on Augmented Reality for Iraqi Archaeology by suha Dh. Athab, Abdulamir Abdullah Karim

“…The proposed model utilizes a pre-trained backbone network to extract complicated spatial features from input images; additional convolutional and fully connected layers are introduced to refine these features. …”
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Intrusion detection model based on fuzzy theory and association rules by Jianwu ZHANG, Jiasen HUANG, Di ZHOU

“…An intrusion detection model based on fuzzy theory and improved Apriori algorithm was proposed.The BV-Apriori algorithm was used to generate the matching rule base,and the problem of excessive boundary in the continuous data partitioning process was solved by fuzzy set technology.The real-time analysis of the relationship between features and the update of the rule base were completed,and the intrusion detection model BVA-IDS (Boolean vector Apriori-intrusion detection system) was built.The results show that the mining efficiency of the BV-Apriori algorithm is significantly improved when compared with the existing Apriori-BR algorithm,in addition,the BVA-IDS model also performs well on intrusion detection indicators with high detection accuracy,and low false positive rate and false negative rate.…”
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Intrusion detection model based on fuzzy theory and association rules by Jianwu ZHANG, Jiasen HUANG, Di ZHOU

“…An intrusion detection model based on fuzzy theory and improved Apriori algorithm was proposed.The BV-Apriori algorithm was used to generate the matching rule base,and the problem of excessive boundary in the continuous data partitioning process was solved by fuzzy set technology.The real-time analysis of the relationship between features and the update of the rule base were completed,and the intrusion detection model BVA-IDS (Boolean vector Apriori-intrusion detection system) was built.The results show that the mining efficiency of the BV-Apriori algorithm is significantly improved when compared with the existing Apriori-BR algorithm,in addition,the BVA-IDS model also performs well on intrusion detection indicators with high detection accuracy,and low false positive rate and false negative rate.…”
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Anomaly Detection for MVB Network Based on Logistic Ensemble Learning by Huizhen WANG, Lide WANG, Yueyi YANG, Ping SHEN

“…Multifunction vehicle bus (MVB) has been widely used in rail transit vehicles, but the poor working environment may result in the performance degradation of MVB network, which even endangers the driving safety in serious cases. Based on the analysis of common faults in MVB network, with extracting the network state features from the MVB physical layer and data link layer, an detection method based on heterogeneous Logistic ensemble learning to detect MVB network anomaly and avoid breakdown maintenance to the maximum extent was proposed. …”
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APPLICATION OF CLASSIFICATION BASED ASSOCIATION (CBA) FOR MONKEYPOX DISEASE DETECTION by Qoria Yudi Pratama, Mohammad Isa Irawan

“…CBA integrates the advantages of classification and association analysis, allowing the classification process and a deeper understanding of the strength of the relationship between features in the dataset through the analysis of metrics such as support and confidence. …”
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TATPat based explainable EEG model for neonatal seizure detection by Turker Tuncer, Sengul Dogan, Irem Tasci, Burak Tasci, Rena Hajiyeva

“…In this EFE model, there are four essential phases and these phases: (i) automaton and transformer-based feature extraction, (ii) feature selection deploying cumulative weight-based neighborhood component analysis (CWNCA), (iii) the Directed Lobish (DLob) and Causal Connectome Theory (CCT)-based explainable result generation and (iv) classification deploying t algorithm-based support vector machine (tSVM). …”
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Transformer Self-Attention Change Detection Network with Frozen Parameters by Peiyang Cheng, Min Xia, Dehao Wang, Haifeng Lin, Zikai Zhao

“…These results fully demonstrate the superiority, robustness, and generalization ability of ZAQNet in change detection tasks and provide an efficient and reliable solution for remote sensing image analysis.…”
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Comparison of Moving Average and Differential Operation for Wheeze Detection in Spectrograms by Meng-Lun Hsueh, Jin-Peng Chen, Bing-Yuh Lu, Huey-Dong Wu, Pei-Yi Liu

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Deep learning-based edge detection for random natural images by Kanija Muntarina, Rafid Mostafiz, Sumaita Binte Shorif, Mohammad Shorif Uddin

“…Edge detection plays a critical role in computer vision, particularly in the analysis of random natural images. …”
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YOLOv8 with Post-Processing for Small Object Detection Enhancement by Jinkyu Ryu, Dongkurl Kwak, Seungmin Choi

“…Small-object detection in images, a core task in unstructured big-data analysis, remains challenging due to low resolution, background noise, and occlusion. …”
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