Distrust Spillover in Sharing Accommodation: Evidence From Airbnb in Beijing by Xin Jin, Bo Wang, Ning Ma

“…Beijing Airbnb listings data were collected and analyzed using sentiment analysis, machine learning, and econometric statistics in English and Chinese languages. …”
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Towards the Development of a Cloud Computing Intrusion Detection Framework Using an Ensemble Hybrid Feature Selection Approach by Noah Oghenefego Ogwara, Krassie Petrova, Mee Loong Yang

“…The selected features used to train the ML (machine learning) model of the intrusion detection component comprised a binary detection engine for the identification of malicious/attack packets and a multiclassification detection engine for the identification of the type of attack. …”
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Image Processing-Based Spall Object Detection Using Gabor Filter, Texture Analysis, and Adaptive Moment Estimation (Adam) Optimized Logistic Regression Models by Nhat-Duc Hoang

“…The new model is an integration of image processing techniques and machine learning approaches. The Gabor filter supported by principal component analysis and k-means clustering is used for identifying the region of interest within an image sample. …”
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A UWB NLOS identification method under pedestrian occlusion by Tong WU, Yeshen LI, Zhenhuang HUANG, Yu ZHANG, Wanle ZHANG, Ke XIONG

“…Ultrawideband (UWB) is a hot technology for indoor positioning with large bandwidth, strong anti-interference ability, and high multipath resolution capacity.However, due to the complex indoor environment, UWB signal propagation will inevitably be blocked, resulting in non-line-of-sight (NLOS) propagation, which greatly reduces the accuracy of UWB positioning.Therefore, identifying NLOS signals accurately and discarding or correcting them are important to alleviate the problem of the decline in positioning accuracy.The majority of present NLOS identification work focuses on scenes with building structures such as walls.Further discussion is needed for scenes obscured by pedestrians.Since the impact of human obstacles on the signals is more complex and cannot be ignored, the NLOS identification under pedestrian occlusion was studied.By comparing a variety of machine learning methods and signal feature combinations, the random forest method based on the three-dimensional features of the first path signal power, the received signal power, and the measured distance was proposed.These features with fewer dimensions and easy extraction were used to achieve a high identification percentage for NLOS.The experimental results based on the measured data of different devices show that the NLOS identification accuracy based on the proposed method reaches 99.05%, 99.32% and 98.81% respectively.…”
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Gaussian Pyramid for Nonlinear Support Vector Machine by Rawan Abo Zidan, George Karraz

“…Support vector machine (SVM) is one of the most efficient machine learning tools, and it is fast, simple to use, reliable, and provides accurate classification results. …”
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Research on Spam Filters Based on NB Algorithm by Su Shengyue

“…Future work may focus on improving the model’s accuracy and robustness by integrating it with other machine learning models, like Support Vector Machines (SVMs) and deep learning techniques, to enhance spam classification capabilities.…”
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Multivariate Image Analysis Applied to Cross-Laminated Timber: Combined Hyperspectral Near-Infrared and X-ray Computed Tomography by Dietrich Buck, Olle Hagman

“…In exploring ways of improving efficiency, this study explores multivariate image analysis (MIA) via partial least squares discriminant analysis (PLS-DA) machine learning as a means to classify CLT material features. …”
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A Comprehensive Investigation of Fraud Detection Behavior in Federated Learning by Sun Rui

“…The comparison involves three machine learning models - Artificial Neural Networks (ANN), Random Forest (RF), and Convolutional Neural Networks (CNN) - to assess their efficacy in the FL context. …”
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From threat to response: Cybersecurity evolution in Albania by Klorenta PASHAJ, Vilma TOMÇO, Eralda GJIKA

“…One key recommendation is the forecasting of cyber-attacks, which could benefit from the application of time-series and machine learning techniques to enhance predictive capabilities. …”
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Rancang Bangun Purwarupa Pemilah Sampah Pintar Berbasis Deep Learning by Kahlil Muchtar, Nyak Twoman Anshari, Chairuman Chairuman, Khalid Alhabibie, Khairul Munadi

“…In this case, Deep Learning, a branch of (Machine Learning) is used to be able to understand a set of images and classify them. …”
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ANALISIS SENTIMEN DATA TWITTER TERKAIT CHATGPT MENGGUNAKAN ORANGE DATA MINING by Tri Yuli Pahtoni, Handaru Jati

“…Positive, negative, and neutral responses were processed using orange data mining software, namely machine learning tools, data mining, and data visualization. …”
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Identifying health risk determinants and molecular targets in patients with idiopathic pulmonary fibrosis via combined differential and weighted gene co-expression analysis by Abu Tayab Moin, Md. Asad Ullah, Jannatul Ferdous Nipa, Mohammad Sheikh Farider Rahman, Afsana Emran, Md. Minhazul Islam, Swapnil Das, Tawsif Al Arian, Mohammad Mahfuz Enam Elahi, Mukta Akter, Umme Sadea Rahman, Arnab Halder, Shoaib Saikat, Mohammad Jakir Hosen

“…Co-expression analysis revealed DEG modules correlated with varying IPF severity phenotypes. Machine learning analysis pinpointed a subset of genes with high discriminatory power between IPF and healthy individuals. …”
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Penerapan SMOTE untuk Mengatasi Imbalance Class dalam Klasifikasi Kepribadian MBTI Menggunakan Naive Bayes Classifier by Mutiara Persada Pulungan, Andi Purnomo, Aliyah Kurniasih

“… Kepribadian Myers-Briggs Type Indicator ( MBTI ) telah menjadi topik populer dalam memahami karakteristik individu dan dampaknya pada interaksi sosial, karir, dan pengambilan keputusan. Model Machine Learning dengan algoritma Naive Bayes Classifier sering digunakan untuk memprediksi kepribadian MBTI berdasarkan data Twitter. …”
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Single‐cell RNA‐sequencing and spatial transcriptomic analysis reveal a distinct population of APOE− cells yielding pathological lymph node metastasis in papillary thyroid cancer... by Guohui Xiao, Rongli Xie, Jianhua Gu, Yishu Huang, Min Ding, Dongjie Shen, Jiqi Yan, Jianming Yuan, Qiong Yang, Wen He, Siyu Xiao, Haizhen Chen, Dan Xu, Jian Wu, Jian Fei

“…We established a machine learning‐based scRNA‐seq data, 13‐gene signature predictive of lymph node metastasis. …”
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Perancangan User Experience Aplikasi Penghemat Listrik myECO dengan Otomatisasi dan Manajemen Listrik untuk Rumah Tangga by Maulana Derifato Achmad, Herman Tolle, Buce Trias Hanggara

“…Maka dapat dihadirkan suatu solusi yaitu aplikasi berbasis Internet of Things (IoT), Artificial Intelligence dan Machine Learning yang dapat menganalisis pemborosan dan memudahkan manajemen perangkat listrik. …”
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Anatomical, functional, and blood-born predictors of severity of brachycephalic obstructive airway syndrome severity in French Bulldogs by Claudia Schmid, Claudia Schmid, Claudia Schmid, Aline R. Steiner, Léonie Spielhofer, Léonie Spielhofer, Meltem Galfetti, Meltem Galfetti, Nikki Rentsch, Nikolay Bogdanov, Johannes Vogel, Regina Hofmann-Lehmann, Regina Hofmann-Lehmann, Sonja Hartnack, Georgy Astakhov, Reinhard Furrer, Anna Bogdanova, Anna Bogdanova, Iris Margaret Reichler

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Pengembangan Auto-AI Model Generatif Analisis Kompleksitas Waktu Algoritma Untuk Data Multi-Sensor IoT Pada Node-RED Menggunakan Extreme Learning Machine by Imam Cholissodin, Dahnial Syauqy, Dwi Ady Firmanda, Ibrahim Aji, Edy Rahman, Syazwandy Harahap, Fernando Septino

“…Namun dengan perkembangan teknologi komputer untuk AI, Machine Learning maupun Deep Learning, algoritma dengan basis AI tersebut, dalam penelitian ini dikembangkan untuk menemukan solusi general persamaan model T(n) secara otomatis dari desain algoritma sederhana atau kompleks. …”
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Noninvasive Oral Hyperspectral Imaging–Driven Digital Diagnosis of Heart Failure With Preserved Ejection Fraction: Model Development and Validation Study by Xiaomeng Yang, Zeyan Li, Lei Lei, Xiaoyu Shi, Dingming Zhang, Fei Zhou, Wenjing Li, Tianyou Xu, Xinyu Liu, Songyun Wang, Quan Yuan, Jian Yang, Xinyu Wang, Yanfei Zhong, Lilei Yu

“…We extracted 25 spectral bands from each patient image and obtained 8 corresponding texture features to evaluate the performance of 28 machine learning algorithms for their ability to distinguish control participants from participants with HFpEF. …”
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Classification of Prominent Cacao Pod Diseases Using Multi-Feature Visual Analysis and k-Nearest Neighbors Algorithm by Earl Clarence San Diego, Seph Gerald Rodrin, Edwin Arboleda

“…The study's outcome suggested the continuous practicality of fusing visual feature extraction processes with supervised machine learning to generate models that can be applied to improve agricultural methods.         …”
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Modeling of Human Skin by the Use of Deep Learning by Xin Xiong, Xuexun Guo, Yiping Wang

“…Pattern recognition gets more attention in machine learning field to take advantage of data available for modern life. …”
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