Application of Phi (<italic>&#x03A6;</italic>), the Golden Ratio, in Computing: A Systematic Review by M. Akhtaruzzaman, Jamal Uddin Tanvin, Amir Akramin Shafie, Fahim Shahryer, Sachitra Halder

“…This article systematically examines <inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula>&#x2019;s diverse applications in computing, focusing on its role in enhancing visual appeal, optimizing algorithms, system design, and influencing fields such as biometrics, machine intelligence, and engineering. …”
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Prediction of Groundwater Level Based on the Integration of Electromagnetic Induction, Satellite Data, and Artificial Intelligent by Fei Wang, Lili Han, Lulu Liu, Yang Wei, Xian Guo

“…Remote sensing data combined with machine learning algorithms have become one of the important tools for groundwater level modeling. …”
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Construction of machine learning-based models for screening the high-risk patients with gastric precancerous lesions by Shuxian Yu, Haiyang Jiang, Jing Xia, Jie Gu, Mengting Chen, Yan Wang, Xiaohong Zhao, Zehua Liao, Puhua Zeng, Tian Xie, Xinbing Sui

“…Then, the prediction model was established using ten different machine learning algorithms and the Random Forest (RF) model achieved the highest accuracy at 85.65%. …”
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Assessing the readability, quality and reliability of responses produced by ChatGPT, Gemini, and Perplexity regarding most frequently asked keywords about low back pain by Erkan Ozduran, Volkan Hancı, Yüksel Erkin, İlhan Celil Özbek, Vugar Abdulkerimov

“…This study can provide inspiration for future studies on improving the algorithms and responses of AI chatbots.…”
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Genetic Determinants of Immune Cells and Hepatocellular Carcinoma Risk: A Bioinformatics and Bidirectional Mendelian Randomization Study by Tong WU, Fei GAO, Fei TENG, Qiaoli ZHANG

“…ObjectiveTo identify core targets of hepatocellular carcinoma (HCC) by using bioinformatics and specific algorithms, explore their relationships with immune cells, and investigate the causal relationships between immune cells and HCC through Mendelian randomization. …”
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Pendekatan Ensemble untuk Analisis Sentimen Covid19 Menggunakan Pengklasifikasi Soft Voting by Nova Agustina, Candra Nur Ihsan

“…In this study, all algorithms get the same accuracy for sentiment analysis, which is 89%. …”
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Exploring timely and safe discharge from ICU: a comparative study of machine learning predictions and clinical practices by Chao Ping Wu, Rachel Benish Shirley, Alex Milinovich, Kaiyin Liu, Eduardo Mireles-Cabodevila, Hassan Khouli, Abhijit Duggal, Anirban Bhattacharyya

“…The LightGBM model outperformed other algorithms, achieving a AUROC of 0.91 (95%CI 0.9–0.91) and performance was held in the 2020 validation cohort (n = 509) with an AUROC of 0.85 (95%CI 0.84–0.85). …”
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Tourism Growth Prediction Based on Deep Learning Approach by Xiaoling Ren, Yanyan Li, JuanJuan Zhao, Yan Qiang

“…The main objective in this study is to predict the tourism growth via one of the deep learning algorithms of extracting new features. The outcome of this study showed that the performance of the adopted deep learning framework was better than that of artificial neural network and support vector regression models. …”
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Gesture recognition based on flexible solar cells and ultrathin hydrogel film by Rucheng WU, Wenbo DING, Xiaomin XU, Linqi SONG, Weitao XU

“…Daily life involves various gestures, and combining these with smart wearable devices is crucial for improving quality of life.One effective solution to the challenges of gesture recognition and device energy consumption isutilizing the photoelectric conversion characteristics of solar energy-related devices.The data of five commonly used gestures were collected in the research of the combination of flexible solar cells and gesture recognition.Z-Score, low-pass filter, sliding window techniques for signal processing were applied, and successfully achieved 100% predicted accuracy using random forest, support vector machine and neural network algorithms even with small samples which showed that this method had significant advantages in the application of gesture recognition.…”
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Distributed trust model based on parameter modeling by Jing-pei WANG, Bin SUN, Xin-xin NIU, Yi-xian YANG

“…A distributed trust model based on parameter modeling was posed.Nine functional parameters were extracted after investigating the trust mechanism and current trust models.These parameters included flexibility,subjectivity,fuzziness,time decay property,transitivity,anti-attacks property,rewards ＆amp; punishment property,sensitivity and scalability.Each parameter was modeled and integrated to form a comprehensive trust model.Analytical results indicate that the proposed trust model satisfies all the nine functional parameters and thus has fair universality Experimental results show that the proposed trust model is reasonable and effective.Comparisons with previous algorithms indicate that the performance of the proposed trust model has been improved.…”
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ANALYSIS OF CELLULAR REACTION TO IFN-γ STIMULATION BY A SOFTWARE PACKAGE GeneExpressionAnalyser by A. V. Saetchnikov, M. M. Yatskou, P. V. Nazarov, L. Vallar, V. V. Apanasovich

“…The software package GeneExpressionAnalyser for analysis of the DNA microarray experi-mental data has been developed. The algorithms of data analysis, differentially expressed genes and biological functions of the cell are described. …”
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Integrating Radar-Based Obstacle Detection with Deep Reinforcement Learning for Robust Autonomous Navigation by Nabih Pico, Estrella Montero, Maykoll Vanegas, Jose Miguel Erazo Ayon, Eugene Auh, Jiyou Shin, Myeongyun Doh, Sang-Hyeon Park, Hyungpil Moon

“…Using filtering and tracking algorithms, the proposed system leverages radar sensors to cluster object points and track dynamic obstacles, enhancing precision by reducing noise and fluctuations. …”
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Exploring QSAR for Antimalarial Activities and Drug Distribution within Blood of a Series of 4-Aminoquinoline Drugs Using Genetic-MLR by Amir Najafi, Soheil Sobhanardakani, Mehdi Marjani

“…QSAR modeling of the antimalarial activity and blood-to-plasma concentration ratio of Chloroquine and a new series of 4-aminoquinoline derivatives were developed using genetic algorithms with multiple linear regression (GA-MLR) method. …”
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A Primer for Disease Gene Prioritization Using Next-Generation Sequencing Data by Shuoguo Wang, Jinchuan Xing

“…The recent development of many computational algorithms and programs has vastly improved the ability to translate sequence data into valuable information for disease gene identification. …”
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Identifying Smart Strategies for Effective Agriculture Solution Using Data Mining Techniques by Anthony Jesus Bustamante Suarez, Barjinder Singh, Firas Husham Almukhtar, Rajnish Kler, Sonali Vyas, Karthikeyan Kaliyaperumal

“…Use of the CART and random forest algorithms is a data mining technique that may be used to various datasets. …”
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Taking into account the lens geometric distortion during accumulation of blurred star images in an astro-inertial attitude sensor by S. N. Vasilyuk

“…This approach makes it possible to preserve the structure of the subpixel accumulation and star detection algorithms previously obtained for an ideal image. An example of allowing for the radial distortion parameters obtained by calibrating a real camera is given.…”
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Surface Approximation using Growing Self-Organizing Nets and Gradient Information by Jorge Rivera-Rovelo, Eduardo Bayro-Corrochano

“…Also, we show that in the adaptation stage the network utilizes efficient transformations, expressed as versors in the conformal geometric algebra framework, which build the shape of the object independent of its position in space (coordinate free). Our algorithms were tested with several images, including medical images (CT and MR images). …”
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A Survey of Datacenter and Optical Data Center Networks by Esraa Ali Abdulmahdi Abdul Mahdi, Ali Al-Askery, Adnan Hussein Ali, Safiye Ghasemi

“…Finally, we make a comprehensive between some related works with an analysis of the algorithmic challenges faced by these technologies. …”
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A New Legendre Spectral Galerkin and Pseudo-Spectral Approximations for Fractional Initial Value Problems by A. H. Bhrawy, M. A. Alghamdi

“…Illustrative examples are presented to ensure the high accuracy and effectiveness of the proposed algorithms are discussed.…”
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Machine Learning Approaches to Natural Fiber Composites: A Review of Methodologies and Applications by Sivasubramanian Palanisamy, Nadir Ayrilmis, Kumar Sureshkumar, Carlo Santulli, Tabrej Khan, Harri Junaedi, Tamer Ali Sebaey

“…This work elucidates the functions of the types and applications of the ML algorithms and evolutionary computing techniques, with a particular focus on their applicability within the domain of NFCs. …”
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