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Search Results (13)
  • Open Access

    ARTICLE

    Floating Waste Discovery by Request via Object-Centric Learning

    Bingfei Fu*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1407-1424, 2024, DOI:10.32604/cmc.2024.052656

    Abstract Discovering floating wastes, especially bottles on water, is a crucial research problem in environmental hygiene. Nevertheless, real-world applications often face challenges such as interference from irrelevant objects and the high cost associated with data collection. Consequently, devising algorithms capable of accurately localizing specific objects within a scene in scenarios where annotated data is limited remains a formidable challenge. To solve this problem, this paper proposes an object discovery by request problem setting and a corresponding algorithmic framework. The proposed problem setting aims to identify specified objects in scenes, and the associated algorithmic framework comprises pseudo… More >

  • Open Access

    ARTICLE

    A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

    Elif Varol Altay, Osman Altay, Yusuf Özçevik*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 1039-1094, 2024, DOI:10.32604/cmes.2023.029404

    Abstract Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve. Such design problems are widely experienced in many engineering fields, such as industry, automotive, construction, machinery, and interdisciplinary research. However, there are established optimization techniques that have shown effectiveness in addressing these types of issues. This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues. The algorithms used in the study are listed as: transient search optimization (TSO), equilibrium optimizer (EO), grey wolf optimizer… More >

  • Open Access

    ARTICLE

    Retrospective Analysis of Postprandial Glucose-Response Data Collected in a Free-Living Environment

    Colleen Crangle1,2,*, Bude Piccin2, Lara Hyde3, Elin Östman4

    Journal of Intelligent Medicine and Healthcare, Vol.1, No.2, pp. 91-102, 2022, DOI:10.32604/jimh.2022.038379

    Abstract Postprandial glucose responses provide vital information on an individual’s risk of major diet-related chronic diseases. This study features digital health technology, namely Continuous Glucose Monitoring (CGM) sensors, along with mobile devices (iPhones running an app) used to collect data from individuals and their environment, specifically nutritional information on what they eat and drink. The paper presents a retrospective analysis of data collected during an investigation into the use of a functional drink taken as a supplement with a standardized meal to reduce postprandial responses to that meal. Given that there are consequential differences between individuals… More >

  • Open Access

    ARTICLE

    New Trends in the Modeling of Diseases Through Computational Techniques

    Nesreen Althobaiti1, Ali Raza2,*, Arooj Nasir3,4, Jan Awrejcewicz5, Muhammad Rafiq6, Nauman Ahmed7, Witold Pawłowski8, Muhammad Jawaz7, Emad E. Mahmoud1

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2935-2951, 2023, DOI:10.32604/csse.2023.033935

    Abstract The computational techniques are a set of novel problem-solving methodologies that have attracted wider attention for their excellent performance. The handling strategies of real-world problems are artificial neural networks (ANN), evolutionary computing (EC), and many more. An estimated fifty thousand to ninety thousand new leishmaniasis cases occur annually, with only 25% to 45% reported to the World Health Organization (WHO). It remains one of the top parasitic diseases with outbreak and mortality potential. In 2020, more than ninety percent of new cases reported to World Health Organization (WHO) occurred in ten countries: Brazil, China, Ethiopia,… More >

  • Open Access

    ARTICLE

    Data-Driven Load Forecasting Using Machine Learning and Meteorological Data

    Aishah Alrashidi, Ali Mustafa Qamar*

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1973-1988, 2023, DOI:10.32604/csse.2023.024633

    Abstract Electrical load forecasting is very crucial for electrical power systems’ planning and operation. Both electrical buildings’ load demand and meteorological datasets may contain hidden patterns that are required to be investigated and studied to show their potential impact on load forecasting. The meteorological data are analyzed in this study through different data mining techniques aiming to predict the electrical load demand of a factory located in Riyadh, Saudi Arabia. The factory load and meteorological data used in this study are recorded hourly between 2016 and 2017. These data are provided by King Abdullah City for… More >

  • Open Access

    ARTICLE

    Vinorelbine in Non-Small Cell Lung Cancer: Real-World Data From a Single-Institution Experience

    Stefania Nobili*, Daniele Lavacchi, Gabriele Perrone*, Giulio Vicini, Renato Tassi‡1, Ida Landini*, AnnaMaria Grosso§, Giandomenico Roviello, Roberto Mazzanti, Carmine Santomaggio¶2, Enrico Mini

    Oncology Research, Vol.28, No.3, pp. 237-248, 2020, DOI:10.3727/096504019X15755437099308

    Abstract The use of vinorelbine as a single agent or in combination regimens in non-small cell lung cancer (NSCLC) is associated with satisfactory clinical activity. However, the role of vinorelbine-based chemotherapy in chemonaive locally advanced unresectable or metastatic NSCLC patients, according to real-world treatment patterns, has still not been widely explored. Eighty-one patients treated at a single institution were retrospectively analyzed. Thirty-seven received standard first-line single-agent vinorelbine, and 44 received vinorelbine plus platinum drugs, based on physician’s choice; 61.7% were older than 70 years, and 60.5% were affected by 2 comorbidities. Sixty-three patients were evaluable for… More >

  • Open Access

    ARTICLE

    Real-World Data: Fruquintinib in Treating Metastatic Colorectal Cancer

    Shuai Liu*†1, Lu Lu*†1, Feng Pan, Chunsheng Yang*†, Jing Liang§, Jinfeng Liu, Jian Wang#, Rong Shen**, Fu-Ze Xin††, Nan Zhang*†

    Oncology Research, Vol.29, No.1, pp. 25-31, 2021, DOI:10.3727/096504022X16427607626672

    Abstract Fruquintinib, also called HMPL-013, was first discovered by Hutchison Whampoa Pharmaceuticals Co. Ltd., Shanghai, China, and it is an oral vascular endothelial growth factor receptor (VEGFR) inhibitor. In clinical trials, fruquintinib has demonstrated a survival benefit in metastatic colorectal cancer (mCRC) patients. The purpose of this study was to retrospectively evaluate the efficacy and toxicity of fruquintinib in real-world patients. We collected data from patients with mCRC treated with oral fruquintinib from 2018 to 2020 in six different institutions. Patients with mCRC initially received 5 mg of oral fruquintinib daily for 3 weeks. Progression-free survival… More >

  • Open Access

    ARTICLE

    A Real-World Study on Oral Vinorelbine for the Treatment of Metastatic Breast Cancer

    Jiayi Huang1, Xue Bai1, Xiaofeng Xie1, Liping Chen1, Xiaofeng Lan1, Qiuyi Zhang1, Lin Song1, Pengjiao Hong2,3, Caiwen Du1,*

    Oncologie, Vol.24, No.1, pp. 131-145, 2022, DOI:10.32604/oncologie.2022.019881

    Abstract Background: Vinorelbine can be used to treat metastatic breast cancer as a single agent or in combination with other chemotherapy agents, although there is little real-world data for its use, particularly the oral form, in China. The current study aimed to explore the efficacy and safety of oral vinorelbine in patients with metastatic breast cancer in real-world clinical practice. Methods: A total of 194 patients with metastatic breast cancer received oral vinorelbine as a treatment between February 2017 and January 2021 at the National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese… More >

  • Open Access

    ARTICLE

    Computational Approximations for Real-World Application of Epidemic Model

    Shami A. M. Alsallami1, Ali Raza2,*, Mona Elmahi3, Muhammad Rafiq4, Shamas Bilal5, Nauman Ahmed6, Emad E. Mahmoud7

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1923-1939, 2022, DOI:10.32604/iasc.2022.024993

    Abstract The real-world applications and analysis have a significant role in the scientific literature. For instance, mathematical modeling, computer graphics, camera, operating system, Java, disk encryption, web, streaming, and many more are the applications of real-world problems. In this case, we consider disease modeling and its computational treatment. Computational approximations have a significant role in different sciences such as behavioral, social, physical, and biological sciences. But the well-known techniques that are widely used in the literature have many problems. These methods are not consistent with the physical nature and even violate the actual behavior of the… More >

  • Open Access

    ARTICLE

    Effective Frameworks Based on Infinite Mixture Model for Real-World Applications

    Norah Saleh Alghamdi1, Sami Bourouis2,*, Nizar Bouguila3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1139-1156, 2022, DOI:10.32604/cmc.2022.022959

    Abstract Interest in automated data classification and identification systems has increased over the past years in conjunction with the high demand for artificial intelligence and security applications. In particular, recognizing human activities with accurate results have become a topic of high interest. Although the current tools have reached remarkable successes, it is still a challenging problem due to various uncontrolled environments and conditions. In this paper two statistical frameworks based on nonparametric hierarchical Bayesian models and Gamma distribution are proposed to solve some real-world applications. In particular, two nonparametric hierarchical Bayesian models based on Dirichlet process… More >

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