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  • Open Access

    ARTICLE

    Analysis of Social Media Impact on Stock Price Movements Using Machine Learning Anomaly Detection

    Richard Cruz1, Johnson Kinyua1,*, Charles Mutigwe2

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3405-3423, 2023, DOI:10.32604/iasc.2023.035906 - 15 March 2023

    Abstract The massive increase in the volume of data generated by individuals on social media microblog platforms such as Twitter and Reddit every day offers researchers unique opportunities to analyze financial markets from new perspectives. The meme stock mania of 2021 brought together stock traders and investors that were also active on social media. This mania was in good part driven by retail investors’ discussions on investment strategies that occurred on social media platforms such as Reddit during the COVID-19 lockdowns. The stock trades by these retail investors were then executed using services like Robinhood. In… More >

  • Open Access

    ARTICLE

    Ensemble Voting-Based Anomaly Detection for a Smart Grid Communication Infrastructure

    Hend Alshede1,2,*, Laila Nassef1, Nahed Alowidi1, Etimad Fadel1

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3257-3278, 2023, DOI:10.32604/iasc.2023.035874 - 15 March 2023

    Abstract Advanced Metering Infrastructure (AMI) is the metering network of the smart grid that enables bidirectional communications between each consumer’s premises and the provider’s control center. The massive amount of data collected supports the real-time decision-making required for diverse applications. The communication infrastructure relies on different network types, including the Internet. This makes the infrastructure vulnerable to various attacks, which could compromise security or have devastating effects. However, traditional machine learning solutions cannot adapt to the increasing complexity and diversity of attacks. The objective of this paper is to develop an Anomaly Detection System (ADS) based… More >

  • Open Access

    ARTICLE

    Segmentation Based Real Time Anomaly Detection and Tracking Model for Pedestrian Walkways

    B. Sophia1,*, D. Chitra2

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2491-2504, 2023, DOI:10.32604/iasc.2023.029799 - 15 March 2023

    Abstract Presently, video surveillance is commonly employed to ensure security in public places such as traffic signals, malls, railway stations, etc. A major challenge in video surveillance is the identification of anomalies that exist in it such as crimes, thefts, and so on. Besides, the anomaly detection in pedestrian walkways has gained significant attention among the computer vision communities to enhance pedestrian safety. The recent advances of Deep Learning (DL) models have received considerable attention in different processes such as object detection, image classification, etc. In this aspect, this article designs a new Panoptic Feature Pyramid… More >

  • Open Access

    ARTICLE

    Anomaly Detection of UAV State Data Based on Single-Class Triangular Global Alignment Kernel Extreme Learning Machine

    Feisha Hu1, Qi Wang1,*, Haijian Shao1,2, Shang Gao1, Hualong Yu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2405-2424, 2023, DOI:10.32604/cmes.2023.026732 - 09 March 2023

    Abstract Unmanned Aerial Vehicles (UAVs) are widely used and meet many demands in military and civilian fields. With the continuous enrichment and extensive expansion of application scenarios, the safety of UAVs is constantly being challenged. To address this challenge, we propose algorithms to detect anomalous data collected from drones to improve drone safety. We deployed a one-class kernel extreme learning machine (OCKELM) to detect anomalies in drone data. By default, OCKELM uses the radial basis (RBF) kernel function as the kernel function of the model. To improve the performance of OCKELM, we choose a Triangular Global More > Graphic Abstract

    Anomaly Detection of UAV State Data Based on Single-Class Triangular Global Alignment Kernel Extreme Learning Machine

  • Open Access

    ARTICLE

    In vitro polymerization of the dopamine-borate melanin precursor: A proof-of-concept regarding boron neutron-capture therapy for melanoma

    JUAN C. STOCKERT1,2,*, SILVINA A. ROMERO1, MARCELO N. FELIX-POZZI3, ALFONSO BLÁZQUEZ-CASTRO4

    BIOCELL, Vol.47, No.4, pp. 919-928, 2023, DOI:10.32604/biocell.2023.026631 - 08 March 2023

    Abstract

    The 10boron neutron-capture therapy (BNCT) is an emerging antitumoral method that shows increasing biomedical interest. BNCT is based on the selective accumulation of the 10boron isotope within the tumor, which is then irradiated with low-energy thermal neutrons, generating nuclear fission that produces 7lithium, 4helium, and γ rays. Simple catechol-borate esters have been rather overlooked as precursors of melanin biosynthesis, and therefore, a proof-of-concept approach for using dopamine-borate (DABO) as a suitable boron-containing candidate for potential BNCT is presented here. DABO can spontaneously oxidize and autopolymerize in vitro, giving a soluble, eumelanin-like brown-black poly-DABO product. Melanotic melanoma cell cultures treated

    More >

  • Open Access

    VIEWPOINT

    Junctional adhesion molecule-A (JAM-A) in gynecological cancers: Current state of knowledge

    KAMILA CZUBAK-PROWIZOR*, MARIA SWIATKOWSKA

    BIOCELL, Vol.47, No.4, pp. 731-737, 2023, DOI:10.32604/biocell.2023.025677 - 08 March 2023

    Abstract Junctional adhesion molecule-A (JAM-A), also known as the F11 receptor (F11R), is one of the tight junction components. JAM-A is a transmembrane glycoprotein that regulates many cellular processes, i.e., angiogenesis, leukocyte transendothelial migration, intercellular permeability, epithelial-to-mesenchymal transition, and platelet activation. Of note, it is involved in the pathogenesis of various cancer types, including gynecological cancers. Only a few studies are available about this cancer type. Observed aberrant JAM-A expression in gynecological cancers correlates with poor patient prognosis. To the best of our knowledge, conflicting JAM-A roles in various cancer types suggest that its involvement is More >

  • Open Access

    ARTICLE

    Thioredoxin domain-containing protein 9 protects cells against UV-B-provoked apoptosis via NF-κB/p65 activation in cutaneous squamous cell carcinoma

    ZHIXUN XIAO1, QIUYUN XU1, HAIQING WANG1, XIAOTONG ZHOU2, YANTING ZHU1, CHENGBEI BAO1, LIHONG CHEN1, PENG ZHANG1, MIN LIN1, CHAO JI1,*, TING GONG3,*

    Oncology Research, Vol.31, No.1, pp. 71-82, 2023, DOI:10.32604/or.2022.028075 - 01 March 2023

    Abstract Cutaneous squamous cell carcinoma (cSCC), a type of non-melanoma skin cancer (NMSC), is the most common malignancy worldwide. Thioredoxin (TXN) domain-containing protein 9 (TXNDC9) is a member of the TXN family that is important in cell differentiation. However, the biological function of this protein in cancer, particularly cSCC, is still unknown. In the present study, our experiments revealed the protective effects of TXNDC9 on UV-B-irritated cSCC cells. The initial findings showed that TXNDC9 is significantly upregulated in cSCC tissue and cells compared to normal skin tissue and keratinocytes. UV-B radiation robustly induces the expression of More >

  • Open Access

    ARTICLE

    Identification and verification of aging-related lncRNAs for prognosis prediction and immune microenvironment in patients with head and neck squamous carcinoma

    QING GAO1,#, YUJING SHI2,#, YUANYUAN SUN1,#, SHU ZHOU1, ZEYUAN LIU3, XINCHEN SUN1,*, XIAOKE DI1,*

    Oncology Research, Vol.31, No.1, pp. 35-61, 2023, DOI:10.32604/or.2022.028193 - 01 March 2023

    Abstract Aging is highly associated with tumor formation and progression. However, little research has explored the association of aging-related lncRNAs (ARLs) with the prognosis and tumor immune microenvironment (TIME) of head and neck squamous cell carcinoma (HNSCC). RNA sequences and clinicopathological data of HNSCC patients and normal subjects were downloaded from The Cancer Genome Atlas. In the training group, we used Pearson correlation, univariate Cox regression, least absolute shrinkage/selection operator regression analyses, and multivariate Cox regression to build a prognostic model. In the test group, we evaluated the model. Multivariate Cox regression was done to screen… More >

  • Open Access

    ARTICLE

    Quantum Computing Based Neural Networks for Anomaly Classification in Real-Time Surveillance Videos

    MD. Yasar Arafath1,*, A. Niranjil Kumar2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2489-2508, 2023, DOI:10.32604/csse.2023.035732 - 09 February 2023

    Abstract For intelligent surveillance videos, anomaly detection is extremely important. Deep learning algorithms have been popular for evaluating real-time surveillance recordings, like traffic accidents, and criminal or unlawful incidents such as suicide attempts. Nevertheless, Deep learning methods for classification, like convolutional neural networks, necessitate a lot of computing power. Quantum computing is a branch of technology that solves abnormal and complex problems using quantum mechanics. As a result, the focus of this research is on developing a hybrid quantum computing model which is based on deep learning. This research develops a Quantum Computing-based Convolutional Neural Network… More >

  • Open Access

    ARTICLE

    Aquila Optimization with Machine Learning-Based Anomaly Detection Technique in Cyber-Physical Systems

    A. Ramachandran1,*, K. Gayathri2, Ahmed Alkhayyat3, Rami Q. Malik4

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2177-2194, 2023, DOI:10.32604/csse.2023.034438 - 09 February 2023

    Abstract Cyber-physical system (CPS) is a concept that integrates every computer-driven system interacting closely with its physical environment. Internet-of-things (IoT) is a union of devices and technologies that provide universal interconnection mechanisms between the physical and digital worlds. Since the complexity level of the CPS increases, an adversary attack becomes possible in several ways. Assuring security is a vital aspect of the CPS environment. Due to the massive surge in the data size, the design of anomaly detection techniques becomes a challenging issue, and domain-specific knowledge can be applied to resolve it. This article develops an… More >

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