Ala’a R. Al-Shamasneh¹, Rabha W. Ibrahim^2,3,4,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.042755

Abstract The growing prevalence of fake images on the Internet and social media makes image integrity verification a crucial research topic. One of the most popular methods for manipulating digital images is image splicing, which involves copying a specific area from one image and pasting it into another. Attempts were made to mitigate the effects of image splicing, which continues to be a significant research challenge. This study proposes a new splicing detection model, combining Sonine functions-derived convex-based features and deep features. Two stages make up the proposed method. The first step entails feature extraction, then classification using the “support vector… More >

Hyun Kwon^1,*, Sanghyun Lee²

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.042466

Abstract Deep neural networks perform well in image recognition, object recognition, pattern analysis, and speech recognition. In military applications, deep neural networks can detect equipment and recognize objects. In military equipment, it is necessary to detect and recognize rifle management, which is an important piece of equipment, using deep neural networks. There have been no previous studies on the detection of real rifle numbers using real rifle image datasets. In this study, we propose a method for detecting and recognizing rifle numbers when rifle image data are insufficient. The proposed method was designed to improve the recognition rate of a specific… More >

Arslan Akram^1,2, Imran Khan¹, Javed Rashid^2,3, Mubbashar Saddique^4,*, Muhammad Idrees⁴, Yazeed Yasin Ghadi⁵, Abdulmohsen Algarni⁶

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.040512

Abstract Algorithms for steganography are methods of hiding data transfers in media files. Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial information, and these methods have made it feasible to handle a wide range of problems associated with image analysis. Images with little information or low payload are used by information embedding methods, but the goal of all contemporary research is to employ high-payload images for classification. To address the need for both low- and high-payload images, this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to… More >

Muhammad Rizwan^1,2, Muhammad Faheem Mushtaq¹, Maryam Rafiq², Arif Mehmood³, Isabel de la Torre Diez⁴, Monica Gracia Villar^5,6,7, Helena Garay^5,8,9, Imran Ashraf^10,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.037347

Abstract Predicting depression intensity from microblogs and social media posts has numerous benefits and applications, including predicting early psychological disorders and stress in individuals or the general public. A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media text. This study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter… More >

TIANKAI DI^1,2,#, ZHIFEI ZHOU^3,#, FEN LIU^4,#, YUJIANG CHEN^5,*, LULU WANG^1,*

BIOCELL, Vol., , DOI:10.32604/biocell.2023.031638

Abstract Autophagy is a widespread biological process that controls cellular growth, survival, development, and death. Circadian rhythm is a recurring reaction of living organisms and behaviors to variations in surrounding brightness and obscurity. Most of the fundamental physiological processes in mammals, such as the sleep-wake pattern and the rhythm of nutrition and energy metabolism, are governed by circadian rhythms. Research has indicated that autophagy exhibits a specific circadian pattern in both normal and abnormal conditions. Autophagy can modulate circadian rhythms by breaking down proteins that regulate the circadian clock. The potential regulatory connection between the two has been a popular subject… More >

JINNI MA^#, MEILIN ZHOU^#, XIN XU, XINYAO GAO, HAIXIA WANG, JINHUA SHEN, LU XUE^*

BIOCELL, Vol., , DOI:10.32604/biocell.2023.045076

Abstract Background: Placenta specific 8 (PLAC8) is a candidate oncogene involved in the development and progression of solid tumors. However, the status of PLAC8 in lung cancer (LC), especially non-small cell lung cancer (NSCLC) is still not lucid. Methods: Tissue microarray analysis (TMA) was performed to detect the expression patterns of PLAC8 in LC tissues and cell lines. Then a series of cellular experiments were performed fto assess cell proliferation, cell cycle profiles, and cell motility to explore the role of PLAC8 in NSCLC-derived cell lines: H1299 and A549. Results: TMA results showed that PLAC8 played complex and even contradictory roles… More >

MONA S. ABDELLATEIF^1,*, NAGLAA M. HASSAN², MAHMOUD M. KAMEL², YOMNA M. EL-MELIGUI²

Oncology Research, Vol., , DOI:10.32604/or.2023.043026

Abstract Background: microRNA-34a (miR-34a) had been reported to have a diagnostic role in acute myeloid leukemia (AML). However, its value in the bone marrow (BM) of AML patients, in addition to its role in response to therapy is still unclear. The current study was designed to assess the diagnostic, prognostic, and predictive significance of miR-34a in the BM of AML patients. Methods: The miR-34a was assessed in BM aspirate of 82 AML patients in relation to 12 normal control subjects using qRT-PCR. The data were assessed for correlation with the relevant clinical criteria, response to therapy, disease-free survival (DFS), and overall… More >

Muhammad Ali, Minhaj Ahmad Khan^*

Computer Systems Science and Engineering, Vol., , DOI:10.32604/csse.2023.043010

Abstract The Extensible Markup Language (XML) files, widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the applications. With the existing Document Object Model (DOM) based parsing, the performance degrades due to sequential processing and large memory requirements, thereby requiring an efficient XML parser to mitigate these issues. In this paper, we propose a Parallel XML Tree Generator (PXTG) algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework (RXPF) that analyzes and predicts performance through profiling, regression, and code generation for efficient parsing. The PXTG algorithm… More >

Shujiang Xu^1,2,*, Ziye Wang^1,2, Lianhai Wang^1,2, Miodrag J. Mihaljević^1,2,3, Shuhui Zhang^1,2, Wei Shao^1,2, Qizheng Wang^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.046164

Abstract Blockchain technology, with its attributes of decentralization, immutability, and traceability, has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business processes. However, transaction performance and scalability has become the main challenges hindering the widespread adoption of blockchain. Due to its inability to meet the demands of high-frequency trading, blockchain cannot be adopted in many scenarios. To improve the transaction capacity, researchers have proposed some on-chain scaling technologies, including lightning networks, directed acyclic graph technology, state channels, and sharding mechanisms, in which sharding emerges as a potential scaling technology. Nevertheless, excessive cross-shard transactions and uneven shard… More > Graphic Abstract

Yu Cheng^1,2,5, Yajun Huang³, Shuai Li⁴, Zhongbin Zhou⁵, Xiaohui Yuan^1,2,*, Yanming Xu^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.045668

Abstract A new approach for flexoelectric material shape optimization is proposed in this study. In this work, a proxy model based on artificial neural network (ANN) is used to solve the parameter optimization and shape optimization problems. To improve the fitting ability of the neural network, we use the idea of pre-training to determine the structure of the neural network and combine different optimizers for training. The isogeometric analysis-finite element method (IGA-FEM) is used to discretize the flexural theoretical formulas and obtain samples, which helps ANN to build a proxy model from the model shape to the target value. The effectiveness… More >