Diamond-like carbon, amorphous hydrogenated films forms of carbon, were pretreated from cyclohexane (C6H12) liquid using plasma jet which operates with alternating voltage 7.5kv and frequency 28kHz. The plasma Separates molecules of cyclohexane and Transform it into carbon nanoparticles. The effect of argon flow rate (0.5, 1 and 1.5 L/min) on the optical and chemical bonding properties of the films were investigated. These films were characterized by UV-Visible spectrophotometer, X-ray diffractometer (XRD) Raman spectroscopy and scanning electron microscopy (SEM). The main absorption appears around 296, 299 and 309nm at the three flow rate of argon gas. The value of the optical energy gap is 3.37, 3.55 and 3.68 eV at a different flow rate o

This paper presents a proposed method for (CBIR) from using Discrete Cosine Transform with Kekre Wavelet Transform (DCT/KWT), and Daubechies Wavelet Transform with Kekre Wavelet Transform (D4/KWT) to extract features for Distributed Database system where clients/server as a Star topology, client send the query image and server (which has the database) make all the work and then send the retrieval images to the client. A comparison between these two approaches: first DCT compare with DCT/KWT and second D4 compare with D4/KWT are made. The work experimented over the image database of 200 images of 4 categories and the performance of image retrieval with respect to two similarity measures namely Euclidian distance (ED) and sum of absolute diff

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

This article aims to provide a bibliometric analysis of intellectual capital research published in the Scopus database from 1956 to 2020 to trace the development of scientific activities that can pave the way for future studies by shedding light on the gaps in the field. The analysis focuses on 638 intellectual capital-related papers published in the Scopus database over 60 years, drawing upon a bibliometric analysis using VOSviewer. This paper highlights the mainstream of the current research in the intellectual capital field, based on the Scopus database, by presenting a detailed bibliometric analysis of the trend and development of intellectual capital research in the past six decades, including journals, authors, countries, inst

With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

In the digital age, protecting intellectual property and sensitive information against unauthorized access is of paramount importance. While encryption helps keep data private and steganography hides the fact that data are present, using both together makes the security much stronger. This paper introduces a new way to hide encrypted text inside color images by integrating discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD), along with AES-GCM encryption, to guarantee data integrity and authenticity. The proposed method operates in the YCbCr color space, targeting the luminance (Y) channel to preserve perceptual quality. Embedding is performed within the HL subband obtained from DWT deco

This review investigates the practice and influence of chatbots and ChatGPT as employable tools in writing for scientific academic purposes. A primary collection of 150 articles was gathered from academic databases, but it was systematically chosen and refined to include 30 studies that focused on the use of ChatGPT and chatbot technology in academic writing contexts. Chatbots and ChatGPT in writing enhancement, support for student learning at higher education institutions, scientific and medical writing, and the evolution of research and academic publishing are some of the topics covered in the reviewed literature. The review finds these tools helpful, with their greatest advantages being in areas such as structuring writings, gram