APDBN Rashid, International Journal of Humanities and Social Sciences/ RIMAK, 2023

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

     A hybrid cadmium sulfide nanoparticles (CdSNPs) electroluminescence (EL) device was fabricated by Phase – Segregated Method and characterized. It was fabricated as layers of (ITO/poly-TPD:CdS ) and (ITO/poly-TPD:CdS /Alq3). Poly-TPD is an excellent Hole Transport Layer (HTL), CdSNPs is an emitting layer and Alq3 as electron transport layer (ETL). The EL of Organic-Inorganic Light Emitting Diode (OILED) was studied at room temperature at 26V. This was achieved according to band-to-band transition in CdSNPs. From the I-V curve behavior, the addition of Alq3 layer decreased the transfer of electrons by about 250 times. The I-V behavior for (poly-TPD/CdS) is exponential with a maximum current of 4500 µA. While, the current i

An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

The aim of the current study is to identify the level of goal conflict with twelfth-grade students in South Sharqiah/ Sultanate of Oman according to gender and specialization. The study used the descriptive method. A scale of (28) items was developed and divided into six dimensions: time pressure, goal achievement, limit of power, limit of budget, incompatible strategies, and unclear task. To validate the scale, it was piloted (40) students. The scale was administered to a sample of (402) students (209) males in the Governorate of South Sharqiah. The results showed that the conflict level was high in “unclear task”, and an average conflict level in “limit of power”. Other dimensions (goal achievement, time pressure, limit of powe

Abstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to

The increased size of grayscale images or upscale plays a central role in various fields such as medicine, satellite imagery, and photography. This paper presents a technique for improving upscaling gray images using a new mixing wavelet generation by tensor product. The proposed technique employs a multi-resolution analysis provided by a new mixing wavelet transform algorithm to decompose the input image into different frequency components. After processing, the low-resolution input image is effectively transformed into a higher-resolution representation by adding a zeroes matrix. Discrete wavelets transform (Daubechies wavelet Haar) as a 2D matrix is used but is mixed using tensor product with another wavelet matrix’s size. MATLAB R2021

One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are genera

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye