Modified unsaturated polyester (MUPE) was blended with Cellulose (Cls) and with ethyl cellulose (ECls) at ambient conditions in the presence of ethyl methyl ketone peroxide (EMKP) as hardener. The blends containing different weight percentages (5-25 %) of Cls or ECls. Mechanical properties (impact strength, hardness, and bending) and dielectric constant were determined. The results observed that Cls increases the impact strength, hardness, and dielectric constant and decreases the bending of the MUPS, while ECls causes an increase in the three mechanical behaviours and a decrease in the dielectric constant of the MU-PS.

Students’ feedback is crucial for educational institutions to assess the performance of their teachers, most opinions are expressed in their native language, especially for people in south Asian regions. In Pakistan, people use Roman Urdu to express their reviews, and this applied in the education domain where students used Roman Urdu to express their feedback. It is very time-consuming and labor-intensive process to handle qualitative opinions manually. Additionally, it can be difficult to determine sentence semantics in a text that is written in a colloquial style like Roman Urdu. This study proposes an enhanced word embedding technique and investigates the neural word Embedding (Word2Vec and Glove) to determine which perfo

This study presents the debonding propagation in single NiTi wire shape memory alloy into linear low-density polyethylene matrix composite the study of using the pull-out test. The aim of this study is to investigate the pull-out tests to check the interfacial strength of the polymer composite in two cases, with activation NiTinol wire and without activation. In this study, shape memory alloy NiTinol wire 2 mm diameter and linear fully annealed straight shape were used. The study involved experimental and finite element analysis and eventually comparison between them. This pull-out test is considered a substantial test because its results have a relation with behavior of smart composite materials. The pull-out test was carried out by a u

يعتقد البعض ان مفهوم العلم يعني الآلات والاجهزة العلمية (تقنيات التعليم) وهي لا تختلف عن مفهوم تكنولوجيا المعلومات , ويعد هذا الاعتقاد خاطئ , لان العلم هو بناء المعرفة العلمية المنظمة والتي يتم التوصل اليها عن طريق البحث العلمي , اما تكنولوجيا المعلومات فهي "التطبيقات العملية للمعرفة العلمية في مختلف المجالات ذات الفائدة المباشرة بحياة الانسان, او هي النواحي التطبيقية للعلم وما يرتبط بها من آلات واجهزة".

 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

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

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet