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

Cybersecurity involves protecting computer networks, systems, and data from unauthorized access and disruptions using advanced technologies. The purpose of this research is to establish a novel cyber security framework for strengthening cloud data protection. In this paper, we propose a novel Dung Beetle optimization-redefined Intelligent Random Forest (DB-IRF) for accurate detection of intrusions in a cloud environment. We obtained a dataset that includes cloud system logs and network traffic data, including normal and malicious activities, to train our proposed model. We utilized z-score normalization to pre-process the gathered raw data. Our suggested model enhances classification accuracy by integrating DB optimization with the

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

Voting is one of the most fundamental components of a democratic society. In 2021 Iraq held the Council of Representatives (CoR) elections in 83 electoral constituencies in 19 governorates. Nonetheless, several significant issues arose during this election, including the problem of logistics distribution, the excessively long period of ballot counting, voters can't know if their votes were counted or if their ballots were tampered with, and the inconsistent regulation of vote counting. Blockchain technology, which was just invented, may offer a solution to these problems. This paper introduces an electronic voting system for the Iraq Council of Representatives elections that is based on a prototype of the permission hyperledger fabr

Copper with different concentrations doped with zinc oxide nanoparticles were prepared from a mixture of zinc acetate and copper acetate with sodium hydroxide in aqueous solution. The structure of the prepared samples was done by X-ray diffraction, atomic force microscopy (AFM) and UV-VIS absorption spectrophotometer. Debye-Scherer formula was used to calculate the size of the prepared samples. The band gap of the nanoparticle ZnO was determined by using UV-VIS optical spectroscopy.

In search of novel antibacterial agent, a series of new isatin derivatives (3a-d) have been synthesized by condensation isatin (2,3-indolinendione) with piperidine (hexahydropyridine), hydrazine hydrate and Boc-amino acids respectively. Compounds synthesized have been characterized by IR spectroscopy and elemental analysis. In addition, the in vitro antibacterial properties have been tested against E. coli, P. aeruginosa, and Bacillus cereus, S. aureus by employing the well diffusion technique. A majority of the synthesized compounds were showing good antibacterial activity and from comparisons of the compounds, compound 3d has been determined to be the most active compound.

The present investigation developed the ester prodrugs of Non-steroidal anti inflammatory drugs (NSAIDs), Mefenamic acid and Flurbiprofen by conjugating with the natural antioxidant, 4-methyl umbelliferone that resulted the formation of Mefenamic acid-umbelliferone ester prodrug and Flurbiprofen-umbelliferone ester prodrug .The principal objective this study is the synthesis of the ester prodrugs of NSAIDs with the enhanced therapeutic activity and minimized side effects. Prodrugs were synthesized by coupling method using N,N^’- dicyclohexylcarbodiimide/4-dimethylaminopyrimidine, subjected to  physical, chemical characterization, spectral characterization (IR, ¹H NMR, ¹³C NMR and Mass spectra),hydro