This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substantial improvement of 59.90% is observed for data files sized at 1500000kb. Partitioning larger files notably reduces encryption time, while smaller files experience marginal benefits. Certain file types benefit from both strategies. Evaluation metrics include encryption execution time and throughput, consistently demonstrating ERC5's superiority over the original RC5. Moreover, ERC5 exhibits reduced power consumption and heightened throughput, highlighting its multifaceted benefits in resource-constrained environments. ERC5 is developed and tested on various file types and sizes to evaluate encryption speed, power consumption, and throughput. ERC5 significantly improves encryption speed across different file types and sizes, with notable gains for audio, image, and large data files. While partitioning smaller files only slightly improves encryption time, larger files partitioning yields faster results. Future research could explore ERC5 optimizations for different computing environments, its integration into real-time encryption scenarios, and its impact on other cryptographic operations and security protocols.
The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
... Show MoreThe flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha
... Show MoreInvestigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent
The inhibitory behavior of L-Cysteine (Cys) and its derivatives towards iron corrosion through density functional theory (DFT) was investigated. The current research study undertakes a rigorous evaluation of global as well as local reactivity descriptors of the Cys in protonated as well as neutral forms and the changes in reactivity after the combination of Cys into di- and tripeptides. The inhibitory effect of di- and tri-peptides increases since, in the molecular structure, the number of reaction centers increase. We computed the adsorption energies (Eads) and low energy complexes with most stability for the adsorption of small peptides and Cys amino acids onto the surfaces of Fe (1 1 1). We found that the adsorption of tri-peptides onto
... Show MoreComputer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
... Show Moreيهدف البحث الى أعداد بعض تمرينات الاساسية لسلاح الشيش بأستخدام المرايا في تطوير قدرة مستوى تعلم الطالبات في المبارزة ومعرفة الفروق بين المجموعتين التجريبي والضابطة بتأثير استخدام المرايا في مستوى اداء بعض مهارات سلاح الشيش لطالبات المرحلة الثالثة , وقد أستخدمت الباحثتان المنهج التجريبي على عينة من طالبات المرحلة الثالثة , وقد بلغ عددهم (45) طالبة , وقد خرجت الباحثتين بعدة أستنتاجات وهي:- - أن المنهاج التعليمي
... Show MoreThis study was carried out in Artificial Insemination Center of Iraq to revealed FMD disease effect on some seminal attributer parameters of 14 imported Holstein bulls divided to three groups according to different reproductive efficiency (four High, five medium and five weak). Results showed that FMD disease had significant (P < 0.05) adverse effect on most seminal attributer parameters, mass, individual motility and sperm concentration / ml during post disease in first of two, four, all months of high, medium and weak semen quality bulls respectively .but semen volume didn’t influenced significantly with this disease. So semen collection should be suspended until resume normal fertility of sperm, after two, four month of high and
... Show MoreThe current study aims to investigate the effect of strategic knowledge management practices on an excellent performance at the Institution of Industrial Development and Research- the Ministry of Iraqi Industry (IDRMII). The present research is designed according to the descriptive method. To achieve the mentioned research objective, the researchers used the questionnaire as the main data collection tool. The research sample was 150 managers who are working at the top and middle management levels. To analyses the data gathered and reaching the results, several statistical techniques were used within AMOS.V25, SPSS.V21Software, This study reached a set of results, the most important of which is the existence of a positive correlat
... Show More