The convergence of cloud and edge computing in smart manufacturing offers significant potential for improving efficiency in Industry 4.0. However, task scheduling in this context remains a complex, multi-objective challenge. This study introduces a novel Cloud-Edge Smart Manufacturing Architecture (CESMA), leveraging a hybrid approach that integrates NSGA-II and the Improved Monarch Butterfly Optimization (IMBO) algorithms. The combination utilizes NSGA-II's global search and non-dominated solution capabilities with IMBO's fine-tuning and local optimization strengths to enhance task scheduling performance. Where CESMA combines the scalability and analytics power of cloud computing with edge-based real-time decision-making to address the dynamic demands of smart manufacturing. Through extensive simulations and experiments, the feasibility and effectiveness of CESMA are validated, showing improved task scheduling quality, resource utilization, and adaptability to changing conditions. This research establishes a robust platform for managing the complexities of task scheduling in cloud-edge environments, advancing intelligent manufacturing processes, and contributing to the integration of evolutionary algorithms for real-time industrial decision-making
Cosmetic surgery is more prevalent in the world in recent years. A beautiful and flawless face is everyone's dream. Aging, environmental factors, disease, or poor diet are among the factors that influence body wrinkles. Various methods are used to reduce these lines. It can be said that the simplest and most effective solution is to inject cosmetic fluids into these areas. But, due to the increase in facial injections using cosmetic fluids, which are considered toxins, the risk of injury to the surrounding facial nerves and injury to one of the main facial nerves is increasing, creating a catastrophe or deformation in the face irreversibly. Deep learning algorithms have been used to determine whether cosmetic fluids are injected or not. Deep Convolutional Neural Networks (CNNs), VGG16, ResNet....etc deep learning algorithms have demonstrated excellent performance in terms of object detection, picture classification, and semantic segmentation. all the suggested approach consists of three stages: feature extraction, training, and testing/validation. Deep learning technology is used to train and test the system with before and after photographs. Numerous investigations have been carried out using various deep learning algorithms and databases the main goal is to attain maximum accuracy to ensure that injected cosmetic fluids by specialists have been injected in safe areas in addition to facial recognition and determining whether or not the person received an injection. The most used databases are IIITD plastic surgery and HDA_Plastic surgery.
CAPTCHA, which stands for Completely Automated Public Turing Test to Tell Computers and Humans Apart, is a commonly employed security measure to distinguish between humans and computers. The Turing Test, designed to guarantee network security, is the foundation of this security technique. Usability is a crucial concern that can prevent human users from engaging in laborious and time-consuming tasks. When designing CAPTCHA, security and usability must be addressed simultaneously. When designing CAPTCHA, it is crucial to address security and usability simultaneously. A concerted effort is required to protect online data and guarantee privacy and security. The personal information of Internet users remains susceptible to theft. This study uses an information extraction technique called CAPTCHA to investigate the hazards associated with violating user privacy. It is a highly harmful process due to hacking, theft, unauthorized reuse, and the breach of user information. This study proposes a privacy preservation system employing concurrent encryption techniques, multilateral security computing, and zero-knowledge proof. The objective is to create a system that allows for uncomplicated and secure puzzle-solving using dice gas. CAPTCHA limits access to users' information. In the overview and application of evidentiary measurable methods, we can draw significant conclusions about the more extensive client group's discernments and encounters with CAPTCHA as a privacy-preserving component.
The field of image processing has several applications in our daily life. The image quality can be affected by a wide variety of deformations during image acquisition, transmission, compression, etc. Image compression is one of the applications where the quality of the image plays an important role since it can be used to evaluate the performance of various image compression techniques. Many image quality assessment metrics have been proposed. This paper proposes a new metric to assess the quality of compressed images. The principle idea of this metric is to estimate the amount of lost information during image compression process using three components: error magnitude, error location and error distribution. We denote this metric as MLD, which combines the objective assessment (error magnitude) and the subjective assessment (error location and error distribution). First, the metric is used to estimate the quality of compressed images using the JPEG algorithm as this is a standard lossy image compression technique. Then, the metric is used to estimate the quality of compressed images using other compression techniques. The results illustrate that the proposed quality metric is correlated with the subjective assessment better than other well-known objective quality metrics such as SSIM, MSE and PSNR. Moreover, using the proposed metric the JPEG2000 algorithm produces better quality results as compared to the JPEG algorithm especially for higher compression ratios
The scientific paper examined the possibility of developing an advanced healthcare management system in Iraq through the use of Cisco Packet Tracer software. The article stated that the aforementioned software has the potential to speed up network management operations and reduce expenses incurred in maintenance and repair activities. In addition, the article explained several challenges that may arise during the implementation of the smart hospital management system, including providing the required technical expertise, infrastructure provisions, and procedural measures necessary to protect the confidentiality of patient and employee information. The study confirmed that implementing an intelligent hospital management system in Iraq has the potential to improve healthcare quality, mitigate medical errors, enhance employee communication, and reduce disturbances within the hospital setting. Furthermore, this intervention is expected to enhance the efficiency of resource and inventory management and increase patients' experience and satisfaction with healthcare services. The article concludes that achieving the desired results in implementing a smart hospital management system using Cisco Packet Tracer software depends on the collaborative contributions of employees, managers, and technical professionals. This initiative is expected to enhance the hospital's ability to provide medical services of exceptional quality and effectively meet the diverse needs of patients.
In this work, a new key exchange protocol for IP-based mobile networks is introduced. This protocol is called KEPSOM (Key Exchange Protocol Supporting Mobility and Multihoming). The goals of designing KEPSOM are to develop key exchange protocol proposal characterized by its secrecy, simplicity, efficiency, resistivity, and its ability to support mobility and multihoming. The protocol requires only two roundtrips. The design limits the private information revealed by the initiator. An old security association (SA) can be replaced with a new one by rekeying without the need of restarting the protocol with a new session. On the other hand, the changes in IP address due to mobility or multihoming need not to restart the protocol with a new SA session. The proposed protocol can also support key exchange in hybrid wireless network, in which the mobile node can operate in both Ad Hoc and Base Station-oriented wireless network environments using different transmission modes. KEPSOM has been analyzed and proven secure. Several tests have been done to measure and evaluate the performance of the protocol. In these tests, it is found that the required time for rekeying is about 27% of the total required time for exchanging the keys. And the required time to detect and update the change in IP address, which may occur due to mobility or multihoming, is less than 10% of the total required time to establish a new SA sessions.
Internet-based platforms such as social media have a great deal of big data that is available in the shape of text, audio, video, and image. Sentiment Analysis (SA) of this big data has become a field of computational studies. Therefore, SA is necessary in texts in the form of messages or posts to determine whether a sentiment is negative or positive. SA is also crucial for the development of opinion mining systems. SA combines techniques of Natural Language Processing (NLP) with data mining approaches for developing inelegant systems. Therefore, an approach that can classify sentiments into two classes, namely, positive sentiment and negative sentiment is proposed. A Multilayer Perceptron (MLP) classifier has been used in this document classification system. The present research aims to provide an effective approach to improving the accuracy of SA systems. The proposed approach is applied to and tested on two datasets, namely, a Twitter dataset and a movie review dataset; the accuracies achieved reach 85% and 99% respectively.
Our project was divided into two distinct sections, circuit transmitting and receiving ultrasoundWave Based on Laser Light. A Wien Bridge and a Triangle Wave Oscillators used to obtain a sineand a triangular wave, respectively. A comparator circuit which produces Pulse Width Modulation(PWM) that has the same frequency for triangle wave. The PWM was used to drive laserdiode that produced laser light through by MOSFET transistor and received this light by receivingcircuit which consists of a photodiode with resistor as a voltage divider, amplifier circuit to amplifythe signal and filter to get any desired frequency. The main objective of this project primarilywas to realize a transmission-reception system to transfer ultrasound Frequency via Laser withouta guiding medium, using modulation with little quality loss.