The most popular evolutionary search techniques are genetic algorithms (GAs). Even though they are frequently used to solve control engineering problems, they are currently not a common tool in the control engineer's toolbox. This may be due in part to the fact that there are currently few general overviews of the employment of GAs for control engineering problems, and that they are often reported on at computer science conferences rather than conferences for control engineers. This review study is intended to assist researchers and practitioners in identifying prospective research issues, potential solutions, as well as advantages and disadvantages of each technique. This study gives a brief overview of contemporary a Genetic Algorithm (GA) in control systems. Additionally, offers a number of control techniques used with the GA that have undergone extensive research. The conclusion of this study listed in a table to show the effectiveness of GA in various control technique and which field didn’t used till the time of preparing this review.
The detection of faults in electronic circuits is crucial to ensure the proper performance and reliability of electronic applications that utilize these devices. This work discovers, for the first time, that a direct tester board for fault diagnosis can be used not only for the intended measurement of current and voltage but also for studying the potential development of these magnitudes in inaccessible locations, as it detects register transfer level signals through oscilloscopes with low acquisition speeds. The experimental analysis carried out combines the use of commercial software with spatial distribution tracking and the exploitation of the sizes of network links in their computer graphical representation. The proper detection of malfunctions in electronic systems is crucial for enhancing their performance and reliability. We intend to explore the troubleshooting of analog electronic systems, for which we use wide-band direct tester boards. To evaluate its performance in routine practice, we perform experimentation using two different analog circuits designed. They consist of conventional operational amplifiers and element modeling based on equivalent resistance-capacitance networks. Given the procedure followed, commercial programs were used. Special mention should be made of the conclusion matrix, which is interesting when selecting suitable diagnostic parameters. The effectiveness of direct measurement based on integrated probes in the two projects, which allowed for fault insertion, was also confirmed. The results and discussions were enriched by the summarized experimental test report. The work concludes with a reflection on the relationship between this work and the existing state of the art, as well as the new challenges posed by international researchers.
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
Advanced prosthetics are a crucial aspect of rehabilitation technology and are receiving increased attention globally. Approximately 2 million people require prosthetic limbs, presenting opportunities for enhancing their quality of life. State-of-the-art technologies such as realistic arms and myoelectric prostheses are gaining popularity. Progress in sensor technology, artificial intelligence, and materials has driven the field forward. Various types of controllers, including direct, pattern recognition, and proportional-derivative, have been developed. Integration of material science, computer science, artificial intelligence, and neurology has facilitated controller advancements. Techniques like targeted muscle reinnervation and Osseo integrated prostheses offer improved surgical options. Gesture recognition technologies and intelligent sensors are enhancing hand control. Future advancements will involve machine learning, artificial intelligence, and sensing techniques, while ethical concerns must be addressed. Advanced myoelectric prostheses, also known as myocontrolled or lower-limb micromod investigative prostheses, have a patient acceptance rate of 75% to 80%. However, while these methods offer advantages, there are also drawbacks. Integrating different types of controllers for these smart prostheses and enhancing the overall device's strength and robustness will have a significant impact. This discussion focuses on various types of smart prosthetic controllers, dividing muscle activity into extracellular myoelectric potential and EEG signals
Uncontrolled garbage disposal related to urban settings can be extremely harmful to the health of individuals as well as the environment. This paper proposes the construction of an intelligent surveillance system based on the YOLOv5 object detection model and an ultra-convolutional net (U-Net), which we will call (YOLOv5-U-Net model), capable of monitoring waste management facilities in real-time through image processing and artificial intelligence. An illustration of an intelligent surveillance system is provided in the following statement. Besides identifying different categories of garbage and possible risks to public health, the system can also identify situations of unsuitable accumulation of waste. For that purpose, to ensure that local authorities will act in due time, the framework integrates several technologies, including object detection algorithms, classification networks as well as real-time warning systems. It is through the amalgamation of these technologies. Testing of the prototype has elicited an outcome; that accuracy related to waste categorization has increased, while reaction times have decreased, all discovered due to prototype examination. Implementation of this strategy does not only increase the linkage between environmental monitoring as well as protection of public health but also gives some help in promoting a conscious urban development, right through ensuring health.
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.
Hydraulic structures are structures submerged or partially submerged in water, they’re used to retain or divert natural water flow. Any hydraulic structure that retains water is faced with seep-age problems as the water seeks the path with the least resistance through or under the hydraulic structure. If the water carries materials as it flows or exerts high pressure on the floor of the structure, it will cause failures such as piping and cracks and there are many ways to prevent that, including cutoffs. In this paper, seepage is analyzed for different cases by using the empirical method (Khosla’s theory) and the numerical method by using computer software (SEEP/W). The results had some slight differences between the two methods as a result of not taking into ac-count the effect of soil characteristics of the empirical method. However, the water pressure heads underneath the impervious floor that calculated by the numerical method were greater
The purpose of this paper is to present a new method to establish a kinematic model for different manipulators, whose can be simulate the move in a two-dimensional workspace.The model is applied and implemented to four robot arm manipulators witha different DOF.The first step of modelling a robot is establishing its mathematical model parameters. It requires assigning proper length and angle for each link and creation rotational matrics. Simulation based on Matlabsoftware was implemented for finding their workspace
The paper concentrates on the latest developments in the field of deep-learning-based image deblurring and specifically, Convolutional Neural Networks (CNNs) and how they are able to be used to deblur images. It discusses the different forms of blur such as motion blur, out-of-focus blur, and mixed blur and compares these methods under the basis of blind and non-blind methods. The article sheds light on the various architecture and model design, loss functions, and performance indicators applied in image deblurring. Moreover, it draws attention to the issues that are presently observed in the sphere and gives possible path directions of the future research. The review has condensed and synthesized existing literature to provide a clear overview of the current solutions in image deblurring and offers guidance to the researchers on how to come up with the more precise, efficient, and adaptive methods of deblurring. The developments are meant to enhance the use of image restoration techniques in practical applications and this will lead to the quality and reliability of deblurring processes.
This investigation provides experimental results and nonlinear analysis by using finite element model of thick hollow core slab made from recycled lightweight material. Four hollow core slabs specimens were cast and tested in this investigation with dimensions (1200mm length, 450mm width and 250mm thickness). The crushed clay brick was used as a coarse aggregate instead of gravel. The iron powder waste and silica fume were used in order to increase the compressive strength of concrete. The techniques reduction hollow length and use shear reinforcement were used to improve shear strength and avoid shear failure. The specimens were tested by applying two-line load up to failure. The experimental results were showed these techniques were resisted the shear failure significantly and works to change failure mode from shear to flexural failure. Finite element computer software program (ANSYS) was used to analysis hollow core slabs specimens and compare the experimental results with the theoretical results. Good agreement have been obtained between experimental and numerical results.
The performance of electronic devices, especially computers, depends on the efficiency of the electronic chips and Computer processing units, which are mainly made of semiconductors, so their working efficiency is inversely proportional to their working temperature. Therefore, this paper presents an experimental investigation of the design, implementation, and testing of three cooling systems to maintain the temperature of the processing unit as minimum as possible. The first is a traditional system dissipates heat from the working fluid to the air through a finned tube heat exchanger. The second successive hybrid system was designed to integrate with the first one in addition to a thermoelectric cooling system to cool the working fluid. The third system included in addition to the traditional heat dissipation one, an intercooler cylinder with a large quantity of the working fluid in the main system beside a separate system for cooling the working fluid using thermoelectric cooling to ensure sufficient cooling of the processing units when working at high frequencies by providing a large capacity of working fluid pre-cooled to a low temperature. Comparing the experimental results of the cooling systems with the traditional one under the same test conditions showed that the second system led to a reduction in the temperature of the processing unit by 5.2%, while employing the third system reduced the temperature to 11.3%., When the thermoelectric cooling unit operates at a performance factor of about 1.76.
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.
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.
In The present work, a thermal analysis of two different chimneys by studying the effect of the flue gases on the chimney shell structure was presented. A computer program was constructing using Fortran language to estimate the thermal stresses that: radial, circumferential and longitudinal thermal stresses which will induced as a result of thermal gradient across the chimney wall structure. The results show, the radial thermal stresses has the minimum value at the middle of the concrete layer in the unlined chimney. The circumferential and longitudinal thermal stresses are transferred from the negative value to the positive value. The maximum value of stresses is found in the inner surface negative value and on the outer surface positive value of the chimney.
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.
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.