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.
Obesity is the excess of body weight relative to height above the desired level as a result of excessive increase in the ratio of body fat mass to lean mass. It causes many health problems due to its negative effects on body systems (cardiovascular system, musculoskeletal system, gastrointestinal system, respiratory system, skin, endocrine system, genitourinary system) and psychosocial status. In this study is aimed to effective detection of the eating and physical condition-based obesity stages using machine learning algorithms. The dataset contains data for the estimation of obesity stages in individuals from Mexico, Peru, and Colombia and is available as open source. There are 2111 records and 17 attributes in the dataset. In the records, obesity stages were categorized as insufficient weight, normal weight, overweight level I, overweight level II, obesity type I, obesity type II and obesity type III. The 10-fold cross-validation method was used to validate the model and the performances of the Support Vector Machine (SVM), Random Forest (RF), and Multilayer Perceptron (MLP) classification algorithms were compared. It has been determined that the highest performance among the algorithms whose performances are compared belongs to the RF Algorithm (95.78%). This paper’s abstract has been presented at the International Conference on Computational Mathematics and Engineering Sciences held in Ordu (Turkey), / 20-22 May. 2022.
Severe three phase trips are simulated on four arbitrary locations of an uncontrolled power system transmission lines. The responses of three measurable state variables of the system (rotor speed, stator direct axis current, and stator quadrature - axis current) are recorded, and suitable ANNs are trained to detect and locate the positions of the corresponding trips. The paper proves that this method is quick, active and accurate to diagnose and find the locations of that kind of trips.
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.
This paper specifies a proposed improvement model of Data Encryption Standard (DES) which may be used to protect sensitive data. Protection of data during transmission may be necessary to maintain the confidentiality and integrity of the transformation represented by data. Instead of expansion step in each round which made by copying 16 bit from 32 bits data in each right side of the standard algorithm, the unused 8-bits as a key (sometimes it is used for error detection and correction purposes, or it is possible to generate an additional 8-bits with the 56-bits standard key) in the first starting round with the other 8-neglected bits from each of 16 round in the key algorithm will be used, and take the same locations of the expanded data. As a result, the complexity to cryptanalysis of the secured data has been increased. The proposed method was more active and reliable than standard conventional DES, where it can be switched to the system at any round for working with original DES algorithm, which means that an additional security has been added