Enhancing the mechanical properties and formability of low carbon steel with dual-phase microstructures

In the present study, a special heat treatment cycle (step quenching) was used to produce a dual-phase (DP) microstructure in low carbon steel. By producing this DP microstructure, the mechanical properties of the investigated steel such as yield stress, tensile strength, and Vickers hardness were increased 14, 55, and 38%, respectively. In order to investigate the effect of heat treatment on formability of the steel, Nakazima forming test was applied and subsequently finite element base modeling was used to predict the outcome on forming limit diagrams. The results show that the DP microstructure also has a positive effect on formability. The results of finite element simulations are in a good agreement with those obtained by the experimental test

IRIS observational approach to the oscillatory and damping nature of network and internetwork chromosphere small-scale brightening (SSBs) and their unusual dynamical and morphological differences in different regions on the solar disk

One of the most exciting benefits of solar small-scale brightening is their oscillations, this study investigated the properties of small-scale brightening (SSBs) in different regions of the Sun and found that there are differences and similarities in the properties of oscillated and non-oscillated SSBs in different regions of the Sun, including quiet Sun (QS), the adjacent to active regions (AAR), and coronal hole (CH). The damping per period (Q-factor) and maximum Doppler velocity of SSBs varied depending on the region, with the less bright internetwork SSBs in QS having lower damping time (120 seconds) and higher maximum Doppler velocities (47 km/s) compared to the brighter network SSBs (with 216 seconds & 37 km/s, respectively), while in AAR, internetwork SSBs tend to have higher damping time (about of 220 seconds) and wider maximum Doppler velocity (10 to 140 km/s) ranges compared to network SSBs (130 seconds & 10 to 85 km/s). In CH, both types of SSBs show similar damping time (120 seconds), but internetwork SSBs tend to have higher maximum Doppler velocities (100 km/s) compared to network SSBs (85 km/s). Also, it was pointed out that the majority of network SSBs in AARs are in the overdamping mode, while in QS, internetwork SSBs demonstrate overdamping behavior and oscillated network SSBs exhibit critical damping behavior. It is important to bear in mind, however, that the physical mechanisms underlying the damping of SSBs may vary depending on the local plasma conditions and magnetic environment.Comment: 36 pages and 10 figs., accepted in solar physics journa

Dampening Long-Period Doppler Shift Oscillations using Deep Machine Learning Techniques in the Solar Network and Internetwork

This study explores the Doppler shift at different wavelengths in the Interface Region Imaging Spectrograph (IRIS) solar spectrum and implements a comprehensive consideration of Doppler velocity oscillations in the IRIS channels. This comprehensive consideration reveals a propagating periodic perturbation in a large number of chromosphere and transition region (TR) bright points (BPs). To our knowledge, this is the first investigation of the longitudinal oscillations with damping in BPs using comprehensive consideration of the Doppler velocity at various wavelengths. The phenomena of attenuation in the red and blue Doppler shifts of the solar wavelength range were seen several times during the experiments. We utilized deep learning techniques to examine the statistical properties of damping in network and internetwork BPs, as well as active, quiet areas, and coronal hole areas. Our results revealed varying damping rates across different regions, with 80 percent of network BPs exhibiting damping in quiet areas and 72 in coronal hole areas. In active areas, the figure approached 33. For internetwork BPs, the values were 65, 54, and 63 percent for quiet areas, coronal hole areas, and active regions, respectively. The damping rate in active regions is twice as high at Internetwork's BPs. The damping components in this study were computed, and the findings show that the damping at all points is underdamped. The observed damping process suggests the propagation and leaking of energetic waves out of TR bright points, potentially contributing to the energy transport from the bright magnetic footpoints to the upper chromosphere, transition region, and corona.Comment: 25 pages, 7 figs. accepted in Advances in Space Researc

Breast cancer diagnosis: a survey of pre-processing, segmentation, feature extraction and classification

Machine learning methods have been an interesting method in the field of medical for many years, and they have achieved successful results in various fields of medical science. This paper examines the effects of using machine learning algorithms in the diagnosis and classification of breast cancer from mammography imaging data. Cancer diagnosis is the identification of images as cancer or non-cancer, and this involves image preprocessing, feature extraction, classification, and performance analysis. This article studied 93 different references mentioned in the previous years in the field of processing and tries to find an effective way to diagnose and classify breast cancer. Based on the results of this research, it can be concluded that most of today’s successful methods focus on the use of deep learning methods. Finding a new method requires an overview of existing methods in the field of deep learning methods in order to make a comparison and case study

Non-Invasive Monitoring of Vital Signs in Calves Using Thermal Imaging Technology

This study presents a non-invasive method using thermal imaging to estimate heart and respiration rates in calves, avoiding the stress from wearables. Using Kernelised Correlation Filters (KCF) for movement tracking and advanced signal processing, we targeted one ROI for respiration and four for heart rate based on their thermal correlation. Achieving Mean Absolute Percentage Errors (MAPE) of 3.08% for respiration and 3.15% for heart rate validates the efficacy of thermal imaging in vital signs monitoring, offering a practical, less intrusive tool for Precision Livestock Farming (PLF), improving animal welfare and management

Comprehensive mm-Wave FMCW Radar Dataset for Vital Sign Monitoring: Embracing Extreme Physiological Scenarios

Recent advancements in non-invasive health monitoring technologies underscore the potential of mm-Wave Frequency-Modulated Continuous Wave (FMCW) radar in real-time vital sign detection. This paper introduces a novel dataset, the first of its kind, derived from mm-Wave FMCW radar, meticulously capturing heart rate and respiratory rate under various conditions. Comprising data from ten participants, including scenarios with elevated heart rates and participants with diverse physiological profiles such as asthma and meditation practitioners, this dataset is validated against the Polar H10 sensor, ensuring its reliability for scientific research. This dataset can offer a significant resource for developing and testing algorithms aimed at non-invasive health monitoring, promising to facilitate advancements in remote health monitoring technologies

Comprehensive mm-Wave FMCW Radar Dataset for Vital Sign Monitoring:Embracing Extreme Physiological Scenarios

Recent advancements in non-invasive health monitoring technologies underscore the potential of mm-Wave Frequency-Modulated Continuous Wave (FMCW) radar in real-time vital sign detection. This paper introduces a novel dataset, the first of its kind, derived from mm-Wave FMCW radar, meticulously capturing heart rate and respiratory rate under various conditions. Comprising data from ten participants, including scenarios with elevated heart rates and participants with diverse physiological profiles such as asthma and meditation practitioners, this dataset is validated against the Polar H10 sensor, ensuring its reliability for scientific research. This dataset can offer a significant resource for developing and testing algorithms aimed at non-invasive health monitoring, promising to facilitate advancements in remote health monitoring technologies

Non-Invasive Monitoring of Vital Signs in Calves Using Thermal Imaging Technology

This study presents a non-invasive method using thermal imaging to estimate heart and respiration rates in calves, avoiding the stress from wearables. Using Kernelised Correlation Filters (KCF) for movement tracking and advanced signal processing, we targeted one ROI for respiration and four for heart rate based on their thermal correlation. Achieving Mean Absolute Percentage Errors (MAPE) of 3.08% for respiration and 3.15% for heart rate validates the efficacy of thermal imaging in vital signs monitoring, offering a practical, less intrusive tool for Precision Livestock Farming (PLF), improving animal welfare and management

Intelligent Detection of Intrusion into Databases Using Extended Classifier System (XCS)

With increasing tendency of users to distributed computer systems in comparison with concentrat-ed systems, intrusion into such systems has emerged as a serious challenge. Since techniques of intrusion into systems are being intelligent, it seems necessary to use intelligent methods to en-counter them. Success of the intrusion systems depends on the strategy employed in these sys-tems for attack detection. Application of eXtended Classifier Systems (XCS) is proposed in this paper for detection of intrusions to databases. The extended classifier systems which are known as one of the most successful types of learning agents create a set of stochastic rules and com-plete them based on the methods inspired from human learning process. Thereby, they can grad-ually get a comprehensive understanding of the environment under study which enables them to predict the correct answer at an acceptable accuracy once encountered with new issues. The method suggested in this paper an improved version of extended classifier systems is “trained” using a set of existing examples in order to identify and avoid attempts to intrude computer sys-tems during phases of application and encountering these attempts. The proposed method has been tested on several problems to demonstrate its performance while its results indicate a 91% detection of various known intrusions to the databases.DOI:http://dx.doi.org/10.11591/ijece.v3i5.403