Lead-free halide double perovskite Cs2AgBiBr6 is a nontoxic promising material for optoelectronic applications. However, halide mixing in Cs2AgBiBr6 is expected to be a valuable process that may result in favorable optical properties. Here, we studied the optical properties along with band structures of mixed halide Cs2AgBi(Br1-xIx)6 for different iodine (I) concentrations using density functional theory (DFT). The indirect bandgap is confirmed from the energy band structures having nonlinearly decreasing energy gaps with the increment of I-content. The I-content-dependent different optical properties like refractive index, absorption coefficient, extinction coefficient, reflectivity, optical conductivity, and energy loss are studied. Two absorption windows in the visible and ultraviolet regions are noticed having a redshift in the absorption spectra with increasing I-content. The peak absorption is recorded to be in the order of 105 cm-1 to 106 cm-1 having I-content dependence. Other optical properties also show promising characteristics both in the visible and ultraviolet regions demonstrating its potential applications in next-generation optoelectronic devices.
Sentiment analysis can largely influence the people to get the update of the current situation. Coronavirus (COVID-19) is a contagious illness caused by the SARS-CoV-2 virus that causes severe respiratory symptoms. The lives of millions have continued to be affected by this pandemic, several countries have resorted to a full lockdown. During this lockdown, people have taken social networks to express their emotions to find a way to calm themselves down. People are spreading their sentiments through microblogging websites as one of the most preventive steps of this disease is the socialization to gain people’s awareness to stay home and keep their distance when they are outside home. Twitter is a popular online social media platform for exchanging ideas. People can post their different sentiments, which can be used to aware people. But, some people want to spread fake news to frighten the people. So, it is necessary to identify the positive, negative, and neutral thoughts so that the positive opinions can be delivered to the mass people for spreading awareness to the people. Moreover, a huge volume of data is floating on Twitter. So, it is also important to identify the context of the dataset. In this paper, we have analyzed the twitter dataset for evaluating the sentiment using several machine learning algorithms, where the random forest algorithm achieved the highest accuracy of 93%. Later, we have found out the context learning of the dataset based on the sentiments.
Cognitive load is a measure of effort while performing any task through memory resources. Researchers are now concentrating on Galvanic Skin Response (GSR) as an emerging technique for measuring cognitive load in different cases. In this study, the variation of cognitive load has been revealed for online exams with various difficulty levels. GSR data has been collected for thirteen jobs of three different categories of online exams. Then the time-domain feature of GSR data against different task levels has been calculated and variance test is also accomplished. Thus change in cognitive load with respect to the variation of different levels for online exams such as written, multiple-choice question (mcq) and viva has been observed. This monitoring has a comprehensive application for understanding the proper way of taking online exams which will reveal the best possible output from an examinee so that the cognitive load remains low. As taking exams is the best way of testing an examinee, our research will suggest the best method of taking online exams.
An ultra-wideband (UWB) monopole antenna excited by a two-branch feeding strip is proposed for detecting both types of human brain stroke called hemorrhagic stroke and ischemic stroke. With the proposed feeding strip, the antenna achieves an ultra-wide impedance bandwidth of 3.85 GHz which is nearly twice the bandwidth obtained with a simple feeding strip. The operating frequency of the antenna lies in the range between 3.08 GHz and 6.93 GHz. Besides, a gain of 2.05 dB and a radiation efficiency of 78.76 % are obtained. The proposed antenna possesses a compact dimension of 30×20×1.5 mm3. The antenna is designed on a 1.5 mm thick Rogers RO3003 dielectric substrate having a relative permittivity of 3 as it is suitable for high frequency applications. Furthermore, a six-layer human head phantom model consisting of skin, fat, bone, dura, cerebrospinal fluid (CSF) and brain is proposed in which a hemorrhagic stroke and an ischemic stroke of 5 mm radius is individually inserted for assessing antenna performance. The safety level of specific absorption rate (SAR) is retained in each case to avoid health risk. The detection of hemorrhagic stroke is confirmed with an excess of current density and SAR while ischemic stroke with a deficit of current density compared to the healthy brain.
The most diagnosed cancer among women worldwide is breast cancer. X-ray mammography, magnetic resonance imaging (MRI), and ultrasound are all medical procedures that have a few numbers of drawback. In this research, a microstrip patch antenna operating in ISM frequency range along with two types of 3D breast phantom has been created using CST microwave studio in order to identifying the presence of the malignant tumor. The aim of this paper is to detect the cancerous tumor in breast phantom by the variation of S11 parameters & SAR analysis. To reach this goal other parameters such as efficiency, reflection parameters, SAR have been evaluated. As reflection coefficient varies in the presence of tumor in the breast phantom & SAR value is higher for tumor cells, the tumor can be easily detected in this process. Detecting the cancerous tumor in this process is better than other processes because biological tissues remain harmless due to the non-ionizing nature of microwave.
