Ceramics and Composites

В книге представлен современный обзор керамики и композитов. Она фокусируется на гибком и эффективном производстве изделий определенной формы, сложности и индивидуальных характеристик и свойств.Используемые программы Adobe AcrobatThe book presents a state-of-the-art survey of ceramics and composites. It focuses on the flexible and efficient manufacture of objects with specific shapes, complexity and tailor-made characteristics and properties

Audio-Visual Stress Classification Using Cascaded RNN-LSTM Networks

The purpose of this research is to emphasize the importance of mental health and contribute to the overall well-being of humankind by detecting stress. Stress is a state of strain, whether it be mental or physical. It can result from anything that frustrates, incenses, or unnerves you in an event or thinking. Your body’s response to a demand or challenge is stress. Stress affects people on a daily basis. Stress can be regarded as a hidden pandemic. Long-term (chronic) stress results in ongoing activation of the stress response, which wears down the body over time. Symptoms manifest as behavioral, emotional, and physical effects. The most common method involves administering brief self-report questionnaires such as the Perceived Stress Scale. However, self-report questionnaires frequently lack item specificity and validity, and interview-based measures can be time- and money-consuming. In this research, a novel method used to detect human mental stress by processing audio-visual data is proposed. In this paper, the focus is on understanding the use of audio-visual stress identification. Using the cascaded RNN-LSTM strategy, we achieved 91% accuracy on the RAVDESS dataset, classifying eight emotions and eventually stressed and unstressed states

Multi Response Optimization of ECDM Process for Generating Micro Holes in CFRP Composite Using TOPSIS Methodology

The applications of carbon fiber reinforced polymer composites (CFRPCs) in aerospace, automotive, electronics and lab-on-chip devices require precise machining processes. Over the past decade, there have been numerous attempts to machine CFRPCs using both traditional and unconventional machining techniques. However, because of their limitations, these methods have not gained widespread acceptance. In the present research investigation, Electrochemical Discharge Machining (ECDM) process has been employed to produce micro-holes on CFRPC. The experimental strategy was scheduled using L9 orthogonal array keeping applied voltage, electrolyte concentration and inter-electrode gap as input parameters. The material removal rate (MRR) and overcut were selected as output parameters. The technique for order preference by similarity to the ideal solution (TOPSIS) methodology was executed for multi-response optimization. The overcut and MRR of machined samples improved from 150 µm to 48 µm and 2.232 mg/min to 2.1267 mg/min correspondingly while using the optimum parametric settings of the TOPSIS approach. The shape of drilled micro-holes produced by the TOPSIS process is indicative of a machined surface of superior quality, with a reduction in the number of micro-cracks and a diameter that is uniform

Role of Gender in Predicting Determinant of Financial Risk Tolerance

This research was conducted to determine whether the determinants of financial risk tolerance varied by gender or whether the same factors influenced the risk-taking capacities of both genders. This study utilised personality types (Type-A and Type-B), financial literacy, and six demographic parameters, including marital status, age, education, income, occupation, and the number of dependents, as independent variables, and gender as a dividing variable. In order to conduct this study, information was gathered from 671 investors. The financial risk tolerance of male investors was determined by six out of eight independent factors (personality type, financial literacy, marital status, income, occupation, and the number of dependents). However, just four factors (personality type, financial literacy, marital status, and income) have a substantial impact on the financial risk tolerance of female investors

Role of Gender in Predicting Determinant of Financial Risk Tolerance

This research was conducted to determine whether the determinants of financial risk tolerance varied by gender or whether the same factors influenced the risk-taking capacities of both genders. This study utilised personality types (Type-A and Type-B), financial literacy, and six demographic parameters, including marital status, age, education, income, occupation, and the number of dependents, as independent variables, and gender as a dividing variable. In order to conduct this study, information was gathered from 671 investors. The financial risk tolerance of male investors was determined by six out of eight independent factors (personality type, financial literacy, marital status, income, occupation, and the number of dependents). However, just four factors (personality type, financial literacy, marital status, and income) have a substantial impact on the financial risk tolerance of female investors

Investigation on the Impact of Different Absorber Materials in Solar Still Using CFD Simulation—Economic and Environmental Analysis

Solar stills are one of the low water production desalination systems, but its low yield makes it necessary to investigate different design and performance parameters to improve its productivity. This paper aims to perform a parametric analysis of a solar still desalination system and study the effect of different absorber materials on the performance of a single-slope solar desalination unit employing computational fluid dynamics (CFD) numerical simulation via COMSOL® Multiphysics software. To consider the absorptivity of water with different absorbing materials, simulation was conducted with the application of effective emissivity for the solar still walls. In addition, the economic, exergoeconomic, and CO2 mitigation of solar stills were studied. The results revealed that the hourly water output of the solar desalination unit, with different absorbing materials (black ink, black dye, and black toner), reached the maximum values at 1:00 PM. On comparing the simulation results of solar stills with and without absorbing materials, it has been observed that the solar still painted with black toner shows the highest improvement in hourly productivity, the exergy of evaporation, and evaporative heat transfer coefficient with a maximum increase in respective values by 10.52%, 13.68% and 5.37%. The CO2 mitigation and enviroeconomic parameter of the solar still using black toner were equal to 31.4 tons and 455.3 USD, respectively. Moreover, the lowest cost per liter (CPL) of the solar still was obtained using black toner, which was about 0.0066 USD/L

Employing Energy and Statistical Features for Automatic Diagnosis of Voice Disorders

The presence of laryngeal disease affects vocal fold(s) dynamics and thus causes changes in pitch, loudness, and other characteristics of the human voice. Many frameworks based on the acoustic analysis of speech signals have been created in recent years; however, they are evaluated on just one or two corpora and are not independent to voice illnesses and human bias. In this article, a unified wavelet-based paradigm for evaluating voice diseases is presented. This approach is independent of voice diseases, human bias, or dialect. The vocal folds’ dynamics are impacted by the voice disorder, and this further modifies the sound source. Therefore, inverse filtering is used to capture the modified voice source. Furthermore, the fundamental frequency independent statistical and energy metrics are derived from each spectral sub-band to characterize the retrieved voice source. Speech recordings of the sustained vowel /a/ were collected from four different datasets in German, Spanish, English, and Arabic to run the several intra and inter-dataset experiments. The classifiers’ achieved performance indicators show that energy and statistical features uncover vital information on a variety of clinical voices, and therefore the suggested approach can be used as a complementary means for the automatic medical assessment of voice diseases