Search results for: aluminium matrix composite

Authors: Abdullah Bal, Sevdenur Bal

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This paper purposes a new type of hardware application for training of cellular neural networks (CNN) using optical joint transform correlation (JTC) architecture for image feature extraction. CNNs require much more computation during the training stage compare to test process. Since optoelectronic hardware applications offer possibility of parallel high speed processing capability for 2D data processing applications, CNN training algorithm can be realized using Fourier optics technique. JTC employs lens and CCD cameras with laser beam that realize 2D matrix multiplication and summation in the light speed. Therefore, in the each iteration of training, JTC carries more computation burden inherently and the rest of mathematical computation realized digitally. The bipolar data is encoded by phase and summation of correlation operations is realized using multi-object input joint images. Overlapping properties of JTC are then utilized for summation of two cross-correlations which provide less computation possibility for training stage. Phase-only JTC does not require data rearrangement, electronic pre-calculation and strict system alignment. The proposed system can be incorporated simultaneously with various optical image processing or optical pattern recognition techniques just in the same optical system.

Keywords: CNN training, image processing, joint transform correlation, optoelectronic hardware

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Authors: Kyle Phillips, Ndiko Ludidi

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Global climate change has resulted in altered rainfall patterns, which has resulted in annual losses in maize crop yields due to drought. Therefore it is important to produce maize cultivars that are more drought-tolerant, which is not an easily accomplished task as plants have a plethora of physical and biochemical adaptation methods. One such mechanism is the drought-induced expression of enzymatic and non-enzymatic proteins which assist plants to resist the effects of drought on their growth and development. One of these proteins is AtRD22 which has been identified in Arabidopsis thaliana. Using an in silico approach, a maize protein with 48% sequence homology to AtRD22 has been identified. This protein appears to be localized in the extracellular matrix, similarly to AtRD22. Promoter analysis of the encoding gene reveals cis-acting elements suggestive of induction of the gene’s expression by abscisic acid (ABA). Semi-quantitative transcriptomic analysis of the putative maize RD22 has revealed an increase in transcript levels after the exposure to drought. Current work elucidates the effect of up-regulation and silencing of the maize RD22 gene on the tolerance of maize to drought. The potential role of the maize RD22 gene in maize drought tolerance can be used as a tool to improve food security.

Keywords: abscisic acid, drought-responsive cis-acting elements, maize drought tolerance, RD22

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Authors: Sandra C. L. Dorea, Joann K. Whalen, Yixin Shao, Oumarou Savadogo

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The major challenge for industries that rely on fossil fuels in manufacturing processes or to provide goods and services is to lower their CO2 emissions, as the case for the manufacture of Portland cement. Feasible materials for this purpose can include agro-industrial or agricultural wastes, which are termed 'biosilica' since the silica was contained in a biological matrix (biomass). Corn cob (CC) has some characteristics that make it a good candidate as biosilica source: 1) it is an abundant grain crop produced around the world; 2) more production means more available residues is left in the field to be used. This work aims to evaluate the CC collected from different farms in Canada during the corn harvest in order to see if they can be used together as a biosilica source. The characterization of the raw CC was made in the physical, chemical, and thermal way. The moisture content, the granulometry, and the morphology were also analyzed. The ash content measured was 2,1%. The Thermogravimetric Analysis (TGA) and its Derivative (DTG) evaluated of CC as a function of weight loss with temperature variation ranging between 30°C and 800°C in an atmosphere of N2. The chemical composition and the presence of silica revealed that the different sources of the CC do not interfere in its basic chemical composition, which means that this kind of waste can be used together as a source of biosilica no matter where they come from. Then, this biosilica can partially replace the cement Portland making sustainable cementitious mixtures and contributing to reduce the CO2 emissions.

Keywords: biosilica, characterization, corn cob, sustainable cementitious materials

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Authors: Wei Zhang, Yan He, Yan Wang, Yufeng Li, Chuanpeng Hao

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Surface roughness is an important index for evaluating surface quality, needs to be accurately measured to ensure the performance of the workpiece. The roughness measurement based on machine vision involves various image features, some of which are redundant. These redundant features affect the accuracy and speed of the visual approach. Previous research used correlation analysis methods to select the appropriate features. However, this feature analysis is independent and cannot fully utilize the information of data. Besides, blindly reducing features lose a lot of useful information, resulting in unreliable results. Therefore, the focus of this paper is on providing a redundant feature removal approach for visual roughness measurement. In this paper, the statistical methods and gray-level co-occurrence matrix(GLCM) are employed to extract the texture features of machined images effectively. Then, the principal component analysis(PCA) is used to fuse all extracted features into a new one, which reduces the feature dimension and maintains the integrity of the original information. Finally, the relationship between new features and roughness is established by the support vector machine(SVM). The experimental results show that the approach can effectively solve multi-feature information redundancy of machined surface images and provides a new idea for the visual evaluation of surface roughness.

Keywords: feature analysis, machine vision, PCA, surface roughness, SVM

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Authors: S. Dikmen Kucuk, A. Tozluoglu, Y. Guner

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In recent years, petroleum-based polymers began to be limited due to effects on human and environmental point of view in many countries. Thus, organic-based biodegradable materials have attracted much interest in the composite industry because of environmental concerns. As a result of this, it has been asked that inorganic and petroleum-based materials should be reduced and altered with biodegradable materials. In this point, in this study, it is aimed to investigate the potential of use of TEMPO (2,2,6,6- tetramethylpiperidine 1-oxyl)-mediated oxidation nano-fibrillated cellulose instead of EPDM (ethylene-propylene-diene monomer) rubber, which is a petroleum-based material. Thus, the exchange of petroleum-based EPDM rubber with organic based cellulose nanofibers, which are environmentally friendly (green) and biodegradable, will be realized. The effect of tempo-oxidized cellulose nanofibers (TCNF) instead of EPDM rubber was analyzed by rheological, mechanical, chemical, thermal and aging analyses. The aged surfaces were visually scrutinized and surface morphological changes were examined via scanning electron microscopy (SEM). The results obtained showed that TEMPO oxidation nano-fibrillated cellulose can be used at an amount of 1.0 and 2.2 phr resulting the values stay within tolerance according to customer standard and without any chemical degradation, crack, colour change or staining.

Keywords: EPDM, cellulose, green materials, nanofibrillated cellulose, TCNF, tempo-oxidized nanofiber

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Authors: Daniela Greven, Kathrin Endres, Shugana Sundralingam

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The use of chatbots has hardly been established in B2B companies to date and involves various challenges. The goal of this paper is to identify the biggest obstacles to the successful implementation of chatbots in B2B companies and to develop measures to overcome them. The obstacles are identified by conducting expert interviews within the framework of Eisenhardt's case study research. These are examined through a socio-technical analysis focusing on people, technology, and organization. By means of systematic literature research and in-depth interviews with German chatbot providers and customers of chatbots, measures for overcoming the obstacles are identified. Using interviews with experts from German chatbot providers, the responsible stakeholders of each measure according to the RASCI Responsibility Matrix are identified. The study shows that there are major obstacles in all areas of a socio-technical system that can cause the implementation of a chatbot to fail. A total of 44 implementation obstacles and 58 measures to overcome these obstacles are identified. The study shows that there are major obstacles in the areas of people, technology, and organization of a socio-technical system that can cause the implementation of a chatbot to fail. A holistic view is therefore essential. The results provide firms with a guideline on how to overcome potential obstacles during chatbot implementation in B2B customer service.

Keywords: chatbots, socio-technical analysis, B2B customer service, implementation success factors

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Authors: Ouahiba Taamallah, Tarek Litim

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The study deals with the burnishing effect of AISI 52100 steel and parameters influence (Py, i and f on surface integrity. The results show that the optimal effects are closely related to the treatment parameters. With a 92% improvement in roughness, SB can be defined as a finishing operation within the machining range. Due to 85% gain in consolidation rate, this treatment constitutes an efficient process for work-hardening of material. In addition, a statistical study based on regression and Taguchi's design has made it possible to develop mathematical models to predict output responses according to the studied burnishing parameters. Response Surface Methodology RSM showed a simultaneous influence of the burnishing parameters and to observe the optimal parameters of the treatment. ANOVA Analysis of results led to validate the prediction model with a determination coefficient R2=94.60% and R2=93.41% for surface roughness and micro-hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=20 Kgf, i=5 passes and f=0.08 mm.rev-1, which favors minimum surface roughness and a maximum of micro-hardness. The result was validated by a composite desirability D_i=1 for both surface roughness and microhardness, respectively. Applying optimal parameters, burnishing showed its beneficial effects in fatigue resistance, especially for imposed loading in the low cycle fatigue of the material where the lifespan increased by 90%.

Keywords: AISI 52100 steel, burnishing, Taguchi, fatigue

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Authors: Yu Zhang, Il Kim

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Polypeptides with defined peptide sequences illustrate the power of remarkable applications in drug delivery, tissue engineering, sensing and catalysis. Especially the cyclic polypeptides, the distinctive topological architecture imparts many characteristic properties comparing to linear polypeptides. Here, a facile and highly efficient strategy for the synthesis of linear and cyclic polypeptides is reported using N-heterocyclic carbenes (NHCs)-mediated ring-opening polymerization (ROP) of α-amino acid N-carboxyanhydrides (NCA) in the presence or absence of primary amine initiator. The polymerization proceeds rapidly in a quasi-living manner, allowing access to linear and cyclic polypeptides of well-defined chain length and narrow polydispersity, as evidenced by nuclear magnetic resonance spectrum (1H NMR and 13C NMR spectra) and size exclusion chromatography (SEC) analysis. The cyclic architecture of the polypeptides was further verified by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectra (MALDI-TOF MS) and electrospray ionization (ESI) mass spectra, as well as viscosity studies. This approach can also simplify workup procedures and make bulk scale synthesis possible, which thereby opens avenues for practical uses in diverse areas, opening up the new generation of polypeptide synthesis.

Keywords: α-amino acid N-carboxyanhydrides, living polymerization, polypeptides, N-heterocyclic carbenes, ring-opening polymerization

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Authors: Haneef Ur Rehman, Afsheen Aman, Abdul Hameed Baloch, Shah Ali Ul Qader

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Pectinase is a heterogeneous group of enzymes that catalyze the hydrolysis of pectin substances and widely has been used in food and textile industries. In current study, pectinase from B. licheniformis KIBGE-IB21 was immobilized within different polymers (calcium alginate beads, polyacrylamide gel and agar-agar matrix) to enhance its catalytic properties. Polyacrylamide gel was found to be most promising one and gave maximum (89%) immobilization yield. While less immobilization yield was observed in case of calcium alginate beads that only retained 46 % activity. The reaction time for maximum pectinolytic activity was increased from 5.0 to 10 minutes after immobilization. The temperature of pectinase for maximum enzyme activity was increased from 45 °C to 50 °C and 55 °C when it was immobilized within agar-agar and calcium alginate beads, respectively. The optimum pH of pectinase didn’t alter when it was immobilized within polyacrylamide gel and calcium alginate beads, but in case of agar-agar it was changed from pH 10 to pH 9.0. Thermal stability of pectinase was improved after immobilization and immobilized pectinase showed higher toleration against different temperatures as compared to free enzyme. It can be concluded that the entrapment is a simple, single step and promising procedure to immobilized pectinase within different synthetic and non-synthetic polymers and enhanced its catalytic properties.

Keywords: pectinase, characterization immobilization, polyacrylamide, agar-agar, calcium alginate beads

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Authors: Nana Adjoah Mbroh, Suares Clovis Oukouomi Noutchie

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Singularly perturbed problems are parameter dependent problems, and they play major roles in the modelling of real-life situational problems in applied sciences. Thus, designing efficient numerical schemes to solve these problems is of much interest since the exact solutions of such problems may not even exist. Generally, singularly perturbed problems are identified by a small parameter multiplying at least the highest derivative in the equation. The presence of this parameter causes the solution of these problems to be characterized by rapid oscillations. This unique feature renders classical numerical schemes inefficient since they are unable to capture the behaviour of the exact solution in the part of the domain where the rapid oscillations are present. In this paper, a numerical scheme is proposed to solve a singularly perturbed Volterra Integro-differential equation. The scheme is based on the midpoint rule and employs the non-standard finite difference scheme to solve the differential part whilst the composite trapezoidal rule is used for the integral part. A fully fledged error estimate is performed, and Richardson extrapolation is applied to accelerate the convergence of the scheme. Numerical simulations are conducted to confirm the theoretical findings before and after extrapolation.

Keywords: midpoint rule, non-standard finite difference schemes, Richardson extrapolation, singularly perturbed problems, trapezoidal rule, uniform convergence

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Authors: Ricardo Mestre

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The soundscape stands out as an agglomeration of sounds available in the world, associated with different contexts and origins, being a theme studied by various areas of knowledge, seeking to guide their benefits and their consequences, contributing to the welfare of society and other ecosystems. Murray Schafer, the author who originally developed this concept, highlights the need for a greater recognition of sound reality, through the selection and differentiation of sounds, contributing to a tuning of the world and to the balance and well-being of humanity. According to some authors sound environment, produced and created in various ways, provides various sources of information, contributing to the orientation of the human being, alerting and manipulating him during his daily journey, like small notifications received on a cell phone or other device with these features. In this way, it becomes possible to give sound its due importance in relation to the processes of individual representation, in manners of social, professional and emotional life. Ensuring an individual representation means providing the human being with new tools for the long process of reflection by recognizing his environment, the sounds that represent him, and his perspective on his respective function in it. In order to provide more information about the importance of the sound environment inherent to the individual reality, one introduces the term sound instance, in order to refer to the whole sound field existing in the individual's life, which is divided into four distinct subfields, but essential to the process of individual representation, called sound matrix, sound cycles, sound traces and sound interference.

Keywords: sound instance, soundscape, sound art, perception, composition

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Authors: Xiang Jianhong, Wang Cong, Wang Linyu

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With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal ECG, compressed sensing, joint sparse reconstruction, block sparse signal

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Authors: Anika Pallapothu

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Periodontitis, a severe gum disease, poses a significant threat to the integrity of bone and soft tissues supporting teeth, primarily initiated by bacterial accumulation around the gum line. Conventional treatments like scaling/root planning and plaque removal are widely employed, but integrating modern technologies such as nanotechnology holds promise for innovative therapeutic approaches. This study explores the utilization of silver nanoparticles encapsulated within cellulose nanofiber (CNF) and mesoporous bioactive glass hydrogel matrices for periodontitis management. Silver nanoparticles exhibit potent antimicrobial properties by disrupting microbial cell membranes, inducing reactive oxygen species (ROS) generation, and interfering with vital cellular processes like ATP production and nucleic acid synthesis. Mesoporous bioactive glass, renowned for its high surface area, osteoconductive, and bioactivity, presents a favorable platform for pharmaceutical applications. Incorporating CNF enhances the properties of the hydrogel due to its biocompatibility, biodegradability, and water absorption capacity. The proposed composite material is anticipated to exert beneficial effects in periodontitis treatment by demonstrating antibacterial and anti-inflammatory activities, offering a promising avenue for future therapeutic interventions.

Keywords: periodontitis, cellulose nanofibers, silver nanoparticles, mesoporous bioactive glass, antibacterial activity, anti-inflammatory activity

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Authors: Adrian Ionut Nicoara, Denisa Ionela Ene, Alina Maria Holban, Cristina Busuioc

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At present, the development of materials with biomedical applications is a domain of interest that will produce a full series of benefits in engineering and medicine. In this sense, it is required to use a natural material, and this paper is focused on the development of a composite material based on bacterial cellulose – hydroxyapatite and silver nanoparticles with applications in hard tissue. Bacterial cellulose own features like biocompatibility, non-toxicity character and flexibility. Moreover, the bacterial cellulose can be conjugated with different forms of active silver to possess antimicrobial activity. Hydroxyapatite is well known that can mimic at a significant level the activity of the initial bone. The material was synthesized by using an ultrasound probe and finally characterized by several methods. Thereby, the morphological properties were analyzed by using Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). Because the synthesized material has medical application in restore the tissue and to fight against microbial invasion, the samples were tested from the biological point of view by evaluating the biodegradability in phosphate-buffered saline (PBS) and simulated body fluid (SBF) and moreover the antimicrobial effect was performed on Gram-positive bacterium Staphylococcus aureus, Gram-negative bacterium Escherichia coli, and fungi Candida albicans. The results reveal that the obtained material has specific characteristics for bone regeneration.

Keywords: bacterial cellulose, biomaterials, hydroxyapatite, scaffolds materials

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Authors: Biskri Yasmina, Laidi Babouri, Dehas Ouided, Bougherira Nadjiba, Baghloul Rahima

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Algeria is one of the countries which have extraordinary resources in vegetable fibers (Palmier, Alfa, Cotton, Sisal). Unfortunately, their valorization in the practical fields, among other things, in building materials, is still little exploited. Several works align with the fact that the use of plant fibers in mortar is an advantageous solution, given its abundance and its socio-economic and environmental impact. The idea of introducing plant fiber into the field of Civil Engineering is not new. Based on the work of several researchers in this field, we propose to study the mechanical behavior of mortar based on Sisal fibers. This work consists of the experimental characterization in the fresh state (workability) and in the hardened state (mechanical resistance to compression and traction by three-point bending) on the scale of mortar mortars based on sisal plant fibers. The main objective of this work is the study of the effect of fiber incorporation on mechanical properties (compressive strength and three-point bending strength). In this study, we varied two parameters, such as the length of the fiber (7cm, 10 cm) and the fibers percentage (0.25%, 0.5%, 0.75%, 1%, 1.25% and 1.5%). The results show that there is a slight increase in the compressive strength of the fiber-reinforced mortars compared to the reference mortar (mortar without fibers). With regard to the three-point bending tests, the fiber-reinforced mortars presented higher resistances compared to the reference mortar and this was for the different lengths and different percentages studied.

Keywords: mortar, plant fiber, experimentation, mechanical characterization, analysis

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Authors: Karla Lienau, Rafael Müller, René Moré, Debora Ressnig, Dan Cook, Richard Walton, Greta R. Patzke

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The increasing demand for renewable energy sources and storable fuels underscores the high potential of artificial photosynthesis. The four electron transfer process of water oxidation remains the bottleneck of water splitting, so that special emphasis is placed on the development of economic, stable and efficient water oxidation catalysts (WOCs). Our investigations introduced cobalt carbodiimide CoNCN and its transition metal analogues as WOC types, and further studies are focused on the interaction of different transition metals in the convenient all-nitrogen/carbon matrix. This provides further insights into the nature of the ‘true catalyst’ for cobalt centers in this non-oxide environment. Water oxidation activity is evaluated with complementary methods, namely photocatalytically using a Ru-dye sensitized standard setup as well as electrocatalytically, via immobilization of the WOCs on glassy carbon electrodes. To further explore the tuning potential of transition metal combinations, complementary investigations were carried out in oxidic spinel WOC matrices with more versatile host options than the carbodiimide framework. The influence of the preparative history on the WOC performance was evaluated with different synthetic methods (e.g. hydrothermally or microwave assisted). Moreover, the growth mechanism of nanoscale Co3O4-spinel as a benchmark WOC was investigated with in-situ PXRD techniques.

Keywords: carbodiimide, photocatalysis, spinels, water oxidation

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Authors: Prashant Pandey

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In the present article, an effective Laguerre collocation method is used to obtain the approximate solution of a system of coupled fractional-order non-linear reaction-advection-diffusion equation with prescribed initial and boundary conditions. In the proposed scheme, Laguerre polynomials are used together with an operational matrix and collocation method to obtain approximate solutions of the coupled system, so that our proposed model is converted into a system of algebraic equations which can be solved employing the Newton method. The solution profiles of the coupled system are presented graphically for different particular cases. The salient feature of the present article is finding the stability analysis of the proposed method and also the demonstration of the lower variation of solute concentrations with respect to the column length in the fractional-order system compared to the integer-order system. To show the higher efficiency, reliability, and accuracy of the proposed scheme, a comparison between the numerical results of Burger’s coupled system and its existing analytical result is reported. There are high compatibility and consistency between the approximate solution and its exact solution to a higher order of accuracy. The exhibition of error analysis for each case through tables and graphs confirms the super-linearly convergence rate of the proposed method.

Keywords: fractional coupled PDE, stability and convergence analysis, diffusion equation, Laguerre polynomials, spectral method

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Authors: Yina F. Muñoz, Alexander Paz, Hanns De La Fuente-Mella, Joaquin V. Fariña, Guilherme M. Sales

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The primary approach for estimating bridge deterioration uses Markov-chain models and regression analysis. Traditional Markov models have problems in estimating the required transition probabilities when a small sample size is used. Often, reliable bridge data have not been taken over large periods, thus large data sets may not be available. This study presents an important change to the traditional approach by using the Small Data Method to estimate transition probabilities. The results illustrate that the Small Data Method and traditional approach both provide similar estimates; however, the former method provides results that are more conservative. That is, Small Data Method provided slightly lower than expected bridge condition ratings compared with the traditional approach. Considering that bridges are critical infrastructures, the Small Data Method, which uses more information and provides more conservative estimates, may be more appropriate when the available sample size is small. In addition, regression analysis was used to calculate bridge deterioration. Condition ratings were determined for bridge groups, and the best regression model was selected for each group. The results obtained were very similar to those obtained when using Markov chains; however, it is desirable to use more data for better results.

Keywords: concrete bridges, deterioration, Markov chains, probability matrix

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: Yuan Wan, Shumei Cui, Shaopeng Wu

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Toroidal windings were taken advantage of to reduce of axial length of the motor, so as to match the applications that have severe restrictions on the axial length. But slotting in the out edge of the stator will decrease the heat-dissipation capacity of the water cooling of the housing. Besides, the windings in the outer slots will increase the copper loss, which will further increase the difficult for heat dissipation of the motor. At present, carbon-fiber composite retaining sleeve are increasingly used to be mounted over the magnets to ensure the rotor strength at high speeds. Due to the poor thermal conductivity of carbon-fiber sleeve, the cooling of the rotor becomes very difficult, which may result in the irreversible demagnetization of magnets for the excessively high temperature. So it is necessary to analyze the temperature rise of such motor. This paper builds a computational fluid dynamic (CFD) model of a toroidal-winding high-speed permanent magnet synchronous motor (PMSM) with water cooling of housing and forced air cooling of rotor. Thermal analysis was carried out based on the model and the factors that affects the temperature rise were investigated. Then thermal optimization for the prototype was achieved. Finally, a small-size prototype was manufactured and the thermal analysis results were verified.

Keywords: thermal analysis, temperature rise, toroidal windings, high-speed PMSM, CFD

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Authors: Raymond Feng, Shadi Ghiasi

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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

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Authors: Talakokula Visalakshi

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Concrete is the most commonly used construction material across the globe, its usage is second only to water. It is prepared using ordinary Portland cement whose production contributes to 5-8% of total carbon emission in the world. On the other hand the fly ash by product from the power plants is produced in huge quantities is termed as waste and disposed in landfills. In order to address the above issues mentioned, it is essential that other forms of binding material must be developed in place of cement to make concrete. The geo polymer concrete is one such alternative developed by Davidovits in 1980’s. Geopolymer do not form calcium-silicate hydrates for matrix formation and strength but undergo polycondensation of silica and alumina precursors to attain structural strength. Its setting mechanism depends upon polymerization rather than hydration. As a result it is able to achieve its strength in 3-5 days whereas concrete requires about a month to do the same. The objective of this research is to assess the performance of geopolymer concrete under sulphate and acid attack. The assessment is done based on the experiments conducted on geopolymer concrete. The expected outcomes include that if geopolymer concrete is more durable than normal concrete, then it could be a competitive replacement option of concrete and can lead to significant reduction of carbon foot print and have a positive impact on the environment. Fly ash based geopolymer concrete offers an opportunity to completely remove the cement content from concrete thereby making the concrete a greener and future construction material.

Keywords: fly ash, geo polymer, geopolymer concrete, construction material

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Authors: Nacer Eddine Chelbi, Ayet Bagane, Annie Saleh, Claude Sauvageau, Denis Gingras

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As recently stated by National Highway Traffic Safety Administration (NHTSA), to demonstrate the expected performance of a highly automated vehicles system, test approaches should include a combination of simulation, test track, and on-road testing. In this paper, we propose a new validation method for autonomous vehicles involving on-road tests (Field Operational Tests), test track (Test Matrix) and simulation (Worst Case Scenarios). We concentrate our discussion on the simulation aspects, in particular, we extend recent work based on Importance Sampling by using a Metropolis-Hasting algorithm (MHS) to sample collected data from the Safety Pilot Model Deployment (SPMD) in lane-change scenarios. Our proposed MH sampling method will be compared to the Importance Sampling method, which does not perform well in high-dimensional problems. The importance of this study is to obtain a sampler that could be applied to high dimensional simulation problems in order to reduce and optimize the number of test scenarios that are necessary for validation and certification of autonomous vehicles.

Keywords: automated driving, autonomous emergency braking (AEB), autonomous vehicles, certification, evaluation, importance sampling, metropolis-hastings sampling, tests

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Authors: Simon Bard, Martin Demleitner, Florian Schonl, Volker Altstadt

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For an electrically driven aircraft, whose engine is based on semiconductors, alternative materials are needed. The avoid hotspots in the materials thermally conductive polymers are necessary. Nevertheless, the mechanical properties of these materials should remain. Herein, the work of three years in a project with airbus and Siemens is presented. Different strategies have been pursued to achieve conductive fiber-reinforced composites: Metal-coated carbon fibers, pitch-based fibers and particle-loaded matrices have been investigated. In addition, a combination of copper-coated fibers and a conductive matrix has been successfully tested for its conductivity and mechanical properties. First, prepregs have been produced with a laboratory scale prepreg line, which can handle materials with maximum width of 300 mm. These materials have then been processed to fiber-reinforced laminates. For the PAN-fiber reinforced laminates, it could be shown that there is a strong dependency between fiber volume content and thermal conductivity. Laminates with 50 vol% of carbon fiber offer a conductivity of 0.6 W/mK, those with 66 vol% of fiber a thermal conductivity of 1 W/mK. With pitch-based fiber, the conductivity enhances to 1.5 W/mK for 61 vol% of fiber, compared to 0.81 W/mK with the same amount of fibers produced from PAN (+83% in conducitivity). The thermal conductivity of PAN-based composites with 50 vol% of fiber is at 0.6 W/mK, their nickel-coated counterparts with the same fiber volume content offer a conductivity of 1 W/mK, an increase of 66%.

Keywords: carbon, electric aircraft, polymer, thermal conductivity

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Authors: Ogbole Alexandra Simi, Wuyep Solomon Zitta, Monday Seri Nentok, Boilif Yilni Edward, Ocheri Maxwell Idoko

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Vegetables have positive antioxidative properties and are abundant in vitamins, minerals, and fiber. However, if consumed in large quantities, it may be harmful to human health. Therefore, this study assessed the effects of heavy metals on irrigated pepper, cabbage, and Irish potatoes grown in Butura. Atomic absorption spectrophotometry (AA240FS) was used to analyze cadmium (Cd), cobalt (Co), nickel (Ni), lead (Pb), zinc (Zn), copper (Cu), chromium (Cr), and arsenic (As) levels. Three samples were selected from each of the vegetables grown on nine selected farms at distances of 0 m, 10 m, and 30 m. This forms a composite sample of vegetables at each farm. The study showed that the concentrations of cobalt, chromium, cadmium, copper, arsenic, zinc and nickel were within the standard limits set by the FAO/WHO, except for lead, which is higher than the allowable limits for vegetables. These may have behavioral problems, neurological complications, and hematologic disorders for consumers. Thus, these findings could lead to a risk for the human population consuming these vegetables. It is recommended that irrigation water and agricultural soils be constantly monitored to determine the concentration of metals accumulated by crop plants to ensure that crop plants are safe for consumption by humans.

Keywords: vegetable, cabbage, heavy metals, irrigated, Irish potato, Bokkos, pepper

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Authors: YingWei Tan, XueFeng Ding

Abstract:

Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: Feng Zisu

Abstract:

Community is the basic unit of the city, community pedestrian space is also an important part of the urban public space, and its quality improvement is also closely related to the residents' happiness and sense of belonging. Domestic and international research perspectives on community pedestrian space have gradually changed to inclusive design for the whole population, paying more attention to the equitable accessibility of urban space and the multiple composite enhancement of spatial connotation. In order to realize the inclusive and sustainable development of pedestrian space in old communities, this article selects Cao Yang New Village in Shanghai as a practice case, and based on the connotation of inclusiveness, the four dimensions of space, traffic, function and emotion are selected as the layers of inclusive connotation of pedestrian space in old communities. This article identifies the objective social needs, dynamic activity characteristics and subjective feelings of multiple subjects, and reconstructs the structural hierarchy of “spatial perception - behavioral characteristics - subjective feelings” of walking. It also proposes a governance strategy of “reconfiguring the pedestrian network, optimizing street quality, integrating ecological space and reshaping the community scene” from the aspects of quality of physical environment and quality of behavioral perception, aiming to provide new ideas for promoting the inclusive and sustainable development of pedestrian space in old communities.

Keywords: inclusivity, old community, pedestrian space, spatial quality, sustainable renovation

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Authors: Mohammed Abubakar Mawoli

Abstract:

Theory of Planned Behavior (TPB) is a useful tool for predicting entrepreneurial intentions among individuals or groups of people. In view of the Nigerian government’s renewed educational policies and programs to prepare Nigerian undergraduates towards self-reliance and employers of labor after graduation, it becomes pertinent to empirically examine and predict the undergraduate’s entrepreneurial intentions at graduation. Thus, this study primarily examines the undergraduates entrepreneurial intentions using TPB, which includes perceived desirability, perceived social norm, and perceived feasibility factors. In so doing, a questionnaire research method was adopted in which 219 copies of a questionnaire distributed to final year undergraduates were belonging to five departments with a total population of 487 students. A combination of relative frequency, mean standard deviation and multiple regression statistical tools were employed for data analysis. The study found that TPB components exert a significant composite effect on undergraduate’s entrepreneurial intentions. Based on individual contribution of the independent variables, Perceived Desirability is the strongest predictor of the undergraduate’s entrepreneurial intentions, while Perceived Social Norm is a strong predictor of the undergraduate’s entrepreneurial intentions. However, Perceived Feasibility is not a strong predictor of student’s entrepreneurial intentions. The study therefore, recommends that the Perceived desirability, which is formed and shaped by ones level of education and skills acquisition, be improved upon to create the expected positive impact on graduates entrepreneurial intentions and possible venture creation.

Keywords: entrepreneurship, entrepreneurship education, entrepreneurial intentions, planned behaviour, prediction, Nigeria

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Authors: Olga A. Krysiak, Grzegorz Cichowicz, Wojciech Hyk, Michal Cyranski, Jan Augustynski

Abstract:

Metal oxides are known electrocatalyst in water oxidation reaction. Due to the fact that it is desirable for efficient oxygen evolution catalyst to contain numerous redox-active metal ions to guard four electron water oxidation reaction, mixed metal oxides exhibit enhanced catalytic activity towards oxygen evolution reaction compared to single metal oxide systems. On the surface of fluorine doped tin oxide coated glass slide (FTO) deposited (doctor blade technique) mixed metal oxide layer composed of nickel, iron, and chromium. Oxide coating was acquired by heat treatment of the aqueous precursors' solutions of the corresponding salts. As-prepared electrodes were photosensitive and acted as an efficient oxygen evolution catalyst. Our results showed that obtained by this method electrodes can be activated which leads to achieving of higher current densities. The recorded current and photocurrent associated with oxygen evolution process were at least two orders of magnitude higher in the presence of oxide layer compared to bare FTO electrode. The overpotential of the process is low (ca. 0,2 V). We have also checked the activity of the catalyst at different known photoanodes used in sun-driven water splitting. Herein, we demonstrate that we were able to achieve efficient oxygen evolution catalysts using relatively cheap precursor consisting of earth abundant metals and simple method of preparation.

Keywords: chromium, electrocatalysis, iron, metal oxides, nickel, oxygen evolution

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Authors: Nixon Kuruvila, H. V. Ravindra

Abstract:

Wire-cut Electro Discharge Machining (WEDM) is a special form of conventional EDM process in which electrode is a continuously moving conductive wire. The present study aims at determining parametric influence and optimum process parameters of Wire-EDM using Taguchi’s Technique and Genetic algorithm. The variation of the performance parameters with machining parameters was mathematically modeled by Regression analysis method. The objective functions are Dimensional Accuracy (DA) and Material Removal Rate (MRR). Experiments were designed as per Taguchi’s L16 Orthogonal Array (OA) where in Pulse-on duration, Pulse-off duration, Current, Bed-speed and Flushing rate have been considered as the important input parameters. The matrix experiments were conducted for the material Oil Hardened Non Shrinking Steel (OHNS) having the thickness of 40 mm. The results of the study reveals that among the machining parameters it is preferable to go in for lower pulse-off duration for achieving over all good performance. Regarding MRR, OHNS is to be eroded with medium pulse-off duration and higher flush rate. Finally, the validation exercise performed with the optimum levels of the process parameters. The results confirm the efficiency of the approach employed for optimization of process parameters in this study.

Keywords: dimensional accuracy (DA), regression analysis (RA), Taguchi method (TM), volumetric material removal rate (VMRR)

Procedia PDF Downloads 409