Search results for: permittivity measurement techniques

Authors: A. S. V. Carvalho, J. Luis, L. S. O. Pires, J. M. Oliveira

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Additive manufacturing technologies (AM) experienced a remarkable growth in the latest years due to the development and diffusion of a wide range of three-dimensional (3D) printing techniques. Nowadays we can find techniques available for non-industrial users, like fused filament fabrication, but techniques like 3D printing, polyjet, selective laser sintering and stereolithography are mainly spread in the industry. Robocasting (R3D) shows a great potential due to its ability to shape materials with a wide range of viscosity. Industrial porcelain compositions showing different rheological behaviour can be prepared and used as candidate materials to be processed by R3D. The use of this AM technique in industry is very residual. In this work, a specific porcelain composition with suitable rheological properties will be processed by R3D, and a systematic study of the printing parameters tuning will be shown. The porcelain composition was formulated based on an industrial spray dried porcelain powder. The powder particle size and morphology was analysed. The powders were mixed with water and an organic binder on a ball mill at 200 rpm/min for 24 hours. The batch viscosity was adjusted by the addition of an acid solution and mixed again. The paste density, viscosity, zeta potential, particle size distribution and pH were determined. In a R3D system, different speed and pressure settings were studied to access their impact on the fabrication of porcelain models. These models were dried at 80 °C, during 24 hours and sintered in air at 1350 °C for 2 hours. The stability of the models, its walls and surface quality were studied and their physical properties were accessed. The microstructure and layer adhesion were observed by SEM. The studied processing parameters have a high impact on the models quality. Moreover, they have a high impact on the stacking of the filaments. The adequate tuning of the parameters has a huge influence on the final properties of the porcelain models. This work contributes to a better assimilation of AM technologies in ceramic industry. Acknowledgments: The RoboCer3D project – project of additive rapid manufacturing through 3D printing ceramic material (POCI-01-0247-FEDER-003350) financed by Compete 2020, PT 2020, European Regional Development Fund – FEDER through the International and Competitive Operational Program (POCI) under the PT2020 partnership agreement.

Keywords: additive manufacturing, porcelain, robocasting, R3D

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Authors: Young Jae Choung, Seoung Bum Kim

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Statistical Process Control (SPC) is a popular technique for process monitoring. A widely used tool in SPC is a control chart, which is used to detect the abnormal status of a process and maintain the controlled status of the process. Traditional control charts, such as Hotelling’s T2 control chart, are effective techniques to detect abnormal observations and monitor processes. However, many complicated manufacturing systems exhibit nonlinearity because of the different demands of the market. In this case, the unregulated use of a traditional linear modeling approach may not be effective. In reality, many industrial processes contain the nonlinear and time-varying properties because of the fluctuation of process raw materials, slowing shift of the set points, aging of the main process components, seasoning effects, and catalyst deactivation. The use of traditional SPC techniques with time-varying data will degrade the performance of the monitoring scheme. To address these issues, in the present study, we propose a parameterless self-organizing map (PLSOM)-based control chart. The PLSOM-based control chart not only can manage a situation where the distribution or parameter of the target observations changes, but also address the nonlinearity of modern manufacturing systems. The control limits of the proposed PLSOM chart are established by estimating the empirical level of significance on the percentile using a bootstrap method. Experimental results with simulated data and actual process data from a thin-film transistor-liquid crystal display process demonstrated the effectiveness and usefulness of the proposed chart.

Keywords: control chart, parameter-less self-organizing map, self-organizing map, time-varying property

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Authors: Pedro Ferraz-Gameiro

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Introduction: The Pellegrini-Stieda lesion is the result of post-traumatic calcification and/or ossification on the medial collateral ligament (MCL) of the knee. When this calcification is accompanied by gonalgia and limitation of knee flexion, it is called Pellegrini-Stieda syndrome. The pathogenesis is probably the calcification of a post-traumatic hematoma at least three weeks after the initial trauma or secondary to repetitive microtrauma. On anteroposterior radiographs, a Pellegrini-Stieda lesion is a linear vertical ossification or calcification of the proximal portion of the MCL and usually near the medial femoral condyle. Patients with Pellegrini-Stieda syndrome present knee pain associated with loss of range of motion. The treatment is usually conservative with analgesic and anti-inflammatory drugs, either systemic or intra-articular. Physical medicine and rehabilitation techniques associated with shock wave therapy can be a way of reduction of pain/inflammation. Patients who maintain instability with significant limitation of knee mobility may require surgical excision. Methods: Research was done using PubMed central using the terms Pellegrini-Stieda syndrome. Discussion/conclusion: Medical treatment is the rule, with initial rest, anti-inflammatory, and physiotherapy. If left untreated, this ossification can potentially form a significant bone mass, which can compromise the range of motion of the knee. Physical medicine and rehabilitation techniques associated with shock wave therapy are a way of reduction of pain/inflammation.

Keywords: knee, Pellegrini-Stieda syndrome, rehabilitation, shock waves therapy

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Authors: Jarek Krajewski, David Daxberger, Luzi Beyer

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Finding objective and non-intrusive measurements of emotional and psychopathological states (e.g., post-traumatic stress disorder, PTSD) is an important challenge. Thus, the proposed approach here uses Photoplethysmographic imaging (PPGI) applying facial RGB Cam videos to estimate heart rate levels. A pipeline for the signal processing of the raw image has been proposed containing different preprocessing approaches, e.g., Independent Component Analysis, Non-negative Matrix factorization, and various other artefact correction approaches. Under resting and constant light conditions, we reached a sensitivity of 84% for pulse peak detection. The results indicate that PPGI can be a suitable solution for providing heart rate data derived from these indirectly post-traumatic stress states.

Keywords: heart rate, PTSD, PPGI, stress, preprocessing

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Authors: Udeh Nneka Evelyn

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The shortcoming of traditional costing system in terms of validity, accuracy, consistency, and Relevance increased the need for modern management accounting system. Activity –Based Costing (ABC) can be used as a modern tool for planning, Control and decision making for management. Past studies on ABC system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing technique in service oriented business organizations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on ABC. Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry and government organization. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: identification the most profitable customers: more accurate product and service pricing: increase product profitability: Well organized process costs.

Keywords: business, costing, organizations, planning, techniques

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Authors: Lennart Dimberg, Lala Joulha Ian

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Introduction: Overweight (BMI 25-30) and obesity (BMI 30+) have consistently been associated with cardiovascular (CV) risk and death since the Framingham heart study in 1948, and BMI was included in the original Framingham risk score (FRS). Background: Myocardial infarction (MI) poses a serious threat to the patient's life. In addition to BMI, several other indices of overweight have been presented and argued to replace FRS as more relevant measures of CV risk. These indices include waist circumference (WC), waist/hip ratio (WHR), sagittal abdominal diameter (SAD), and sagittal abdominal diameter to height (SADHtR). Specific research question: The research question of this study is to evaluate the interrelationship between the various body measurements, BMI, WC, WHR, SAD, and SADHtR, and which measurement is strongly associated with MI and death. Methods: In 1993, 1,000 middle-aged Caucasian, randomly selected working men of the Swedish Volvo-Renault cohort were surveyed at a nurse-led health examination with a questionnaire, EKG, laboratory tests, blood pressure, height, weight, waist, and sagittal abdominal diameter measurements. Outcome data of myocardial infarction over 28 years come from Swedeheart (the Swedish national myocardial infarction registry) and the Swedish death registry. The Aalen-Johansen and Kaplan–Meier methods were used to estimate the cumulative incidences of MI and death. Multiple logistic regression analyses were conducted to compare BMI with the other four body measurements. The risk for the various measures of obesity was calculated with outcomes of accumulated first-time myocardial infarction and death as odds ratios (OR) in quartiles. The ORs between the 4th and the 1st quartile of each measure were calculated to estimate the association between the body measurement variables and the probability of cumulative incidences of myocardial infarction (MI) over time. Double-sided P values below 0.05 will be considered statistically significant. Unadjusted odds ratios were calculated for obesity indicators, MI, and death. Adjustments for age, diabetes, SBP, and the ratio of total cholesterol/HDL-C and blue/white collar status were performed. Results: Out of 1000 people, 959 subjects had full information about the five different body measurements. Of those, 90 participants had a first MI, and 194 persons died. The study showed that there was a high and significant correlation between the five different body measurements, and they were all associated with CVD risk factors. All body measurements were significantly associated with MI, with the highest (OR=3.6) seen for SADHtR and WC. After adjustment, all but SADHtR remained significant with weaker ORs. As for all-cause mortality, WHR (OR=1.7), SAD (OR=1.9), and SADHtR (OR=1.6) were significantly associated, but not WC and BMI. However, after adjustment, only WHR and SAD were significantly associated with death, but with attenuated ORs.

Keywords: BMI, death, epidemiology, myocardial infarction, risk factor, sagittal abdominal diameter, sagittal abdominal diameter to height, waist circumference, waist-hip ratio

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Authors: Viney Dixit, Rohit R. Shahi, Ashish Bhatnagar, P. Jain, T. P. Yadav, O. N. Srivastava

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Carbons are being widely investigated as hydrogen storage material owing to their light weight, fast hydrogen absorption kinetics and low cost. However, these materials suffer from low hydrogen storage capacity at room temperature. The aim of the present study is to synthesize carbon based material which shows moderate hydrogen storage at room temperature. For this purpose, hydrogenation characteristics of natural precursor coconut kernel is studied in this work. The hydrogen storage measurement reveals that the as-synthesized materials have good hydrogen adsorption and desorption capacity with fast kinetics. The synthesized material absorbs 8 wt.% of hydrogen at liquid nitrogen temperature and 2.3 wt.% at room temperature. This could be due to the presence of certain elements (KCl, Mg, Ca) which are confirmed by TEM.

Keywords: coconut kernel, carbonization, hydrogenation, KCl, Mg, Ca

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Authors: Ömer Tamer, Davut Avcı, Yusuf Atalay

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Novel picolinate complex of manganese(II) ion, [Mn(pic)2] [pic: picolinate or 2-pyridinecarboxylate], was prepared and fully characterized by single crystal X-ray structure determination. The manganese(II) complex was characterized by FT-IR, FT-Raman and UV–Vis spectroscopic techniques. The C=O, C=N and C=C stretching vibrations were found to be strong and simultaneously active in IR and spectra. In order to support these experimental techniques, density functional theory (DFT) calculations were performed at Gaussian 09W. Although the supramolecular interactions have some influences on the molecular geometry in solid state phase, the calculated data show that the predicted geometries can reproduce the structural parameters. The molecular modeling and calculations of IR, Raman and UV-vis spectra were performed by using DFT levels. Nonlinear optical (NLO) properties of synthesized complex were evaluated by the determining of dipole moment (µ), polarizability (α) and hyperpolarizability (β). Obtained results demonstrated that the manganese(II) complex is a good candidate for NLO material. Stability of the molecule arising from hyperconjugative interactions and charge delocalization was analyzed using natural bond orbital (NBO) analysis. The highest occupied and the lowest unoccupied molecular orbitals (HOMO and LUMO) which is also known the frontier molecular orbitals were simulated, and obtained energy gap confirmed that charge transfer occurs within manganese(II) complex. Molecular electrostatic potential (MEP) for synthesized manganese(II) complex displays the electrophilic and nucleophilic regions. From MEP, the the most negative region is located over carboxyl O atoms while positive region is located over H atoms.

Keywords: DFT, picolinate, IR, Raman, nonlinear optic

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Authors: A. S. Ibrahim Mamane, S. Giljean, M.-J. Pac, G. L’Hostis

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Fiber reinforced composite laminates are particularly subject to residual stresses due to their heterogeneity and the complex chemical, mechanical and thermal mechanisms that occur during their processing. Residual stresses are now well known to cause damage accumulation, shape instability, and behavior disturbance in composite parts. Many works exist in the literature on techniques for minimizing residual stresses in thermosetting and thermoplastic composites mainly. To study in-depth the influence of processing mechanisms on the formation of residual stresses and to minimize them by establishing a reliable correlation, it is essential to be able to measure very precisely the profile of residual stresses in the composite. Residual stresses are important data to consider when sizing composite parts and predicting their behavior. The incremental hole drilling is very effective in measuring the gradient of residual stresses in composite laminates. This method is semi-destructive and consists of drilling incrementally a hole through the thickness of the material and measuring relaxation strains around the hole for each increment using three strain gauges. These strains are then converted into residual stresses using a matrix of coefficients. These coefficients, called calibration coefficients, depending on the diameter of the hole and the dimensions of the gauges used. The reliability of the incremental hole drilling depends on the accuracy with which the calibration coefficients are determined. These coefficients are calculated using a finite element model. The samples’ features and the experimental conditions must be considered in the simulation. Any mismatch can lead to inadequate calibration coefficients, thus introducing errors on residual stresses. Several calibration coefficient correction methods exist for isotropic material, but there is a lack of information on this subject concerning composite laminates. In this work, a Python program was developed to automatically generate the adequate finite element model. This model allowed us to perform a parametric study to assess the influence of experimental errors on the calibration coefficients. The results highlighted the sensitivity of the calibration coefficients to the considered errors and gave an order of magnitude of the precisions required on the experimental device to have reliable measurements. On the basis of these results, improvements were proposed on the experimental device. Furthermore, a numerical method was proposed to correct the calibration coefficients for different types of materials, including thick composite parts for which the analytical approach is too complex. This method consists of taking into account the experimental errors in the simulation. Accurate measurement of the experimental errors (such as eccentricity of the hole, angular deviation of the gauges from their theoretical position, or errors on increment depth) is therefore necessary. The aim is to determine more precisely the residual stresses and to expand the validity domain of the incremental hole drilling technique.

Keywords: fiber reinforced composites, finite element simulation, incremental hole drilling method, numerical correction of the calibration coefficients, residual stresses

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Authors: Majid Hejazian, Nam-Trung Nguyen

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Over the past few years, microfluidic devices have generated significant attention from industry and academia due to advantages such as small sample volume, low cost and high efficiency. Microfluidic devices have applications in chemical, biological and industry analysis and can facilitate assay of bio-materials and chemical reactions, separation, and sensing. Micromixers are one of the important microfluidic concepts. Micromixers can work as stand-alone devices or be integrated in a more complex microfluidic system such as a lab on a chip (LOC). Micromixers are categorized as passive and active types. Passive micromixers rely only on the arrangement of the phases to be mixed and contain no moving parts and require no energy. Active micromixers require external fields such as pressure, temperature, electric and acoustic fields. Rapid and efficient mixing is important for many applications such as biological, chemical and biochemical analysis. Achieving fast and homogenous mixing of multiple samples in the microfluidic devices has been studied and discussed in the literature recently. Improvement in mixing rely on effective mass transport in microscale, but are currently limited to molecular diffusion due to the predominant laminar flow in this size scale. Using magnetic field to elevate mass transport is an effective solution for mixing enhancement in microfluidics. The use of a non-uniform magnetic field to improve mass transfer performance in a microfluidic device is demonstrated in this work. The phenomenon of mixing ferrofluid and DI-water streams has been reported before, but mass transfer enhancement for other non-magnetic species through magnetic field have not been studied and evaluated extensively. In the present work, permanent magnets were used in a simple microfluidic device to create a non-uniform magnetic field. Two streams are introduced into the microchannel: one contains fluorescent dye mixed with diluted ferrofluid to induce enhanced mass transport of the dye, and the other one is a non-magnetic DI-water stream. Mass transport enhancement of fluorescent dye is evaluated using fluorescent measurement techniques. The concentration field is measured for different flow rates. Due to effect of magnetic field, a body force is exerted on the paramagnetic stream and expands the ferrofluid stream into non-magnetic DI-water flow. The experimental results demonstrate that without a magnetic field, both magnetic nanoparticles of the ferrofluid and the fluorescent dye solely rely on molecular diffusion to spread. The non-uniform magnetic field, created by the permanent magnets around the microchannel, and diluted ferrofluid can improve mass transport of non-magnetic solutes in a microfluidic device. The susceptibility mismatch between the fluids results in a magnetoconvective secondary flow towards the magnets and subsequently the mass transport of the non-magnetic fluorescent dye. A significant enhancement in mass transport of the fluorescent dye was observed. The platform presented here could be used as a microfluidics-based micromixer for chemical and biological applications.

Keywords: ferrofluid, mass transfer, micromixer, microfluidics, magnetic

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Authors: Walaa Hamed Mohamed Hamza

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Textile structures are the way in which the threading process of both thread and loom is done together to form the woven. Different methods of attaching the clothing and the flesh produce different textile structures, which differ in their surface appearance from each other, including so-called simple textile structures. Textile compositions are the basis of woven fabric, through which aesthetic values can be achieved in the textile industry by weaving threads of yarn with the weft at varying degrees that may reach the total control of one of the two groups on the other. Hence the idea of how art and design can be used using different textile structures under the modern techniques of pate de verre. In the creation of designs suitable for glass products employed in the interior architecture. The problem of research: The textile structures, in general, have a significant impact on the appearance of the fabrics in terms of form and aesthetic. How can we benefit from the characteristics of different textile compositions in different glass designs with different artistic values. The research achieves its goal by the investment of simple textile structures in innovative artistic designs using the pate de verre technique, as well as the use of designs resulting from the textile structures in the external architecture to add various aesthetic values. The importance of research in the revival of heritage using ancient techniques, as well as synergy between different fields of applied arts such as glass and textile, and also study the different and diverse effects resulting from each fabric composition and the possibility of use in various designs in the interior architecture. The research will be achieved that by investing in simple textile compositions, innovative artistic designs produced using pate de verre technology can be used in interior architecture.

Keywords: glass, interior architecture, pate de verre, textile structures

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Authors: Ragea Alqahtani

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The purpose of the study was to measure the effectiveness of the Goldstein’s social skill streaming model based on the special and general pre-service teachers’ knowledge about controlling their emotions in conflict situations. A review of previous pieces of literature guided the design and measurement of the effectiveness of the approach to the control of emotions. The teachers were assessed using the coping strategy, adult anger, and Goldstein’s skill streaming inventories. Lastly, the paper provides various recommendations on the sensitization of the Goldstein’s Social Skill streaming model to both the special and pre-service teachers to promote their knowledge about controlling emotions in conflicts.

Keywords: emotional control, Goldstein social skill streaming model, modeling technique, self- as-a-model, self-efficacy, self-regulation

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Authors: Hamed Ahari, Behrouz Akbari Adreghani, Vadood Razavilar, Amirali Anvar, Sima Moradi, Hourieh Shalchi

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Considering the ever increasing population and industrialization of the developmental trend of humankind's life, we are no longer able to detect the toxins produced in food products using the traditional techniques. This is due to the fact that the isolation time for food products is not cost-effective and even in most of the cases, the precision in the practical techniques like the bacterial cultivation and other techniques suffer from operator errors or the errors of the mixtures used. Hence with the advent of nanotechnology, the design of selective and smart sensors is one of the greatest industrial revelations of the quality control of food products that in few minutes time, and with a very high precision can identify the volume and toxicity of the bacteria. Methods and Materials: In this technique, based on the bacterial antibody connection to nanoparticle, a sensor was used. In this part of the research, as the basis for absorption for the recognition of bacterial toxin, medium sized silica nanoparticles of 10 nanometer in form of solid powder were utilized with Notrino brand. Then the suspension produced from agent-linked nanosilica which was connected to bacterial antibody was positioned near the samples of distilled water, which were contaminated with Staphylococcus aureus bacterial toxin with the density of 10-3, so that in case any toxin exists in the sample, a connection between toxin antigen and antibody would be formed. Finally, the light absorption related to the connection of antigen to the particle attached antibody was measured using spectrophotometry. The gene of 23S rRNA that is conserved in all Staphylococcus spp., also used as control. The accuracy of the test was monitored by using serial dilution (l0-6) of overnight cell culture of Staphylococcus spp., bacteria (OD600: 0.02 = 107 cell). It showed that the sensitivity of PCR is 10 bacteria per ml of cells within few hours. Result: The results indicate that the sensor detects up to 10-4 density. Additionally, the sensitivity of the sensors was examined after 60 days, the sensor by the 56 days had confirmatory results and started to decrease after those time periods. Conclusions: Comparing practical nano biosensory to conventional methods like that culture and biotechnology methods(such as polymerase chain reaction) is accuracy, sensitiveness and being unique. In the other way, they reduce the time from the hours to the 30 minutes.

Keywords: exotoxin, nanobiosensor, recognition, Staphylococcus aureus

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Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Essam Amerian

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The aim of this study was to investigate the effects of improving waist-to-hip ratio (WHR) and visceral fat components on the health of shift workers in an offshore petrochemical company. A total of 100 male shift workers participated in the study, with an average age of 40.5 years and an average BMI of 28.2 kg/m². The study employed a randomized controlled trial design, with participants assigned to either an intervention group or a control group. The intervention group received a 12-week program that included dietary counseling, physical activity recommendations, and stress management techniques. The control group received no intervention. The outcomes measured were changes in WHR, visceral fat components, blood pressure, and lipid profile. The results showed that the intervention group had a statistically significant improvement in WHR (p<0.001) and visceral fat components (p<0.001) compared to the control group. Furthermore, there were statistically significant improvements in systolic blood pressure (p=0.015) and total cholesterol (p=0.034) in the intervention group compared to the control group. These findings suggest that implementing a 12-week program that includes dietary counseling, physical activity recommendations, and stress management techniques can effectively improve WHR, visceral fat components, and cardiovascular health among shift workers in an offshore petrochemical company.

Keywords: body composition, waist-hip-ratio, visceral fat, shift worker, work efficiency

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Authors: Maria Fonseca, Ana Branco, Joao Graca, Rui Mendes, Pedro Mimoso

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The present work is focused on the production of a carbon composite element for cycling through different techniques, namely, blow-molding and high-pressure resin transfer injection (HP-RTM). The main objective of this work is to compare both processes to produce carbon composite elements for the cycling industry. It is well known that the carbon composite components for cycling are produced mainly through blow-molding; however, this technique depends strongly on manual labour, resulting in a time-consuming production process. Comparatively, HP-RTM offers a more automated process which should lead to higher production rates. Nevertheless, a comparison of the elements produced through both techniques must be done, in order to assess if the final products comply with the required standards of the industry. The main difference between said techniques lies in the used material. Blow-moulding uses carbon prepreg (carbon fibres pre-impregnated with a resin system), and the material is laid up by hand, piece by piece, on a mould or on a hard male. After that, the material is cured at a high temperature. On the other hand, in the HP-RTM technique, dry carbon fibres are placed on a mould, and then resin is injected at high pressure. After some research regarding the best material systems (prepregs and braids) and suppliers, an element was designed (similar to a handlebar) to be constructed. The next step was to perform FEM simulations in order to determine what the best layup of the composite material was. The simulations were done for the prepreg material, and the obtained layup was transposed to the braids. The selected material was a prepreg with T700 carbon fibre (24K) and an epoxy resin system, for the blow-molding technique. For HP-RTM, carbon fibre elastic UD tubes and ± 45º braids were used, with both 3K and 6K filaments per tow, and the resin system was an epoxy as well. After the simulations for the prepreg material, the optimized layup was: [45°, -45°,45°, -45°,0°,0°]. For HP-RTM, the transposed layup was [ ± 45° (6k); 0° (6k); partial ± 45° (6k); partial ± 45° (6k); ± 45° (3k); ± 45° (3k)]. The mechanical tests showed that both elements can withstand the maximum load (in this case, 1000 N); however, the one produced through blow-molding can support higher loads (≈1300N against 1100N from HP-RTM). In what concerns to the fibre volume fraction (FVF), the HP-RTM element has a slightly higher value ( > 61% compared to 59% of the blow-molding technique). The optical microscopy has shown that both elements have a low void content. In conclusion, the elements produced using HP-RTM can compare to the ones produced through blow-molding, both in mechanical testing and in the visual aspect. Nevertheless, there is still space for improvement in the HP-RTM elements since the layup of the braids, and UD tubes could be optimized.

Keywords: HP-RTM, carbon composites, cycling, FEM

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: Alpana Saini, Sanghamitra Barman

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Investigations were carried out to determine whether low cost peanut hull as adsorbent hold promise in removal of thionine dyes in the biomedical industries. Pollution of water due to presence of colorants is a severe socio-environmental problem caused by the discharge of industrial wastewater. In view of their toxicity, non-biodegradability and persistent nature, their removal becomes an absolute necessity. For the removal of Thionine Dye using Peanut Hull, the 10mg/L concentration of dyes, 0.5g/l of adsorbent and 200 rpm agitation speed are found to be optimum for the adsorption studies. The Spectrophotometric technique was adopted for the measurement of concentration of dyes before and after adsorption at ʎmax 598nm. The adsorption data has been fitted well to Langmuir isotherm than to Freundlich adsorption isotherm. The adsorbent was characterized by Scanning Electron Microscopy (SEM).

Keywords: adsorption, langmuir isotherm, peanut hull, thionine

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Authors: L. Freeborn

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Recent years have seen an increasing number of neuroimaging studies related to language learning as imaging techniques such as fMRI and EEG have become more widely accessible to researchers. By using a variety of structural and functional neuroimaging techniques, these studies have already made considerable progress in terms of our understanding of neural networks and processing related to first and second language acquisition. However, the methodological designs employed in neuroimaging studies to test language learning have been questioned by applied linguists working within the field of second language acquisition (SLA). One of the major criticisms is that tasks designed to measure language learning gains rarely have a communicative function, and seldom assess learners’ ability to use the language in authentic situations. This brings the validity of many neuroimaging tasks into question. The fundamental reason why people learn a language is to communicate, and it is well-known that both first and second language proficiency are developed through meaningful social interaction. With this in mind, the SLA field is in agreement that second language acquisition and proficiency should be measured through learners’ ability to communicate in authentic real-life situations. Whilst authenticity is not always possible to achieve in a classroom environment, the importance of task authenticity should be reflected in the design of language assessments, teaching materials, and curricula. Tasks that bear little relation to how language is used in real-life situations can be considered to lack construct validity. This paper first describes the typical tasks used in neuroimaging studies to measure language gains and proficiency, then analyses to what extent these tasks can validly assess these constructs.

Keywords: neuroimaging studies, research design, second language acquisition, task validity

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Mohammad A. Bani-Khaled

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In this work we use the Discrete Proper Orthogonal Decomposition transform to characterize the properties of coupled dynamics in thin-walled beams by exploiting numerical simulations obtained from finite element simulations. The outcomes of the will improve our understanding of the linear and nonlinear coupled behavior of thin-walled beams structures. Thin-walled beams have widespread usage in modern engineering application in both large scale structures (aeronautical structures), as well as in nano-structures (nano-tubes). Therefore, detailed knowledge in regard to the properties of coupled vibrations and buckling in these structures are of great interest in the research community. Due to the geometric complexity in the overall structure and in particular in the cross-sections it is necessary to involve computational mechanics to numerically simulate the dynamics. In using numerical computational techniques, it is not necessary to over simplify a model in order to solve the equations of motions. Computational dynamics methods produce databases of controlled resolution in time and space. These numerical databases contain information on the properties of the coupled dynamics. In order to extract the system dynamic properties and strength of coupling among the various fields of the motion, processing techniques are required. Time- Proper Orthogonal Decomposition transform is a powerful tool for processing databases for the dynamics. It will be used to study the coupled dynamics of thin-walled basic structures. These structures are ideal to form a basis for a systematic study of coupled dynamics in structures of complex geometry.

Keywords: coupled dynamics, geometric complexity, proper orthogonal decomposition (POD), thin walled beams

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Authors: Khaled M. El Naggar

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This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection.

Keywords: optimization, estimation, faults, measurement, high voltage, simulated annealing

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Authors: Miesam Golzadeh Gangraj, Younes Parvasi, Mohammad Ghasemi, Ahmad Abdi, Saeid Fazelifar

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The purpose of the study was to determine the effect of glucose feeding on energy and hormonal indexes in plasma and lymphocyte immediately after wrestling – base techniques circuit exercise (WBTCE) in young male freestyle wrestlers. Sixteen wrestlers (weight = 75/45 ± 12/92 kg, age = 22/29 ± 0/90 years, BMI = 26/23 ± 2/64 kg/m²) were randomly divided into two groups: control (water), glucose (2 gr per kg body weight). Blood samples were obtained before, immediately, and 90 minutes of the post-exercise recovery period. Glucose (2 g/kg of body weight, 1W/5V) and water (equal volumes) solutions were given immediately after the second blood sampling. Data were analyzed by using an ANOVA (a repeated measure) and a suitable post hoc test (LSD). A significant decrease was observed in lymphocytes glycogen immediately after exercise (P < 0.001). In the experimental group, increase Lymphocyte glycogen concentration (P < 0.028) than in the control group in 90 min post-exercise. Plasma glucose concentrations increased in all groups immediately after exercise (P < 0.05). Plasma insulin concentrations in both groups decreased immediately after exercise, but at 90 min after exercise, its level was significantly increased only in glucose group (P < 0.001). Our results suggested that WBTCE protocol could be affected cellular energy sources and hormonal response. Furthermore, Glucose consumption can increase the lymphocyte glycogen and better energy within the cell.

Keywords: glucose feeding, lymphocyte, Wrestling – base techniques circuit , exercise

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Authors: Javid Iqbal, Zhu Shifan

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The development in the construction of unconventional ships and the implementation of lightweight materials have shown a large impulse towards finite element (FE) method, making it a general tool for ship design. This paper briefly presents the modeling and analysis techniques of ship structures using FE method for complex boundary conditions which are difficult to analyze by existing Ship Classification Societies rules. During operation, all ships experience complex loading conditions. These loads are general categories into thermal loads, linear static, dynamic and non-linear loads. General strength of the ship structure is analyzed using static FE analysis. FE method is also suitable to consider the local loads generated by ballast tanks and cargo in addition to hydrostatic and hydrodynamic loads. Vibration analysis of a ship structure and its components can be performed using FE method which helps in obtaining the dynamic stability of the ship. FE method has developed better techniques for calculation of natural frequencies and different mode shapes of ship structure to avoid resonance both globally and locally. There is a lot of development towards the ideal design in ship industry over the past few years for solving complex engineering problems by employing the data stored in the FE model. This paper provides an overview of ship modeling methodology for FE analysis and its general application. Historical background, the basic concept of FE, advantages, and disadvantages of FE analysis are also reported along with examples related to hull strength and structural components.

Keywords: dynamic analysis, finite element methods, ship structure, vibration analysis

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Authors: Ka C. Lam, Oluwafunmibi S. Idowu

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Uncertainty in cost is a major factor affecting performance of construction projects. To our knowledge, several conceptual cost models have been developed with varying degrees of accuracy. Incorporating conceptual quantities into conceptual cost models could improve the accuracy of early predesign cost estimates. Hence, the development of quantity models for estimating conceptual quantities of framed reinforced concrete structures using supervised machine learning is the aim of the current research. Using measured quantities of structural elements and design variables such as live loads and soil bearing pressures, response and predictor variables were defined and used for constructing conceptual quantities models. Twenty-four models were developed for comparison using a combination of non-parametric support vector regression, linear regression, and bootstrap resampling techniques. R programming language was used for data analysis and model implementation. Gross soil bearing pressure and gross floor loading were discovered to have a major influence on the quantities of concrete and reinforcement used for foundations. Building footprint and gross floor loading had a similar influence on beams and slabs. Future research could explore the modelling of other conceptual quantities for walls, finishes, and services using machine learning techniques. Estimation of conceptual quantities would assist construction planners in early resource planning and enable detailed performance evaluation of early cost predictions.

Keywords: bootstrapping, conceptual quantities, modelling, reinforced concrete, support vector regression

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Authors: Taro Komori, Toshiki Gushi, Akihito Anzai, Taku Hirose, Kaoru Toko, Shinji Isogami, Takashi Suemasu

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Ferrimagnetic antiperovskite Mn₄₋ₓNiₓN thin film exhibits both small saturation magnetization and rather large perpendicular magnetic anisotropy (PMA) when x is small. Both of them are suitable features for application to current induced domain wall motion devices using spin transfer torque (STT). In this work, we successfully grew antiperovskite 30-nm-thick Mn₄₋ₓNiₓN epitaxial thin films on MgO(001) and STO(001) substrates by MBE in order to investigate their crystalline qualities and magnetic and magneto-transport properties. Crystalline qualities were investigated by X-ray diffraction (XRD). The magnetic properties were measured by vibrating sample magnetometer (VSM) at room temperature. Anomalous Hall effect was measured by physical properties measurement system. Both measurements were performed at room temperature. Temperature dependence of magnetization was measured by VSM-Superconducting quantum interference device. XRD patterns indicate epitaxial growth of Mn₄₋ₓNiₓN thin films on both substrates, ones on STO(001) especially have higher c-axis orientation thanks to greater lattice matching. According to VSM measurement, PMA was observed in Mn₄₋ₓNiₓN on MgO(001) when x ≤ 0.25 and on STO(001) when x ≤ 0.5, and MS decreased drastically with x. For example, MS of Mn₃.₉Ni₀.₁N on STO(001) was 47.4 emu/cm³. From the anomalous Hall resistivity (ρAH) of Mn₄₋ₓNiₓN thin films on STO(001) with the magnetic field perpendicular to the plane, we found out Mr/MS was about 1 when x ≤ 0.25, which suggests large magnetic domains in samples and suitable features for DW motion device application. In contrast, such square curves were not observed for Mn₄₋ₓNiₓN on MgO(001), which we attribute to difference in lattice matching. Furthermore, it’s notable that although the sign of ρAH was negative when x = 0 and 0.1, it reversed positive when x = 0.25 and 0.5. The similar reversal occurred for temperature dependence of magnetization. The magnetization of Mn₄₋ₓNiₓN on STO(001) increases with decreasing temperature when x = 0 and 0.1, while it decreases when x = 0.25. We considered that these reversals were caused by magnetic compensation which occurred in Mn₄₋ₓNiₓN between x = 0.1 and 0.25. We expect Mn atoms of Mn₄₋ₓNiₓN crystal have larger magnetic moments than Ni atoms do. The temperature dependence stated above can be explained if we assume that Ni atoms preferentially occupy the corner sites, and their magnetic moments have different temperature dependence from Mn atoms at the face-centered sites. At the compensation point, Mn₄₋ₓNiₓN is expected to show very efficient STT and ultrafast DW motion with small current density. What’s more, if angular momentum compensation is found, the efficiency will be best optimized. In order to prove the magnetic compensation, X-ray magnetic circular dichroism will be performed. Energy dispersive X-ray spectrometry is a candidate method to analyze the accurate composition ratio of samples.

Keywords: compensation, ferrimagnetism, Mn₄N, PMA

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Authors: Yemane Tadesse Gebreslassie, Henok Gidey Gebretnsae

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Nanotechnology has emerged as a highly promising field of research with wide-ranging applications across various scientific disciplines. In recent years, tin oxide has garnered significant attention due to its intriguing properties, particularly when synthesized in the nanoscale range. While numerous physical and chemical methods exist for producing tin oxide nanoparticles, these approaches tend to be costly, energy-intensive, and involve the use of toxic chemicals. Given the growing concerns regarding human health and environmental impact, there has been a shift towards developing cost-effective and environmentally friendly processes for tin oxide nanoparticle synthesis. Green synthesis methods utilizing biological entities such as plant extracts, bacteria, and natural biomolecules have shown promise in successfully producing tin oxide nanoparticles. However, scaling up the production to an industrial level using green synthesis approaches remains challenging due to the complexity of biological substrates, which hinders the elucidation of reaction mechanisms and formation processes. Thus, this review aims to provide an overview of the various sources of biological entities and methodologies employed in the green synthesis of tin oxide nanoparticles, as well as their impact on nanoparticle properties. Furthermore, this research delves into the strides made in comprehending the mechanisms behind the formation of nanoparticles as documented in existing literature. It also sheds light on the array of analytical techniques employed to investigate and elucidate the characteristics of these minuscule particles.

Keywords: nanotechnology, tin oxide, green synthesis, formation mechanisms

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Authors: N. K. Mohd Affendi, T. A. R. Tuan Abdullah, S. A. Syed Mustaffa

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In power industry transformer is an important component and most of us familiar by the functioning principle of a transformer electrically. There are many losses occur during the operation of a transformer that causes heat generation. This heat, if not dissipated properly will reduce the lifetime and effectiveness of the transformer. Transformer cooling helps in maintaining the temperature rise of various paths. This paper proposed to minimize the ambient temperature of the transformer room in order to lower down the temperature of the transformer. A simulation has been made using finite element methods programs called FEMM (Finite Elements Method Magnetics) to create a virtual model based on actual measurement of a transformer. The generalization of the two-dimensional (2D) FEMM results proves that by minimizing the ambient temperature, the heat of the transformer is decreased. The modeling process and of the transformer heat flow has been presented.

Keywords: heat generation, temperature rise, ambient temperature, FEMM

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Authors: Praveen Kumar, Nitin Kumar, Hemant Kumar

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The modernization of computer technology and commercial computational fluid dynamic (CFD) simulation has given better detailed results as compared to experimental investigation techniques. CFD techniques are widely used in different field due to its flexibility and performance. Evaluation of pipeline erosion is complex phenomenon to solve by numerical arithmetic technique, whereas CFD simulation is an easy tool to resolve that type of problem. Erosion wear behaviour due to solid–liquid mixture in the slurry pipeline has been investigated using commercial CFD code in FLUENT. Multi-phase Euler-Lagrange model was adopted to predict the solid particle erosion wear in 22.5° pipe bend for the flow of bottom ash-water suspension. The present study addresses erosion prediction in three dimensional 22.5° pipe bend for two-phase (solid and liquid) flow using finite volume method with standard k-ε turbulence, discrete phase model and evaluation of erosion wear rate with varying velocity 2-4 m/s. The result shows that velocity of solid-liquid mixture found to be highly dominating parameter as compared to solid concentration, density, and particle size. At low velocity, settling takes place in the pipe bend due to low inertia and gravitational effect on solid particulate which leads to high erosion at bottom side of pipeline.

Keywords: computational fluid dynamics (CFD), erosion, slurry transportation, k-ε Model

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Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim

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Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of predictive models has facilitated the estimation process in recent years. In this research, 176 crude palm oil (CPO) samples acquired from Felda Johor Bulker Sdn Bhd were studied. A FOSS NIRSystem was used to tak e absorbance measurements from the sample. The wavelength range for the spectral measurement is taken at 1600nm to 1900nm. Partial Least Square Regression (PLSR) prediction model with 50 optimal number of principal components was implemented to study the relationship between the measured Free Fatty Acid (FFA) values and the measured spectral absorption. PLSR showed predictive ability of FFA values with correlative coefficient (R) of 0.9808 for the training set and 0.9684 for the testing set.

Keywords: palm oil, fatty acid, NIRS, PLSR

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