Search results for: surface features

Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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Authors: Latha Nataraj, Todd Henry, Micheal Wallock, Asha Hall, Christine Hatter, Babak Anasori, Yury Gogotsi

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Multifunctional composites with enhanced strength and toughness for superior damage tolerance are essential for advanced aerospace and military applications. Detection of structural changes prior to visible damage may be achieved by incorporating fillers with tunable properties such as two-dimensional (2D) nanomaterials with high aspect ratios and more surface-active sites. While 2D graphene with large surface areas, good mechanical properties, and high electrical conductivity seems ideal as a filler, the single-atomic thickness can lead to bending and rolling during processing, requiring post-processing to bond to polymer matrices. Lately, an emerging family of 2D transition metal carbides and nitrides, MXenes, has attracted much attention since their discovery in 2011. Metallic electronic conductivity and good mechanical properties, even with increased polymer content, coupled with hydrophilicity make MXenes a good candidate as a filler material in polymer composites and exceptional as multifunctional damage indicators in composites. Here, we systematically study MXene-based (Ti₃C₂) coated on glass fibers for fiber reinforced polymer composite for self-sensing using microscopy and micromechanical testing. Further testing is in progress through the investigation of local variations in optical, acoustic, and thermal properties within the damage sites in response to strain caused by mechanical loading.

Keywords: damage sensing, fiber composites, MXene, self-sensing

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Authors: Hemalatha Ganapathyswamy, Thirukkumar Subramani

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Celiac disease is an autoimmune response to dietary wheat gluten. Gluten is the main structure forming protein in bread and hence developing gluten-free bread is a technological challenge. The study aims at using nonwheat flours like barnyard millet and lentil flour to replace wheat in bread formulations. Other characteristics of these grains, such as high protein, soluble fiber, mineral content and bioactive components make them attractive alternatives to traditional gluten-free ingredients in the production of high protein, gluten-free bread. The composite flour formulations for the development of gluten-free bread were optimized using lentil flour (50 to 70 g), barnyard millet flour (0 to 30 g) and corn flour (0 to 30 g) by means of response surface methodology with various independent variables for physical, sensorial and nutritional characteristics. The optimized composite flour which had a desirability value of 0.517, included lentil flour –62.94 g, barnyard millet flour– 24.34 g and corn flour– 12.72 g with overall acceptability score 8.00/9.00. The optimized gluten-free bread formulation had high protein (14.99g/100g) and fiber (1.95g/100g) content. The glycemic index of the gluten-free bread was 54.58 rendering it as low glycemic which enhances the functional benefit of the gluten-free bread. Since the standardised gluten-free bread from barnyard millet and lentil flour are high protein, and gluten-free with low glycemic index, the product would serve as an ideal therapeutic food in the management of both celiac disease and diabetes mellitus with better nutritional value.

Keywords: gluten free bread, lentil, low glycemic index, response surface methodology

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Authors: Akhila Konala, Jagadeeswara Reddy Vennapusa, Sujay Chattopadhyay

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The energy consumption of humankind is growing day by day due to an increase in the population, industrialization and their needs for living. Fossil fuels are the major source of energy to satisfy energy needs, which are non-renewable energy resources. So, there is a need to develop green resources for energy production and storage. Phase change materials (PCMs) derived from plants (green resources) are well known for their capacity to store the thermal energy as latent heat during their phase change from solid to liquid. This property of PCM could be used for storage of thermal energy. In this study, a composite with fatty acid (caprylic acid; M.P 15°C, Enthalpy 179kJ/kg) as a phase change material and expanded perlite as support porous matrix was prepared through direct impregnation method for thermal energy storage applications. The prepared composite was characterized using Differential scanning calorimetry (DSC), Field Emission Scanning Electron Microscope (FESEM), Thermal Gravimetric Analysis (TGA), and Fourier Transform Infrared (FTIR) spectrometer. The melting point of the prepared composite was 15.65°C, and the melting enthalpy was 82kJ/kg. The surface nature of the perlite was observed through FESEM. It was observed that there are micro size pores in the perlite surface, which were responsible for the absorption of PCM into perlite. In TGA thermogram, the PCM loss from composite was started at ~90°C. FTIR curves proved there was no chemical interaction between the perlite and caprylic acid. So, the PCM composite prepared in this work could be effective to use in temperature maintenance of buildings.

Keywords: caprylic acid, composite, phase change materials, PCM, perlite, thermal energy

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Authors: C. Rekha, G. N. Krishnamurthy

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This paper attempts to develop a different approach for key scheduling algorithm which uses both Blowfish and AES algorithms. The main drawback of Blowfish algorithm is, it takes more time to create the S-box entries. To overcome this, we are replacing process of S-box creation in blowfish, by using key dependent S-box creation from AES without affecting the basic operation of blowfish. The method proposed in this paper uses good features of blowfish as well as AES and also this paper demonstrates the performance of blowfish and new algorithm by considering different aspects of security namely Encryption Quality, Key Sensitivity, and Correlation of horizontally adjacent pixels in an encrypted image.

Keywords: AES, blowfish, correlation coefficient, encryption quality, key sensitivity, s-box

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Authors: Neha Parekh, Divya Ladha, Poonam Wadhwani, Nisha Shah

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Nano scaled materials have attracted tremendous interest as corrosion inhibitor due to their high surface area on the metal surfaces. It is well known that the zinc oxide nanoparticles have higher reactivity towards aqueous acidic solution. This work presents a new method to incorporate zinc oxide nanoparticles with white sesame seeds extract (nano-green inhibitor) for corrosion protection of zinc in acidic medium. The morphology of the zinc oxide nanoparticles was investigated by TEM and DLS. The corrosion inhibition efficiency of the green inhibitor and nano-green inhibitor was determined by Gravimetric and electrochemical impedance spectroscopy (EIS) methods. Gravimetric measurements suggested that nano-green inhibitor is more effective than green inhibitor. Furthermore, with the increasing temperature, inhibition efficiency increases for both the inhibitors. In addition, it was established the Temkin adsorption isotherm fits well with the experimental data for both the inhibitors. The effect of temperature and Temkin adsorption isotherm revealed Chemisorption mechanism occurring in the system. The activation energy (Ea) and other thermodynamic parameters for inhibition process were calculated. The data of EIS showed that the charge transfer controls the corrosion process. The surface morphology of zinc metal (specimen) in absence and presence of green inhibitor and nano-green inhibitor were performed using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM) techniques. The outcomes indicated a formation of a protective layer over zinc metal (specimen).

Keywords: corrosion, green inhibitor, nanoparticles, zinc

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Authors: Kali Prasad Sarma, Nibedita Baul, Jinu Deka

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In the present study, pollution level of polycyclic aromatic hydrocarbon (PAH) in surface soil of historic Tezpur town located in the north bank of the River Brahmaputra were evaluated. In order to determine the seasonal distribution and concentration level of 16 USEPA priority PAHs surface soil samples were collected from 12 different sampling sites with various land use type. The total concentrations of 16 PAHs (∑16 PAHs) varied from 242.68µgkg-1to 7901.89µgkg-1. Concentration of total probable carcinogenic PAH ranged between 7.285µgkg-1 and 479.184 µgkg-1 in different seasons. However, the concentration of BaP, the most carcinogenic PAH, was found in the range of BDL to 50.01 µgkg-1. The composition profiles of PAHs in 3 different seasons were characterized by following two different types of ring: (1) 4-ring PAHs, contributed to highest percentage of total PAHs (43.75%) (2) while in pre- and post- monsoon season 3- ring compounds dominated the PAH profile, contributing 65.58% and 74.41% respectively. A high PAHs concentration with significant seasonality and high abundance of LMWPAHs was observed in Tezpur town. Soil PAHs toxicity was evaluated taking toxic equivalency factors (TEFs), which quantify the carcinogenic potential of other PAHs relative to BaP and estimate benzo[a]pyrene-equivalent concentration (BaPeq). The calculated BaPeq value signifies considerable risk to contact with soil PAHs. We applied cluster analysis and principal component analysis (PCA) with multivariate linear regression (MLR) to apportion sources of polycyclic aromatic hydrocarbons (PAHs) in surface soil of Tezpur town, based on the measured PAH concentrations. The results indicate that petrogenic and pyrogenic sources are the important sources of PAHs. A combination of chemometric and molecular indices were used to identify the sources of PAHs, which could be attributed to vehicle emissions, a mixed source input, natural gas combustion, wood or biomass burning and coal combustion. Source apportionment using absolute principle component scores–multiple linear regression showed that the main sources of PAHs are 22.3% mix sources comprising of diesel and biomass combustion and petroleum spill,13.55% from vehicle emission, 9.15% from diesel and natural gas burning, 38.05% from wood and biomass burning and 16.95% contribute coal combustion. Pyrogenic input was found to dominate source of PAHs origin with more contribution from vehicular exhaust. PAHs have often been found to co-emit with other environmental pollutants like heavy metals due to similar source of origin. A positive correlation was observed between PAH with Cr and Pb (r2 = 0.54 and 0.55 respectively) in monsoon season and PAH with Cd and Pb (r2 = 0.54 and 0.61 respectively) indicating their common source. Strong correlation was observed between PAH and OC during pre- and post- monsoon (r2=0.46 and r2=0.65 respectively) whereas during monsoon season no significant correlation was observed (r2=0.24).

Keywords: polycyclic aromatic hydrocarbon, Tezpur town, chemometric analysis, ecological risk assessment, pollution

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Authors: J. Satya Eswari, J. Sekhar Babub, Meena Murmu, Govardhan Bhat

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Electrical Discharge Machining (EDM) is an unconventional manufacturing process based on removal of material from a part by means of a series of repeated electrical sparks created by electric pulse generators at short intervals between a electrode tool and the part to be machined emmersed in dielectric fluid. In this paper, a study will be performed on the influence of the factors of peak current, pulse on time, interval time and power supply voltage. The output responses measured were material removal rate (MRR) and surface roughness. Finally, the parameters were optimized for maximum MRR with the desired surface roughness. RSM involves establishing mathematical relations between the design variables and the resulting responses and optimizing the process conditions. RSM is not free from problems when it is applied to multi-factor and multi-response situations. Design of experiments (DOE) technique to select the optimum machining conditions for machining AISI 4140 using EDM. The purpose of this paper is to determine the optimal factors of the electro-discharge machining (EDM) process investigate feasibility of design of experiment techniques. The work pieces used were rectangular plates of AISI 4140 grade steel alloy. The study of optimized settings of key machining factors like pulse on time, gap voltage, flushing pressure, input current and duty cycle on the material removal, surface roughness is been carried out using central composite design. The objective is to maximize the Material removal rate (MRR). Central composite design data is used to develop second order polynomial models with interaction terms. The insignificant coefficients’ are eliminated with these models by using student t test and F test for the goodness of fit. CCD is first used to establish the determine the optimal factors of the electro-discharge machining (EDM) for maximizing the MRR. The responses are further treated through a objective function to establish the same set of key machining factors to satisfy the optimization problem of the electro-discharge machining (EDM) process. The results demonstrate the better performance of CCD data based RSM for optimizing the electro-discharge machining (EDM) process.

Keywords: electric discharge machining (EDM), modeling, optimization, CCRD

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Authors: Fouzieh Rouzmehr, Mehdi Mousavi

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Hot mix asphalt concrete (HMAC) is a mixture of aggregates and bitumen. The primary ingredient that determines the mechanical properties of HMAC is the bitumen in it, which displays viscoelastic behavior under normal service conditions. For simplicity, asphalt concrete is considered an elastic material, but this is far from reality at high service temperatures and longer loading times. Viscoelasticity means that the material's stress-strain relationship depends on the strain rate and loading duration. The goal of this paper is to simulate the mechanical response of flexible pavements using linear elastic and viscoelastic modeling of asphalt concrete and predict pavement performance. Falling Weight Deflectometer (FWD) load will be simulated and the results for elastic and viscoelastic modeling will be evaluated. The viscoelastic simulation is performed by the Prony series, which will be modeled by using ANSYS software. Inflexible pavement design, tensile strain at the bottom of the surface layer and compressive strain at the top of the last layer plays an important role in the structural response of the pavement and they will imply the number of loads for fatigue (Nf) and rutting (Nd) respectively. The differences of these two modelings are investigated on fatigue cracking and rutting problem, which are the two main design parameters in flexible pavement design. Although the differences in rutting problem between the two models were negligible, in fatigue cracking, the viscoelastic model results were more accurate. Results indicate that modeling the flexible pavement with elastic material is efficient enough and gives acceptable results.

Keywords: flexible pavement, asphalt, FEM, viscoelastic, elastic, ANSYS, modeling

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Authors: Hafiz Muhammad Adeel Sharif, Tian Li, Changping Li

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Recently, the emission of nitrogen-sulphur oxides (NOₓ, SO₂) has become a global issue and causing serious threats to health and the environment. Catalytic reduction of NOx and SOₓ gases into friendly gases is considered one of the best approaches. However, regeneration of the catalyst, higher bond-dissociation energy for NOx, i.e., 150.7 kcal/mol, escape of intermediate gas (N₂O, a greenhouse gas) with treated flue-gas, and limited activity of catalyst remains a great challenge. Here, a cheap, binderless naturally-extracted bass-wood thin carbon electrode (TCE) is presented, which shows excellent catalytic activity towards NOx reduction. The bass-wood carbonization at 900 ℃ followed by thermal activation in the presence of CO2 gas at 750 ℃. The thermal activation resulted in an increase in epoxy groups on the surface of the TCE and enhancement in the surface area as well as the degree of graphitization. The TCE unique 3D strongly inter-connected network through hierarchical micro/meso/macro pores that allow large electrode/electrolyte interface. Owing to these characteristics, the TCE exhibited excellent catalytic efficiency towards NOx (~83.3%) under ambient conditions and enhanced catalytic response under pH and sulphite exposure as well as excellent stability up to 168 hours. Moreover, a temperature-dependent activity trend was found where the highest catalytic activity was achieved at 80 ℃, beyond which the electrolyte became evaporative and resulted in a performance decrease. The designed electrocatalyst showed great potential for effective NOx-reduction, which is highly cost-effective, green, and sustainable.

Keywords: electrocatalyst, NOx-reduction, bass-wood electrode, integrated wet-scrubbing, sustainable

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Authors: Jung Park, Anca Mazare, Klaus Von Der Mark, Patrik Schmuki

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In clinical application of TiO2 implants on tooth and hip replacement, migration, adhesion and differentiation of neighboring mesenchymal stem cells onto implant surfaces are critical steps for successful bone regeneration. In a recent decade, accumulated attention has been paid on nanoscale electrochemical surface modifications on TiO2 layer for improving bone-TiO2 surface integration. We generated, on titanium surfaces, self-assembled layers of vertically oriented TiO2 nanotubes with defined diameters between 15 and 100 nm and here we show that mesenchymal stem cells finely sense TiO2 nanotubular geometry and quickly decide their cell fate either to differentiation into osteoblasts or to programmed cell death (apoptosis) on TiO2 nanotube layers. These cell fate decisions are critically dependent on nanotube size differences (15-100nm in diameters) of TiO2 nanotubes sensing by integrin clustering. We further demonstrate that nanoscale topography-sensing is feasible not only in mesenchymal stem cells but rather seems as generalized nanoscale microenvironment-cell interaction mechanism in several cell types composing bone tissue network including osteoblasts, osteoclast, endothelial cells and hematopoietic stem cells. Additionally we discuss the synergistic effect of simultaneous stimulation by nanotube-bound growth factor and nanoscale topographic cues on enhanced bone regeneration.

Keywords: TiO2 nanotube, stem cell fate decision, nano-scale microenvironment, bone regeneration

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Authors: Abinaya Balasubramanian, Satyabrata Ghosh, Satyahari Dey

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Non-Digestible Oligosaccharides(NDOs) are low molecular weight carbohydrates with degree of polymerization (DP) 3-20, that are delivered intact to the large intestine. NDOs are gaining attention as effective prebiotic molecules that facilitate prevention and treatment of several chronic diseases. Recently, NDOs are being obtained by cleaving complex polysaccharides as it results in high yield and also as the former tend to display greater bioactivity. Thelebolus sp. IITKGP BT-12, a recently identified psychrophilic, Ascomycetes fungus has been reported to produce a bioactive extracellular polysaccharide(EPS). The EPS has been proved to possess strong prebiotic activity and anti- proliferative effects. The current study is an attempt to identify and optimise the most suitable method for hydrolysis of the above mentioned novel EPS into NDOs, and further purify and characterise the same. Among physical, chemical and enzymatic methods, enzymatic hydrolysis was identified as the best method and the optimum hydrolysis conditions obtained using response surface methodology were: reaction time of 24h, β-(1,3) endo-glucanase concentration of 0.53U and substrate concentration of 10 mg/ml. The NDOs were purified using gel filtration chromatography and their molecular weights were determined using MALDI-TOF. The major fraction was found to have a DP of 7,8. The monomeric units of the NDOs were confirmed to be glucose using TLC and GCMS-MS analysis. The obtained oligosaccharides proved to be non-digestible when subjected to gastric acidity, salivary and pancreatic amylases and hence could serve as efficient prebiotics.

Keywords: characterisation, enzymatic hydrolysis, non-digestible oligosaccharides, response surface methodology

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Authors: Yongjian Gu

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Ocean thermal energy is one of the ocean energy sources. It is a renewable, sustainable, and green energy source. Ocean thermal energy conversion (OTEC) applies the ocean temperature gradient between the warmer surface seawater and the cooler deep seawater to run a heat engine and produce a useful power output. Unfortunately, the ocean temperature gradient is not big. Even in the tropical and equatorial regions, the surface water temperature can only reach up to 28oC and the deep water temperature can be as low as 4oC. The thermal efficiency of the OTEC plants, therefore, is low. In order to improve the plant thermal efficiency by using the limited ocean temperature gradient, some OTEC plants use the method of adding more equipment for better heat recovery, such as heat exchangers, pumps, etc. Obviously, the method will increase the plant's complexity and cost. The more important impact of the method is the additional equipment needs to consume power too, which may have an adverse effect on the plant net power output, in turn, the plant thermal efficiency. In the paper, the author first describes varied OTEC plants and the practice of using the method of adding more equipment for improving the plant's thermal efficiency. Then the author proposes a parameter, plant back works ratio ϕ, for measuring if the added equipment is appropriate for the plant thermal efficiency improvement. Finally, in the paper, the author presents examples to illustrate the application of the back work ratio ϕ as a key parameter in the OTEC plant design and operation.

Keywords: ocean thermal energy, ocean thermal energy conversion (OTEC), OTEC plant, plant back work ratio ϕ

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Authors: Mauro Masili, Fernanda O. Duarte, Liliane Ventura

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Ultraviolet (UV) radiation is electromagnetic waves from 100 – 400 nm wavelength. The World Health Organization and the International Commission on Non-Ionizing Radiation Protection (ICNIRP) recommend guidelines on the exposure of the eyes to UV radiation because it is correlated to ophthalmic diseases. Those exposure limits for an 8-h period are 1) UV radiant exposure should not exceed 30 J/m2 when irradiance is spectrally weighted using an actinic action spectrum; 2) unweighted radiant exposure in the UV-A spectral region 315 – 400 nm should not exceed 10 kJ/m2. Sunglasses play an important role in preventing eye injuries related to Sun exposure. We have calculated the direct and diffuse solar UV irradiance in a geometry that refers to an individual wearing a sunglass, in which the solar rays strike on a vertical surface. The diffuse rays are those scattered from the atmosphere and from the local environment. The calculations used the open-source SMARTS2 spectral model, in which we assumed a clear sky condition, aside from information about site location, date, time, ozone column, aerosols, and turbidity. In addition, we measured the spectral transmittance of a typical sunglasses lens and the global solar irradiance was weighted with the spectral transmittance profile of the lens. The radiant exposure incident on the eye’s surface was calculated in the UV and UV-A ranges following the ICNIRP’s recommendations for each day of the year. The tested lens failed the UV-A safe limit, while the UV limit failed to comply with this limit after the aging process. Hence, the ICNIRP safe limits should be considered in the standards to increase the protection against UV radiation on the eye.

Keywords: ICNIRP safe limits, ISO-12312-1, sunglasses, ultraviolet radiation

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Authors: Ricardo Torcato, Helder Morais

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The manufacture of crystal glass parts is based on obtaining the rough geometry by blowing and/or injection, generally followed by a set of manual finishing operations using cutting and grinding tools. The forming techniques used do not allow the obtainment, with repeatability, of parts with complex shapes and the finishing operations use intensive specialized labor resulting in high cycle times and production costs. This work aims to explore the digital manufacture of crystal glass parts by investigating new subtractive techniques for the automated, flexible finishing of these parts. Finishing operations are essential to respond to customer demands in terms of crystal feel and shine. It is intended to investigate the applicability of different computerized finishing technologies, namely milling and grinding in a CNC machining center with or without ultrasonic assistance, to crystal processing. Research in the field of grinding hard and brittle materials, despite not being extensive, has increased in recent years, and scientific knowledge about the machinability of crystal glass is still very limited. However, it can be said that the unique properties of glass, such as high hardness and very low toughness, make any glass machining technology a very challenging process. This work will measure the performance improvement brought about by the use of ultrasound compared to conventional crystal grinding. This presentation is focused on the mechanical characterization and analysis of the cutting forces in CNC machining of superior crystal glass (Pb ≥ 30%). For the mechanical characterization, the Vickers hardness test provides an estimate of the material hardness (Hv) and the fracture toughness based on cracks that appear in the indentation. Mechanical impulse excitation test estimates the Young’s Modulus, shear modulus and Poisson ratio of the material. For the cutting forces, it a dynamometer was used to measure the forces in the face grinding process. The tests were made based on the Taguchi method to correlate the input parameters (feed rate, tool rotation speed and depth of cut) with the output parameters (surface roughness and cutting forces) to optimize the process (better roughness using the cutting forces that do not compromise the material structure and the tool life) using ANOVA. This study was conducted for conventional grinding and for the ultrasonic grinding process with the same cutting tools. It was possible to determine the optimum cutting parameters for minimum cutting forces and for minimum surface roughness in both grinding processes. Ultrasonic-assisted grinding provides a better surface roughness than conventional grinding.

Keywords: CNC machining, crystal glass, cutting forces, hardness

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Authors: K. X. Cheng, A. L. Goh, K. T. Ooi

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The effectiveness of microchannels in enhancing heat transfer has been demonstrated in the semiconductor industry. In order to tap the microscale heat transfer effects into macro geometries, overcoming the cost and technological constraints, microscale passages were created in macro geometries machined using conventional fabrication methods. A cylindrical insert was placed within a pipe, and geometrical profiles were created on the outer surface of the insert to enhance heat transfer under steady-state single-phase liquid flow conditions. However, while heat transfer coefficient values of above 10 kW/m2·K were achieved, the heat transfer enhancement was accompanied by undesirable pressure drop increment. Therefore, this study aims to address the high pressure drop issue using Constructal theory, a universal design law for both animate and inanimate systems. Two designs based on Constructal theory were developed to study the effectiveness of Constructal features in reducing the pressure drop increment as compared to parallel channels, which are commonly found in microchannel fabrication. The hydrodynamic and heat transfer performance for the Tree insert and Constructal fin (Cfin) insert were studied using experimental methods, and the underlying mechanisms were substantiated by numerical results. In technical terms, the objective is to achieve at least comparable increment in both heat transfer coefficient and pressure drop, if not higher increment in the former parameter. Results show that the Tree insert improved the heat transfer performance by more than 16 percent at low flow rates, as compared to the Tree-parallel insert. However, the heat transfer enhancement reduced to less than 5 percent at high Reynolds numbers. On the other hand, the pressure drop increment stayed almost constant at 20 percent. This suggests that the Tree insert has better heat transfer performance in the low Reynolds number region. More importantly, the Cfin insert displayed improved heat transfer performance along with favourable hydrodynamic performance, as compared to Cfinparallel insert, at all flow rates in this study. At 2 L/min, the enhancement of heat transfer was more than 30 percent, with 20 percent pressure drop increment, as compared to Cfin-parallel insert. Furthermore, comparable increment in both heat transfer coefficient and pressure drop was observed at 8 L/min. In other words, the Cfin insert successfully achieved the objective of this study. Analysis of the results suggests that bifurcation of flows is effective in reducing the increment in pressure drop relative to heat transfer enhancement. Optimising the geometries of the Constructal fins is therefore the potential future study in achieving a bigger stride in energy efficiency at much lower costs.

Keywords: constructal theory, enhanced heat transfer, microchannel, pressure drop

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Authors: O. Berriche, R. Ben Othmen, H. Sfar, H. Abdesslam, S. Bou Meftah, S. Bhouri, F. Mahjoub, C. Amrouche, H. Jamoussi

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Introduction: Although current evidence emphasizes a high prevalence of vitamin D deficiency and an inverse association between serum 25-hydroxyvitamin D (25-OHD) concentration and obesity, no studies have been conducted in Tunisian obese. The objectives of our study were to estimate the vitamin D deficiency in obese, identify risk factors for vitamin D deficiency, demonstrating a possible association between vitamin D levels and metabolic parameters. Methods: This was a descriptive study of 100 obese 18-65 year-old. Anthropometric measurements were determined. Fasting blood samples were assessed for the following essays : serum calcium, 25 OH vitamin D, inorganic phosphorus, fasting glucose, HDL, LDL cholesterol and triglyceride. Insulin resistance was evaluated by fasting insulin, HOMA-IR and HOMA-ß. Consumption of foods riche in vitamin D, sunscreen use, wearing protective clothes and exposed surface were assessed through applied questionnaires. Results: The deficit of vitamin D (< 30 ng/ml) among obese was 98,8%. Half of them had a rate < 10ng/ml. Environmental factors involved in vitamin D deficiency are : the veil (p = 0,001), wearing protective clothes (p = 0,04) and the exposed surface (p = 0,011) and dietary factors are represented by the daily caloric intake (p = 0,0001). The percent of fat mass was negatively related to vitamin D levels (p = 0,01) but not with BMI (p = 0,11) or waist circumference (p = 0,88). Similarly, lipid and glucose profile had no link with vitamin D. We found no relationship between Insulin resistance and vitamin D levels. Conclusion: At the end of our study, we have identified a very important vitamin D deficiency among obese. Dosage and systematic supplementation should be applied and for that physician awareness is needed.

Keywords: insulinresistance, risk factors, obesity, vitamin D

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Authors: Nazi Pharsadanishvili, Anastasia Kitiashvili

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The importance of studying the social-psychological features of people living in poverty is often emphasized in international research. Building a multidimensional economic framework for reducing poverty grounded in people’s experiences and values is the main goal of famous Poverty Research Centers (such as Oxford Poverty and Human Development Initiative, Abdul Latif Jameel Poverty Action Lab). The aims of the proposed research are to investigate the following characteristics of socially vulnerable people living in Georgia: 1) The features of the perceived stigma of poverty; 2) economic system justification and social justice beliefs; 3) Perceived social mobility and actual attempts at upward social mobility. Qualitative research was conducted to address the indicated research goals and descriptive research questions. Conducting in-depth interviews was considered to be the most appropriate method to capture the vivid feelings and experiences of people living in poverty. 17 respondents (registered in the unified database of socially vulnerable families) participated in in-depth interviews. According to the research results, socially vulnerable people living in Georgia perceive stigma targeted toward them. Two sub-dimensions were identified in perceived stigma: experienced stigma and internalized stigma. Experienced stigma reflects the instances of being discriminated and perceptions of negative treatment from other members of society. Internalized stigma covers negative personal emotions, the feelings of shame, the fear of future stigmatization, and self-isolation. The attitudes and justifications of the existing economic system affect people’s attempts to cope with poverty. Complex analysis of those results is important during the planning and implementing of social welfare reforms. Particularly, it is important to implement poverty stigma reduction mechanisms and help socially vulnerable people to see real perspectives on upward social mobility.

Keywords: coping with poverty, economic system justification, perceived stigma of poverty, upward social mobility

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Authors: X. Wang

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Timely and accurate information on urban building damage caused by earthquake is important basis for disaster assessment and emergency relief. Very high resolution (VHR) remotely sensed imagery containing abundant fine-scale information offers a large quantity of data for detecting and assessing urban building damage in the aftermath of earthquake disasters. However, the accuracy obtained using spectral features alone is comparatively low, since building damage, intact buildings and pavements are spectrally similar. Therefore, it is of great significance to detect urban building damage effectively using multi-source data. Considering that in general height or geometric structure of buildings change dramatically in the devastated areas, a novel multi-stage urban building damage detection method, using bi-temporal spectral, height and corner information, was proposed in this study. The pre-event height information was generated using stereo VHR images acquired from two different satellites, while the post-event height information was produced from airborne LiDAR data. The corner information was extracted from pre- and post-event panchromatic images. The proposed method can be summarized as follows. To reduce the classification errors caused by spectral similarity and errors in extracting height information, ground surface, shadows, and vegetation were first extracted using the post-event VHR image and height data and were masked out. Two different types of building damage were then extracted from the remaining areas: the height difference between pre- and post-event was used for detecting building damage showing significant height change; the difference in the density of corners between pre- and post-event was used for extracting building damage showing drastic change in geometric structure. The initial building damage result was generated by combining above two building damage results. Finally, a post-processing procedure was adopted to refine the obtained initial result. The proposed method was quantitatively evaluated and compared to two existing methods in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010, using pre-event GeoEye-1 image, pre-event WorldView-2 image, post-event QuickBird image and post-event LiDAR data. The results showed that the method proposed in this study significantly outperformed the two comparative methods in terms of urban building damage extraction accuracy. The proposed method provides a fast and reliable method to detect urban building collapse, which is also applicable to relevant applications.

Keywords: building damage, corner, earthquake, height, very high resolution (VHR)

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

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Authors: Magdalena Diaka, Paweł Mazierski, Joanna Żebrowska, Michał Winiarski, Tomasz Klimczuk, Adriana Zaleska-Medynska

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During the last years, TiO2 nanotubes have been widely studied due to their unique highly ordered array structure, unidirectional charge transfer and higher specific surface area compared to conventional TiO2 powder. These photoactive materials, in the form of thin layer, can be activated by low powered and low cost irradiation sources (such as LEDs) to remove VOCs, microorganism and to deodorize air streams. This is possible due to their directly growth on a support material and high surface area, which guarantee enhanced photon absorption together with an extensive adsorption of reactant molecules on the photocatalyst surface. TiO2 nanotubes exhibit also lots of other attractive properties, such as potential enhancement of electron percolation pathways, light conversion, and ion diffusion at the semiconductor-electrolyte interface. Pure TiO2 nanotubes were previously used to remove organic compounds from the gas phase as well as in water splitting reaction. The major factors limiting the use of TiO2 nanotubes, which have not been fully overcome, are their relatively large band gap (3-3,2 eV) and high recombination rate of photogenerated electron–hole pairs. Many different strategies were proposed to solve this problem, however titania nanostructures containing incorporated metal oxides like Ag2O shows very promising, new optical and photocatalytic properties. Unfortunately, there is still very limited number of reports regarding application of TiO2/MxOy nanostructures. In the present work, we prepared TiO2/Ag2O nanotubes obtained by anodization of Ti-Ag alloys containing 5, 10 and 15 wt. % Ag. Photocatalysts prepared in this way were characterized by X-ray diffraction spectroscopy (XRD), scanning electron microscopy (SEM), luminescence spectroscopy and UV-Vis spectroscopy. The activities of new TiO2/Ag2O were examined by photocatalytic degradation of toluene in gas phase reaction and phenol in aqueous phase using 1000 W Xenon lamp (Oriel) and light emitting diodes (LED) as a irradiation sources. Additionally efficiency of bacteria (Pseudomonas aeruginosa) removal from the gas phase was estimated. The number of surviving bacteria was determined by the serial twofold dilution microtiter plate method, in Tryptic Soy Broth medium (TSB, GibcoBRL).

Keywords: photocatalysis, antibacterial properties, titania nanotubes, new TiO2/MxOy nanostructures

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Authors: Munir Ashraf, Shagufta Riaz

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Personal protective equipment (PPE) and bioactive textiles are highly important for the health care of front line hospital workers, patients, and the general population to be safe from highly infectious diseases. This was even more critical in the wake of COVID-19 outbreak. Most of the medical textiles are inactive against various viruses and bacteria, hence there is a need to wash them frequently to avoid the spread of microorganisms. According to survey conducted by the world health organization, more than 500 million people get infected from hospitals, and more than 13 million died due to these hospitals’ acquired deadly diseases. The market available PPE are though effective against the penetration of pathogens and to kill bacteria but, they are not breathable and active against different viruses. Therefore, there was a great need to develop textiles that are not only effective against bacteria, fungi, and viruses but also are comfortable to the medical personnel and patients. In the present study, waterproof breathable, and biologically active textiles were developed using antiviral and antibacterial nanomaterials. These nanomaterials like TiO₂, ZnO, Cu, and Ag were immobilized at the surface of cotton fabric by using different silane coupling agents and electroless deposition that they retained their functionality even after 30 industrial laundering cycles. Afterwards, the treated fabrics were coated with a waterproof breathable film to prevent the permeation of liquid droplets, any particle or microorganisms greater than 80 nm. The developed cotton fabric was highly active against bacteria and viruses. The good durability of nanomaterials at the cotton surface after several industrial washing cycles makes this fabric an ideal candidate for bioactive textiles used in the medical field.

Keywords: antibacterial, antiviral, cotton, durable

Procedia PDF Downloads 179

Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

Procedia PDF Downloads 113

Authors: Rabia Göçmen, Gülşah Kanbur, Sinan Sefa Parlat

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In this study, in the breeding Japanese quails (coturnix coturnix japonica), it was aimed to study the effects of cellular insulin receptor stimulation on the performance, some blood parameters, and hatchability features. In the study, a total of 84 breeding quails were used, which are in 6 weeks age, and whose 24 are male and 60 female. In the trial, rations which contain 2900 kcal/kg metabolic energy; crude protein of 20%, and water whose pH is calibrated to 7.45 were administered as ad-libitum, to the animals, as metformin source, metformin-HCl was used and as chrome resource, Chromium Picolinate. Trial groups were formed as control group (basal ration), metformin group (basal ration, added metformin at the level of fodder of 20 mg/kg), and chromium picolinate group (basal ration, added fodder of 1500 ppb Cr. When regarded to the results of performance at the end of trial, it is seen that live weight gain, fodder consumption, egg weight, fodder evaluation coefficient, and egg production were affected at the significant level (p < 0.05). When the results are evaluated in terms of incubation features at the end of trial, it was identified that incubation yield and hatchability are not affected by the treatments but in the groups, in which metformin and chromium picolinate are added to ration, that fertility rose at the significant level compared to control group (p < 0,05). According to the results of blood parameters and hormone at the end of the trial, while the level of plasma glucose level was not affected by treatments (p > 0.05), with the addition of metformin and chromium picolinate to ration, plasma, total control, cholesterol, HDL, LDL, and triglyceride levels were significantly affected from insulin receptor stimulators added to ration (p<0,05). Hormone level of Plasma T3 and T4 were also affected at the significant level from insulin receptor stimulators added to ration (p < 0,05).

Keywords: cholesterol, chromium picolinate, hormone, metformin, performance, quail

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Authors: Mohammad Reza Ghaani, Niall English

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Hydrogen is looked upon as the next-generation clean-energy carrier; the search for an efficient material and method for storing hydrogen has been, and is, pursued relentlessly. Clathrate hydrates are inclusion compounds wherein guest gas molecules like hydrogen are trapped in a host water-lattice framework. These types of materials can be categorised as potentially attractive hosting environments for physical hydrogen storage (i.e., no chemical reaction upon storage). Non-equilibrium molecular dynamics (NEMD) simulations have been performed to investigate thermal-driven break-up of propane-hydrate interfaces with liquid water at 270-300 K, with the propane hydrate containing either one or no hydrogen molecule in each of its small cavities. In addition, two types of hydrate-surface water-lattice molecular termination were adopted, at the hydrate edge with water: a 001-direct surface cleavage and one with completed cages. The geometric hydrate-ice-liquid distinction criteria of Báez and Clancy were employed to distinguish between the hydrate, ice lattices, and liquid-phase. Consequently, the melting temperatures of interface were estimated, and dissociation rates were observed to be strongly dependent on temperature, with higher dissociation rates at larger over-temperatures vis-à-vis melting. The different hydrate-edge terminations for the hydrate-water interface led to statistically-significant differences in the observed melting point and dissociation profile: it was found that the clathrate with the planar interface melts at around 280 K, whilst the melting temperature of the cage-completed interface was determined to be circa 270 K.

Keywords: hydrogen storage, clathrate hydrate, molecular dynamics, thermal dissociation

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Authors: P. Jayashree, S. Rajkumar

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With the trend of virtual and augmented reality environments booming to provide a life like experience, gaming is a major tool in supporting such learning environments. In this work, a variant of Voronoi heuristics, employing supervised learning for the TRON game is proposed. The paper discusses the features that would be really useful when a machine learning bot is to be used as an opponent against a human player. Various game scenarios, nature of the bot and the experimental results are provided for the proposed variant to prove that the approach is better than those that are currently followed.

Keywords: artificial Intelligence, automation, machine learning, TRON game, Voronoi heuristics

Procedia PDF Downloads 467

Authors: Paul W. Murray

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This research explores the relationship between leadership style and continuous improvement (CI) teams. CI teams have several features that are not always found in other types of teams, including multi-functional members, short time period for performance, positive and actionable results, and exposure to senior leadership. There is not only one best style of leadership for these teams. Instead, it is important to select the best leadership style for the situation. The leader must have the flexibility to change styles and the skill to use the chosen style effectively in order to ensure the team’s success.

Keywords: leadership style, lean manufacturing, teams, cross-functional

Procedia PDF Downloads 372

Authors: M. Abouleish, R. Umer, Z. Sara

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Nitrate can cause serious environmental and human health problems. Effluent from different industries and excessive use of fertilizers have increased the level of nitrate in ground and surface water. Nitrate can convert to nitrite in the body, and as a result, can lead to Methemoglobinemia and cancer. Therefore, different organizations have set standard limits for nitrate and nitrite. The United States Environmental Protection Agency (USEPA) has set a Maximum Contaminant Level Goal (MCLG) of 10 mg N/L for nitrate and 1 mg N/L for nitrite. The removal of nitrate from water and wastewater is very important to ensure the availability of clean water. Different plant materials such as banana peel, rice hull, coconut and bamboo shells, have been studied as biosorbents for the removal of nitrates from water. The use of abundantly existing plant material as an adsorbent material and the lack of energy requirement for the adsorption process makes biosorption a sustainable approach. Therefore, in this research, the fruit of the plant was investigated for its ability to act as a biosorbent to remove the nitrate from wastewater. The effect of pH on nitrate removal was studied using both the raw and chemically activated fruit (adsorbent). Results demonstrated that the adsorbent needs to be chemically activated before usage to remove the nitrate from wastewater. pH did not have a significant effect on the adsorption process, with maximum adsorption of nitrate occurring at pH 4. SEM/EDX results demonstrated that there is no change in the surface of the adsorbent as a result of the chemical activation. Chemical activation of the adsorbent using NaOH increased the removal of nitrate by 6%; therefore, various methods of activation of the adsorbent will be investigated to increase the removal of nitrate.

Keywords: biosorption, nitrates, plant material, water, and wastewater treatment

Procedia PDF Downloads 153

Authors: James Cairns, Marco Vezza, Richard Green, Donald MacVicar

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Significant legislative changes are set to revolutionise the commercial shipping industry. Upcoming emissions restrictions will force operators to look at technologies that can improve the efficiency of their vessels -reducing fuel consumption and emissions. A device which may help in this challenge is the Ship Wind-Assisted Propulsion system (SWAP), an actively controlled aerofoil mounted vertically on the deck of a ship. The device functions in a similar manner to a sail on a yacht, whereby the aerodynamic forces generated by the sail reach an equilibrium with the hydrodynamic forces on the hull and a forward velocity results. Numerical and experimental testing of the SWAP device is presented in this study. Circulation control takes the form of a co-flow jet aerofoil, utilising both blowing from the leading edge and suction from the trailing edge. A jet at the leading edge uses the Coanda effect to energise the boundary layer in order to delay flow separation and create high lift with low drag. The SWAP concept has been originated by the research and development team at SMAR Azure Ltd. The device will be retrofitted to existing ships so that a component of the aerodynamic forces acts forward and partially reduces the reliance on existing propulsion systems. Wind tunnel tests have been carried out at the de Havilland wind tunnel at the University of Glasgow on a 1:20 scale model of this system. The tests aim to understand the airflow characteristics around the aerofoil and investigate the approximate lift and drag coefficients that an early iteration of the SWAP device may produce. The data exhibits clear trends of increasing lift as injection momentum increases, with critical flow attachment points being identified at specific combinations of jet momentum coefficient, Cµ, and angle of attack, AOA. Various combinations of flow conditions were tested, with the jet momentum coefficient ranging from 0 to 0.7 and the AOA ranging from 0° to 35°. The Reynolds number across the tested conditions ranged from 80,000 to 240,000. Comparisons between 2D computational fluid dynamics (CFD) simulations and the experimental data are presented for multiple Reynolds-Averaged Navier-Stokes (RANS) turbulence models in the form of normalised surface pressure comparisons. These show good agreement for most of the tested cases. However, certain simulation conditions exhibited a well-documented shortcoming of RANS-based turbulence models for circulation control flows and over-predicted surface pressures and lift coefficient for fully attached flow cases. Work must be continued in finding an all-encompassing modelling approach which predicts surface pressures well for all combinations of jet injection momentum and AOA.

Keywords: CFD, circulation control, Coanda, turbo wing sail, wind tunnel

Procedia PDF Downloads 135

Authors: R. Tajau, R. Rohani, M. S. Alias, N. H. Mudri, K. A. Abdul Halim, M. H. Harun, N. Mat Isa, R. Che Ismail, S. Muhammad Faisal, M. Talib, M. R. Mohamed Zin

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Bio-based polymeric materials are increasingly used for a variety of applications, including surface coating, drug delivery systems, and tissue engineering. These polymeric materials are ideal for the aforementioned applications because they are derived from natural resources, non-toxic, low-cost, biocompatible, and biodegradable, and have promising thermal and mechanical properties. The nature of hydrocarbon chains, carbon double bonds, and ester bonds allows various sources of oil (edible), such as soy, sunflower, olive, and oil palm, to fine-tune their particular structures in the development of innovative materials. Palm oil can be the most eminent raw material used for manufacturing new and advanced natural polymeric materials involving radiation techniques, such as coating resins, nanoparticles, scaffold, nanotubes, nanocomposites, and lithography for different branches of the industry in countries where oil palm is abundant. The radiation technique is among the most versatile, cost-effective, simple, and effective methods. Crosslinking, reversible addition-fragmentation chain transfer (RAFT), polymerisation, grafting, and degradation are among the radiation mechanisms. Exposure to gamma, EB, UV, or laser irradiation, which are commonly used in the development of polymeric materials, is used in these mechanisms. Therefore, this review focuses on current radiation processing technologies for the development of various radiation-curable bio-based polymeric materials with a promising future in biomedical and industrial applications. The key focus of this review is on radiation curable palm oil-based products, which have been published frequently in recent studies.

Keywords: palm oil, radiation processing, surface coatings, VOC

Procedia PDF Downloads 183