Search results for: inverse laplace transform techniques

Authors: Özge Alptoğa, Nuray Uçar, Nilgün Karatepe Yavuz, Ayşen Önen

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Sulfur dioxide (SO₂) is a very toxic air pollutant gas and it causes the greenhouse effect, photochemical smog, and acid rain, which threaten human health severely. Thus, the capture of SO₂ gas is very important for the environment. Graphene which is two-dimensional material has excellent mechanical, chemical, thermal properties, and many application areas such as energy storage devices, gas adsorption, sensing devices, and optical electronics. Further, graphene oxide (GO) is examined as a good adsorbent because of its important features such as functional groups (epoxy, carboxyl and hydroxyl) on the surface and layered structure. The SO₂ adsorption properties of the fibers are usually investigated on carbon fibers. In this study, potential adsorption capacity of GO fibers was researched. GO dispersion was first obtained with Hummers’ method from graphite, and then GO fibers were obtained via wet spinning process. These fibers were converted into a disc shape, dried, and then subjected to SO₂ gas adsorption test. The SO₂ gas adsorption capacity of GO fiber discs was investigated in the fields of utilization of different coagulation baths and reduction by hydrazine hydrate. As coagulation baths, single and triple baths were used. In single bath, only ethanol and CaCl₂ (calcium chloride) salt were added. In triple bath, each bath has a different concentration of water/ethanol and CaCl₂ salt, and the disc obtained from triple bath has been called as reference disk. The fibers which were produced with single bath were flexible and rough, and the analyses show that they had higher SO₂ adsorption capacity than triple bath fibers (reference disk). However, the reduction process did not increase the adsorption capacity, because the SEM images showed that the layers and uniform structure in the fiber form were damaged, and reduction decreased the functional groups which SO₂ will be attached. Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD) analyzes were performed on the fibers and discs, and the effects on the results were interpreted. In the future applications of the study, it is aimed that subjects such as pH and additives will be examined.

Keywords: coagulation bath, graphene oxide fiber, reduction, SO2 gas adsorption

Procedia PDF Downloads 346

Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

Procedia PDF Downloads 39

Authors: Umar Hayatu Sidik

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Application of liquid base petroleum fuel (petrol and diesel) for transportation fuel causes emissions of greenhouse gases (GHGs), while natural gas (NG) reduces the emissions of greenhouse gases (GHGs). At present, compression and liquefaction are the most matured technology used for transportation system. For transportation use, compression requires high pressure (200–300 bar) while liquefaction is impractical. A relatively low pressure of 30-40 bar is achievable by adsorbed natural gas (ANG) to store nearly compressed natural gas (CNG). In this study, adsorbents for high-pressure adsorption of methane (CH4) was prepared from coconut shells and polyetheretherketone (PEEK) using potassium hydroxide (KOH) and microwave-assisted activation. Design expert software version 7.1.6 was used for optimization and prediction of preparation conditions of the adsorbents for CH₄ adsorption. Effects of microwave power, activation time and quantity of PEEK on the adsorbents performance toward CH₄ adsorption was investigated. The adsorbents were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric (TG) and derivative thermogravimetric (DTG) and scanning electron microscopy (SEM). The ideal CH4 adsorption capacities of adsorbents were determined using volumetric method at pressures of 5, 17, and 35 bar at an ambient temperature and 5 oC respectively. Isotherm and kinetics models were used to validate the experimental results. The optimum preparation conditions were found to be 15 wt% amount of PEEK, 3 minutes activation time and 300 W microwave power. The highest CH4 uptake of 9.7045 mmol CH4 adsorbed/g adsorbent was recorded by M33P15 (300 W of microwave power, 3 min activation time and 15 wt% amount of PEEK) among the sorbents at an ambient temperature and 35 bar. The CH4 equilibrium data is well correlated with Sips, Toth, Freundlich and Langmuir. Isotherms revealed that the Sips isotherm has the best fit, while the kinetics studies revealed that the pseudo-second-order kinetic model best describes the adsorption process. In all scenarios studied, a decrease in temperature led to an increase in adsorption of both gases. The adsorbent (M33P15) maintained its stability even after seven adsorption/desorption cycles. The findings revealed the potential of coconut shell-PEEK as CH₄ adsorbents.

Keywords: adsorption, desorption, activated carbon, coconut shells, polyetheretherketone

Procedia PDF Downloads 55

Authors: Gaylord K. Booto, Marinelli Giuseppe, Helge Brattebø, Rolf A. Bohne

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Emissions reduction has emerged among the principal targets in the process of planning and designing road alignments today. Intelligent road design methods that can result in optimized alignment constitute concrete and innovative responses towards better alternatives and more sustainable road infrastructures. As the largest amount of emissions of road infrastructures occur in the operation stage, it becomes very important to consider traffic weight and distribution in alignment design process. This study analyzes the effects of four traffic factors (i.e. operating speed, vehicle category, technology and fuel type) on adjusting the vertical alignment of a given road, using optimization techniques. Further, factors’ effects are assessed qualitatively and quantitatively, and the emission profiles of resulting alignment alternatives are compared.

Keywords: alignment adjustment, emissions reduction, optimization, traffic-oriented

Procedia PDF Downloads 356

Authors: Pamphile Ndagijimana, Xuejiao Liu, Zhiwei Li, Yin Wang

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Enhancing the properties of activated carbon is very imperative for various applications. Indeed, the activated carbon has promising physicochemical properties desired for a considerable number of applications. In this regard, we are proposing an enhanced and green technology for increasing the efficiency and performance of the activated carbon to various applications. The technique poses on the use of natural extracts from tuberous and cereals based-solutions. These solutions showed high potentiality to be used in the synthesis of activated carbon-graphene composite with only 3 mL. The extracted liquid from tuberous sourcing was enough to induce precipitation within a fraction of a minute in contrast to that from cereal sourced. Using these extracts, a synthesis of activated carbon-graphene composite was successful. Different characterization techniques such as XRD, SEM, FTIR, BET, and Raman spectroscopy were performed to investigate the composite materials. The results confirmed a conjugation between activated carbon and graphene material.

Keywords: activated carbon, cereals, extract solution, graphene, tuberous

Procedia PDF Downloads 131

Authors: Dandi Bachtiar, Mohammed Ausama Abbas, Januar Parlaungan Siregar, Mohd Ruzaimi Bin Mat Rejab

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Short sugar palm fibre and thermoplastic polyurethane were combined to produce new composites by using the extrude method. Two techniques used to prepare a new composite material, firstly, extrusion of the base material with short fibre, secondly hot pressing them. The size of sugar palm fibre was fixed at 250µm. Different weight percent (10 wt%, 20 wt% and 30 wt%) were used in order to optimise preparation process. The optimization of process depended on the characterization mechanical properties such as impact, tensile, and flexural of the new (TPU/SPF) composite material. The results proved that best tensile and impact properties of weight additive fibre applied 10 wt%. There was an increasing trend recorded of flexural properties during increased the fibre loading. Meanwhile, the maximum tensile strength was 14.0 MPa at 10 wt% of the fibre. Moreover, there was no significant effect for additions more than 30 wt% of the fibre.

Keywords: composites, natural fibre, polyurethane, sugar palm

Procedia PDF Downloads 369

Authors: Zh. Saffari, A. Naeimi, M. S. Ekrami-Kakhki, Kh. Khandan-Barani

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The textile industries are becoming a major source of environmental contamination because an alarming amount of dye pollutants are generated during the dyeing processes. Organic dyes are one of the largest pollutants released into wastewater from textile and other industrial processes, which have shown severe impacts on human physiology. Nano-structure compounds have gained importance in this category due their anticipated high surface area and improved reactive sites. In recent years several novel adsorbents have been reported to possess great adsorption potential due to their enhanced adsorptive capacity. Nano-MnO2 has great potential applications in environment protection field and has gained importance in this category because it has a wide variety of structure with large surface area. The diverse structures, chemical properties of manganese oxides are taken advantage of in potential applications such as adsorbents, sensor catalysis and it is also used for wide catalytic applications, such as degradation of dyes. In this study, adsorption of Methyl Violet (MV) dye from aqueous solutions onto MnO2 nanoparticles (MNP) has been investigated. The surface characterization of these nano particles was examined by Particle size analysis, Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR) spectroscopy and X-Ray Diffraction (XRD). The effects of process parameters such as initial concentration, pH, temperature and contact duration on the adsorption capacities have been evaluated, in which pH has been found to be most effective parameter among all. The data were analyzed using the Langmuir and Freundlich for explaining the equilibrium characteristics of adsorption. And kinetic models like pseudo first- order, second-order model and Elovich equation were utilized to describe the kinetic data. The experimental data were well fitted with Langmuir adsorption isotherm model and pseudo second order kinetic model. The thermodynamic parameters, such as Free energy of adsorption (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°) were also determined and evaluated.

Keywords: MnO2 nanoparticles, adsorption, methyl violet, isotherm models, kinetic models, surface chemistry

Procedia PDF Downloads 245

Authors: Wighens Ngoie Ilunga, Pamela J. Welz, Olewaseun O. Oyekola, Daniel Ikhu-Omoregbe

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Currently, most sludge from the wastewater treatment plants of edible oil factories is disposed to landfills, but landfill sites are finite and potential sources of environmental pollution. Production of biodiesel from wastewater sludge can contribute to energy production and waste minimization. However, conventional biodiesel production is energy and waste intensive. Generally, biodiesel is produced from the transesterification reaction of oils with alcohol (i.e., Methanol, ethanol) in the presence of a catalyst. Homogeneously catalysed transesterification is the conventional approach for large-scale production of biodiesel as reaction times are relatively short. Nevertheless, homogenous catalysis presents several challenges such as high probability of soap. The current study aimed to reuse wastewater sludge from the edible oil industry as a novel feedstock for both monounsaturated fats and bioethanol for the production of biodiesel. Preliminary results have shown that the fatty acid profile of the oilseed wastewater sludge is favourable for biodiesel production with 48% (w/w) monounsaturated fats and that the residue left after the extraction of fats from the sludge contains sufficient fermentable sugars after steam explosion followed by an enzymatic hydrolysis for the successful production of bioethanol [29% (w/w)] using a commercial strain of Saccharomyces cerevisiae. A novel nano-magnetic catalyst was synthesised from mineral processing alkaline tailings, mainly containing dolomite originating from cupriferous ores using a modified sol-gel. The catalyst elemental chemical compositions and structural properties were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infra-red (FTIR) and the BET for the surface area with 14.3 m²/g and 34.1 nm average pore diameter. The mass magnetization of the nano-magnetic catalyst was 170 emu/g. Both the catalytic properties and reusability of the catalyst were investigated. A maximum biodiesel yield of 78% was obtained, which dropped to 52% after the fourth transesterification reaction cycle. The proposed approach has the potential to reduce material costs, energy consumption and water usage associated with conventional biodiesel production technologies. It may also mitigate the impact of conventional biodiesel production on food and land security, while simultaneously reducing waste.

Keywords: biodiesel, bioethanol, edible oil wastewater sludge, nano-magnetism

Procedia PDF Downloads 129

Authors: Aleš Florian, Lenka Ševelová, Jaroslav Žák

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Formation of tensile cracks in concrete slabs of rigid pavement can be (among others) the initiation point of the other, more serious failures which can ultimately lead to complete degradation of the concrete slab and thus the whole pavement. Two measures can be used for reliability assessment of this phenomenon - the probability of failure and/or the reliability index. Different methods can be used for their calculation. The simple ones are called moment methods and simulation techniques. Two methods - FOSM Method and Simple Random Sampling Method - are verified and their comparison is performed. The influence of information about the probability distribution and the statistical parameters of input variables as well as of the limit state function on the calculated reliability index and failure probability are studied in three points on the lower surface of concrete slabs of the older type of rigid pavement formerly used in the Czech Republic.

Keywords: failure, pavement, probability, reliability index, simulation, tensile crack

Procedia PDF Downloads 532

Authors: S. K. M. Nzaba, H. H. Nyoni, B. Ntsendwana, B. B. Mamba, A. T. Kuvarega

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Azo dye effluents, released into water bodies are not only toxic to the ecosystem but also pose a serious impact on human health due to the carcinogenic and mutagenic effects of the compounds present in the dye discharge. Conventional water treatment methods such as adsorption, flocculation/coagulation and biological processes are not effective in completely removing most of the dyes and their natural degradation by-products. Advanced oxidation processes (AOPs) have proven to be effective technologies for complete mineralization of these recalcitrant pollutants. Therefore, there is a need for new technology that can solve the problem. Thus, this study examined the photocatalytic degradation of an azo dye brilliant black (BB) using non-metal/metal codoped TiO₂. N, Pt co-doped TiO₂ photocatalysts were prepared by a modified sol-gel method using amine-terminated polyamidoamine dendrimer generation 0 (PAMAM G0), amine-terminated polyamidoamine dendrimer generation 1 ( PAMAM G1) and hyperbranched polyethyleneimine (HPEI) as templates and source of nitrogen. Structural, morphological, and textural properties were evaluated using scanning electron microscopy coupled to energy dispersive X-ray spectroscopy (SEM/EDX), high-resolution transmission electron microscopy (HRTEM), X-ray diffraction spectroscopy (XRD), X-ray photoelectron spectroscopy (XPS), thermal gravimetric analysis (TGA), Fourier- transform infrared (FTIR), Raman spectroscopy (RS), photoluminescence (PL) and ultra-violet /visible spectroscopy (UV-Vis). The synthesized photocatalysts exhibited lower band gap energies as compared to the Degussa P-25 revealing a red shift in band gap towards the visible light absorption region. Photocatalytic activity of N, Pt co-doped TiO₂ was measured by the reaction of photocatalytic degradation of brilliant black (BB) dye. The N, metal codoped TiO₂ containing 0.5 wt. % of the metal consisted mainly of the anatase phase as confirmed by XRD results of all three samples, with a particle size range of 13–30 nm. The particles were largely spherical and shifted the absorption edge well into the visible region. Band gap reduction was more pronounced for the N, Pt HPEI (Pt 0.5 wt. %) codoped TiO₂ compared to PAMAM G0 and PAMAM G1. Consequently, codoping led to an enhancement in the photocatalytic activity of the materials for the degradation of brilliant black (BB).

Keywords: codoped TiO₂, dendrimer, photodegradation, wastewater

Procedia PDF Downloads 157

Authors: Nathainail Bashir, Neil Anderson

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The objective of this study site was to investigate the current state of the practice with regards to karst detection methods and recommend the best method and pattern of arrays to acquire the desire results. Proper site investigation in karst prone regions is extremely valuable in determining the location of possible voids. Two geophysical techniques were employed: multichannel analysis of surface waves (MASW) and electric resistivity tomography (ERT).The MASW data was acquired at each test location using different array lengths and different array orientations (to increase the probability of getting interpretable data in karst terrain). The ERT data were acquired using a dipole-dipole array consisting of 168 electrodes. The MASW data was interpreted (re: estimated depth to physical top of rock) and used to constrain and verify the interpretation of the ERT data. The ERT data indicates poorer quality MASW data were acquired in areas where there was significant local variation in the depth to top of rock.

Keywords: dipole-dipole, ERT, Karst terrains, MASW

Procedia PDF Downloads 299

Authors: Romulo D. C. Santos, Silvio M. A. Gama, Ramiro G. R. Camacho

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In this present paper, the thermos-fluid dynamics considering the mixed convection (natural and forced convections) and the principles of turbulence flow around complex geometries have been studied. In these applications, it was necessary to analyze the influence between the flow field and the heated immersed body with constant temperature on its surface. This paper presents a study about the Newtonian incompressible two-dimensional fluid around isothermal geometry using the immersed boundary method (IBM) with the virtual physical model (VPM). The numerical code proposed for all simulations satisfy the calculation of temperature considering Dirichlet boundary conditions. Important dimensionless numbers such as Strouhal number is calculated using the Fast Fourier Transform (FFT), Nusselt number, drag and lift coefficients, velocity and pressure. Streamlines and isothermal lines are presented for each simulation showing the flow dynamics and patterns. The Navier-Stokes and energy equations for mixed convection were discretized using the finite difference method for space and a second order Adams-Bashforth and Runge-Kuta 4th order methods for time considering the fractional step method to couple the calculation of pressure, velocity, and temperature. This work used for simulation of turbulence, the Smagorinsky, and Spalart-Allmaras models. The first model is based on the local equilibrium hypothesis for small scales and hypothesis of Boussinesq, such that the energy is injected into spectrum of the turbulence, being equal to the energy dissipated by the convective effects. The Spalart-Allmaras model, use only one transport equation for turbulent viscosity. The results were compared with numerical data, validating the effect of heat-transfer together with turbulence models. The IBM/VPM is a powerful tool to simulate flow around complex geometries. The results showed a good numerical convergence in relation the references adopted.

Keywords: immersed boundary method, mixed convection, turbulence methods, virtual physical model

Procedia PDF Downloads 103

Authors: Anwaar O. Ali, Mahmoud Fathy Mubarak, Mahmoud Ibrahim Abdou, Hector Cano Esteban, Amany A. Aboulrous

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Corrosion resistance and lubrication are crucial characteristics required for geothermal drilling fluids. In this study, a ZnO/Fe₂O₃ nanocomposite was fabricated and incorporated into the structure of Cetyltrimethylammonium bromide (CTAB). Several physicochemical techniques were utilized to analyze and describe the synthesized nanomaterials. The surface morphology of the composite was assessed through scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDAX). The corrosion inhibition capabilities of these materials were explored across various corrosive environments. The weight loss and electrochemical methods were utilized to determine the corrosion inhibition activity of the prepared nanomaterials. The results demonstrate a high level of protection achieved by the composite. Additionally, the lubricant coefficient and extreme pressure properties were evaluated.

Keywords: nanofluid, corrosion, geothermal drilling fluids, ZnO/Fe2O3

Procedia PDF Downloads 52

Authors: Marwa I. Shabayek, Ola A. Said, Hanan A. Attaia, Heba A. Awida

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Bladder carcinoma is an important worldwide health problem. Both cystoscopy and urine cytology used in detecting bladder cancer suffer from drawbacks where cystoscopy is an invasive method and urine cytology shows low sensitivity in low grade tumors. This study validates easier and less time-consuming techniques to evaluate the value of combined use of angiogenin and clusterin in comparison and combination with voided urine cytology in the detection of bladder cancer patients. This study includes malignant (bladder cancer patients, n= 50), benign (n=20), and healthy (n=20) groups. The studied groups were subjected to cystoscopic examination, detection of bilharzial antibodies, urine cytology, and estimation of urinary angiogenin and clusterin by ELISA. The overall sensitivity and specifcity were 66% and 75% for angiogenin, 70% and 82.5% for clusterin and 46% and 80% for voided urine cytology. Combined sensitivity of angiogenin and clusterin with urine cytology increased from 82 to 88%.

Keywords: angiogenin, bladder cancer, clusterin, cytology

Procedia PDF Downloads 280

Authors: Alaa M. M. Badr Eldin, Marwa I. Ezzat, Mohammed S. Sedeek, Manal S. Afifi, Omar M. Sabry

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Cytotoxic activity of the total methanol extract against breast cancer cell line MCF-7 was amazing IC50 at 54 ug/ml. 130 polyphenolic compounds were tentatively identified in pomegranate peel (Punica granatum L.) methanol extract using HPLC-MS/MS technique. The antiestrogenic activity of the polyphenolic constituents found in pomegranate extract was confirmed experimentally in-vitro and by the in-silico molecular docking using gallagic acid, ellagic acid, and Punicalagin as these are considered model compounds confirmed in pomegranate peel extract. The methanolic extract was found to suppress ER, TGF-β, and NF-kB in-vitro gene expression strongly, and that was verified by qPCR and Western Blot gel electrophoresis techniques.

Keywords: HPLC-MS/MS, pomegranate, breast cancer, ovarian cancer, ER, TGF-β, NF-kB

Procedia PDF Downloads 91

Authors: Natália Botica, Luís Luís, Paulo Bernardes

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The Côa Valley, listed World Heritage since 1998, presents more than 1300 open-air engraved rock panels. The Archaeological Park of the Côa Valley recorded the rock art motifs, testing various techniques based on direct tracing processes on the rock, using natural and artificial lighting. In this work, integrated in the "Open Access Rock Art Repository" (RARAA) project, we present the methodology adopted for the vectorial drawing of the rock art motifs based on orthophotos taken from the photogrammetric survey and 3D models of the rocks. We also present the information system designed to integrate the vector drawing and the characterization data of the motifs, as well as the open access sharing, in order to promote their reuse in multiple areas. The 3D models themselves constitute a very detailed record, ensuring the digital preservation of the rock and iconography. Thus, even if a rock or motif disappears, it can continue to be studied and even recreated.

Keywords: rock art, archaeology, iron age, 3D models

Procedia PDF Downloads 70

Authors: Jaria A. Polog, Norjana Lao-Pimping, Bedoria M. Macabalang, Monrizah M. Guiling

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Ultrasound-guided single-shot peripheral nerve blocks (PNB) such as erector spinae plane block (ESPB) and pectoral nerve block (PECS I and II) are emerging anesthetic techniques used to provide complete surgical anesthesia without general anesthesia and adequate postoperative analgesia for breast surgeries. Peripheral nerve blocks with sedation could be a better option for breast surgery than general anesthesia in patients with multiple preexisting comorbidities and those refusing general anesthesia. However, an anesthesiologist with optimum knowledge of regional anesthesia and ultrasound experience plays a key factor in the success of doing PNB.

Keywords: mastectomy, peripheral nerve block, erecto spinae block, PECS-2 block

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Authors: Niken Hartati

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This study provides a description of the problem and sources of social support that given to 90 mothers from poor households. Data were collected using structured interviews with the three main questions: 1) what kind of problem in mothers daily life, 2) to whom mothers ask for help to overcome it and 3) the form of the assistances that provided. Furthermore, the data were analyzed using content analysis techniques were then coded and categorized. The results of the study illustrate the problems experienced by mothers of poor households in the form of: subsistence (37%), child care (27%), management of money and time (20%), housework (5%), bad place of living (5%), the main breadwinner (3%), and extra costs (3%). While the sources of social support that obtained by mothers were; neighbors (10%), extended family (8%), children (8%), husband (7%), parents (7%), and siblings (5%). Unfortunately, more mothers who admitted not getting any social support when having problems (55%). The form of social support that given to mother from poor household were: instrumental support (91%), emotional support (5%) and informational support (2%). Implications for further intervention also discussed in this study.

Keywords: household problems, social support, mothers, poor households

Procedia PDF Downloads 349

Authors: Sarah Odofin, Zhiwei Gao

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Operations and maintenance of wind turbine have received much attention by researcher due to rapid expansion of wind farms. This paper explores a novel fault diagnosis that is designed and optimized to be very sensitive to faults and robust to disturbances. The faults considered are the sensor faults of which the augmented observer is considered to enlarge faults and to be robust to disturbance. A qualitative model based analysis is proposed for early fault diagnosis to minimize downtime mostly caused by components breakdown and exploit productivity. Simulation results are computed validating the models provided which demonstrates system performance using practical application of fault type examples. The results demonstrate the effectiveness of the developed techniques investigated in a Matlab/Simulink environment.

Keywords: wind turbine, condition monitoring, genetic algorithm, fault diagnosis, augmented observer, disturbance robustness, fault estimation, sensor monitoring

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Authors: M. Sirhan, S. Bekhor, A. Sidess

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In-service pavements deteriorate with time due to traffic wheel loads, environment, and climate conditions. Pavement deterioration leads to a reduction in their serviceability and structural behavior. Consequently, proper maintenance and rehabilitation (M&R) are necessary actions to keep the in-service pavement network at the desired level of serviceability. Due to resource and financial constraints, the pavement management system (PMS) prioritizes roads most in need of maintenance and rehabilitation action. It recommends a suitable action for each pavement based on the performance and surface condition of each road in the network. The pavement performance and condition are usually quantified and evaluated by different types of roughness-based and stress-based indices. Examples of such indices are Pavement Serviceability Index (PSI), Pavement Serviceability Ratio (PSR), Mean Panel Rating (MPR), Pavement Condition Rating (PCR), Ride Number (RN), Profile Index (PI), International Roughness Index (IRI), and Pavement Condition Index (PCI). PCI is commonly used in PMS as an indicator of the extent of the distresses on the pavement surface. PCI values range between 0 and 100; where 0 and 100 represent a highly deteriorated pavement and a newly constructed pavement, respectively. The PCI value is a function of distress type, severity, and density (measured as a percentage of the total pavement area). PCI is usually calculated iteratively using the 'Paver' program developed by the US Army Corps. The use of soft computing techniques, especially Artificial Neural Network (ANN), has become increasingly popular in the modeling of engineering problems. ANN techniques have successfully modeled the performance of the in-service pavements, due to its efficiency in predicting and solving non-linear relationships and dealing with an uncertain large amount of data. Typical regression models, which require a pre-defined relationship, can be replaced by ANN, which was found to be an appropriate tool for predicting the different pavement performance indices versus different factors as well. Subsequently, the objective of the presented study is to develop and train an ANN model that predicts the PCI values. The model’s input consists of percentage areas of 11 different damage types; alligator cracking, swelling, rutting, block cracking, longitudinal/transverse cracking, edge cracking, shoving, raveling, potholes, patching, and lane drop off, at three severity levels (low, medium, high) for each. The developed model was trained using 536,000 samples and tested on 134,000 samples. The samples were collected and prepared by The National Transport Infrastructure Company. The predicted results yielded satisfactory compliance with field measurements. The proposed model predicted PCI values with relatively low standard deviations, suggesting that it could be incorporated into the PMS for PCI determination. It is worth mentioning that the most influencing variables for PCI prediction are damages related to alligator cracking, swelling, rutting, and potholes.

Keywords: artificial neural networks, computer programming, pavement condition index, pavement management, performance prediction

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Authors: Sandesh Achar

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Cloud computing security is a broad term that covers a variety of security concerns for organizations that use cloud services. Multi-cloud service providers must consider several factors when addressing security for their customers, including identity and access management, data at rest and in transit, egress and ingress traffic control, vulnerability and threat management, and auditing. This paper explores each of these aspects of cloud security in detail and provides recommendations for best practices for multi-cloud service providers. It also discusses the challenges inherent in securing a multi-cloud environment and offers solutions for overcoming these challenges. By the end of this paper, readers should have a good understanding of the various security concerns associated with multi-cloud environments in the context of today’s modern cyber threats and how to address them.

Keywords: multi-cloud service, system organization control, data loss prevention, identity and access management

Procedia PDF Downloads 81

Authors: Frank Alexis, Jenny Antonia Rodriguez Leon, Cristobal Leonardo Dominguez Borbor, Mery Rosario Ramirez Munoz

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The shrimp industry has increased in the last years to the point of becoming one of the most dynamic industries. However, the appearance of diseases that significantly affect the production of shrimps has been an obstacle for the shrimp industry. We hypothesized that natural fibers from biodiversity can stimulate the immune system to prevent shrimp diseases like vibriosis. In this project, we extracted the fibers from vegetal sources in Ecuador and characterized them using common techniques like XRD, SEM, and then we tested the effect of fibers as immunostimulants for shrimps in-vitro and in-vivo using small aquarium and large pools. Our results demonstrate that vegetal fibers can significantly increase the survival of shrimps. Moreover, the production of shrimps in a large pool was significantly increased. Lastly, the test of color and taste successfully surpass the control group of shrimps not treated with fiber food supplements.

Keywords: fibers, immunostimulant, shrimp, vibriosis

Procedia PDF Downloads 144

Authors: Nasser A. Al-Azri

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The effectiveness of passive cooling techniques is assessed based on bioclimatic charts that require the typical meteorological year (TMY) for a specified location for their development. However, TMYs are not always available; mainly due to the scarcity of records of solar radiation which is an essential component used in developing common TMYs intended for general uses. Since solar radiation is not required in the development of the bioclimatic chart, this work suggests developing TMYs based solely on the relevant parameters. This approach improves the accuracy of the developed TMY since only the relevant parameters are considered and it also makes the development of the TMY more accessible since solar radiation data are not used. The presented paper will also discuss the development of the TMY from the raw data available at the NOAA-NCDC archive of world weather data and the construction of the bioclimatic charts for some randomly selected locations around the world.

Keywords: bioclimatic charts, passive cooling, TMY, weather data

Procedia PDF Downloads 226

Authors: Broderick Crawford, Ricardo Soto, Natalia Berrios, Eduardo Olguin

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In this paper, we present a binary cat swarm optimization for solving the Set covering problem. The set covering problem is a well-known NP-hard problem with many practical applications, including those involving scheduling, production planning and location problems. Binary cat swarm optimization is a recent swarm metaheuristic technique based on the behavior of discrete cats. Domestic cats show the ability to hunt and are curious about moving objects. The cats have two modes of behavior: seeking mode and tracing mode. We illustrate this approach with 65 instances of the problem from the OR-Library. Moreover, we solve this problem with 40 new binarization techniques and we select the technical with the best results obtained. Finally, we make a comparison between results obtained in previous studies and the new binarization technique, that is, with roulette wheel as transfer function and V3 as discretization technique.

Keywords: binary cat swarm optimization, binarization methods, metaheuristic, set covering problem

Procedia PDF Downloads 382

Authors: Artemis Louppis, Michalis Constantinou, Ioanna Kosma, Federica Blando, Michael Kontominas, Anastasia Badeka

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The aim of the present study was to differentiate yellow prickly pear according to geographical origin based on the combination of mineral content, physicochemical parameters, vitamins and antioxidants. A total of 240 yellow prickly pear samples from Cyprus, Spain, Italy and Greece were analyzed for pH, titratable acidity, electrical conductivity, protein, moisture, ash, fat, antioxidant activity, individual antioxidants, sugars and vitamins by UPLC-MS/MS as well as minerals by ICP-MS. Statistical treatment of the data included multivariate analysis of variance followed by linear discriminant analysis. Based on results, a correct classification of 66.7% was achieved using the cross validation by mineral content while 86.1% was achieved using the cross validation method by combination of all analytical parameters.

Keywords: geographical differentiation, prickly pear, chemometrics, analytical techniques

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder

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Authors: Ines Raies, Eric Kohler, Marc Fleury, Béatrice Ledésert

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In this work, the impact of clay minerals on the formation damage of sandstone reservoirs is studied to provide a better understanding of the problem of deep geothermal reservoir permeability reduction due to fine particle dispersion and migration. In some situations, despite the presence of filters in the geothermal loop at the surface, particles smaller than the filter size (<1 µm) may surprisingly generate significant permeability reduction affecting in the long term the overall performance of the geothermal system. Our study is carried out on cores from a Triassic reservoir in the Paris Basin (Feigneux, 60 km Northeast of Paris). Our goal is to first identify the clays responsible for clogging, a mineralogical characterization of these natural samples was carried out by coupling X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS). The results show that the studied stratigraphic interval contains mostly illite and chlorite particles. Moreover, the spatial arrangement of the clays in the rocks as well as the morphology and size of the particles, suggest that illite is more easily mobilized than chlorite by the flow in the pore network. Thus, based on these results, illite particles were prepared and used in core flooding in order to better understand the factors leading to the aggregation and deposition of this type of clay particles in geothermal reservoirs under various physicochemical and hydrodynamic conditions. First, the stability of illite suspensions under geothermal conditions has been investigated using different characterization techniques, including Dynamic Light Scattering (DLS) and Scanning Transmission Electron Microscopy (STEM). Various parameters such as the hydrodynamic radius (around 100 nm), the morphology and surface area of aggregates were measured. Then, core-flooding experiments were carried out using sand columns to mimic the permeability decline due to the injection of illite-containing fluids in sandstone reservoirs. In particular, the effects of ionic strength, temperature, particle concentration and flow rate of the injected fluid were investigated. When the ionic strength increases, a permeability decline of more than a factor of 2 could be observed for pore velocities representative of in-situ conditions. Further details of the retention of particles in the columns were obtained from Magnetic Resonance Imaging and X-ray Tomography techniques, showing that the particle deposition is nonuniform along the column. It is clearly shown that very fine particles as small as 100 nm can generate significant permeability reduction under specific conditions in high permeability porous media representative of the Triassic reservoirs of the Paris basin. These retention mechanisms are explained in the general framework of the DLVO theory

Keywords: geothermal energy, reinjection, clays, colloids, retention, porosity, permeability decline, clogging, characterization, XRD, SEM-EDS, STEM, DLS, NMR, core flooding experiments

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Authors: Houcine Ammar

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Chromenederivatives are an important class of heterocycles that are found in a wide range of natural products. Chromenes are commonly used as cosmetics, food additives, and possibly biodegradable agrochemicals. Recently, the synthesis of chromene derivatives has drawn more attention due to their pharmacological and biological applications. In the present work, we are interested in the synthesis and characterization of chromeno [2,3-b] pyridin-4-yl) formimidate, carried out in 4 steps: (i) the synthesis of 3-cyanoiminocoumarins is realized first by Knœvenagel reaction by reacting malonitrile with variously substituted o-phenolic benzaldehydes. In order to undergo reduction by sodium tetraborohydride NaBH4 to lead to new 2-amino-3-cyano-4H-chromenes, these compounds were easily transformed by the action of malonitrile leading to 2,4-diamino-5H-chromeno [2,3-b] pyridine-3-carbonitrile under microwave activation. For the final step, the action of triethylorthoformate on 2,4-diamino-5H-chromeno [2,3-b] pyridine-3-carbonitrile leads to new chromeno [2,3-b] pyridinheterocycles. -4-yl) formimidate. The synthesized compounds have been characterized by different spectroscopic techniques 1 H-NMR, 13 C-NMR, and IRTF.

Keywords: chromene, microwave, knovenagel condensation, chromeno [2, 3-b] pyridine

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Authors: Celestine Mbakaan, Iorkyaa Ahemen, A. D. Onoja, A. N. Amah, Emmanuel Barki

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Rice husk (RH) is a natural sheath that forms and covers the grain of rice. The husk composed of hard materials, including opaline silica and lignin. It separates from its grain during rice milling. RH also contains approximately 15 to 28 wt % of silica in hydrated amorphous form. Nanosilica was derived from the husk of different rice varieties after pre-treating the husk (RH) with HCl and calcination at 550°C. Nanosilica derived from the husk of Osi rice variety produced the highest silica yield, and further pretreatment with 0.8 M H₃PO₄ acid removed more mineral impurities. The silica obtained from this rice variety was selected as a host matrix for doping with Sm³⁺ ions. Rice husk silica (RH-SiO₂) doped with samarium (RH-SiO₂: xSm³⁺ (x=0.01, 0.05, and 0.1 molar ratios) nanophosphors were synthesized via the sol-gel method. The structural analysis by X-ray diffraction analysis (XRD) reveals amorphous structure while the surface morphology, as revealed by SEM and TEM, indicates agglomerates of nano-sized spherical particles with an average particle size measuring 21 nm. The nanophosphor has a large surface area measuring 198.0 m²/g, and Fourier transform infrared spectroscopy (FT-IR) shows only a single absorption band which is strong and broad with a valley at 1063 cm⁻¹. Diffuse reflectance spectroscopy (DRS) shows strong absorptions at 319, 345, 362, 375, 401, and 474 nm, which can be exclusively assigned to the 6H5/2→4F11/2, 3H7/2, 4F9/2, 4D5/2, 4K11/2, and 4M15/2 + 4I11/2, transitions of Sm³⁺ respectively. The photoluminescence excitation spectra show that near UV and blue LEDs can effectively be used as excitation sources to produce red-orange and yellow-orange emission from Sm³⁺ ion-doped RH-SiO₂ nanophosphors. The photoluminescence (PL) of the nanophosphors gives three main lines; 568, 605, and 652 nm, which are attributed to the intra-4f shell transitions from the excited level to ground levels, respectively under excitation wavelengths of 365 and 400 nm. The result, as confirmed from the 1931 CIE coordinates diagram, indicates the emission of red-orange light by RH-SiO₂: xSm³⁺ (x=0.01 and 0.1 molar ratios) and yellow-orange light from RH-SiO₂: 0.05 Sm³⁺. Finally, the result shows that RH-SiO₂ doped with samarium (Sm³⁺) ions can be applicable in display applications.

Keywords: luminescence, nanosilica, nanophosphors, Sm³⁺

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Authors: Tuğba Horzum, Ahmet Arikan

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This paper was part of a broader study that investigated what blind students (BSs) understood and how they used concept definitions (CDs) and concept images (CIs) for some mathematical concepts. This paper focused on the polygon concept. For this purpose, four open-ended questions were asked to five blind middle school students. During the interviews, BSs were presented with raised-line materials and were given opportunities to construct geometric shapes with magnetic sticks and micro-balls. Qualitative research techniques applied in grounded theory were used for analyzing documents pictures which were taken from magnetic geometric shapes that BSs constructed, raised-line materials and researcher’s observation notes and interviews. At the end of the analysis, it was observed that BSs used mostly their CIs and never took into account the CDs. Besides, BSs encountered with the difficulties associated with the combination of polygon edges’ endpoints consecutively. Additionally, they focused on the interior of the polygon and the angles which have smaller a size. Lastly, BSs were often conflicted about triangle, rectangle, square and circle whether or not a polygon.

Keywords: blind students, concept definition, concept image, polygon

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