Search results for: cost accounting systems

Authors: Papon Thamvasupong, Kwanchanok Viravaidya-Pasuwat

Abstract:

Osteoarthritis affects a lot of people worldwide. Local injection of glucosamine is one of the alternative treatment methods to replenish the natural lubrication of cartilage. However, multiple injections can potentially lead to possible bacterial infection. Therefore, a drug delivery system is desired to reduce the frequencies of injections. A hydrogel is one of the delivery systems that can control the release of drugs. Thermo-reversible hydrogels can be beneficial to the drug delivery system especially in the local injection route because this formulation can change from liquid to gel after getting into human body. Once the gel is in the body, it will slowly release the drug in a controlled manner. In this study, various formulations of Pluronic-based hydrogels were synthesized for the controlled release of glucosamine. One of the challenges of the Pluronic controlled release system is its fast dissolution rate. To overcome this problem, alginate and calcium sulfate (CaSO₄) were added to the polymer solution. The characteristics of the hydrogels were investigated including the gelation temperature, gelation time, hydrogel dissolution and glucosamine release mechanism. Finally, a mathematical model of glucosamine release from Pluronic-alginate-hyaluronic acid hydrogel was developed. Our results have shown that crosslinking Pluronic gel with alginate did not significantly extend the dissolution rate of the gel. Moreover, the gel dissolution profiles and the glucosamine release mechanisms were best described using the zeroth-order kinetic model, indicating that the release of glucosamine was primarily governed by the gel dissolution.

Keywords: controlled release, drug delivery system, glucosamine, pluronic, thermoreversible hydrogel

Procedia PDF Downloads 270

Authors: Maryam Hasheminasab, Ahmed Cheldavi, Ahmed Kishk

Abstract:

Frequency-diverse arrays (FDAs) have garnered significant attention from researchers due to their ability to combine frequency diversity with the inherent spatial diversity of an array. The introduction of frequency diversity in FDAs enables the generation of auto-scanning patterns that are range-dependent, which can have advantageous applications in communication and radar systems. However, the main challenge in implementing FDAs lies in determining the technique for distributing frequencies among the array elements. One approach to address this challenge is by utilizing coupled oscillators, which are a technique commonly employed in active microwave theory. Nevertheless, the limited stability range of coupled oscillators poses another obstacle to effectively utilizing this technique. In this paper, we explore the possibility of employing a coupled oscillator array in the mode lock state (MLS) for implementing frequency distribution in FDAs. Additionally, we propose and simulate the use of a digital phase-locked loop (DPLL) as a backup technique to stabilize the oscillators. Through simulations, we validate the functionality of this technique. This technique holds great promise for advancing the implementation of phased arrays and overcoming current scan rate and phase shifter limitations, especially in millimeter wave frequencies.

Keywords: angle-changing rate, auto scanning beam, pull-in range, hold-in range, locking range, mode locked state, frequency locked state

Procedia PDF Downloads 86

Authors: Z. Karahaliloğlu, C. Hacker, M. Demirbilek, G. Seide, E. B. Denkbaş, T. Gries

Abstract:

Currently, textile industry has played an important role in world’s economy, especially in developing countries. Dyes and pigments used in textile industry are significant pollutants. Most of theirs are azo dyes that have chromophore (-N=N-) in their structure. There are many methods for removal of the dyes from wastewater such as chemical coagulation, flocculation, precipitation and ozonation. But these methods have numerous disadvantages and alternative methods are needed for wastewater decolorization. Titanium-mediated photodegradation has been used generally due to non-toxic, insoluble, inexpensive, and highly reactive properties of titanium dioxide semiconductor (TiO2). Melt electrospinning is an attractive manufacturing process for thin fiber production through electrospinning from PP (Polyprophylene). PP fibers have been widely used in the filtration due to theirs unique properties such as hydrophobicity, good mechanical strength, chemical resistance and low-cost production. In this study, we aimed to investigate the effect of titanium nanoparticle localization and amine modification on the dye degradation. The applicability of the prepared chemical activated composite and pristine fabrics for a novel treatment of dyeing wastewater were evaluated.In this study, a photocatalyzer material was prepared from nTi (titanium dioxide nanoparticles) and PP by a melt-electrospinning technique. The electrospinning parameters of pristine PP and PP/nTi nanocomposite fabrics were optimized. Before functionalization with nTi, the surface of fabrics was activated by a technique using glutaraldehyde (GA) and polyethyleneimine to promote the dye degredation. Pristine PP and PP/nTi nanocomposite melt-electrospun fabrics were characterized using scanning electron microscopy (SEM) and X-Ray Photon Spectroscopy (XPS). Methyl orange (MO) was used as a model compound for the decolorization experiments. Photocatalytic performance of nTi-loaded pristine and nanocomposite melt-electrospun filters was investigated by varying initial dye concentration 10, 20, 40 mg/L). nTi-PP composite fabrics were successfully processed into a uniform, fibrous network of beadless fibers with diameters of 800±0.4 nm. The process parameters were determined as a voltage of 30 kV, a working distance of 5 cm, a temperature of the thermocouple and hotcoil of 260–300 ºC and a flow rate of 0.07 mL/h. SEM results indicated that TiO2 nanoparticles were deposited uniformly on the nanofibers and XPS results confirmed the presence of titanium nanoparticles and generation of amine groups after modification. According to photocatalytic decolarization test results, nTi-loaded GA-treated pristine or nTi-PP nanocomposite fabric filtern have superior properties, especially over 90% decolorization efficiency at GA-treated pristine and nTi-PP composite PP fabrics. In this work, as a photocatalyzer for wastewater treatment, surface functionalized with nTi melt-electrospun fabrics from PP were prepared. Results showed melt-electrospun nTi-loaded GA-tretaed composite or pristine PP fabrics have a great potential for use as a photocatalytic filter to decolorization of wastewater and thus, requires further investigation.

Keywords: titanium oxide nanoparticles, polyprophylene, melt-electrospinning

Procedia PDF Downloads 267

Authors: S. Colclough, V. Costanzo, K. Fabbri, S. Piraccini, P. Griffiths

Abstract:

The near Zero Energy Building (nZEB) standard is required for all buildings from 2020. The Passive House (PH) standard is a well-established low-energy building standard, having been designed over 25 years ago, and could potentially be used to achieve the nZEB standard in combination with renewables. By comparing measured performance with design predictions, this paper considers if there is a performance gap for a number of monitored properties and assesses if the nZEB standard can be achieved by following the well-established PH scheme. Analysis is carried out based on monitoring results from real buildings located in Northern Ireland, the Republic of Ireland and Italy respectively, with particular focus on the indoor air quality including the assumed and measured indoor temperature and heating periods for both standards as recorded during a full annual cycle. An analysis is carried out also on the energy performance certificates of each of the dwellings to determine if they meet the near Zero Energy Buildings primary energy consumption targets set in the respective jurisdictions. Each of the dwellings is certified as complying with the passive house standard, and accordingly have very good insulation levels, heat recovery and ventilation systems of greater than 75% efficiency and an airtightness of less than 0.6 air changes per hour at 50 Pa. It is found that indoor temperature and relative humidity were within the comfort boundaries set in the design stage, while carbon dioxide concentrations are sometimes higher than the values suggested by EN 15251 Standard for comfort class I especially in bedrooms.

Keywords: monitoring campaign, nZEB (near zero energy buildings), Passivhaus, performance gap

Procedia PDF Downloads 152

Authors: Maxime A. J. Kuitche, Ruxandra M. Botez, Arthur Guillemin

Abstract:

As the Unmanned Aerial Systems have found diverse utilities in both military and civil aviation, the necessity to obtain an accurate aerodynamic model has shown an enormous growth of interest. Recent modeling techniques are procedures using optimization algorithms and statistics that require many flight tests and are therefore extremely demanding in terms of costs. This paper presents a procedure to estimate the aerodynamic behavior of an unmanned aerial system from a numerical approach using computational fluid dynamic analysis. The study was performed using an unstructured mesh obtained from a grid convergence analysis at a Mach number of 0.14, and at an angle of attack of 0°. The flow around the aircraft was described using a standard k-ω turbulence model. Thus, the Reynold Averaged Navier-Stokes (RANS) equations were solved using ANSYS FLUENT software. The method was applied on the UAS-S45 designed and manufactured by Hydra Technologies in Mexico. The lift, the drag, and the pitching moment coefficients were obtained at different angles of attack for several flight conditions defined in terms of altitudes and Mach numbers. The results obtained from the Computational Fluid Dynamics analysis were compared with the results obtained by using the DATCOM semi-empirical procedure. This comparison has indicated that our approach is highly accurate and that the aerodynamic model obtained could be useful to estimate the flight dynamics of the UAS-S45.

Keywords: aerodynamic modelling, CFD Analysis, ANSYS FLUENT, UAS-S45

Procedia PDF Downloads 375

Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

Abstract:

Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

Procedia PDF Downloads 98

Authors: Pedro J. Rolim-Neto, Leslie R. M. Ferraz, Fabiana L. A. Santos, Pablo A. Ferreira, Ricardo T. L. Maia-Jr., Magaly A. M. Lyra, Danilo A F. Fonte, Salvana P. M. Costa, Amanda C. Q. M. Vieira, Larissa A. Rolim

Abstract:

Initially developed as an antimalarial agent, hydroxychloroquine (HCQ) sulfate is often used as a slow-acting antirheumatic drug in the treatment of disorders of connective tissue. The United States Pharmacopeia (USP) 37 provides a reversed-phase HPLC method for quantification of HCQ. However, this method was not reproducible, producing asymmetric peaks in a long analysis time. The asymmetry of the peak may cause an incorrect calculation of the concentration of the sample. Furthermore, the analysis time is unacceptable, especially regarding the routine of a pharmaceutical industry. The aiming of this study was to develop a fast, easy and efficient method for quantification of HCQ sulfate by High Performance Liquid Chromatography (HPLC) based on the Quality by Design (QbD) methodology. This method was optimized in terms of peak symmetry using the surface area graphic as the Design of Experiments (DoE) and the tailing factor (TF) as an indicator to the Design Space (DS). The reference method used was that described at USP 37 to the quantification of the drug. For the optimized method, was proposed a 33 factorial design, based on the QbD concepts. The DS was created with the TF (in a range between 0.98 and 1.2) in order to demonstrate the ideal analytical conditions. Changes were made in the composition of the USP mobile-phase (USP-MP): USP-MP: Methanol (90:10 v/v, 80:20 v/v and 70:30 v/v), in the flow (0.8, 1.0 and 1.2 mL) and in the oven temperature (30, 35, and 40ºC). The USP method allowed the quantification of drug in a long time (40-50 minutes). In addition, the method uses a high flow rate (1,5 mL.min-1) which increases the consumption of expensive solvents HPLC grade. The main problem observed was the TF value (1,8) that would be accepted if the drug was not a racemic mixture, since the co-elution of the isomers can become an unreliable peak integration. Therefore, the optimization was suggested in order to reduce the analysis time, aiming a better peak resolution and TF. For the optimization method, by the analysis of the surface-response plot it was possible to confirm the ideal setting analytical condition: 45 °C, 0,8 mL.min-1 and 80:20 USP-MP: Methanol. The optimized HPLC method enabled the quantification of HCQ sulfate, with a peak of high resolution, showing a TF value of 1,17. This promotes good co-elution of isomers of the HCQ, ensuring an accurate quantification of the raw material as racemic mixture. This method also proved to be 18 times faster, approximately, compared to the reference method, using a lower flow rate, reducing even more the consumption of the solvents and, consequently, the analysis cost. Thus, an analytical method for the quantification of HCQ sulfate was optimized using QbD methodology. This method proved to be faster and more efficient than the USP method, regarding the retention time and, especially, the peak resolution. The higher resolution in the chromatogram peaks supports the implementation of the method for quantification of the drug as racemic mixture, not requiring the separation of isomers.

Keywords: analytical method, hydroxychloroquine sulfate, quality by design, surface area graphic

Procedia PDF Downloads 639

Authors: Ts. Lazarova, V. Tumbalev, S. Atanacova-Vladimirova, G. Ivanov, A. Naydenov, D. Kovacheva

Abstract:

Methane is a major Greenhouse Gas (GHG) that accounts for 14% of the world’s total amount of GHG emissions, originating mainly from agriculture, Coal mines, land fields, wastewater and oil and gas facilities. Nowadays the problem caused by the methane emissions has been a subject of an increased concern. One of the methods for neutralization of the methane emissions is it's complete catalytic oxidation. The efforts of the researchers are focused on the development of new types of catalysts and optimizing the existing catalytic systems in order to prevent the sintering of the palladium, providing at the same time a sufficient activity at temperatures below 500oC. The aim of the present work is to prepare mixed Cu-Ag-Pd oxide catalysts supported on alumina and to test them for methane complete catalytic oxidation. Cu-Ag-Pd/Al2O3 were prepared on a γ-Al2O3 (BET surface area = 220 m2/g) by the incipient wetness method using the corresponding metal nitrates (Cu:Ag = 90:10, Cu:Pd =97:3, Cu:Ag:Pd= 87:10:3) as precursors. A second set of samples were prepared with addition of urea to the metal nitrate solutions with the above mentioned ratios assuming increased dispersivity of the catalysts. The catalyst samples were dried at 100°C for 3 hours and calcined at 550°C for 30 minutes. Catalysts samples were characterized using X-ray diffraction (XRD), low temperature adsorption of nitrogen (BET) and scanning electron microscopy (SEM). The catalytic activity tests were carried out in a continuous flow type of reactor at atmospheric pressure. The effect of catalyst aging at 500 oC for 120 h on the methane combustion activity was also investigated. The results clearly indicate the synergetic effect of Ag and Pd on the catalytic activity.

Keywords: catalysts, XRD, BET, SEM, catalytic oxidation

Procedia PDF Downloads 382

Authors: Bipasa Dey, Varsha Panwar, Tanmay Dutta

Abstract:

Laccase, a multicopper oxidase (EC 1.10.3.2) have been at the forefront as a superior industrial biocatalyst. They are versatile in terms of bestowing sustainable and ecological catalytic reactions such as polymerisation, xenobiotic degradation and bioremediation of phenolic and non-phenolic compounds. Regardless of the wide biotechnological applications, the critical limiting factors viz. reusability, retrieval, and storage stability still prevail. This can cause an impediment in their applicability. Crosslinked enzyme aggregates (CLEAs) have emerged as a promising technique that rehabilitates these essential facets, albeit at the expense of their enzymatic activity. The carrier free crosslinking method prevails over the carrier-bound immobilisation in conferring high productivity, low production cost owing to the absence of additional carrier and circumvent any non-catalytic ballast which could dilute the volumetric activity. To the best of our knowledge, the ε-amino group of lysyl residue is speculated as the best choice for forming Schiff’s base with glutaraldehyde. Despite being most preferrable, excess glutaraldehyde can bring about disproportionate and undesirable crosslinking within the catalytic site and hence could deliver undesirable catalytic losses. Moreover, the surface distribution of lysine residues in Trametes versicolor laccase is significantly less. Thus, to mitigate the adverse effect of glutaraldehyde in conjunction with scaling down the degradation or catalytic loss of the enzyme, crosslinking with inert substances like gelatine, collagen, Bovine serum albumin (BSA) or excess lysine is practiced. Analogous to these molecules, sugars have been well known as a protein stabiliser. It helps to retain the structural integrity, specifically secondary structure of the protein during aggregation by changing the solvent properties. They are comprehended to avert protein denaturation or enzyme deactivation during precipitation. We prepared crosslinked enzyme aggregates (CLEAs) of laccase from T. versicolor with the aid of sugars. The sugar CLEAs were compared with the classic BSA and glutaraldehyde laccase CLEAs concerning physico-chemical properties. The activity recovery for the fructose CLEAs were found to be ~20% higher than the non-sugar CLEA. Moreover, the 𝐾𝑐𝑎𝑡𝐾𝑚⁄ values of the CLEAs were two and three-fold higher than BSA-CLEA and GACLEA, respectively. The half-life (t1/2) deciphered by sugar-CLEA was higher than the t1/2 of GA-CLEAs and free enzyme, portraying more thermal stability. Besides, it demonstrated extraordinarily high pH stability, which was analogous to BSA-CLEA. The promising attributes of increased storage stability and recyclability (>80%) gives more edge to the sugar-CLEAs over conventional CLEAs of their corresponding free enzyme. Thus, sugar-CLEA prevails in furnishing the rudimentary properties required for a biocatalyst and holds many prospects.

Keywords: cross-linked enzyme aggregates, laccase immobilization, enzyme reusability, enzyme stability

Procedia PDF Downloads 102

Authors: Jaime E. Munoz, Jose C. Arcos, Oscar E. Bautista, Ivan E. Campos

Abstract:

The influence of slippage phenomenon over the destabilization and atomization mechanisms induced via surface acoustic waves on a Newtonian, millimeter-sized, drop deposited on a hydrophilic substrate is studied theoretically. By implementing the Navier-slip model and a lubrication-type approach into the equations which govern the dynamic response of a drop exposed to acoustic stress, a highly nonlinear evolution equation for the air-liquid interface is derived in terms of the acoustic capillary number and the slip coefficient. By numerically solving such an evolution equation, the Spatio-temporal deformation of the drop's free surface is obtained; in this context, atomization of the initial drop into micron-sized droplets is predicted at our numerical model once the acoustically-driven capillary waves reach a critical value: the instability length. Our results show slippage phenomenon at systems with partial and complete wetting favors the formation of capillary waves at the free surface, which traduces in a major volume of liquid being atomized in comparison to the no-slip case for a given time interval. In consequence, slippage at the wall possesses the capability to affect and improve the atomization rate for a drop exposed to a high-frequency acoustic field.

Keywords: capillary instability, lubrication theory, navier-slip condition, SAW atomization

Procedia PDF Downloads 156

Authors: Anne M. Denton, Rahul Gomes, David W. Franzen

Abstract:

High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.

Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression

Procedia PDF Downloads 129

Authors: Xiaoling Ren, Guidong Yang

Abstract:

Ammonia, as one of the largest-volume industrial chemicals, is mostly produced by century-old Haber-Bosch process with extreme conditionsand high-cost. Under the circumstance, researchersarededicated in finding new ways to replace the Haber-Bosch process. Photocatalytic nitrogen fixation is a promising sustainable, clear and green strategy for ammonia synthesis, butit is still a big challenge due to the high activation energy for nitrogen. It is essential to develop an efficient photocatalyst for making this approach industrial application. Constructing chemisorption active sites through defect engineering can be defined as an effective and reliable means to improve nitrogen activation by forming the extraordinary coordination environment and electronic structure. Besides, the construction of three-dimensionally orderdmacroporous (3DOM) structured photocatalyst is considered to be one of effectivestrategiesto improve the activity due to it canincrease the diffusion rate of reactants in the interior, which isbeneficial to the mass transfer process of nitrogen molecules in photocatalytic nitrogen reduction. Herein, Fe doped 3DOM WO₃(Fe-3DOM WO₃) without noble metal cocatalysts is synthesized by a polystyrene-template strategy, which is firstly used for photocatalytic nitrogen fixation. To elucidate the chemical nature of the dopant, the X-ray diffraction (XRD) analysiswas conducted. The pure 3DOM WO₃ has a monoclinic type crystal structure. And no additional peak is observed in Fe doped 3DOM WO₃, indicating that the incorporation of Fe atoms did not result in a secondary phase formation. In order to confirm the morphologies of Fe-3DOM WO₃and 3DOM WO₃, scanning electron microscopy (SEM) was employed. The synthesized Fe-3DOM WO₃and 3DOM WO₃ both exhibit a highly ordered three dimensional inverse opal structure with interconnected pores. From high-resolution TEM image of Fe-3DOM WO₃, the ordered lattice fringes with a spacing of 3.84 Å can be assigned to the (001) plane of WO₃, which is consistent with the XRD results. Finally, the photocatalytic nitrogen reduction performance of 3DOM WO₃ and Fe doped 3DOM WO₃with various Fe contents were examined. As a result, both Fe-3DOM WO₃ samples achieve higher ammonia production rate than that of pure 3DOM WO₃, indicating that the doped Fe plays a critical role in the photocatalytic nitrogen fixation performance. To verify the reaction process upon N2 reduction on the Fe-3DOM WO₃, in-situ diffuse reflectance infrared Fourier-transform spectroscopy was employed to monitor the intermediates. The in-situ DRIFTS spectra of Fe-3DOM WO₃ exhibit the increased signals with the irradiation time from 0–60min in the N2 atmosphere. The above results prove that nitrogen is gradually hydrogenated to produce ammonia over Fe-3DOM WO₃. Thiswork would enrich our knowledge in designing efficient photocatalystsfor photocatalytic nitrogen reduction.

Keywords: ammonia, photocatalytic, nitrogen fixation, Fe doped 3DOM WO₃

Procedia PDF Downloads 171

Authors: Masahiro Miyaji

Abstract:

When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

Procedia PDF Downloads 359

Authors: Ehsan Mohseni, Waiching Tang, Shanyong Wang

Abstract:

Low thermal conductivity of phase change materials (PCMs) affects the thermal performance and energy storage efficiency of latent heat thermal energy storage systems. In the current research, a structural lightweight concrete with function of indoor temperature control was developed using thermal energy storage aggregates (TESA) and nano-titanium (NT). The macro-encapsulated technique was served to incorporate the PCM into the lightweight aggregate through vacuum impregnation. The compressive strength was measured, and the thermal performance of concrete panel was evaluated by using a self-designed environmental chamber. The impact of NT on microstructure was also assessed via scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) tests. The test results indicated that NT was able to increase the compressive strength by filling the micro pores and making the microstructure denser and more homogeneous. In addition, the environmental chamber experiment showed that introduction of NT into TESA improved the heat transfer of composites noticeably. The changes were illustrated by the reduction in peak temperatures in the centre, outside and inside surfaces of concrete panels by the inclusion of NT. It can be concluded that NT particles had the capability to decrease the energy consumption and obtain higher energy storage efficiency by the reduction of indoor temperature.

Keywords: heat transfer, macro-encapsulation, microstructure properties, nanoparticles, phase change material

Procedia PDF Downloads 105

Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

Abstract:

We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

Procedia PDF Downloads 369

Authors: Surena V.

Abstract:

Background and Aim: Periodontal diseases are among the most common infectious diseases all around the world, even in developed countries. Considering the increased rate of microbial resistance to antibiotics and the chemical side effects of antibiotics and antiseptics used for the treatment of periodontal disease, there is a need for an alternative antimicrobial agent with fewer complications. Medicinal herbs have recently become popular as antimicrobial and preventive agents. This study aimed to assess the antibacterial effects of hydroalcoholic extracts of Lawsonia inermis, Malva sylvestris and Boswellia serrata on Aggregatibacter actinomycetemcomitans (A. actinomycetemcomitans). Materials and Methods: Hydroalcoholic extracts of the three medicinal plants were obtained by the maceration technique and A. actinomycetemcomitans was cultured. The antimicrobial efficacy of the three medicinal plants was compared with that of 0.2% chlorhexidine (CHX) according to the CLSI protocol using agar disc diffusion and broth microdilution techniques. All tests were repeated three times. Results: Hydroalcoholic extracts of all three plants had antimicrobial activity against A. actinomycetemcomitans. The minimum inhibitory concentration (MIC) of Lawsonia inermis, Malva sylvestris, and Boswellia serrata was 78.1, 156.2, and 1666 µg/mL with no significant difference between them. The MIC of CHX was 3.33 µg/mL, which was significantly higher than that of Boswellia serrata extract. Conclusion: Given that, further in vivo studies confirm other properties of these extracts and their safety in terms of cytotoxicity and mutagenicity, hydroalcoholic extracts of Lawsonia inermis and Malva sylvestris may be used in mouthwashes or local delivery systems to affect periodontal biofilm.

Keywords: actinobacilus actinomycetem commitans, lawsonia inermis, malva sylvestris, boswellia serrata

Procedia PDF Downloads 59

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

Abstract:

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

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

Procedia PDF Downloads 210

Authors: Bulcha Belay Etana

Abstract:

Research shows that several challenges are to be resolved for textile sensors and wearable smart textiles systems to make it accurate and reproducible minimizing variability issues when tested. To achieve this, we developed stimulating embroidery electrode with three different filling textiles such as 3Dknit, microfiber, and nonwoven fabric, and tested with FTT for high recoverability on compression. Hence The impedance characteristics of wetted electrodes were caried out after 1hr of wetting under normal environmental conditions. The wetted 3D knit (W-3D knit), Wetted nonwoven (W-nonwoven), and wetted microfiber (W-microfiber) developed using Satin stitch performed better than a dry standard stitch or dry Satin stitch electrodes. Its performance was almost the same as that of the gel electrode (Ag/AgCl) as shown by the impedance result in figure 2 .The impedance characteristics of Dry and wetted 3D knit based Embroidered electrodes are better than that of the microfiber, and nonwoven filling textile. This is due to the fact that 3D knit fabric has high recoverability on compression to retain electrolyte gel than microfiber, and nonwoven. However,The non-woven fabric held the electrolyte for longer time without releasing it to the skin when needed, thus making its impedance characteristics poor as observed from the results. Whereas the dry Satin stitch performs better than the standard stitch based developed electrode. The inter electrode distance of all types of the electrode was 25mm, with the area of the electrode being 20mm by 20mm. Detail evaluation and further analysis is in progress for EMG monitoring application

Keywords: impedance, moisture retention, 3D knit fabric, microfiber, nonwoven

Procedia PDF Downloads 140

Authors: Rajvir Kaur, Jeewani Anupama Ginige

Abstract:

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

Procedia PDF Downloads 277

Authors: Atish Bagchi, Siva Chandrasekaran

Abstract:

Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

Procedia PDF Downloads 150

Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

Abstract:

Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

Procedia PDF Downloads 237

Authors: Miriam Corrado, Roberta Ciccola, Maria Serena Chiucchi

Abstract:

SDGs represent the last edge in the sustainability corporate practices, including the supply chain management. Supply chains are becoming more global and complex, can create more inclusive markets and make contribution to the advance of the sustainable development. In corporate practices, the presence of sustainability criteria in supply chain management could offer an opportunity to increase competitiveness and to meet stakeholders’ expectations in terms of sustainability and corporate accountability. The research aims to understand how focal companies can integrate SDGs in their supply chain and how they can measure and assess their impacts on SDGs. The study adopts a multiple case study methodology based on four case studies referred to companies committed in measuring SDGs’ performance in their supply chains. Preliminary findings demonstrate the willingness and the need of companies to commit under a supply-chain perspective for the achievement of SDGs. Companies recognize their role in impacting the SDGs through their procurement choices by defining and implementing an SDGs scoring system. The contribution of the study is twofold: first, given the lack of research and studies addressing the integration of SDGs in the supply chain and in the performance measurement systems, the research provides a contribution to the current academic literature in relation to these emerging gaps; second, the research provides a practical guidance to implement a sustainable supply chain and advance towards the achievement of SDGs.

Keywords: sustainable supply chains, sustainable development goals, performance measurement, performance management

Procedia PDF Downloads 195

Authors: Maria Pintea, Nigel Mason

Abstract:

Induced chemistry is one of the newest pathways in the nanotechnology field with applications in the focused electron beam induced processes for deposition of nm scale structures. Si(OPr)₄ and Ti(OEt)₄ are two of the precursors that have not been so extensively researched, though highly sought for semiconductor and medical applications fields, the two compounds make good candidates for FEBIP and are the subject of velocity slice map imaging analysis for deposition purposes, offering information on kinetic energies, fragmentation channels, and angular distributions. The velocity slice map imaging technique is a method used for the characterization of molecular dynamics of the molecule and the fragmentation channels as a result of induced chemistry. To support the gas-phase analysis, Meso-Bio-Nano simulations of irradiation dynamics studies are employed with final results on Fe(CO)₅ deposited on various substrates. The software is capable of running large scale simulations for complex biomolecular, nano- and mesoscopic systems with applications to thermos-mechanical DNA damage, complex materials, gases, nanoparticles for cancer research and deposition applications for nanotechnology, using a large library of classical potentials, many-body force fields, molecular force fields involved in the classical molecular dynamics.

Keywords: focused electron beam induced deposition, FEBID, induced chemistry, molecular dynamics, velocity map slice imaging

Procedia PDF Downloads 109

Authors: Rituparna Pal, Faiz Ahmed

Abstract:

Neighbourhood energy efficiency is a newly emerged term to address the quality of urban strata of built environment in terms of various covariates of sustainability. The concept of sustainability paradigm in developed nations has encouraged the policymakers for developing urban scale cities to envision plans under the aegis of urban scale sustainability. The concept of neighbourhood energy efficiency is realized a lot lately just when the cities, towns and other areas comprising this massive global urban strata have started facing a strong blow from climate change, energy crisis, cost hike and an alarming shortfall in the justice which the urban areas required. So this step of urban sustainability can be easily referred more as a ‘Retrofit Action’ which is to cover up the already affected urban structure. So even if we start energy efficiency for existing cities and urban areas the initial layer remains, for which a complete model of urban sustainability still lacks definition. Urban sustainability is a broadly spoken off word with end number of parameters and policies through which the loop can be met. Out of which neighbourhood energy efficiency can be an integral part where the concept and index of neighbourhood scale indicators, block level indicators and building physics parameters can be understood, analyzed and concluded to help emerge guidelines for urban scale sustainability. The future of neighbourhood energy efficiency not only lies in energy efficiency but also important parameters like quality of life, access to green, access to daylight, outdoor comfort, natural ventilation etc. So apart from designing less energy-hungry buildings, it is required to create a built environment which will create less stress on buildings to consume more energy. A lot of literary analysis has been done in the Western countries prominently in Spain, Paris and also Hong Kong, leaving a distinct gap in the Indian scenario in exploring the sustainability at the urban strata. The site for the study has been selected in the upcoming capital city of Amaravati which can be replicated with similar neighbourhood typologies in the area. The paper suggests a methodical intent to quantify energy and sustainability indices in detail taking by involving several macro, meso and micro level covariates and parameters. Several iterations have been made both at macro and micro level and have been subjected to simulation, computation and mathematical models and finally to comparative analysis. Parameters at all levels are analyzed to suggest the best case scenarios which in turn is extrapolated to the macro level finally coming out with a proposal model for energy efficient neighbourhood and worked out guidelines with significance and correlations derived.

Keywords: energy quantification, macro scale parameters, meso scale parameters, micro scale parameters

Procedia PDF Downloads 176

Authors: Preethi Kumari P., Shetty Prakasha, Rao Suma A.

Abstract:

Mild steel has been widely employed as construction materials for pipe work in the oil and gas production such as down hole tubular, flow lines and transmission pipelines, in chemical and allied industries for handling acids, alkalis and salt solutions due to its excellent mechanical property and low cost. Acid solutions are widely used for removal of undesirable scale and rust in many industrial processes. Among the commercially available acids hydrochloric acid is widely used for pickling, cleaning, de-scaling and acidization of oil process. Mild steel exhibits poor corrosion resistance in presence of hydrochloric acid. The high reactivity of mild steel in presence of hydrochloric acid is due to the soluble nature of ferrous chloride formed and the cementite phase (Fe3C) normally present in the steel is also readily soluble in hydrochloric acid. Pitting attack is also reported to be a major form of corrosion in mild steel in the presence of high concentrations of acids and thereby causing the complete destruction of metal. Hydrogen from acid reacts with the metal surface and makes it brittle and causes cracks, which leads to pitting type of corrosion. The use of chemical inhibitor to minimize the rate of corrosion has been considered to be the first line of defense against corrosion. In spite of long history of corrosion inhibition, a highly efficient and durable inhibitor that can completely protect mild steel in aggressive environment is yet to be realized. It is clear from the literature review that there is ample scope for the development of new organic inhibitors, which can be conveniently synthesized from relatively cheap raw materials and provide good inhibition efficiency with least risk of environmental pollution. The aim of the present work is to evaluate the electrochemical parameters for the corrosion inhibition behavior of an aromatic hydrazide derivative, 4-hydroxy- N '-[(E)-1H-indole-2-ylmethylidene)] benzohydrazide (HIBH) on mild steel in 2M hydrochloric acid using Tafel polarization and electrochemical impedance spectroscopy (EIS) techniques at 30-60 °C. The results showed that inhibition efficiency increased with increase in inhibitor concentration and decreased marginally with increase in temperature. HIBH showed a maximum inhibition efficiency of 95 % at 8×10-4 M concentration at 30 °C. Polarization curves showed that HIBH act as a mixed-type inhibitor. The adsorption of HIBH on mild steel surface obeys the Langmuir adsorption isotherm. The adsorption process of HIBH at the mild steel/hydrochloric acid solution interface followed mixed adsorption with predominantly physisorption at lower temperature and chemisorption at higher temperature. Thermodynamic parameters for the adsorption process and kinetic parameters for the metal dissolution reaction were determined.

Keywords: electrochemical parameters, EIS, mild steel, tafel polarization

Procedia PDF Downloads 337

Authors: Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran

Abstract:

Dengue outbreaks are affected by biological, ecological, socio-economic and demographic factors that vary over time and space. These factors have been examined separately and still require systematic clarification. The present study aimed to investigate the spatial-temporal clustering relationships between these factors and dengue outbreaks in the northern region of Sri Lanka. Remote sensing (RS) data gathered from a plurality of satellites were used to develop an index comprising rainfall, humidity and temperature data. RS data gathered by ALOS/AVNIR-2 were used to detect urbanization, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analyzed RS data and databases were integrated into geographic information systems, enabling temporal analysis, spatial statistical analysis and space-time clustering analysis. Our present results showed that increases in the number of the combination of ecological factor and socio-economic and demographic factors with above the average or the presence contribute to significantly high rates of space-time dengue clusters.

Keywords: ALOS/AVNIR-2, dengue, space-time clustering analysis, Sri Lanka

Procedia PDF Downloads 476

Authors: Kanagarajah Ravishankar

Abstract:

This paper describes a study performed for a project featuring an elevated steel bridge structure supported by various types of foundation systems. This project focused on rehabilitation or redesign of a portion of the bridge substructures founded on caisson foundations. The study that this paper focuses on is the evaluation of foundation and soil stiffnesses and interactions between the existing caissons and proposed foundations. The caisson foundations were founded on top of rock, where the depth to the top of rock varies from approximately 50 to 140 feet below ground surface. Based on a comprehensive investigation of the existing piers and caissons, the presence of ASR was suspected from observed whitish deposits on cracked surfaces as well as internal damages sustained through the entire depth of foundation structures. Reuse of existing piers and caissons was precluded and deemed unsuitable under the earthquake condition because of these defects on the structures. The proposed design of new foundations and substructures which was selected ultimately neglected the contribution from the existing caisson and pier columns. Due to the complicated configuration between the existing caisson and the proposed foundation system, three-dimensional finite element method (FEM) was employed to evaluate soil-structure interaction (SSI), to evaluate the effect of the existing caissons on the proposed foundations, and to compare the results with conventional group analysis. The FEM models include separate models for existing caissons, proposed foundations, and combining both.

Keywords: soil-structure interaction, foundation stiffness, finite element, seismic design

Procedia PDF Downloads 138

Authors: C. V. Aravinda, H. N. Prakash

Abstract:

In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.

Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages

Procedia PDF Downloads 494

Authors: Mónica Catarina Soares

Abstract:

Neoliberal rationality is currently changing the ways concepts like freedom or equality are framed. As an omnipresent and context-sensitive paradigm, homo oeconomicus is continuously taking place in realms of life previously insulated from economic and market-driven principles. This presentation is based on the argument that, more than ever, this paradigm is nowadays framing institutional and everyday discourses in regard to social problems. Although neoliberal rationality is based on the putative ideological basis that everyone is equal, equality seems to be reshaped by specific meanings apprehended by this rationality. In this sense, an illusion of equality seems to be relevant to legitimize different social inequalities (e.g., access to health care or to habitation). Political psychology has studied how ideology is relevant to legitimize market and unequal systems, but still the specific relation between markets, (in)equality and neoliberal languages is not widely addressed. The goal is to discuss the smithereens of the neoliberal rationality when it comes to legitimizing social inequalities by contesting the arguments of meritocracy, progressive freedom and minimal guarantees obeying to market-rules and principles. This analysis can be helpful to grasp for instance the continuously dismantlement of the welfare-state in different countries of the global north and how it is turning the regulation/emancipation tension inside out. The ultimate goal is to contribute to the breaking up of a paradigm that is still too big to capture, too depoliticized and chameleonic to fully acknowledge the biopolitics of power that is helping to create it.

Keywords: discourses, legitimacy, neoliberal rationality, social inequality

Procedia PDF Downloads 221

Authors: Hamid El Qarnia

Abstract:

This study investigates the impact of the eccentricity of the central tube on the thermal and fluid characteristics of a triplex tube used in latent heat energy storage technologies. Two triplex tube orientations are considered in the proposed study: vertical and horizontal. The energy storage material, which is a phase change material (PCM), is placed in the space between the inside and outside tubes. During the thermal energy storage period, a heat transfer fluid (HTF) flows inside the two tubes, transmitting the heat to the PCM through two heat exchange surfaces instead of one heat exchange surface as it is the case for double tube heat storage systems. A CFD model is developed and validated against experimental data available in the literature. The mesh independency study is carried out to select the appropriate mesh. In addition, different time steps are examined to determine a time step ensuring accuracy of the numerical results and reduction in the computational time. The numerical model is then used to conduct numerical investigations of the thermal behavior and thermal performance of the storage unit. The effects of eccentricity of the central tube and HTF mass flow rate on thermal characteristics and performance indicators are examined for two flow arrangements: co-current and counter current flows. The results are given in terms of isotherm plots, streamlines, melting time and thermal energy storage efficiency.

Keywords: energy storage, heat transfer, melting, solidification

Procedia PDF Downloads 56