Search results for: dairy industries inventory optimization

Authors: Mohammadreza Heydariazad

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Productivity growth of wind energy as a clean source needed to achieve improved strategy in production and transmission and management of wind resources in order to increase quality of power and reduce costs. New technologies based on power converters that cause changing turbine speed to suit the wind speed blowing turbine improve extraction efficiency power from wind. This article introduces variable speed wind turbines and optimization of power, and presented methods to use superconducting inductor in the composition of power converter and is proposed the dc measurement for the wind farm and especially is considered techniques available to them. In fact, this article reviews mechanisms and function, changes of wind speed turbine according to speed control strategies of various types of wind turbines and examines power possible transmission and ac from producing location to suitable location for a strong connection integrating wind farm generators, without additional cost or equipment. It also covers main objectives of the dynamic control of wind turbines, and the methods of exploitation and the ways of using it that includes the unique process of these components. Effective algorithm is presented for power control in order to extract maximum active power and maintains power factor at the desired value.

Keywords: wind energy, generator, superconducting inductor, wind turbine power

Procedia PDF Downloads 327

Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

Procedia PDF Downloads 126

Authors: Laxmi R. Kasaraneni

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The Internet connects all the networks, including the nation’s critical infrastructure that are used extensively by not only a nation’s government and military to protect sensitive information and execute missions, but also the primary infrastructure that provides services that enable modern conveniences such as education, potable water, electricity, natural gas, and financial transactions. It has become the central nervous system for the government, the citizens, and the industries. When it is attacked, the effects can ripple far and wide impacts not only to citizens’ well-being but nation’s economy, civil infrastructure, and national security. As such, these critical services may be targeted by malicious hackers during cyber warfare, it is imperative to not only protect them and mitigate any immediate or potential threats, but to also understand the current or potential impacts beyond the IT networks or the organization. The Nation’s IT infrastructure which is now vital for communication, commerce, and control of our physical infrastructure, is highly vulnerable to attack. While existing technologies can address some vulnerabilities, fundamentally new architectures and technologies are needed to address the larger structural insecurities of an infrastructure developed in a more trusting time when mass cyber attacks were not foreseen. This research is intended to improve the core functions of the Internet and critical-sector information systems by providing a clear path to create a safe, secure, and resilient cyber environment that help stakeholders at all levels of government, and the private sector work together to develop the cybersecurity capabilities that are key to our economy, national security, and public health and safety. This research paper also emphasizes the present and future cyber security threats, the capabilities and goals of cyber attackers, a strategic concept and steps to implement cybersecurity for maximum effectiveness, enabling technologies, some strategic assumptions and critical challenges, and the future of cyberspace.

Keywords: critical challenges, critical infrastructure, cyber security, enabling technologies, national security

Procedia PDF Downloads 294

Authors: Ajay Kumar Choubey, Geeta Agnihotri, C. Sasikumar, Rashmi Dwivedi

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Deep-drawing operations are performed widely in industrial applications. It is very important for efficiency to achieve parts with no or minimum defects. Deep drawn parts are used in high performance, high strength and high reliability applications where tension, stress, load and human safety are critical considerations. Wrinkling is a kind of defect caused by stresses in the flange part of the blank during metal forming operations. To avoid wrinkling appropriate blank-holder pressure/force or drawbead can be applied. Now-a-day computer simulation plays a vital role in the field of manufacturing process. So computer simulation of manufacturing has much advantage over previous conventional process i.e. mass production, good quality of product, fast working etc. In this study, a two dimensional elasto-plastic Finite Element (F.E.) model for Mild Steel material blank has been developed to study the behavior of the flange wrinkling and deep drawing parameters under different Blank-Holder Pressure (B.H.P.). For this, commercially available Finite Element software ANSYS 14 has been used in this study. Simulation results are critically studied and salient conclusions have been drawn.

Keywords: ANSYS, deep drawing, BHP, finite element simulation, wrinkling

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Authors: Halison da Silva Pereira, Ciro Sobrinho Campolina Martins, Vitor Mainenti Leal Lopes

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Long range performance is a goal for aircraft configuration optimization. Blended Wing Body (BWB) is presented in many works of literature as the most aerodynamically efficient design for a fixed-wing aircraft. Because of its high weight to thrust ratio, BWB is the ideal configuration for many Unmanned Aerial Vehicle (UAV) missions on geomatics applications. In this work, a BWB aerodynamic design for typical light geomatics payload is presented. Aerodynamic non-dimensional coefficients are predicted using low Reynolds number computational techniques (3D Panel Method) and wing parameters like aspect ratio, taper ratio, wing twist and sweep are optimized for high cruise performance and flight quality. The methodology of this work is a summary of tailless aircraft wing design and its application, with appropriate computational schemes, to light UAV subjected to low Reynolds number flows leads to conclusions like the higher performance and flight quality of thicker airfoils in the airframe body and the benefits of using aerodynamic twist rather than just geometric.

Keywords: blended wing body, low Reynolds number, panel method, UAV

Procedia PDF Downloads 586

Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

Procedia PDF Downloads 441

Authors: Adnan I. O. Zaid

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Zinc aluminum alloys are versatile materials which are widely used in manufacturing several parts in the automobile and aircraft industries. The effect of grain refinement of these alloys by rare earth elements on their mechanical characteristics is scarce. The equal channel angular pressing is relatively recent method for producing severe plastic deformation in materials subjected to it resulting in refinement of their structure and enhancement of their mechanical characteristics. The phase diagram of these alloys indicates that large dendrites of large grain size can be formed during their solidification of the cast which tends to deteriorate their mechanical strength and surface quality. To overcome this problem they are normally grain refined by either titanium or titanium + boron to their melt prior to solidification. In this paper, comparison between the effect of adding either titanium, (Ti), titanium+boron, (Ti+B), or Molybdenum, Mo, to zinc-aluminum22, alloy, (ZA22) on its metallurgical and mechanical characteristics in the cast condition and after pressing by the ECAP process is investigated. It was found that addition of either Ti, Ti+B, or Mo to the ZA22 alloy in the cast condition resulted in refining of their structure being more refined by the addition of Mo, then .Ti+B and less refining by Ti addition. Furthermore, the ECAP process resulted in further refinement of the alloy micro structure except in case of Ti+B addition where poisoning i.e. coarsening of the grains has occurred. Regarding the addition of these element on the mechanical behavior; it was found that addition of Ti Or Ti+B resulted in little enhancement of the alloy strength factor and its flow stress at 20% true strain; whereas, the addition of resulted in deteriorating of its mechanical behavior as % decrease in the strength factor and % in its flow stress of 20%. As for the strain hardening index; addition of any of these elements resulted in decreasing the strain hardening index.

Keywords: addition, grain refinement, mechanical characteristics, microstructure, rare earth elements, ZA-22, Zinc- aluminum alloy

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Authors: D. S. Naumann, B. J. Evans, O. Hassan

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This paper outlines the development of an automated aerodynamic optimisation algorithm using a novel method of parameterising a computational mesh by employing user–defined control nodes. The shape boundary movement is coupled to the movement of the novel concept of the control nodes via a quasi-1D-linear deformation. Additionally, a second order smoothing step has been integrated to act on the boundary during the mesh movement based on the change in its second derivative. This allows for both linear and non-linear shape transformations dependent on the preference of the user. The domain mesh movement is then coupled to the shape boundary movement via a Delaunay graph mapping. A Modified Cuckoo Search (MCS) algorithm is used for optimisation within the prescribed design space defined by the allowed range of control node displacement. A finite volume compressible NavierStokes solver is used for aerodynamic modelling to predict aerodynamic design fitness. The resulting coupled algorithm is applied to a range of test cases in two dimensions including the design of a subsonic, transonic and supersonic intake and the optimisation approach is compared with more conventional optimisation strategies. Ultimately, the algorithm is tested on a three dimensional wing optimisation case.

Keywords: mesh movement, aerodynamic shape optimization, cuckoo search, shape parameterisation

Procedia PDF Downloads 337

Authors: M. Sazali Said, Rahim Jamian, Shahrizan Yusoff, Shahruzaman Sulaiman, Jum'Azulhisham Abdul Shukor

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This case study focuses on the role of Universiti Kuala Lumpur Malaysian Spanish Institute (UniKL MSI) to produce technologist in order to reduce the shortage of skilled workers especially in the automotive industry. The purpose of the study therefore seeks to examine the effectiveness of Technical Education and Vocational Training (TEVT) curriculum of UniKL MSI to produce graduates that could immediately be productively employed by the automotive industry. The approach used in this study is through performance evaluation of students attending the Industrial Training Attachment (INTRA). The sample of study comprises of 37 students, 16 university supervisors and 26 industrial supervisors. The research methodology involves the use of quantitative and qualitative methods of data collections through the triangulation approach. The quantitative data was gathered from the students, university supervisors and industrial supervisors through the use of questionnaire. Meanwhile, the qualitative data was obtained from the students and university supervisors through the use of interview and observation. Both types of data have been processed and analyzed in order to summarize the results in terms of frequency and percentage by using a computerized spread sheet. The result shows that industrial supervisors were satisfied with the students’ performance. Meanwhile, university supervisors rated moderate effectiveness of the UniKL MSI curriculum in producing graduates with appropriate skills and in meeting the industrial needs. During the period of study, several weaknesses in the curriculum have been identified for further continuous improvements. Recommendations and suggestions for curriculum improvement also include the enhancement of technical skills and competences of students towards fulfilling the needs and demand of the automotive industries.

Keywords: technical education and vocational training (TEVT), industrial training attachment (INTRA), curriculum improvement, automotive industry

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view football datasets. Our HMR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH multi-view football datasets, respectively.

Keywords: computer vision, human motion analysis, random forest, machine learning

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Authors: Wen-Chyan Tsai, Syed S. H. Rizvi

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Organic solvent residues are always associated with liposomes produced by the traditional techniques like the thin film hydration and reverse phase evaporation methods, which limit the applications of these vesicles in the pharmaceutical, food and cosmetic industries. Our objective was to develop a novel and benign process of liposomal microencapsulation by using supercritical carbon dioxide (SC-CO2) as the sole phospholipid-dissolving medium and a green substitute for organic solvents. This process consists of supercritical fluid extraction followed by rapid expansion via a nozzle and automatic cargo suction. Lecithin and cholesterol mixed in 10:1 mass ratio were dissolved in SC-CO2 at 20 ± 0.5 MPa and 60 oC. After at least two hours of equilibrium, the lecithin/cholesterol-laden SC-CO2 was passed through a 1000-micron nozzle and immediately mixed with the cargo solution to form liposomes. Liposomal micro-encapsulation was conducted at three pressures (8.27, 12.41, 16.55 MPa), three temperatures (75, 83 and 90 oC) and two flow rates (0.25 ml/sec and 0.5 ml/sec). Liposome size, zeta potential and encapsulation efficiency were characterized as functions of the operating parameters. The average liposomal size varied from 400-500 nm to 1000-1200 nm when the pressure was increased from 8.27 to 16.55 MPa. At 12.41 MPa, 90 oC and 0.25 ml per second of 0.2 M glucose cargo loading rate, the highest encapsulation efficiency of 31.65 % was achieved. Under a confocal laser scanning microscope, large unilamellar vesicles and multivesicular vesicles were observed to make up a majority of the liposomal emulsion. This new approach is a rapid and continuous process for bulk production of liposomes using a green solvent. Based on the results to date, it is feasible to apply this technique to encapsulate hydrophilic compounds inside the aqueous core as well as lipophilic compounds in the phospholipid bilayers of the liposomes for controlled release, solubility improvement and targeted therapy of bioactive compounds.

Keywords: liposome, micro encapsulation, supercritical carbon dioxide, non-toxic process

Procedia PDF Downloads 431

Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

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Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

Procedia PDF Downloads 280

Authors: G. H. B. Dilhari, A. A. D. T. Saparamadu

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Sri Lanka is one of the prominent countries for the coir production. The coir is one of the by-products of the coconut and the coir industry is considered to be one of the traditional industries in Sri Lanka. Because of the inherent nature of the coir industry, labourers play a significant role in the coir production process. The study has analyzed the determinants of the income of the household level coir yarn labourers. The study was conducted in the Kumarakanda Grama Niladhari division. Simple random sampling was used to generate a sample of 100 household level coir yarn labourers and structured questionnaire, personal interviews, and discussion were performed to gather the required data. The obtained data were statistically analyzed by using Statistical Package for Social Science (SPSS) software. Mann-Whitney U and Kruskal-Wallis test were performed for mean comparison. The findings revealed that the household level coir yarn industry is dominated by the female workers and it was identified that fewer numbers of workers have engaged in this industry as the main occupation. In addition to that, elderly participation in the industry is higher than the younger participation and most of them have engaged in the industry as a source of extra income. Level of education, the methods of engagement, satisfaction, engagement in the industry by the next generation, support from the government, method of government support, working hours per day, employed as a main job, number of completed units per day, suffering from job related diseases and type of the diseases were related with income level of household level coir yarn laboures. The recommendations as to flourish in future includes, technological transformation for coir yarn production, strengthening the raw material base and regulating the raw material supply, introduction of new technologies, markets and training programmes, the establishment of the labourers’ association, the initiation of micro credit schemes and better consideration about the job oriented diseases.

Keywords: coir yarn, determinants, income, Sri Lanka

Procedia PDF Downloads 312

Authors: N. Piwpuan, J. Tosalee, N. Phonkerd

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Malachite green (MG), a synthetic dye, is used in industries and aquaculture and also disposed in the effluent. Use of wastewater in irrigation increases due to water shortage. However, wastewater containing dyes, MG, are toxic to biological systems. Therefore, effects of MG on growth of vegetables were evaluated in order to utilize dye-contaminated wastewater for irrigation. In this study, Pak choy (Brassica chinensis) and Chinese convolvulus (Ipomoea aquatica) were grown in growing material (mixture of soil, coconut fiber, and compost) for four weeks and afterward kept watering with 200 ml of tap water containing MG at the concentrations of 0 (control), 1, 2, 10, and 20 mg/L. At harvest, number of leaf and shoot and root dry weight of the treated plants were measured and compared with control. For both species, their biomass values were similar among treatments and did not differ from the control plants (dry weight were 0.6-1.0 and 1.1-1.7 g/plant for B. chinensis and I. aquatica, respectively). B. chinensis treated with 2, 10, and 20 mg/L of MG produced lower number of new leaf and had smaller and shorter leaf compared to control and treatment of 1 mg/L. These results indicate the different responses between plant species, which B. chinensis is more sensitive to contaminant compared to I. aquatica. There was no sign of MG and leucomalachite green (LMG) detected in root and shoot tissues of plants treated with MG at 20 mg/L, tested by thin layer chromatography. After plant harvest, toxicity of the growing material from all treatments was tested on mung beans. Percent germination (83-97%), seedling fresh weight (0.3-0.5 g/plant), and shoot length (11-12.5 cm) were similar to the control. These indicated that contaminant in growing material did not pose detrimental effect on mung beans. Based on these results, the water contaminated with low concentration of MG, such as discharge from aquaculture, may serve as ferti-irrigation water to compensate water shortage.

Keywords: ferti-irrigation, soil toxicity, triphenylmethane dye, wastewater reuse

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

Procedia PDF Downloads 182

Authors: Sena Su, Burak Ozbek, Yesim M. Sahin, Sevil Yucel, Dilek Kazan, Faik N. Oktar, Nazmi Ekren, Oguzhan Gunduz

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In recent years, protein, lipid or polysaccharide-based polymers have been used in order to develop biodegradable materials and their chemical nature determines the physical properties of the resulting films. Among these polymers, proteins from different sources have been extensively employed because of their relative abundance, film forming ability, and nutritional qualities. In this study, the biodegradable composite nanofiber films based on fish sarcoplasmic protein (FSP) were prepared via electrospinning technique. Biodegradable polycaprolactone (PCL) was blended with the FSP to obtain hybrid FSP/PCL nanofiber mats with desirable physical properties. Mixture solutions of FSP and PCL were produced at different concentrations and their density, viscosity, electrical conductivity and surface tension were measured. Mechanical properties of electrospun nanofibers were evaluated. Morphology of composite nanofibers was observed using scanning electron microscopy (SEM). Moreover, Fourier transform infrared spectrometer (FTIR) studies were used for analysis chemical composition of composite nanofibers. This study revealed that the FSP based nanofibers have the potential to be used for different applications such as biodegradable packaging, drug delivery, and wound dressing, etc.

Keywords: edible film, electrospinning, fish sarcoplasmic protein, nanofiber

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Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

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This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

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Authors: Hassan Beigi Rizi, Harold Auradou, Lamine Hattali

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Various industries, including civil engineering, automotive, aerospace, and biomedical fields, are currently seeking novel and innovative high-performance lightweight materials to reduce energy consumption. Inspired by the structure of Euplectella Aspergillum Glass Sponges (EA-sponge), 2D unit cells were created and fabricated using a Fused Filament Fabrication (FFF) process with Polylactic acid (PLA) filaments. The stiffness and strength of bio-inspired EA-sponge lattices were investigated both experimentally and numerically under uniaxial tensile loading and are compared to three standard square lattices with diagonal struts (Designs B and C) and non-diagonal struts (Design D) reinforcements. The aim is to establish predictive scaling laws models and examine the deformation mechanisms involved. The results indicated that for the EA-sponge structure, the relative moduli and yield strength scaled linearly with relative density, suggesting that the deformation mechanism is stretching-dominated. The Finite element analysis (FEA), with periodic boundary conditions for volumetric homogenization, confirms these trends and goes beyond the experimental limits imposed by the FFF printing process. Therefore, the stretching-dominated behavior, investigated from 0.1 to 0.5 relative density, demonstrate that the study of EA-sponge structure can be exploited for the realization of square lattice topologies that are stiff and strong and have attractive potential for lightweight structural applications. However, the FFF process introduces an accuracy limitation, with approximately 10% error, making it challenging to print structures with a relative density below 0.2. Future work could focus on exploring the impact of different printing materials on the performance of EA-sponge structures.

Keywords: bio-inspiration, lattice structures, fused filament fabrication, scaling laws

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Authors: Linhang Zhu, Hongyu Zhu, Jiahe Liu

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This paper investigated a method of indoor real-time positioning and mapping based on the Manhattan world assumption. In indoor environments, relying solely on feature matching techniques or other geometric algorithms for sensor pose estimation inevitably resulted in cumulative errors, posing a significant challenge to indoor positioning. To address this issue, we adopt the Manhattan world hypothesis to optimize the camera pose algorithm based on feature matching, which improves the accuracy of camera pose estimation. A special processing method was applied to image data frames that conformed to the Manhattan world assumption. When similar data frames appeared subsequently, this could be used to eliminate drift in sensor pose estimation, thereby reducing cumulative errors in estimation and optimizing mapping and positioning. Through experimental verification, it is found that our method achieves high-precision real-time positioning in indoor environments and successfully generates maps of indoor environments. This provides effective technical support for applications such as indoor navigation and robot control.

Keywords: Manhattan world hypothesis, real-time positioning and mapping, feature matching, loopback detection

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Authors: Risdiana, D. Suhendar, S. Pratiwi, W. A. Somantri, T. Saragi

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Superconductor is a promising material for future applications especially for energy saving because of their advantages properties such as zero electrical resistivity when they are cooled down to sufficiently low temperatures. However, the mechanism describing the role of physical properties in superconductor is far from being understood clearly, so that the application of this material for wider benefit in various industries is very limited. Most of superconductors are cuprate compounds, which has CuO2 as a conducting plane in their crystal structures. The study of physical properties through the partially substitution of impurity for Cu in superconducting cuprates has been one of great interests in relation to the mechanism of superconductivity. Different behaviors between the substitution of nonmagnetic impurity and magnetic impurity for Cu are observed. For examples, the superconductivity and Cu-spin fluctuations in the electron-doped system are suppressed through the substitution of magnetic Ni for Cu more markedly than through the substitution of nonmagnetic Zn for Cu, which is contrary to the result in the hole-doped system. Here, we reported the effect of partially substitution of magnetic impurity Fe for Cu to the magnetic and transport properties in electron-doped superconducting cuprates of Eu1.85+yCe0.15-yCu1-yFeyO4+α-δ (ECCFO) with y = 0.01, 0.02, and 0.05, in order to investigate the mechanism of magnetic and transport properties of ECCFO in normal-state. Magnetic properties are investigated by DC magnetic-susceptibility measurements that carried out at low temperatures down to 2 K using a standard SQUID magnetometer in a magnetic field of 5 Oe on field cooling. Transport properties addressed to electron mobility, are extracted from radius of electron localization calculated from temperature dependence of resistivity. For y = 0, temperature dependence of dc magnetic-susceptibility indicated the change of magnetic behavior from paramagnetic to diamagnetic below 15 K. Above 15 K, all samples show paramagnetic behavior with the values of magnetic moment in every volume unit increased with increasing y. Electron mobility decreased with increasing y. Some reasons for these results will be discussed.

Keywords: DC magnetic-susceptibility, electron mobility, Eu1.85+yCe0.15-yCu1-yFeyO4+α-δ, normal state

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Authors: Haritha Saranga

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Service quality has become an important driver of competition in manufacturing industries of late, as many products are being sold in conjunction with service offerings. With increase in computational power and data capture capabilities, it has become possible to analyze and estimate various aspects of service quality at the granular level and determine their impact on business performance. In the current study context, dealer level, model-wise warranty data from one of the top two-wheeler manufacturers in India is used to estimate service quality of individual dealers and its impact on warranty related costs and sales performance. We collected primary data on warranty costs, number of complaints, monthly sales, type of quality upgrades, etc. from the two-wheeler automaker. In addition, we gathered secondary data on various regions in India, such as petrol and diesel prices, geographic and climatic conditions of various regions where the dealers are located, to control for customer usage patterns. We analyze this primary and secondary data with the help of a variety of analytics tools such as Auto-Regressive Integrated Moving Average (ARIMA), Seasonal ARIMA and ARIMAX. Study results, after controlling for a variety of factors, such as size, age, region of the dealership, and customer usage pattern, show that service quality does influence sales of the products in a significant manner. A more nuanced analysis reveals the dynamics between product quality and service quality, and how their interaction affects sales performance in the Indian two-wheeler industry context. We also provide various managerial insights using descriptive analytics and build a model that can provide sales projections using a variety of forecasting techniques.

Keywords: service quality, product quality, automobile industry, business analytics, auto-regressive integrated moving average

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Authors: Mojtaba Esmaeilzad Limoudehi, Ebrahim Amiri

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Water scarcity is now one of the leading challenges for human societies. In this regard, recognizing the relationship between soil, water, plant growth, and plant response to stress is very significant. In this paper, considering the importance of drought stress and the role of choosing suitable cultivars in resistance against drought, a split-plot experiment using early, intermediate, and late-maturing cultivars was carried out in Katul filed, Golestan province during two cultivation years of 2015 and 2016. The main factor was irrigation intervals at four levels, including 7 days, 14 days, 21 days, and 28 days. The subfactor was the subplot of six maize cultivars (two early maturing cultivars, two medium maturing cultivars, and two late-maturing cultivars). The results of variance analysis have revealed that irrigation interval and cultivars treatment have significant effects on the number of grain in each corn, number of rows in each corn, number of grain per row, the weight of 1000 grains, grain yield, and biomass yield. Although, the interaction of these two factors on the mentioned attributes was meaningful. The best grain yield was achieved at 7 days irrigation interval and late maturing maize cultivars treatment, which was equal to 12301 kg/ha.

Keywords: corn, growth period, optimization, stress

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Authors: Carlos Cuenca, Diego Sarzosa

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Ductile fracture occurs by the mechanism of void nucleation, void growth and coalescence. Potential sites for initiation are second phase particles or non-metallic inclusions. Modelling of ductile damage at the microscopic level is very difficult and complex task for engineers. Therefore, conservative predictions of ductile failure using simple models are necessary during the design and optimization of critical structures like pressure vessels and pipelines. Nowadays, it is well known that the initiation phase is strongly influenced by the stress triaxiality and plastic deformation at the microscopic level. Thus, a simple model used to study the ductile failure under multiaxial stress condition is the Stress Modified Critical Strain (SMCS) approach. Ductile rupture has been study for a structural steel under different stress triaxiality conditions using the SMCS method. Experimental tests are carried out to characterize the relation between stress triaxiality and equivalent plastic strain by notched round bars. After calibration of the plasticity and damage properties, predictions are made for low constraint bending specimens with and without side grooves. Stress/strain fields evolution are compared between the different geometries. Advantages and disadvantages of the SMCS methodology are discussed.

Keywords: damage, SMSC, SEB, steel, failure

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Authors: Olusegun Ayodeji Olagunju, Christine Tyreesa Pillay

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Biodiesel from waste sources is regarded as an economical and most viable fuel alternative to depleting fossil fuels. In this work, biodiesel was produced from three different sources of waste cooking oil; from cafeterias, which is vegetable-based using the transesterification method. The free fatty acids (% FFA) of the feedstocks were conducted successfully through the titration method. The results for sources 1, 2, and 3 were 0.86 %, 0.54 % and 0.20 %, respectively. The three variables considered in this process were temperature, reaction time, and catalyst concentration within the following range: 50 oC – 70 oC, 30 min – 90 min, and 0.5 % – 1.5 % catalyst. Produced biodiesel was characterized using ASTM standard methods for biodiesel property testing to determine the fuel properties, including kinematic viscosity, specific gravity, flash point, pour point, cloud point, and acid number. The results obtained indicate that the biodiesel yield from source 3 was greater than the other sources. All produced biodiesel fuel properties are within the standard biodiesel fuel specifications ASTM D6751. The optimum yield of biodiesel was obtained at 98.76%, 96.4%, and 94.53% from source 3, source 2, and source 1, respectively at optimum operating variables of 65 oC temperature, 90 minutes reaction time, and 0.5 wt% potassium hydroxide.

Keywords: waste cooking oil, biodiesel, free fatty acid content, potassium hydroxide catalyst, optimization analysis

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Authors: Tae Hyun Ahn, Gyo Woo Lee, Man Young Kim

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Because of high thermal efficiency and low CO2 emission, diesel engines are being used widely in many industrial fields although it makes many PM and NOx which give both human health and environment a negative effect. NOx regulations for diesel engines, however, are being strengthened and it is impossible to meet the emission standard without NOx reduction devices such as SCR (Selective Catalytic Reduction), LNC (Lean NOx Catalyst), and LNT (Lean NOx Trap). Among the NOx reduction devices, urea-SCR system is known as the most stable and efficient method to solve the problem of NOx emission. But this device has some issues associated with the ammonia slip phenomenon which is occurred by shortage of evaporation and thermolysis time, and that makes it difficult to achieve uniform distribution of the injected urea in front of monolith. Therefore, this study has focused on the mixing enhancement between urea and exhaust gases to enhance the efficiency of the SCR catalyst equipped in catalytic muffler by changing inlet gas temperature and spray conditions to improve the spray uniformity of the urea water solution. Finally, it can be found that various parameters such as inlet gas temperature and injector and injection angles significantly affect the evaporation and mixing of the urea water solution with exhaust gases, and therefore, optimization of these parameters are required.

Keywords: UWS (Urea-Water-Solution), selective catalytic reduction (SCR), evaporation, thermolysis, injection

Procedia PDF Downloads 395

Authors: Mohammad Tofayel Ahmed, Seung Kook An

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In contemporary research world, focus is more set on sustainable products and innovative processes. The global textile industries are putting tremendous effort to achieve a balance between economic development and ecological protection concurrently. The conservation of water sources and environment have become immensely significant issue in textile dyeing production. Accordingly, an attempt has been taken in this study to develop a process to dye polyester blend cotton without reduction clearing process and any extra wash off chemical by simple modification aiming at cost reduction and sustainability. A widely used combination of 60/40 cotton/polyester (c/p) single jersey knitted fabric of 30’s, 180 g/m² was considered for study. Traditionally, pretreatment is done followed by polyester part dyeing, reduction clearing and cotton part dyeing for c/p blend dyeing. But in this study, polyester part is dyed right away followed by pretreatment process and cotton part dyeing by skipping the reduction clearing process diametrically. The dyed samples of both traditional and modified samples were scrutinized by various color fastness tests, dyeing parameters and by consumption of water, steam, power, process time and total batch cost. The modified process in this study showed no necessity of reduction clearing process for polyester blend cotton dyeing. The key issue contributing to avoid the reduction clearing after polyester part dyeing has been the multifunctional effect of NaOH and H₂O₂ while pretreatment of cotton after polyester part dyeing. The results also revealed that the modified process could reduce the consumption of water, steam, power, time and cost remarkably. The bulk trial of modified process demonstrated the well exploitability to dye polyester blend cotton substrate ensuring all fastness and dyeing properties regardless of dyes category, blend ratio, color, and shade percentage thus making the process sustainable, eco-friendly and economical. Furthermore, the proposed method could be applicable to any cellulosic blend with polyester.

Keywords: cotton, dyeing, economical, polyester

Procedia PDF Downloads 189

Authors: Sarekha Woranuch, Rangrong Yoksan

Abstract:

Chitosan is a derivative of chitin, which is a second most naturally abundant polysaccharide found in crab shells, shrimp shells, and squid pens. The applications of chitosan in pharmaceutical, cosmetics, food and packaging industries have been reported owing to its general recognition as safe, excellent biodegradability and biocompatibility, as well as ability to form films, membranes, gels, beads, fibers and particles. Nevertheless, chitosan is an amino polysaccharide consisting of strong inter- and intramolecular hydrogen bonds which limit its solubility in neutral pH water resulting in restricted utilization. Chemical modification is an alternative way to impede hydrogen bond formation. The objective of the present research is to improve water solubility and antioxidant activity of chitosan by grafting with ferulic acid. Ferulic acid was grafted onto chitosan at the C-2 position via a carbodiimide-mediated coupling reaction. Different mole ratios of chitosan to ferulic acid (i.e. 1.0:0.0, 1.0:0.5, 1.0:1.0, 1.0:1.5, 1.0:2.0, and 1.0:2.5) and various reaction temperatures (i.e. 40, 60, and 80 °C) were used. The reaction was performed at different times (i.e. 1.5, 3.0, 4.5, and 6.0 h). The obtained ferulic acid-grafted chitosan was characterized by FTIR and 1H NMR technique. The influences of ferulic acid on crystallinity, solubility and radical scavenging activity of chitosan were also investigated. Ferulic acid grafted chitosan was successfully synthesized as confirmed from (i) the appearance of FTIR absorption band at 1517 cm-1 belonging to C=C aromatic ring of ferulic acid and the increased C–H stretching band intensity and (ii) the appearance of proton signals at δ = 6.31-7.67 ppm ascribing to methine protons of ferulic acid. The condition in which the reaction temperature of 60°C, reaction time of 3 h and the mole ratio of chitosan to ferulic acid of 1:1 gave the highest ferulic acid substitution degree, i.e. 0.37. The resulting ferulic acid grafted chitosan was soluble in water (1.3 mg/mL) due to its reduced crystallinity as compared with chitosan and also exhibited 90% greater radical scavenging activity than chitosan. The result suggested the utilization of ferulic acid grafted chitosan as an antioxidant material.

Keywords: antioxidant property, chitosan, ferulic acid, grafting

Procedia PDF Downloads 459

Authors: Vivek B. Ravindran, Aravind Surapaneni, Rebecca Traub, Sarvesh K. Soni, Andrew S. Ball

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Parasitic diseases have a devastating, long-term impact on human health and welfare. More than two billion people are infected with soil-transmitted helminths (STHs), including the roundworms (Ascaris), hookworms (Necator and Ancylostoma) and whipworm (Trichuris) with majority occurring in the tropical and subtropical regions of the world. Despite its low prevalence in developed countries, the removal of STHs from wastewater remains crucial to allow the safe use of sludge or recycled water in agriculture. Conventional methods such as incubation and optical microscopy are cumbersome; consequently, the results drastically vary from person-to-person observing the ova (eggs) under microscope. Although PCR-based methods are an alternative to conventional techniques, it lacks the ability to distinguish between viable and non-viable helminth ova. As a result, wastewater treatment industries are in major need for radically new and innovative tools to detect and quantify STHs eggs with precision, accuracy and being cost-effective. In our study, we focus on the following novel and innovative techniques: -Recombinase polymerase amplification and Surface enhanced Raman spectroscopy (RPA-SERS) based detection of helminth ova. -Use of metal nanoparticles and their relative nanozyme activity. -Colorimetric detection, differentiation and enumeration of genera of helminth ova using hydrolytic enzymes (chitinase and lipase). -Propidium monoazide (PMA)-qPCR to detect viable helminth ova. -Modified assay to recover and enumerate helminth eggs from fresh raw sewage. -Transcriptome analysis of ascaris ova in fresh raw sewage. The aforementioned techniques have the potential to replace current conventional and molecular methods thereby producing a standard protocol for the determination and enumeration of helminth ova in sewage sludge.

Keywords: colorimetry, helminth, PMA-QPCR, nanoparticles, RPA, viable

Procedia PDF Downloads 299

Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

Abstract:

The U.S. Federal Emergency Management Agency (FEMA) developed flood maps based on experts’ experience and estimates of the probability of flooding. Current flood-risk models evaluate flood risk with regional and subjective measures without impact from torrential rain and nuisance flooding at the neighborhood level. Nuisance flooding occurs in small areas in the community, where a few streets or blocks are routinely impacted. This type of flooding event occurs when torrential rainstorm combined with high tide and sea level rise temporarily exceeds a given threshold. In South Florida, this threshold is 1.7 ft above Mean Higher High Water (MHHW). The National Weather Service defines torrential rain as rain deposition at a rate greater than 0.3-inches per hour or three inches in a single day. Data from the Florida Climate Center, 1970 to 2020, shows 371 events with more than 3-inches of rain in a day in 612 months. The purpose of this research is to develop a data-driven method to determine comprehensive analytical damage-avoidance criteria that account for nuisance flood events at the single-family home level. The method developed uses the Failure Mode and Effect Analysis (FMEA) method from the American Society of Quality (ASQ) to estimate the Damage Avoidance (DA) preparation for a 1-day 100-year storm. The Consequence of Nuisance Flooding (CoNF) is estimated from community mitigation efforts to prevent nuisance flooding damage. The Probability of Nuisance Flooding (PoNF) is derived from the frequency and duration of torrential rainfall causing delays and community disruptions to daily transportation, human illnesses, and property damage. Urbanization and population changes are related to the U.S. Census Bureau's annual population estimates. Data collected by the United States Department of Agriculture (USDA) Natural Resources Conservation Service’s National Resources Inventory (NRI) and locally by the South Florida Water Management District (SFWMD) track the development and land use/land cover changes with time. The intent is to include temporal trends in population density growth and the impact on land development. Results from this investigation provide the risk of nuisance flooding as a function of CoNF and PoNF for coastal areas of South Florida. The data-based criterion provides awareness to local municipalities on their flood-risk assessment and gives insight into flood management actions and watershed development.

Keywords: flood risk, nuisance flooding, urban flooding, FMEA

Procedia PDF Downloads 100

Authors: Ahmed Hamzi, Bryan Norman

Abstract:

Having scribes help document patient records in electronic health record systems can improve hospitalists’ productivity. But hospitals need to determine the optimum number of scribes to hire to maximize scribe cost effectiveness. Scribe attendance uncertainty due to planned and unplanned absences is a primary challenge. This paper presents simulation and analytical models to determine the optimum number of scribes for a hospital to hire. Scribe staffing practices vary from one context to another; different staffing scenarios are considered where having extra attending scribes provides or does not provide additional value and utilizing on-call scribes to fill in for potentially absent scribes. These staffing scenarios are assessed for different scribe revenue ratios (ratio of the value of the scribe relative to scribe costs) ranging from 100% to 300%. The optimum solution depends on the absenteeism rate, revenue ratio, and desired service level. The analytical model obtains solutions easier and faster than the simulation model, but the simulation model is more accurate. Therefore, the analytical model’s solutions are compared with the simulation model’s solutions regarding both the number of scribes hired and cost-effectiveness. Additionally, an Excel tool has been developed to facilitate decision-makers in easily obtaining solutions using the analytical model.

Keywords: hospitalists, workload, optimization cost, economic analysis

Procedia PDF Downloads 45