Search results for: uniform error

Authors: Emine Ebru Demirci, Remzi Şahin

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The purpose of this study is to compare Self Compacting Concrete (SCC) and Conventional Concrete (CC), which are used in beams with dense reinforcement, in terms of their capillary absorption. During the comparison of SCC and CC, the effects of two different factors were also investigated: concrete strength class and curing condition. In the study, both SCC and CC were produced in three different concrete classes (C25, C50 and C70) and the other parameter (i.e curing condition) was determined as two levels: moisture and air curing. Beam dimensions were determined to be 200 x 250 x 3000 mm. Reinforcements of the beams were calculated and placed as 2ø12 for the top and 3ø12 for the bottom. Stirrups with dimension 8 mm were used as lateral rebar and stirrup distances were chosen as 10 cm in the confinement zone and 15 cm at the central zone. In this manner, densification of rebars in lateral cross-sections of beams and handling of SCC in real conditions were aimed. Concrete covers of the rebars were chosen to be equal in all directions as 25 mm. The capillary absorption measurements were performed on core samples taken from the beams. Core samples of ø8x16 cm were taken from the beginning (0-100 cm), middle (100-200 cm) and end (200-300 cm) region of the beams according to the casting direction of SCC. However core samples were taken from lateral surface of the beams. In the study, capillary absorption experiments were performed according to Turkish Standard TS EN 13057. It was observed that, for both curing environments and all strength classes of concrete, SCC’s had lower capillary absorption values than that of CC’s. The capillary absorption values of C25 class of SCC are 11% and 16% lower than that of C25 class of CC for air and moisture conditions, respectively. For C50 class, these decreases were 6% and 18%, while for C70 class, they were 16% and 9%, respectively. It was also detected that, for both SCC and CC, capillary absorption values of samples kept in moisture curing are significantly lower than that of samples stored in air curing. For CC’s; C25, C50 and C70 class moisture-cured samples were found to have 26%, 12% and 31% lower capillary absorption values, respectively, when compared to the air-cured ones. For SCC’s; these values were 30%, 23% and 24%, respectively. Apart from that, it was determined that capillary absorption values for both SCC and CC decrease with increasing strength class of concrete for both curing environments. It was found that, for air cured CC, C50 and C70 class of concretes had 39% and 63% lower capillary absorption values compared to the C25 class of concrete. For the same type of concrete samples cured in the moisture environment, these values were found to be 27% and 66%. It was found that for SCC samples, capillary absorption value of C50 and C70 concretes, which were kept in air curing, were 35% and 65% lower than that of C25, while for moisture-cured samples these values were 29% and 63%, respectively. When standard deviations of the capillary absorption values are compared for core samples obtained from the beginning, middle and end of the CC and SCC beams, it was found that, in all three strength classes of concrete, the variation is much smaller for SCC than CC. This demonstrated that SCC’s had more uniform character than CC’s.

Keywords: self compacting concrete, reinforced concrete beam, capillary absorption, strength class, curing condition

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Authors: Nishal Parbhoo, John B. Dewar, Samantha Gildenhuys

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Rotavirus is the major cause of severe gastroenteritis worldwide in children aged 5 and younger. Death rates are high particularly in developing countries. The mature rotavirus is a non-enveloped triple-layered nucleocapsid containing 11 double-stranded RNA segments. Here a global view on the sequence and structure of the three main capsid proteins, VP7, VP6, and VP2 is taken by generating a consensus sequence for each of these rotavirus proteins, for each species obtained from published data of representative rotavirus genotypes from across the world and across species. The degree of conservation between species was represented on homology models for each of the proteins. VP7 shows the highest level of variation with 14 - 45 amino acids showing conservation of less than 60%. These changes are localized to the outer surface which is exposed to antibodies alluding to a possible mechanism in evading the immune system. The middle layer, VP6 shows lower variability with only 14-32 sites having lower than 70% conservation. The inner structural layer made up of VP2 showed the lowest variability with only 1-16 sites having less than 70% conservation across species. The results correlate with proteins’ multiple structural roles. Although the nucleotide sequences vary due to an error-prone replication and lack of proofreading, the corresponding amino acid sequence of VP2, 6 and 7 remains conserved. Sequence conservation maintained for the virus results in stable protein structures, fit for function. This can be exploited in drug design, molecular studies and biotechnological applications.

Keywords: amino acid sequence conservation, capsid protein, protein structure, vaccine candidate

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Authors: Siphat Lim

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This study used Autoregressive Distributed Lag (ARDL) approach to cointegration. In the long-run the general price level and exchange rate have a positively significant effect on domestic output. The estimated result further revealed that fiscal stimulus help stimulate domestic output in the long-run, but not in the short-run, while monetary expansion help to stimulate output in both short-run and long-run. The result is complied with the theory which is the macroeconomic policies, fiscal and monetary policy; help to stimulate domestic output in the long-run. The estimated result of the Vector Error Correction Model (VECM) has indicated more clearly that the consumer price index has a positive effect on output with highly statistically significant. Increasing in the general price level would increase the competitiveness among producers than increase in the output. However, the exchange rate also has a positive effect and highly significant on the gross domestic product. The exchange rate depreciation might increase export since the purchasing power of foreigners has increased. More importantly, fiscal stimulus would help stimulate the domestic output in the long-run since the coefficient of government expenditure is positive. In addition, monetary expansion would also help stimulate the output and the result is highly significant. Thus, fiscal stimulus and monetary expansionary would help stimulate the domestic output in the long-run in Cambodia.

Keywords: fiscal policy, monetary policy, ARDL, VECM

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Authors: Amin Asgarian, Ghyslaine McClure

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Experiences in the past earthquakes have clearly demonstrated the necessity of seismic design and assessment of Non-Structural Components (NSCs) particularly in post-disaster structures such as hospitals, power plants, etc. as they have to be permanently functional and operational. Meeting this objective is contingent upon having proper seismic performance of both structural and non-structural components. Proper seismic design, analysis, and assessment of NSCs can be attained through generation of Floor Design Spectrum (FDS) in a similar fashion as target spectrum for structural components. This paper presents the developed methodology to generate FDS directly from corresponding Uniform Hazard Spectrum (UHS) (i.e. design spectra for structural components). The methodology is based on the experimental and numerical analysis of a database of 27 real Reinforced Concrete (RC) buildings which are located in Montreal, Canada. The buildings were tested by Ambient Vibration Measurements (AVM) and their dynamic properties have been extracted and used as part of the approach. Database comprises 12 low-rises, 10 medium-rises, and 5 high-rises and they are mostly designated as post-disaster\emergency shelters by the city of Montreal. The buildings are subjected to 20 compatible seismic records to UHS of Montreal and Floor Response Spectra (FRS) are developed for every floors in two horizontal direction considering four different damping ratios of NSCs (i.e. 2, 5, 10, and 20 % viscous damping). Generated FRS (approximately 132’000 curves) are statistically studied and the methodology is proposed to generate the FDS directly from corresponding UHS. The approach is capable of generating the FDS for any selection of floor level and damping ratio of NSCs. It captures the effect of: dynamic interaction between primary (structural) and secondary (NSCs) systems, higher and torsional modes of primary structure. These are important improvements of this approach compared to conventional methods and code recommendations. Application of the proposed approach are represented here through two real case-study buildings: one low-rise building and one medium-rise. The proposed approach can be used as practical and robust tool for seismic assessment and design of NSCs especially in existing post-disaster structures.

Keywords: earthquake engineering, operational and functional components, operational modal analysis, seismic assessment and design

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Authors: Mogale Sabone, Thabiso Ntlole

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The pressure from globalization has made manufacturing organizations to move towards three major competitive arenas: quality, cost, and responsiveness. Quality is a universal value and has become a global issue. In order to survive and be able to provide customers with good products, manufacturing organizations’ supporting systems, tools, and structures it uses must grow or evolve. The majority of quality management concepts and strategies that are practiced recently are aimed at detecting and correcting problems which already exist and serve to limit losses. In agile manufacturing environment there is no room for defect and error so it needs a quality management which is proactively directed at problem prevention. This proactive quality management avoids losses by focusing on failure prevention, virtual elimination of the possibility of premature failure, mistake-proofing, and assuring consistently high quality in the definition and design of creation processes. To achieve this, a decision support tool for quality control and management is suggested. Current decision support tools/methods used by most manufacturing companies in Botswana for quality management and control are not integrated, for example they are not consistent since some tests results data is recorded manually only whilst others are recorded electronically. It is only a set of procedures not a tool. These procedures cannot offer interactive decision support. This point brings to light the aim of this research which is to develop a framework which will help manufacturing companies in Botswana build a decision support tool for quality control and management.

Keywords: decision support tool, manufacturing, quality control, quality management

Procedia PDF Downloads 566

Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany

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In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.

Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities

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Authors: Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka

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This study employs a method based on image analyses and structure information to detect accumulated ice on known structures. The icing of marine vessels and offshore structures causes significant reductions in their efficiency and creates unsafe working conditions. Image processing methods are used to measure ice loads automatically. Most image processing methods are developed based on captured image analyses. In this method, ice loads on structures are calculated by defining structure coordinates and processing captured images. A pyramidal structure is designed with nine cylindrical bars as the known structure of experimental setup. Unsymmetrical ice accumulated on the structure in a cold room represents the actual case of experiments. Camera intrinsic and extrinsic parameters are used to define structure coordinates in the image coordinate system according to the camera location and angle. The thresholding method is applied to capture images and detect iced structures in a binary image. The ice thickness of each element is calculated by combining the information from the binary image and the structure coordinate. Averaging ice diameters from different camera views obtains ice thicknesses of structure elements. Comparison between ice load measurements using this method and the actual ice loads shows positive correlations with an acceptable range of error. The method can be applied to complex structures defining structure and camera coordinates.

Keywords: camera calibration, ice detection, ice load measurements, image processing

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Authors: Abhay Asthana, Shally Toshkhani, Gyati Shilakari

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The objective of the present research work is to develop a topical biodegradable dermal patch based formulation to aid accelerated wound healing. It is always better for patient compliance to be able to reduce the frequency of dressings with improved drug delivery and overall therapeutic efficacy. In present study optimized formulation using biodegradable components was obtained evaluating polymers and excipients (HPMC K4M, Ethylcellulose, Povidone, Polyethylene glycol and Gelatin) to impart significant folding endurance, elasticity, and strength. Molten gelatin was used to get a mixture using ethylene glycol. Chitosan dissolved in acidic medium was mixed with stirring to Gelatin mixture. With continued stirring to the mixture Curcumin was added with the aid of DCM and Methanol in an optimized ratio of 60:40 to get homogenous dispersion. Polymers were dispersed with stirring in the final formulation. The mixture was sonicated casted to get the film form. All steps were carried out under strict aseptic conditions. The final formulation was a thin uniformly smooth textured film with dark brown-yellow color. The film was found to have folding endurance was around 20 to 21 times without a crack in an optimized formulation at RT (23°C). The drug content was in range 96 to 102% and it passed the content uniform test. The final moisture content of the optimized formulation film was NMT 9.0%. The films passed stability study conducted at refrigerated conditions (4±0.2°C) and at room temperature (23 ± 2°C) for 30 days. Further, the drug content and texture remained undisturbed with stability study conducted at RT 23±2°C for 45 and 90 days. Percentage cumulative drug release was found to be 80% in 12h and matched the biodegradation rate as tested in vivo with correlation factor R2>0.9. In in vivo study administration of one dose in equivalent quantity per 2 days was applied topically. The data demonstrated a significant improvement with percentage wound contraction in contrast to control and plain drug respectively in given period. The film based formulation developed shows promising results in terms of stability and in vivo performance.

Keywords: wound healing, biodegradable, polymers, patch

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Authors: M. Ananthakrishnan, Sunil K Patil, Koti Naveen, Inuganti Hemanth Kumar

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State estimation output of EMS forms the base case for all other advanced applications used in real time by a power system operator. Ensuring tuning of state estimator is a repeated process and cannot be left once a good solution is obtained. This paper attempts to demonstrate methods to improve state estimator solution by identifying incorrect modelling and telemetry inputs to the application. In this work, identification of database topology modelling error by plotting static network using node-to-node connection details is demonstrated with examples. Analytical methods to identify wrong transmission parameters, incorrect limits and mistakes in pseudo load and generator modelling are explained with various cases observed. Further, methods used for active and reactive power tuning using bus summation display, reactive power absorption summary, and transformer tap correction are also described. In a large power system, verifying all network static data and modelling parameter on regular basis is difficult .The proposed tuning methods can be easily used by operators to quickly identify errors to obtain the best possible state estimation performance. This, in turn, can lead to improved decision-support capabilities, ultimately enhancing the safety and reliability of the power grid.

Keywords: active power tuning, database modelling, reactive power, state estimator

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Authors: Davit Shahnazaryan, Diogo Gomes, Mher Safaryan

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Many symbolic computations and manipulations required in the analysis of partial differential equations (PDE) or systems of PDEs are tedious and error-prone. These computations arise when determining conservation laws, entropies or integral identities, which are essential tools for the study of PDEs. Here, we discuss a new Mathematica package for the symbolic analysis of PDEs that automate multiple tasks, saving time and effort. Methodologies: During the research, we have used concepts of linear algebra and partial differential equations. We have been working on creating algorithms based on theoretical mathematics to find results mentioned below. Major Findings: Our package provides the following functionalities; finding symmetry group of different PDE systems, generation of polynomials invariant with respect to different symmetry groups; simplification of integral quantities by integration by parts and null Lagrangian cleaning, computing general forms of expressions by integration by parts; finding equivalent forms of an integral expression that are simpler or more symmetric form; determining necessary and sufficient conditions on the coefficients for the positivity of a given symbolic expression. Conclusion: Using this package, we can simplify integral identities, find conserved and dissipated quantities of time-dependent PDE or system of PDEs. Some examples in the theory of mean-field games and semiconductor equations are discussed.

Keywords: partial differential equations, symbolic computation, conserved and dissipated quantities, mathematica

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Authors: Haggay Etkes

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This study provides evidence for the impact of monthly interviews conducted for the Israeli Labor Force Surveys (LFSs) on estimated flows between labor force (LF) statuses and on coefficients in fixed-effects estimations. The study uses the natural experiment of parallel interviews for the quarterly and the monthly LFSs in Israel in 2011 for demonstrating that the Labor Force Participation (LFP) rate of Jewish persons who participated in the monthly LFS increased between interviews, while in the quarterly LFS it decreased. Interestingly, the estimated impact on the LFP rate of self-reporting individuals is 2.6–3.5 percentage points while the impact on the LFP rate of individuals whose data was reported by another member of their household (a proxy), is lower and statistically insignificant. The relative increase of the LFP rate in the monthly survey is a result of a lower rate of exit from the LF and a somewhat higher rate of entry into the LF relative to these flows in the quarterly survey. These differing flows have a bearing on labor search models as the monthly survey portrays a labor market with less friction and a “steady state” LFP rate that is 5.9 percentage points higher than the quarterly survey. The study also demonstrates that monthly interviews affect a specific group (45–64 year-olds); thus the sign of coefficient of age as an explanatory variable in fixed-effects regressions on LFP is negative in the monthly survey and positive in the quarterly survey.

Keywords: measurement error, surveys, search, LFSs

Procedia PDF Downloads 270

Authors: Feng Yang

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Machine learning (ML), especially deep learning (DL), has been extensively applied to many applications in recently years and gained great success in solving different problems, including scientific problems. However, conventional ML/DL methodologies are purely data-driven which have the limitations, such as need of ample amount of labelled training data, lack of consistency to physical principles, and lack of generalizability to new problems/domains. Recently, there is a growing consensus that ML models need to further take advantage of prior knowledge to deal with these limitations. Physics-informed machine learning, aiming at integration of physics/domain knowledge into ML, has been recognized as an emerging area of research, especially in the recent 2 to 3 years. In this work, physics-informed ML, specifically physics-informed neural network (NN), is employed and implemented to estimate the displacements at x, y, z directions in a solid mechanics problem that is controlled by equilibrium equations with boundary conditions. By incorporating the physics (i.e. the equilibrium equations) into the learning process of NN, it is showed that the NN can be trained very efficiently with a small set of labelled training data. Experiments with different settings of the NN model and the amount of labelled training data were conducted, and the results show that very high accuracy can be achieved in fulfilling the equilibrium equations as well as in predicting the displacements, e.g. in setting the overall displacement of 0.1, a root mean square error (RMSE) of 2.09 × 10−4 was achieved.

Keywords: deep learning, neural network, physics-informed machine learning, solid mechanics

Procedia PDF Downloads 150

Authors: Nalini C. Iyer, Shraddha H., Anagha B. Varahamurthy, Dikshith C. S., Ishwar G. Kubasad, Vinayak I. Karalatti, Pavan B. Mulimani

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The current scenario of the pandemic due to COVID-19 has led to the awareness among the people to avoid unneces-sary contact in public places. There is a need to avoid contact with physical objects to stop the spreading of infection. The contactless feature has to be included in the systems in public places wherever possible. For example, attendance monitoring systems with fingerprint biometric can be replaced with a contactless feature. One more important protocol followed in the current situation is temperature monitoring and screening. The paper describes an attendance system with a contactless feature and temperature screening for the university. The system displays a QR code to scan, which redirects to the student login web page only if the location is valid (the location where the student scans the QR code should be the location of the display of the QR code). Once the student logs in, the temperature of the student is scanned by the contactless temperature sensor (mlx90614) with an error of 0.5°C. If the temperature falls in the range of the desired value (range of normal body temperature), then the attendance of the student is marked as present, stored in the database, and the door opens automatically. The attendance is marked as absent in the other case, alerted with the display of temperature, and the door remains closed. The door is automated with the help of a servomotor. To avoid the proxy, IR sensors are used to count the number of students in the classroom. The hardware system consisting of a contactless temperature sensor and IR sensor is implemented on the microcontroller, NodeMCU.

Keywords: NodeMCU, IR sensor, attendance monitoring, contactless, temperature

Procedia PDF Downloads 185

Authors: Ki-Yeo Kim

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Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined genomic expression achieved better performance in the discrimination of different conditions than in a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.

Keywords: oral squamous cell carcinoma, combined biomarker, microarray dataset, correlated genes

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Authors: Anupam Sibal

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Apollo Quality Program(AQP) was launched across the Apollo Group of Hospitals to address the four patient safety areas; Safety during Clinical Handovers, Medication Safety, Surgical Safety and the six International Patient Safety Goals(IPSGs) of JCI. A measurable, online, quality dashboard covering 20 process and outcome parameters was devised for monthly monitoring. The expected outcomes were also defined and categorized into green, yellow and red ranges. An audit methodology was also devised to check the processes for the measurable dashboard. Documented clinical handovers were introduced for the first time at many locations for in-house patient transfer, nursing-handover, and physician-handover. Prototype forms using the SBAR format were made. Patient-identifiers, read-back for verbal orders, safety of high-alert medications, site marking and time-outs and falls risk-assessment were introduced for all hospitals irrespective of accreditation status. Measurement of Surgical-Site-Infection (SSI) for 30 days postoperatively, was done. All hospitals now tracked the time of administration of antimicrobial prophylaxis before surgery. Situations with high risk of retention of foreign body were delineated and precautionary measures instituted. Audit of medications prescribed in the discharge summaries was made uniform. Formularies, prescription-audits and other means for reduction of medication errors were implemented. There is a marked increase in the compliance to processes and patient safety outcomes. Compliance to read-back for verbal orders rose from 86.83% in April’11 to 96.95% in June’15, to policy for high alert medications from 87.83% to 98.82%, to use of measures to prevent wrong-site, wrong-patient, wrong procedure surgery from 85.75% to 97.66%, to hand-washing from 69.18% to 92.54%, to antimicrobial prophylaxis within one hour before incision from 79.43% to 93.46%. Percentage of patients excluded from SSI calculation due to lack of follow-up for the requisite time frame decreased from 21.25% to 10.25%. The average AQP scores for all Apollo Hospitals improved from 62 in April’11 to 87.7 in Jun’15.

Keywords: clinical handovers, international patient safety goals, medication safety, surgical safety

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Authors: Shubham Jaiswal

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During modelling of many physical problems and engineering processes, fractional calculus plays an important role. Those are greatly described by fractional differential equations (FDEs). So a reliable and efficient technique to solve such types of FDEs is needed. In this article, a numerical solution of a class of fractional differential equations namely space fractional order reaction-advection dispersion equations subject to initial and boundary conditions is derived. In the proposed approach shifted Jacobi polynomials are used to approximate the solutions together with shifted Jacobi operational matrix of fractional order and spectral collocation method. The main advantage of this approach is that it converts such problems in the systems of algebraic equations which are easier to be solved. The proposed approach is effective to solve the linear as well as non-linear FDEs. To show the reliability, validity and high accuracy of proposed approach, the numerical results of some illustrative examples are reported, which are compared with the existing analytical results already reported in the literature. The error analysis for each case exhibited through graphs and tables confirms the exponential convergence rate of the proposed method.

Keywords: space fractional order linear/nonlinear reaction-advection diffusion equation, shifted Jacobi polynomials, operational matrix, collocation method, Caputo derivative

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Authors: Ahmed Mahmoud Ahmed Abouelmagd

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The diversity is the usual remedy of the transmitted signal level variations (Fading phenomena) in radio frequency channels. Diversity techniques utilize two or more copies of a signal and combine those signals to combat fading. The basic concept of diversity is to transmit the signal via several independent diversity branches to get independent signal replicas via time – frequency - space - and polarization diversity domains. Coding and decoding processes can be an alternative remedy for fading phenomena, it cannot increase the channel capacity, but it can improve the error performance. In this paper we propose the use of replication decoding with BCH code class, and Viterbi decoding algorithm with convolution coding; as examples of coding and decoding processes. The results are compared to those obtained from two optimized selection space diversity techniques. The performance of Rayleigh fading channel, as the model considered for radio frequency channels, is evaluated for each case. The evaluation results show that the coding and decoding approaches, especially the BCH coding approach with replication decoding scheme, give better performance compared to that of selection space diversity optimization approaches. Also, an approach for combining the coding and decoding diversity as well as the space diversity is considered, the main disadvantage of this approach is its complexity but it yields good performance results.

Keywords: Rayleigh fading, diversity, BCH codes, Replication decoding, ‎convolution coding, viterbi decoding, space diversity

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Authors: Abdullahi Jibrin, Aishetu Abdulkadir

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The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

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Authors: Olawale S. Fatoba, Stephen A. Akinlabi, Esther T. Akinlabi, Rezvan Gharehbaghi

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The performance of material surface under wear and corrosion environments cannot be fulfilled by the conventional surface modifications and coatings. Therefore, different industrial sectors need an alternative technique for enhanced surface properties. Titanium and its alloys possess poor tribological properties which limit their use in certain industries. This paper focuses on the effect of hybrid coatings Al-Cu-Fe on a grade five titanium alloy using laser metal deposition (LMD) process. Icosahedral Al-Cu-Fe as quasicrystals is a relatively new class of materials which exhibit unusual atomic structure and useful physical and chemical properties. A 3kW continuous wave ytterbium laser system (YLS) attached to a KUKA robot which controls the movement of the cladding process was utilized for the fabrication of the coatings. The titanium cladded surfaces were investigated for its hardness, corrosion and tribological behaviour at different laser processing conditions. The samples were cut to corrosion coupons, and immersed into 3.65% NaCl solution at 28oC using Electrochemical Impedance Spectroscopy (EIS) and Linear Polarization (LP) techniques. The cross-sectional view of the samples was analysed. It was found that the geometrical properties of the deposits such as width, height and the Heat Affected Zone (HAZ) of each sample remarkably increased with increasing laser power due to the laser-material interaction. It was observed that there are higher number of aluminum and titanium presented in the formation of the composite. The indentation testing reveals that for both scanning speed of 0.8 m/min and 1m/min, the mean hardness value decreases with increasing laser power. The low coefficient of friction, excellent wear resistance and high microhardness were attributed to the formation of hard intermetallic compounds (TiCu, Ti2Cu, Ti3Al, Al3Ti) produced through the in situ metallurgical reactions during the LMD process. The load-bearing capability of the substrate was improved due to the excellent wear resistance of the coatings. The cladded layer showed a uniform crack free surface due to optimized laser process parameters which led to the refinement of the coatings.

Keywords: Al-Cu-Fe coating, corrosion, intermetallics, laser metal deposition, Ti-6Al-4V alloy, wear resistance

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Authors: Soyoon Bak, Sunyoung Bu, Philsu Kim

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In this paper, a backward semi-Lagrangian scheme combined with the second-order backward difference formula is designed to calculate the numerical solutions of nonlinear advection-diffusion equations. The primary aims of this paper are to remove any iteration process and to get an efficient algorithm with the convergence order of accuracy 2 in time. In order to achieve these objects, we use the second-order central finite difference and the B-spline approximations of degree 2 and 3 in order to approximate the diffusion term and the spatial discretization, respectively. For the temporal discretization, the second order backward difference formula is applied. To calculate the numerical solution of the starting point of the characteristic curves, we use the error correction methodology developed by the authors recently. The proposed algorithm turns out to be completely iteration-free, which resolves the main weakness of the conventional backward semi-Lagrangian method. Also, the adaptability of the proposed method is indicated by numerical simulations for Burgers’ equations. Throughout these numerical simulations, it is shown that the numerical results are in good agreement with the analytic solution and the present scheme offer better accuracy in comparison with other existing numerical schemes. Semi-Lagrangian method, iteration-free method, nonlinear advection-diffusion equation, second-order backward difference formula

Keywords: Semi-Lagrangian method, iteration free method, nonlinear advection-diffusion equation, second-order backward difference formula

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

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

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

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Authors: A. Dashti, M. Eskandari, L. Farahmand, P. Parvin, A. Jafargholi

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Breast Cancer is one of the most considerable diseases in the United States and other countries and is the second leading cause of death in women. Common breast cancer treatments would lead to adverse side effects such as loss of hair, nausea, and weakness. These complications arise because these cancer treatments damage some healthy cells while eliminating the cancer cells. In an effort to address these complications, laser radiation was utilized and tested as a targeted cancer treatment for breast cancer. In this regard, tissue engineering approaches are being employed by using an electrospun scaffold in order to facilitate the growth of breast cancer cells. Polycaprolacton (PCL) was used as a material for scaffold fabricating because of its biocompatibility, biodegradability, and supporting cell growth. The specific breast cancer cells have the ability to create a three-dimensional cell cluster due to the spontaneous accumulation of cells in the porosity of the scaffold under some specific conditions. Therefore, we are looking for a higher density of porosity and larger pore size. Fibers showed uniform diameter distribution and final scaffold had optimum characteristics with approximately 40% porosity. The images were taken by SEM and the density and the size of the porosity were determined with the Image. After scaffold preparation, it has cross-linked by glutaraldehyde. Then, it has been washed with glycine and phosphate buffer saline (PBS), in order to neutralize the residual glutaraldehyde. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromidefor (MTT) results have represented approximately 91.13% viability of the scaffolds for cancer cells. In order to create a cluster, Michigan Cancer Foundation-7 (MCF-7, breast cancer cell line) and Michigan Cancer Foundation-10A (MCF-10A, human mammary epithelial cell line) cells were cultured on the scaffold in 24 well plate for five days. Then, we have exposed the cluster to the laser diode 808 nm radiation to investigate the effect of laser on the tumor with different power and time. Under the same conditions, cancer cells lost their viability more than the healthy ones. In conclusion, laser therapy is a viable method to destroy the target cells and has a minimum effect on the healthy tissues and cells and it can improve the other method of cancer treatments limitations.

Keywords: breast cancer, electrospun scaffold, polycaprolacton, laser diode, cancer treatment

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Authors: Manveen Singh

Abstract:

Since the very advent of law enforcement, eyewitness testimony has played a pivotal role in identifying, arresting and convicting suspects. Reliant heavily on the accuracy of human memory, nothing seems to carry more weight with the judiciary than the testimony of an actual witness. The acceptance of eyewitness testimony as a substantive piece of evidence lies embedded in the assumption that the human mind is adept at recording and storing events. Research though, has proven otherwise. Having carried out extensive study in the field of eyewitness testimony for the past 40 years, psychologists have concluded that human memory is fragile and needs to be treated carefully. The question that arises then, is how reliable is eyewitness testimony? The credibility of eyewitness testimony, simply put, depends on several factors leaving it reliable at times while not so much at others. This is further substantiated by the fact that as per scientific research, over 75 percent of all eyewitness testimonies may stand in error; quite a few of these cases resulting in life sentences. Although the advancement of scientific techniques, especially DNA testing, helped overturn many of these eyewitness testimony-based convictions, yet eyewitness identifications continue to form the backbone of most police investigations and courtroom decisions till date. What then is the solution to this long standing concern regarding the accuracy of eyewitness accounts? The present paper shall analyze the linkage between human memory and eyewitness identification as well as look at the various factors governing the credibility of eyewitness testimonies. Furthermore, it shall elaborate upon some best practices developed over the years to help reduce mistaken identifications. Thus, in the process, trace out the changing landscape of eyewitness testimony amidst the evolution of DNA and trace evidence.

Keywords: DNA, eyewitness, identification, testimony, evidence

Procedia PDF Downloads 328

Authors: A. M. Tiara, Sudipto Chakraborty, S. K. Pal

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Impinging jets and their different configurations are important from the viewpoint of the fluid flow characteristics and their influence on heat transfer from metal surfaces due to their complex flow characteristics. Such flow characteristics results in highly variable heat transfer from the surface, resulting in varying cooling rates which affects the mechanical properties including hardness and strength. The overall objective of the current research is to conduct a fundamental investigation of the heat transfer mechanisms for an impinging coolant jet. Numerical simulation of the cooling process gives a detailed analysis of the different parameters involved even though employing Computational Fluid Dynamics (CFD) to simulate the real time process, being a relatively new research area, poses many challenges. The heat transfer mechanism in the current research is actuated by jet cooling. The computational tool used in the ongoing research for simulation of the cooling process is ANSYS Workbench software. The temperature and heat flux distribution along the steel strip with the effect of various flow parameters on the heat transfer rate can be observed in addition to determination of the jet impingement patterns, which is the major aim of the present analysis. Modelling both jet and air atomized cooling techniques using CFD methodology and validating with those obtained experimentally- including trial and error with different models and comparison of cooling rates from both the techniques have been included in this work. Finally some concluding remarks are made that identify some gaps in the available literature that have influenced the path of the current investigation.

Keywords: CFD, heat transfer, impinging jets, numerical simulation

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Authors: Asif Arshid, Ying Huang, Denver Tolliver

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Finite Element (FE) method coupled with ever-increasing computational powers has substantially advanced the reliability of deterministic three dimensional structural analyses of a structure with uniform material properties. However, railways trackbed is made up of diverse group of materials including steel, wood, rock and soil, while each material has its own varying levels of heterogeneity and imperfections. It is observed that the application of probabilistic methods for trackbed structural analysis while incorporating the material and geometric variabilities is deeply underworked. The authors developed and validated a 3-dimensional FE based numerical trackbed model and in this study, they investigated the influence of variability in Young modulus and thicknesses of granular layers (Ballast and Subgrade) on the reliability index (-index) of the subgrade layer. The influence of these factors is accounted for by changing their Coefficients of Variance (COV) while keeping their means constant. These variations are formulated using Gaussian Normal distribution. Two failure mechanisms in subgrade namely Progressive Shear Failure and Excessive Plastic Deformation are examined. Preliminary results of risk-based probabilistic analysis for Progressive Shear Failure revealed that the variations in Ballast depth are the most influential factor for vertical stress at the top of subgrade surface. Whereas, in case of Excessive Plastic Deformations in subgrade layer, the variations in its own depth and Young modulus proved to be most important while ballast properties remained almost indifferent. For both these failure moods, it is also observed that the reliability index for subgrade failure increases with the increase in COV of ballast depth and subgrade Young modulus. The findings of this work is of particular significance in studying the combined effect of construction imperfections and variations in ground conditions on the structural performance of railroad trackbed and evaluating the associated risk involved. In addition, it also provides an additional tool to supplement the deterministic analysis procedures and decision making for railroad maintenance.

Keywords: finite element analysis, numerical modeling, probabilistic methods, risk and reliability analysis, subgrade

Procedia PDF Downloads 139

Authors: Emmanuel Okechukwu Nwafor, Folake Olubunmi Akintayo, Denis Alcides Rezende

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Decision tree models are versatile and interpretable machine learning algorithms widely used for both classification and regression tasks, which can be related to cities, whether physical or digital. The aim of this research is to assess how well decision tree algorithms can predict trip purposes in Makurdi, Nigeria, while also exploring their connection to the strategic digital city initiative. The research methodology involves formalizing household demographic and trips information datasets obtained from extensive survey process. Modelling and Prediction were achieved using Python Programming Language and the evaluation metrics like R-squared and mean absolute error were used to assess the decision tree algorithm's performance. The results indicate that the model performed well, with accuracies of 84% and 68%, and low MAE values of 0.188 and 0.314, on training and validation data, respectively. This suggests the model can be relied upon for future prediction. The conclusion reiterates that This model will assist decision-makers, including urban planners, transportation engineers, government officials, and commuters, in making informed decisions on transportation planning and management within the framework of a strategic digital city. Its application will enhance the efficiency, sustainability, and overall quality of transportation services in Makurdi, Nigeria.

Keywords: decision tree algorithm, trip purpose, intelligent transport, strategic digital city, travel pattern, sustainable transport

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Authors: Hilal Uslu, Salih Eroglu, Betul Ozkan, Ozcan Bulantekin, Alper Kuscu

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In this study, the strawberry (Fragaria L.) fruits, which were pretreated with ultrasound (US), were worked on in the microwave by using 90W power. Then mathematical modelling was applied to dried fruits by using different experimental thin layer models. The sliced fruits were subjected to ultrasound treatment at a frequency of 40 kHz for 10, 20, and 30 minutes, in an ultrasonic water bath, with a ratio of 1:4 to fruit/water. They are then dried in the microwave (90W). The drying process continued until the product moisture was below 10%. By analyzing the moisture change of the products at a certain time, eight different thin-layer drying models, (Newton, page, modified page, Midilli, Henderson and Pabis, logarithmic, two-term, Wang and Singh) were tested for verification of experimental data. MATLAB R2015a statistical program was used for the modelling, and the best suitable model was determined with R²adj (coefficient of determination of compatibility), and root mean square error (RMSE) values. According to analysis, the drying model that best describes the drying behavior for both drying conditions was determined as the Midilli model by high R²adj and low RMSE values. Control, 10, 20, and 30 min US for groups R²adj and RMSE values was established as respectively; 0,9997- 0,005298; 0,9998- 0,004735; 0,9995- 0,007031; 0,9917-0,02773. In addition, effective diffusion coefficients were calculated for each group and were determined as 3,80x 10⁻⁸, 3,71 x 10⁻⁸, 3,26 x10⁻⁸ ve 3,5 x 10⁻⁸ m/s, respectively.

Keywords: mathematical modelling, microwave drying, strawberry, ultrasound

Procedia PDF Downloads 153

Authors: K. K. Lee, H. W. Han, H. L. Kang, T. A. Kim, S. H. Han

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For the robust optimization of the manufacturing product design, there are design objectives that must be achieved, such as a minimization of the mean and standard deviation in objective functions within the required sensitivity constraints. The authors utilized the sensitivity of objective functions and constraints with respect to the effective design variables to reduce the computational burden associated with the evaluation of the probabilities. The individual mean and sensitivity values could be estimated easily by using the 9 level orthogonal array based response surface models optimized by the stepwise regression. The present study evaluates a proposed procedure from the robust optimization of rubber domes that are commonly used for keyboard switching, by using the 9 level orthogonal array and stepwise regression along with a desirability function. In addition, a new robust optimization process, i.e., the I2GEO (Identify, Integrate, Generate, Explore and Optimize), was proposed on the basis of the robust optimization in rubber domes. The optimized results from the response surface models and the estimated results by using the finite element analysis were consistent within a small margin of error. The standard deviation of objective function is decreasing 54.17% with suggested sensitivity based robust optimization. (Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2017, S2455569)

Keywords: objective function, orthogonal array, response surface model, robust optimization, stepwise regression

Procedia PDF Downloads 288

Authors: Soumia Merat, Lynda Djerbal, Ramdane Bahar, Mohammed Amin Benbouras

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Along with shear wave, many soil parameters are associated with the standard penetration test (SPT) as a dynamic in situ experiment. Both SPT-N data and geophysical data do not often exist in the same area. Statistical analysis of correlation between these parameters is an alternate method to estimate Vₛ conveniently and without additional investigations or data acquisition. Shear wave velocity is a basic engineering tool required to define dynamic properties of soils. In many instances, engineers opt for empirical correlations between shear wave velocity (Vₛ) and reliable static field test data like standard penetration test (SPT) N value, CPT (Cone Penetration Test) values, etc., to estimate shear wave velocity or dynamic soil parameters. The relation between Vs and SPT- N values of Algiers area is predicted using the collected data, and it is also compared with the previously suggested formulas of Vₛ determination by measuring Root Mean Square Error (RMSE) of each model. Algiers area is situated in high seismic zone (Zone III [RPA 2003: réglement parasismique algerien]), therefore the study is important for this region. The principal aim of this paper is to compare the field measurements of Down-hole test and the empirical models to show which one of these proposed formulas are applicable to predict and deduce shear wave velocity values.

Keywords: empirical models, RMSE, shear wave velocity, standard penetration test

Procedia PDF Downloads 338

Authors: Rutuja Upadhyay, Anurag Mehra

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Solid food foams/cellular foods are colloidal systems which impart structure, texture and mouthfeel to many food products such as bread, cakes, ice-cream, meringues, etc. Their heterogeneous morphology makes the quantification of structure/mechanical relationships complex. The porous structure of solid food foams is highly influenced by the processing conditions, ingredient composition, and their interactions. Sensory perceptions of food foams are dependent on bubble size, shape, orientation, quantity and distribution and determines the texture of foamed foods. The state and structure of the solid matrix control the deformation behavior of the food, such as elasticity/plasticity or fracture, which in turn has an effect on the force-deformation curves. The obvious step in obtaining the relationship between the mechanical properties and the porous structure is to quantify them simultaneously. Here, we attempt to research food foams such as bread dough, baked bread and steamed rice cakes to determine the link between ingredients and the corresponding effect of each of them on the rheology, microstructure, bubble size and texture of the final product. Dynamic rheometry (SAOS), confocal laser scanning microscopy, flatbed scanning, image analysis and texture profile analysis (TPA) has been used to characterize the foods studied. In all the above systems, there was a common observation that when the mean bubble diameter is smaller, the product becomes harder as evidenced by the increase in storage and loss modulus (G′, G″), whereas when the mean bubble diameter is large the product is softer with decrease in moduli values (G′, G″). Also, the bubble size distribution affects texture of foods. It was found that bread doughs with hydrocolloids (xanthan gum, alginate) aid a more uniform bubble size distribution. Bread baking experiments were done to study the rheological changes and mechanisms involved in the structural transition of dough to crumb. Steamed rice cakes with xanthan gum (XG) addition at 0.1% concentration resulted in lower hardness with a narrower pore size distribution and larger mean pore diameter. Thus, control of bubble size could be an important parameter defining final food texture.

Keywords: food foams, rheology, microstructure, texture

Procedia PDF Downloads 334