Search results for: dimensionality reduction

Authors: Mounira Laabidi, Rafik Zayani, Ridha Bouallegue, Daniel Roviras

Abstract:

The Filter Bank multicarrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM) has been introduced to overcome the poor spectral characteristics and the waste in both bandwidth and energy caused by the use of the cyclic prefix. However, the FBMC-OQAM signals suffer from the high Peak to Average Power Ratio (PAPR) problem. Due to the overlapping structure of the FBMC-OQAM signals, directly applying the PAPR reduction schemes conceived for the OFDM one turns out to be ineffective. In this paper, we address the problem of PAPR reduction for FBMC-OQAM systems by suggesting a new scheme based on an improved version of Active Constellation Extension scheme (ACE) of OFDM. The proposed scheme, named Rolling Window ACE, takes into consideration the overlapping naturally emanating from the FBMC-OQAM signals.

Keywords: ACE, FBMC, OQAM, OFDM, PAPR, rolling-window

Procedia PDF Downloads 537

Authors: Suvidha Gupta, R. A. Pandey, Sanjay Pawar

Abstract:

The effluents from various food processing industries are found with high BOD, COD, suspended solids, nitrate, and phosphate. Mixotrophic growth of microalgae using food processing industrial wastewater as an organic carbon source has emerged as more effective and energy intensive means for the nutrient removal and COD reduction. The present study details the treatment of non-sterilized unfiltered food processing industrial wastewater by microalgae for nutrient removal as well as to determine the tolerance to COD by taking different dilutions of wastewater. In addition, the effect of different inoculum percentages of microalgae on removal efficiency of the nutrients for given dilution has been studied. To see the effect of dilution and COD tolerance, the wastewater having initial COD 5000 mg/L (±5), nitrate 28 mg/L (±10), and phosphate 24 mg/L (±10) was diluted to get COD of 3000 mg/L and 1000 mg/L. The experiments were carried out in 1L conical flask by intermittent aeration with different inoculum percentage i.e. 10%, 20%, and 30% of Chlorella sp. isolated from nearby area of NEERI, Nagpur. The experiments were conducted for 6 days by providing 12:12 light- dark period and determined various parameters such as COD, TOC, NO3-- N, PO4-- P, and total solids on daily basis. Results revealed that, for 10% and 20% inoculum, over 90% COD and TOC reduction was obtained with wastewater containing COD of 3000 mg/L whereas over 80% COD and TOC reduction was obtained with wastewater containing COD of 1000 mg/L. Moreover, microalgae was found to tolerate wastewater containing COD 5000 mg/L and obtained over 60% and 80% reduction in COD and TOC respectively. The obtained results were found similar with 10% and 20% inoculum in all COD dilutions whereas for 30% inoculum over 60% COD and 70% TOC reduction was obtained. In case of nutrient removal, over 70% nitrate removal and 45% phosphate removal was obtained with 20% inoculum in all dilutions. The obtained results indicated that Microalgae assisted nutrient removal gives maximum COD and TOC reduction with 3000 mg/L COD and 20% inoculum. Hence, microalgae assisted wastewater treatment is not only effective for removal of nutrients but also can tolerate high COD up to 5000 mg/L and solid content.

Keywords: Chlorella sp., chemical oxygen demand, food processing industrial wastewater, mixotrophic growth

Procedia PDF Downloads 323

Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

Abstract:

Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

Procedia PDF Downloads 174

Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

Abstract:

The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

Procedia PDF Downloads 279

Authors: Fengxia Li, Lufeng Zhang, Haibo Wang

Abstract:

The tight sandstone gas reservoir in the Xujiahe Formation of the Sichuan Basin has huge reserves, but its utilization rate is low. Fracturing and stimulation are indispensable technologies to unlock their potential and achieve commercial exploitation. Slickwater is the most widely used fracturing fluid system in the fracturing and renovation of tight reservoirs. However, its viscosity is low, its sand-carrying performance is poor, and the risk of sand blockage is high. Increasing the sand carrying capacity by increasing the displacement will increase the frictional resistance of the pipe string, affecting the resistance reduction performance. The variable viscosity slickwater can flexibly switch between different viscosities in real-time online, effectively overcoming problems such as sand carrying and resistance reduction. Based on a self-developed indoor loop friction testing system, a visualization device for proppant transport, and a HAAKE MARS III rheometer, a comprehensive evaluation was conducted on the performance of variable viscosity slickwater, including resistance reduction, rheology, and sand carrying. The indoor experimental results show that: 1. by changing the concentration of drag-reducing agents, the viscosity of the slippery water can be changed between 2~30mPa. s; 2. the drag reduction rate of the variable viscosity slickwater is above 80%, and the shear rate will not reduce the drag reduction rate of the liquid; under indoor experimental conditions, 15mPa. s of variable viscosity and slickwater can basically achieve effective carrying and uniform placement of proppant. The layered fracturing effect of the JiangX well in the dense sandstone of the Xujiahe Formation shows that the drag reduction rate of the variable viscosity slickwater is 80.42%, and the daily production of the single layer after fracturing is over 50000 cubic meters. This study provides theoretical support and on-site experience for promoting the application of variable viscosity slickwater in tight sandstone gas reservoirs.

Keywords: slickwater, hydraulic fracturing, dynamic sand laying, drag reduction rate, rheological properties

Procedia PDF Downloads 66

Authors: Waleerak Sittisom

Abstract:

The objectives of this research were to analyze transportation route management, to identify potential cost reductions in logistic operation. In-depth interview techniques and small group discussions were utilized with 25 participants from various backgrounds in the areas of logistics. The findings of this research revealed that there were four areas that companies are able to effectively manage a logistic cost reduction: managing the space within the transportation vehicles, managing transportation personnel, managing transportation cost, and managing control of transportation. On the other hand, there were four areas that companies were unable to effectively manage a logistic cost reduction: the working process of transportation, the route planning of transportation, the service point management, and technology management. There are five areas that cost reduction is feasible: personnel management, process of working, map planning, service point planning, and technology implementation. To be able to reduce costs, the transportation companies should suggest that customers use a file system to save truck space. Also, the transportation companies need to adopt new technology to manage their information system so that packages can be reached easy, safe, and fast. Staff needs to be trained regularly to increase knowledge and skills. Teamwork is required to effectively reduce the costs.

Keywords: cost reduction, management, logistics, transportation

Procedia PDF Downloads 493

Authors: Muntanavadee Maytapattana

Abstract:

The purposes of the study were to evaluate the effectiveness of the Parent Training Program for Obesity Reduction (PTPOR) on health behaviors of school-age children. An Ecological Systems Theory (EST) was approached the study and a randomized control trial was used in this study. Participants were school-age overweight or obese children and their parents. One hundred and one parent-child dyads were recruited and random assigned into the PTPOR (N=30), Educational Intervention or EI (N=32), and control group (N=39). The parents in the PTPOR group participated in five sessions including an educational session, a cooking session, aerobic exercise training, 2-time group discussion sessions, and 4-time telephoned counseling sessions. Repeated Measure ANCOVA was used to analyze data. The results presented that the outcomes of the PTPOR group were better than the EI and the control groups at 1st, 8th, and 32nd weeks after finishing the program such as child exercise behavior (F(2,97) = 3.98, p = .02) and child dietary behavior (F(2,97) = 9.42, p = .00). The results suggest that nurses and health care providers should utilize the PTPOR for child weight reduction and for the health promotion of a lifestyle among overweight and obese children.

Keywords: parent training program, obesity reduction, child health behaviors, school-age children

Procedia PDF Downloads 435

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

Abstract:

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 385

Authors: Jong-Yeon Kim, Kwang-Bok Shin, Tae-Hwan Ko

Abstract:

The purpose of this paper is to suggest a weight-reduction design method for the aluminum extrusion carbody structure of a double deck high-speed train using size optimization method. The size optimization method was used to optimize thicknesses of skin and rib of the aluminum extrusion for the carbody structure. Thicknesses of 1st underframe, 2nd underframe, solebar and roof frame were selected by design variables in order to conduct size optimization. The results of the size optimization analysis showed that the weight of the aluminum extrusion could be reduced by 0.61 tons (5.60%) compared to the weight of the original carbody structure.

Keywords: double deck high-speed train, size optimization, weigh-reduction, aluminum extrusion

Procedia PDF Downloads 283

Authors: Leila Samiee, Amir Yadegari, Saeedeh Tasharrofi

Abstract:

In the work presented here, nitrogen-doped graphene materials were synthesized and used as metal-free electrocatalysts for oxygen reduction reaction (ORR) under alkaline conditions. Paraphenylenediamine was used as N precursor. The N-doped graphene was synthesized under hydrothermal treatment at 200°C. All the materials have been characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Transmission electron microscopy (TEM) and X-ray photo-electron spectroscopy (XPS). Moreover, for electrochemical evaluation of samples, Rotating Disk electrode (RDE) and Cyclic Voltammetry techniques (CV) were employed. The resulting material exhibits an outstanding catalytic activity for the oxygen reduction reaction (ORR) as well as excellent resistance towards methanol crossover effects, indicating their promising potential as ORR electrocatalysts for alkaline fuel cells.

Keywords: alkaline fuel cell, graphene, metal-free catalyst, paraphenylen diamine

Procedia PDF Downloads 466

Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi

Abstract:

The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.

Keywords: classification, random subspace, ensemble, CMAC neural network

Procedia PDF Downloads 322

Authors: Doo Ki Lee, Kumaresh Selvakumar, Man Young Kim, In Jae Song

Abstract:

The widespread utilization of mixer in selective catalytic reduction (SCR) system marks a remarkable advantage in diesel engines. In the automotive selective catalytic reduction (SCR) system, the de-NOX efficiency can be improved by highly uniform flow with effective turbulent mixing. In this paper, the exhaust pipe is complemented with the swirling mixers of three different vane angles installed at the upstream of the SCR reactor. The attributes of the mixer are established by the variation in flow behavior followed by the drawback owing to the absence of mixer. In particular, the information pertaining to the selection of proper static mixer is provided based on the correlation between the uniformity index (UI) and the pressure drop. The uniform distribution of the flow at the entrance of the SCR reactor aids to determine the configuration which gives high mixing performance and comprehend the function of the mixer.

Keywords: pressure drop, selective catalytic reduction, static mixer, turbulent mixing, uniformity index

Procedia PDF Downloads 928

Authors: Zoran Herceg, Višnja Stulić, Anet Režek Jambrak, Tomislava Vukušić

Abstract:

Electrical discharge plasma is a new non-thermal processing technique which is used for the inactivation of contaminating and hazardous microbes in liquids. Plasma is a source of different antimicrobial species including UV photons, charged particles, and reactive species such as superoxide, hydroxyl radicals, nitric oxide and ozone. Escherichia coli was studied as foodborne pathogen. The aim of this work was to examine inactivation effects of electrical discharge plasma treatment on the Escherichia coli MG 1655 in pure culture. Two types of plasma configuration and polarity were used. First configuration was with titanium wire as high voltage needle and another with medical stainless steel needle used to form bubbles in treated volume and titanium wire as high voltage needle. Model solution samples were inoculated with Escerichia coli MG 1655 and treated by electrical discharge plasma at treatment time of 5 and 10 min, and frequency of 60, 90 and 120 Hz. With the first configuration after 5 minutes of treatment at frequency of 120 Hz the inactivation rate was 1.3 log₁₀ reduction and after 10 minutes of treatment the inactivation rate was 3.0 log₁₀ reduction. At the frequency of 90 Hz after 10 minutes inactivation rate was 1.3 log₁₀ reduction. With the second configuration after 5 minutes of treatment at frequency of 120 Hz the inactivation rate was 1.2 log₁₀ reduction and after 10 minutes of treatment the inactivation rate was also 3.0 log₁₀ reduction. In this work it was also examined the formation of biofilm, nucleotide and protein leakage at 260/280 nm, before and after treatment and recuperation of treated samples. Further optimization of method is needed to understand mechanism of inactivation.

Keywords: electrical discharge plasma, escherichia coli MG 1655, inactivation, point-to-plate electrode configuration

Procedia PDF Downloads 423

Authors: Mohammad Aynal Haque

Abstract:

Under the international cooperation — Paris Agreement — countries outline their self-determined policy ambition for emissions reduction in their Nationally Determined Contributions (NDCs) as a key to addressing climate change globally. Although practically all countries commit themselves to reach the Paris landmark (below 20 C) globally, some act as climate leaders, others behave as followers, and others turn out to be climate laggards. As a result, there is a substantial variation in ‘emissions reduction targets’ across countries. Thus, a question emerges: What explains this variation? Or why do some countries opt for higher while others opt for lower ‘emissions reduction targets toward global mitigation efforts? Conceptualizing the ‘emissions reduction targets by 2030’ outlined in NDCs by each country as the climate policy ambition (CPA), this paper explores how certain national political, economic, environmental, and external factors play vital roles in determining climate policy ambition. Based on the cross-country regression analysis among 168 countries, this study finds that democracy, vulnerability to climate change effects, and foreign direct investment have substantial effects on CPA. The paper also finds that resource capacity has a minimal negative effect on CPA across developed countries.

Keywords: climate change, Paris agreement, international cooperation, political economy, environmental politics, NDCs

Procedia PDF Downloads 67

Authors: Samina Sarwar, Hajra Khalil

Abstract:

Mycoremediation is emerging as a potential approach for eco-friendly and cost-effective remediation of polluted effluents collected from the dyeing unit of the textile industry was examined. This work dealt with the analyses of the bio remedial capability of some potential indigenous six fungal isolates viz., Aspergillus alliaceus, Aspergillus flavus, Aspergillus fumigatus Aspergillus niger, Penicillium sp. and Rhizopus oryzae were identified and selected for studies. All fungal species were known to bring bioremediation, which had been confirmed by measuring the percentage reduction potential in different parameters, i.e., pH, Electrical Conductivity (EC), Total Suspended Solids (TSS), Total Dissolved Solids (TDS), Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Rhizopus oryzae showed the highest reduction in pH, EC, and BOD, while Aspergillus fumigatus showed the highest reduction in TDS and TSS, and COD under the optimal conditions of this study. The biodegradation potential of these fungal species was confirmed, evidenced by excellent evaluation of experimental data to propose Rhizopus oryzae and Aspergillus fumigatus as a cost-effective solution to treat the effluents from the dyeing unit of the textile industry.

Keywords: biological reduction, fungal isolates, micromycetes, mycoremediation

Procedia PDF Downloads 68

Authors: Samina Sarwar, Hajra Khalil

Abstract:

Mycoremediation is emerging as a potential approach for eco-friendly and cost-effective remediation of polluted effluents collected from the dyeing unit of the textile industry was examined. This work dealt with the analyses of the bio remedial capability of some potential indigenous six fungal isolates viz., Aspergillus alliaceus, Aspergillus flavus, Aspergillus fumigatus Aspergillus niger, Penicillium sp. and Rhizopus oryzae were identified and selected for studies. All fungal species were known to bring bioremediation, which had been confirmed by measuring the percentage reduction potential in different parameters, i.e., pH, Electrical Conductivity (EC), Total Suspended Solids (TSS), Total Dissolved Solids (TDS), Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Rhizopus oryzae showed the highest reduction in pH, EC, and BOD, while Aspergillus fumigatus showed the highest reduction in TDS and TSS, and COD under the optimal conditions of this study. The biodegradation potential of these fungal species was confirmed, evidenced by excellent evaluation of experimental data to propose Rhizopus oryzae and Aspergillus fumigatus as a cost-effective solution to treat the effluents from the dyeing unit of the textile industry.

Keywords: biological reduction, fungal isolates, micromycetes, mycoremediation

Procedia PDF Downloads 83

Authors: Razieh Khalafi

Abstract:

Myocardial infarction (MI) or acute myocardial infarction (AMI), commonly known as a heart attack, occurs when blood flow stops to part of the heart causing damage to the heart muscle. An ECG can often show evidence of a previous heart attack or one that's in progress. The patterns on the ECG may indicate which part of your heart has been damaged, as well as the extent of the damage. In chaos theory, the correlation dimension is a measure of the dimensionality of the space occupied by a set of random points, often referred to as a type of fractal dimension. In this research by considering ECG signal as a random walk we work on forecasting the oncoming heart attack by analyzing the ECG signals using the correlation dimension. In order to test the model a set of ECG signals for patients before and after heart attack was used and the strength of model for forecasting the behavior of these signals were checked. Results shows this methodology can forecast the ECG and accordingly heart attack with high accuracy.

Keywords: heart attack, ECG, random walk, correlation dimension, forecasting

Procedia PDF Downloads 525

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.

Keywords: classification, achine learning, predictive quality, feature selection

Procedia PDF Downloads 156

Authors: Gabriel Sunday Ayayia

Abstract:

Food waste has reached alarming levels worldwide, contributing to food insecurity, resource depletion, and environmental degradation. While numerous strategies exist to mitigate this issue, the role of traditional practices and indigenous knowledge remains underexplored. There is a need to investigate how these age-old practices can contribute to sustainable food waste reduction, particularly in the African context. This study explores the potential of traditional practices and indigenous knowledge in Africa to address this challenge sustainably. The study examines traditional African food management practices and indigenous knowledge related to food preservation and utilization; assess the impact of traditional practices on reducing food waste and its broader implications for sustainable development, and identify key factors influencing the continued use and effectiveness of traditional practices in contemporary African societies. Thus, the study argues that traditional practices and indigenous knowledge in Africa offer valuable insights and strategies for sustainable food waste reduction that can be adapted and integrated into global initiatives This research will employ a mixed-methods approach, combining qualitative and quantitative research techniques. Data collection will involve in-depth interviews, surveys, and participant observations in selected African communities. Moreover, a comprehensive review of literature on traditional food management practices and their impact on food waste reduction will be conducted. The significance of this study lies in its potential to bridge the gap between traditional knowledge and modern sustainability efforts. By uncovering the value of traditional practices in reducing food waste, this research can inform policies, interventions, and awareness campaigns aimed at achieving sustainable food systems worldwide.

Keywords: traditional practices, indigenous knowledge, food waste reduction, sustainability

Procedia PDF Downloads 63

Authors: Florian Gschösser, Walter Purrer

Abstract:

The paper shows examples for the (environmental) optimization of production processes for asphalt mixtures applied for typical road pavements in Austria and Switzerland. The conducted “from-cradle-to-gate” LCA firstly analyzes the production one cubic meter of asphalt and secondly all material production processes for exemplary highway pavements applied in Austria and Switzerland. It is shown that environmental impacts can be reduced by the application of reclaimed asphalt pavement (RAP) and by the optimization of specific production characteristics, e.g. the reduction of the initial moisture of the mineral aggregate and the reduction of the mixing temperature by the application of low-viscosity and foam bitumen. The results of the LCA study demonstrate reduction potentials per cubic meter asphalt of up to 57 % (Global Warming Potential–GWP) and 77 % (Ozone depletion–ODP). The analysis per square meter of asphalt pavement determined environmental potentials of up to 40 % (GWP) and 56 % (ODP).

Keywords: asphalt mixtures, environmental potentials, life cycle assessment, material production

Procedia PDF Downloads 521

Authors: Mohamed E. Eleshaky

Abstract:

This paper investigates the dynamic behavior of laminar water flows inside superhydrophobic micro-pipes patterned with square micro-posts features under different operating conditions. It also investigates the effects of air fraction and Reynolds number on the frictional performance of these pipes. Rather than modeling the air-water interfaces of superhydrophobic as a flat inflexible surface, a transient, incompressible, three-dimensional, volume-of-fluid (VOF) methodology has been employed to continuously track the air–water interface shape inside micro-pipes. Also, the entrance effects on the flow field have been taken into consideration. The results revealed the strong dependency of the frictional performance on the air fractions and Reynolds number. The frictional resistance reduction becomes increasingly more significant at large air fractions and low Reynolds numbers. Increasing Reynolds number has an adverse effect on the frictional resistance reduction.

Keywords: drag reduction, laminar flow in micropipes, numerical simulation, superhyrophobic surfaces, microposts

Procedia PDF Downloads 317

Authors: Razi Khalafi

Abstract:

Myocardial Infarction (MI) or acute Myocardial Infarction (AMI), commonly known as a heart attack, occurs when blood flow stops to part of the heart causing damage to the heart muscle. An ECG can often show evidence of a previous heart attack or one that's in progress. The patterns on the ECG may indicate which part of your heart has been damaged, as well as the extent of the damage. In chaos theory, the correlation dimension is a measure of the dimensionality of the space occupied by a set of random points, often referred to as a type of fractal dimension. In this research by considering ECG signal as a random walk we work on forecasting the oncoming heart attack by analysing the ECG signals using the correlation dimension. In order to test the model a set of ECG signals for patients before and after heart attack was used and the strength of model for forecasting the behaviour of these signals were checked. Results show this methodology can forecast the ECG and accordingly heart attack with high accuracy.

Keywords: heart attack, ECG, random walk, correlation dimension, forecasting

Procedia PDF Downloads 493

Authors: G. Tamulevičius, A. Serackis, T. Sledevič, D. Navakauskas

Abstract:

We consider the biggest challenge in speech recognition – noise reduction. Traditionally detected transient noise pulses are removed with the corrupted speech using pulse models. In this paper we propose to cope with the problem directly in Dynamic Time Warping domain. Bidirectional Dynamic Time Warping algorithm for the recognition of isolated words impacted by transient noise pulses is proposed. It uses simple transient noise pulse detector, employs bidirectional computation of dynamic time warping and directly manipulates with warping results. Experimental investigation with several alternative solutions confirms effectiveness of the proposed algorithm in the reduction of impact of noise on recognition process – 3.9% increase of the noisy speech recognition is achieved.

Keywords: transient noise pulses, noise reduction, dynamic time warping, speech recognition

Procedia PDF Downloads 547

Authors: Edward J. Kansa, Pavel Holoborodko

Abstract:

Continuously differentiable radial basis functions (RBFs) are meshfree, converge faster as the dimensionality increases, and is theoretically spectrally convergent. When implemented on current single and double precision computers, such RBFs can suffer from ill-conditioning because the systems of equations needed to be solved to find the expansion coefficients are full. However, the Advanpix extended precision software package allows computer mathematics to resemble asymptotically ideal Platonic mathematics. Additionally, full systems with extended precision execute faster graphical processors units and field-programmable gate arrays because no branching is needed. Sparse equation systems are fast for iterative solvers in a very limited number of cases.

Keywords: partial differential equations, Meshfree radial basis functions, , no restrictions on spatial dimensions, Extended arithmetic precision.

Procedia PDF Downloads 144

Authors: Kumaresh Selvakumar, Man Young Kim

Abstract:

Selective catalytic reduction (SCR) converts the nitrogen oxides with the aid of a catalyst by adding aqueous urea into the exhaust stream. In this work, the urea water droplets are sprayed over the exhaust gases by treating with Lagrangian particle tracking. The evaporation of ammonia from a single droplet of urea water solution is investigated computationally by convection-diffusion controlled model. The conversion to ammonia due to thermolysis of urea water droplets is measured downstream at different sections using finite rate/eddy dissipation model. In this paper, the mixer installed at the upstream enhances the distribution of ammonia over the entire domain which is calculated for different time steps. Calculations are made within the respective duration such that the complete decomposition of urea is possible at a much shorter residence time.

Keywords: convection-diffusion controlled model, lagrangian particle tracking, selective catalytic reduction, thermolysis

Procedia PDF Downloads 398

Authors: Amir Hossein Haji, Nabeel Al-Rawahi, Gholamreza Vakili-Nezhaad

Abstract:

An innovative design has been examined for a gas-oil separator based on pressure reduction over an airfoil surface. The primary motivations are to shorten the release trajectory of the bubbles by minimizing the thickness of the oil layer as well as improving uniform pressure reduction zones. Restricted airflow over an airfoil is investigated for its effect on the pressure drop enhancement and the maximum attainable attack angle prior to the stall condition. Aerodynamic separation is delayed based on numerical simulation of Wortmann FX 63137 Airfoil in a confined domain using FLUENT 6.3.26. The proposed set up results in higher pressure drop compared with the free stream case. With the aim of optimum power consumption we have pursued further restriction to an air jet case over the airfoil. Then, a curved strip model is suggested for the air jet which can be applied as an analysis/design tool for the best performance conditions. Pressure reduction is shown to be inversely proportional to the curvature of the upper airfoil profile. This reduction occurs within the tracking zones where the air jet is effectively attached to the airfoil surface. The zero slope condition is suggested to estimate the onset of these zones after which the minimum curvature should be searched. The corresponding zero slope curvature is applied for estimation of the maximum pressure drop which shows satisfactory agreement with the simulation results.

Keywords: airfoil, air jet, curved fluid flow, gas-oil separator

Procedia PDF Downloads 457

Authors: Muneerah Jeludin, V. Sivakumar

Abstract:

Numerous laboratory-based research studies on the behavior of ground improved with granular columns with respect to bearing capacity have been well-documented. However, information on its settlement performance is still scarce. Laboratory model study on the settlement behavior of soft clay reinforced with granular columns was conducted and results are presented. The investigation uses a soft kaolin clay sample of 300 mm in diameter and 400 mm in length. The clay samples were reinforced with single and multiple granular columns of various lengths using the displacement and replacement installation method. The results indicated that that no settlement reduction was achieved for a short single floating column. The settlement reduction factors reported for L/d ratios of 5.0, 7.5 and 10.0 are in the range of 1 to 2. The findings obtained in this research showed that the reduction factors are considerably less and that load-sharing mechanism between columns and surrounding clay is complex, particularly for column groups and is affected by other factors such as negative skin friction.

Keywords: ground improvement, model test, reinforced soil, settlement

Procedia PDF Downloads 455

Authors: Wilmer Esteban Vallejo Narváez, Serguei Fomine

Abstract:

The theoretical investigation of Si-doped graphene nanoflakes (NFs) was conducted to understand their catalytic impact on CO₂ reduction using molecular hydrogen at the Density Functional Theory (DFT) level. The introduction of silicon by substituting carbon induces defects in the NF structure, resulting in a polyradical ground state. This silicon defect significantly boosts reactivity towards substrates, making Si-doped graphene NFs more catalytically active in CO₂ reduction to formic acid compared to silicene. Notably, Si-doped graphene demonstrates a preference for formic acid over carbon monoxide, mirroring the behavior of silicene. Furthermore, investigations into formic acid-to-formaldehyde and formaldehyde-to-methanol conversions reveal instances where Si-doped graphene outperforms silicene in terms of efficacy. In the final reduction step, the methanol-to-methane reaction unfolds in four stages, with the rate-determining step involving hydrogen transfer from silicon to methyl. Notably, the activation energy for this step is lower in Si-doped graphene compared to silicene. Consequently, Si-doped graphene NFs emerge as superior catalysts with lower activation energies overall. Remarkably, throughout these catalytic processes, Si-doped graphene maintains environmental stability, further highlighting its enhanced catalytic activity without compromising graphene's inherent stability.

Keywords: silicon-doped graphene, CO₂ reduction, DFT, catalysis

Procedia PDF Downloads 44

Authors: Dhyaalddin Bahaalddin Noori Zangana

Abstract:

This study involves the behavior of reinforced sand under a square footing. A series of bearing capacity tests were performed on a small-scale laboratory model, which filled with a poorly-graded homogenous bed of sand, which was placed in a medium dense state using sand raining technique. The sand was reinforced with 40 mm wide household aluminum foil strips. The main studied parameters was to consider the effect of reinforcing strip length, with various linear density of reinforcement, number of reinforcement layers and depth of top layer of reinforcement below the footing, on load-settlement behavior, bearing capacity ratio and settlement reduction factor. The relation of load-settlement generally showed similar trend in all the tests. Failure was defined as settlement equal to 10% of the footing width. The recommended optimum reinforcing strip length, linear density of reinforcement, number of reinforcement layers and depth of top layer of reinforcing strips that give the maximum bearing capacity improvement and minimum settlement reduction factor were presented and discussed. Different bearing capacity ration versus length of the reinforcing strips and settlement reduction factor versus length of the reinforcing strips relations at failure were showed improvement of bearing capacity ratio by a factor of 3.82 and reduction of settlement reduction factor by a factor of 0.813. The optimum length of reinforcement was found to be 7.5 times the footing width.

Keywords: square footing, relative density, linear density of reinforcement, bearing capacity ratio, load-settlement behaviour

Procedia PDF Downloads 90

Authors: Gopi Ram, Durbadal Mandal, Rajib Kar, Sakti Prasad Ghoshal

Abstract:

A design problem of non-uniform circular antenna arrays for maximum reduction of both the side lobe level (SLL) and first null beam width (FNBW) is dealt with. This problem is modeled as a simple optimization problem. The method of Firefly algorithm (FFA) is used to determine an optimal set of current excitation weights and antenna inter-element separations that provide radiation pattern with maximum SLL reduction and much improvement on FNBW as well. Circular array antenna laid on x-y plane is assumed. FFA is applied on circular arrays of 8-, 10-, and 12- elements. Various simulation results are presented and hence performances of side lobe and FNBW are analyzed. Experimental results show considerable reductions of both the SLL and FNBW with respect to those of the uniform case and some standard algorithms GA, PSO, and SA applied to the same problem.

Keywords: circular arrays, first null beam width, side lobe level, FFA

Procedia PDF Downloads 246