Search results for: optimal sensing

Authors: Indu Chandran, Shubham Sharma, Rohan Mehta, Vipin Kizheppatt

Abstract:

Unmanned aerial vehicles are increasingly being explored as the most promising solution to disaster monitoring, assessment, and recovery. Current relief operations heavily rely on intelligent robot swarms to capture the damage caused, provide timely rescue, and create road maps for the victims. To perform these time-critical missions, efficient path planning that ensures quick coverage of the area is vital. This study aims to develop a technically balanced approach to provide maximum coverage of the affected area in a minimum time using the optimal number of UAVs. A coverage trajectory is designed through area decomposition and task assignment. To perform efficient and autonomous coverage mission, solution to a TSP-based optimization problem using meta-heuristic approaches is designed to allocate waypoints to the UAVs of different flight capacities. The study exploits multi-agent simulations like PX4-SITL and QGroundcontrol through the ROS framework and visualizes the dynamics of UAV deployment to different search paths in a 3D Gazebo environment. Through detailed theoretical analysis and simulation tests, we illustrate the optimality and efficiency of the proposed methodologies.

Keywords: area coverage, coverage path planning, heuristic algorithm, mission monitoring, optimization, task assignment, unmanned aerial vehicles

Procedia PDF Downloads 213

Authors: Kai-Chieh Lin, Chih-Fu Wu, Hsiang Ling Hsu, Yung-Hsiang Tu, Chia-Chen Wu

Abstract:

With the rapid development of computer technology, the design of computers and keyboards moves towards a trend of slimness. The change of mobile input devices directly influences users’ behavior. Although multi-touch applications allow entering texts through a virtual keyboard, the performance, feedback, and comfortableness of the technology is inferior to traditional keyboard, and while manufacturers launch mobile touch keyboards and projection keyboards, the performance has not been satisfying. Therefore, this study discussed the design factors of slim pressure-sensitive keyboards. The factors were evaluated with an objective (accuracy and speed) and a subjective evaluation (operability, recognition, feedback, and difficulty) depending on the shape (circle, rectangle, and L-shaped), thickness (flat, 3mm, and 6mm), and force (35±10g, 60±10g, and 85±10g) of the keyboard. Moreover, MANOVA and Taguchi methods (regarding signal-to-noise ratios) were conducted to find the optimal level of each design factor. The research participants, by their typing speed (30 words/ minute), were divided in two groups. Considering the multitude of variables and levels, the experiments were implemented using the fractional factorial design. A representative model of the research samples were established for input task testing. The findings of this study showed that participants with low typing speed primarily relied on vision to recognize the keys, and those with high typing speed relied on tactile feedback that was affected by the thickness and force of the keys. In the objective and subjective evaluation, a combination of keyboard design factors that might result in higher performance and satisfaction was identified (L-shaped, 3mm, and 60±10g) as the optimal combination. The learning curve was analyzed to make a comparison with a traditional standard keyboard to investigate the influence of user experience on keyboard operation. The research results indicated the optimal combination provided input performance to inferior to a standard keyboard. The results could serve as a reference for the development of related products in industry and for applying comprehensively to touch devices and input interfaces which are interacted with people.

Keywords: input performance, mobile device, slim keyboard, tactile feedback

Procedia PDF Downloads 298

Authors: Barenten Suciu, Yuya Nakamoto

Abstract:

Power generation effect, obtained by inserting a piezo- electric sheet in the backlash clearance of a circular arc helical gear, is evaluated. Such type of screw gear is preferred since, in comparison with the involute tooth profile, the circular arc profile leads to reduced stress-concentration effects, and improved life of the piezoelectric film. Firstly, geometry of the circular arc helical gear, and properties of the piezoelectric sheet are presented. Then, description of the test-rig, consisted of a right-hand thread gear meshing with a left-hand thread gear, and the voltage measurement procedure are given. After creating the tridimensional (3D) model of the meshing gears in SolidWorks, they are 3D-printed in acrylonitrile butadiene styrene (ABS) resin. Variation of the generated voltage versus time, during a meshing cycle of the circular arc helical gear, is measured for various values of the center distance. Then, the change of the maximal, minimal, and peak-to-peak voltage versus the center distance is illustrated. Optimal center distance of the gear, to achieve voltage maximization, is found and its significance is discussed. Such results prove that the contact pressure of the meshing gears can be measured, and also, the electrical power can be generated by employing the proposed technique.

Keywords: circular arc helical gear, contact problem, optimal center distance, piezoelectric sheet, power generation

Procedia PDF Downloads 166

Authors: E. K. Hardwick, L. B. Siwela, J. G. Falconer, M. E. Mathibela, W. Rolfe

Abstract:

Lithium-ion battery (LiB) demand has increased with the advancement in technologies. The applications include electric vehicles, cell phones, laptops, and many more devices. Typical components of the cathodes include lithium, cobalt, nickel, and manganese. Recycling the spent LiBs is necessary to reduce the ecological footprint of their production and use and to have a secondary source of valuable metals. A hydrometallurgical method was investigated for the recovery of cobalt and nickel from LiB cathodes. The cathodes were leached using a chloride solution. Ion exchange was then used to recover the chloro-complexes of the metals. The aim of the research was to determine the efficiency of a chloride leach, as well as ion exchange operating capacities that can be achieved for LiB recycling, and to establish the optimal operating conditions (ideal pH, temperature, leachate and eluant, flowrate, and reagent concentrations) for the recovery of the cathode metals. It was found that the leaching of the cathodes could be hindered by the formation of refractory metal oxides of cathode components. A reducing agent was necessary to improve the leaching rate and efficiency. Leaching was achieved using various chloride-containing solutions. The chloro-complexes were absorbed by the ion exchange resin and eluted to produce concentrated cobalt, nickel, lithium, and manganese streams. Chromatographic separation of these elements was achieved. Further work is currently underway to determine the optimal operating conditions for the recovery by ion exchange.

Keywords: cobalt, ion exchange, leachate formation, lithium-ion batteries, manganese, nickel

Procedia PDF Downloads 95

Authors: Sinsze Koo, Benjin Luo, Matthew Henry

Abstract:

In order to increase the performance of an automatic transmission, the automatic transmission fluid is required to be warm up to an optimal operating temperature. In a conventional vehicle, cold starts result in friction loss occurring in the gear box and engine. The stop and go nature of city driving dramatically affect the warm-up of engine oil and automatic transmission fluid and delay the time frame needed to reach an optimal operating temperature. This temperature phenomenon impacts both engine and transmission performance but also increases fuel consumption and CO2 emission. The aim of this study is to develop know-how of the thermal behavior in order to identify thermal impacts and functional principles in automatic transmissions. Thermal behavior was studied using models and simulations, developed using GT-Suit, on a one-dimensional thermal and flow transport. A power train of a conventional vehicle was modeled in order to emphasis the thermal phenomena occurring in the various components and how they impact the automatic transmission performance. The simulation demonstrates the thermal model of a transmission fluid cooling system and its component parts in warm-up after a cold start. The result of these analyses will support the future designs of transmission systems and components in an attempt to obtain better fuel efficiency and transmission performance. Therefore, these thermal analyses could possibly identify ways that improve existing thermal management techniques with prioritization on fuel efficiency.

Keywords: thermal management, automatic transmission, hybrid, and systematic approach

Procedia PDF Downloads 375

Authors: Sohyoung Won, Heebal Kim, Dajeong Lim

Abstract:

Genomic prediction is an effective way to measure the abilities of livestock for breeding based on genomic estimated breeding values, statistically predicted values from genotype data using best linear unbiased prediction (BLUP). Using haplotypes, clusters of linked single nucleotide polymorphisms (SNPs), as markers instead of individual SNPs can improve the reliability of genomic prediction since the probability of a quantitative trait loci to be in strong linkage disequilibrium (LD) with markers is higher. To efficiently use haplotypes in genomic prediction, finding optimal ways to define haplotypes is needed. In this study, 770K SNP chip data was collected from Hanwoo (Korean cattle) population consisted of 2506 cattle. Haplotypes were first defined in three different ways using 770K SNP chip data: haplotypes were defined based on 1) length of haplotypes (bp), 2) the number of SNPs, and 3) k-medoids clustering by LD. To compare the methods in parallel, haplotypes defined by all methods were set to have comparable sizes; in each method, haplotypes defined to have an average number of 5, 10, 20 or 50 SNPs were tested respectively. A modified GBLUP method using haplotype alleles as predictor variables was implemented for testing the prediction reliability of each haplotype set. Also, conventional genomic BLUP (GBLUP) method, which uses individual SNPs were tested to evaluate the performance of the haplotype sets on genomic prediction. Carcass weight was used as the phenotype for testing. As a result, using haplotypes defined by all three methods showed increased reliability compared to conventional GBLUP. There were not many differences in the reliability between different haplotype defining methods. The reliability of genomic prediction was highest when the average number of SNPs per haplotype was 20 in all three methods, implying that haplotypes including around 20 SNPs can be optimal to use as markers for genomic prediction. When the number of alleles generated by each haplotype defining methods was compared, clustering by LD generated the least number of alleles. Using haplotype alleles for genomic prediction showed better performance, suggesting improved accuracy in genomic selection. The number of predictor variables was decreased when the LD-based method was used while all three haplotype defining methods showed similar performances. This suggests that defining haplotypes based on LD can reduce computational costs and allows efficient prediction. Finding optimal ways to define haplotypes and using the haplotype alleles as markers can provide improved performance and efficiency in genomic prediction.

Keywords: best linear unbiased predictor, genomic prediction, haplotype, linkage disequilibrium

Procedia PDF Downloads 139

Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

Abstract:

In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

Procedia PDF Downloads 419

Authors: L. Grinis, N. Lubashevsky, Y. Ostrovski

Abstract:

A jet pump is a type of pump that accelerates the flow of a secondary fluid (driven fluid) by introducing a motive fluid with high velocity into a converging-diverging nozzle. Jet pumps are also known as adductors or ejectors depending on the motivator phase. The ejector's motivator is of a gaseous nature, usually steam or air, while the educator's motivator is a liquid, usually water. Jet pumps are devices that use air bubbles and are widely used in wastewater treatment processes. In this work, we will discuss about the characteristics of the jet pump and the computational simulation of this device. To find the optimal angle and depth for the air pipe, so as to achieve the maximal air volumetric flow rate, an experimental apparatus was constructed to ascertain the best geometrical configuration for this new type of jet pump. By using 3D printing technology, a series of jet pumps was printed and tested whilst aspiring to maximize air flow rate dependent on angle and depth of the air pipe insertion. The experimental results show a major difference of up to 300% in performance between the different pumps (ratio of air flow rate to supplied power) where the optimal geometric model has an insertion angle of 60⁰ and air pipe insertion depth ending at the center of the mixing chamber. The differences between the pumps were further explained by using CFD for better understanding the reasons that affect the airflow rate. The validity of the computational simulation and the corresponding assumptions have been proved experimentally. The present research showed high degree of congruence with the results of the laboratory tests. This study demonstrates the potential of using of the jet pump in many practical applications.

Keywords: air bubbles, CFD simulation, jet pump, applications

Procedia PDF Downloads 242

Authors: Connor Dunlop, Bassim Abbassi, Richard G. Zytner

Abstract:

Life cycle assessment (LCA) is a powerful tool established by the International Organization for Standardization (ISO) that can be used to assess the environmental impacts of a product or process from cradle to grave. Many studies utilize the LCA methodology within the site remediation field to compare various decontamination methods, including bioremediation, soil vapor extraction or excavation, and off-site disposal. However, with the authors' best knowledge, limited information is available in the literature on a sustainability tool that could be used to help with the selection of the optimal remediation technology. This tool, based on the LCA methodology, would consider site conditions like environmental, economic, and social impacts. Accordingly, this project was undertaken to develop a tool to assist with the selection of optimal sustainable technology. Developing a proper tool requires a large amount of data. As such, data was collected from previous LCA studies looking at site remediation technologies. This step identified knowledge gaps or limitations within project data. Next, utilizing the data obtained from the literature review and other organizations, an extensive LCA study is being completed following the ISO 14040 requirements. Initial technologies being compared include bioremediation, excavation with off-site disposal, and a no-remediation option for a generic gasoline-contaminated site. To complete the LCA study, the modelling software SimaPro is being utilized. A sensitivity analysis of the LCA results will also be incorporated to evaluate the impact on the overall results. Finally, the economic and social impacts associated with each option will then be reviewed to understand how they fluctuate at different sites. All the results will then be summarized, and an interactive tool using Excel will be developed to help select the best sustainable site remediation technology. Preliminary LCA results show improved sustainability for the decontamination of a gasoline-contaminated site for each technology compared to the no-remediation option. Sensitivity analyses are now being completed on on-site parameters to determine how the environmental impacts fluctuate at other contaminated gasoline locations as the parameters vary, including soil type and transportation distances. Additionally, the social improvements and overall economic costs associated with each technology are being reviewed. Utilizing these results, the sustainability tool created to assist in the selection of the overall best option will be refined.

Keywords: life cycle assessment, site remediation, sustainability tool, contaminated sites

Procedia PDF Downloads 57

Authors: Bansal Ashwani

Abstract:

Cartographic depiction and visualization of wetland changes is an important tool to map spatial-temporal information about the wetland dynamics effectively and to comprehend the response of these water bodies in maintaining the groundwater and surrounding ecosystem. This is true for the states of North Western India, i.e., J&K, Himachal, Punjab, and Haryana that are bestowed upon with several natural wetlands in the flood plains or on the courses of its rivers. Thus, the present study documents, analyses and reconstructs the lost wetlands, which existed in the flood plains of the major river basins of these states, i.e., Chenab, Jhelum, Satluj, Beas, Ravi, and Ghagar, in the beginning of the 20th century. To achieve the objective, the study has used multi-temporal datasets since the 1960s using high to medium resolution satellite datasets, e.g., Corona (1960s/70s), Landsat (1990s-2017) and Sentinel (2017). The Sentinel (2017) satellite image has been used for making the wetland inventory owing to its comparatively higher spatial resolution with multi-spectral bands. In addition, historical records, repeated photographs, historical maps, field observations including geomorphological evidence were also used. The water index techniques, i.e., band rationing, normalized difference water index (NDWI), modified NDWI (MNDWI) have been compared and used to map the wetlands. The wetland types found in the north-western states have been categorized under 19 classes suggested by Space Application Centre, India. These enable the researcher to provide with the wetlands inventory and a series of cartographic representation that includes overlaying multiple temporal wetlands extent vectors. A preliminary result shows the general state of wetland shrinkage since the 1960s with varying area shrinkage rate from one wetland to another. In addition, it is observed that majority of wetlands have not been documented so far and even do not have names. Moreover, the purpose is to emphasize their elimination in addition to establishing a baseline dataset that can be a tool for wetland planning and management. Finally, the applicability of cartographic depiction and visualization, historical map sources, repeated photographs and remote sensing data for reconstruction of long term wetlands fluctuations, especially in the northern part of India, will be addressed.

Keywords: cartographic depiction and visualization, wetland changes, NDWI/MDWI, geomorphological evidence and remote sensing

Procedia PDF Downloads 261

Authors: Rajeev Jain, Nimisha Jadon, Kshiti Singh

Abstract:

Titanium oxide nanoparticles and 1-butyl-2,3-dimethylimidazolium bis (trifluoromethane- sulfonyl) imide modified glassy carbon electrode (TiO2/IL/GCE) has been fabricated for electrochemical sensing of flunarizine dihydrochloride (FRH). The electrochemical properties and morphology of the prepared nanocomposite were studied by electrochemical impedance spectroscopy (EIS) and transmission electron microscopy (TEM). The response of the electrochemical sensor was found to be proportional to the concentrations of FRH in the range from 0.5 µg mL-1 to 16 µg mL-1. The detection limit obtained was 0.03 µg mL-1. The proposed method was also applied to the determination of FRH in pharmaceutical formulation and human serum with good recoveries.

Keywords: flunarizine dihydrochloride, ionic liquid, nanoparticles, voltammetry, human serum

Procedia PDF Downloads 328

Authors: Willi Zschiebsch, Alrik Dargel, Sebastian Spitzer, Philipp Johst, Robert Böhm, Niels Modler

Abstract:

In this article, we investigate an approach that digitally links individual development process steps by using the drive shaft of an aircraft engine as a representative example of a fiber polymer composite. Such high-performance, lightweight composite structures have many adjustable parameters that influence the mechanical properties. Only a combination of optimal parameter values can lead to energy efficient lightweight structures. The development tools required for the Engineering Design Process (EDP) are often isolated solutions, and their compatibility with each other is limited. A digital framework is presented in this study, which allows individual specialised tools to be linked via the generated data in such a way that automated optimization across programs becomes possible. This is demonstrated using the example of linking geometry generation with numerical structural analysis. The proposed digital framework for automated design optimization demonstrates the feasibility of developing a complete digital approach to design optimization. The methodology shows promising potential for achieving optimal solutions in terms of mass, material utilization, eigenfrequency, and deformation under lateral load with less development effort. The development of such a framework is an important step towards promoting a more efficient design approach that can lead to stable and balanced results.

Keywords: digital linked process, composite, CFRP, multi-objective, EDP, NSGA-2, NSGA-3, TPE

Procedia PDF Downloads 75

Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

Abstract:

Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

Procedia PDF Downloads 98

Authors: Shuwen Hu, Yuancheng Lou, Dongxu Ji

Abstract:

Photovoltaic (PV) power generation, as one of the most commercialized methods to utilize solar power, can only convert a limited range of solar spectrum into electricity, whereas the majority of the solar energy is dissipated as heat. To address this problem, thermoelectric (TE) module is often integrated with the concentrated PV module for waste heat recovery and regeneration. In this research, a feasibility analysis is conducted for the tandem concentrated photovoltaic-thermoelectric (CPV-TE) hybrid system considering various operational parameters as well as TE material properties. Furthermore, the power output density of the CPV-TE hybrid system is maximized by selecting the optimal TE material with application of a systematic assessment methodology. In the feasibility analysis, CPV-TE is found to be more advantageous than sole CPV system except under high optical concentration ratio with low cold side convective coefficient. It is also shown that the effects of the TE material properties, including Seebeck coefficient, thermal conductivity, and electrical resistivity, on the feasibility of CPV-TE are interacted with each other and might have opposite effect on the system performance under different operational conditions. In addition, the optimal TE material selected by the proposed assessment methodology can improve the system power output density by 227 W/m2 under highly concentrated solar irradiance hence broaden the feasible range of CPV-TE considering optical concentration ratio.

Keywords: feasibility analysis, material assessment methodology, photovoltaic waste heat recovery, tandem photovoltaic-thermoelectric

Procedia PDF Downloads 71

Authors: Massimo Ferrari, Maria Sole Pagliari

Abstract:

Pollution is a classic example of economic externality: agents who produce it do not face direct costs from emissions. Therefore, there are no direct economic incentives for reducing pollution. One way to address this market failure would be directly taxing emissions. However, because emissions are global, governments might as well find it optimal to wait let foreign countries to tax emissions so that they can enjoy the benefits of lower pollution without facing its direct costs. In this paper, we first document the empirical relation between pollution and economic output with static and dynamic regression methods. We show that there is a negative relation between aggregate output and the stock of pollution (measured as the stock of CO₂ emissions). This relationship is also highly non-linear, increasing at an exponential rate. In the second part of the paper, we develop and estimate a two-country, two-sector model for the US and the euro area. With this model, we aim at analyzing how the public sector should respond to higher emissions and what are the direct costs that these policies might have. In the model, there are two types of firms, brown firms (which produce a polluting technology) and green firms. Brown firms also produce an externality, CO₂ emissions, which has detrimental effects on aggregate output. As brown firms do not face direct costs from polluting, they do not have incentives to reduce emissions. Notably, emissions in our model are global: the stock of CO₂ in the economy affects all countries, independently from where it is produced. This simplified economy captures the main trade-off between emissions and production, generating a classic market failure. According to our results, the current level of emission reduces output by between 0.4 and 0.75%. Notably, these estimates lay in the upper bound of the distribution of those delivered by studies in the early 2000s. To address market failure, governments should step in introducing taxes on emissions. With the tax, brown firms pay a cost for polluting hence facing the incentive to move to green technologies. Governments, however, might also adopt a beggar-thy-neighbour strategy. Reducing emissions is costly, as moves production away from the 'optimal' production mix of brown and green technology. Because emissions are global, a government could just wait for the other country to tackle climate change, ripping the benefits without facing any costs. We study how this strategic game unfolds and show three important results: first, cooperation is first-best optimal from a global prospective; second, countries face incentives to deviate from the cooperating equilibria; third, tariffs on imported brown goods (the only retaliation policy in case of deviation from the cooperation equilibrium) are ineffective because the exchange rate would move to compensate. We finally study monetary policy under when costs for climate change rise and show that the monetary authority should react stronger to deviations of inflation from its target.

Keywords: climate change, general equilibrium, optimal taxation, monetary policy

Procedia PDF Downloads 157

Authors: Riaan Kleyn

Abstract:

Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

Procedia PDF Downloads 93

Authors: Aadiv Shah, Hari Nair, Vedant Mittal, Alice Cheeran

Abstract:

Present-day agricultural practices such as blanket spraying not only lead to excessive usage of pesticides but also harm the overall crop yield. This paper introduces an algorithm to optimize the traversal of an unmanned aerial vehicle (UAV) in constrained environments. The proposed system focuses on the agricultural application of targeted spraying for locust elimination. Given a satellite image of a farm, target zones that are prone to locust swarm formation are detected through the calculation of the normalized difference vegetation index (NDVI). This is followed by determining the optimal path for traversal of a UAV through these target zones using the proposed algorithm in order to perform pesticide spraying in the most efficient manner possible. Unlike the classic travelling salesman problem involving point-to-point optimization, the proposed algorithm determines an optimal path for multiple regions, independent of its geometry. Finally, the paper explores the idea of implementing reinforcement learning to model complex environmental behaviour and make the path planning mechanism for UAVs agnostic to external environment changes. This system not only presents a solution to the enormous losses incurred due to locust attacks but also an efficient way to automate agricultural practices across the globe in order to improve farmer ergonomics.

Keywords: locust, NDVI, optimization, path planning, reinforcement learning, UAV

Procedia PDF Downloads 246

Authors: Selvaprakash Ramalingam, Rabi N. Sahoo, Dharmendra Saraswat, A. Kumar, Rajeev Ranjan, Joydeep Mukerjee, Viswanathan Chinnasamy, K. K. Chaturvedi, Sanjeev Kumar

Abstract:

Rice is one of the most important staple food crops in the world. Among the various diseases that affect rice crops, rice blast is particularly significant, causing crop yield and economic losses. While the plant has defense mechanisms in place, such as chemical indicators (proteins, salicylic acid, jasmonic acid, ethylene, and azelaic acid) and resistance genes in certain varieties that can protect against diseases, susceptible varieties remain vulnerable to these fungal diseases. Early prediction of rice blast (RB) disease is crucial, but conventional techniques for early prediction are time-consuming and labor-intensive. Hyperspectral remote sensing techniques hold the potential to predict RB disease at its asymptomatic stage. In this study, we aimed to demonstrate the prediction of RB disease at the asymptomatic stage using non-imaging hyperspectral ASD spectroradiometer under controlled laboratory conditions. We applied statistical spectral discrimination theory to identify unknown spectra of M. Oryzae, the fungus responsible for rice blast disease. The infrared (IR) region was found to be significantly affected by RB disease. These changes may result in alterations in the absorption, reflection, or emission of infrared radiation by the affected plant tissues. Our research revealed that the protein spectrum in the IR region is impacted by RB disease. In our study, we identified strong correlations in the region (Amide group - I) around X 1064 nm and Y 1300 nm with the Lambda / Lambda derived spectra methods for protein detection. During the stages when the disease is developing, typically from day 3 to day 5, the plant's defense mechanisms are not as effective. This is especially true for the PB-1 variety of rice, which is highly susceptible to rice blast disease. Consequently, the proteins in the plant are adversely affected during this critical time. The spectral contour plot reveals the highly correlated spectral regions 1064 nm and Y 1300 nm associated with RB disease infection. Based on these spectral sensitivities, we developed new spectral disease indices for predicting different stages of disease emergence. The goal of this research is to lay the foundation for future UAV and satellite-based studies aimed at long-term monitoring of RB disease.

Keywords: rice blast, asymptomatic stage, spectral sensitivity, IR

Procedia PDF Downloads 85

Authors: O. Tovide, N. Jahed, N. Mohammed, C. E. Sunday, H. R. Makelane, R. F. Ajayi, K. M. Molapo, A. Tsegaye, M. Masikini, S. Mailu, A. Baleg, T. Waryo, P. G. Baker, E. I. Iwuoha

Abstract:

A graphenated–polyaniline (GR-PANI) nanocomposite sensor was constructed and used for the determination of anthracene. The direct electro-oxidation behavior of anthracene on the GR-PANI modified glassy carbon electrode (GCE) was used as the sensing principle. The results indicate thatthe response profile of the oxidation of anthracene on GR-PANI-modified GCE provides for the construction of sensor systems based onamperometric and potentiometric signal transductions. A dynamic linear range of 0.12- 100 µM anthracene and a detection limit of 0.044 µM anthracene were established for the sensor system.

Keywords: electrochemical sensors, environmental pollutants, graphenated-polymers, polyaromatic hydrocarbon

Procedia PDF Downloads 354

Authors: Mingyan Hong, Shuozhao Hou

Abstract:

Collaborative Strategic Learning (CSL) teaches students to use learning strategies while working cooperatively. Student strategies include the following steps: defining the learning task and purpose; conducting ongoing negotiation of the learning materials by deciding "click" (I get it and I can teach it – green card, I get it –yellow card) or "clunk" (I don't get it – red card) at the end of each learning unit; "getting the gist" of the most important parts of the learning materials; and "wrapping up" key ideas. Find out how to help students of mixed achievement levels apply learning strategies while learning content area in materials in small groups. The design of CSL is based on social-constructivism and Vygotsky’s best-known concept of the Zone of Proximal Development (ZPD). The definition of ZPD is the distance between the actual acquisition level as decided by individual problem solution case and the level of potential acquisition level, similar to Krashen (1980)’s i+1, as decided through the problem-solution case under the facilitator’s guidance, or in group work with other more capable members (Vygotsky, 1978). Vygotsky claimed that learners’ ideal learning environment is in the ZPD. An ideal teacher or more-knowledgable-other (MKO) should be able to recognize a learner’s ZPD and facilitates them to develop beyond it. Then the MKO is able to leave the support step by step until the learner can perform the task without aid. Steven Krashen (1980) proposed Input hypothesis including i+1 hypothesis. The input hypothesis models are the application of ZPD in second language acquisition and have been widely recognized until today. Krashen (2019)’s optimal language learning environment (2019) further developed the application of ZPD and added the component of strategic group learning. The strategic group learning is composed of desirable learning materials learners are motivated to learn and desirable group members who are more capable and are therefore able to offer meaningful input to the learners. Purpose-driven Collaborative Strategic Learning Model is a strategic integration of ZPD, i+1 hypothesis model, and Optimal Language Learning Environment Model. It is purpose driven to ensure group members are motivated. It is collaborative so that an optimal learning environment where meaningful input from meaningful conversation can be generated. It is strategic because facilitators in the model strategically assign each member a meaningful and collaborative role, e.g., team leader, technician, problem solver, appraiser, offer group learning instrument so that the learning process is structured, and integrate group learning and team building making sure holistic development of each participant. Using data collected from college year one and year two students’ English courses, this presentation will demonstrate how purpose-driven collaborative strategic learning model is implemented in the second/foreign language classroom, using the qualitative data from questionnaire and interview. Particular, this presentation will show how second/foreign language learners grow from functioning with facilitator or more capable peer’s aid to performing without aid. The implication of this research is that purpose-driven collaborative strategic learning model can be used not only in language learning, but also in any subject area.

Keywords: collaborative, strategic, optimal input, second language acquisition

Procedia PDF Downloads 125

Authors: B. R. Raut

Abstract:

The seismic performance of 20-storey benchmark building with semi-active dampers is investigated under various earthquake ground motions. The Semi-Active Variable Friction Dampers (SAVFD) and Magnetorheological Dampers (MR) are used in this study. A recently proposed predictive control algorithm is employed for SAVFD and a simple mechanical model based on a Bouc–Wen element with clipped optimal control algorithm is employed for MR damper. A parametric study is carried out to ascertain the optimum parameters of the semi-active controllers, which yields the minimum performance indices of controlled benchmark building. The effectiveness of dampers is studied in terms of the reduction in structural responses and performance criteria. To minimize the cost of the dampers, the optimal location of the damper, rather than providing the dampers at all floors, is also investigated. The semi-active dampers installed in benchmark building effectively reduces the earthquake-induced responses. Lesser number of dampers at appropriate locations also provides comparable response of benchmark building, thereby reducing cost of dampers significantly. The effectiveness of two semi-active devices in mitigating seismic responses is cross compared. Among two semi-active devices majority of the performance criteria of MR dampers are lower than SAVFD installed with benchmark building. Thus the performance of the MR dampers is far better than SAVFD in reducing displacement, drift, acceleration and base shear of mid to high-rise building against seismic forces.

Keywords: benchmark building, control strategy, input excitation, MR dampers, peak response, semi-active variable friction dampers

Procedia PDF Downloads 283

Authors: Dali Nikolaishvili, Nino Khareba, Mariam Tsitsagi

Abstract:

Tbilisi has been a capital of Georgia since the 5ᵗʰ century. City area was covered by forest in historical past. Nowadays the situation has been changing dramatically. Dozens of problems are caused by damages/destruction of green cover and solution, at one glance, seems to be uncomplicated (planting trees and creating green quarters), but on the other hand, according to the increasing tendency, the built up of areas still remains unsolved. Finding out the ways to overcome such obstacles is important even for protecting the health of society. Making of Retrospective cartography of the forest area of Tbilisi with use of GIS technology and remote sensing was the main aim of the research. Research about the dynamic of forest-cover in Tbilisi and its surroundings included the following steps: assessment of the dynamic of forest in Tbilisi and its surroundings. The survey was mainly based on the retrospective mapping method. Using of GIS technology, studying, comparing and identifying the narrative sources was the next step. And the last one was analyzed of the changes from the 80s to the present days on the basis of decryption of remotely sensed images. After creating a unified cartographic basis, the mapping and plans of different periods have been linked to this geodatabase. Data about green parks, individual old plants existing in the private yards and respondents' Information (according to a questionnaire created in advance) was added to the basic database, the general plan of Tbilisi and Scientific works as well. On the basis of analysis of historic, including cartographic sources, forest-cover maps for different periods of time were made. In addition, was made the catalog of individual green parks (location, area, typical composition, name and so on), which was the basis of creating several thematic maps. Areas with a high rate of green area degradation were identified. Several maps depicting the dynamics of forest cover of Tbilisi were created and analyzed. The methods of linking the data of the old cartographic sources to the modern basis were developed too, the result of which may be used in Urban Planning of Tbilisi. Understanding, perceiving and analyzing the real condition of green cover in Tbilisi and its problems, in turn, will help to take appropriate measures for the maintenance of ancient plants, to develop forests and to plan properly parks, squares, and recreational sites. Because the healthy environment is the main condition of human health and implies to the rational development of the city.

Keywords: catalogue of green area, GIS, historical cartography, cartography, remote sensing, Tbilisi

Procedia PDF Downloads 136

Authors: Samar Y. Al-Dabagh, Adawiya J. Haider, Mirvat D. Majed

Abstract:

Pure nanostructure TiO2 and thin films doped with transition metal Fe were prepared by pulsed laser deposition (PLD) on Si (111) substrate. The thin films structures were determined by X-ray diffraction (XRD). The morphology properties were determined from atomic force microscopy (AFM), which shows that the roughness increases when TiO2 is doped with Fe. Results show TiO2 doped with Fe metal thin films deposited on Si (111) substrate has maximum sensitivity to ethanol vapor at 10 mbar oxygen pressure than at 0.01 and 0.1 mbar with optimum operation temperature of 250°C.

Keywords: pulsed laser deposition (PLD), TiO2 doped thin films, nanostructure, gas sensor

Procedia PDF Downloads 378

Authors: Salem Alsanusi, Loubna Bentaher

Abstract:

Response Surface Methods (RSM) provide statistically validated predictive models that can then be manipulated for finding optimal process configurations. Variation transmitted to responses from poorly controlled process factors can be accounted for by the mathematical technique of propagation of error (POE), which facilitates ‘finding the flats’ on the surfaces generated by RSM. The dual response approach to RSM captures the standard deviation of the output as well as the average. It accounts for unknown sources of variation. Dual response plus propagation of error (POE) provides a more useful model of overall response variation. In our case, we implemented this technique in predicting compressive strength of concrete of 28 days in age. Since 28 days is quite time consuming, while it is important to ensure the quality control process. This paper investigates the potential of using design of experiments (DOE-RSM) to predict the compressive strength of concrete at 28th day. Data used for this study was carried out from experiment schemes at university of Benghazi, civil engineering department. A total of 114 sets of data were implemented. ACI mix design method was utilized for the mix design. No admixtures were used, only the main concrete mix constituents such as cement, coarse-aggregate, fine aggregate and water were utilized in all mixes. Different mix proportions of the ingredients and different water cement ratio were used. The proposed mathematical models are capable of predicting the required concrete compressive strength of concrete from early ages.

Keywords: mix proportioning, response surface methodology, compressive strength, optimal design

Procedia PDF Downloads 266

Authors: Martin Kittel, Alexander Roth

Abstract:

The continuous integration of variable renewable energy sources (VRE) in the power sector is required for decarbonizing the European economy. Power sectors become increasingly exposed to weather variability, as the availability of VRE, i.e., mainly wind and solar photovoltaic, is not persistent. Extreme events, e.g., long-lasting periods of scarce VRE availability (‘VRE droughts’), challenge the reliability of supply. Properly accounting for the severity of VRE droughts is crucial for designing a resilient renewable European power sector. Energy system modeling is used to identify such a design. Our analysis reveals the sensitivity of the optimal design of the European power sector towards VRE droughts. We analyze how VRE droughts impact optimal power sector investments, especially in generation and flexibility capacity. We draw upon work that systematically identifies VRE drought patterns in Europe in terms of frequency, duration, and seasonality, as well as the cross-regional and cross-technological correlation of most extreme drought periods. Based on their analysis, the authors provide a selection of relevant historical weather years representing different grades of VRE drought severity. These weather years will serve as input for the capacity expansion model for the European power sector used in this analysis (DIETER). We additionally conduct robustness checks varying policy-relevant assumptions on capacity expansion limits, interconnections, and level of sector coupling. Preliminary results illustrate how an imprudent selection of weather years may cause underestimating the severity of VRE droughts, flawing modeling insights concerning the need for flexibility. Sub-optimal European power sector designs vulnerable to extreme weather can result. Using relevant weather years that appropriately represent extreme weather events, our analysis identifies a resilient design of the European power sector. Although the scope of this work is limited to the European power sector, we are confident that our insights apply to other regions of the world with similar weather patterns. Many energy system studies still rely on one or a limited number of sometimes arbitrarily chosen weather years. We argue that the deliberate selection of relevant weather years is imperative for robust modeling results.

Keywords: energy systems, numerical optimization, variable renewable energy sources, energy drought, flexibility

Procedia PDF Downloads 71

Authors: M. A. Spielmann, L. Schebek

Abstract:

In order to reach the long-term national climate goals of the German government for the building sector, substantial energetic measures have to be executed. Historically, those measures were primarily energetic efficiency measures at the buildings’ shells. Advanced technologies for the on-site generation of heat (or other types of energy) often are not feasible at this small spatial scale of a single building. Therefore, the present approach uses the spatially larger dimension of a quarter. The main focus of the present paper is the long-term economic-ecological assessment of available decentralized heat-generating (CHP power plants and electrical heat pumps) technologies at the quarter level for the German unrefurbished residential buildings. Three distinct terms have to be described methodologically: i) Quarter approach, ii) Economic assessment, iii) Ecological assessment. The quarter approach is used to enable synergies and scaling effects over a single-building. For the present study, generic quarters that are differentiated according to significant parameters concerning their heat demand are used. The core differentiation of those quarters is made by the construction time period of the buildings. The economic assessment as the second crucial parameter is executed with the following structure: Full costs are quantized for each technology combination and quarter. The investment costs are analyzed on an annual basis and are modeled with the acquisition of debt. Annuity loans are assumed. Consequently, for each generic quarter, an optimal technology combination for decentralized heat generation is provided in each year of the temporal boundaries (2016-2050). The ecological assessment elaborates for each technology combination and each quarter a Life Cycle assessment. The measured impact category hereby is GWP 100. The technology combinations for heat production can be therefore compared against each other concerning their long-term climatic impacts. Core results of the approach can be differentiated to an economic and ecological dimension. With an annual resolution, the investment and running costs of different energetic technology combinations are quantified. For each quarter an optimal technology combination for local heat supply and/or energetic refurbishment of the buildings within the quarter is provided. Coherently to the economic assessment, the climatic impacts of the technology combinations are quantized and compared against each other.

Keywords: building sector, economic-ecological assessment, heat, LCA, quarter level

Procedia PDF Downloads 223

Authors: Hassan M. H. Mustafa

Abstract:

This piece of research addresses an interesting comparative analytical study. Which considers two concepts of diverse algorithmic computational intelligence approaches related tightly with Neural and Non-Neural Systems. The first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Besides a mouse’s trial during its movement inside figure of eight (8) maze, to reach an optimal solution for reconstruction problem. Conversely, second algorithmic intelligent approach originated from observed activities’ results for Non-Neural Ant Colony System (ACS). These results obtained after reaching an optimal solution while solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced systems. Finally, performance of both intelligent learning paradigms shown to be in agreement with learning convergence process searching for least mean square error LMS algorithm. While its application for training some Artificial Neural Network (ANN) models. Accordingly, adopted ANN modeling is a relevant and realistic tool to investigate observations and analyze performance for both selected computational intelligence (biological behavioral learning) systems.

Keywords: artificial neural network modeling, animal learning, ant colony system, traveling salesman problem, computational biology

Procedia PDF Downloads 469

Authors: Belal Mohamadi Kalesar, Raouf Hasanpour

Abstract:

Proper placement of Distributed Generation (DG) units such as wind turbine generators in distribution system are still very challenging issue for obtaining their maximum potential benefits because inappropriate placement may increase the system losses. This paper proposes Particle Swarm Optimization (PSO) technique for optimal placement of wind based DG (WDG) in the primary distribution system to reduce energy losses and voltage profile improvement with four different wind levels modeling in year duration. Also, wind turbine is modeled as a DFIG that will be operated at unity power factor and only one wind turbine tower will be considered to install at each bus of network. Finally, proposed method will be implemented on widely used 69 bus power distribution system in MATLAB software environment under four scenario (without, one, two and three WDG units) and for capability test of implemented program it is supposed that all buses of standard system can be candidate for WDG installing (large search space), though this program can consider predetermined number of candidate location in WDG placement to model financial limitation of project. Obtained results illustrate that wind speed increasing in some months will increase output power generated but this can increase / decrease power loss in some wind level, also results show that it is required about 3MW WDG capacity to install in different buses but when this is distributed in overall network (more number of WDG) it can cause better solution from point of view of power loss and voltage profile.

Keywords: wind turbine, DG placement, wind levels effect, PSO algorithm

Procedia PDF Downloads 446

Authors: Ebrahim Taherzadeh, Helmi Z. M. Shafri, Kaveh Shahi

Abstract:

One of the most important tasks in urban area remote sensing is detection of impervious surface (IS), such as building roof and roads. However, detection of IS in heterogeneous areas still remains as one of the most challenging works. In this study, detection of concrete roof using an object-oriented approach was proposed. A new rule-based classification was developed to detect concrete roof tile. The proposed rule-based classification was applied to WorldView-2 image. Results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images with 85% accuracy.

Keywords: object-based, roof material, concrete tile, WorldView-2

Procedia PDF Downloads 422

Authors: Yu Zhang, Mingxue Lang, Li Dong

Abstract:

The hundreds of years of slow succession of living environment in rural area is a crucial carrier of China’s long history of culture and national wisdom. In recent years, the space evolution of traditional rural settlements has been promoted by the intervention of tourism development, among which the public architecture and outdoor activity areas together served as the major places for villagers, and tourists’ social activities are an important characterization for settlement spatial evolution. Traditional public space upgrade and layout study of new public space can effectively promote the tourism industry development of traditional rural settlements. This article takes Qi County, one China Traditional Culture Village as the exemplification and uses the technology of Remote Sensing (RS), Geographic Information System (GIS) and Space Syntax, studies the evolution features of public space of tourism-oriented traditional rural settlements in four steps. First, acquire the 2003 and 2016 image data of Qi County, using the remote sensing application EDRAS8.6. Second, vectorize the basic maps of Qi County including its land use map with the application of ArcGIS 9.3 meanwhile, associating with architectural and site information concluded from field research. Third, analyze the accessibility and connectivity of the inner space of settlements using space syntax; run cross-correlation with the public space data of 2003 and 2016. Finally, summarize the evolution law of the public space of settlements; study the upgrade pattern of traditional public space and location plan for new public space. Major findings of this paper including: first, location layout of traditional public space has a larger association with the calculation results of space syntax and further confirmed the objective value of space syntax in expressing the space and social relations. Second, the intervention of tourism development generates remarkable impact on public space location of tradition rural settlements. Third, traditional public space produces the symbols of both strengthening and decline and forms a diversified upgrade pattern for the purpose of meeting the different tourism functional needs. Finally, space syntax provides an objective basis for location plan of new public space that meets the needs of tourism service. Tourism development has a significant impact on the evolution of public space of traditional rural settlements. Two types of public space, architecture, and site are both with changes seen from the perspective of quantity, location, dimension and function after the intervention of tourism development. Function upgrade of traditional public space and scientific layout of new public space are two important ways in achieving the goal of sustainable development of tourism-oriented traditional rural settlements.

Keywords: public space evolution, Qi county, space syntax, tourism oriented, traditional rural settlements

Procedia PDF Downloads 340