Search results for: Reynolds stress model

Authors: Maram Shahad Dana Anfal

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This research paper presents the design of a surveillance drone with computer-aided durability and model analyses that provides a cost-effective and efficient solution for various applications. The quadcopter's design is based on a lightweight and strong structure made of materials such as aluminum and titanium, which provide a durable structure for the quadcopter. The structure of this product and the computer-aided durability system are both designed to ensure frequent repairs or replacements, which will save time and money in the long run. Moreover, the study discusses the drone's ability to track, investigate, and deliver objects more quickly than traditional methods, makes it a highly efficient and cost-effective technology. In this paper, a comprehensive analysis of the quadcopter's operation dynamics and limitations is presented. In both simulation and experimental data, the computer-aided durability system and the drone's design demonstrate their effectiveness, highlighting the potential for a variety of applications, such as search and rescue missions, infrastructure monitoring, and agricultural operations. Also, the findings provide insights into possible areas for improvement in the design and operation of the drone. Ultimately, this paper presents a reliable and cost-effective solution for surveillance applications by designing a drone with computer-aided durability and modeling. With its potential to save time and money, increase reliability, and enhance safety, it is a promising technology for the future of surveillance drones. operation dynamic equations have been evaluated successfully for different flight conditions of a quadcopter. Also, CAE modeling techniques have been applied for the modal risk assessment at operating conditions.Stress analysis have been performed under the loadings of the worst-case combined motion flight conditions.

Keywords: drone, material, solidwork, hypermesh

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Authors: Yue Meng, Lingyun Wei

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In this paper, the coordination problem of a supply chain system composed of multiple retailers and manufacturers is studied under the background of the new retail supply chain. Taking a system composed of two retailers and one manufacturer as an example, this paper introduces an online store owned by the manufacturer to reflect the characteristics of the combination of online and offline new retail. Then, this paper gives the conditions that need to be satisfied to realize the coordination between retailers and manufacturers, such as the revenue sharing coefficient. The supply chain coordination model is compared with the newsboy model through a specific example. Finally, the conclusion is drawn that the profits of the coordinated supply chain and its members are better than the corresponding profits under the newsboy model; that is, the coordination of the supply chain is realized by using the revenue sharing contract and the transshipment fund mechanism.

Keywords: transshipment, coordination, multi-retailer, revenue-sharing contract

Procedia PDF Downloads 149

Authors: Avatharam Ganivada, Krishna Shah

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The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

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Authors: F. Demir

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Strategic Management is highly critical for all types of organizations. This paper examines maturity level of strategic management practices of public and private sector organizations in Turkey, and presents a conceptual model for assessing the maturity of strategic management in any organization. This research focuses on R&D intensive organizations (RDO) because it is claimed that such organizations are more innovative and innovation is a critical part of the model. The Strategic management maturity model (S-3M) is basically composed of six maturity levels with five different dimensions. Based on 63 organizations, the findings reveal that the average maturity of all organizations in the sample group is three out of five. It corresponds to the stage of ‘performed’. Results simply show that the majority of organizations from various industries and sectors implement strategic management activities; however, they experience multiple challenges to optimize strategic management processes and integrate organizational components with business strategies. Briefly, they struggle to become an innovative organization.

Keywords: strategic management maturity, innovation, developing countries, research and development

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Authors: Ahmad Ammar, Umar Khan Khattak, Muhammad Majid

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Empirically based lumped hydrologic models have an extensive track record of use for various watershed managements and flood related studies. This study focuses on the impacts of LULC change for 10 year period on the discharge in watershed using lumped model HEC-HMS. The Indus above Tarbela region acts as a source of the main flood events in the middle and lower portions of Indus because of the amount of rainfall and topographic setting of the region. The discharge pattern of the region is influenced by the LULC associated with it. In this study the Landsat TM images were used to do LULC analysis of the watershed. Satellite daily precipitation TRMM data was used as input rainfall. The input variables for model building in HEC-HMS were then calculated based on the GIS data collected and pre-processed in HEC-GeoHMS. SCS-CN was used as transform model, SCS unit hydrograph method was used as loss model and Muskingum was used as routing model. For discharge simulation years 2000 and 2010 were taken. HEC-HMS was calibrated for the year 2000 and then validated for 2010.The performance of the model was assessed through calibration and validation process and resulted R2=0.92 during calibration and validation. Relative Bias for the years 2000 was -9% and for2010 was -14%. The result shows that in 10 years the impact of LULC change on discharge has been negligible in the study area overall. One reason is that, the proportion of built-up area in the watershed, which is the main causative factor of change in discharge, is less than 1% of the total area. However, locally, the impact of development was found significant in built up area of Mansehra city. The analysis was done on Mansehra city sub-watershed with an area of about 16 km2 and has more than 13% built up area in 2010. The results showed that with an increase of 40% built-up area in the city from 2000 to 2010 the discharge values increased about 33 percent, indicating the impact of LULC change on discharge value.

Keywords: LULC change, HEC-HMS, Indus Above Tarbela, SCS-CN

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Alkaben Patel

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The proposed RP-HPLC method is easy, rapid, economical, precise and accurate stability indicating RP-HPLC method for simultaneous estimation of Astorvastatin and Methylcobalamine in their combined dosage form has been developed.The separation was achieved by LC-20 AT C18(250mm*4.6mm*2.6mm)Colum and water (pH 3.5): methanol 70:30 as mobile phase, at a flow rate of 1ml/min. wavelength of this dosage form is 215nm.The drug is related to stress condition of hydrolysis, oxidation, photolysis and thermal degradation.

Keywords: RP- HPLC, atorvastatin, methylcobalamine, method, development, validation

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Authors: Yang Xiong, Hua Cheng

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In this paper, for the basic problem of wireless sensor network topology control and deployment, the Roesser model in rectangular grid sensor networks is presented. In addition, a general constructive realization procedure will be proposed. The procedure enables a distributed implementation of linear systems on a sensor network. A non-trivial example is illustrated.

Keywords: grid sensor networks, Roesser model, state-space realization, multidimensional systems

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Authors: Swetha Priya Darshini Thammadi, Sateesh Kumar Pisini, Sanjay Kumar Shukla

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Source apportionment using Dispersion model depends primarily on the quality of Emission Inventory. In the present study, a CMB receptor model has been used to identify the sources of PM_2.5, while the AERMOD dispersion model has been used to account for missing sources of PM_2.5 in the Emission Inventory. A statistical approach has been developed to quantify the missing sources not considered in the Emission Inventory. The inventory of each grid was improved by adjusting emissions based on road lengths and deficit in measured and modelled concentrations. The results showed that in CMB analyses, fugitive sources - soil and road dust - contribute significantly to ambient PM_2.5 pollution. As a result, AERMOD significantly underestimated the ambient air concentration at most locations. The revised Emission Inventory showed a significant improvement in AERMOD performance which is evident through statistical tests.

Keywords: CMB, GIS, AERMOD, PM₂.₅, fugitive, emission inventory

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Authors: Pornsiri Kaewpradit, Chalisa Pourneaw

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Temperature control improvement of a membrane reactor with exothermic and reversible esterification reaction is studied in this work. It is well known that a batch membrane reactor requires different control strategies from a continuous one due to the fact that it is operated dynamically. Due to the effect of the operating temperature, the suitable control scheme has to be designed based reliable predictive model to achieve a desired objective. In the study, the optimization framework has been preliminary formulated in order to determine an optimal temperature trajectory for maximizing a desired product. In model predictive control scheme, a set of predictive models have been initially developed corresponding to the possible operating points of the system. The multiple predictive control moves have been further calculated on-line using the developed models corresponding to current operating point. It is obviously seen in the simulation results that the temperature control has been improved compared to the performance obtained by the conventional predictive controller. Further robustness tests have also been investigated in this study.

Keywords: model predictive control, batch reactor, temperature control, membrane reactor

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Authors: Titus G. Kassem, Izang A. Nyam

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A mathematical model is constructed to study the effect of predation on two competing species in which one of the competing species is a prey to the predator whilst the other species are not under predation. Conditions for the existence and stability of equilibrium solutions were determined. Numerical simulation results indicate the possibility of a stable coexistence of the three interacting species in form of stable oscillations under certain parameter values. We also noticed that under some certain parameter values, species under predation go into extinction.

Keywords: competition, predator-prey, species, ecology

Procedia PDF Downloads 282

Authors: Meghdad Payan, Kostas Senetakis, Arman Khoshghalb, Nasser Khalili

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Dynamic properties of soils, especially at the range of very small strains, are of particular interest in geotechnical engineering practice for characterization of the behavior of geo-structures subjected to a variety of stress states. This study reports on the small-strain dynamic properties of sand-silt mixtures with particular emphasis on the effect of non-plastic fines content on the small strain shear modulus (Gmax), Young’s Modulus (Emax), material damping (Ds,min) and Poisson’s Ratio (v). Several clean sands with a wide range of grain size characteristics and particle shape are mixed with variable percentages of a silica non-plastic silt as fines content. Prepared specimens of sand-silt mixtures at different initial void ratios are subjected to sequential torsional and flexural resonant column tests with elastic dynamic properties measured along an isotropic stress path up to 800 kPa. It is shown that while at low percentages of fines content, there is a significant difference between the dynamic properties of the various samples due to the different characteristics of the sand portion of the mixtures, this variance diminishes as the fines content increases and the soil behavior becomes mainly silt-dominant, rendering no significant influence of sand properties on the elastic dynamic parameters. Indeed, beyond a specific portion of fines content, around 20% to 30% typically denoted as threshold fines content, silt is controlling the behavior of the mixture. Using the experimental results, new expressions for the prediction of small-strain dynamic properties of sand-silt mixtures are developed accounting for the percentage of silt and the characteristics of the sand portion. These expressions are general in nature and are capable of evaluating the elastic dynamic properties of sand-silt mixtures with any types of parent sand in the whole range of silt percentage. The inefficiency of skeleton void ratio concept in the estimation of small-strain stiffness of sand-silt mixtures is also illustrated.

Keywords: damping ratio, Poisson’s ratio, resonant column, sand-silt mixture, shear modulus, Young’s modulus

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Authors: Giselle Maggie Fer Castañeda, Diego Iván González

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The objective of this work was to study the autoshaped choice behavior in the Donahoe, Burgos and Palmer (DBP) neural network model and analyze it under the matching law. Autoshaped choice can be viewed as a form of economic behavior defined as the preference between alternatives according to their relative outcomes. The Donahoe, Burgos and Palmer (DBP) model is a connectionist proposal that unifies operant and Pavlovian conditioning. This model has been used for more than three decades as a neurobehavioral explanation of conditioning phenomena, as well as a generator of predictions suitable for experimental testing with non-human animals and humans. The study consisted of different simulations in which, in each one, a ratio of reinforcement was established for two alternatives, and the responses (i.e., activations) in each of them were measured. Choice studies with animals have demonstrated that the data generally conform closely to the generalized matching law equation, which states that the response ratio equals proportionally to the reinforcement ratio; therefore, it was expected to find similar results with the neural networks of the Donahoe, Burgos and Palmer (DBP) model since these networks have simulated and predicted various conditioning phenomena. The results were analyzed by the generalized matching law equation, and it was observed that under some contingencies, the data from the networks adjusted approximately to what was established by the equation. Implications and limitations are discussed.

Keywords: matching law, neural networks, computational models, behavioral sciences

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Authors: Pakawhat Khumkhreung, Yottana Khunatorn

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The flow pattern inside rectangular intake air duct of 300 MW lignite coal-fired power plant is investigated in order to analyze and reduce overall inlet system pressure drop. The system consists of the 45-degree inlet elbow, the flow instrument, the 90-degree mitered elbow and fans, respectively. The energy loss in each section can be determined by Bernoulli’s equation and ASHRAE standard table. Hence, computational fluid dynamics (CFD) is used in this study based on Navier-Stroke equation and the standard k-epsilon turbulence modeling. Input boundary condition is 175 kg/s mass flow rate inside the 11-m² cross sectional duct. According to the inlet air flow rate, the Reynolds number of airstream is 2.7x10⁶ (based on the hydraulic duct diameter), thus the flow behavior is turbulence. The numerical results are validated with the real operation data. It is found that the numerical result agrees well with the operating data, and dominant loss occurs at the flow rate measurement device. Normally, the air flow rate is measured by the airfoil and it gets high pressure drop inside the duct. To overcome this problem, the airfoil is planned to be replaced with the other type measuring instrument, such as the average pitot tube which generates low pressure drop of airstream. The numerical result in case of average pitot tube shows that the pressure drop inside the inlet airstream duct is decreased significantly. It should be noted that the energy consumption of inlet air system is reduced too.

Keywords: airfoil, average pitot tube, combustion air, CFD, pressure drop, rectangular duct

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Authors: Nadia Adnan, Muhammad Mohsin Raza, Latha Ravindran

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Based on the principles above, the study presents an economic model of food waste for consumers, intermediaries, and producers. We discriminate between purchasing and selling, purchases versus customers consumption, and gross output versus sales for each intermediary. To compensate for waste at each level of the supply chain, agents must charge higher sales prices. The research model can produce more accurate predictions about how actions (public regulations or private efforts) to reduce food waste impact markets, including indirect (cascading) effects. With a formal model, researchers demonstrate the uniqueness of these interaction effects and simulate an empirical model calibrated to market characteristics and waste rates in Saudi Arabia. Researchers demonstrate that the effects of waste reduction differ per commodity, depending on supply and demand elasticities, degree of openness to international commerce, and the beginning rates of food loss and waste at each level of the value chain. Because of the consequential effects related to the supply chain, initiatives to minimize food waste will be strengthened in some circumstances and partially countered in others.

Keywords: food loss, food waste, supply chain management, Saudi Arabia, food supply

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Authors: Tai-Yue Wang, Yi-Ho Chen

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In this study, we investigate a two-echelon supply chain with two suppliers and three retailers among which one retailer dominates other retailers. A price competition demand function is used to model this dominant retailer, which is leading market. The promotion strategies and negotiation schemes are integrated to form decision-making models under different scenarios. These models are then formulated into different mathematical programming models. The decision variables such as promotional costs, retailer prices, wholesale price, and order quantity are included in these models. At last, the distributions of promotion costs under different cost allocation strategies are discussed. Finally, an empirical example used to validate our models. The results from this empirical example show that the profit model will create the largest profit for the supply chain but with different profit-sharing results. At the same time, the more risk a member can take, the more profits are distributed to that member in the utility model.

Keywords: supply chain, price promotion, mathematical models, dominant retailer

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Authors: András Szekrényes

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Delamination is one of the major failure modes in laminated composite structures. Delamination tips are mostly captured by spatial numerical models in order to predict crack growth. This paper presents some mechanical models of delaminated composite shells based on shallow shell theories. The mechanical fields are based on a third-order displacement field in terms of the through-thickness coordinate of the laminated shell. The undelaminated and delaminated parts are captured by separate models and the continuity and boundary conditions are also formulated in a general way providing a large size boundary value problem. The system of differential equations is solved by the state space method for an elliptic delaminated shell having simply supported edges. The comparison of the proposed and a numerical model indicates that the primary indicator of the model is the deflection, the secondary is the widthwise distribution of the energy release rate. The model is promising and suitable to determine accurately the J-integral distribution along the delamination front. Based on the proposed model it is also possible to develop finite elements which are able to replace the computationally expensive spatial models of delaminated structures.

Keywords: J-integral, levy method, third-order shell theory, state space solution

Procedia PDF Downloads 137

Authors: Andi Darmawan, Dewi Retno Sari Saputro, Purnami Widyaningsih

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Diabetes mellitus (DM) is a chronic disease in human that occurred if pancreas cannot produce enough of insulin hormone or the body uses ineffectively insulin hormone which causes increasing level of glucose in the blood, or it was called hyperglycemia. In Indonesia, DM is a serious disease on health because it can cause blindness, kidney disease, diabetic feet (gangrene), and stroke. The type of DM criteria can also be divided based on the main causes; they are DM type 1, type 2, and gestational. Diabetes type 1 or previously known as insulin-independent diabetes is due to a lack of production of insulin hormone. Diabetes type 2 or previously known as non-insulin dependent diabetes is due to ineffective use of insulin while gestational diabetes is a hyperglycemia that found during pregnancy. The most one type commonly found in patient is DM type 2. The main factors of this disease are genetic (A) and life style (E). Those disease with 2 factors can be constructed with additive genetic and unique environment (AE) model. In this article was discussed parameter estimation of AE model using Bayesian method and the inheritance character simulation on parent-offspring. On the AE model, there are response variable, predictor variables, and parameters were capable of representing the number of population on research. The population can be measured through a taken random sample. The response and predictor variables can be determined by sample while the parameters are unknown, so it was required to estimate the parameters based on the sample. Estimation of AE model parameters was obtained based on a joint posterior distribution. The simulation was conducted to get the value of genetic variance and life style variance. The results of simulation are 0.3600 for genetic variance and 0.0899 for life style variance. Therefore, the variance of genetic factor in DM type 2 is greater than life style.

Keywords: AE model, Bayesian method, diabetes mellitus type 2, genetic, life style

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Authors: V. Pourmostaghimi, M. Zadshakoyan

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Efficiency and productivity of the finish hard turning can be enhanced impressively by utilizing accurate predictive models for cutting tool wear. However, the ability of genetic programming in presenting an accurate analytical model is a notable characteristic which makes it more applicable than other predictive modeling methods. In this paper, the genetic equation for modeling of tool flank wear is developed with the use of the experimentally measured flank wear values and genetic programming during finish turning of hardened AISI D2. Series of tests were conducted over a range of cutting parameters and the values of tool flank wear were measured. On the basis of obtained results, genetic model presenting connection between cutting parameters and tool flank wear were extracted. The accuracy of the genetically obtained model was assessed by using two statistical measures, which were root mean square error (RMSE) and coefficient of determination (R²). Evaluation results revealed that presented genetic model predicted flank wear over the study area accurately (R² = 0.9902 and RMSE = 0.0102). These results allow concluding that the proposed genetic equation corresponds well with experimental data and can be implemented in real industrial applications.

Keywords: cutting parameters, flank wear, genetic programming, hard turning

Procedia PDF Downloads 183

Authors: G. Wojcik, J. Gindlhuber, A. Syarif, K. Hoetzenecker, P. Bohm, P. Vesely, V. Biasin, G. Kwapiszewska

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Pulmonary fibrosis is a rare disease where uncontrolled wound healing processes damage the lung structure. Intensive changes within the extracellular matrix (ECM) and its interaction with fibroblasts have a major role in pulmonary fibrosis development. Among others, collagen is one of the main components of the ECM, and it is important for lung structure. In IPF, constant production of collagen by fibroblast, through TGFβ1-SMAD2/3 pathways, leads to an uncontrolled deposition of matrix and hence lung remodeling. Abnormal changes in lipid production, alterations in fatty acids (FAs) metabolism, enhanced oxidative stress, and lipid peroxidation in fibrotic lung and fibrotic fibroblasts have been reported; however, the interplay between the collagen and lipids is not yet established. One of the FAs influx regulators is Angiopoietin-like 4 (ANGPTL4), which inhibits lipoprotein lipase work, decreasing the availability of FAs. We hypothesized that altered lipid composition or availability could have the capability to influence the phenotype of different fibroblast populations in the lung and hence influence lung fibrosis. To prove our hypothesis, we aim to investigate lipids and their influence on human, animal, and in vitro levels. In the bleomycin model, treatment with the well-known metabolic drugs Rosiglitazone or Metformin significantly lower collagen production. Similar results were noticed in ANGPTL4 KO animals, where the KO of ANGPTL4 leads to an increase of FAs availability and lower collagen deposition after the bleomycin challenge. Currently, we study the treatment of different FAs on human lung para fibroblasts (hPF) isolated from donors. To understand the lipid composition, we are collecting human lung tissue from donors and pulmonary fibrosis patients for Liquid chromatography-mass spectrometry. In conclusion, our results suggest the lipid influence on collagen deposition during lung fibrosis, but further research needs to be conducted to understand the matter of this relationship.

Keywords: collagen, fibroblasts, lipidomics, lung, pulmonary fibrosis

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Authors: Gleda Kutrolli, Maksi Kutrolli, Etjon Meco

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SARS-CoV-2 virus is currently one of the most infectious pathogens for humans. It started in China at the end of 2019 and now it is spread in all over the world. The origin and diffusion of the SARS-CoV-2 epidemic, is analysed based on the discussion of viral phylogeny theory. With the aim of understanding the spread of infection in the affected countries, it is crucial to modelize the spread of the virus and simulate its activity. In this paper, the prediction of coronavirus outbreak is done by using SIR model without vital dynamics, applying different numerical technique solving ordinary differential equations (ODEs). We find out that ABM and MRT methods perform better than other techniques and that the activity of the virus will decrease in April but it never cease (for some time the activity will remain low) and the next cycle will start in the middle July 2020 for Norway and Denmark, and October 2020 for Sweden, and September for Finland.

Keywords: forecasting, ordinary differential equations, SARS-COV-2 epidemic, SIR model

Procedia PDF Downloads 155

Authors: Muhammad Ashfaq, Muhammad Saleem Haider, Muhammad Ali, Muhammad Sajjad, Amna Ali, Urooj Mubashar

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Phenotypic diversity was confirmed by measuring different morphological traits i.e. seed traits (seed length, seed width, seed thickness, seed length-width ratio, 1000 grain weight) and root-shoot traits (shoot length, root length, shoot fresh weight, root fresh weight, root-shoot ratio, root numbers and root thickness). Variance and association study of desirable traits determine the genotypic differences among the rice germplasm. All the traits showed significant differences among the genotypes. The traits were studied in Randomized complete block design (RCBD) at different water levels. Some traits showed positive correlation with each other and beneficial for increasing the yield and production of the crop. Seed thickness has positive correlation with seed length and seed width (r= 0.104**, r=0.246**). On the other hand, various root shoot traits showed positive highly significant association at different water levels i.e. root length, fresh root weight, root thickness, shoot thickness and root numbers. Our main focus to study the performance/correlation of root shoots traits under stress condition. Fresh root weight, shoot thickness and root numbers showed positive significant association with shoot length, root length, fresh root and shoot weight (r=0.2530**, r=0.2891**, r=0.4626**, r=0.4515**, r=0.5781**, r=0.7164**, r=0.0603**, r= 0.5570**, r=0.5824**). Long root length genotypes favors and suitable for drought stress conditions and screening of diverse genotypes for the further development of new plant material that performing well under different environmental conditions. After screening genetic diversity of potential rice, lines were studied to check the polymorphism by using some SSR markers. DNA was extracted, and PCR analyses were done to study PIC values and allelic diversity of the genotypes. The main objective of this study is to screen out the genotypes on the basis of various genotypic and phenotypic traits.

Keywords: rice, morphological traits, association, germplasm, genetic diversity, water levels, variation

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Authors: Sanchay Vaidya, Sourabh Gupta, Gouresh Singhal

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There are various modes of transport in metro cities in India, auto-rickshaws being one of them. Auto-rickshaws provide connectivity to all the places in the city offering last mile connectivity. Among all the modes of transport, the auto-rickshaw industry is the most unorganized and inefficient. Although unions exist in different cities they aren’t good enough to cope up with the upcoming advancements in the field of technology. An introduction of simple technology in this field may do wonder and help increase the revenues. This paper aims to organize this segment under a single umbrella using GPS devices and mobile phones. The paper includes surveys of about 300 auto-rickshaw drivers and 1000 plus commuters across 6 metro cities in India. Carrying out research and analysis provides a base for the development of this model and implementation of this innovative technique, which is discussed in this paper in detail with ample emphasis given on the implementation of this model.

Keywords: auto-rickshaws, business model, GPS device, mobile application

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Authors: Adelia Desi Agnesita

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The advent of a new disease called covid-19 made many major changes in the world, one of which is the process of learning and teaching. Learning formerly offline but now is done online, which makes students need adaptation to the learning process. The covid-19 pandemic that occurs almost worldwide causes activities that involve many people to be avoided, one of which is learning to teach. In Indonesia, since March 2020, the process of college learning is turning into online/ long-distance learning. It's to prevent the spread of the covid-19. Student online learning presents some of the obstacles to poor signals, many of the tasks, lack of focus, difficulty sleeping, and resulting stress.

Keywords: learning, online, covid-19, pandemic

Procedia PDF Downloads 222

Authors: M. Brandt, A. Peniak, J. Makarovič, P. Rafajdus

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This paper deals with a novel approach of power transformers diagnostics. This approach identifies the exact location and the range of a fault in the transformer and helps to reduce operation costs related to handling of the faulty transformer, its disassembly and repair. The advantage of the approach is a possibility to simulate healthy transformer and also all faults, which can occur in transformer during its operation without its disassembling, which is very expensive in practice. The approach is based on creating frequency dependent impedance of the transformer by sweep frequency response analysis measurements and by 3D FE parametrical modeling of the fault in the transformer. The parameters of the 3D FE model are the position and the range of the axial short circuit. Then, by comparing the frequency dependent impedances of the parametrical models with the measured ones, the location and the range of the fault is identified. The approach was tested on a real transformer and showed high coincidence between the real fault and the simulated one.

Keywords: transformer, parametrical model of transformer, fault, sweep frequency response analysis, finite element method

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Authors: M. Kiran Reddy, K. Sreenivasa Rao

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The conventional Hidden Markov Model (HMM)-based speech synthesis system (HTS) uses only a pulse excitation model, which significantly differs from natural excitation signal. Hence, buzziness can be perceived in the speech generated using HTS. This paper proposes an efficient excitation modeling method that can significantly reduce the buzziness, and improve the quality of HMM-based speech synthesis. The proposed approach models the pitch-synchronous residual frames extracted from the residual excitation signal. Each pitch synchronous residual frame is parameterized using 30 wavelet coefficients. These 30 wavelet coefficients are found to accurately capture the perceptually important information present in the residual waveform. In synthesis phase, the residual frames are reconstructed from the generated wavelet coefficients and are pitch-synchronously overlap-added to generate the excitation signal. The proposed excitation modeling method is integrated into HMM-based speech synthesis system. Evaluation results indicate that the speech synthesized by the proposed excitation model is significantly better than the speech generated using state-of-the-art excitation modeling methods.

Keywords: excitation modeling, hidden Markov models, pitch-synchronous frames, speech synthesis, wavelet coefficients

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Authors: Hsiao-Chien Tsai, Yu-Pin Chen, Ruei-Ming Chen

Abstract:

Introduction: Osteoarthritis (OA) is characterized by joint destruction and causes chronic disability. One of the prominent symptoms is pain. Alleviating the pain is necessary and urgent for the therapy of OA patients. However, currently, understanding the mechanisms that drive OA-induced pain remains challenging, which hampers the optimistic management of pain in OA patients. Semaphorin 4D (Sema4D) participates in axon guidance pathway and bone remodeling, thus, may play a role in the regulation of pain in OA. In this study, we have established a rat model of OA to find out the mechanisms of OA-induced pain and to deliberate the roles of Sema4D. Methods: Behavioral changes and the pro-inflammatory cytokines (IL-1β, TNF-α, and IL-17) associated with pain were measured during the development of OA. Sema4D expression in cartilage and synovial membrane at 1, 4, and 12 weeks after inducing OA was analyzed. To assess if Sema4D is related to the neurogenesis in OA as an axon repellant, we analyzed the expression of PGP9.5 as well. Results: Synovitis and cartilage degradation were evident histologically during the development of OA. Mechanical hyperalgesia was most severe at week 1, then persisted thereafter. It was associated with stress coping strategies. Similar to the pain behavioral results, levels of IL-1β and TNF-α in synovial lavage fluid were significantly elevated in the OA group at weeks 1 and 4, respectively. Sema4D expression in cartilage and the synovial membrane was also enhanced in the OA group and was correlated with pain and pro-inflammatory cytokines. The marker of neurogenesis, PGP9.5, was also enhanced during the development of OA. Discussion: OA induced mechanical hyperalgesia, which might be through upregulating IL-1β/TNF-α-mediated Sema4D expressions. If anti-Sema4D treatment could reduce OA-induced mechanical hyperalgesia and prevent the subsequent progression of OA needs to be further investigated. Significance: OA can induce mechanical hyperalgesia through upregulation of IL-1β/TNF-α-mediated Sema4D and PGP9.5 expressions. And the upregulation of Sema4D may indicate the severity or active status of OA and OA-induced pain.

Keywords: traumatic osteoarthritis, mechanical hyperalgesia, Sema4D, inflammatory cytokines

Procedia PDF Downloads 83

Authors: Ali Bakari Mohammed

Abstract:

Transitioning is a continuous process of radical change in a society which involves co-evolution of institutional, technological, socio-cultural, and ecological developments at different scales and levels. Transition management model is a methodology that influences structural change of complex systems over a period (0-30 years) by experimenting and implementing new techniques. A transition management in the context of groundwater is a radical change from the current operate and control system to a next generation integrated and sustainable system that takes into account quality protection and sustained supply into the future. This study evaluates the transition management model in adopting it as a viable tool for the attainment of sustainable groundwater management. The outcome of the evaluation shows that there are three levels (strategic, tactical and operational) of operating the transition management model. At the strategic level, long-term goals for sustainable groundwater management are formulated, at the tactical level activities such as inter institutional networking, negotiation, planning and financing are carried out, and at the operational level, transition experiments and strategic niche management are carried out at the societal level. Overall, different actors and set of activities are required to partake at each management level. The outcome of this paper will provide basis for the implementation of the Sustainable Development Goal (SDG) 6 in Nigeria.

Keywords: transition management, groundwater, sustainable management, tool, Nigeria

Procedia PDF Downloads 274

Authors: Gopal Lamichhane, Biswash Sapkota, Grinsun Sharma, Mahendra Adhikari

Abstract:

Urolithiasis is a condition in which insoluble or less soluble salts like oxalate, phosphate etc. precipitate in urinary tract and causes obstruction in ureter resulting renal colic or sometimes haematuria. It is the third most common disorder of urinary tract affecting nearly 2% of world’s population. Poor urinary drainage, microbial infection, oxalate and calcium containing diet, calciferol, hyperparathyroidism, cysteine in urine, gout, dysfunction of intestine, drought environment, lifestyle, exercise, stress etc. are risk factors for urolithiasis. Wide ranges of treatments are available in allopathic system of medicine but reoccurrence is unpreventable even with the surgical removal of stone or lithotripsy. So, people prefer alternative medicinal systems such as Unani, homeopathic, ayurvedic etc. systems of medicine due to their fewer side effects over allopathic counterpart. Different plants based ethnomedicines are being well established by their continuous effective use in human since long time in treatment of urinary problem. Many studies have scientifically proved those ethnomedicines for antiurolithiatic effect in animal and in vitro model. Plant-based remedies were found to be therapeutically effective for both prevention as well as cure of calcium oxalate urolithiasis. Plants were known to show these effects through a combination of many effects such as antioxidant, diuretic, hypocalciuric, urine alkalinizing effect in them. Berberine, triterpenoids, lupeol are the phytochemicals established for antiurolithiatic effect. Hence, plant-based medicine can be the effective herbal alternative as well as means of discovery of novel drug molecule for curing urolithiatic disorder and should be focused on further research to discover their value in coming future.

Keywords: urolithiasis, herbal medicine, ethnomedicine, kidney stone, calcium oxalate

Procedia PDF Downloads 276

Authors: Shivahari Revathi Venkateswaran

Abstract:

Segmenting customers plays a significant role in churn prediction. It helps the marketing team with proactive and reactive customer retention. For the reactive retention, the retention team reaches out to customers who already showed intent to disconnect by giving some special offers. When coming to proactive retention, the marketing team uses churn prediction model, which ranks each customer from rank 1 to 100, where 1 being more risk to churn/disconnect (high ranks have high propensity to churn). The churn prediction model is built by using XGBoost model. However, with the churn rank, the marketing team can only reach out to the customers based on their individual ranks. To profile different groups of customers and to frame different marketing strategies for targeted groups of customers are not possible with the churn ranks. For this, the customers must be grouped in different segments based on their profiles, like demographics and other non-controllable attributes. This helps the marketing team to frame different offer groups for the targeted audience and prevent them from disconnecting (proactive retention). For segmentation, machine learning approaches like k-mean clustering will not form unique customer segments that have customers with same attributes. This paper finds an alternate approach to find all the combination of unique segments that can be formed from the user attributes and then finds the segments who have uplift (churn rate higher than the baseline churn rate). For this, search algorithms like fast search and recursive search are used. Further, for each segment, all customers can be targeted using individual churn ranks from the churn prediction model. Finally, a UI (User Interface) is developed for the marketing team to interactively search for the meaningful segments that are formed and target the right set of audience for future marketing campaigns and prevent them from disconnecting.

Keywords: churn prediction modeling, XGBoost model, uplift segments, proactive marketing, search algorithms, retention, k-mean clustering

Procedia PDF Downloads 74