Search results for: optimizing crops
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1497

Search results for: optimizing crops

1047 Iron(III)-Tosylate Doped PEDOT and PEG: A Nanoscale Conductivity Study of an Electrochemical System with Biosensing Applications

Authors: Giulio Rosati, Luciano Sappia, Rossana Madrid, Noemi Rozlòsnik

Abstract:

The addition of PEG of different molecular weights has important effects on the physical, electrical and electrochemical properties of iron(III)-tosylate doped PEDOT. This particular polymer can be easily spin coated over plastic discs, optimizing thickness and uniformity of the PEDOT-PEG films. The conductivity and morphological analysis of the hybrid PEDOT-PEG polymer by 4-point probe (4PP), 12-point probe (12PP), and conductive AFM (C-AFM) show strong effects of the PEG doping. Moreover, the conductive films kinetics at the nanoscale, in response to different bias voltages, change radically depending on the PEG molecular weight. The hybrid conductive films show also interesting electrochemical properties, making the PEDOT PEG doping appealing for biosensing applications both for EIS-based and amperometric affinity/catalytic biosensors.

Keywords: atomic force microscopy, biosensors, four-point probe, nano-films, PEDOT

Procedia PDF Downloads 315
1046 Using Greywolf Optimized Machine Learning Algorithms to Improve Accuracy for Predicting Hospital Readmission for Diabetes

Authors: Vincent Liu

Abstract:

Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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1045 Leadership Dynamics and Teacher Engagement in Greek Education

Authors: Vasileios Floros

Abstract:

This article delves into the intricate interplay between leadership styles and teacher satisfaction within the Greek educational framework, underscoring the pivotal role of school leadership in shaping educational success and fostering a conducive school culture. Through a comprehensive analysis, the study explores various leadership theories, the psychological contract between teachers and leaders, and the impact of leadership on teacher job satisfaction and group dynamics within educational institutions. It highlights how leadership efficacy can significantly influence the organizational climate, teacher motivation, and, ultimately, educational outcomes. The findings suggest that effective leadership, characterized by a deep understanding of teacher psychology, thoughtful engagement with the school culture, and strategic application of leadership styles, can lead to heightened teacher satisfaction and enhanced educational performance. This research offers valuable insights for educational policymakers, school leaders, and the broader academic community interested in optimizing leadership practices to foster an enriching educational environment in Greece.

Keywords: educational leadership, teacher satisfaction, school culture, leadership styles, Greek education

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1044 Effect of Entomopathogenic Fungi on the Food Consumption of Acrididae Species

Authors: S. Kumar, R. Sultana

Abstract:

This study was conducted to evaluate the effect of Aspergillus species on acridid populations which are major agricultural pests of rice, sugarcane, wheat, maize and fodder crops in Pakistan. Three and replicates i.e. Aspergillus flavus, A. fumigatus and A. niger, excluding the control, were held under laboratory conditions. It was observed that consumption faecal production of acridids was significantly reduced after the pathogenic application of Aspergillus. In the control replicate, the mortality ratio for stage (N4-N6) was maximum on day 2nd i.e. [F10.7 = 18.33, P < 0.05] followed by [F4.20 = 07.85, P < 0.05] and [F3.77 = 06.11, P < 0.05] on 4th and 3rd day, respectively. Similarly, it was a minimum i.e. [F0.48 = 84.65, P < 0.05] on the 1st day. It was also noted that faecal production of Acridid nymphs was not significantly affected when treated with conidial concentration in H2O formulation; however, it was significantly reduced after the contamination with conidial concentration in oil. The high morality of acridids after contamination of Aspergillus supports their use as bio-control agent for reducing pest population. The present study recommends that exploration and screening must be conducted to provide additional pathogens for evaluation as potential biological control against grasshoppers and locusts.

Keywords: acridid, agriculture, formulation, grasshoppers

Procedia PDF Downloads 231
1043 Optimal Cropping Pattern in an Irrigation Project: A Hybrid Model of Artificial Neural Network and Modified Simplex Algorithm

Authors: Safayat Ali Shaikh

Abstract:

Software has been developed for optimal cropping pattern in an irrigation project considering land constraint, water availability constraint and pick up flow constraint using modified Simplex Algorithm. Artificial Neural Network Models (ANN) have been developed to predict rainfall. AR (1) model used to generate 1000 years rainfall data to train the ANN. Simulation has been done with expected rainfall data. Eight number crops and three types of soil class have been considered for optimization model. Area under each crop and each soil class have been quantified using Modified Simplex Algorithm to get optimum net return. Efficacy of the software has been tested using data of large irrigation project in India.

Keywords: artificial neural network, large irrigation project, modified simplex algorithm, optimal cropping pattern

Procedia PDF Downloads 179
1042 Design of a Telemetry, Tracking, and Command Radio-Frequency Receiver for Small Satellites Based on Commercial Off-The-Shelf Components

Authors: A. Lovascio, A. D’Orazio, V. Centonze

Abstract:

From several years till now the aerospace industry is developing more and more small satellites for Low-Earth Orbit (LEO) missions. Such satellites have a low cost of making and launching since they have a size and weight smaller than other types of satellites. However, because of size limitations, small satellites need integrated electronic equipment based on digital logic. Moreover, the LEOs require telecommunication modules with high throughput to transmit to earth a big amount of data in a short time. In order to meet such requirements, in this paper we propose a Telemetry, Tracking & Command module optimized through the use of the Commercial Off-The-Shelf components. The proposed approach exploits the major flexibility offered by these components in reducing costs and optimizing the performance. The method has been applied in detail for the design of the front-end receiver, which has a low noise figure (1.5 dB) and DC power consumption (smaller than 2 W). Such a performance is particularly attractive since it allows fulfilling the energy budget stringent constraints that are typical for LEO small platforms.

Keywords: COTS, LEO, small-satellite, TT&C

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1041 3D Numerical Studies on External Aerodynamics of a Flying Car

Authors: Sasitharan Ambicapathy, J. Vignesh, P. Sivaraj, Godfrey Derek Sams, K. Sabarinath, V. R. Sanal Kumar

Abstract:

The external flow simulation of a flying car at take off phase is a daunting task owing to the fact that the prediction of the transient unsteady flow features during its deployment phase is very complex. In this paper 3D numerical simulations of external flow of Ferrari F430 proposed flying car with different NACA 9618 rectangular wings have been carried. Additionally, the aerodynamics characteristics have been generated for optimizing its geometry for achieving the minimum take off velocity with better overall performance in both road and air. The three-dimensional standard k-omega turbulence model has been used for capturing the intrinsic flow physics during the take off phase. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier-Stokes equations is employed. Through the detailed parametric analytical studies we have conjectured that Ferrari F430 flying car facilitated with high wings having three different deployment histories during the take off phase is the best choice for accomplishing its better performance for the commercial applications.

Keywords: aerodynamics of flying car, air taxi, negative lift, roadable airplane

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1040 Optimal Hedging of a Portfolio of European Options in an Extended Binomial Model under Proportional Transaction Costs

Authors: Norm Josephy, Lucy Kimball, Victoria Steblovskaya

Abstract:

Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data.

Keywords: extended binomial model, non-self-financing hedging, optimization, proportional transaction costs

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1039 Approximation of Convex Set by Compactly Semidefinite Representable Set

Authors: Anusuya Ghosh, Vishnu Narayanan

Abstract:

The approximation of convex set by semidefinite representable set plays an important role in semidefinite programming, especially in modern convex optimization. To optimize a linear function over a convex set is a hard problem. But optimizing the linear function over the semidefinite representable set which approximates the convex set is easy to solve as there exists numerous efficient algorithms to solve semidefinite programming problems. So, our approximation technique is significant in optimization. We develop a technique to approximate any closed convex set, say K by compactly semidefinite representable set. Further we prove that there exists a sequence of compactly semidefinite representable sets which give tighter approximation of the closed convex set, K gradually. We discuss about the convergence of the sequence of compactly semidefinite representable sets to closed convex set K. The recession cone of K and the recession cone of the compactly semidefinite representable set are equal. So, we say that the sequence of compactly semidefinite representable sets converge strongly to the closed convex set. Thus, this approximation technique is very useful development in semidefinite programming.

Keywords: semidefinite programming, semidefinite representable set, compactly semidefinite representable set, approximation

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1038 Hydraulic Analysis of Irrigation Approach Channel Using HEC-RAS Model

Authors: Muluegziabher Semagne Mekonnen

Abstract:

This study was intended to show the irrigation water requirements and evaluation of canal hydraulics steady state conditions to improve on scheme performance of the Meki-Ziway irrigation project. The methodology used was the CROPWAT 8.0 model to estimate the irrigation water requirements of five major crops irrigated in the study area. The results showed that for the whole existing and potential irrigation development area of 2000 ha and 2599 ha, crop water requirements were 3,339,200 and 4,339,090.4 m³, respectively. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. In this study Hydraulic Analysis of Irrigation Canals Using HEC-RAS Model was conducted in Meki-Ziway Irrigation Scheme. The HEC-RAS model was tested in terms of error estimation and used to determine canal capacity potential.

Keywords: HEC-RAS, irrigation, hydraulic. canal reach, capacity

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1037 Detection of Antibiotic Resistance Genes and Antibiotic Residues in Plant-based Products

Authors: Morello Sara, Pederiva Sabina, Bianchi Manila, Martucci Francesca, Marchis Daniela, Decastelli Lucia

Abstract:

Vegetables represent an integral part of a healthy diet due to their valuable nutritional properties and the growth in consumer demand in recent years is particularly remarkable for a diet rich in vitamins and micronutrients. However, plant-based products are involved in several food outbreaks connected to various sources of contamination and quite often, bacteria responsible for side effects showed high resistance to antibiotics. The abuse of antibiotics can be one of the main mechanisms responsible for increasing antibiotic resistance (AR). Plants grown for food use can be contaminated directly by spraying antibiotics on crops or indirectly by treatments with antibiotics due to the use of manure, which may contain both antibiotics and genes of antibiotic resistance (ARG). Antibiotic residues could represent a potential way of human health risk due to exposure through the consumption of plant-based foods. The presence of antibiotic-resistant bacteria might pose a particular risk to consumers. The present work aims to investigate through a multidisciplinary approach the occurrence of ARG by means of a biomolecular approach (PCR) and the prevalence of antibiotic residues using a multi residues LC-MS/MS method, both in different plant-based products. During the period from July 2020 to October 2021, a total of 74 plant samples (33 lettuces and 41 tomatoes) were collected from 57 farms located throughout the Piedmont area, and18 out of 74 samples (11 lettuces and 7 tomatoes) were selected to LC-MS/MS analyses. DNA extracted (ExtractME, Blirt, Poland) from plants used on crops and isolated bacteria were analyzed with 6 sets of end-point multiplex PCR (Qiagen, Germany) to detect the presence of resistance genes of the main antibiotic families, such as tet genes (tetracyclines), bla (β-lactams) and mcr (colistin). Simultaneous detection of 43 molecules of antibiotics belonging to 10 different classes (tetracyclines, sulphonamides, quinolones, penicillins, amphenicols, macrolides, pleuromotilines, lincosamides, diaminopyrimidines) was performed using Exion LC system AB SCIEX coupled to a triple quadrupole mass spectrometer QTRAP 5500 from AB SCIEX. The PCR assays showed the presence of ARG in 57% (n=42): tetB (4.8%; n=2), tetA (9.5%; n=4), tetE (2.4%; n=1), tetL (12%; n=5), tetM (26%; n=11), blaSHV (21.5%; n=9), blaTEM (4.8%; n =2) and blaCTX-M (19%; n=8). In none of the analyzed samples was the mcr gene responsible for colistin resistance detected. Results obtained from LC-MS/MS analyses showed that none of the tested antibiotics appear to exceed the LOQ (100 ppb). Data obtained confirmed the presence of bacterial populations containing antibiotic resistance determinants such as tet gene (tetracycline) and bla genes (beta-lactams), widely used in human medicine, which can join the food chain and represent a risk for consumers, especially with raw products. The presence of traces of antibiotic residues in vegetables, in concentration below the LOQ of the LC-MS/MS method applied, cannot be excluded. In conclusion, traces of antibiotic residues could be a health risk to the consumer due to potential involvement in the spread of AR. PCR represents a useful and effective approach to characterize and monitor AR carried by bacteria from the entire food chain.

Keywords: plant-based products, ARG, PCR, antibiotic residues

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1036 Industrial Ecology Perspectives of Food Supply Chains: A Framework of Analysis

Authors: Luciano Batista, Sylvia Saes, Nuno Fouto, Liam Fassam

Abstract:

This paper introduces the theoretical and methodological basis of an analytical framework conceived with the purpose of bringing industrial ecology perspectives into the core of the underlying disciplines supporting analyses in studies concerned with environmental sustainability aspects beyond the product cycle in a supply chain. Given the pressing challenges faced by the food sector, the framework focuses upon waste minimization through industrial linkages in food supply chains. The combination of industrial ecology practice with basic LCA elements, the waste hierarchy model, and the spatial scale of industrial symbiosis allows the standardization of qualitative analyses and associated outcomes. Such standardization enables comparative analysis not only between different stages of a supply chain, but also between different supply chains. The analytical approach proposed contributes more coherently to the wider circular economy aspiration of optimizing the flow of goods to get the most out of raw materials and cuts wastes to a minimum.

Keywords: by-product synergy, food supply chain, industrial ecology, industrial symbiosis

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1035 A Coupling Study of Public Service Facilities and Land Price Based on Big Data Perspective in Wuxi City

Authors: Sisi Xia, Dezhuan Tao, Junyan Yang, Weiting Xiong

Abstract:

Under the background of Chinese urbanization changing from incremental development to stock development, the completion of urban public service facilities is essential to urban spatial quality. As public services facilities is a huge and complicated system, clarifying the various types of internal rules associated with the land market price is key to optimizing spatial layout. This paper takes Wuxi City as a representative sample location and establishes the digital analysis platform using urban price and several high-precision big data acquisition methods. On this basis, it analyzes the coupling relationship between different public service categories and land price, summarizing the coupling patterns of urban public facilities distribution and urban land price fluctuations. Finally, the internal mechanism within each of the two elements is explored, providing the reference of the optimum layout of urban planning and public service facilities.

Keywords: public service facilities, land price, urban spatial morphology, big data

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1034 Optimizing PelletPAVE Rubberized Asphalt MIX Design Using Gyratory Compaction and Volumetrics

Authors: Hussain Al-Baghli

Abstract:

In comparison to hot mix asphalt (HMAs) composed of non-modified bitumens, the superior performance of rubberized HMAs is very well documented, and numerous trials in the USA and elsewhere have demonstrated excellent performance in terms of creep, fatigue, and durability. In this investigation, rubberized HMA technology was examined to address the most critical forms of pavement distresses in the State of Kuwait, namely, high-temperature rutting and moisture-induced raveling. Pelletpave additive was selected as the preferred technology since it offered a convenient method of directly modifying the exiting local HMA recipe without having to polymer modify the bitumen. Experimental work using various Pelletpave contents was carried out at Kuwait Institute for Scientific Research (KISR) to design an optimum rubberized HMA formulation prior to conducting a pilot-scale road trial. With the aid of a gyratory compactor, the compaction and volumetric properties of HMAs containing 2.5% and 3.0% Pelletpave additive were investigated at a range of bitumen contents, all by mass of total mix.

Keywords: modified bitumen, rubberized hot mix asphalt, gyratory compaction, volumetric properties

Procedia PDF Downloads 153
1033 Role of Honey Bees in Our Ecosystem

Authors: Akhter Hussain Najar

Abstract:

Honey bees are the best insect grown on earth and are taking the lead in the global ecosystem. Life on earth depends upon honey bees pollinating each and every flower in its reign. The global economy is balanced by providing financial attribute due to the use of valuable resources generated from honey bees like honey, royal jelly, bee venom, propolis, bee wax even queens from parent colonies is now in demand. Livelihood stability is also maintained by the rearing of honey bees; beekeeping became a new professional work to be cared for by the experts. Indigenous methodologies are used to rear honey bees. The rearing of honey bees showed variation in different states like Uttar Pradesh, Rajasthan, Haryana, Punjab, Jammu, Kashmir, etc. The production of honey depends upon the area and the availability of crops and the colonies of beekeepers in these states. However, the kind of honey from Jammu and Kashmir, like Accacia and Solai, has different color and odour from the honey generated in the rest of the states. However, the nature and viscosity vary from state to state. But in the last few years, the honey from Jammu and Kashmir has given different shapes when kept at room temperature due to unconditional rainfall during honey peak season in J&K.

Keywords: ecosystem pollen, pollination, honey bee

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1032 Metareasoning Image Optimization Q-Learning

Authors: Mahasa Zahirnia

Abstract:

The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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1031 Analysing the Influence of COVID-19 on Major Agricultural Commodity Prices in South Africa

Authors: D. Mokatsanyane, J. Jansen Van Rensburg

Abstract:

This paper analyses the influence and impact of COVID-19 on major agricultural commodity prices in South Africa. According to a World Bank report, the agricultural sector in South Africa has been unable to reduce the domestic food crisis that has been occurring over the past years, hence the increased rate of poverty, which is currently at 55.5 percent as of April 2020. Despite the significance of this sector, empirical findings concluded that the agricultural sector now accounts for 1.88 percent of South Africa's gross domestic product (GDP). Suggesting that the agricultural sector's contribution to the economy has diminished. Despite the low contribution to GDP, this primary sector continues to play an essential role in the economy. Over the past years, multiple factors have contributed to the soaring commodities prices, namely, climate shocks, biofuel demand, demand and supply shocks, the exchange rate, speculation in commodity derivative markets, trade restrictions, and economic growth. The COVID-19 outbursts have currently disturbed the supply and demand of staple crops. To address the disruption, the government has exempted the agricultural sector from closure and restrictions on movement. The spread of COVID-19 has caused turmoil all around the world, but mostly in developing countries. According to Statistic South Africa, South Africa's economy decreased by seven percent in 2020. Consequently, this has arguably made the agricultural sector the most affected sector since slumped economic growth negatively impacts food security, trade, farm livelihood, and greenhouse gas emissions. South Africa is sensitive to the fruitfulness of global food chains. Restrictions in trade, reinforced sanitary control systems, and border controls have influenced food availability and prices internationally. The main objective of this study is to evaluate the behavior of agricultural commodity prices pre-and during-COVID to determine the impact of volatility drivers on these crops. Historical secondary data of spot prices for the top five major commodities, namely white maize, yellow maize, wheat, soybeans, and sunflower seeds, are analysed from 01 January 2017 to 1 September 2021. The timeframe was chosen to capture price fluctuations between pre-COVID-19 (01 January 2017 to 23 March 2020) and during-COVID-19 (24 March 2020 to 01 September 2021). The Generalised Autoregressive Conditional Heteroscedasticity (GARCH) statistical model will be used to measure the influence of price fluctuations. The results reveal that the commodity market has been experiencing volatility at different points. Extremely high volatility is represented during the first quarter of 2020. During this period, there was high uncertainty, and grain prices were very volatile. Despite the influence of COVID-19 on agricultural prices, the demand for these commodities is still existing and decent. During COVID-19, analysis indicates that prices were low and less volatile during the pandemic. The prices and returns of these commodities were low during COVID-19 because of the government's actions to respond to the virus's spread, which collapsed the market demand for food commodities.

Keywords: commodities market, commodity prices, generalised autoregressive conditional heteroscedasticity (GARCH), Price volatility, SAFEX

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1030 Visualization of Quantitative Thresholds in Stocks

Authors: Siddhant Sahu, P. James Daniel Paul

Abstract:

Technical analysis comprised by various technical indicators is a holistic way of representing price movement of stocks in the market. Various forms of indicators have evolved from the primitive ones in the past decades. There have been many attempts to introduce volume as a major determinant to determine strong patterns in market forecasting. The law of demand defines the relationship between the volume and price. Most of the traders are familiar with the volume game. Including the time dimension to the law of demand provides a different visualization to the theory. While attempting the same, it was found that there are different thresholds in the market for different companies. These thresholds have a significant influence on the price. This article is an attempt in determining the thresholds for companies using the three dimensional graphs for optimizing the portfolios. It also emphasizes on the magnitude of importance of volumes as a key factor for determining of predicting strong price movements, bullish and bearish markets. It uses a comprehensive data set of major companies which form a major chunk of the Indian automotive sector and are thus used as an illustration.

Keywords: technical analysis, expert system, law of demand, stocks, portfolio analysis, Indian automotive sector

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1029 Deep Reinforcement Learning for Optimal Decision-Making in Supply Chains

Authors: Nitin Singh, Meng Ling, Talha Ahmed, Tianxia Zhao, Reinier van de Pol

Abstract:

We propose the use of reinforcement learning (RL) as a viable alternative for optimizing supply chain management, particularly in scenarios with stochasticity in product demands. RL’s adaptability to changing conditions and its demonstrated success in diverse fields of sequential decision-making makes it a promising candidate for addressing supply chain problems. We investigate the impact of demand fluctuations in a multi-product supply chain system and develop RL agents with learned generalizable policies. We provide experimentation details for training RL agents and statistical analysis of the results. We study the generalization ability of RL agents for different demand uncertainty scenarios and observe superior performance compared to the agents trained with fixed demand curves. The proposed methodology has the potential to lead to cost reduction and increased profit for companies dealing with frequent inventory movement between supply and demand nodes.

Keywords: inventory management, reinforcement learning, supply chain optimization, uncertainty

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1028 Role of Phenylalanine and Glycine in Plant Signaling to Improve Drought Tolerance Potential in Wheat

Authors: Abida Kausar, Shagufta Parveen

Abstract:

The priming of seeds was carried out by two amino acids (phenylalanine and glycine) to improve the drought tolerance potential of two wheat varieties. As wheat is a staple food of more than half of the population of the world, including Pakistan. However, its productivity is mainly adversely affected by abiotic stresses. The current research plan was to investigate the effect of hydropriming and priming by amino acids on wheat varieties under drought stress (50% field capacity). Therefore morphological, biochemical, physiological, and yield attributes were recorded. It was revealed that drought stress significantly decreased the biochemical, morpho-physiological, and growth attributes of the wheat crop. However, the priming treatments have shown a positive correlation with all the studied attributes. It was concluded that priming might involve plant signaling to produce the drought tolerance metabolites under stress conditions which, as a consequence, enhanced the drought tolerance potential of crops.

Keywords: plant biomass, biochemical parameters, chlorophyll contents, yield

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1027 Electrodeposition of NiO Films from Organic Solvent-Based Electrolytic Solutions for Solar Cell Application

Authors: Thierry Pauporté, Sana Koussi, Fabrice Odobel

Abstract:

The preparation of semiconductor oxide layers and structures by soft techniques is an important field of research. Higher performances are expected from the optimizing of the oxide films and then use of new methods of preparation for a better control of their chemical, morphological, electrical and optical properties. We present the preparation of NiO by electrodeposition from pure polar aprotic medium and mixtures with water. The effect of the solvent, of the electrochemical deposition parameters and post-deposition annealing treatment on the structural, morphological and optical properties of the films is investigated. We remarkably show that the solvent is inserted in the deposited layer and act as a blowing agent, giving rise to mesoporous films after elimination by thermal annealing. These layers of p-type oxide have been successfully used, after sensitization by a dye, in p-type dye-sensitized solar cells. The effects of the solvent on the layer properties and the application of these layers in p-type dye-sensitized solar cells are described.

Keywords: NiO, layer, p-type sensitized solar cells, electrodeposition

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1026 The Application of Nuclear Energy for Sustainable Agriculture and Food Security: A Review

Authors: Gholamreza Farrokhi, Behzad Sani

Abstract:

The goals of sustainable agricultural are development, improved nutrition, and food security. Sustainable agriculture must be developed that will meet today’s needs for food and other products, as well as preserving the vital natural resource base that will allow future generations to meet their needs. Sustainable development requires international cooperation and the effective use of technology. Access to sustainable sources of food will remain a preeminent challenge in the decades to come. Based upon current practice and consumption, agricultural production will have to increase by about 70% by 2050 to meet demand. Nuclear techniques are used in developing countries to increase production sustainably by breeding improved crops, enhancing livestock reproduction and nutrition, as well as controlling animal and plant pests and diseases. Post-harvest losses can be reduced and safety increased with nuclear technology. Soil can be evaluated with nuclear techniques to conserve and improve soil productivity and water management.

Keywords: food safety, food security, nuclear techniques, sustainable agriculture, sustainable future

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1025 Host Plant Range of Aphidophagus Hoverflies in Relation to Their Pray Aphids in Thatta Pakistan

Authors: Kamal Khan Abro, Attaullah Ansari, Mahpara Pirzada

Abstract:

Hoverflies are commonly known as flower flies, sun flies or garden flies. Hoverflies are very important group of insects because their ecosystem services are diverse. They are an attractive group of insects with their striped abdomens. They are day-flying insects from small to large size, have worldwide distribution, but mostly prefer to live in relatively cold weather areas. In the world, about 6,000 species of 200 genera of two sub-families have been described. Their larvae exhibit a variety of feeding modes i.e. aphidophagous, saprophagous, zoophagous and Phytophagus, where adults are floral visitors of hundreds of different plants species. These floral resources enhance the longevity and fecundity of adult dipterous flies. Many syrphid species also have been documented as efficient crop pollinators. Aphids are commonly called plant louse, greenflies and blackflies. They are major pest of crops; about 4000 species of aphids have been described, feeding on 250 species of plants.

Keywords: host plant range, aphidophagous hoverflies, their prey aphids, Thatta Pakistan

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1024 Simulation Study of the Microwave Heating of the Hematite and Coal Mixture

Authors: Prasenjit Singha, Sunil Yadav, Soumya Ranjan Mohantry, Ajay Kumar Shukla

Abstract:

Temperature distribution in the hematite ore mixed with 7.5% coal was predicted by solving a 1-D heat conduction equation using an implicit finite difference approach. In this work, it was considered a square slab of 20 cm x 20 cm, which assumed the coal to be uniformly mixed with hematite ore. It was solved the equations with the use of MATLAB 2018a software. Heat transfer effects in this 1D dimensional slab convective and the radiative boundary conditions are also considered. Temperature distribution obtained inside hematite slab by considering microwave heating time, thermal conductivity, heat capacity, carbon percentage, sample dimensions, and many other factors such as penetration depth, permittivity, and permeability of coal and hematite ore mixtures. The resulting temperature profile can be used as a guiding tool for optimizing the microwave-assisted carbothermal reduction process of hematite slab was extended to other dimensions as well, viz., 1 cm x 1 cm, 5 cm x 5 cm, 10 cm x 10 cm, 20 cm x 20 cm. The model predictions are in good agreement with experimental results.

Keywords: hematite ore, coal, microwave processing, heat transfer, implicit method, temperature distribution

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1023 A Novel Gateway Location Algorithm for Wireless Mesh Networks

Authors: G. M. Komba

Abstract:

The Internet Gateway (IGW) has extra ability than a simple Mesh Router (MR) and the responsibility to route mostly the all traffic from Mesh Clients (MCs) to the Internet backbone however, IGWs are more expensive. Choosing strategic locations for the Internet Gateways (IGWs) best location in Backbone Wireless Mesh (BWM) precarious to the Wireless Mesh Network (WMN) and the location of IGW can improve a quantity of performance related problem. In this paper, we propose a novel algorithm, namely New Gateway Location Algorithm (NGLA), which aims to achieve four objectives, decreasing the network cost effective, minimizing delay, optimizing the throughput capacity, Different from existing algorithms, the NGLA increasingly recognizes IGWs, allocates mesh routers (MRs) to identify IGWs and promises to find a feasible IGW location and install minimum as possible number of IGWs while regularly conserving the all Quality of Service (QoS) requests. Simulation results showing that the NGLA outperforms other different algorithms by comparing the number of IGWs with a large margin and it placed 40% less IGWs and 80% gain of throughput. Furthermore the NGLA is easy to implement and could be employed for BWM.

Keywords: Wireless Mesh Network, Gateway Location Algorithm, Quality of Service, BWM

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1022 Theoretical and Experimental Study on the NO Reduction by H₂ over Char Decorated with Ni at low Temperatures

Authors: Kaixuan Feng, Ruixiang Lin, Yuyan Hu, Yuheng Feng, Dezhen Chen, Tongcheng Cao

Abstract:

In this study, we propose a reaction system for the low-temperature reduction of NO by H₂ on carbon-based materials decorated with 5%wt. Ni. This cost-effective catalyst system efficiently utilizes pyrolysis carbon-based materials and waste hydrogen. Additionally, it yields environmentally friendly products without requiring extra heat sources in practical SCR devices. Density functional theory elucidates the mechanism of NO heterogeneous reduction by H₂ on Ni-decorated char surfaces. Two distinct reaction paths were identified, one involving the intermediate product N₂O and the other not. These pathways exhibit different rate-determination steps and activation energies. Kinetic analysis indicates that the N₂O byproduct pathway has a lower activation energy. Experimental results corroborate the theoretical findings. Thus, this research enhances our mechanistic understanding of the NO-H₂ reaction over char and offers insights for optimizing catalyst design in low-temperature NO reduction.

Keywords: char-based catalysis, NO reduction, DFT study, heterogeneous reaction, low-temperature H₂-reduction

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1021 The Effects of Learning Engagement on Interpreting Performance among English Major Students

Authors: Jianhua Wang, Ying Zhou, Xi Zhang

Abstract:

To establish the influential mechanism of learning engagement on interpreter’s performance, the present study submitted a questionnaire to a sample of 927 English major students with 804 valid ones and used the structural equation model as the basis for empirical analysis and statistical inference on the sample data. In order to explore the mechanism for interpreting learning engagement on student interpreters’ performance, a path model of interpreting processes with three variables of ‘input-environment-output’ was constructed. The results showed that the effect of each ‘environment’ variable on interpreting ability was different from and greater than the ‘input’ variable, and learning engagement was the greatest influencing factor. At the same time, peer interaction on interpreting performance has significant influence. Results suggest that it is crucial to provide effective guidance for optimizing learning engagement and interpreting teaching research by both improving the environmental support and building the platform of peer interaction, beginning with learning engagement.

Keywords: learning engagement, interpreting performance, interpreter training, English major students

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1020 Intensive Biological Control in Spanish Greenhouses: Problems of the Success

Authors: Carolina Sanchez, Juan R. Gallego, Manuel Gamez, Tomas Cabello

Abstract:

Currently, biological control programs in greenhouse crops involve the use, at the same time, several natural enemies during the crop cycle. Also, large number of plant species grown in greenhouses, among them, the used cultivars are also wide. However, the cultivar effects on entomophagous species efficacy (predators and parasitoids) have been scarcely studied. A new method had been developed, using the factitious prey or host Ephestia kuehniella. It allows us to evaluate, under greenhouse or controlled conditions (semi-field), the cultivar effects on the entomophagous species effectiveness. The work was carried out in greenhouse tomato crop. It has been found the biological and ecological activities of predatory species (Nesidiocoris tenuis) and egg-parasitoid (Trichogramma achaeae) can be well represented with the use of the factitious prey or host; being better in the former than the latter. The data found in the trial are shown and discussed. The developed method could be applied to evaluate new plant materials before making available to farmers as commercial varieties, at low costs and easy use.

Keywords: cultivar effects, efficiency, predators, parasitoids

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1019 The Study of the Mutual Effect of Genotype in Environment by Percent of Oil Criterion in Sunflower

Authors: Seyed Mohammad Nasir Mousavi, Pasha Hejazi, Maryam Ebrahimian Dehkordi

Abstract:

In order to study the Mutual effect of genotype × environment for the percent of oil index in sunflower items, an experiment was accomplished in form of complete random block designs in four iteration in four diverse researching station comprising Esfahan, Birjand, Sari, and Karaj. Complex variance analysis showed that there is an important diversity between the items under investigation. The results pertaining the coefficient variation of items Azargol and Vidoc has respectively allocated the minimum coefficient of variations. According to the results extrapolated from Shokla stability variance, the Items Brocar, Allison and Fabiola, are among the stable genotypes for oil percent respectively. in the biplot GGE, the location under investigations divided in two super-environment, first one comprised of locations naming Esfahan, Karaj, and Birjand, and second one were such a location as Sari. By this point of view, in the first super-environment, the Item Fabiola and in the second Almanzor item was among the best items and crops.

Keywords: sunflower, stability, GGE bipilot, super-environment

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1018 Optimization of Submerged Arc Welding Parameters for Joining SS304 and MS1018

Authors: Jasvinder Singh, Manjinder Singh

Abstract:

Welding of dissimilar materials is a complicated process due to the difference in melting point of two materials. Thermal conductivity and coefficient of thermal expansion of dissimilar materials also different; therefore, residual stresses produced in the weldment and base metal are the most critical problem associated with the joining of dissimilar materials. Tensile strength and impact toughness also reduced due to the residual stresses. In the present research work, an attempt has been made to weld SS304 and MS1018 dissimilar materials by submerged arc welding (SAW). By conducting trail, runs most effective parameters welding current, Arc voltage, welding speed and nozzle to plate distance were selected to weld these materials. The fractional factorial technique was used to optimize the welding parameters. Effect on tensile strength (TS), fracture toughness (FT) and microhardness of weldment were studied. It was concluded that by optimizing welding current, voltage and welding speed the properties of weldment can be enhanced.

Keywords: SAW, Tensile Strength (TS), fracture toughness, micro hardness

Procedia PDF Downloads 511