Search results for: PM machinesautonomous agricultural machines
1340 A Phenomenological Approach to Computational Modeling of Analogy
Authors: José Eduardo García-Mendiola
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In this work, a phenomenological approach to computational modeling of analogy processing is carried out. The paper goes through the consideration of the structure of the analogy, based on the possibility of sustaining the genesis of its elements regarding Husserl's genetic theory of association. Among particular processes which take place in order to get analogical inferences, there is one which arises crucial for enabling efficient base cases retrieval through long-term memory, namely analogical transference grounded on familiarity. In general, it has been argued that analogical reasoning is a way by which a conscious agent tries to determine or define a certain scope of objects and relationships between them using previous knowledge of other familiar domain of objects and relations. However, looking for a complete description of analogy process, a deeper consideration of phenomenological nature is required in so far, its simulation by computational programs is aimed. Also, one would get an idea of how complex it would be to have a fully computational account of the analogy elements. In fact, familiarity is not a result of a mere chain of repetitions of objects or events but generated insofar as the object/attribute or event in question is integrable inside a certain context that is taking shape as functionalities and functional approaches or perspectives of the object are being defined. Its familiarity is generated not by the identification of its parts or objective determinations as if they were isolated from those functionalities and approaches. Rather, at the core of such a familiarity between entities of different kinds lays the way they are functionally encoded. So, and hoping to make deeper inroads towards these topics, this essay allows us to consider that cognitive-computational perspectives can visualize, from the phenomenological projection of the analogy process reviewing achievements already obtained as well as exploration of new theoretical-experimental configurations towards implementation of analogy models in specific as well as in general purpose machines.Keywords: analogy, association, encoding, retrieval
Procedia PDF Downloads 1121339 Prediction of Remaining Life of Industrial Cutting Tools with Deep Learning-Assisted Image Processing Techniques
Authors: Gizem Eser Erdek
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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet
Procedia PDF Downloads 651338 Window Analysis and Malmquist Index for Assessing Efficiency and Productivity Growth in a Pharmaceutical Industry
Authors: Abbas Al-Refaie, Ruba Najdawi, Nour Bata, Mohammad D. AL-Tahat
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The pharmaceutical industry is an important component of health care systems throughout the world. Measurement of a production unit-performance is crucial in determining whether it has achieved its objectives or not. This paper applies data envelopment (DEA) window analysis to assess the efficiencies of two packaging lines; Allfill (new) and DP6, in the Penicillin plant in a Jordanian Medical Company in 2010. The CCR and BCC models are used to estimate the technical efficiency, pure technical efficiency, and scale efficiency. Further, the Malmquist productivity index is computed to measure then employed to assess productivity growth relative to a reference technology. Two primary issues are addressed in computation of Malmquist indices of productivity growth. The first issue is the measurement of productivity change over the period, while the second is to decompose changes in productivity into what are generally referred to as a ‘catching-up’ effect (efficiency change) and a ‘frontier shift’ effect (technological change). Results showed that DP6 line outperforms the Allfill in technical and pure technical efficiency. However, the Allfill line outperforms DP6 line in scale efficiency. The obtained efficiency values can guide production managers in taking effective decisions related to operation, management, and plant size. Moreover, both machines exhibit a clear fluctuations in technological change, which is the main reason for the positive total factor productivity change. That is, installing a new Allfill production line can be of great benefit to increasing productivity. In conclusions, the DEA window analysis combined with the Malmquist index are supportive measures in assessing efficiency and productivity in pharmaceutical industry.Keywords: window analysis, malmquist index, efficiency, productivity
Procedia PDF Downloads 6031337 Predictions of Thermo-Hydrodynamic State for Single and Three Pads Gas Foil Bearings Operating at Steady-State Based on Multi-Physics Coupling Computer Aided Engineering Simulations
Authors: Tai Yuan Yu, Pei-Jen Wang
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Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings, abbreviated as GFBs, are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional, abbreviated as 3D, fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.Keywords: fluid-structure interaction, multi-physics simulations, gas foil bearing, oil-free, transient thermo-hydrodynamic
Procedia PDF Downloads 1591336 Production of Alcohol from Sweet Potato
Authors: Abhishek S. Shete
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There is nothing new in the use of alcohol made from root crops as a motor fuel. Alcohol is an excellent alternative motor fuel for petrol engines. The reason alcohol fuel has not been fully exploited is that, up until now; gasoline has been cheap, available, and easy to produce. However, nowadays, crude oil is getting scarce, and the historic price difference between alcohol and gasoline is getting narrower. Alcohol fuel can be an important part of the solution for Rwanda because there is tremendous scope to use bulk production of sweet potato into alcohol. The total sweet potato production in both seasons is found to be 1.607.296 tones/year. The average productivity of sweet potato in the country irrespective of seasons is found to be 8.9 tones/ha. If all of the available agricultural surplus were converted to ethanol, alcohol would supply less than 5% of motor fuel needs.Keywords: root crops, sweet potato, surplus, alcohol
Procedia PDF Downloads 4161335 Comparison of MODIS-Based Rice Extent Map and Landsat-Based Rice Classification Map in Determining Biomass Energy Potential of Rice Hull in Nueva Ecija, Philippines
Authors: Klathea Sevilla, Marjorie Remolador, Bryan Baltazar, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion Ang
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The underutilization of biomass resources in the Philippines, combined with its growing population and the rise in fossil fuel prices confirms demand for alternative energy sources. The goal of this paper is to provide a comparison of MODIS-based and Landsat-based agricultural land cover maps when used in the estimation of rice hull’s available energy potential. Biomass resource assessment was done using mathematical models and remote sensing techniques employed in a GIS platform.Keywords: biomass, geographic information system (GIS), remote sensing, renewable energy
Procedia PDF Downloads 4771334 Customer’s Choice of a Bank: An Empirical Enquiry from the Banked Ghanaian
Authors: Emmanuel Larbi Offei, Felix Agyei-Sasu, Maura Naa Densua Ashong
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Ghana has 26 universal banks and several banking and non-banking financial institutions operating in the country. The growing number of banks has heightened competition among banks to attract and retain customers more customers to ensure sustainability. Hence the need to identify and understand factors that influences customers’ choice of banks cannot be overemphasised. This study investigates the determinants of bank selection criteria by banking customers in Ghana. Four banks were purposively sampled for this study namely Barclays, Standard Chartered, Sahel Sahara and Unibank. Convenience sampling was then used to select 114 bank customers in Accra and interviewed. Questionnaires were used to collect data that were analysed in tables and charts with the use of STATA software. The findings of the study revealed that quick/prompt services and complaint handling, safety of funds, networked branches, easy access to functional Automated Teller Machines (ATMs) and low/moderate service charges were the major determinants of customers’ choice of banks. The results further show that 89.5 percent of all deposits are held in either current or savings accounts. About 22.1 percent of the respondents indicated that they have plans of changing their banks in the near future because they are not satisfied with their banks. A gender analysis of the choice criteria showed differences between the choice criteria of the male as compared to the female. The study recommends that banks in Ghana should focus on products and policies that will not compromise on the safety of funds of their customers. Again, banks must address customer complaints and dissatisfactions as promptly as possible by taking pragmatic steps to address administrative bureaucracies and infrastructural challenges that prolong the duration of banking transactions.Keywords: Ghana, banks, determinants, customers’ choice, competition
Procedia PDF Downloads 4311333 Advances in Genome Editing and Future Prospects for Sorghum Improvement: A Review
Authors: Micheale Yifter Weldemichael, Hailay Mehari Gebremedhn, Teklehaimanot Hailesslasie Teklu
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Recent developments in targeted genome editing accelerated genetic research and opened new potentials to improve crops for better yields and quality. Given the significance of cereal crops as a primary source of food for the global population, the utilization of contemporary genome editing techniques like CRISPR/Cas9 is timely and crucial. CRISPR/Cas technology has enabled targeted genomic modifications, revolutionizing genetic research and exploration. Application of gene editing through CRISPR/Cas9 in enhancing sorghum is particularly vital given the current ecological, environmental, and agricultural challenges exacerbated by climate change. As sorghum is one of the main staple foods of our region and is known to be a resilient crop with a high potential to overcome the above challenges, the application of genome editing technology will enhance the investigation of gene functionality. CRISPR/Cas9 enables the improvement of desirable sorghum traits, including nutritional value, yield, resistance to pests and diseases, and tolerance to various abiotic stresses. Furthermore, CRISPR/Cas9 has the potential to perform intricate editing and reshape the existing elite sorghum varieties, and introduce new genetic variations. However, current research primarily focuses on improving the efficacy of the CRISPR/Cas9 system in successfully editing endogenous sorghum genes, making it a feasible and successful undertaking in sorghum improvement. Recent advancements and developments in CRISPR/Cas9 techniques have further empowered researchers to modify additional genes in sorghum with greater efficiency. Successful application and advancement of CRISPR techniques in sorghum will aid not only in gene discovery and the creation of novel traits that regulate gene expression and functional genomics but also in facilitating site-specific integration events. The purpose of this review is, therefore, to elucidate the current advances in sorghum genome editing and highlight its potential in addressing food security issues. It also assesses the efficiency of CRISPR-mediated improvement and its long-term effects on crop improvement and host resistance against parasites, including tissue-specific activity and the ability to induce resistance. This review ends by emphasizing the challenges and opportunities of CRISPR technology in combating parasitic plants and proposing directions for future research to safeguard global agricultural productivity.Keywords: CRISPR/Cas9, genome editing, quality, sorghum, stress, yield
Procedia PDF Downloads 171332 Innovative Predictive Modeling and Characterization of Composite Material Properties Using Machine Learning and Genetic Algorithms
Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager
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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties
Procedia PDF Downloads 521331 Evaluation of the Potential of Olive Pomace Compost for Using as a Soil Amendment
Authors: M. Černe, I. Palčić, D. Anđelini, D. Cvitan, N. Major, M. Lukić, S. Goreta Ban, D. Ban, T. Rijavec, A. Lapanje
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Context: In the Mediterranean basin, large quantities of lignocellulosic by-products, such as olive pomace (OP), are generated during olive processing on an annual basis. Due to the phytotoxic nature of OP, composting is recommended for its stabilisation to produce the end-product safe for agricultural use. Research Aim: This study aims to evaluate the applicability of olive pomace compost (OPC) for use as a soil amendment by considering its physical and chemical characteristics and microbiological parameters. Methodology: The OPC samples were collected from the surface and depth layers of the compost pile after 8 months. The samples were analyzed for their C/N, pH, EC, total phenolic content, residual oils, and elemental content, as well as colloidal properties and microbial community structure. The specific analytical approaches used are detailed in the poster. Findings: The results showed that the pH of OPC ranged from 7.8 to 8.6, while the electrical conductivity was from 770 to 1608 mS/cm. The levels of nitrogen (N), phosphorus (P), and potassium (K) varied within the ranges of 1.5 to 27.2 g/kg d.w., 1.6 to 1.8 g/kg d.w., and 6.5 to 7.5 g/kg d.w., respectively. The contents of potentially toxic metals such as chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) were below the EU limits for soil improvers. The microbial structure follows the changes of the gradient from the outer to the innermost layer with relatively low amounts of DNA. The gradient nature shows that it is needed to develop better strategies for composting surpassing the conventional approach. However, the low amounts of total phenols and oil residues indicated efficient biodegradation during composting. The carbon-to-nitrogen ratio (C/N) within the range of 13 to 16 suggested that OPC can be used as a soil amendment. Overall, the study suggests that composting can be a promising strategy for environmentally-friendly OP recycling. Theoretical Importance: This study contributes to the understanding of the use of OPC as a soil amendment and its potential benefits in resource recycling and reducing environmental burdens. It also highlights the need for improved composting strategies to optimize its process. Data Collection and Analysis Procedures: The OPC samples were taken from the compost pile and charasterised for selected chemical, physical and microbial parameters. The specific analytical procedures utilized are described in detail in the poster. Question Addressed: This study addresses the question of whether composting can be optimized to improve the biodegradation of OP. Conclusion: The study concludes that OPC has the potential to be used as a soil amendment due to its favorable physical and chemical characteristics, low levels of potentially toxic metals, and efficient biodegradation during composting. However, the results also suggest the need for improved composting strategies to improve the quality of OPC.Keywords: olive pomace compost, waste valorisation, agricultural use, soil amendment
Procedia PDF Downloads 631330 Bifurcations of a System of Rotor-Ball Bearings with Waviness and Squeeze Film Dampers
Authors: Sina Modares Ahmadi, Mohamad Reza Ghazavi, Mandana Sheikhzad
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Squeeze film damper systems (SFD) are often used in machines with high rotational speed to reduce non-periodic behavior by creating external damping. These types of systems are frequently used in aircraft gas turbine engines. There are some structural parameters which are of great importance in designing these kinds of systems, such as oil film thickness, C, and outer race mass, mo. Moreover, there is a crucial parameter associated with manufacturing process, under the title of waviness. Geometric imperfections are often called waviness if its wavelength is much longer than Hertzian contact width which is a considerable source of vibration in ball bearings. In this paper, a system of a flexible rotor and two ball bearings with floating ring squeeze film dampers and consideration of waviness has been modeled and solved by a numerical integration method, namely Runge-Kutta method to investigate the dynamic response of the system. The results show that by increasing the number of wave lobes, which is due to inappropriate manufacturing, non- periodic and chaotic behavior increases. This result reveals the importance of manufacturing accuracy. Moreover, as long as C< 1.5×10-4 m, by increasing the oil film thickness, unwanted vibrations and non-periodic behavior of the system have been reduced, On the other hand, when C>1.5×10-4 m, increasing the outer oil film thickness results in the increasing chaotic and non-periodic responses. This result shows that although the presence of oil film results in reduction the non-periodic and chaotic behaviors, but the oil film has an optimal thickness. In addition, with increasing mo, the disc displacement amplitude increases. This result reveals the importance of utilizing light materials in manufacturing the squeeze film dampers.Keywords: squeeze-film damper, waviness, ball bearing, bifurcation
Procedia PDF Downloads 3751329 Study and Simulation of a Dynamic System Using Digital Twin
Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli
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Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models
Procedia PDF Downloads 1361328 Monitoring and Evaluation of the Distributed Agricultural Machinery of the Department of Agriculture Using a Web-Based Information System with a Short Messaging Service Technology
Authors: Jimmy L. Caldoza, Erlito M. Albina
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Information Systems are increasingly being used to monitor and assess government projects as well as improve transparency and combat corruption. With reference to existing information systems relevant to monitoring and evaluation systems adopted by various government agencies from other countries, this research paper aims to help the Philippine government, particularly the Department of Agriculture, in assessing the impact of their programs and projects on their target beneficiaries through the development of the web-based Monitoring and Evaluation Information System with the application of a short messaging system (sms) technology.Keywords: monitoring and evaluation system, web-based information system, short messaging system technology, database structure and management
Procedia PDF Downloads 1321327 The Use of a Geographical Information System in the Field of Irrigation (Moyen-Chéliff)
Authors: Benhenni Abdellaziz
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Irrigation is a limiting factor for agricultural production and socioeconomic development of many countries in the arid and semi-arid world. However, the sustainability of irrigation systems requires rational management of the water resource, which is becoming increasingly rare in these regions. The objective of this work is to apply a geographic information system (GIS) coupled with a model for calculating crop water requirements (CROPWATER) for the management of irrigation water in irrigated areas and offer managers an effective tool to better manage water resources in these areas. The application area of GIS is the irrigated perimeter of Western Middle Cheliff, which is located in a semi-arid region (Middle Cheliff). The scope in question is considerable agrarian dynamics and an increased need for irrigation of most crops.Keywords: GIS, CROPWAT, irrigation, water management, middle cheliff
Procedia PDF Downloads 641326 The Use of a Geographical Information System in the Field of Irrigation (Moyen-Chéliff)
Authors: Benhenni Abdellaziz
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Irrigation is a limiting factor for agricultural production and socio-economic development of many countries in arid and semiarid in the world. However, the sustainability of irrigation systems requires a rational management of the water resource that is becoming increasingly rare in these regions. The objective of this work is to apply a geographic information system (GIS) coupled to a model for calculating crop water requirements (CROPWATER) for the management of irrigation water in irrigated area and offer managers with an effective tool to better manage water resources in these areas. The application area of GIS is the irrigated perimeter of Western Middle Cheliff which is located in a semi-arid region (Middle Cheliff). The scope in question is a considerable agrarian dynamics and an increased need for irrigation of most crops.Keywords: geographical information, irrigation, economical, use rational
Procedia PDF Downloads 2371325 Dynamic Analysis of Mono-Pile: Spectral Element Method
Authors: Rishab Das, Arnab Banerjee, Bappaditya Manna
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Mono-pile foundations are often used in soft soils in order to support heavy mega-structures, whereby often these deep footings may undergo dynamic excitation due to many causes like earthquake, wind or wave loads acting on the superstructure, blasting, and unbalanced machines, etc. A comprehensive analytical study is performed to study the dynamics of the mono-pile system embedded in cohesion-less soil. The soil is considered homogeneous and visco-elastic in nature and is analytically modeled using complex springs. Considering the N number of the elements of the pile, the final global stiffness matrix is obtained by using the theories of the spectral element matrix method. Further, statically condensing the intermediate internal nodes of the global stiffness matrix results to a smaller sub matrix containing the nodes experiencing the external translation and rotation, and the stiffness and damping functions (impedance functions) of the embedded piles are determined. Proper plots showing the variation of the real and imaginary parts of these impedance functions with the dimensionless frequency parameter are obtained. The plots obtained from this study are validated by that provided by Novak,1974. Further, the dynamic analysis of the resonator impregnated pile is proposed within this study. Moreover, with the aid of Wood's 1g laboratory scaling law, a proper scaled-down resonator-pile model is 3D printed using PLA material. Dynamic analysis of the scaled model is carried out in the time domain, whereby the lateral loads are imposed on the pile head. The response obtained from the sensors through the LabView software is compared with the proposed theoretical data.Keywords: mono-pile, visco-elastic, impedance, LabView
Procedia PDF Downloads 1041324 Studies on Optimizing the Level of Liquid Biofertilizers in Peanut and Maize and Their Economic Analysis
Authors: Chandragouda R. Patil, K. S. Jagadeesh, S. D. Kalolgi
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Biofertilizers containing live microbial cells can mobilize one or more nutrients to plants when applied to either seed or rhizosphere. They form an integral part of nutrient management strategies for sustainable production of agricultural crops. Annually, about 22 tons of lignite-based biofertilizers are being produced and supplied to farmers at the Institute of Organic Farming, University of Agricultural Sciences, Dharwad, Karnataka state India. Although carrier based biofertilizers are common, they have shorter shelf life, poor quality, high contamination, unpredictable field performance and high cost of solid carriers. Hence, liquid formulations are being developed to increase their efficacy and broaden field applicability. An attempt was made to develop liquid formulation of strains of Rhizobium NC-92 (Groundnut), Azospirillum ACD15 both nitrogen-fixing biofertilizers and Pseudomonas striata an efficient P-solubilizing bacteria (PSB). Different concentration of amendments such as additives (glycerol and polyethylene glycol), adjuvants (carboxyl methyl cellulose), gum arabica (GA), surfactant (polysorbate) and trehalose specifically for Azospirillum were found essential. Combinations of formulations of Rhizobium and PSB for groundnut and Azospirillum and PSB for maize were evaluated under field conditions to determine the optimum level of inoculum required. Each biofertilizer strain was inoculated at the rate of 2, 4, 8 ml per kg of seeds and the efficacy of each formulation both individually and in combinations was evaluated against the lignite-based formulation at the rate of 20 g each per kg seeds and a un-inoculated set was included to compare the inoculation effect. The field experiment had 17 treatments in three replicates and the best level of inoculum was decided based on net returns and cost: benefit ratio. In peanut, the combination of 4 ml of Rhizobium and 2 ml of PSB resulted in the highest net returns and higher cost to benefit ratio of 1:2.98 followed by treatment with a combination of 2 ml per kg each of Rhizobium and PSB with a B;C ratio of 1:2.84. The benefits in terms of net returns were to the extent of 16 percent due to inoculation with lignite based formulations while it was up to 48 percent due to the best combination of liquid biofertilizers. In maize combination of liquid formulations consisting of 4 ml of Azospirillum and 2 ml of PSB resulted in the highest net returns; about 53 percent higher than the un-inoculated control and 20 percent higher than the treatment with lignite based formulation. In both the crops inoculation with lignite based formulations significantly increased the net returns over un-inoculated control while levels higher or lesser than 4 ml of Rhizobium and Azospirillum and higher or lesser than 2 ml of PSB were not economical and hence not optimal for these two crops.Keywords: Rhizobium, Azospirillum, phosphate solubilizing bacteria, liquid formulation, benefit-cost ratio
Procedia PDF Downloads 4821323 The Impact of Generative AI Illustrations on Aesthetic Symbol Consumption among Consumers: A Case Study of Japanese Anime Style
Authors: Han-Yu Cheng
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This study aims to explore the impact of AI-generated illustration works on the aesthetic symbol consumption of consumers in Taiwan. The advancement of artificial intelligence drawing has lowered the barriers to entry, enabling more individuals to easily enter the field of illustration. Using Japanese anime style as an example, with the development of Generative Artificial Intelligence (Generative AI), an increasing number of illustration works are being generated by machines, sparking discussions about aesthetics and art consumption. Through surveys and the analysis of consumer perspectives, this research investigates how this influences consumers' aesthetic experiences and the resulting changes in the traditional art market and among creators. The study reveals that among consumers in Taiwan, particularly those interested in Japanese anime style, there is a pronounced interest and curiosity surrounding the emergence of Generative AI. This curiosity is particularly notable among individuals interested in this style but lacking the technical skills required for creating such artworks. These works, rooted in elements of Japanese anime style, find ready acceptance among enthusiasts of this style due to their stylistic alignment. Consequently, they have garnered a substantial following. Furthermore, with the reduction in entry barriers, more individuals interested in this style but lacking traditional drawing skills have been able to participate in producing such works. Against the backdrop of ongoing debates about artistic value since the advent of artificial intelligence (AI), Generative AI-generated illustration works, while not entirely displacing traditional art, to a certain extent, fulfill the aesthetic demands of this consumer group, providing a similar or analogous aesthetic consumption experience. Additionally, this research underscores the advantages and limitations of Generative AI-generated illustration works within this consumption environment.Keywords: generative AI, anime aesthetics, Japanese anime illustration, art consumption
Procedia PDF Downloads 671322 Oil Palm Leaf and Corn Stalk, Mechanical Properties and Surface Characterization
Authors: Zawawi Daud
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Agro waste can be defined as waste from agricultural plant. Oil palm leaf and corn stalk can be categorized as ago waste material. At first, the comparison between oil palm leaf and corn stalk by mechanical properties from soda pulping process. After that, focusing on surface characterization by Scanning Electron Microscopy (SEM). Both material have a potential due to mechanical properties (tensile, tear, burst and fold) and surface characterization but corn stalk shows more in strength and compactness due to fiber characterization compared to oil palm leaf. This study promoting the green technology in develop a friendly product and suitable to be used as an alternative pulp in paper making industry.Keywords: fiber, oil palm leaf, corn stalk, green technology
Procedia PDF Downloads 4801321 A Comparative Study of Dengue Fever in Taiwan and Singapore Based on Open Data
Authors: Wei Wen Yang, Emily Chia Yu Su
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Dengue fever is a mosquito-borne tropical infectious disease caused by the dengue virus. After infection, symptoms usually start from three to fourteen days. Dengue virus may cause a high fever and at least two of the following symptoms, severe headache, severe eye pain, joint pains, muscle or bone pain, vomiting, feature skin rash, and mild bleeding manifestation. In addition, recovery will take at least two to seven days. Dengue fever has rapidly spread in tropical and subtropical areas in recent years. Several phenomena around the world such as global warming, urbanization, and international travel are the main reasons in boosting the spread of dengue. In Taiwan, epidemics occur annually, especially during summer and fall seasons. On the other side, Singapore government also has announced the amounts number of dengue cases spreading in Singapore. As the serious epidemic of dengue fever outbreaks in Taiwan and Singapore, countries around the Asia-Pacific region are becoming high risks of susceptible to the outbreaks and local hub of spreading the virus. To improve public safety and public health issues, firstly, we are going to use Microsoft Excel and SAS EG to do data preprocessing. Secondly, using support vector machines and decision trees builds predict model, and analyzes the infectious cases between Taiwan and Singapore. By comparing different factors causing vector mosquito from model classification and regression, we can find similar spreading patterns where the disease occurred most frequently. The result can provide sufficient information to predict the future dengue infection outbreaks and control the diffusion of dengue fever among countries.Keywords: dengue fever, Taiwan, Singapore, Aedes aegypti
Procedia PDF Downloads 2251320 Mitigating the Negative Health Effects from Stress - A Social Network Analysis
Authors: Jennifer A. Kowalkowski
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Production agriculture (farming) is a physically, emotionally, and cognitively stressful occupation, where workers have little control over the stressors that impact both their work and their lives. In an occupation already rife with hazards, these occupational-related stressors have been shown to increase farm workers’ risks for illness, injury, disability, and death associated with their work. Despite efforts to mitigate the negative health effects from occupational-related stress (ORS) and to promote health and well-being (HWB) among farmers in the US, marked improvements have not been attained. Social support accessed through social networks has been shown to buffer against the negative health effects from stress, yet no studies have directly examined these relationships among farmers. The purpose of this study was to use social network analysis to explore the social networks of farm owner-operators and the social supports available to them for mitigating the negative health effects of ORS. A convenience sample of 71 farm owner-operators from a Midwestern County in the US completed and returned a mailed survey (55.5% response rate) that solicited information about their social networks related to ORS. Farmers reported an average of 2.4 individuals in their personal networks and higher levels of comfort discussing ORS with female network members. Farmers also identified few connections (3.4% density) and indicated low comfort with members of affiliation networks specific to ORS. Findings from this study highlighted that farmers accessed different social networks and resources for their personal HWB than for issues related to occupational(farm-related) health and safety. In addition, farmers’ social networks for personal HWB were smaller, with different relational characteristics than reported in studies of farmers’ social networks related to occupational health and safety. Collectively, these findings suggest that farmers conceptualize personal HWB differently than farm health and safety. Therefore, the same research approaches and targets that guide occupational health and safety research may not be appropriate for personal HWB for farmers. Interventions and programming targeting ORS and HWB have largely been offered through the same platforms or mechanisms as occupational health and safety programs. This may be attributed to the significant overlap between the farm as a family business and place of residence, or that ORS stems from farm-related issues. However, these assumptions translated to health research of farmers and farm families from the occupational health and safety literature have not been directly studied or challenged. Thismay explain why past interventions have not been effective at improving health outcomes for farmers and farm families. A close examination of findings from this study raises important questions for researchers who study agricultural health. Findings from this study have significant implications for future research agendas focused on addressing ORS, HWB, and health disparities for farmersand farm families.Keywords: agricultural health, occupational-related stress, social networks, well-being
Procedia PDF Downloads 1001319 Analysis of the Savings Behaviour of Rice Farmers in Tiaong, Quezon, Philippines
Authors: Angelika Kris D. Dalangin, Cesar B. Quicoy
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Rice farming is a major source of livelihood and employment in the Philippines, but it requires a substantial amount of capital. Capital may come from income (farm, non-farm, and off-farm), savings and credit. However, rice farmers suffer from lack of capital due to high costs of inputs and low productivity. Capital insufficiency, coupled with low productivity, hindered them to meet their basic household and production needs. Hence, they resorted to borrowing money, mostly from informal lenders who charge very high interest rates. As another source of capital, savings can help rice farmers meet their basic needs for both the household and the farm. However, information is inadequate whether the farmers save or not, as well as, why they do not depend on savings to augment their lack of capital. Thus, it is worth analyzing how rice farmers saved. The study revealed, using the actual savings which is the difference between the household income and expenditure, that about three-fourths (72%) of the total number of farmers interviewed are savers. However, when they were asked whether they are savers or not, more than half of them considered themselves as non-savers. This gap shows that there are many farmers who think that they do not have savings at all; hence they continue to borrow money and do not depend on savings to augment their lack of capital. The study also identified the forms of savings, saving motives, and savings utilization among rice farmers. Results revealed that, for the past 12 months, most of the farmers saved cash at home for liquidity purposes while others deposited cash in banks and/or saved their money in the form of livestock. Among the most important reasons of farmers for saving are for daily household expenses, for building a house, for emergency purposes, for retirement, and for their next production. Furthermore, the study assessed the factors affecting the rice farmers’ savings behaviour using logistic regression. Results showed that the factors found to be significant were presence of non-farm income, per capita net farm income, and per capita household expense. The presence of non-farm income and per capita net farm income positively affects the farmers’ savings behaviour. On the other hand, per capita household expenses have negative effect. The effect, however, of per capita net farm income and household expenses is very negligible because of the very small chance that the farmer is a saver. Generally, income and expenditure were proved to be significant factors that affect the savings behaviour of the rice farmers. However, most farmers could not save regularly due to low farm income and high household and farm expenditures. Thus, it is highly recommended that government should develop programs or implement policies that will create more jobs for the farmers and their family members. In addition, programs and policies should be implemented to increase farm productivity and income.Keywords: agricultural economics, agricultural finance, binary logistic regression, logit, Philippines, Quezon, rice farmers, savings, savings behaviour
Procedia PDF Downloads 2201318 Development of Palm Kernel Shell Lightweight Masonry Mortar
Authors: Kazeem K. Adewole
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There need to construct building walls with lightweight masonry bricks/blocks and mortar to reduce the weight and cost of cooling/heating of buildings in hot/cold climates is growing partly due to legislations on energy use and global warming. In this paper, the development of Palm Kernel Shell masonry mortar (PKSMM) prepared with Portland cement and crushed PKS fine aggregate (an agricultural waste) is demonstrated. We show that PKSMM can be used as a lightweight mortar for the construction of lightweight masonry walls with good thermal insulation efficiency than the natural river sand commonly used for masonry mortar production.Keywords: building walls, fine aggregate, lightweight masonry mortar, palm kernel shell, wall thermal insulation efficacy
Procedia PDF Downloads 3111317 Hydrological Challenges and Solutions in the Nashik Region: A Multi Tracer and Geochemistry Approach to Groundwater Management
Authors: Gokul Prasad, Pennan Chinnasamy
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The degradation of groundwater resources, attributed to factors such as excessive abstraction and contamination, has emerged as a global concern. This study delves into the stable isotopes of water) in a hard-rock aquifer situated in the Upper Godavari watershed, an agriculturally rich region in India underlain by Basalt. The higher groundwater draft (> 90%) poses significant risks; comprehending groundwater sources, flow patterns, and their environmental impacts is pivotal for researchers and water managers. The region has faced five droughts in the past 20 years; four are categorized as medium. The recharge rates are variable and show a very minimum contribution to groundwater. The rainfall pattern shows vast variability, with the region receiving seasonal monsoon rainfall for just four months and the rest of the year experiencing minimal rainfall. This research closely monitored monsoon precipitation inputs and examined spatial and temporal fluctuations in δ18O and δ2H in both groundwater and precipitation. By discerning individual recharge events during monsoons, it became possible to identify periods when evaporation led to groundwater quality deterioration, characterized by elevated salinity and stable isotope values in the return flow. The locally derived meteoric water line (LMWL) (δ2H = 6.72 * δ18O + 1.53, r² = 0.6) provided valuable insights into the groundwater system. The leftward shift of the Nashik LMWL in relation to the GMWL and LMWL indicated groundwater evaporation (-33 ‰), supported by spatial variations in electrical conductivity (EC) data. Groundwater in the eastern and northern watershed areas exhibited higher salinity > 3000uS/cm, expanding > 40% of the area compared to the western and southern regions due to geological disparities (alluvium vs basalt). The findings emphasize meteoric precipitation as the primary groundwater source in the watershed. However, spatial variations in isotope values and chemical constituents indicate other contributing factors, including evaporation, groundwater source type, and natural or anthropogenic (specifically agricultural and industrial) contaminants. Therefore, the study recommends focused hydro geochemistry and isotope analysis in areas with strong agricultural and industrial influence for the development of holistic groundwater management plans for protecting the groundwater aquifers' quantity and quality.Keywords: groundwater quality, stable isotopes, salinity, groundwater management, hard-rock aquifer
Procedia PDF Downloads 441316 Increase of Atmosphere CO2 Concentration and Its Effects on Culture/Weed Interaction
Authors: J. I. Santos, A. E. Cesarin, C. A. R. Sales, M. B. B. Triano, P. F. R. B. Martins, A. F. Braga, N. J. Neto, A., A. M. Barroso, P. L. C. A. Alves, C. A. M. Huaman
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Climate change projections based on the emission of greenhouse effect gases suggest an increase in the concentration of atmospheric carbon dioxide, in up to 750 ppm. In this scenario, we have significant changes in plant development, and consequently, in agricultural systems. This study aims to evaluate the interaction between culture (Glycine max) and weed (Amaranthus viridis and Euphorbia heterophylla) in two conditions of CO2, 400 and 800 ppm. The results showed that the coexistence of culture with both weed species resulted in a mutual loss, with decrease in dry mass productivity of culture + weeds, in both conditions of CO2. However, when the culture is grown in association with E. heterophylla, total dry mass of culture + weed was smaller at 800 ppm. Soybean was more aggressive in comparison to the A. viridis in both the concentrations of CO2, but not in relation to the E. heterophylla.Keywords: plants interaction, increase of [CO₂], plants of metabolismo C3, glycine max
Procedia PDF Downloads 3901315 Change of Substrate in Solid State Fermentation Can Produce Proteases and Phytases with Extremely Distinct Biochemical Characteristics and Promising Applications for Animal Nutrition
Authors: Paula K. Novelli, Margarida M. Barros, Luciana F. Flueri
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Utilization of agricultural by-products, wheat ban and soybean bran, as substrate for solid state fermentation (SSF) was studied, aiming the achievement of different enzymes from Aspergillus sp. with distinct biological characteristics and its application and improvement on animal nutrition. Aspergillus niger and Aspergillus oryzea were studied as they showed very high yield of phytase and protease production, respectively. Phytase activity was measure using p-nitrophenilphosphate as substrate and a standard curve of p-nitrophenol, as the enzymatic activity unit was the quantity of enzyme necessary to release one μmol of p-nitrophenol. Protease activity was measure using azocasein as substrate. Activity for phytase and protease substantially increased when the different biochemical characteristics were considered in the study. Optimum pH and stability of the phytase produced by A. niger with wheat bran as substrate was between 4.0 - 5.0 and optimum temperature of activity was 37oC. Phytase fermented in soybean bran showed constant values at all pHs studied, for optimal and stability, but low production. Phytase with both substrates showed stable activity for temperatures higher than 80oC. Protease from A. niger showed very distinct behavior of optimum pH, acid for wheat bran and basic for soybean bran, respectively and optimal values of temperature and stability at 50oC. Phytase produced by A. oryzae in wheat bran had optimum pH and temperature of 9 and 37oC, respectively, but it was very unstable. On the other hand, proteases were stable at high temperatures, all pH’s studied and showed very high yield when fermented in wheat bran, however when it was fermented in soybean bran the production was very low. Subsequently the upscale production of phytase from A. niger and proteases from A. oryzae were applied as an enzyme additive in fish fed for digestibility studies. Phytases and proteases were produced with stable enzyme activity of 7,000 U.g-1 and 2,500 U.g-1, respectively. When those enzymes were applied in a plant protein based fish diet for digestibility studies, they increased protein, mineral, energy and lipids availability, showing that these new enzymes can improve animal production and performance. In conclusion, the substrate, as well as, the microorganism species can affect the biochemical character of the enzyme produced. Moreover, the production of these enzymes by SSF can be up to 90% cheaper than commercial ones produced with the same fungi species but submerged fermentation. Add to that these cheap enzymes can be easily applied as animal diet additives to improve production and performance.Keywords: agricultural by-products, animal nutrition, enzymes production, solid state fermentation
Procedia PDF Downloads 3201314 A Comprehensive Study and Evaluation on Image Fashion Features Extraction
Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen
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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.Keywords: convolutional neural network, feature representation, image processing, machine modelling
Procedia PDF Downloads 1321313 Industrial Hemp Agronomy and Fibre Value Chain in Pakistan: Current Progress, Challenges, and Prospects
Authors: Saddam Hussain, Ghadeer Mohsen Albadrani
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Pakistan is one of the most vulnerable countries to climate change. Being a country where 23% of the country’s GDP relies on agriculture, this is a serious cause of concern. Introducing industrial hemp in Pakistan can help build climate resilience in the agricultural sector of the country, as hemp has recently emerged as a sustainable, eco-friendly, resource-efficient, and climate-resilient crop globally. Hemp has the potential to absorb huge amounts of CO₂, nourish the soil, and be used to create various biodegradable and eco-friendly products. Hemp is twice as effective as trees at absorbing and locking up carbon, with 1 hectare (2.5 acres) of hemp reckoned to absorb 8 to 22 tonnes of CO₂ a year, more than any woodland. Along with its high carbon-sequestration ability, it produces higher biomass and can be successfully grown as a cover crop. Hemp can grow in almost all soil conditions and does not require pesticides. It has fast-growing qualities and needs only 120 days to be ready for harvest. Compared with cotton, hemp requires 50% less water to grow and can produce three times higher fiber yield with a lower ecological footprint. Recently, the Government of Pakistan has allowed the cultivation of industrial hemp for industrial and medicinal purposes, making it possible for hemp to be reinserted into the country’s economy. Pakistan’s agro-climatic and edaphic conditions are well-suitable to produce industrial hemp, and its cultivation can bring economic benefits to the country. Pakistan can enter global markets as a new exporter of hemp products. The production of hemp in Pakistan can be most exciting to the workforce, especially for farmers participating in hemp markets. The minimum production cost of hemp makes it affordable to small holding farmers, especially those who need their cropping system to be as highly sustainable as possible. Dr. Saddam Hussain is leading the first pilot project of Industrial Hemp in Pakistan. In the past three years, he has been able to recruit high-impact research grants on industrial hemp as Principal Investigator. He has already screened the non-toxic hemp genotypes, tested the adaptability of exotic material in various agroecological conditions, formulated the production agronomy, and successfully developed the complete value chain. He has developed prototypes (fabric, denim, knitwear) using hemp fibre in collaboration with industrial partners and has optimized the indigenous fibre processing techniques. In this lecture, Dr. Hussain will talk on hemp agronomy and its complete fibre value chain. He will discuss the current progress, and will highlight the major challenges and future research direction on hemp research.Keywords: industrial hemp, agricultural sustainability, agronomic evaluation, hemp value chain
Procedia PDF Downloads 711312 Life Cycle Assessment of Bioethanol from Feedstocks in Thailand
Authors: Thanapat Chaireongsirikul, Apichit Svang-Ariyaskul
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An analysis of mass balance, energy performance, and environmental impact assessment were performed to evaluate bioethanol production in Thailand. Thailand is an agricultural country. Thai government plans to increase the use of alternative energy to 20 percent by 2022. One of the primary campaigns is to promote a bioethanol production from abundant biomass resources such as bitter cassava, molasses and sugarcane. The bioethanol production is composed of three stages: cultivation, pretreatment, and bioethanol conversion. All of mass, material, fuel, and energy were calculated to determine the environmental impact of three types of bioethanol production: bioethanol production from cassava (CBP), bioethanol production from molasses (MBP), and bioethanol production from rice straw (RBP). The results showed that bioethanol production from cassava has the best environmental performance. CBP contributes less impact when compared to the other processes.Keywords: bioethanol production, biofuel, LCA, chemical engineering
Procedia PDF Downloads 3591311 Review on Rainfall Prediction Using Machine Learning Technique
Authors: Prachi Desai, Ankita Gandhi, Mitali Acharya
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Rainfall forecast is mainly used for predictions of rainfall in a specified area and determining their future rainfall conditions. Rainfall is always a global issue as it affects all major aspects of one's life. Agricultural, fisheries, forestry, tourism industry and other industries are widely affected by these conditions. The studies have resulted in insufficient availability of water resources and an increase in water demand in the near future. We already have a new forecast system that uses the deep Convolutional Neural Network (CNN) to forecast monthly rainfall and climate changes. We have also compared CNN against Artificial Neural Networks (ANN). Machine Learning techniques that are used in rainfall predictions include ARIMA Model, ANN, LR, SVM etc. The dataset on which we are experimenting is gathered online over the year 1901 to 20118. Test results have suggested more realistic improvements than conventional rainfall forecasts.Keywords: ANN, CNN, supervised learning, machine learning, deep learning
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