Search results for: precision agriculture

Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

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The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: artificial neural networks, cellular automata, decision support system, pattern recognition

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Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom, Sawanath Treesathon

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As there are several countries which import agriculture product from Thailand, those countries demand Thailand to establish the traceability system. The traceability system is the tool to reduce the risk in the supply chain in a very effective way as it will help the stakeholder in the supply chain to identify the defect point which will reduce the cost of operation in the supply chain. This research is aimed to design the traceability system for Tubtimjun roseapple for exporting to China, and it is the qualitative research. The data was collected from the expert in the tuntimjun roseapple and fruit exporting industry, and the data was used to design the traceability system. The design of the tubtimjun roseapple traceability system was followed the theory of supply chain which starts from the upstream of the supply chain to the downstream of the supply chain to support the process and condition of the exporting which included the database designing, system architecture, user interface design and information technology of the traceability system.

Keywords: design information, technology system, traceability, tubtimjun roseapple

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Authors: Mina Mortazavi

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The common approach in the construction industry for restraint requirements in existing structures or new constructions is to have Non-Structural Components (NSCs) assembled and installed on-site by different MEP subcontractors. This leads to a lack of coordination and higher costs, construction time, and complications due to inaccurate building information modelling (BIM) systems. Introducing NSCs to a consistent BIM system from the beginning of the design process and considering their seismic loads in the analysis and design process can improve coordination and reduce costs and time. One solution is to use prefabricated mounts with attached MEPs delivered as an integral module. This eliminates the majority of coordination complications and reduces design and installation costs and time. An advanced approach is to have as many NSCs as possible installed in the same prefabricated module, which gives the structural engineer the opportunity to consider the involved component weights and locations in the analysis and design of the prefabricated support. This efficient approach eliminates coordination and access issues, leading to enhanced quality control. This research will focus on the existing literature on modular sub-assemblies that are integrated with architectural and structural components. Modular MEP systems take advantage of the precision provided by BIM tools to meet exact requirements and achieve a buildable design every time. Modular installations that include MEP systems provide efficient solutions for the installation of MEP services or components.

Keywords: building services, modularisation, prefabrication, integral building design

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Authors: Saul A. Torres Z., Eduardo Liceaga C., Alfredo Arias M.

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Agriculture in the world falls within the main sources of economic and global needs, so care of crop is extremely important for owners and workers; one of the major causes of loss of product is the pest infection of different types of organisms. We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB"," ANSYS FLUENT"," XFoil " package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi- objective problems can be helpful for future developments. The program has 10 functions developed in MATLAB, these functions are related to each other to enable the development of design, and all these functions are controlled by the principal code "Master.m".

Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, stability, vortex

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Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Ruedee Niyomrath, Somboon Sarasit, Chaisri Tharaswatpipat

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This research aims to study the potential of local waste material in quantity and quality. The potential for such local forms of waste material used as renewable energy for the production of processed agricultural products. The results of this study are useful to producers of agricultural products to use fuel that in local, reduce production costs, and conservation. The results showed that Samut Songkhram is a small province located in the central Thailand, sea area, and subdivided into 3 districts. This province has a population of 80 percent of farmers and agriculture with 50 percent of the area planted to coconut growing. Productivity of coconut help create value for the primacy of the province. Waste materials from coconut have quantity and quality potentials for processing biomass into charcoal as the renewable energy for the production of processed agricultural products.

Keywords: waste, renewable energy, producing of product, processed agricultural products

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Authors: Amer Ait Sidhoum

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Interest in sustainability has gained ground among practitioners, academics and policy-makers due to growing stakeholders’ awareness of environmental and social concerns. This is particularly true for agriculture. However, relatively little research has been conducted on the quantification of social sustainability and the contribution of social issues to the agricultural production efficiency. This research's main objective is to propose a method for evaluating prices of social outputs, more precisely shadow prices, by allowing for the stochastic nature of agricultural production that is to say for production uncertainty. In this article, the assessment of social outputs’ shadow prices is conducted within the methodological framework of nonparametric Data Envelopment Analysis (DEA). An output-oriented directional distance function (DDF) is implemented to represent the technology of a sample of Catalan arable crop farms and derive the efficiency scores the overall production technology of our sample is assumed to be the intersection of two different sub-technologies. The first sub-technology models the production of random desirable agricultural outputs, while the second sub-technology reflects the social outcomes from agricultural activities. Once a nonparametric production technology has been represented, the DDF primal approach can be used for efficiency measurement, while shadow prices are drawn from the dual representation of the DDF. Computing shadow prices is a method to assign an economic value to non-marketed social outcomes. Our research uses cross sectional, farm-level data collected in 2015 from a sample of 180 Catalan arable crop farms specialized in the production of cereals, oilseeds and protein (COP) crops. Our results suggest that our sample farms show high performance scores, from 85% for the bad state of nature to 88% for the normal and ideal crop growing conditions. This suggests that farm performance is increasing with an improvement in crop growth conditions. Results also show that average shadow prices of desirable state-contingent output and social outcomes for efficient and inefficient farms are positive, suggesting that the production of desirable marketable outputs and of non-marketable outputs makes a positive contribution to the farm production efficiency. Results also indicate that social outputs’ shadow prices are contingent upon the growing conditions. The shadow prices follow an upward trend as crop-growing conditions improve. This finding suggests that these efficient farms prefer to allocate more resources in the production of desirable outputs than of social outcomes. To our knowledge, this study represents the first attempt to compute shadow prices of social outcomes while accounting for the stochastic nature of the production technology. Our findings suggest that the decision-making process of the efficient farms in dealing with social issues are stochastic and strongly dependent on the growth conditions. This implies that policy-makers should adjust their instruments according to the stochastic environmental conditions. An optimal redistribution of rural development support, by increasing the public payment with the improvement in crop growth conditions, would likely enhance the effectiveness of public policies.

Keywords: data envelopment analysis, shadow prices, social sustainability, sustainable farming

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Authors: Thapelo Jacob Moloi

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This paper purports to present the findings in relation to the competencies of commercial grain farmers using a classic grounded theory method. A total of about eighteen semi-structured interviews with farmers, former farmers, farm workers, and agriculture experts were conducted. Findings explored competencies in the form of skills, knowledge and personal attributes that commercial grain farmers possess. Skills range from production skills, financial management skill, time management skill, human resource management skill, planning skill to mechanical skill. Knowledge ranges from soil preparation, locality, and technology to weather knowledge. The personal attributes that contribute to shaping a commercial grain farmer are so many, but for this study, seven stood out as a passion, work dedication, self-efficacy, humbleness, intelligence, emotional stability, and patience.

Keywords: grain farming, farming competencies, classic grounded theory, competency model

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Authors: Samira Khalil, Adib Saad, Malek Ali

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The aim of this research is to determine fish species belonging to the order Pleuronectiforme fish found in Syrian marine water confirm or deny the continuity of the previously registered species, and record the unregistered species that appeared during this research for the first time. The research was carried out in the Laboratory of Marine Sciences, Faculty of Agriculture (Tishreen University); fish samples were collected periodically (bi-monthly) from fishermen in landing areas along the Syrian coast caught from depths (3m to 700m), using various mediums. An appropriate hand is available to fishermen on the Syrian coast (cliff bottom, fixed nets, enclosure nets, shelf nest, and manual disposal network; 451 individuals were captured and studied during the research period. During this study, it was found that the Syrian water includes 15 species, including one species recorded for the first time. On the eastern coast of the Mediterranean, it is Pegusa impar.

Keywords: pleuronectiformes, Syrian coast, flatfish, mediterranean

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Authors: Diana Gomez-Cano, J. C. Ochoa-Botero, Roberto Bernal Correa, Yhan Paul Arias

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To obtain high mechanical performance, the fresh conditions of a mortar are decisive. Measuring the absorption of aggregates used in mortar mixes is a fundamental requirement for proper design of the mixes prior to their placement in construction sites. In this sense, absorption is a determining factor in the design of a mix because it conditions the amount of water, which in turn affects the water/cement ratio and the final porosity of the mortar. Thus, this work focuses on the mechanical behavior of recycled mortars manufactured from moisture correction using the Thermogravimetric Balancing Halogen Light (TBHL) technique in comparison with the traditional ASTM C 128 International Standard method. The advantages of using the TBHL technique are favorable in terms of reduced consumption of resources such as materials, energy, and time. The results show that in contrast to the ASTM C 128 method, the TBHL alternative technique allows obtaining a higher precision in the absorption values of recycled aggregates, which is reflected not only in a more efficient process in terms of sustainability in the characterization of construction materials but also in an effect on the mechanical performance of recycled mortars.

Keywords: alternative raw materials, halogen light, recycled mortar, resources optimization, water absorption

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Authors: Vangelis Papadimitropoulos

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This paper is part of the research program “Techno-Social Innovation in the Collaborative Economy”, funded by the Hellenic Foundation for Research and Innovation (H.F.R.I.) for the years 2022-2024. The paper showcases the Open Food Network (OFN) as an open-sourced digital platform supporting short food supply chains in local agricultural production and consumption. The paper outlines the research hypothesis, the theoretical framework, and the methodology of research as well as the findings and conclusions. Research hypothesis: The model of open cooperativism as a vehicle for systemic change in the agricultural sector. Theoretical framework: The research reviews the OFN as an illustrative case study of the three-zoned model of open cooperativism. The OFN is considered a paradigmatic case of the model of open cooperativism inasmuch as it produces commons, it consists of multiple stakeholders including ethical market entities, and it is variously supported by local authorities across the globe, the latter prefiguring the mini role of a partner state. Methodology: Research employs Ernesto Laclau and Chantal Mouffe’s discourse analysis -elements, floating signifiers, nodal points, discourses, logics of equivalence and difference- to analyse the breadth of empirical data gathered through literature review, digital ethnography, a survey, and in-depth interviews with core OFN members. Discourse analysis classifies OFN floating signifiers, nodal points, and discourses into four themes: value proposition, governance, economic policy, and legal policy. Findings: OFN floating signifiers align around the following nodal points and discourses: “digital commons”, “short food supply chains”, “sustainability”, “local”, “the elimination of intermediaries” and “systemic change”. The current research identifies a lack of common ground of what the discourse of “systemic change” signifies on the premises of the OFN’s value proposition. The lack of a common mission may be detrimental to the formation of a common strategy that would be perhaps deemed necessary to bring about systemic change in agriculture. Conclusions: Drawing on Laclau and Mouffe’s discourse theory of hegemony, research introduces a chain of equivalence by aligning discourses such as “agro-ecology”, “commons-based peer production”, “partner state” and “ethical market entities” under the model of open cooperativism, juxtaposed against the current hegemony of neoliberalism, which articulates discourses such as “market fundamentalism”, “privatization”, “green growth” and “the capitalist state” to promote corporatism and entrepreneurship. Research makes the case that for OFN to further agroecology and challenge the current hegemony of industrial agriculture, it is vital that it opens up its supply chains into equivalent sectors of the economy, civil society, and politics to form a chain of equivalence linking together ethical market entities, the commons and a partner state around the model of open cooperativism.

Keywords: sustainability, the digital commons, open cooperativism, innovation

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Authors: Candra Irawan, David Yudianto, Ahsanu Nadiyya, Dewi Anna Br Sitepu, Hanafi, Erna Styani

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Jelly drink was produced from a combination of both natural and synthetic materials, such as acesulfame potassium (acesulfame-K) as synthetic sweetener material. Acesulfame-K content in jelly drink could be determined by High-Performance Liquid Chromatography (HPLC), but this method needed validation due to having a change on the reagent addition step which skips the carrez addition and comparison of mix mobile phase (potassium dihydrogen phosphate and acetonitrile) with ratio from 75:25 to 90:10 to be more efficient and cheap. This study was conducted to evaluate the performance of determination method for acesulfame-K content in the jelly drink by HPLC. The method referred to Deutsches Institut fur Normung European Standard International Organization for Standardization (DIN EN ISO):12856 (1999) about Foodstuffs, Determination of acesulfame-K, aspartame and saccharin. The result of the correlation coefficient value (r) on the linearity test was 0.9987 at concentration range 5-100 mg/L. Detection limit value was 0.9153 ppm, while the quantitation limit value was 1.1932 ppm. The recovery (%) value on accuracy test for sample concentration by spiking 100 mg/L was 102-105%. Relative Standard Deviation (RSD) value for precision and homogenization tests were 2.815% and 4.978%, respectively. Meanwhile, the comparative and stability tests were tstat (0.136) < ttable (2.101) and |µ1-µ2| (1.502) ≤ 0.3×CV Horwitz. Obstinacy test value was tstat < ttable. It can be concluded that the HPLC  method for the determination of acesulfame-K in jelly drink product by HPLC has been valid and can be used for analysis with good performance.

Keywords: acesulfame-K, jelly drink, HPLC, validation

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Authors: Ghulam Haider Haidaree, Nsenda Lukumwena

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Today the world of research enjoys abundant data, available in virtually any field, technology, science, and business, politics, etc. This is commonly referred to as big data. This offers a great deal of precision and accuracy, supportive of an in-depth look at any decision-making process. When and if well used, Big Data affords its users with the opportunity to produce substantially well supported and good results. This paper leans extensively on big data to investigate possible smart solutions to urban mobility and related issues, namely road traffic accidents, its casualties, and fatalities based on multiple factors, including age, gender, location occurrences of accidents, etc. Multiple technologies were used in combination to produce an Information Communication Technology (ICT) based solution with embedded technology. Those technologies include principally Geographic Information System (GIS), Orange Data Mining Software, Bayesian Statistics, to name a few. The study uses the Leeds accident 2016 to illustrate the thinking process and extracts thereof a model that can be tested, evaluated, and replicated. The authors optimistically believe that the proposed model will significantly and smartly help to flatten the curve of road traffic accidents in the fast-growing population densities, which increases considerably motor-based mobility.

Keywords: accident factors, geographic information system, information communication technology, mobility

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Authors: Mustafa M. Bob, Norhan Rahman, Abdalla Elamin, Saud Taher

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The objective of this study was to assess the suitability of Madinah city groundwater for irrigation purposes. Of the twenty three wells that were drilled in different locations in the city for the purposes of this study, twenty wells were sampled for water quality analyses. The United States Department of Agriculture (USDA) classification of irrigation water that is based on Sodium hazard (SAR) and salinity hazard was used for suitability assessment. In addition, the residual sodium carbonate (RSC) was calculated for all samples and also used for irrigation suitability assessment. Results showed that all groundwater samples are in the acceptable quality range for irrigation based on RSC values. When SAR and salinity hazard were assessed, results showed that while all groundwater samples (except one) fell in the acceptable range of SAR, they were either in the high or very high salinity zone which indicates that care should be taken regarding the type of soil and crops in the study area.

Keywords: irrigation suitability, TDS, salinity, SAR

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Authors: Mohamed Mahmoud Hasan, Hoda M. O. Mokhtar

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With the gigantic increment in portable applications use and the spread of positioning and location-aware technologies that we are seeing today, new procedures and methodologies for location-based strategies are required. Location recommendation is one of the highly demanded location-aware applications uniquely with the wide accessibility of social network applications that are location-aware including Facebook check-ins, Foursquare, and others. In this paper, we aim to present a new methodology for location recommendation. The proposed approach coordinates customary spatial traits alongside other essential components including shortest distance, and user interests. We also present another idea namely, "activity trajectory" that represents trajectory that fulfills the set of activities that the user is intrigued to do. The approach dispatched acquaints the related distance value to select trajectory(ies) with minimum cost value (distance) and spatial-area to prune unneeded directions. The proposed calculation utilizes the idea of movement direction to prescribe most comparable N-trajectory(ies) that matches the client's required action design with least voyaging separation. To upgrade the execution of the proposed approach, parallel handling is applied through the employment of a MapReduce based approach. Experiments taking into account genuine information sets were built up and tested for assessing the proposed approach. The exhibited tests indicate how the proposed approach beets different strategies giving better precision and run time.

Keywords: location based recommendation, map-reduce, recommendation system, trajectory search

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Authors: N. Ouslimani, M. T. Abadlia, S. Yakoub, F. Tebbani

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Water has always been synonymous with life and growth. Blue gold is first essential to the survival of the human being whose body consists of more than 65% with the development of industrialization and consumption patterns; volumes of wastewater discharges have increased considerably whether industrial or domestic, waste water must be purified before discharge. Treatment, therefore, aims to reduce the pollution load which contain. The resources in Algeria are limited and unevenly distributed. Thus, to meet all the water needs of the country and to preserve the waters of good quality drinking water supply, one solution would be to use them according to their quality and to irrigate crops for the food or be directed to the irrigation of green areas or sports complex. The purification performance of this STEP has been established since the pH analyzed pollution criteria (7.36) and temperature (16°C), MES (10 mg / l), electrical conductivity (1122 / µs / cm), DBO5 (6mg / l), DCO (15mg / l) meet the discharge standards. Arguably the purified water discharged out of the boumerdes STEP comply with Algerian regulations and can be reused in agriculture. COD biodegradability of the coefficient / BOD5 is 2.5 (less than 3) indicates that of the effluent are biodegradable hence their urban origin.

Keywords: irrigation, recovery, treated, wastewater

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Authors: Alok S Chauhan, Sridhar S., Pradyumna R.

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In the process of precision investment casting of turbine hollow blade/vane components, a part of the dimensional deviations observed in the castings can be attributed to the wax pattern. In the process of injection moulding of wax to produce patterns, heated wax shrinks in size during cooling in the die, leading to a reduction in the dimensions of the pattern. Also, flow and thermal induced residual stresses result in shrinkage & warpage of the component after removal from the die, further adding to the deviations. Injection moulding parameters such as wax temperature, flow rate, packing pressure, etc. affect the flow and thermal behavior of the component and hence are directly responsible for the dimensional deviations. There is a need to precisely determine and control these deviations in order to achieve stringent dimensional accuracies imposed on these castings by aerospace standards. Simulation based approaches provide a platform to predict these dimensional deviations without resorting to elaborate experimentation. In the present paper, Moldex3D simulation package has been utilized to analyze the effect of variations in injection temperature, packing pressure and cooling time on the shrinkage behavior of a stepped pattern. Two types of waxes with different rheological properties have been included in the study to gauge the effect of change in wax on the dimensional deviations. A full factorial design of experiments has been configured with these parameters and results of analysis of variance have been presented.

Keywords: wax patterns, investment casting, pattern die/mould, wax injection, Moldex3D simulation

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Authors: Ruchira Das

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The major Metropolises of India are resultant of Colonial manifestation of Production, Consumption and Sustenance. These cities grew, survived, and sustained on the basic whims of Colonial Power and Administrative Agendas. They were symbols of power, authority and administration. Within them some Colonial Towns remained as small towns within the close vicinity of the major metropolises and functioned as self–sufficient units until peripheral development due to tremendous pressure occurred in the metropolises. After independence huge expansion in Judiciary and Administration system resulted City Oriented Employment. A large number of people started residing within the city or within commutable distance of the city and it accelerated expansion of the cities. Since then Budgetary and Planning expenditure brought a new pace in Economic Activities. Investment in Industry and Agriculture sector generated opportunity of employment which further led towards urbanization. After two decades of Budgetary and Planning economic activities in India, a new era started in metropolitan expansion. Four major metropolises started further expansion rapidly towards its suburbs. A concept of large Metropolitan Area developed. Cities became nucleus of suburbs and rural areas. In most of the cases such expansion was not favorable to the relationship between City and its hinterland due to absence of visualization of Compact Sustainable Development. The search for solutions needs to weigh the choices between Rural and Urban based development initiatives. Policymakers need to focus on areas which will give the greatest impact. The impact of development initiatives will spread the significant benefit to all. There is an assumption that development integrates Economic, Social and Environmental considerations with equal weighing. The traditional narrower and almost exclusive focus on economic criteria as the determinant of the level of development is thus re–described and expanded. The Social and Environmental aspects are equally important as Economic aspect to achieve Sustainable Development. The arrangement of opportunities for Public, Semi – Public facilities for its citizen is very much relevant to development. It is responsibility of the administration to provide opportunities for the basic requirement of its inhabitants. Development should be in terms of both Industrial and Agricultural to maintain a balance between city and its hinterland. Thus, policy is to formulate shifting the emphasis away from Economic growth towards Sustainable Human Development. The goal of Policymaker should aim at creating environments in which people’s capabilities can be enhanced by the effective dynamic and adaptable policy. The poverty could not be eradicated simply by increasing income. The improvement of the condition of the people would have to lead to an expansion of basic human capabilities. In this scenario the suburbs/rural areas are considered as environmental burden to the metropolises. A new living has to be encouraged in the suburban or rural. We tend to segregate agriculture from the city and city life, this leads to over consumption, but this urbanism model attempts both these to co–exists and hence create an interesting overlapping of production and consumption network towards sustainable Rurbanism.

Keywords: socio–economic progress, sustainability, social equity, urbanism

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Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Eva Tolmeijer, Emmanuelle Peters, Veena Kumari, Liam Mason

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Cognitive behavioral therapy for psychosis (CBTp) is effective in many but not all patients, making it important to better understand the factors that determine treatment outcomes. To date, no studies have examined whether neuroimaging can make clinically useful predictions about who will respond to CBTp. To this end, we used machine learning methods that make predictions about symptom improvement at the individual patient level. Prior to receiving CBTp, 22 patients with a diagnosis of schizophrenia completed a social-affective processing task during functional MRI. Multivariate pattern analysis assessed whether treatment response could be predicted by brain activation responses to facial affect that was either socially threatening or prosocial. The resulting models did significantly predict symptom improvement, with distinct multivariate signatures predicting psychotic (r=0.54, p=0.01) and affective (r=0.32, p=0.05) symptoms. Psychotic symptom improvement was accurately predicted from relatively focal threat-related activation across hippocampal, occipital, and temporal regions; affective symptom improvement was predicted by a more dispersed profile of responses to prosocial affect. These findings enrich our understanding of the neurobiological underpinning of treatment response. This study provides a foundation that will hopefully lead to greater precision and tailoring of the interventions offered to patients.

Keywords: cognitive behavioral therapy, machine learning, psychosis, schizophrenia

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Authors: Chia-Jung Li, Li-Te Lin, Kuan-Hao Tsui

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The study identifies SPP1 as a potential gene associated with ovarian aging, revealing a significant decline in its expression in aged ovaries. SPP1, also known as osteopontin (OPN), is a multifunctional glycoprotein involved with regulatory proteins and pro-inflammatory immune chemokines. However, its genetic links to ovarian aging have not been extensively explored. Spatial transcriptomic analyses were conducted on ovaries from young and aged female mice, along with a sample from a 73-year-old individual. Additionally, single-cell RNA sequencing analysis was performed to identify associations between SPP1 and key genes. The study focused on crucial genes, including ITGAV, ITGB1, CD44, MMP3, and FN1, with a particular emphasis on the correlation between SPP1 and ITGB1. The findings indicate a significant decline in SPP1 expression in aged ovaries, which was consistent in the 73-year-old sample. Single-cell RNA sequencing unveiled associations between SPP1 and key genes, emphasizing a strong co-expression correlation between SPP1 and ITGB1. While the study provides valuable insights, further research is necessary to understand the broader implications and potential applications of SPP1 in ovarian aging. Translating these findings to clinical settings requires careful consideration. The identification of SPP1 as a gene implicated in ovarian aging opens new avenues for advancing precision medicine and refining treatment strategies for conditions related to ovarian aging.

Keywords: SPP1, ovarian aging, spatial transcriptomic, single-cell RNA sequencing

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Authors: S. Kumar, R. Sultana

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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 2^nd i.e. [F_10.7 = 18.33, P < 0.05] followed by [F_4.20 = 07.85, P < 0.05] and [F_3.77 = 06.11, P < 0.05] on 4^th and 3^rd day, respectively. Similarly, it was a minimum i.e. [F_0.48 = 84.65, P < 0.05] on the 1^st 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

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Authors: Nazli Uren, Ayse Okur

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Tactile comfort of a textile product is an essential property and a major concern when it comes to customer perceptions and preferences. The subjective nature of comfort and the difficulties regarding the simulation of human hand sensory feelings make it hard to establish a well-accepted link between tactile comfort and objective evaluations. On the other hand, shear behavior of a fabric is a mechanical parameter which can be measured by various objective test methods. The principal aim of this study is to determine the tactile comfort of commercially available denim fabrics by subjective measurements, create a tactile score database for denim fabrics and investigate the relations between tactile comfort and shear behavior. In-plane shear behaviors of 17 different commercially available denim fabrics with a variety of raw material and weave structure were measured by a custom design shear frame and conventional bias extension method in two corresponding diagonal directions. Tactile comfort of denim fabrics was determined via subjective customer evaluations as well. Aforesaid relations were statistically investigated and introduced as regression equations. The analyses regarding the relations between tactile comfort and shear behavior showed that there are considerably high correlation coefficients. The suggested regression equations were likewise found out to be statistically significant. Accordingly, it was concluded that the tactile comfort of denim fabrics can be estimated with a high precision, based on the results of in-plane shear behavior measurements.

Keywords: denim fabrics, in-plane shear behavior, linear regression estimation, tactile comfort

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Authors: Lingling Shui, Shuting Xie

Abstract:

As alternatives to electronic devices, optically active structures from responsive nanomaterials offer great opportunity buildup smart functional sensors. Hereby, we report on droplet microfluidics enabled construction and application of photonic microcapsules (PMCs) for colorimetric temperature microsensors, enabling miniaturization for injectable local micro-area sensing and integration for large-area sensing. Monodispersed PMCs are produced by in-situ photopolymerization of hydrogel shells of cholesteric liquid crystal (CLC)-in-water-in-oil double emulsion droplets prepared using microfluidic devices, with controllable physical structures and chemical compositions. Constructed PMCs exhibit thermal responsive structural color according to the selective Bragg reflection of CLC’s periodical helical structures within the microdroplet’s spherical confinement. Constructed PMCs with tunable size and composition have been successfully applied for monitoring the living cell extracellular temperature via co-incubation with cell suspension, and for detecting human body temperature via a flexible device from assembled PMCs. These PMCs could be flexibly applied in either micro-environment or large-area surface, enabling wide applications for precision temperature monitoring biological activities (e.g. cells or organs), optoelectronic devices working conditions (e.g. temperature indicators under extreme conditions), and etc.

Keywords: droplet, microfluidics, assembly, soft materials, microsensor

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Authors: Mohammad Tayefeh Norooz, Amirhossein Kargarzadeh

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Overweight and obesity as an abnormality are health threatening factors. Body mass index (BMI) above 25 is referred to as overweight and above 30 as obese. Apollo Endosurgery, Inc., a pioneering company in endoscopy surgeries, is poised to revolutionize patient care with its minimally invasive treatment options. Some product solutions are designed to improve patient outcomes and redefine the future of healthcare. Weight gain post-weight-loss surgery may stem from an enlarged stomach opening, reducing fullness and increasing food intake. Apollo Endosurgery's OverStitch system, a minimally invasive approach, addresses this by using sutures to reduce stomach opening size. This reflects Apollo's commitment to transformative improvements in healing endoscopy, emphasizing a shift towards minimally invasive options. The system's versatility and precision in full-thickness suturing offer treatment alternatives, exemplified in applications like Endoscopic Sleeve Gastroplasty for reshaping obesity management. Apollo’s dedication to pioneering advancements suggests ongoing breakthroughs in minimally invasive surgery, positioning the OverStitch systems as a testament to innovation in patient care.

Keywords: apollo endosurgery, endoscopic sleeve gastroplasty, weight loss system, overstitch endoscopic suturing system, therapeutic, perforations, fistula

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Authors: Shripad Kulkarni

Abstract:

Plant disease is an impairment of the normal state of a plant that interrupts or modifies its vital functions. Disease occurs on different parts of plants and cause heavy losses. Diagnosis of Problem is very important before planning any management practice and this can be done based on appearance of the crop, examination of the root and examination of the soil. There are various types of diseases such as biotic (transmissible) which accounts for ~30% whereas , abiotic (not transmissible) diseases are the major one with ~70% incidence. Plant diseases caused by different groups of organism’s belonging fungi, bacteria, viruses, nematodes and few others have remained important in causing significant losses in different crops indicating the urgent need of their integrated management. Various factors favor disease development and different steps and methods are involved in management of diseases under protected condition. Management of diseases through botanicals and bioagents by modifying root and aerial environment, vector management along with care to be taken while managing the disease are analysed.

Keywords: organic production system, diseases, bioagents and polyhouse, agriculture

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Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

Abstract:

Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

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Authors: R. Zh. Abdukerim, D. A. Absatarova, A. T. Aitbayeva, M. A. Askarova, S. T. Turuspekova, E. V. Zhunus

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The resilience of agricultural systems at the global level to climate change and their ability to recover determines the prospects for food security on a global scale. Since climate change will lead to changes in temperatures, precipitation, weather conditions and mass outbreaks of harmful organisms. The issue of adaptation to climate change in the agricultural sector is one of the priorities of Kazakhstan's Development Strategy for the period up to 2050. Since Kazakhstan is an agroindustrial country in which agriculture plays an important economic role. Kazakhstan is the largest potato producer in Central Asia, accounting for about 60% of the total vegetable production, which determines the urgency of solving the problem of increasing yields and quality. The control harmful organisms plays an important role in solving this issue. Due to the fact that climate change can lead to an increase in the number of harmful organisms and, accordingly, to a complete loss of harvest.

Keywords: potato pests, Colorado potato beetle, soil pests, global climate change

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Authors: Pia Ulvenblad, Henrik Barth, Jennie Cederholm BjöRklund, Maya Hoveskog, Per-Ola Ulvenblad

Abstract:

The importance of business model innovation (BMI) is widely recognized. This is also valid for firms in the agri-food industry, closely connected to global challenges. Worldwide food production will have to increase 70% by 2050 and the United Nations’ sustainable development goals prioritize research and innovation on food security and sustainable agriculture. The firms of the agri-food industry have opportunities to increase their competitive advantage through BMI. However, the process of BMI is complex and the implementation of new business models is associated with high degree of risk and failure. Thus, managers from all industries and scholars need to better understand how to address this complexity. Therefore, the research presented in this paper (i) explores different categories of barriers in research literature on business models in the agri-food industry, and (ii) illustrates categories of barriers with empirical cases. This study is addressing the rather limited understanding on barriers for BMI in the agri-food industry, through a systematic literature review (SLR) of 570 peer-reviewed journal articles that contained a combination of ‘BM’ or ‘BMI’ with agriculture-related and food-related terms (e.g. ‘agri-food sector’) published in the period 1990-2014. The study classifies the barriers in several categories and illustrates the identified barriers with ten empirical cases. Findings from the literature review show that barriers are mainly identified as outcomes. It can be assumed that a perceived barrier to growth can often be initially exaggerated or underestimated before being challenged by appropriate measures or courses of action. What may be considered by the public mind to be a barrier could in reality be very different from an actual barrier that needs to be challenged. One way of addressing barriers to growth is to define barriers according to their origin (internal/external) and nature (tangible/intangible). The framework encompasses barriers related to the firm (internal addressing in-house conditions) or to the industrial or national levels (external addressing environmental conditions). Tangible barriers can include asset shortages in the area of equipment or facilities, while human resources deficiencies or negative willingness towards growth are examples of intangible barriers. Our findings are consistent with previous research on barriers for BMI that has identified human factors barriers (individuals’ attitudes, histories, etc.); contextual barriers related to company and industry settings; and more abstract barriers (government regulations, value chain position, and weather). However, human factor barriers – and opportunities - related to family-owned businesses with idealistic values and attitudes and owning the real estate where the business is situated, are more frequent in the agri-food industry than other industries. This paper contributes by generating a classification of the barriers for BMI as well as illustrating them with empirical cases. We argue that internal barriers such as human factors barriers; values and attitudes are crucial to overcome in order to develop BMI. However, they can be as hard to overcome as for example institutional barriers such as governments’ regulations. Implications for research and practice are to focus on cognitive barriers and to develop the BMI capability of the owners and managers of agri-industry firms.

Keywords: agri-food, barriers, business model, innovation

Procedia PDF Downloads 241