10 research outputs found

    Defect classification of radius shaping in the tire curing process using Fine-Tuned Deep Neural Network

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    The curing process or vulcanization process is the final stage of the tire manufacturing process, where the properties of the tire compound change from rubber-plastic material to become elastic by forming cross-links in its molecular structure. The green tire is formed in the curing process, which is placed on the bottom mould. The inside of the green tire surrounds the bladder. The top mould will close to carry out the next curing process. In closing the mould, there is a shaping process of forming a green tire placed on the bladder and given a proportional pressure. Improper or abnormal radius shaping results cause seventy percent of product defects. This paper proposed abnormal detection of radius shaping in the curing process using Fine-tuned Deep Neural Network (DNN). Several DNN models have been examined to analyze an optimized DNN model for abnormal detection of radius shaping in the curing process. The fine-tuned DNN architecture has been exported for the curing system. The DNN was trained with a training accuracy of 97.88%, a validation accuracy of 95%, a testing accuracy of 100%, and a loss of 4.93%

    A survey of the application of soft computing to investment and financial trading

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    Pertanika Journal of Science & Technology

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    Pertanika Journal of Science & Technology

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    Intelligent Control of Bulk Tobacco Curing Schedule Using LS-SVM- and ANFIS-Based Multi-Sensor Data Fusion Approaches

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    The bulk tobacco flue-curing process is followed by a bulk tobacco curing schedule, which is typically pre-set at the beginning and might be adjusted by the curer to accommodate the need for tobacco leaves during curing. In this study, the controlled parameters of a bulk tobacco curing schedule were presented, which is significant for the systematic modelling of an intelligent tobacco flue-curing process. To fully imitate the curer’s control of the bulk tobacco curing schedule, three types of sensors were applied, namely, a gas sensor, image sensor, and moisture sensor. Feature extraction methods were given forward to extract the odor, image, and moisture features of the tobacco leaves individually. Three multi-sensor data fusion schemes were applied, where a least squares support vector machines (LS-SVM) regression model and adaptive neuro-fuzzy inference system (ANFIS) decision model were used. Four experiments were conducted from July to September 2014, with a total of 603 measurement points, ensuring the results’ robustness and validness. The results demonstrate that a hybrid fusion scheme achieves a superior prediction performance with the coefficients of determination of the controlled parameters, reaching 0.9991, 0.9589, and 0.9479, respectively. The high prediction accuracy made the proposed hybrid fusion scheme a feasible, reliable, and effective method to intelligently control over the tobacco curing schedule

    Participation of smallholder farmers in the production of high-value commodities: The case of smallholder tobacco farmers in

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    Participation in the production of high-value export commodities is important in increasing incomes and in enhancing smallholder farmers’ livelihoods. However, the level of their participation may be limited by several factors. Despite the limiting factors, smallholder tobacco farming has gained popularity, especially for the Zimbabwean tobacco industry. Since the Fast Track Land Reform Programme (FTLRP), the tobacco industry in Zimbabwe has seen an influx of smallholder farmers who have since dominated the industry producing over half of the national total tobacco output. The participation by smallholder farmers in tobacco production can be influenced by many factors, the main being income realisation. However, for farmers to realise reasonable incomes, they should be able to produce reasonable levels of good quality tobacco otherwise their farming would be in vain. It has been shown in the literature that smallholder farmers can be constrained by several factors to produce high levels of produce and these factors may include one or more of the following; lack of capital, lack of productive assets, lack of tobacco production skills, lack of financial resources to finance productive activities properly, lack of access to land to expand production among others. Given this background, this study sought to assess the participation of smallholder farmers in tobacco production in terms of quantities and qualities produced given the differences in their productive capacities. The study utilised both primary and secondary data for analysis. Primary data were collected from individual farmers and contract firms’ representatives. The unit of analysis was the smallholder farmer. Primary data were collected through structured questionnaires and a semi-structured interview guide for the contract representatives. Secondary data for the 2018 season were obtained from TIMB. Descriptive statistics, binary logistic regression analysis and multiple linear regression analysis were used to analyse the data. The descriptive statistics results showed that; the majority of the tobacco farmers had low levels of education and they relied mainly on farm incomes for survival. Concerning farm assets, the results showed that; on average, farmers own at least one of the following traditional assets; plough, scotch cart, cattle, storage facility, tobacco curing barn, (athough among the farmers some had indicated that they do not own curing facilities but used hired facilities to cure tobacco). Modern assets like tractors, ox-drawn ridgers and truck motor vehicles were owned by only a few farmers. The results further showed that contracted farmers were more productive and produced better quality tobacco than independent tobacco producers. The binary regression results showed that Ox-drawn ridgers, ploughs, having had a contract before, pricing, distance to the market, age of the farmer, type of curing facility, number of extension visits, number of bales produced and access to credit were significant factors influencing farmers’ participation in contract farming. However, four of the tested factors; tractors, cattle, number of hectares utilised for tobacco farming and number of years in tobacco farming were insignificant in influencing participation in contract farming. The results from the multiple linear regression analysis showed that the number of hectares utilised, the number of bales produced, market preferred, household size, tobacco production training, tractors, and type of curing facility were significant factors influencing the quality of tobacco produce. The other four variables that were tested; farmer category, type of energy used, being a member of a peer group and the number of years in tobacco farming; had no significant effect on the quality of tobacco produced by smallholder farmers. The study recommended that farmers should try and invest in commercial assets such as tractors, modern curing facilities, irrigation systems and other modern equipment that have potential to highly boost production rather than traditional assets like ox-drawn ploughs. The study also recommended that farmers should aim at maximising quantity per hectare of tobacco planted rather than planting larger crop areas they are unable to finance properly. Finally, it is recommended that farmers should get training on tobacco grading to avoid product quality loses that come with improper grading.Thesis (PhD) -- Faculty of Science and Agriculture, 202

    Participation of smallholder farmers in the production of high-value commodities: The case of smallholder tobacco farmers in

    Get PDF
    Participation in the production of high-value export commodities is important in increasing incomes and in enhancing smallholder farmers’ livelihoods. However, the level of their participation may be limited by several factors. Despite the limiting factors, smallholder tobacco farming has gained popularity, especially for the Zimbabwean tobacco industry. Since the Fast Track Land Reform Programme (FTLRP), the tobacco industry in Zimbabwe has seen an influx of smallholder farmers who have since dominated the industry producing over half of the national total tobacco output. The participation by smallholder farmers in tobacco production can be influenced by many factors, the main being income realisation. However, for farmers to realise reasonable incomes, they should be able to produce reasonable levels of good quality tobacco otherwise their farming would be in vain. It has been shown in the literature that smallholder farmers can be constrained by several factors to produce high levels of produce and these factors may include one or more of the following; lack of capital, lack of productive assets, lack of tobacco production skills, lack of financial resources to finance productive activities properly, lack of access to land to expand production among others. Given this background, this study sought to assess the participation of smallholder farmers in tobacco production in terms of quantities and qualities produced given the differences in their productive capacities. The study utilised both primary and secondary data for analysis. Primary data were collected from individual farmers and contract firms’ representatives. The unit of analysis was the smallholder farmer. Primary data were collected through structured questionnaires and a semi-structured interview guide for the contract representatives. Secondary data for the 2018 season were obtained from TIMB. Descriptive statistics, binary logistic regression analysis and multiple linear regression analysis were used to analyse the data. The descriptive statistics results showed that; the majority of the tobacco farmers had low levels of education and they relied mainly on farm incomes for survival. Concerning farm assets, the results showed that; on average, farmers own at least one of the following traditional assets; plough, scotch cart, cattle, storage facility, tobacco curing barn, (athough among the farmers some had indicated that they do not own curing facilities but used hired facilities to cure tobacco). Modern assets like tractors, ox-drawn ridgers and truck motor vehicles were owned by only a few farmers. The results further showed that contracted farmers were more productive and produced better quality tobacco than independent tobacco producers. The binary regression results showed that Ox-drawn ridgers, ploughs, having had a contract before, pricing, distance to the market, age of the farmer, type of curing facility, number of extension visits, number of bales produced and access to credit were significant factors influencing farmers’ participation in contract farming. However, four of the tested factors; tractors, cattle, number of hectares utilised for tobacco farming and number of years in tobacco farming were insignificant in influencing participation in contract farming. The results from the multiple linear regression analysis showed that the number of hectares utilised, the number of bales produced, market preferred, household size, tobacco production training, tractors, and type of curing facility were significant factors influencing the quality of tobacco produce. The other four variables that were tested; farmer category, type of energy used, being a member of a peer group and the number of years in tobacco farming; had no significant effect on the quality of tobacco produced by smallholder farmers. The study recommended that farmers should try and invest in commercial assets such as tractors, modern curing facilities, irrigation systems and other modern equipment that have potential to highly boost production rather than traditional assets like ox-drawn ploughs. The study also recommended that farmers should aim at maximising quantity per hectare of tobacco planted rather than planting larger crop areas they are unable to finance properly. Finally, it is recommended that farmers should get training on tobacco grading to avoid product quality loses that come with improper grading.Thesis (PhD) -- Faculty of Science and Agriculture, 202

    Applied Ecology and Environmental Research 2017

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    Mathematical model of interactions immune system with Micobacterium tuberculosis

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    Tuberculosis (TB) remains a public health problem in the world, because of the increasing prevalence and treatment outcomes are less satisfactory. About 3 million people die each year and an estimated one third of the world's population infected with Mycobacterium Tuberculosis (M.tb) is latent. This is apparently related to incomplete understanding of the immune system in infection M.tb. When this has been known that immune responses that play a role in controlling the development of M.tb is Macrophages, T Lymphocytes and Cytokines as mediators. However, how the interaction between the two populations and a variety of cytokines in suppressing the growth of Mycobacterium tuberculosis germ is still unclear. To be able to better understand the dynamics of infection with M tuberculosis host immune response is required of a model.One interesting study on the interaction of the immune system with M.tb mulalui mathematical model approach. Mathematical model is a good tool in understanding the dynamic behavior of a system. With the mediation of mathematical models are expected to know what variables are most responsible for suppressing the growth of Mycobacterium tuberculosis germ that can be a more appropriate approach to treatment and prevention target is to develop a vaccine. This research aims to create dynamic models of interaction between macrophages (Macrophages resting, macrophages activated and macrophages infected), T lymphocytes (CD4 + T cells and T cells CD8 +) and cytokine (IL-2, IL-4, IL-10,IL-12,IFN-dan TNF-) on TB infection in the lung. To see the changes in each variable used parameter values derived from experimental literature. With the understanding that the variable most responsible for defense against Mycobacterium tuberculosis germs, it can be used as the basis for the development of a vaccine or drug delivery targeted so hopefully will improve the management of patients with tuberculosis. Mathematical models used in building Ordinary Differential Equations (ODE) in the form of differential equation systems Non-linear first order, the equation contains the functions used in biological systems such as the Hill function, Monod function, Menten- Kinetic Function. To validate the system used 4th order Runge Kutta method with the help of software in making the program Matlab or Maple to view the behavior and the quantity of cells of each population

    Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року

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    Second International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2021). Kryvyi Rih, Ukraine, May 19-21, 2021.Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року
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