Search results for: autonomous agricultural machines

Authors: M. A. Ashour

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As it is known Egypt is one of the countries having oldest sugarcane industry, which goes back to the year 710 AD. Cane plantations are the main agricultural product in five governorates in Upper Egypt (El-Menia, Sohag, Qena, Luxor, and Aswan), producing not less than 16 million tons a year. Eight factories (Abou-korkas, Gena, Nagaa-Hamadi, Deshna, Kous, Armant, Edfuo, and Komombo), located in such upper Egypt governorates generates huge amount of wastes during the manufacturing stage, the so called bagasse which is the fibrous, and cellulosic materials remaining after the era of the sugarcane and the juice extraction, presents about 30% of such wastes. The amount of bagasse generated yearly through the manufacturing stage of the above mentioned 8 factories is approximately about 2.8 million tons, getting red safely of such huge amount, presents a serious environmental problem. Storage of that material openly in the so hot climate in upper Egypt, may cause its self-ignition under air temperature reaches 50 degrees centigrade in summer, due to the remained residual content of sugar. At the same time preparing places for safely storage for such amount is very expensive with respect to the valueless of it. So the best way for getting rid of bagasse is converting it into an added value environmentally friendly material, especially till now the utilization of it is so limited. Since oil pollution became a serious concern, the issue of environmental cleaning arises. With the structure of sugarcane bagasse, which contains fiber and high content of carbon, it can be an adsorbent to adsorb the oil contamination from the water. The present study is a trail to introduce a new material for the purification of water systems to score two goals at once, the first is getting rid of that harmful waste safely, the second is converting it to a commercial valuable material for cleaning, and purifying the water from oil spills, and petroleum pollution. Introduced the new material proved very good performance, and higher efficiency than other similar materials available in the local market, in both closed and open systems. The introduced modified material can absorb 10 times its weight of oil, while don't absorb any water.

Keywords: environment, water resources, agricultural wastes, oil pollution control, sugarcane

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Authors: Laura Piedra-Muñoz, Ángeles Godoy-Durán, Emilio Galdeano-Gómez, Juan C. Pérez-Mesa

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The current agricultural system in some arid and semi-arid areas is not sustainable in the long term. In southeast Spain, groundwater is the main water source and is overexploited, while alternatives like desalination are still limited. The Water Plan for the Mediterranean Basins 2015-2020 indicates a global deficit of 73.42 hm3 and an overexploitation of the aquifers of 205.58hm3. In order to solve this serious problem, two major actions can be taken: increasing available water, and/or improving the efficiency of its use. This study focuses on the latter. The main aim of this study is to present the major factors related to water usage efficiency in farming. It focuses on Almería province, southeast Spain, one of the most arid areas of the country, and in particular on family farms as the main direct managers of water use in this zone. Many of these farms are among the most water efficient in Spanish agriculture, but this efficiency is not generalized throughout the sector. This work conducts a comprehensive assessment of water performance in this area, using on-farm water-use, structural, socio-economic and environmental information. Two statistical techniques are used: descriptive analysis and cluster analysis. Thus, two groups are identified: the least and the most efficient farms regarding water usage. By analyzing both the common characteristics within each group and the differences between the groups with a one-way ANOVA analysis, several conclusions can be reached. The main differences between the two clusters center on the extent to which innovation and new technologies are used in irrigation. The most water efficient farms are characterized by more educated farmers, a greater degree of innovation, new irrigation technology, specialized production and awareness of water issues and environmental sustainability. The research shows that better practices and policies can have a substantial impact on achieving a more sustainable and efficient use of water. The findings of this study can be extended to farms in similar arid and semi-arid areas and contribute to foster appropriate policies to improve the efficiency of water usage in the agricultural sector.

Keywords: cluster analysis, family farms, Spain, water-use efficiency

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Authors: Harsh Sadawarti, Kamal Malik

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Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

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Authors: Madalin Enache, Simona Neagu, Roxana Cojoc, Ioana Gomoiu, Delia Ionela Dobre, Ancuta Roxana Trifoi

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Various types of halophilic and halotolerant microorganisms able to be cultivated in laboratory on culture media with a wide range of sodium chloride content are isolated from several salted environments. The extracellular enzymes of these microorganisms showed the enzymatic activity in these spectrums of salinity thus being attractive for several biotechnological processes developed at high ionic strength. In present work, a number of amylase, protease, esterase, lipase, cellulase, pectinase, xilanases and innulinase were identified for more than 50th bacterial strains isolated from water samples and sapropelic mud from four saline and hypersaline lakes located in Romanian plain. On the other hand, the cellulase and pectinase activity were also detected in some halotolerant microorganisms isolated from secondary agricultural flow of grapes processing. The preliminary data revealed that from totally tested strains seven harbor proteases activity, eight amylase activity, four for esterase and another four for lipase, three for pectinase and for one strain were identified either cellulase or pectinase activity. There were no identified enzymes able to hydrolase innulin added to culture media. Several strains isolated from sapropelic mud showed multiple extracellular enzymatic activities, namely three strains harbor three activities and another seven harbor two activities. The data revealed that amylase and protease activities were frequently detected if compare with other tested enzymes. In the case of pectinase were investigated, their ability to be used for increasing resveratrol recovery from material resulted after grapes processing. In this way, the resulted material from grapes processing was treated with microbial supernatant for several times (two, four and 24 hours) and the content of resveratrol was detected by High Performance Liquid Chromatography method (HPLC). The preliminary data revealed some positive results of this treatment.

Keywords: halophilic microorganisms, enzymes, pectinase, salinity

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Authors: Kiana Taheri

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Rural tourism has garnered significant attention as a catalyst for rural development and sustainability, particularly in regions like Tuscany, Italy, where the convergence of cultural heritage, picturesque landscapes, and agricultural traditions provides a fertile ground for tourism activities. This paper investigates the pivotal role of women entrepreneurs in driving sustainable rural tourism development, with a specific focus on Tuscany. Drawing upon a synthesis of literature on rural tourism, entrepreneurship, and gender studies, this research offers insights into how women entrepreneurs contribute to the economic, social, and environmental dimensions of rural tourism in Tuscany. The conceptual framework of this study is rooted in the evolving landscape of rural development, shaped by shifting paradigms in agricultural policies, such as the Common Agricultural Policy (CAP) of the European Union. This framework underscores the transition from traditional agrarian economies to dynamic rural tourism destinations characterized by a consumer-centric approach and a focus on sustainable development. Against this backdrop, the study delves into the multifaceted contributions of women entrepreneurs within the rural tourism sector. Central to the analysis is the recognition of rural tourism as a nexus of social, cultural, economic, and environmental interactions, wherein women entrepreneurs play a pivotal role in leveraging local resources, preserving cultural heritage, and fostering community engagement. By capitalizing on their unique perspectives, skills, and networks, women entrepreneurs drive innovation, diversification, and inclusivity within the tourism sector, thereby enhancing its resilience and long-term viability. Moreover, the study highlights the symbiotic relationship between rural tourism development and women's empowerment, as evidenced by the increasing prominence of women entrepreneurs in Tuscany's rural economy. Through their leadership roles in small and medium enterprises (SMEs) and agritourism ventures, women entrepreneurs not only contribute to economic growth but also challenge traditional gender norms and empower local communities. A key empirical focus of this research is a comprehensive case study of Tuscany, renowned for its successful rural tourism model and vibrant entrepreneurial ecosystem. Through qualitative interviews, surveys, and archival analysis, the study elucidates the strategies, challenges, and impacts of women entrepreneurs on sustainable rural tourism development in Tuscany. By examining the experiences of women entrepreneurs across diverse sectors of rural tourism, including hospitality, gastronomy, and cultural heritage, the study offers nuanced insights into their contributions to regional development and empowerment. In conclusion, this research contributes to the burgeoning scholarship on rural tourism, entrepreneurship, and gender studies by shedding light on the transformative role of women entrepreneurs in driving sustainable development agendas in rural areas. By elucidating the interplay between gender dynamics, entrepreneurial activities, and tourism development, this study seeks to inform policy interventions and strategic initiatives aimed at fostering inclusive and sustainable rural tourism ecosystems.

Keywords: rural tourism, women empowerment, entrepreneurship, sustainable development, small and medium-sized enterprises (SMEs)

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Authors: Radheshyam Yadav, Ramakrishna Wusirika

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Plant Growth Promoting Bacteria (PGPB) and Arbuscular Mycorrhizal (AM) Fungi are ubiquitous in soil and often very critical for crop yield and agriculture sustainability, and this has motivated the agricultural practices to support and promote PGPB and AM Fungi in agriculture. PGPB can be involved in a range of processes that affect Nitrogen (N) and Phosphorus (P) transformations in soil and thus influence nutrient availability and uptake to the plants. A field study with two wheat cultivars, HD-3086, and HD-2967 was performed in Malwa region, Bathinda of Punjab, India, to evaluate the effect of native and non-native PGPB alone and in combination with AM fungi as an inoculant on wheat grain yield, nutrient uptake and soil health parameters (dehydrogenase, urease, β‐glucosidase). Our results showed that despite an early insignificant increase in shoot length, plants treated with PGPB (Bacillus sp.) and AM Fungi led to a significant increase in shoot growth at maturity, aboveground biomass, nitrogen (45% - 40%) and phosphorus (40% - 34%) content in wheat grains relative to untreated control plants. Similarly, enhanced grain yield and nutrients uptake i.e. copper (27.15% - 36.25%) iron (43% - 53%) and zinc (44% - 47%) was recorded in PGPB and AM Fungi treated plants relative to untreated control. Overall, inoculation with native PGPB alone and in combination with AM Fungi provided benefits to enhance grain yield, wheat biofortification, and improved soil fertility, despite this effect varied depending on different PGPB isolates and wheat cultivars. These field study results provide evidence of the benefits of agricultural practices involving native PGPB and AM Fungi to the plants. These native strains and AM Fungi increased accumulations of copper, iron, and zinc in wheat grains, enhanced grain yield, and soil fertility.

Keywords: AM Fungi, biofortification, PGPB, soil microbial enzymes

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Authors: Vivek Krishna, Nikhil Jain, A. Mary Posonia A., Albert Mayan J

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Terrorism and insurgency are significant global issues that require constant attention and effort from governments and scientists worldwide. To combat these threats, nations invest billions of dollars in developing new defensive technologies to protect civilians. Breakthroughs in vehicle automation have led to the use of sophisticated machines for many dangerous and critical anti-terrorist activities. Our concept of an "Unmanned Ground Vehicle" can carry out tasks such as border security, surveillance, mine detection, and active combat independently or in tandem with human control. The robot's movement can be wirelessly controlled by a person in a distant location or can travel to a pre-programmed destination autonomously in situations where personal control is not feasible. Our defence system comprises two units: the control unit that regulates mobility and the motion tracking unit. The remote operator robot uses the camera's live visual feed to manually operate both units, and the rover can automatically detect movement. The rover is operated by manpower who controls it using a joystick or mouse, and a wireless modem enables a soldier in a combat zone to control the rover via an additional controller feature.

Keywords: robotics, computer vision, Machine learning, Artificial intelligence, future of AI

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Authors: Rakesh Prajapati, Purvik Patel, Avadhoot Rajurkar

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Nowadays, manufacturing industries augment their production lines with modern machining centers backed by CAM software. Several attempts are being made to cut down the programming time for machining complex geometries. Special programs/software have been developed to generate the digital numerical data and to prepare NC programs by using suitable post-processors for different machines. By selecting the tools and manufacturing process then applying tool paths and NC program are generated. More and more complex mechanical parts that earlier were being cast and assembled/manufactured by other processes are now being machined. Majority of these parts require lots of pocketing operations and find their applications in die and mold, turbo machinery, aircraft, nuclear, defense etc. Pocketing operations involve removal of large quantity of material from the metal surface. The modeling of warm cast and clamping a piece of food processing parts which the used of Pro-E and MasterCAM^® software. Pocketing operation has been specifically chosen for toolpath optimization. Then after apply Pocketing toolpath, Multi Tool Selection and Reduce Air Time give the results of software simulation time and experimental machining time.

Keywords: toolpath, part program, optimization, pocket

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Authors: Khaled Nagaty, Heba Nagaty, Gerard McKee

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A signature is a behavioral biometric that is used for authenticating users in most financial and legal transactions. Signatures can be easily forged by skilled forgers. Therefore, it is essential to verify whether a signature is genuine or forged. The aim of any signature verification algorithm is to accommodate the differences between signatures of the same person and increase the ability to discriminate between signatures of different persons. This work presented in this paper proposes an automatic signature verification system to indicate whether a signature is genuine or not. The system comprises four phases: (1) The pre-processing phase in which image scaling, binarization, image rotation, dilation, thinning, and connecting ridge breaks are applied. (2) The feature extraction phase in which global and local features are extracted. The local features are minutiae points, curvature orientation, and curve plateau. The global features are signature area, signature aspect ratio, and Hu moments. (3) The post-processing phase, in which false minutiae are removed. (4) The classification phase in which features are enhanced before feeding it into the classifier. k-nearest neighbors and support vector machines are used. The classifier was trained on a benchmark dataset to compare the performance of the proposed offline signature verification system against the state-of-the-art. The accuracy of the proposed system is 92.3%.

Keywords: signature, ridge breaks, minutiae, orientation

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Authors: Chokri Slim

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The objective of this research is attempting to respond to this question: Is there a significant difference between the regression model and statistical learning models in predicting credit risk management? A Multiple Linear Regression (MLR) model was compared with neural networks including Multi-Layer Perceptron (MLP), and a Support vector regression (SVR). The population of this study includes 50 listed Banks in Tunis Stock Exchange (TSE) market from 2000 to 2016. Firstly, we show the factors that have significant effect on the quality of loan portfolios of banks in Tunisia. Secondly, it attempts to establish that the systematic use of objective techniques and methods designed to apprehend and assess risk when considering applications for granting credit, has a positive effect on the quality of loan portfolios of banks and their future collectability. Finally, we will try to show that the bank governance has an impact on the choice of methods and techniques for analyzing and measuring the risks inherent in the banking business, including the risk of non-repayment. The results of empirical tests confirm our claims.

Keywords: credit risk management, multiple linear regression, principal components analysis, artificial neural networks, support vector machines

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Authors: Soumen Mitra, Aparna Saha

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The perceived link between the city and the countryside is evolving rapidly and is getting shifted away from the assumptions of mainstream paradigms to new conceptual networks where rural-urban links are being redefined. In this conceptual field, the fringe interface is still considered as a transitional zone between city and countryside, and is defined as a diffused area rather than a discrete territory. In developing countries fringe areas are said to have both rural and urban characteristics but are devoid of basic municipal facilities. Again, when the urban core areas envelopes the fringe areas along with it the character of fringe changes but services are not well facilitated which in turn results to uneven growth, rapid and haphazard development. One of the major services present in fringe areas is inter-linkages in terms of transit corridors. Planning for the appropriate and sustainable future of fringe areas requires a sheer focus on these corridors pertaining to transit facility, for better accessibility and mobility. Inducing a transit facility plan enhances the various facilities and also increases their proximity for user groups. The study focuses on the western fringe region of Kolkata metropolis which is a major source of industrial hub and housing sector, thus converting the agricultural lands into non-agricultural use. The study emphasizes on providing transit facilities both physical (stops, sheds, terminals, etc.) and operational (ticketing system, route prioritization, integration of transit modes, etc.), to facilitate the region as well as accelerate the growth pattern systematically. Hence, the scope of this work is on the basis of prevailing conditions in fringe areas and attempts for an effective transit facility plan. The strategies and recommendations are in terms of road widening, service coverage, feeder route prioritization, bus stops facilitation, pedestrian facilities, etc, which in turn enhances the region’s growth pattern. Thus, this context of transit facility planning acts as a catalytic agent to avoid the future unplanned growth and accelerates it towards an integrated development.

Keywords: feeder route, fringe, municipal planning, transit facility

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Authors: J. E. Mendes, T. T. de Barros, O. B. G. de Assis, J. D. C. Pessoa

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Chitosan, a natural polysaccharide of β-1,4-linked glucosamine residues, is a biopolymer obtained primarily from the exoskeletons of crustaceans. Interest in polymeric materials increases year by year. Chitosan is one of the most plentiful biomaterials, with a wide range of pharmaceutical, biomedical, industrial and agricultural applications. Chitosan nanoparticles were synthesized via the ionotropic gelation of chitosan with sodium tripolyphosphate (TPP). Two concentrations of chitosan microparticles (0.1 and 0.2%) were synthesized. In this study, it was possible to synthesize and characterize microparticles of chitosan biomaterial and this will be used for future applications in cell anchorage for 3D bioprinting.

Keywords: chitosan microparticles, biomaterial, scaffold, bioprinting

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Authors: Safoin Aktaou, Aya Al Masri, Kamel Guerchouche, Malorie Martin, Fouad Maaloul

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Introduction: In the ‘Magnetic Resonance Imaging (MRI)’ department, all workers involved in preparing the patient, setting it up, tunnel cleaning, etc. are likely to be exposed to ‘ElectroMagnetic fields (EMF)’ emitted by the MRI device. Exposure to EMF can cause adverse radio-biological effects to workers. The purpose of this study is to propose an organizational process to manage and control EMF risks. Materials and methods: The study was conducted at seven MRI departments using machines with 1.5 and 3 Tesla magnetic fields. We assessed the exposure of each one by measuring the two electromagnetic fields (static and dynamic) at different distances from the MRI machine both inside and around the examination room. Measurement values were compared with British and American references (those of the UK's ‘Medicines and Healthcare Regulatory Agency (MHRA)’ and the ‘American Radiology Society (ACR)’). Results: Following the results of EMF measurements and their comparison with the recommendations of learned societies, a zoning system that adapts to needs of different MRI services across the country has been proposed. In effect, three risk areas have been identified within the MRI services. This has led to the development of a good practice guide related to the magnetic protection of MRI workers. Conclusion: The guide established by our study is a standard that allows MRI workers to protect themselves against the risk of electromagnetic fields.

Keywords: comparison with international references, measurement of electromagnetic fields, magnetic protection of workers, magnetic resonance imaging

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Authors: A. Alao Olumuyiwa

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Health hazards reported to be associated with exposure to electromagnetic radiations which include brain tumors, genotoxic effects, neurological effects, immune system deregulation, allergic responses and some cardiovascular effects are discussed under a closed tabular model in this study. This review however showed that there is strong and robust evidence that chronic exposures to electromagnetic frequency across the spectrum, through strength, consistency, biological plausibility and many dose-response relationships, may result in brain cancer and other carcinogenic disease symptoms. There is therefore no safe threshold because of the genotoxic nature of the mechanism that may however be involved. The discussed study explains that the cell phone has induced effects upon the blood –brain barrier permeability and the cerebellum exposure to continuous long hours RF radiation may result in significant increase in albumin extravasations. A physical Biomodeling approach is however employed to review this health effects using Specific Absorption Rate (SAR) of different GSM machines to critically examine the symptoms such as a decreased loco motor activity, increased grooming and reduced memory functions in a variety of animal spices in classified grouped and sub grouped models.

Keywords: brain cancer, electromagnetic radiations, physical biomodeling, specific absorption rate (SAR)

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Authors: Inom S. Normatov, Abulqosim Muminov, Parviz I. Normatov

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Problems of food security and the preservation of reserved zones in the region of Central Asia under the conditions of the climate change induced by the placement and construction of large reservoirs are considered. The criteria for the optimum placement and construction of reservoirs that entail the minimum impact on the environment are established. The need for the accounting of climatic parameters is shown by the calculation of the water quantity required for the irrigation of agricultural lands.

Keywords: adaptation, biodiversity, food security, water reservoir, risk

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Authors: Katja Mikhailovich, Barbara Pamphilon

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Farmer training in Papua New Guinea has focused mainly on technology transfer approaches. This has primarily benefited men and often excluded women whose literacy, low education and role in subsistence crops has precluded participation in formal training. The paper discusses an approach that uses both a brokerage model of agricultural extension to link smallholders with private sector agencies and an innovative family team’s approach that aims to support the economic empowerment of women in families and encourages sustainable and gender equitable farming and business practices.

Keywords: women, economic development, agriculture, training

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Authors: Nur Sarma, Paul M. Tuohy, Siniša Djurović

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This paper presents an in-depth investigation of the effects of several grid supply harmonic voltages on the stator currents of an example wound rotor induction machine. The observed effects of higher order grid supply harmonics are identified using a finite element time stepping transient model, as well as a time-stepping electromagnetic model. In addition, a number of analytical equations to calculate the spectral content of the stator currents are presented in the paper. The presented equations are validated through comparison with the obtained spectra predicted using the finite element and electromagnetic models. The presented study provides a better understanding of the origin of supply harmonic effects identified in the stator currents of the example wound rotor induction machine. Furthermore, the study helps to understand the effects of higher order supply harmonics on the harmonic emissions of the wound rotor induction machine.  

Keywords: wound rotor induction machine, supply harmonics, current spectrum, power spectrum, power quality, harmonic emmisions, finite element analysis

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: Byoungjoon Yu, Jihwan Park, Sujung Sin, Junghyun Im, Minsoo Park, Sehwan Park, Seunghee Park

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In this paper, we propose a technology to monitor the soundness of an Internet-based bridge using a non-conductive inspection function. There has been a collapse accident due to the aging of the bridge structure, and it is necessary to prepare for the deterioration of the bridge. The NDT/SHM system for maintenance of existing bridge structures requires a large number of inspection personnel and expensive inspection costs, and access of expensive and large equipment to measurement points is required. Because current drone inspection equipment can only be inspected through camera, it is difficult to inspect inside damage accurately, and the results of an internal damage evaluation are subjective, and it is difficult for non-specialists to recognize the evaluation results. Therefore, it is necessary to develop NDT/SHM techniques for maintenance of new-concept bridge structures that allow for free movement and real-time evaluation of measurement results. This work is financially supported by Korea Ministry of Land, Infrastructure, and Transport (MOLIT) as 'Smart City Master and Doctor Course Grant Program' and a grant (14SCIP-B088624-01) from Construction Technology Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: Structural Health Monitoring, SHM, non-contact sensing, nondestructive testing, NDT, Internet of Things, autonomous self-driving drone

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Authors: Abdul Mannan Akhtar

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In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.

Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection

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Authors: Mohammadreza Delfieh, Seyed Ali Mohammad Modarres Sanavy, Rouzbeh Farhoudi

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Fennel is of most important medicinal plants which is widely used in food and pharmaceutical industries. In order to investigate the effect of different nitrogen nutritional systems including chemical, organic and biologic ones at different plant densities on yield, yield components and seed essential oil content and yield of this valuable medicinal plant, a field experiment was carried out in 2013-2014 agricultural season at Islamic Azad University of Shoushtar agricultural college in split plot design with 18 treatments and based on completely randomized blocks design. Different nitrogen system treatments consisting of: 1. N1 or control (Uniformly spreading urea fertilizer in the plot, 50% at planting time and 50% at stem elongation), 2. N2 (Uniformly spreading 50% of urea fertilizer in the plot at planting time and spraying the other 50% of urea fertilizer at stem elongation on fennel foliage), 3. N3 or cow manure, 4. N4 or biofertilizer (Inoculation of fennel seeds with Azotobacter and Azospirillum), 5. N5 or Integrated-1 (Cow manure + uniformly spreading urea fertilizer in the plot at stem elongation), 6. N6 or Integrated-2 (Cow manure + Inoculation of fennel seeds with Azotobacter and Azospirillum) were applied to the main plots. Three fennel densities consisting of: 1. FD1 (60 plant/m2), 2. FD2 (80 plant/m2) and 3. FD3 (100 plant/m2) were applied to subplots. Results showed that all of the traits were significantly affected by applied treatments (P 0.01). The interaction between treatments also were significant at 5 percent level for shoot dry weight and at 1 percent level for other traits. Based on the results, using the Integrated-1 treatment at 100 plant per m2 produced 94.575 g/m2 seed yield containing 3.375 percent of essential oil. Utilization of such combination not only could lead to a desirable fennel quantity and quality, but also is more consistent with environment.

Keywords: fennel (foeniculum vulgare mill.), nutritional system, nitrogen, biofertilizer, organic fertilizer, chemical fertilizer, density

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Authors: Alondra Balbuena Medina, Carlos Diaz Delgado, Aleida Yadira Vilchis Fránces

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In Mexico, each year news is disseminated about the ravages of floods, such as the total loss of housing, damage to the fields; the increase of the costs of the food, derived from the losses of the harvests, coupled with health problems such as skin infection, etc. In addition to social problems such as delinquency, damage in education institutions and the population in general. The flooding is a consequence of heavy rains, tropical storms and or hurricanes that generate excess water in drainage systems that exceed its capacity. In urban areas, heavy rains can be one of the main factors in causing flooding, in addition to excessive precipitation, dam breakage, and human activities, for example, excessive garbage in the strainers. In agricultural areas, these can hardly achieve large areas of cultivation. It should be mentioned that for both areas, one of the significant impacts of floods is that they can permanently affect the livelihoods of many families, cause damage, for example in their workplaces such as farmlands, commercial or industry areas and where services are provided. In recent years, Information and Communication Technologies (ICT) have had an accelerated development, being reflected in the growth and the exponential evolution of the innovation giving; as a result, the daily generation of new technologies, updates, and applications. Innovation in the development of Information Technology applications has impacted on all areas of human activity. They influence all the orders of life of individuals, reconfiguring the way of perceiving and analyzing the world such as, for instance, interrelating with people as individuals and as a society, in the economic, political, social, cultural, educational, environmental, etc. Therefore the present work describes the creation of a system of calculation of flood costs for housing areas, retail establishments and agricultural areas from the Mexican Republic, based on the use and application of geotechnical tools being able to be useful for the benefit of the sectors of public, education and private. To generate analysis of hydrometereologic affections and with the obtained results to realize the Geoinformatics tool was constructed from two different points of view: the geoinformatic (design and development of GIS software) and the methodology of flood damage validation in order to integrate a tool that provides the user the monetary estimate of the effects caused by the floods. With information from the period 2000-2014, the functionality of the application was corroborated. For the years 2000 to 2009 only the analysis of the agricultural and housing areas was carried out, incorporating for the commercial establishment's information of the period 2010 - 2014. The method proposed for the resolution of this research project is a fundamental contribution to society, in addition to the tool itself. Therefore, it can be summarized that the problems that are in the physical-geographical environment, conceiving them from the point of view of the spatial analysis, allow to offer different alternatives of solution and also to open up slopes towards academia and research.

Keywords: floods, technological innovation, monetary estimation, spatial analysis

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Authors: García López

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The Government Departments of Health have the task of informing and educating citizens about public health issues. For this, they use channels like Twitter, key in the search for health information and the propagation of content. The tweets, important in the virality of the content, may contain emotions that influence the contagion and exchange of knowledge. The goal of this study is to perform an analysis of the emotional projection of health information shared on Twitter by official American accounts: the disease control account CDCgov, National Institutes of Health, NIH, the government agency HHSGov, and the professional organization PublicHealth. For this, we used Tone Analyzer, an International Business Machines Corporation (IBM) tool specialized in emotion detection in text, corresponding to the categorical model of emotion representation. For 15 days, all tweets from these accounts were analyzed with the emotional analysis tool in text. The results showed that their tweets contain an important emotional load, a determining factor in the success of their communications. This exposes that official accounts also use subjective language and contain emotions. The predominance of emotion joy over sadness and the strong presence of emotions in their tweets stimulate the virality of content, a key in the work of informing that government health departments have.

Keywords: emotions in tweets, emotion detection in the text, health information on Twitter, American health official accounts, emotions on Twitter, emotions and content

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Authors: S. Cobos-Guzman

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This paper presents the results of a mechatronic design based on a 4-wheel omnidirectional mobile robot that can be used in indoor logistic applications. The low-level control has been selected using two open-source hardware (Raspberry Pi 3 Model B+ and Arduino Mega 2560) that control four industrial motors, four ultrasound sensors, four optical encoders, a vision system of two cameras, and a Hokuyo URG-04LX-UG01 laser scanner. Moreover, the system is powered with a lithium battery that can supply 24 V DC and a maximum current-hour of 20Ah.The Robot Operating System (ROS) has been implemented in the Raspberry Pi and the performance is evaluated with the selection of the sensors and hardware selected. The mechatronic system is evaluated and proposed safe modes of power distribution for controlling all the electronic devices based on different tests. Therefore, based on different performance results, some recommendations are indicated for using the Raspberry Pi and Arduino in terms of power, communication, and distribution of control for different devices. According to these recommendations, the selection of sensors is distributed in both real-time controllers (Arduino and Raspberry Pi). On the other hand, the drivers of the cameras have been implemented in Linux and a python program has been implemented to access the cameras. These cameras will be used for implementing a deep learning algorithm to recognize people and objects. In this way, the level of intelligence can be increased in combination with the maps that can be obtained from the laser scanner.

Keywords: autonomous, indoor robot, mechatronic, omnidirectional robot

Procedia PDF Downloads 177

Authors: Deepak Loura

Abstract:

Climate change is considered one of the major environmental problems of the 21st century and a lasting change in the statistical distribution of weather patterns over periods ranging from decades to millions of years. Agriculture and climate change are internally correlated with each other in various aspects, as the threat of varying global climate has greatly driven the attention of scientists, as these variations are imparting a negative impact on global crop production and compromising food security worldwide. The fast pace of development and industrialization and indiscriminate destruction of the natural environment, more so in the last century, have altered the concentration of atmospheric gases that lead to global warming. Carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (NO) are important biogenic greenhouse gases (GHGs) from the agricultural sector contributing to global warming and their concentration is increasing alarmingly. Agricultural productivity can be affected by climate change in 2 ways: first, directly, by affecting plant growth development and yield due to changes in rainfall/precipitation and temperature and/or CO₂ levels, and second, indirectly, there may be considerable impact on agricultural land use due to snow melt, availability of irrigation, frequency and intensity of inter- and intra-seasonal droughts and floods, soil organic matter transformations, soil erosion, distribution and frequency of infestation by insect pests, diseases or weeds, the decline in arable areas (due to submergence of coastal lands), and availability of energy. An increase in atmospheric CO₂ promotes the growth and productivity of C3 plants. On the other hand, an increase in temperature, can reduce crop duration, increase crop respiration rates, affect the equilibrium between crops and pests, hasten nutrient mineralization in soils, decrease fertilizer- use efficiencies, and increase evapotranspiration among others. All these could considerably affect crop yield in long run. Climate resilient agriculture consisting of adaptation, mitigation, and other agriculture practices can potentially enhance the capacity of the system to withstand climate-related disturbances by resisting damage and recovering quickly. Climate resilient agriculture turns the climate change threats that have to be tackled into new business opportunities for the sector in different regions and therefore provides a triple win: mitigation, adaptation, and economic growth. Improving the soil organic carbon stock of soil is integral to any strategy towards adapting to and mitigating the abrupt climate change, advancing food security, and improving the environment. Soil carbon sequestration is one of the major mitigation strategies to achieve climate-resilient agriculture. Climate-smart agriculture is the only way to lower the negative impact of climate variations on crop adaptation before it might affect global crop production drastically. To cope with these extreme changes, future development needs to make adjustments in technology, management practices, and legislation. Adaptation and mitigation are twin approaches to bringing resilience to climate change in agriculture.

Keywords: climate change, global warming, crop production, climate resilient agriculture

Procedia PDF Downloads 75

Authors: T. Pakulski, L. Kryza, A. Linossier

Abstract:

The BEar Articulated TeleRobotic Inspection and Clasping Extremity is a lightweight, 5 DoF robotic manipulator for the Berlin Educational Assistant Rover (BEAR). BEAR is one of the educational planetary rovers developed under the Space Rover projects at the Chair of Space Technology of the Technische Universität Berlin. The projects serve to conduct research and train engineers by developing rovers for competitions like the European Rover Challenge and the DLR SpaceBot Cup. BEATRICE is the result of a cost-driven design process to deliver a simple but capable platform for a variety of competition tasks: object grasping and manipulation, inspection, instrument wielding and more. The manipulator’s simple mechatronic design, based on a combination of servomotors and stepper motors with planetary gearboxes, also makes it a practical tool for developing embedded control systems. The platform’s initial implementation relies on tele-operated control but is fully instrumented for future autonomous functionality. This paper describes BEATRICE’s development from its preliminary link model to its structural and mechatronic design, embedded control and AI and T. In parallel, it examines the influence of budget constraints and high personnel turnover commonly associated with student teams on the manipulator’s design. Finally, it comments on the utility of robot design projects for educating future engineers.

Keywords: education, low-cost, manipulator, robotics, rover

Procedia PDF Downloads 257

Authors: Mokhtar Nikgoo

Abstract:

Definition of dam: A dam is one of the most important and widely used engineering structures, which means stopping or changing the course of water on a river. A lake is formed behind the dam, which is called (reservoir). Water is stored in the tank to be used when needed. The dam building industry is a great service to mankind in the use of water and land resources. If they build the dam in a suitable place, they will prevent floods. The water that collects behind the dam and in the dam's lake and reservoir is a valuable reserve for drinking by people and animals. Dry agricultural lands are also irrigated with this water. In addition, in many dams, the pressure caused by the water fall is directed by turbines, and the turbines move the power generation devices and provide power from electricity

Keywords: dam, shaft, gallery, spillway, power plant

Procedia PDF Downloads 63

Authors: Kwadwo Afari Gyan

Abstract:

Cities are growing at unprecedented levels. Meanwhile, governments in the Global South are already overwhelmed by this growth and are unable to provide infrastructure proactively as expected. As a result, urban residents resort to providing their own infrastructure, such as drainage systems, as part of self-built housing development. Their small-scale, incremental housing practices, which often represent the formation of dense and diverse housing types, styles, and ages, have been identified to affect the planning of drainage systems at the regional scale. Such developments reflect the varied, affordable responses as part of a collective effort to curb regional problems, specifically flooding in this case. However, while some are included in this collective action, others are excluded as they are unable to afford to be included. This phenomenon, in addition to the formation of new autonomous localities, has led to challenges in mitigating flooding and has affected resilience to climate change. Using a qualitative approach, this paper explores how the mismatch between housing development, which occurs at an individual scale, and drainage infrastructure, which is provided at a regional scale, affects a regional effort to mitigate flooding in Tema, Ghana. It seeks to explore and reveal a relationship between affordability and inclusiveness. It also explores how density and diversity influence public infrastructure provision and their connection with affordability.

Keywords: climate change, affordability, inclusivity, equity, contextualization, regionalism

Procedia PDF Downloads 99

Authors: Mehmet Savsar, Majid Aldaihani

Abstract:

Flexible Manufacturing Systems (FMS) are used to produce a variety of parts on the same equipment. Therefore, their utilization is higher than traditional machining systems. Higher utilization, on the other hand, results in more frequent equipment failures and additional need for maintenance. Therefore, it is necessary to carefully analyze operational characteristics and productivity of FMS or Flexible Manufacturing Cells (FMC), which are smaller configuration of FMS, before installation or during their operation. Appropriate models should be developed to determine production rates based on operational conditions, including equipment reliability, availability, and repair capacity. In this paper, a stochastic model is developed for an automated FMC system, which consists of two machines served by two robots and a single repairman. The model is used to determine system productivity and equipment utilization under different operational conditions, including random machine failures, random repairs, and limited repair capacity. The results are compared to previous study results for FMC system with sufficient repair capacity assigned to each machine. The results show that the model will be useful for design engineers and operational managers to analyze performance of manufacturing systems at the design or operational stages.

Keywords: flexible manufacturing, FMS, FMC, stochastic modeling, production rate, reliability, availability

Procedia PDF Downloads 518

Authors: Carolina Zambrana, Grover Zurita

Abstract:

The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

Procedia PDF Downloads 81