Search results for: concircular vector field

Authors: Nadeem Munawar, David Galbraith, Tariq Mahmood

Abstract:

Rodenticides are often included as part of an integrated pest management approach for managing rodent species since they are relatively quick and inexpensive to apply. The current field study was conducted to evaluate the effectiveness of formulated baits of zinc phosphide (2%) and the second generation anticoagulant brodifacoum (0.005%) against field rats inhabiting a wheat-groundnut cropping system. Burrow baiting was initiated at the early flowering stages of the respective crops, and continued through three growth stages (tillering / peg formation, flowering, and maturity). Three treatments were done at equal time intervals, with the final baiting being about 2 weeks before harvest. Treatment efficacy of the trials was assessed through counts of active rodent burrows before and after treatments at the three growth stages of these crops. The results indicated variable degrees of reduction in burrow activities following the three bait applications. The reductions in rodent activity in wheat were: 88.8% (at tillering), 92%, (at flowering/grain formation), and 95.5% (at maturity). In groundnut, the rodent activities were reduced by 91.8%, 93.5% and 95.8% at sowing, peg formation, and maturity stages, respectively. The estimated mortality at all three growth stages of both wheat and groundnut ranged between 60-85%. We recommend that a field efficacy study should be conducted with zinc phosphide and brodifacoum bait formulations to determine their field performance in the reduction of agricultural damage by rodent pest species. It is a promising alternative approach for use of the most potent second-generation anticoagulant (brodifacoum) in resistance management, particularly with respect to reducing environmental risks and secondary poisoning.

Keywords: brodifacoum, burrow baiting, second-generation anticoagulant, synergistic effect

Procedia PDF Downloads 116

Authors: Mulue Girmay Gebreslasie

Abstract:

Entomopathogenic fungi are naturally safe and eco-friendly biological agents. Their potential of host specificity and ease handling made them appealing options to substitute synthetic pesticides in pest control programs. However, they are highly delicate and unstable under field conditions. Therefore, the current experiment was held to search out persistent fungal strains by defining the relationship between invitro heat tolerance and field persistence. Current results on leaf and soil persistence assay revealed that strains of Metarhizium species, M. pingshaense (F2685), M. pingshaense (MS2) and M. brunneum (F709) exhibit maximum cumulative CFUs count, relative survival rate and least percent of CFUs reductions showed significant difference at 7 days and 28 days post inoculations (dpi) in hot seasons from sampled soils and leaves and in cold season from soil samples. Whereas relative survival of B. brongniartii (TNO6) found significantly higher in cold weather leaf treatment application as compared to hot season and found as persistent as other fungal strains, while higher deterioration of fungal conidia seen with M. pingshaense (MS2). In the current study, strains of Beauveria brongniartii (TNO6) and Cordyceps javanica (Czy-LP) were relatively vulnerable in field condition with utmost colony forming units (CFUs) reduction and least survival rates. Further, the relationship of the two parameters (heat tolerance and field persistence) was seen with strong linear positive correlations elucidated that heat test could be used in selection of field persistent fungal strains for hot season applications.

Keywords: integrated pest management, biopesticides, Insect pathology and microbial control, entomology

Procedia PDF Downloads 87

Authors: Mohamed H. Khalifa, Fikry I. El-Shahawi, Nabil A. Mansour

Abstract:

The cotton leafworm, Spodoptera littoralis (Boisduval) is a major insect pest of vegetables and cotton crops in Egypt, and exhibits different levels of tolerance to certain insecticides. Chlorantraniliprole has been registered recently in Egypt for control this insect. The susceptibilities of three S. littoralis populations collected from El Behaira governorate, north Egypt to chlorantraniliprole were determined by leaf-dipping technique on 4^th instar larvae. Obvious variation of toxicity was observed among the laboratory susceptible, and three field populations with LC₅₀ values ranged between 1.53 µg/ml and 6.22 µg/ml. However, all the three field populations were less susceptible to chlorantraniliprole than a laboratory susceptible population. The most tolerant populations were sampled from El Delengat (ED) Province where S. littoralis had been frequently challenged by insecticides. Certain enzyme activity assays were carried out to be correlated with the mechanism of the observed field population tolerance. All field populations showed significantly enhanced activities of detoxification enzymes compared with the susceptible strain. The regression analysis between chlorantraniliprole toxicities and enzyme activities revealed that the highest correlation is between α-esterase or β-esterase (α-β-EST) activity and collected field strains susceptibility, otherwise this correlation is not significant (P > 0.05). Synergism assays showed the ED and susceptible strains could be synergized by known detoxification inhibitors such as piperonyl butoxide (PBO), triphenyl phosphate (TPP) and diethyl-maleate (DEM) at different levels (1.01-8.76-fold and 1.09-2.94 fold, respectively), TPP showed the maximum synergism in both strains. The results show that there is a correlation between the enzyme activity and tolerance, and carboxylic-esterase (Car-EST) is likely the main detoxification mechanism responsible for tolerance of S. littoralis to chlorantraniliprole.

Keywords: chlorantraniliprole, detoxification enzymes, Egypt, Spodoptera littoralis

Procedia PDF Downloads 269

Authors: Chariton Christou, David Cornwell

Abstract:

Production Sharing Contract (PSC) is the type of contract that is being used widely in our time. The financial crisis made the governments tightfisted and they do not have the resources to participate in a development of a field. Therefore, more and more countries introduce the PSC. The companies have the power and the money to develop the field with their own way. The main problem is the transparency of oil and gas companies especially in the PSC and how this can be achieved. Many discussions have been made especially in the U.K. What we are suggesting is a dynamic financial simulation with the help of a flow meter. The flow meter will count the production of each field every day (it will be installed in a pipeline). The production will be the basic input of the simulation. It will count the profit, the costs and more according to the information of the flow meter. In addition it will include the terms of the contract and the costs that have been paid. By all these parameters the simulation will be able to present in real time the information of a field (taxes, employees, R-factor). By this simulation the company will share some information with the government but not all of them. The government will know the taxes that should be paid and what is the sharing percentage of it. All of the other information could be confidential for the company. Furthermore, oil company could control the R-factor by changing the production each day to maximize its sharing percentages and as a result of this the profit. This idea aims to change the way that governments 'control' oil companies and bring a transparency evolution in the industry. With the help of a simulation every country could be next to the company and have a better collaboration.

Keywords: production sharing contracts, transparency, simulation

Procedia PDF Downloads 366

Authors: Zabihullah Mahdi, Khwaja Naweed Seddiqi

Abstract:

Afghanistan is located in a tectonically complex and dynamic area, surrounded by rocks that originated on the mother continent of Gondwanaland. The northern Afghanistan basin, which runs along the country's northern border, has the potential for petroleum generation and accumulation. The Amu Darya basin has the largest petroleum potential in the region. Sedimentation occurred in the Amu Darya basin from the Jurassic to the Eocene epochs. Kashkari oil field is located in northern Afghanistan's Amu Darya basin. The field structure consists of a narrow northeast-southwest (NE-SW) anticline with two structural highs, the northwest limb being mild and the southeast limb being steep. The first oil production well in the Kashkari oil field was drilled in 1976, and a total of ten wells were drilled in the area between 1976 and 1979. The amount of original oil in place (OOIP) in the Kashkari oil field, based on the results of surveys and calculations conducted by research institutions, is estimated to be around 140 MMbbls. The objective of this study is to increase recoverable oil reserves in the Kashkari oil field through the implementation of low-salinity water flooding (LSWF) enhanced oil recovery (EOR) technique. The LSWF involved conducting a core flooding laboratory test consisting of four sequential steps with varying salinities. The test commenced with the use of formation water (FW) as the initial salinity, which was subsequently reduced to a salinity level of 0.1%. Afterwards, the numerical simulation model of core scale oil recovery by LSWF was designed by Computer Modelling Group’s General Equation Modeler (CMG-GEM) software to evaluate the applicability of the technology to the field scale. Next, the Kahskari oil field simulation model was designed, and the LSWF method was applied to it. To obtain reasonable results, laboratory settings (temperature, pressure, rock, and oil characteristics) are designed as far as possible based on the condition of the Kashkari oil field, and several injection and production patterns are investigated. The relative permeability of oil and water in this study was obtained using Corey’s equation. In the Kashkari oilfield simulation model, three models: 1. Base model (with no water injection), 2. FW injection model, and 3. The LSW injection model were considered for the evaluation of the LSWF effect on oil recovery. Based on the results of the LSWF laboratory experiment and computer simulation analysis, the oil recovery increased rapidly after the FW was injected into the core. Subsequently, by injecting 1% salinity water, a gradual increase of 4% oil can be observed. About 6.4% of the field, is produced by the application of the LSWF technique. The results of LSWF (salinity 0.1%) on the Kashkari oil field suggest that this technology can be a successful method for developing Kashkari oil production.

Keywords: low salinity water flooding, immiscible displacement, kashkari oil field, twophase flow, numerical reservoir simulation model

Procedia PDF Downloads 30

Authors: Fernández-Brito David, Lopez-Medina Javier Alonso, Murillo-Bracamontes Eduardo Antonio, Palomino-Ovando Martha Alicia, Gervacio-Arciniega José Juan

Abstract:

Magnetic Force Microscopy (MFM) is an Atomic Force Microscopy (AFM) technique that characterizes, at a nanometric scale, the magnetic properties of ferromagnetic materials. Conventional MFM works by scanning in two different AFM modes. The first one is tapping mode, in which the cantilever has short-range force interactions with the sample, with the purpose to obtain the topography. Then, the lift AFM mode starts, raising the cantilever to maintain a fixed distance between the tip and the surface of the sample, only interacting with the magnetic field forces of the sample, which are long-ranged. In recent years, there have been attempts to improve the MFM technique. Bimodal MFM was first theoretically developed and later experimentally proven. In bimodal MFM, the AFM internal piezoelectric is used to cause the cantilever oscillations in two resonance modes simultaneously, the first mode detects the topography, while the second is more sensitive to the magnetic forces between the tip and the sample. However, it has been proven that the cantilever vibrations induced by the internal AFM piezoelectric ceramic are not optimal, affecting the bimodal MFM characterizations. Moreover, the Secondary Resonance Magnetic Force Microscopy (SR-MFM) was developed. In this technique, a coil located below the sample generates an external magnetic field. This alternating magnetic field excites the cantilever at a second frequency to apply the Bimodal MFM mode. Nonetheless, for ferromagnetic materials with a low coercive field, the external field used in SR-MFM technique can modify the magnetic domains of the sample. In this work, a Hybrid Bimodal MFM (HB-MFM) technique is proposed. In HB-MFM, the bimodal MFM is used, but the first resonance frequency of the cantilever is induced by the magnetic field of the ferromagnetic sample due to its vibrations caused by a piezoelectric element placed under the sample. The advantages of this new technique are demonstrated through the preliminary results obtained by HB-MFM on a hard disk sample. Additionally, traditional two pass MFM and HB-MFM measurements were compared.

Keywords: magnetic force microscopy, atomic force microscopy, magnetism, bimodal MFM

Procedia PDF Downloads 64

Authors: P. Abhishesh, B. S. Ryuh, Y. S. Oh, H. J. Moon, R. Akanksha

Abstract:

This paper discusses about the conceptual design and development of the control system software using Programmable logic controller (PLC) for autonomous driving and agricultural operations of Multipurpose Agricultural Robot Platform (MARP). Based on given initial conditions by field analysis and desired agricultural operations, the structural design development of MARP is done using modelling and analysis tool. PLC, being robust and easy to use, has been used to design the autonomous control system of robot platform for desired parameters. The robot is capable of performing autonomous driving and three automatic agricultural operations, viz. hilling, mulching, and sowing of seeds in the respective order. The input received from various sensors on the field is later transmitted to the controller via ZigBee network to make the changes in the control program to get desired field output. The research is conducted to provide assistance to farmers by reducing labor hours for agricultural activities by implementing automation. This study will provide an alternative to the existing systems with machineries attached behind tractors and rigorous manual operations on agricultural field at effective cost.

Keywords: agricultural operations, autonomous driving, MARP, PLC

Procedia PDF Downloads 358

Authors: H. Shokouhmand, M. Tajerian

Abstract:

At this paper velocity profile modeling and heat transfer in the micro heat pipes by using electrohydrodynamic (EHD) field at the transient regime have been studied. In the transient flow, one dimensional and two phase fluid flow and heat transfer for micro heat pipes with square cross section, have been studied. At this model Coulomb and dielectrophoretic forces are considered. Coupled, non-linear equations governed on the model (continuity, momentum, and energy equations) have been solved simultaneously by numerical methods. Transient behavior of affecting parameters e.g. substrate temperature, velocity of coolant liquid, radius of curvature and coolant liquid pressure, has been verified. By obtaining and plotting the mentioned parameters, it has been shown that the EHD field enhances the heat transfer process. So, the time required to reach the steady state regime decreases from 16 seconds to 2.4 seconds after applying EHD field. Another result has been observed implicitly that by increasing the heat input the effect of EHD field became more significant. The numerical results of model predict the experimental results available in the literature successfully, and it has been observed there is a good agreement between them.

Keywords: micro heat pipe, transient modeling, electrohydrodynamics, capillary, meniscus

Procedia PDF Downloads 258

Authors: E. M. S. Azzam, S. A. Ahmed, H. H. Mohamed, M. A. Adly, E. A. M. Gad

Abstract:

In this work we prepared 3-(p-methyl) phenyl-5-thionyl-1,2,4-triazoline (C1). The nanostructure of the prepared C1 compound was fabricated by assembling on silver nanoparticles. The UV and TEM analyses confirm the assembling of C1 compound on silver nanoparticles. The effect of C1 compound on the removal of Iron (II) from Iron contaminated samples and industrial wastewater samples (produced water from oil processing facility) were studied before and after their assembling on silver nanoparticles. The removal of Iron was studied at different concentrations of FeSO4 solution (5, 14 and 39 mg/l) and field sample concentration (661 mg/l). In addition, the removal of Iron (II) was investigated at different times. The Prepared compound and its nanostructure with AgNPs show highly efficient in removing the Iron ions. Quantum chemical descriptors using DFT was discussed. The output of the study pronounces that the C1 molecule can act as chelating agent for Iron (II).

Keywords: triazole derivatives, silver nanoparticles, iron (II), oil field

Procedia PDF Downloads 650

Authors: Ezzat Abd El Lateef

Abstract:

Agroforestry means combining the management of trees with productive agricultural activities, especially in semiarid regions where crop yield increases are limited in agroforestry systems due to the fertility and microclimate improvements and the large competitive effect of trees with crops for water and nutrients, in order to assess the effect of agroforestry of some field crops with citrus trees as an approach to establish biodiversity in fruit tree plantations. Three field crops, i.e., maize, soybean and sunflower, were inter-planted with seedless orange trees (4*4 m) or were planted as solid plantings. The results for the trees indicated a larger fruit yield was obtained when soybean and sunflowers were interplant with citrus. Statistically significant effects (P<0.05) were found for maize grain and biological yields, with increased yields when grown as solid planting. There were no differences in the yields of soya bean and sunflower, where the yields were very similar between the two cropping systems. It is evident from the trials that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Maize, unlike the other crops, was more sensitive to shade conditions under agroforestry practice and not preferred in the biodiversity system. The potential of agroforestry to improve or increase biodiversity is efficient as the understorey crops are usually C4 species, and the overstorey trees are invariably C3 species in agroforestry. Improvement in interplant species is most likely if the understorey crop is a C3 species, which are usually light saturated in the open, and partial shade may have little effect on assimilation or by a concurrent reduction in transpiration. It could be concluded that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Some field crops could be employed successfully, like soybean or sunflowers, while others like maize are sensitive to incorporate in agroforestry system.

Keywords: agroforestry, field crops, C3 and C4 plants, yield

Procedia PDF Downloads 177

Authors: Zabihullah Mahdi, Khwaja Naweed Seddiqi

Abstract:

Afghanistan is located in a tectonically complex and dynamic area, surrounded by rocks that originated on the mother continent of Gondwanaland. The northern Afghanistan basin, which runs along the country's northern border, has the potential for petroleum generation and accumulation. The Amu Darya basin has the largest petroleum potential in the region. Sedimentation occurred in the Amu Darya basin from the Jurassic to the Eocene epochs. Kashkari oil field is located in northern Afghanistan's Amu Darya basin. The field structure consists of a narrow northeast-southwest (NE-SW) anticline with two structural highs, the northwest limb being mild and the southeast limb being steep. The first oil production well in the Kashkari oil field was drilled in 1976, and a total of ten wells were drilled in the area between 1976 and 1979. The amount of original oil in place (OOIP) in the Kashkari oil field, based on the results of surveys and calculations conducted by research institutions, is estimated to be around 140 MMbbls. The objective of this study is to increase recoverable oil reserves in the Kashkari oil field through the implementation of low-salinity water flooding (LSWF) enhanced oil recovery (EOR) technique. The LSWF involved conducting a core flooding laboratory test consisting of four sequential steps with varying salinities. The test commenced with the use of formation water (FW) as the initial salinity, which was subsequently reduced to a salinity level of 0.1%. Afterward, the numerical simulation model of core scale oil recovery by LSWF was designed by Computer Modelling Group’s General Equation Modeler (CMG-GEM) software to evaluate the applicability of the technology to the field scale. Next, the Kahskari oil field simulation model was designed, and the LSWF method was applied to it. To obtain reasonable results, laboratory settings (temperature, pressure, rock, and oil characteristics) are designed as far as possible based on the condition of the Kashkari oil field, and several injection and production patterns are investigated. The relative permeability of oil and water in this study was obtained using Corey’s equation. In the Kashkari oilfield simulation model, three models: 1. Base model (with no water injection), 2. FW injection model, and 3. The LSW injection model was considered for the evaluation of the LSWF effect on oil recovery. Based on the results of the LSWF laboratory experiment and computer simulation analysis, the oil recovery increased rapidly after the FW was injected into the core. Subsequently, by injecting 1% salinity water, a gradual increase of 4% oil can be observed. About 6.4% of the field is produced by the application of the LSWF technique. The results of LSWF (salinity 0.1%) on the Kashkari oil field suggest that this technology can be a successful method for developing Kashkari oil production.

Keywords: low-salinity water flooding, immiscible displacement, Kashkari oil field, two-phase flow, numerical reservoir simulation model

Procedia PDF Downloads 30

Authors: Teoman Ozer, Ozlem Orhan

Abstract:

This study deals with symmetry group properties and conservation laws of partial differential equations. We give a geometrical interpretation of notion of μ-prolongations of vector fields and of the related concept of μ-symmetry for partial differential equations. We show that these are in providing symmetry reduction of partial differential equations and systems and invariant solutions.

Keywords: λ-symmetry, μ-symmetry, classification, invariant solution

Procedia PDF Downloads 311

Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov

Abstract:

For optimal unbiased filter as mean-square and in the case of functioning anomalous noises in the observation memory channel, we have proved insensitivity of filter to inaccurate knowledge of the anomalous noise intensity matrix and its equivalence to truncated filter plotted only by non anomalous components of an observation vector.

Keywords: mathematical expectation, filtration, anomalous noise, memory

Procedia PDF Downloads 356

Authors: Rahim Jafari, Tuba Okutucu-Özyurt

Abstract:

The hydrodynamics and heat transfer characteristics of a vaporized elongated bubble in a rectangular microchannel have been simulated based on Cahn-Hilliard phase-field method. In the simulations, the initially nucleated bubble starts growing as it comes in contact with superheated water. The growing shape of the bubble compared with the available experimental data in the literature.

Keywords: microchannel, boiling, Cahn-Hilliard method, simulation

Procedia PDF Downloads 418

Authors: Zabihullah Mahdi, Mahdi Nayab, Sadaf Jalal, Navid Seddiqi

Abstract:

Hydrocarbons represent an important natural resource for the rehabilitation and sustainable development of Afghanistan. In this paper, the use of waterflooding is demonstrated for the petroleum reservoirs of the Kashkari oil field in northern Afghanistan. The technique is based on the Buckley–Leverett frontal-displacement theory, which enables computation of the progress of the waterfront in the reservoir. The relative permeabilities of oil and water, the residual oil saturation, and the irreducible water saturation are obtained from a laboratory experiment. The technique is applied to the laboratory plane-reservoir model to investigate the displacement mechanism and is then compared with the theoretical calculation. Lastly, the technique is applied to the Kashkari oil field to predict the feasible amount of oil that could be produced from this reservoir.

Keywords: Buckley–Leverett, waterflooding, petroleum reservoir engineering, two-phase flow, immiscible displacement, porous media, relative permeability

Procedia PDF Downloads 187

Authors: Adel M. Zakri, Mohammed A. Al-Saleh, Judith. K. Brown, Ali M. Idris

Abstract:

Betasatellites are small circular single stranded DNA molecules found associated with begomoviruses on field symptomatic plants. Their genome size is about half that of the helper begomovirus, ranging between 1.3 and 1.4 kb. The helper begomoviruses are usually members of the family Geminiviridae. Okra leaves showing vein thickening were collected from okra plants growing in Jazan, Saudi Arabia. Total DNA was extracted from leaves and used as a template to amplify circular DNA using rolling circle amplification (RCA) technology. Products were digested with PstI to linearize the helper viral genome(s), and associated DNA satellite(s), yielding a 2.8kbp and 1.4kbp fragment, respectively. The linearized fragments were cloned into the pGEM-5Zf (+) vector and subjected to DNA sequencing. The 2.8 kb fragment was identified as Cotton leaf curl Gezira virus genome, at 2780bp, an isolate closely related to strains reported previously from Saudi Arabia. A clone obtained from the 1.4 kb fragments he 1.4kb was blasted to GeneBank database found to be a betasatellite. The genome of betasatellite was 1357-bp in size. It was found to be a recombinant containing one fragment (877-bp) that shared 91% nt identity with Cotton leaf curl Gezira betasatellite [KM279620], and a smaller fragment [133--bp) that shared 86% nt identity with Tomato leaf curl Sudan virus [JX483708]. This satellite is thus a recombinant between a malvaceous-infecting satellite and a solanaceous-infecting begomovirus.

Keywords: begomovirus, betasatellites, cotton leaf curl Gezira virus, okra plants

Procedia PDF Downloads 335

Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

Abstract:

The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: artificial neural networks (ANNs), classifier algorithms, credit risk assessment, logistic regression, machine Learning, support vector machines

Procedia PDF Downloads 98

Authors: Tadeus Atraskevic, Asch Dalbajobas, Mazahistas Pukuotukas

Abstract:

The novel ferroelectric properties appeared in the recent ten years. Many scientists consider them as non-statement science. Nevertheless, many papers are published. The Mean field theory takes an important place in the theory of ferroelectric materials which can be applied for Boson induced laser systems for ‘Star Track’ soldiers. The novel Laser, which was produced in The Vilnius Bambalio University is a ‘now-how’ among other laser systems. The laser can produce power of 30 kW during 15 seconds. Its size and compatibility distinguishes it among other devices and safety gadgets. Scientists of Bambalio University have already patented the device. The most interesting in this innovations is the process of operation. Merely it may be operated through a bottle a beer what makes the measurement so convenient, that an ordinary scientist can process all stuff without significant effort just by taking pleasure by drinking a bottle of beer. Here we would like to report on the laser system and present our unique developments.

Keywords: laser, boson, ferroelectrics, mean field theory

Procedia PDF Downloads 169

Authors: Freya Zinovieff

Abstract:

In the age of the Anthropocene, all ecosystems, no matter how remote, is influenced by the relations between humans and technology. These influences are evidenced by current extinction rates, changes in species diversity, and species adaptation to pollution. Field recording is a tool through which we are able to document the extent to which life forms associated with the place are entangled with human-technology relationships. This paper documents the convergence of interaction between technologies, species, and landscape via an auto-ethnographic account of a field recording taken from a cell phone tower in Bali, Indonesia. In the recording, we hear a confluence of relations where critter and technology meet. The electrical hum of the tower merges with frogs and the amaranthine throb of crickets, in such a way that it is hard to tell where technology begins and the voice of creatures ends. The outcomes of this venture resulted in a framework for evaluating the sensorial relations within field recording. The framework calls for the soundscape to be understood as a multilayered ontology through which there is a convergence of multispecies relationships, or entanglements, across time and geographic location. These entanglements are not necessarily obvious. Sometimes quiet, sometimes elusive, sometimes only audible through the mediated conduit of digital technology. The paper argues that to be aware of these entanglements is to open ourselves to a type of beauty that is firmly rooted in the present paradigm of extinction and loss. By virtue of this understanding, we are bestowed with an opportunity to embrace the grave reality of the current sixth mass extinction and move forwards with what activist Joanna Macy calls the compassionate action.

Keywords: anthropocene, human-technology relationships, multispecies ethnography, field recording

Procedia PDF Downloads 147

Authors: Daniel E. Martin, Chenghai Yang

Abstract:

Variable-rate aerial application systems are becoming more readily available; however, aerial applicators typically only use the systems for constant-rate application of materials, allowing the systems to compensate for upwind and downwind ground speed variations. Much of the resistance to variable-rate aerial application system adoption in the U.S. pertains to applicator’s trust in the systems to turn on and off automatically as desired. The objectives of this study were to evaluate a commercially available variable-rate aerial application system under field conditions to demonstrate both the response and accuracy of the system to desired application rate inputs. This study involved planting oats in a 35-acre fallow field during the winter months to establish a uniform green backdrop in early spring. A binary (on/off) prescription application map was generated and a variable-rate aerial application of glyphosate was made to the field. Airborne multispectral imagery taken before and two weeks after the application documented actual field deposition and efficacy of the glyphosate. When compared to the prescription application map, these data provided application system response and accuracy information. The results of this study will be useful for quantifying and documenting the response and accuracy of a commercially available variable-rate aerial application system so that aerial applicators can be more confident in their capabilities and the use of these systems can increase, taking advantage of all that aerial variable-rate technologies have to offer.

Keywords: variable-rate, aerial application, remote sensing, precision application

Procedia PDF Downloads 467

Authors: Wameed Alghazali, Shawn Kenny, Paul J. Van Geel

Abstract:

Settlement of municipal solid waste (MSW) in landfills can be represented by mechanical settlement, which is instantaneous and time-dependent creep components, and biodegradation-induced settlement. Mechanical settlement is governed by the physical characteristics of MSW and the applied overburden pressure. Several research studies used oedometers and different size compression cells to evaluate the primary and mechanical creep compression indices/ratios. However, MSW is known for its heterogeneity, which means data obtained from laboratory testing are not necessary to be a good representation of the mechanical response observed in the field. Furthermore, most of the laboratory tests found in the literature were conducted on shredded samples of MSW to obtain specimens that are suitable for the testing setup. It is believed that shredding MSW samples changes the physical and mechanical properties of the waste. In this study, settlement field data was collected during the filling stage of Ste. Sophie landfill was used to estimate the primary and mechanical creep compression ratios. The field results from Ste. Sophie landfill indicated that both the primary and mechanical creep compression ratios of MSW are not constants but decrease with the increase in the applied vertical stress.

Keywords: mechanical creep compression ratio, municipal solid waste, primary compression ratio, stress level

Procedia PDF Downloads 88

Authors: Emi̇ne Avşar Aydin, Nezahat Günenç Tuncel, A. Hami̇t Serbest

Abstract:

The electromagnetic scattering from a canonical structure is an important issue in electromagnetic theory. In this study, the electromagnetic scattering from a dielectric sphere with oblique incidence is investigated. The incident field is considered as a plane wave with H polarized. The scattered and transmitted field expressions with unknown coefficients are written. The unknown coefficients are obtained by using exact boundary conditions. Then, the sphere is considered as having frequency dependent dielectric permittivity. The frequency dependence is shown by Cole-Cole model. The far scattered field expressions are found respect to different incidence angles in the 1-8 GHz frequency range. The observation point is the angular distance of pi from an incident wave. While an incident wave comes with a certain angle, observation point turns from 0 to 360 degrees. According to this, scattered field amplitude is maximum at the location of the incident wave, scattered field amplitude is minimum at the across incident wave. Also, the scattered fields are plotted versus frequency to show frequency-dependence explicitly. Graphics are shown for some incident angles compared with the Harrington's solution. Thus, the results are obtained faster and more reliable with reciprocal rotation. It is expected that when there is another sphere with different properties in the outer sphere, the presence and location of the sphere will be detected faster. In addition, this study leads to use for biomedical applications in the future.

Keywords: scattering, dielectric sphere, oblique incidence, reciprocal rotation

Procedia PDF Downloads 287

Authors: Zhijun Ren, Zhang Lin, Zhao Ye, Zuo Xiangyu, Mei Dongxing

Abstract:

As a pretreatment process of ballast water treatment, the performance of high gradient magnetic separation (HGMS) technology for the removal of particulates and microorganisms was studied. The results showed that HGMS process could effectively remove suspended particles larger than 5 µm and had ability to resist impact load. Microorganism could also be effectively removed by HGMS process, and the removal effect increased with increasing magnetic field strength. The maximum removal rates for Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) were 4016.1% and 9675.3% higher, respectively, than without the magnetic field. In addition, the superoxide dismutase (SOD) activity of the microbes decreased by 32.2% when the magnetic field strength was 15.4 mT for 72 min. The microstructure of the stainless steel wool was investigated, and the results showed that particle removal by HGMS has common function by the magnetic force of the high-strength, high-gradient magnetic field on weakly magnetic particles in the water, and on the stainless steel wool.

Keywords: HGMS, particulates, superoxide dismutase (SOD) activity, steel wool magnetic medium

Procedia PDF Downloads 444

Authors: P. Selyshchev

Abstract:

We consider fluctuations of defects density taking into account their interaction. Stochastic field of displacement generation rate gives random defect distribution. We determinate statistical characteristics (mean and dispersion) of random field of point defect distribution as function of defect generation parameters, temperature and properties of irradiated crystal.

Keywords: irradiation, primary defects, interaction, fluctuations

Procedia PDF Downloads 335

Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

Abstract:

This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining

Procedia PDF Downloads 415

Authors: M.Rüştü Karaman, İsmail İşeri, Kadir Saltalı, A.Reşit Brohi, Ayhan Horuz, Mümin Dizman

Abstract:

Considerable relations has recently been given to the environmental hazardous caused by agricultural chemicals such as excess fertilizers. In this study, a neural network approach was investigated in the prediction of potential nitrate pollution across different land-use patterns by using a feedforward multilayered computer model of artificial neural network (ANN) with proper training. Periodical concentrations of some anions, especially nitrate (NO3-), and cations were also detected in drainage waters collected from the drain pipes placed in irrigated tomato field, unirrigated wheat field, fallow and pasture lands. The soil samples were collected from the irrigated tomato field and unirrigated wheat field on a grid system with 20 m x 20 m intervals. Site specific nitrate concentrations in the soil samples were measured for ANN based simulation of nitrate leaching potential from the land profiles. In the application of ANN model, a multi layered feedforward was evaluated, and data sets regarding with training, validation and testing containing the measured soil nitrate values were estimated based on spatial variability. As a result of the testing values, while the optimal structures of 2-15-1 was obtained (R2= 0.96, P < 0.01) for unirrigated field, the optimal structures of 2-10-1 was obtained (R2= 0.96, P < 0.01) for irrigated field. The results showed that the ANN model could be successfully used in prediction of the potential leaching levels of nitrate, based on different land use patterns. However, for the most suitable results, the model should be calibrated by training according to different NN structures depending on site specific soil parameters and varied agricultural managements.

Keywords: artificial intelligence, ANN, drainage water, nitrate pollution

Procedia PDF Downloads 301

Authors: Boris Djartov, Sanaz Mostaghim

Abstract:

This paper presents a number-based dominance method. The main idea is how to fragment the many attributes of the problem into subsets suitable for the well-established concept of Pareto dominance. Although other similar methods can be found in the literature, they focus on comparing the solutions one objective at a time, while the focus of this method is to compare entire subsets of the objective vector. Given the nature of the method, it is computationally costlier than other methods and thus, it is geared more towards selecting an option from a finite set of alternatives, where each solution is defined by multiple objectives. The need for this method was motivated by dynamic alternate airport selection (DAAS). In DAAS, pilots, while en route to their destination, can find themselves in a situation where they need to select a new landing airport. In such a predicament, they need to consider multiple alternatives with many different characteristics, such as wind conditions, available landing distance, the fuel needed to reach it, etc. Hence, this method is primarily aimed at human decision-makers. Many methods within the field of multi-objective and many-objective decision-making rely on the decision maker to initially provide the algorithm with preference points and weight vectors; however, this method aims to omit this very difficult step, especially when the number of objectives is so large. The proposed method will be compared to Favour (1 − k)-Dom and L-dominance (LD) methods. The test will be conducted using well-established test problems from the literature, such as the DTLZ problems. The proposed method is expected to outperform the currently available methods in the literature and hopefully provide future decision-makers and pilots with support when dealing with many-objective optimization problems.

Keywords: multi-objective decision-making, many-objective decision-making, multi-objective optimization, many-objective optimization

Procedia PDF Downloads 83

Authors: Jin Sup Kim, Min Seo

Abstract:

An improved cross-shaped hall plate with high sensitivity is described in this paper. Among different geometries that have been simulated and measured using Helmholtz coil. The paper describes the physical hall plate design and implementation in a 0.18-µm CMOS technology. In this paper, the biasing is a constant voltage mode. In the voltage mode, magnetic field is converted into an output voltage. The output voltage is typically in the order of micro- to millivolt and therefore, it must be amplified before being transmitted to the outside world. The study, design and performance optimization of hall plate has been carried out with the COMSOL Multiphysics. It is used to estimate the voltage distribution in the hall plate with and without magnetic field and to optimize the geometry. The simulation uses the nominal bias current of 1mA. The applied magnetic field is in the range from 0 mT to 20 mT. Measured results of the one structure over the 10 available samples show for the best sensitivity of 2.5 %/T at 20mT.

Keywords: cross-shaped hall plate, sensitivity, CMOS technology, Helmholtz coil

Procedia PDF Downloads 191

Authors: Bitewulign Mekonnen

Abstract:

Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

Procedia PDF Downloads 85

Authors: M. Habibi

Abstract:

The feasibility of proton-boron fusion in plasmoids caused by magneto hydrodynamics instabilities in plasma focus devices is studied analytically. In plasmoids, fusion power for 76 keV < Ti < 1500 keV exceeds bremsstrahlung loss (W/Pb=5.39). In such situation gain factor and the ratio of Te to Ti for a typical 150 kJ plasma focus device will be 7.8 and 4.8 respectively. Also with considering the ion viscous heating effect, W/Pb and Ti/Te will be 2.7 and 6 respectively. Strong magnetic field will reduces ion-electron collision rate due to quantization of electron orbits. While approximately there is no change in electron-ion collision rate, the effect of quantum magnetic field makes ions much hotter than electrons which enhance the fraction of fusion power to bremsstrahlung loss. Therefore self-sustained p-11B fusion reactions would be possible and it could be said that p-11B fuelled plasma focus device is a clean and efficient source of energy.

Keywords: plasmoids, p11B fuel, ion viscous heating, quantum magnetic field, plasma focus device

Procedia PDF Downloads 452