Search results for: integrating sensing and modeling system

Authors: Akerele Akintunde Hareef

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GIS is an integrating tool for storing, retrieving, manipulating, and analyzing spatial data. It is a tool which defines an area with respect to features and other relevant thematic delineations. On the other hand, Environmental Impact Assessment in short is both positive and negative impact of an infrastructure on an environment. Impact of infrastructural projects on the environment is an aspect of development that barely get extensive portion of pre-project execution phase and when they do, the effects are most times not implemented to cushion the impact they have on human and the environment. In this research, infrastructural projects like road constructions, water reticulation projects, building constructions, bridge etc. have immense impact on the environment and the people that reside in location of construction. Hence, the need for this research tends to portray the relevance of Environmental Impact assessment in calculating the vulnerability of human and the environment to imbalance necessitated by this infrastructural development and how the use of GIS application can be optimally applied to annul or minimize the effect.

Keywords: environmental impact assessment (EIA), geographic information system (GIS), infrastructural projects, environment

Procedia PDF Downloads 552

Authors: Shahram Payandeh

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This paper presents an overview of a model which can be used as a part of a decision support system when fusing information from multiple sensing environment. Data fusion has been widely studied in the past few decades and numerous frameworks have been proposed to facilitate decision making process under uncertainties. Multi-sensor data fusion technology plays an increasingly significant role during people tracking and activity recognition. This paper presents an overview of a quantum model as a part of a decision-making process in the context of multi-sensor data fusion. The paper presents basic definitions and relationships associating the decision-making process and quantum model formulation in the presence of uncertainties.

Keywords: quantum model, sensor space, sensor network, decision support

Procedia PDF Downloads 227

Authors: Benga Ebouele, Thomas Tengen

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Due to long lead time, work in process (WIP) inventory can manifest within the supply chain of most manufacturing system. It implies that there are lesser finished good on hand and more in the process because the work remains in the factory too long and cannot be sold to either customers The supply chain of most manufacturing system is then considered as inefficient as it take so much time to produce the finished good. Time consumed in each operation of the supply chain has an associated energy costs. Such phenomena can be harmful for a hybrid inventory system because a lot of space to store these semi-finished goods may be needed and one is not sure about the final energy cost of producing, holding and delivering the good to customers. The principle that reduces waste of energy within the supply chain of most manufacturing firms should therefore be available to all inventory managers in pursuit of profitability. Decision making by inventory managers in this condition is a modeling process, whereby a dynamical approach is used to depict, examine, specify and even operationalize the relationship between energy consumption and hybrid inventory level. The relationship between energy consumption and inventory level is established, which indicates a poor level of control and hence a potential for energy savings.

Keywords: dynamic modelling, energy used, hybrid inventory, supply chain

Procedia PDF Downloads 268

Authors: Farooq A. Al-Sheikh, Ali Elkamel, William A. Anderson

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A fluidized catalytic cracking unit (FCCU) is one of the effective units in many refineries. Modeling and optimization of FCCU were done by many researchers in past decades, but in this research, comparison between post- and oxy-combustion was studied in the regenerator-FCCU. Therefore, a simplified mathematical model was derived by doing mass/heat balances around both reactor and regenerator. A state space analysis was employed to show effects of the flow rates variables such as air, feed, spent catalyst, regenerated catalyst and flue gas on the output variables. The main aim of studying dynamic responses is to figure out the most influencing variables that affect both reactor/regenerator temperatures; also, finding the upper/lower limits of the influencing variables to ensure that temperatures of the reactors and regenerator work within normal operating conditions. Therefore, those values will be used as side constraints in the optimization technique to find appropriate operating regimes. The objective functions were modeled to be maximizing the energy in the reactor while minimizing the energy consumption in the regenerator. In conclusion, an oxy-combustion process can be used instead of a post-combustion one.

Keywords: FCCU modeling, optimization, oxy-combustion, post-combustion

Procedia PDF Downloads 211

Authors: Pranita Shivankar, Devashree Hardas, Prabodhachandra Deshmukh, Arun Suryavanshi

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Bhimbetka Rock Shelters is the UNESCO World Heritage Site located about 45 kilometers south of Bhopal in the state of Madhya Pradesh, India. Rapid changes in land use land cover (LULC) adversely affect the environment. In recent past, significant changes are found in the cultural landscape over a period of time. The objective of the paper was to study the changes in land use land cover (LULC) of Bhimbetka and its peripheral region. For this purpose, the supervised classification was carried out by using satellite images of Landsat and IRS LISS III for the year 2000 and 2013. Use of remote sensing in combination with geographic information system is one of the effective information technology tools to generate land use land cover (LULC) change information.

Keywords: IRS LISS III, Landsat, LULC, UNESCO, World Heritage Site

Procedia PDF Downloads 350

Authors: Golak Bihari Mahanta, Bibhuti Bhusan Biswal, B. B. V. L. Deepak, Amruta Rout, Gunji Balamurali

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Robots are widely used in the manufacturing industry for rapid production with higher accuracy and precision. With the help of End-of-Arm Tools (EOATs), robots are interacting with the environment. Robotic grippers are such EOATs which help to grasp the object in an automation system for improving the efficiency. As the robotic gripper directly influence the quality of the product due to the contact between the gripper surface and the object to be grasped, it is necessary to design and optimize the gripper mechanism configuration. In this study, geometric and kinematic modeling of the parallel gripper is proposed. Grey wolf optimizer algorithm is introduced for solving the proposed multiobjective gripper optimization problem. Two objective functions developed from the geometric and kinematic modeling along with several nonlinear constraints of the proposed gripper mechanism is used to optimize the design variables of the systems. Finally, the proposed methodology compared with a previously proposed method such as Teaching Learning Based Optimization (TLBO) algorithm, NSGA II, MODE and it was seen that the proposed method is more efficient compared to the earlier proposed methodology.

Keywords: gripper optimization, metaheuristics, , teaching learning based algorithm, multi-objective optimization, optimal gripper design

Procedia PDF Downloads 188

Authors: Omar A. Abuobidalla, Mingyuan Chen, Satyaveer S. Chauhan

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Railroad transportation of hazardous materials freights is important to the North America economics that supports the national’s supply chain. This paper introduces various extensions of the dynamic hazardous materials trip plan problems. The problem captures most of the operational features of a real-world railroad transportations systems that dynamically initiates a set of blocks and assigns each shipment to a single block path or multiple block paths. The dynamic hazardous materials trip plan policies have distinguishing features that are integrating the blocking plan, and the block activation decisions. We also present a non-linear mixed integer programming formulation for each variant and present managerial insights based on a hypothetical railroad network. The computation results reveal that the dynamic car scheduling policies are not only able to take advantage of the capacity of the network but also capable of diminishing the population, and environment risks by rerouting the active blocks along the least risky train services without sacrificing the cost advantage of the railroad. The empirical results of this research illustrate that the issue of integrating the blocking plan, and the train makeup of the hazardous materials freights must receive closer attentions.

Keywords: dynamic car scheduling, planning and scheduling hazardous materials freights, airborne hazardous materials, gaussian plume model, integrated blocking and routing plans, box model

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Authors: Brian Connett, Bryan O'Halloran

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Systems assets within critical infrastructures were seemingly safe from the exploitation or attack by nefarious cyberspace actors. Now, critical infrastructure is a target and the resources to exploit the cyber physical systems exist. These resources are characterized in terms of patience, stealth, replication-ability and extraordinary robustness. System owners are obligated to maintain a high level of protection measures. The difficulty lies in knowing when to fortify a critical infrastructure against an impending attack. Models currently exist that demonstrate the value of knowing the attacker’s capabilities in the cyber realm and the strength of the target. The shortcomings of these models are that they are not designed to respond to the inherent fast timing of an attack, an impetus that can be derived based on open-source reporting, common knowledge of exploits of and the physical architecture of the infrastructure. A useful model will inform systems owners how to align infrastructure architecture in a manner that is responsive to the capability, willingness and timing of the attacker. This research group has used an existing theoretical model for estimating parameters, and through analysis, to develop a decision tool for would-be target owners. The continuation of the research develops further this model by estimating the variable parameters. Understanding these parameter estimations will uniquely position the decision maker to posture having revealed the vulnerabilities of an attacker’s, persistence and stealth. This research explores different approaches to improve on current attacker-defender models that focus on cyber threats. An existing foundational model takes the point of view of an attacker who must decide what cyber resource to use and when to use it to exploit a system vulnerability. It is valuable for estimating parameters for the model, and through analysis, develop a decision tool for would-be target owners.

Keywords: critical infrastructure, cyber physical systems, modeling, exploitation

Procedia PDF Downloads 192

Authors: Damien Gondre, Hatem Ben Maad, Abdelkrim Trabelsi, Frédéric Kuznik, Joseph Virgone

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The use of a radiant cooling solution would enable to lower cooling needs which is of great interest when the demand is initially high (hot climate). But, radiant systems are not naturally compatibles with humid climates since a low-temperature surface leads to condensation risks as soon as the surface temperature is close to or lower than the dew point temperature. A radiant cooling system combined to a dehumidification system would enable to remove humidity for the space, thereby lowering the dew point temperature. The humidity removal needs to be especially effective near the cooled surface. This requirement could be fulfilled by a system using a single desiccant fluid for the removal of both excessive heat and moisture. This task aims at providing an estimation of the specification requirements of such system in terms of cooling power and dehumidification rate required to fulfill comfort issues and to prevent any condensation risk on the cool panel surface. The present paper develops a preliminary study on the specification requirements, performances and behavior of a combined dehumidifier/cooling ceiling panel for different operating conditions. This study has been carried using the TRNSYS software which allows nodal calculations of thermal systems. It consists of the dynamic modeling of heat and vapor balances of a 5m x 3m x 2.7m office space. In a first design estimation, this room is equipped with an ideal heating, cooling, humidification and dehumidification system so that the room temperature is always maintained in between 21^◦C and 25^◦C with a relative humidity in between 40% and 60%. The room is also equipped with a ventilation system that includes a heat recovery heat exchanger and another heat exchanger connected to a heat sink. Main results show that the system should be designed to meet a cooling power of 42W.m⁻² and a desiccant rate of 45 g_H2O.h⁻¹. In a second time, a parametric study of comfort issues and system performances has been achieved on a more realistic system (that includes a chilled ceiling) under different operating conditions. It enables an estimation of an acceptable range of operating conditions. This preliminary study is intended to provide useful information for the system design.

Keywords: dehumidification, nodal calculation, radiant cooling panel, system sizing

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Authors: Sagar Shiwakoti, Narendra Man Shakya

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The lumped conceptual hydrological model HBV is applied to the Karnali River Basin to estimate runoff at several gauging stations and to analyze the changes in catchment hydrology and future flood magnitude due to climate change. The performance of the model is analyzed to assess its suitability to simulate streamflow in snow fed mountainous catchments. Due to the structural complexity, the model shows difficulties in modeling low and high flows accurately at the same time. It is observed that the low flows were generally underestimated and the peaks were correctly estimated except for some sharp peaks due to isolated precipitation events. In this study, attempt has been made to evaluate the importance of snow melt discharge in the runoff regime of the basin. Quantification of contribution of snowmelt to annual, summer and winter runoff has been done. The contribution is highest at the beginning of the hot months as the accumulated snow begins to melt. Examination of this contribution under conditions of increased temperatures indicate that global warming leading to increase in average basin temperature will significantly lead to higher contributions to runoff from snowmelt. Forcing the model with the output of HadCM3 GCM and the A1B scenario downscaled to the station level show significant changes to catchment hydrology in the 2040s. It is observed that the increase in runoff is most extreme in June - July. A shift in the hydrological regime is also observed.

Keywords: hydrological modeling, HBV light, rainfall runoff modeling, snow melt, climate change

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Authors: Francesca Marsili

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The reliability assessment of existing structures with probabilistic methods is becoming an increasingly important and frequent engineering task. However probabilistic reliability methods are based on an exhaustive knowledge of the stochastic modeling of the variables involved in the assessment; at the moment standards for the modeling of variables are absent, representing an obstacle to the dissemination of probabilistic methods. The framework according to probability distribution functions (PDFs) are established is represented by the Bayesian statistics, which uses Bayes Theorem: a prior PDF for the considered parameter is established based on information derived from the design stage and qualitative judgments based on the engineer past experience; then, the prior model is updated with the results of investigation carried out on the considered structure, such as material testing, determination of action and structural properties. The application of Bayesian statistics arises two different kind of problems: 1. The results of the updating depend on the engineer previous experience; 2. The updating of the prior PDF can be performed only if the structure has been tested, and quantitative data that can be statistically manipulated have been collected; performing tests is always an expensive and time consuming operation; furthermore, if the considered structure is an ancient building, destructive tests could compromise its cultural value and therefore should be avoided. In order to solve those problems, an interesting research path is represented by investigating Artificial Intelligence (AI) techniques that can be useful for the automation of the modeling of variables and for the updating of material parameters without performing destructive tests. Among the others, one that raises particular attention in relation to the object of this study is constituted by Case-Based Reasoning (CBR). In this application, cases will be represented by existing buildings where material tests have already been carried out and an updated PDFs for the material mechanical parameters has been computed through a Bayesian analysis. Then each case will be composed by a qualitative description of the material under assessment and the posterior PDFs that describe its material properties. The problem that will be solved is the definition of PDFs for material parameters involved in the reliability assessment of the considered structure. A CBR system represent a good candi¬date in automating the modelling of variables because: 1. Engineers already draw an estimation of the material properties based on the experience collected during the assessment of similar structures, or based on similar cases collected in literature or in data-bases; 2. Material tests carried out on structure can be easily collected from laboratory database or from literature; 3. The system will provide the user of a reliable probabilistic description of the variables involved in the assessment that will also serve as a tool in support of the engineer’s qualitative judgments. Automated modeling of variables can help in spreading probabilistic reliability assessment of existing buildings in the common engineering practice, and target at the best intervention and further tests on the structure; CBR represents a technique which may help to achieve this.

Keywords: reliability assessment of existing buildings, Bayesian analysis, case-based reasoning, historical structures

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Authors: Khan R. Rahaman, Quazi K. Hassan

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Global changes in climate, environment, economies, populations, governments, institutions, and cultures converge in localities. Changes at a local scale, in turn, contribute to global changes as well as being affected by them. Our hypothesis is built on a consideration that temperature does vary at local level (i.e., termed as local warming) in comparison to the predicted models at the regional and/or global scale. To date, the bulk of the research relating local places to global climate change has been top-down, from the global toward the local, concentrating on methods of impact analysis that use as a starting point climate change scenarios derived from global models, even though these have little regional or local specificity. Thus, our focus is to understand such trends over the southern Alberta, which will enable decision makers, scientists, researcher community, and local people to adapt their policies based on local level temperature variations and to act accordingly. Specific objectives in this study are: (i) to understand the local warming (temperature in particular) trend in context of temperature normal during the period 1961-2010 at point locations using meteorological data; (ii) to validate the data by using specific yearly data, and (iii) to delineate the spatial extent of the local warming trends and understanding influential factors to adopt situation by local governments. Existing data has brought the evidence of such changes and future research emphasis will be given to validate this hypothesis based on remotely sensed data (i.e. MODIS product by NASA).

Keywords: local warming, climate change, urban area, Alberta, Canada

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Authors: Dimitra Das, Anuradha Mitra, Kalyan Kumar Chattopadhyay

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Organic polymers, constructed from light elements like carbon, hydrogen, nitrogen, oxygen, sulphur, and boron atoms, are the emergent class of non-toxic, metal-free, environmental benign advanced materials. Covalent triazine-based polymers with a functional triazine group are significant class of organic materials due to their remarkable stability arising out of strong covalent bonds. They can conventionally form hydrogen bonds, favour π–π contacts, and they were recently revealed to be involved in interesting anion–π interactions. The present work mainly focuses upon the development of a single-crystalline, highly cross-linked triazine-based nitrogen-rich organic polymer with nanodendritic morphology and significant thermal stability. The polymer has been synthesized through hydrothermal treatment of melamine and ethylene glycol resulting in cross-polymerization via condensation-polymerization reaction. The crystal structure of the polymer has been evaluated by employing Rietveld whole profile fitting method. The polymer has been found to be composed of monoclinic melamine having space group P21/a. A detailed insight into the chemical structure of the as synthesized polymer has been elucidated by Fourier Transform Infrared Spectroscopy (FTIR) and Raman spectroscopic analysis. X-Ray Photoelectron Spectroscopic (XPS) analysis has also been carried out for further understanding of the different types of linkages required to create the backbone of the polymer. The unique rod-like morphology of the triazine based polymer has been revealed from the images obtained from Field Emission Scanning Electron Microscopy (FESEM) and Transmission Electron Microscopy (TEM). Interestingly, this polymer has been found to selectively detect mercury (Hg²⁺) ions at an extremely low concentration through fluorescent quenching with detection limit as low as 0.03 ppb. The high toxicity of mercury ions (Hg²⁺) arise from its strong affinity towards the sulphur atoms of biological building blocks. Even a trace quantity of this metal is dangerous for human health. Furthermore, owing to its small ionic radius and high solvation energy, Hg²⁺ ions remain encapsulated by water molecules making its detection a challenging task. There are some existing reports on fluorescent-based heavy metal ion sensors using covalent organic frameworks (COFs) but reports on mercury sensing using triazine based polymers are rather undeveloped. Thus, the importance of ultra-trace detection of Hg²⁺ ions with high level of selectivity and sensitivity has contemporary significance. A plausible sensing phenomenon by the polymer has been proposed to understand the applicability of the material as a potential sensor. The impressive sensitivity of the polymer sample towards Hg²⁺ is the very first report in the field of highly crystalline triazine based polymers (without the introduction of any sulphur groups or functionalization) towards mercury ion detection through photoluminescence quenching technique. This crystalline metal-free organic polymer being cheap, non-toxic and scalable has current relevance and could be a promising candidate for Hg²⁺ ion sensing at commercial level.

Keywords: fluorescence quenching , mercury ion sensing, single-crystalline, triazine-based polymer

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Authors: Kushakov Kholmurodjon, Muhammadjonov Akbarshox

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This present paper is devoted to a system of second-order nonlinear differential equations with a special right-hand side, exactly, the linear part and a third-order polynomial of a special form. It is shown that for some relations between the parameters, there is a second-order curve in which trajectories leaving the points of this curve remain in the same place. Thus, the curve is invariant with respect to the given system. Moreover, this system is invariant under a non-degenerate linear transformation of variables. The form of this curve, depending on the relations between the parameters and the eigenvalues of the matrix, is proved. All solutions of this system of differential equations are shown analytically.

Keywords: dynamic system, ellipse, hyperbola, Hess system, polar coordinate system

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Authors: Suzana Ramli, Wardah Tahir

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Estimation of surface runoff depth is a vital part in any rainfall-runoff modeling. It leads to stream flow calculation and later predicts flood occurrences. GIS (Geographic Information System) is an advanced and opposite tool used in simulating hydrological model due to its realistic application on topography. The paper discusses on calculation of surface runoff depth for two selected events by using GIS with Curve Number method for Upper Klang River basin. GIS enables maps intersection between soil type and land use that later produces curve number map. The results show good correlation between simulated and observed values with more than 0.7 of R2. Acceptable performance of statistical measurements namely mean error, absolute mean error, RMSE, and bias are also deduced in the paper.

Keywords: surface runoff, geographic information system, curve number method, environment

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Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri

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In this study, ¹⁷⁷Lu-DOTATOC was prepared under optimized conditions (radiochemical purity: > 99%, radionuclidic purity: > 99%). The percentage of injected dose per gram (%ID/g) was calculated for organs up to 168 h post injection. Compartmental model was applied to mathematical description of the drug behaviour in tissue at different times. The biodistribution data showed the significant excretion of the radioactivity from the kidneys. The adrenal and pancreas, as major expression sites for somatostatin receptor (SSTR), had significant uptake. A pharmacokinetic model of ¹⁷⁷Lu-DOTATOC was presented by compartmental analysis which demonstrates the behavior of the complex.

Keywords: biodistribution, compartmental modeling, ¹⁷⁷Lu, Octreotide

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Authors: Israt Jahan Eshita

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Flows developed between two parallel disks have many engineering applications. Two types of non-swirling flows can be generated in such a domain. One is purely source flow in disc type domain (outward flow). Other is purely sink flow in disc type domain (inward flow). This situation often appears in some turbo machinery components such as air bearings, heat exchanger, radial diffuser, vortex gyroscope, disc valves, and viscosity meters. The main goal of this paper is to show the mesh convergence, because mesh convergence saves time, and economical to run and increase the efficiency of modeling for both sink and source flow. Then flow field is resolved using a very fine mesh near-wall, using enhanced wall treatment. After that we are going to compare this flow using standard k-epsilon, RNG k-epsilon turbulence models. Lastly compare some experimental data with numerical solution for sink flow. The good agreement of numerical solution with the experimental works validates the current modeling.

Keywords: hydraulic diameter, k-epsilon model, meshes convergence, Reynolds number, RNG model, sink flow, source flow, wall y+

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Authors: Sina Saadati

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OpenSim is a well-known software in biomechanical studies. There are worthy algorithms developed in this program which are used for modeling and simulation of human motions. In this research, we analyze the OpenSim application from the computer science perspective. It is important that every application have a user-friendly interface. An effective user interface can decrease the time, costs, and energy needed to learn how to use a program. In this paper, we survey the user interface of OpenSim as an important factor of the software. Finally, we infer that there are many challenges to be addressed in the development of OpenSim.

Keywords: biomechanics, computer engineering, graphical user interface, modeling and simulation, interface effectiveness

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Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

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The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

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Authors: G. R. Khan, Sadia Mahjabin, A. S. Mollah, M. R. Mawla

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Atmospheric dispersion modeling is significant for any nuclear facilities in the country to predict the impact of radiological doses on environment as well as human health. That is why to ensure safety of workers and population at plant site; Atmospheric dispersion modeling and radiation dose calculations were carried out for a hypothetical accidental release of airborne radionuclide from the 3 MW TRIGA research reactor of Savar, Bangladesh. It is designed with reactor core which consists of 100 fuel elements(1.82245 cm in diameter and 38.1 cm in length), arranged in an annular corefor steady-state and square wave power level of 3 MW (thermal) and for pulsing with maximum power level of 860MWth.The fuel is in the form of a uniform mixture of 20% uranium and 80% zirconium hydride. Total effective doses (TEDs) to the public at various downwind distances were evaluated with a health physics computer code “HotSpot” developed by Lawrence Livermore National Laboratory, USA. The doses were estimated at different Pasquill stability classes (categories A-F) with site-specific averaged meteorological conditions. The meteorological data, such as, average wind speed, frequency distribution of wind direction, etc. have also been analyzed based on the data collected near the reactor site. The results of effective doses obtained remain within the recommended maximum effective dose.

Keywords: accidental release, dispersion modeling, total effective dose, TRIGA

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Authors: Sanaz Seraj, Shohre Rouhani

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Recently, graphene has gained much attention because of its unique optical, mechanical, electrical, and thermal properties. Graphene has been used as a key material in the technological applications in various areas such as sensors, drug delivery, super capacitors, transparent conductor, and solar cell. It has a superior quenching efficiency for various fluorophores. Based on these unique properties, the optical sensors with graphene materials as the energy acceptors have demonstrated great success in recent years. During quenching, the emission of a fluorophore is perturbed by a quencher which can be a substrate or biomolecule, and due to this phenomenon, fluorophore-quencher has been used for selective detection of target molecules. Among fluorescence dyes, 1,8-naphthalimide is well known for its typical intramolecular charge transfer (ICT) and photo-induced charge transfer (PET) fluorophore, strong absorption and emission in the visible region, high photo stability, and large Stokes shift. Derivatives of 1,8-naphthalimides have found applications in some areas, especially fluorescence sensors. Herein, the fluorescence quenching of graphene oxide has been carried out on a naphthalimide dye as a fluorescent probe model. The quenching ability of graphene oxide on naphthalimide dye was studied by UV-VIS and fluorescence spectroscopy. This study showed that graphene is an efficient quencher for fluorescent dyes. Therefore, it can be used as a suitable candidate sensing platform. To the best of our knowledge, studies on the quenching and absorption of naphthalimide dyes by graphene oxide are rare.

Keywords: fluorescence, graphene oxide, naphthalimide dye, quenching

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Authors: Weiliang Wen, Xinyu Guo, Ying Zhang, Jianjun Du, Boxiang Xiao

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Reconstructing and analyzing three-dimensional (3D) models from situ measured data is important for a number of researches and applications in plant science, including plant phenotyping, functional-structural plant modeling (FSPM), plant germplasm resources protection, agricultural technology popularization. It has many scales like cell, tissue, organ, plant and canopy from micro to macroscopic. The techniques currently used for data capture, feature analysis, and 3D reconstruction are quite different of different scales. In this context, morphological data acquisition, 3D analysis and modeling of plants on different scales are introduced systematically. The commonly used data capture equipment for these multiscale is introduced. Then hot issues and difficulties of different scales are described respectively. Some examples are also given, such as Micron-scale phenotyping quantification and 3D microstructure reconstruction of vascular bundles within maize stalks based on micro-CT scanning, 3D reconstruction of leaf surfaces and feature extraction from point cloud acquired by using 3D handheld scanner, plant modeling by combining parameter driven 3D organ templates. Several application examples by using the 3D models and analysis results of plants are also introduced. A 3D maize canopy was constructed, and light distribution was simulated within the canopy, which was used for the designation of ideal plant type. A grape tree model was constructed from 3D digital and point cloud data, which was used for the production of science content of 11th international conference on grapevine breeding and genetics. By using the tissue models of plants, a Google glass was used to look around visually inside the plant to understand the internal structure of plants. With the development of information technology, 3D data acquisition, and data processing techniques will play a greater role in plant science.

Keywords: plant, three dimensional modeling, multi-scale, plant phenotyping, three dimensional data acquisition

Procedia PDF Downloads 277

Authors: F. O. Danquah, F. Frimpong, E. Owusu Danquah, T. Frimpong, J. Adu, S. K. Amposah, P. Amankwaa-Yeboah, N. E. Amengor

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In the face of global concerns such as population increase, climate change, and limited natural resources, sustainable agriculture practices are critical for ensuring food security and environmental stewardship. The study was conducted in the Forest zones of Ghana during the major and minor seasons of 2023 cropping seasons to evaluate maize yield productivity improvement and profitability of integrating Cajanus cajan (pigeonpea) into a maize production system described as a pigeonpea-maize cropping system. This is towards an integrated soil fertility management (ISFM) with a legume shrub pigeonpea for sustainable maize production while improving smallholder farmers' resilience to climate change. A split-plot design with maize-pigeonpea (Pigeonpea-Maize intercrop – MPP and No pigeonpea/ Sole maize – NPP) and inorganic fertilizer rate (250 kg/ha of 15-15-15 N-P2O5-K2O + 250 kg/ha Sulphate of Ammonia (SoA) – Full rate (FR), 125 kg/ha of 15-15-15 N-P2O5-K2O + 125 kg/ha Sulphate of Ammonia (SoA) – Half rate (HR) and no inorganic fertilizer (NF) as control) was used as the main plot and subplot treatments respectively. The results indicated a significant interaction of the pigeonpea-maize cropping system and inorganic fertilizer rate on the growth and yield of the maize with better and similar maize productivity when HR and FR were used with pigeonpea biomass. Thus, the integration of pigeonpea and its biomass would result in the reduction of recommended fertiliser rate to half. This would improve farmers’ income and profitability for sustainable maize production in the face of climate change.

Keywords: agroforestry tree, climate change, integrated soil fertility management, resource use efficiency

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Authors: Monika Sogani, Zainab Syed, Adrian C. Fisher

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Pollution of estrogenic compounds has caught the attention of researchers as the slight increase of estrogens in the water bodies has a significant impact on the aquatic system. They belong to a class of endocrine disrupting compounds (EDCs) and are able to mimic hormones or interfere with the action of endogenous hormones. The microbial electrochemical remediation system (MERS) is employed here for exploiting an electrophototrophic bacterium for evaluating the capacity of biodegradation of ethinylestradiol hormone (EE2) under anaerobic conditions with power generation. MERS using electro-phototrophic bacterium offers a tailored solution of wastewater treatment in a developing country like India which has a huge solar potential. It is a clean energy generating technology as they require only sunlight, water, nutrients, and carbon dioxide to operate. Its main feature that makes it superior over other technologies is that the main fuel for this MERS is sunlight which is indefinitely present. When grown in light with organic compounds, these photosynthetic bacteria generate ATP by cyclic photophosphorylation and use carbon compounds to make cell biomass (photoheterotrophic growth). These cells showed EE2 degradation and were able to generate hydrogen as part of the process of nitrogen fixation. The two designs of MERS were studied, and a maximum of 88.45% decrease in EE2 was seen in a total period of 14 days in the better design. This research provides a better insight into microbial electricity generation and self-sustaining wastewater treatment facilities. Such new models of waste treatment aiming waste to energy generation needs to be followed and implemented for building a resource efficient and sustainable economy.

Keywords: endocrine disrupting compounds, ethinylestradiol, microbial electrochemical remediation systems, wastewater treatment

Procedia PDF Downloads 118

Authors: Moustafa Osman

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Modeling of air pollutants from the accidental release is performed for quantifying the impact of industrial facilities into the ambient air. The mathematical methods are requiring for the prediction of the accidental scenario in probability of failure-safe mode and analysis consequences to quantify the environmental damage upon human health. The initial statement of mitigation plan is supporting implementation during production and maintenance periods. In a number of mathematical methods, the flow rate at which gaseous and liquid pollutants might be accidentally released is determined from various types in term of point, line and area sources. These emissions are integrated meteorological conditions in simplified stability parameters to compare dispersion coefficients from non-continuous air pollution plumes. The differences are reflected in concentrations levels and greenhouse effect to transport the parcel load in both urban and rural areas. This research reveals that the elevation effect nearby buildings with other structure is higher 5 times more than open terrains. These results are agreed with Sutton suggestion for dispersion coefficients in different stability classes.

Keywords: air pollutants, dispersion modeling, GIS, health effect, urban planning

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Authors: Adan Valdez, Shawn Gallaher, James Morison, Jordan Aragon

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Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport and modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116 km3/year. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff. The total climatological freshwater content is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity driven pycnocline as opposed to the temperature driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and remotely sensed dynamic ocean topography (DOT). In-situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time consuming. NASA’s Advanced Topographic Laser Altimeter System (ATLAS) derived dynamic ocean topography (DOT), and Air Expendable CTD (AXCTD) derived Freshwater Content are used to develop a linear regression model. In-situ data for the regression model is collected across the 150° West meridian, which typically defines the centerline of the Beaufort Gyre. Two freshwater content models are determined by integrating the freshwater volume between the surface and an isopycnal corresponding to reference salinities of 28.7 and 34.8. These salinities correspond to those of the winter pycnocline and total climatological freshwater content, respectively. Using each model, we determine the strength of the linear relationship between freshwater content and satellite derived DOT. The result of this modeling study could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non in-situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: ICESat-2, dynamic ocean topography, freshwater content, beaufort gyre

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Authors: Farhad Ghasemi

Abstract:

Along with transforming the international system into a complex and chaotic system, the fundamental question arises: how can deterrence be reconstructed conceptually and theoretically in this system model? The deterrence system is much more complex today than it was seven decades ago. This article suggests that the perception of deterrence as a linear system is a fundamental mistake because it does not consider the new dynamics of the international system, including network power dynamics. The author aims to improve this point by focusing on complexity and chaos theories, especially their nonlinearity and cascading failure principles. This article proposes that the perception of deterrence as a linear system is a fundamental mistake, as the new dynamics of the surrounding international system do not take into account. The author recognizes deterrence as a nonlinear system and introduces it as a concept in strategic studies.

Keywords: complexity, international system, deterrence, linear deterrence, nonlinear deterrence

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Authors: Matheus Madureira Matos, Alexandre Rodrigues Farias

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Magnetic Resonance Imaging (MRI) is a vital imaging technique used in both clinical and pre-clinical areas to obtain detailed anatomical and functional information. However, MRI scans can be expensive, time-consuming, and often require the use of anesthetics to keep animals still during the imaging process. Anesthetics are commonly administered to animals undergoing MRI scans to ensure they remain still during the imaging process. However, prolonged or repeated exposure to anesthetics can have adverse effects on animals, including physiological alterations and potential toxicity. Minimizing the duration and frequency of anesthesia is, therefore, crucial for the well-being of research animals. In recent years, various sampling trajectories have been investigated to reduce the number of MRI measurements leading to shorter scanning time and minimizing the duration of animal exposure to the effects of anesthetics. Compressed sensing (CS) and sampling trajectories, such as cartesian, spiral, and radial, have emerged as powerful tools to reduce MRI data while preserving diagnostic quality. This work aims to apply CS and cartesian, spiral, and radial sampling trajectories for the reconstruction of MRI of the abdomen of mice sub-sampled at levels below that defined by the Nyquist theorem. The methodology of this work consists of using a fully sampled reference MRI of a female model C57B1/6 mouse acquired experimentally in a 4.7 Tesla MRI scanner for small animals using Spin Echo pulse sequences. The image is down-sampled by cartesian, radial, and spiral sampling paths and then reconstructed by CS. The quality of the reconstructed images is objectively assessed by three quality assessment techniques RMSE (Root mean square error), PSNR (Peak to Signal Noise Ratio), and SSIM (Structural similarity index measure). The utilization of optimized sampling trajectories and CS technique has demonstrated the potential for a significant reduction of up to 70% of image data acquisition. This result translates into shorter scan times, minimizing the duration and frequency of anesthesia administration and reducing the potential risks associated with it.

Keywords: compressed sensing, magnetic resonance, sampling trajectories, small animals

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Authors: In-Hwan Baek

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Valsartan is a potent and highly selective antagonist of the angiotensin II type 1 receptor, and is widely used for the treatment of hypertension. The aim of this study was to investigate the pharmacokinetic properties of the valsartan in dogs following oral administration of a single dose using quantitative modeling approaches. Forty beagle dogs were randomly divided into two group. Group A (n=20) was administered a single oral dose of valsartan 80 mg (Diovan® 80 mg), and group B (n=20) was administered a single oral dose of valsartan 160 mg (Diovan® 160 mg) in the morning after an overnight fast. Blood samples were collected into heparinized tubes before and at 0.5, 1, 1.5, 2, 2.5, 3, 4, 6, 8, 12 and 24 h following oral administration. The plasma concentrations of the valsartan were determined using LC-MS/MS. Non-compartmental pharmacokinetic analyses were performed using WinNonlin Standard Edition software, and modeling approaches were performed using maximum-likelihood estimation via the expectation maximization (MLEM) algorithm with sampling using ADAPT 5 software. After a single dose of valsartan 80 mg, the mean value of maximum concentration (Cmax) was 2.68 ± 1.17 μg/mL at 1.83 ± 1.27 h. The area under the plasma concentration-versus-time curve from time zero to the last measurable concentration (AUC24h) value was 13.21 ± 6.88 μg·h/mL. After dosing with valsartan 160 mg, the mean Cmax was 4.13 ± 1.49 μg/mL at 1.80 ± 1.53 h, the AUC24h was 26.02 ± 12.07 μg·h/mL. The Cmax and AUC values increased in proportion to the increment in valsartan dose, while the pharmacokinetic parameters of elimination rate constant, half-life, apparent of total clearance, and apparent of volume of distribution were not significantly different between the doses. Valsartan pharmacokinetic analysis fits a one-compartment model with first-order absorption and elimination following a single dose of valsartan 80 mg and 160 mg. In addition, high inter-individual variability was identified in the absorption rate constant. In conclusion, valsartan displays the dose-dependent pharmacokinetics in dogs, and Subsequent quantitative modeling approaches provided detailed pharmacokinetic information of valsartan. The current findings provide useful information in dogs that will aid future development of improved formulations or fixed-dose combinations.

Keywords: dose-dependent, modeling, pharmacokinetics, valsartan

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Authors: Abdel Hadi Ebraheim

Abstract:

This paper introduces a new extension of the Inverse Pareto distribution in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure data. The statistical properties of the new model are discussed. Several methods are used to estimate the parameters involved. Explicit expressions are derived for different types of moments of value in reliability analysis are obtained. Besides, the order statistics of samples from the new proposed model have been studied. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study.

Keywords: pareto distribution, marshal-Olkin, reliability, hazard functions, moments, estimation

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