Search results for: Kalman filter estimation

Authors: Liang Cheng Chang, Wei Ju Huang, You Cheng Chen

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Investigation and research are keys for conjunctive use of surface and groundwater resources. The hydrogeological structure is an important base for groundwater analysis and simulation. Traditionally, the hydrogeological structure is artificially determined based on geological drill logs, the structure of wells, groundwater levels, and so on. In Taiwan, groundwater observation network has been built and a large amount of groundwater-level observation data are available. The groundwater level is the state variable of the groundwater system, which reflects the system response combining hydrogeological structure, groundwater injection, and extraction. This study applies analytical tools to the observation database to develop a methodology for the identification of confined and unconfined aquifers. These tools include frequency analysis, cross-correlation analysis between rainfall and groundwater level, groundwater regression curve analysis, and decision tree. The developed methodology is then applied to groundwater layer identification of two groundwater systems: Zhuoshui River alluvial fan and Pingtung Plain. The abovementioned frequency analysis uses Fourier Transform processing time-series groundwater level observation data and analyzing daily frequency amplitude of groundwater level caused by artificial groundwater extraction. The cross-correlation analysis between rainfall and groundwater level is used to obtain the groundwater replenishment time between infiltration and the peak groundwater level during wet seasons. The groundwater regression curve, the average rate of groundwater regression, is used to analyze the internal flux in the groundwater system and the flux caused by artificial behaviors. The decision tree uses the information obtained from the above mentioned analytical tools and optimizes the best estimation of the hydrogeological structure. The developed method reaches training accuracy of 92.31% and verification accuracy 93.75% on Zhuoshui River alluvial fan and training accuracy 95.55%, and verification accuracy 100% on Pingtung Plain. This extraordinary accuracy indicates that the developed methodology is a great tool for identifying hydrogeological structures.

Keywords: aquifer identification, decision tree, groundwater, Fourier transform

Procedia PDF Downloads 155

Authors: Defne Uz

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Horizontal Tail of helicopter is exposed to repeated oscillatory loading generated by aerodynamic and inertial loads, and bending moments depending on operating conditions and maneuvers of the helicopter. In order to ensure that maximum stress levels do not exceed certain fatigue limit of the material and to prevent damage, a numerical analysis approach can be utilized through the Finite Element Method. Therefore, in this paper, fatigue analysis of the Horizontal Tail model is studied numerically to predict high-cycle and low-cycle fatigue life related to defined loading. The analysis estimates the stress field at stress concentration regions such as around fastener holes where the maximum principal stresses are considered for each load case. Critical element identification of the main load carrying structural components of the model with rivet holes is performed as a post-process since critical regions with high-stress values are used as an input for fatigue life calculation. Once the maximum stress is obtained at the critical element and the related mean and alternating components, it is compared with the endurance limit by applying Soderberg approach. The constant life straight line provides the limit for several combinations of mean and alternating stresses. The life calculation based on S-N (Stress-Number of Cycles) curve is also applied with fully reversed loading to determine the number of cycles corresponds to the oscillatory stress with zero means. The results determine the appropriateness of the design of the model for its fatigue strength and the number of cycles that the model can withstand for the calculated stress. The effect of correctly determining the critical rivet holes is investigated by analyzing stresses at different structural parts in the model. In the case of low life prediction, alternative design solutions are developed, and flight hours can be estimated for the fatigue safe operation of the model.

Keywords: fatigue analysis, finite element method, helicopter horizontal tail, life prediction, stress concentration

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Authors: Sahar Tabarroki, Ahad Nazari

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The design process is one of the most key project processes in the construction industry. Although architects have the responsibility to produce complete, accurate, and coordinated documents, architectural design is accompanied by many errors. A design error occurs when the constraints and requirements of the design are not satisfied. Errors are potentially costly and time-consuming to correct if not caught early during the design phase, and they become expensive in either construction documents or in the construction phase. The aim of this research is to identify the risk factors of architectural design errors, so identification of risks is necessary. First, a literature review in the design process was conducted and then a questionnaire was designed to identify the risks and risk factors. The questions in the form of the questionnaire were based on the “similar service description of study and supervision of architectural works” published by “Vice Presidency of Strategic Planning & Supervision of I.R. Iran” as the base of architects’ tasks. Second, the top 10 risks of architectural activities were identified. To determine the positions of possible causes of risks with respect to architectural activities, these activities were located in a design process modeled by the IDEF0 technique. The research was carried out by choosing a case study, checking the design drawings, interviewing its architect and client, and providing a checklist in order to identify the concrete examples of architectural design errors. The results revealed that activities such as “defining the current and future requirements of the project”, “studies and space planning,” and “time and cost estimation of suggested solution” has a higher error risk than others. Moreover, the most important causes include “unclear goals of a client”, “time force by a client”, and “lack of knowledge of architects about the requirements of end-users”. For error detecting in the case study, lack of criteria, standards and design criteria, and lack of coordination among them, was a barrier, anyway, “lack of coordination between architectural design and electrical and mechanical facility”, “violation of the standard dimensions and sizes in space designing”, “design omissions” were identified as the most important design errors.

Keywords: architectural design, design error, risk management, risk factor

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Authors: Meghdad Payan, Kostas Senetakis, Arman Khoshghalb, Nasser Khalili

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Dynamic properties of soils, especially at the range of very small strains, are of particular interest in geotechnical engineering practice for characterization of the behavior of geo-structures subjected to a variety of stress states. This study reports on the small-strain dynamic properties of sand-silt mixtures with particular emphasis on the effect of non-plastic fines content on the small strain shear modulus (Gmax), Young’s Modulus (Emax), material damping (Ds,min) and Poisson’s Ratio (v). Several clean sands with a wide range of grain size characteristics and particle shape are mixed with variable percentages of a silica non-plastic silt as fines content. Prepared specimens of sand-silt mixtures at different initial void ratios are subjected to sequential torsional and flexural resonant column tests with elastic dynamic properties measured along an isotropic stress path up to 800 kPa. It is shown that while at low percentages of fines content, there is a significant difference between the dynamic properties of the various samples due to the different characteristics of the sand portion of the mixtures, this variance diminishes as the fines content increases and the soil behavior becomes mainly silt-dominant, rendering no significant influence of sand properties on the elastic dynamic parameters. Indeed, beyond a specific portion of fines content, around 20% to 30% typically denoted as threshold fines content, silt is controlling the behavior of the mixture. Using the experimental results, new expressions for the prediction of small-strain dynamic properties of sand-silt mixtures are developed accounting for the percentage of silt and the characteristics of the sand portion. These expressions are general in nature and are capable of evaluating the elastic dynamic properties of sand-silt mixtures with any types of parent sand in the whole range of silt percentage. The inefficiency of skeleton void ratio concept in the estimation of small-strain stiffness of sand-silt mixtures is also illustrated.

Keywords: damping ratio, Poisson’s ratio, resonant column, sand-silt mixture, shear modulus, Young’s modulus

Procedia PDF Downloads 249

Authors: Abdulmalek Ahmed

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Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%).

Keywords: Artificial Intelligence (AI), Formation pressure, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Networks (FN), Radial Basis Function (RBF)

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Authors: Sachin B. Patil, Narendra M. Kanhe

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A typical cane molasses based distillery generates 15 L of waste water per liter of alcohol production. Distillery waste with COD of over 1,00,000 mg/l and BOD of over 30,000 mg/l ranks high amongst the pollutants produced by industries both in magnitude and strength. Treatment and safe disposal of this waste is a challenging task since long. The high strength of waste water renders aerobic treatment very expensive and physico-chemical processes have met with little success. Thermophilic anaerobic treatment of distillery waste may provide high degree of treatment and better recovery of biogas. It may prove more feasible in most part of tropical country like India, where temperature is suitable for thermophilic micro-organisms. Researchers have reviled that, at thermophilic conditions due to increased destruction rate of organic matter and pathogens, higher digestion rate can be achieved. Literature review reveals that the variety of anaerobic reactors including anaerobic lagoon, conventional digester, anaerobic filter, two staged fixed film reactors, sludge bed and granular bed reactors have been studied, but little attempts have been made to evaluate the usefulness of thermophilic anaerobic treatment for treating distillery waste. The present study has been carried out, to study feasibility of thermophilic anaerobic digestion to facilitate the design of full scale reactor. A pilot scale anaerobic fixed film fixed bed reactor (AFFFB) of capacity 25m3 was designed, fabricated, installed and commissioned for thermophilic (55-65°C) anaerobic digestion at a constant pH of 6.5-7.5, because these temperature and pH ranges are considered to be optimum for biogas recovery from distillery wastewater. In these conditions, working of the reactor was studied, for different hydraulic retention times (HRT) (0.25days to 12days) and variable organic loading rates (361.46 to 7.96 Kg COD/m3d). The parameters such as flow rate and temperature, various chemical parameters such as pH, chemical oxygen demands (COD), biogas quantity, and biogas composition were regularly monitored. It was observed that, with the increase in OLR, the biogas production was increased, but the specific biogas yield decreased. Similarly, with the increase in HRT, the biogas production got decrease, but the specific biogas yield was increased. This may also be due to the predominant activity of acid producers to methane producers at the higher substrate loading rates. From the present investigation, it can be concluded that for thermophilic conditions the highest COD removal percentage was obtained at an HRT of 08 days, thereafter it tends to decrease from 8 to 12 days HRT. There is a little difference between COD removal efficiency of 8 days HRT (74.03%) and 5 day HRT (78.06%), therefore it would not be feasible to increase the reactor size by 1.5 times for mere 4 percent more efficiency. Hence, 5 days HRT is considered to be optimum, at which the biogas yield was 98 m3/day and specific biogas yield was 0.385 CH4 m3/Kg CODr.

Keywords: spent wash, anaerobic digestion, biomass, biogas

Procedia PDF Downloads 261

Authors: K. O’Mara, T. Cresswell

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Nearly half of the world’s population live near the coast, and as a result, estuaries and coastal bays in populated or industrialized areas often receive metal pollution. Heavy metals have a chemical affinity for sediment particles and can be stored in estuarine sediments and become biologically available under changing conditions. Organisms inhabiting estuaries can be exposed to metals from a variety of sources including metals dissolved in water, bound to sediment or within contaminated prey. Metal uptake and assimilation responses can vary even between species that are biologically similar, making pollution effects difficult to predict. A multi-trophic level experiment representing a common Eastern Australian estuarine food chain was used to study the sources for Cd, Mn and Zn uptake and assimilation in organisms occupying several trophic levels. Sand cockles (Katelysia scalarina), school prawns (Metapenaeus macleayi) and sand whiting (Sillago ciliata) were exposed to radiolabelled seawater, suspended sediment and food. Three pulse-chase trials on filter-feeding sand cockles were performed using radiolabelled phytoplankton (Tetraselmis sp.), benthic microalgae (Entomoneis sp.) and suspended sediment. Benthic microalgae had lower metal uptake than phytoplankton during labelling but higher cockle assimilation efficiencies (Cd = 51%, Mn = 42%, Zn = 63 %) than both phytoplankton (Cd = 21%, Mn = 32%, Zn = 33%) and suspended sediment (except Mn; (Cd = 38%, Mn = 42%, Zn = 53%)). Sand cockles were also sensitive to uptake of Cd, Mn and Zn dissolved in seawater. Uptake of these metals from the dissolved phase was negligible in prawns and fish, with prawns only accumulating metals during moulting, which were then lost with subsequent moulting in the depuration phase. Diet appears to be the main source of metal assimilation in school prawns, with 65%, 54% and 58% assimilation efficiencies from Cd, Mn and Zn respectively. Whiting fed contaminated prawns were able to exclude the majority of the metal activity through egestion, with only 10%, 23% and 11% assimilation efficiencies from Cd, Mn and Zn respectively. The findings of this study support previous studies that find diet to be the dominant accumulation source for higher level trophic organisms. These results show that assimilation efficiencies can vary depending on the source of exposure; sand cockles assimilated more Cd, Mn, and Zn from the benthic diatom than phytoplankton and assimilation was higher in sand whiting fed prawns compared to artificial pellets. The sensitivity of sand cockles to metal uptake and assimilation from a variety of sources poses concerns for metal availability to predators ingesting the clam tissue, including humans. The high tolerance of sand whiting to these metals is reflected in their widespread presence in Eastern Australian estuaries, including contaminated estuaries such as Botany Bay and Port Jackson.

Keywords: cadmium, food chain, metal, manganese, trophic, zinc

Procedia PDF Downloads 200

Authors: William Castillo, Hugo Viza, Arturo Vargas

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The Pacific Alliance is a trade bloc that is composed of four emerging economies: Chile, Colombia, Peru, and Mexico. These economies have gained macroeconomic stability in the past decade and as a consequence present future economic progress. Under this positive scenario, international business firms have flourished. However, the literature in this region has been widely unexamined. Therefore, it is critical to fill this theoretical gap, especially considering that Latin America is starting to become a global player and it possesses a different institutional context than developed markets. This paper analyzes the effect of international entrepreneurial orientation and institutionalism on international performance, for the Pacific Alliance small-to-medium enterprises (SMEs). The literature considers international entrepreneurial orientation to be a powerful managerial capability – along the resource based view- that firms can leverage to obtain a satisfactory international performance. Thereby, obtaining a competitive advantage through the correct allocation of key resources to exploit the capabilities here involved. Entrepreneurial Orientation is defined around five factors: innovation, proactiveness, risk-taking, competitive aggressiveness, and autonomy. Nevertheless, the institutional environment – both local and foreign, adversely affects International Performance; this is especially the case for emerging markets with uncertain scenarios. In this way, the study analyzes an Entrepreneurial Orientation, key endogenous variable of international performance, and Institutionalism, an exogenous variable. The survey data consists of Pacific Alliance SMEs that have foreign operations in at least another country in the trade bloc. Findings are still in an ongoing research process. Later, the study will undertake a structural equation modeling (SEM) using the variance-based partial least square estimation procedure. The software that is going to be used is the SmartPLS. This research contributes to the theoretical discussion of a largely postponed topic: SMEs in Latin America, that has had limited academic research. Also, it has practical implication for decision-makers and policy-makers, providing insights into what is behind international performance.

Keywords: institutional theory, international entrepreneurial orientation, international performance, SMEs, Pacific Alliance

Procedia PDF Downloads 248

Authors: Elena Carcano, James Ball, Betty Tiko

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Carrying capacity refers to the maximum population that a given level of resources can sustain over a specific period. In undisturbed environments, the maximum population is determined by the availability and distribution of resources, as well as the competition for their utilization. This information is typically obtained through long-term data collection. In regulated environments, where resources are artificially modified, populations must adapt to changing conditions, which can lead to additional challenges due to fluctuations in resource availability over time and throughout development. An example of this is observed in hydropower plants, which alter water flow and impact fish migration patterns and behaviors. To assess how fish species can adapt to these changes, specialized surveys are conducted, which provide valuable information on fish populations, sample sizes, and density before and after flow modifications. In such situations, it is highly recommended to conduct hydrological and biological monitoring to gain insight into how flow reductions affect species adaptability and to prevent unfavorable exploitation conditions. This analysis involves several planned steps that help design appropriate hydropower production while simultaneously addressing environmental needs. Consequently, the study aims to strike a balance between technical assessment, biological requirements, and societal expectations. Beginning with a small hydro project that requires restoration, this analysis focuses on the lower tail of the Flow Duration Curve (FDC), where both hydrological and environmental goals can be met. The proposed approach involves determining the threshold condition that is tolerable for the most vulnerable species sampled (Telestes Muticellus) by identifying a low flow value from the long-term FDC. The results establish a practical connection between hydrological and environmental information and simplify the process by establishing a single reference flow value that represents the minimum environmental flow that should be maintained.

Keywords: carrying capacity, fish bypass ladder, long-term streamflow duration curve, eta-beta method, environmental flow

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Authors: Hong Wu, Naiji Lu

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Improvement of health behavior among people with chronic diseases is vital for increasing longevity and enhancing quality of life. This paper researched the causal effects of informal care on the compliance with doctor’s health advices – smoking control, dietetic regulation, weight control and keep exercising – among older people with chronic diseases in China, which is facing the challenge of aging. We addressed the selection bias by using propensity score matching in the estimation process. We used the 2011-2012 national baseline data of the China Health and Retirement Longitudinal Study. Our results showed informal care can help improve health behavior of older people. First, informal care improved the compliance of smoking controls: whether smoke, frequency of smoking, and the time lag between wake up and the first cigarette was all lower for these older people with informal care; Second, for dietetic regulation, older people with informal care had more meals every day than older people without informal care; Third, three variables: BMI, whether gain weight and whether lose weight were used to measure the outcome of weight control. There were no significant difference between group with informal care and that without for BMI and the possibility of losing weight. Older people with informal care had lower possibility of gain weight than that without; Last, for the advice of keeping exercising, informal care increased the probability of walking exercise, however, the difference between groups for moderate and vigorous exercise were not significant. Our results indicate policy makers who aim to decrease accidents should take informal care to elders into account and provide an appropriate policy to meet the demand of informal care. Our birth policy and postponed retirement policy may decrease the informal caregiving hours, so adjustments of these policies are important and urgent to meet the current situation of aged tendency of population. In addition, government could give more support to develop organizations to provide formal care, such as nursing home. We infer that formal care is also useful for health behavior improvements.

Keywords: chronic diseases, compliance, CHARLS, health advice, informal care, older people, propensity score matching

Procedia PDF Downloads 404

Authors: Moetazza M. Al-Shafei, Hala Abdel Karim, Eitedal M. Daoud, Hassan Zaki Hassuna

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Epilepsy is a common neurological disorder affecting all age groups. It is one of the world's most prevalent non-communicable diseases. Increased evidence suggesting that long term usage of anti-epileptic drugs can have adverse effects on bone mineralization and bone molding .Aiming to study these effects and to give guide lines to support bone health through early intervention. From Neurology Out-Patient Clinic kaser Elaini University Hospital, 60 Patients were enrolled, 40 patients on antiepileptic drugs for at least two years and 20 controls matched with age and sex, epileptic but before starting treatment both chosen under specific criteria. Patients were divided into four groups, three groups with monotherapy treated with either Phynetoin, Valporic acid or Carbamazipine and fourth group treated with both Valporic acid and Carbamazipine. Estimation of serum Carboxy-Terminal Telopeptide of Type I- Collagen(ICTP) bone resorption marker, serum 25(OH )vit D3, calcium ,magnesium and phosphorus were done .Results showed that all patients on AED had significant low levels of 25(OH) vit D3 (p<0.001) ,with significant elevation of ICTP (P<0.05) versus controls. In group treated with Phynotoin highly significant elevation of (ICTP) marker and decrease of both serum 25(OH) vit D3 (P<0, 0001) and serum calcium(P<0.05)versus control. Double drug group showed significant decrease of serum 25(OH) vit D3 (P<0.0001) and decrease in Phosphorus (P<0.05) versus controls. Serum magnesium showed no significant differences between studied groups. We concluded that Anti- epileptic drugs appears to be an aggravating factor on bone mineralization ,so therapeutically it can be worth wile to supplement calcium and vitamin D even before initiation of antiepileptic therapy. ICTP marker can be used to evaluate change in bone resorption before and during AED therapy.

Keywords: antiepileptic drugs, bone minerals, carboxy teminal telopeptidetype-1-collagen bone resorption marker, vitamin D

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Authors: Lily Ingsrisawang, Tasanee Nacharoen

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Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

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Authors: Parimalah Velo, Ahmad Zakaria

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Introduction: Monte Carlo simulations of preclinical imaging systems allow opportunity to enable new research that could range from designing hardware up to discovery of new imaging application. The simulation system which could accurately model an imaging modality provides a platform for imaging developments that might be inconvenient in physical experiment systems due to the expense, unnecessary radiation exposures and technological difficulties. The aim of present study is to validate the Monte Carlo simulation of thyroid phantom imaging using Geant4-GATE for Siemen’s e-cam single head gamma camera. Upon the validation of the gamma camera simulation model by comparing physical characteristic such as energy resolution, spatial resolution, sensitivity, and dead time, the GATE simulation of thyroid phantom imaging is carried out. Methods: A thyroid phantom is defined geometrically which comprises of 2 lobes with 80mm in diameter, 1 hot spot, and 3 cold spots. This geometry accurately resembling the actual dimensions of thyroid phantom. A planar image of 500k counts with 128x128 matrix size was acquired using simulation model and in actual experimental setup. Upon image acquisition, quantitative image analysis was performed by investigating the total number of counts in image, the contrast of the image, radioactivity distributions on image and the dimension of hot spot. Algorithm for each quantification is described in detail. The difference in estimated and actual values for both simulation and experimental setup is analyzed for radioactivity distribution and dimension of hot spot. Results: The results show that the difference between contrast level of simulation image and experimental image is within 2%. The difference in the total count between simulation and actual study is 0.4%. The results of activity estimation show that the relative difference between estimated and actual activity for experimental and simulation is 4.62% and 3.03% respectively. The deviation in estimated diameter of hot spot for both simulation and experimental study are similar which is 0.5 pixel. In conclusion, the comparisons show good agreement between the simulation and experimental data.

Keywords: gamma camera, Geant4 application of tomographic emission (GATE), Monte Carlo, thyroid imaging

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Authors: Tobias Milz, L. Macpherson, Varvara Vetrova

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The law is a fundamental pillar of human societies as it shapes, controls and governs how humans conduct business, behave and interact with each other. Recent advances in computer-assisted technologies such as NLP, data science and AI are creating opportunities to support the practice, research and study of this pervasive domain. It is therefore not surprising that there has been an increase in investments into supporting technologies for the legal industry (also known as “legal tech” or “law tech”) over the last decade. A sub-discipline of particular appeal is concerned with assisted legal research. Supporting law researchers and practitioners to retrieve information from the vast amount of ever-growing legal documentation is of natural interest to the legal research community. One tool that has been in use for this purpose since the early nineteenth century is legal citation indexing. Among other use cases, they provided an effective means to discover new precedent cases. Nowadays, computer-assisted network analysis tools can allow for new and more efficient ways to reveal the “hidden” information that is conveyed through citation behavior. Unfortunately, access to openly available legal data is still lacking in New Zealand and access to such networks is only commercially available via providers such as LexisNexis. Consequently, there is a need to create, analyze and provide a legal citation network with sufficient data to support legal research tasks. This paper describes the development and analysis of a legal citation Network for New Zealand containing over 300.000 decisions from 125 different courts of all areas of law and jurisdiction. Using python, the authors assembled web crawlers, scrapers and an OCR pipeline to collect and convert court decisions from openly available sources such as NZLII into uniform and machine-readable text. This facilitated the use of regular expressions to identify references to other court decisions from within the decision text. The data was then imported into a graph-based database (Neo4j) with the courts and their respective cases represented as nodes and the extracted citations as links. Furthermore, additional links between courts of connected cases were added to indicate an indirect citation between the courts. Neo4j, as a graph-based database, allows efficient querying and use of network algorithms such as PageRank to reveal the most influential/most cited courts and court decisions over time. This paper shows that the in-degree distribution of the New Zealand legal citation network resembles a power-law distribution, which indicates a possible scale-free behavior of the network. This is in line with findings of the respective citation networks of the U.S. Supreme Court, Austria and Germany. The authors of this paper provide the database as an openly available data source to support further legal research. The decision texts can be exported from the database to be used for NLP-related legal research, while the network can be used for in-depth analysis. For example, users of the database can specify the network algorithms and metrics to only include specific courts to filter the results to the area of law of interest.

Keywords: case citation network, citation analysis, network analysis, Neo4j

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Authors: L. Nathaniel-Wurie

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The Sellick manoeuvre a.k.a the application of cricoid force (CF), was first described by Brian Sellick in 1961. CF is the application of digital pressure against the cricoid cartilage with the intention of posterior force causing oesophageal compression against the vertebrae. This is designed to prevent passive regurgitation of gastric contents, which is a major cause of morbidity and mortality during emergency airway management inside and outside of the hospital. To the authors knowledge, there is no universally standardised training modality and, therefore, no reliable way to examine if there are appropriate outcomes. If force is not measured during training, how can one surmise that appropriate, accurate, or precise amounts of force are being used routinely. Poor homogeneity in teaching and untested outcomes will correlate with reduced efficacy and increased adverse effects. For this study, the accuracy of force delivery in trained professionals was tested, and outcomes contrasted against a novice control and a novice study group. In this study, 20 operating department practitioners were tested (with a mean experience of 5.3years of performing CF). Subsequent contrast with 40 novice students who were randomised into one of two arms. ‘Arm A’ were explained the procedure, then shown the procedure then asked to perform CF with the corresponding force measurement being taken three times. Arm B had the same process as arm A then before being tested, they had 10, and 30 Newtons applied to their hands to increase intuitive understanding of what the required force equated to, then were asked to apply the equivalent amount of force against a visible force metre and asked to hold that force for 20 seconds which allowed direct visualisation and correction of any over or under estimation. Following this, Arm B were then asked to perform the manoeuvre, and the force generated measured three times. This study shows that there is a wide distribution of force produced by trained professionals and novices performing the procedure for the first time. Our methodology for teaching the manoeuvre shows an improved accuracy, precision, and homogeneity within the group when compared to novices and even outperforms trained practitioners. In conclusion, if this methodology is adopted, it may correlate with higher clinical outcomes, less adverse events, and more successful airway management in critical medical scenarios.

Keywords: airway, cricoid, medical education, sellick

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Authors: Manel Hammami, Gabriele Grandi

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In recent years, multilevel inverters have become more attractive for single-phase photovoltaic (PV) systems, due to their known advantages over conventional H-bridge pulse width-modulated (PWM) inverters. They offer improved output waveforms, smaller filter size, lower total harmonic distortion (THD), higher output voltages and others. The most common multilevel converter topologies, presented in literature, are the neutral-point-clamped (NPC), flying capacitor (FC) and Cascaded H-Bridge (CHB) converters. In both NPC and FC configurations, the number of components drastically increases with the number of levels what leads to complexity of the control strategy, high volume, and cost. Whereas, increasing the number of levels in case of the cascaded H-bridge configuration is a flexible solution. However, it needs isolated power sources for each stage, and it can be applied to PV systems only in case of PV sub-fields. In order to improve the ratio between the number of output voltage levels and the number of components, several hybrids and asymmetric topologies of multilevel inverters have been proposed in the literature such as the FC asymmetric H-bridge (FCAH) and the NPC asymmetric H-bridge (NPCAH) topologies. Another asymmetric multilevel inverter configuration that could have interesting applications is the cascaded asymmetric H-bridge (CAH), which is based on a modular half-bridge (two switches and one capacitor, also called level doubling network, LDN) cascaded to a full H-bridge in order to double the output voltage level. This solution has the same number of switches as the above mentioned AH configurations (i.e., six), and just one capacitor (as the FCAH). CAH is becoming popular, due to its simple, modular and reliable structure, and it can be considered as a retrofit which can be added in series to an existing H-Bridge configuration in order to double the output voltage levels. In this paper, an original and effective method for the analysis of the DC-link voltage ripple is given for single-phase asymmetric H-bridge multilevel inverters based on level doubling network (LDN). Different possible configurations of the asymmetric H-Bridge multilevel inverters have been considered and the analysis of input voltage and current are analytically determined and numerically verified by Matlab/Simulink for the case of cascaded asymmetric H-bridge multilevel inverters. A comparison between FCAH and the CAH configurations is done on the basis of the analysis of the DC and voltage ripple for the DC source (i.e., the PV system). The peak-to-peak DC and voltage ripple amplitudes are analytically calculated over the fundamental period as a function of the modulation index. On the basis of the maximum peak-to-peak values of low frequency and switching ripple voltage components, the DC capacitors can be designed. Reference is made to unity output power factor, as in case of most of the grid-connected PV generation systems. Simulation results will be presented in the full paper in order to prove the effectiveness of the proposed developments in all the operating conditions.

Keywords: asymmetric inverters, dc-link voltage, level doubling network, single-phase multilevel inverter

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Authors: Raj Banerjee, Aniruddha Sengupta

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An earthquake event, associated with a typical fault rupture, initiates at the source, propagates through a rock or soil medium and finally daylights at a surface which might be a populous city. The detrimental effects of an earthquake are often quantified in terms of the responses of superstructures resting on the soil. Hence, there is a need for the estimation of amplification of the bedrock motions due to the influence of local site conditions. In the present study, field borehole log data of Mangalwadi and Walkeswar sites in Mumbai city are considered. The data consists of variation of SPT N-value with the depth of soil. A correlation between shear wave velocity (Vₛ) and SPT N value for various soil profiles of Mumbai city has been developed using various existing correlations which is used further for site response analysis. MATLAB program is developed for studying the ground response analysis by performing two dimensional linear and equivalent linear analysis for some of the typical Mumbai soil sites using pure shear (Multi Point Constraint) boundary condition. The model is validated in linear elastic and equivalent linear domain using the popular commercial program, DEEPSOIL. Three actual earthquake motions are selected based on their frequency contents and durations and scaled to a PGA of 0.16g for the present ground response analyses. The results are presented in terms of peak acceleration time history with depth, peak shear strain time history with depth, Fourier amplitude versus frequency, response spectrum at the surface etc. The peak ground acceleration amplification factors are found to be about 2.374, 3.239 and 2.4245 for Mangalwadi site and 3.42, 3.39, 3.83 for Walkeswar site using 1979 Imperial Valley Earthquake, 1989 Loma Gilroy Earthquake and 1987 Whitter Narrows Earthquake, respectively. In the absence of any site-specific response spectrum for the chosen sites in Mumbai, the generated spectrum at the surface may be utilized for the design of any superstructure at these locations.

Keywords: deepsoil, ground response analysis, multi point constraint, response spectrum

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Authors: Pratima Poudel, Austin Himes, Heidi Renninger, Eric McConnel

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Populus spp. (poplar) are the fastest-growing trees in North America, making them ideal for a range of applications as they can achieve high yields on short rotations and regenerate by coppice. Furthermore, poplar undergoes biochemical conversion to fuels without complexity, making it one of the most promising, purpose-grown, woody perennial energy sources. Employing wood-based biomass for bioenergy offers numerous benefits, including reducing greenhouse gas (GHG) emissions compared to non-renewable traditional fuels, the preservation of robust forest ecosystems, and creating economic prospects for rural communities.In order to gain a better understanding of the potential use of poplar as a biomass feedstock for biofuel in the southeastern US, the conducted a techno-economic assessment (TEA). This assessment is an analytical approach that integrates technical and economic factors of a production system to evaluate its economic viability. the TEA specifically focused on a short rotation coppice system employing a single-pass cut-and-chip harvesting method for poplar. It encompassed all the costs associated with establishing dedicated poplar plantations, including land rent, site preparation, planting, fertilizers, and herbicides. Additionally, we performed a sensitivity analysis to evaluate how different costs can affect the economic performance of the poplar cropping system. This analysis aimed to determine the minimum average delivered selling price for one metric ton of biomass necessary to achieve a desired rate of return over the cropping period. To inform the TEA, data on the establishment, crop care activities, and crop yields were derived from a field study conducted at the Mississippi Agricultural and Forestry Experiment Station's Bearden Dairy Research Center in Oktibbeha County and Pontotoc Ridge-Flatwood Branch Experiment Station in Pontotoc County.

Keywords: biomass, populus species, sensitivity analysis, technoeconomic analysis

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Authors: Sakda Loetpiparwanich, Preecha Vichitthamaros

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Nowadays, poor data quality is considered one of the majority costs for a data project. The data project with data quality awareness almost as much time to data quality processes while data project without data quality awareness negatively impacts financial resources, efficiency, productivity, and credibility. One of the processes that take a long time is defining the expectations and measurements of data quality because the expectation is different up to the purpose of each data project. Especially, big data project that maybe involves with many datasets and stakeholders, that take a long time to discuss and define quality expectations and measurements. Therefore, this study aimed at developing meaningful indicators to describe overall data quality for each dataset to quick comparison and priority. The objectives of this study were to: (1) Develop a practical data quality indicators and measurements, (2) Develop data quality dimensions based on statistical characteristics and (3) Develop Composite Indicator that can describe overall data quality for each dataset. The sample consisted of more than 500 datasets from public sources obtained by random sampling. After datasets were collected, there are five steps to develop the Dataset Quality Index (SDQI). First, we define standard data quality expectations. Second, we find any indicators that can measure directly to data within datasets. Thirdly, each indicator aggregates to dimension using factor analysis. Next, the indicators and dimensions were weighted by an effort for data preparing process and usability. Finally, the dimensions aggregate to Composite Indicator. The results of these analyses showed that: (1) The developed useful indicators and measurements contained ten indicators. (2) the developed data quality dimension based on statistical characteristics, we found that ten indicators can be reduced to 4 dimensions. (3) The developed Composite Indicator, we found that the SDQI can describe overall datasets quality of each dataset and can separate into 3 Level as Good Quality, Acceptable Quality, and Poor Quality. The conclusion, the SDQI provide an overall description of data quality within datasets and meaningful composition. We can use SQDI to assess for all data in the data project, effort estimation, and priority. The SDQI also work well with Agile Method by using SDQI to assessment in the first sprint. After passing the initial evaluation, we can add more specific data quality indicators into the next sprint.

Keywords: data quality, dataset quality, data quality management, composite indicator, factor analysis, principal component analysis

Procedia PDF Downloads 138

Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Shin Woo Kim, Eui Ju Lee

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The recent development of biofuel production technology facilitates the use of bioethanol and biodiesel on automobile. Bioethanol, especially, can be used as a fuel for gasoline vehicles because the addition of ethanol has been known to increase octane number and reduce soot emissions. However, the wide application of biofuel has been still limited because of lack of detailed combustion properties such as auto-ignition temperature and pollutant emissions such as NOx and soot, which has been concerned mainly on the vehicle fire safety and environmental safety. In this study, the combustion characteristics of gasoline/ethanol fuel were investigated both numerically and experimentally. For auto-ignition temperature and NOx emission, the numerical simulation was performed on the well-stirred reactor (WSR) to simulate the homogeneous gasoline engine and to clarify the effect of ethanol addition in the gasoline fuel. Also, the response surface method (RSM) was introduced as a design of experiment (DOE), which enables the various combustion properties to be predicted and optimized systematically with respect to three independent variables, i.e., ethanol mole fraction, equivalence ratio and residence time. The results of stoichiometric gasoline surrogate show that the auto-ignition temperature increases but NOx yields decrease with increasing ethanol mole fraction. This implies that the bioethanol added gasoline is an eco-friendly fuel on engine running condition. However, unburned hydrocarbon is increased dramatically with increasing ethanol content, which results from the incomplete combustion and hence needs to adjust combustion itself rather than an after-treatment system. RSM results analyzed with three independent variables predict the auto-ignition temperature accurately. However, NOx emission had a big difference between the calculated values and the predicted values using conventional RSM because NOx emission varies very steeply and hence the obtained second order polynomial cannot follow the rates. To relax the increasing rate of dependent variable, NOx emission is taken as common logarithms and worked again with RSM. NOx emission predicted through logarithm transformation is in a fairly good agreement with the experimental results. For more tangible understanding of gasoline/ethanol fuel on pollutant emissions, experimental measurements of combustion products were performed in gasoline/ethanol pool fires, which is widely used as a fire source of laboratory scale experiments. Three measurement methods were introduced to clarify the pollutant emissions, i.e., various gas concentrations including NOx, gravimetric soot filter sampling for elements analysis and pyrolysis, thermophoretic soot sampling with transmission electron microscopy (TEM). Soot yield by gravimetric sampling was decreased dramatically as ethanol was added, but NOx emission was almost comparable regardless of ethanol mole fraction. The morphology of the soot particle was investigated to address the degree of soot maturing. The incipient soot such as a liquid like PAHs was observed clearly on the soot of higher ethanol containing gasoline, and the soot might be matured under the undiluted gasoline fuel.

Keywords: gasoline/ethanol fuel, NOx, pool fire, soot, well-stirred reactor (WSR)

Procedia PDF Downloads 211

Authors: Anamika Sahu

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The Himalayas, like many mountainous regions, is susceptible to multiple hazards. In recent times, the frequency of such disasters is continuously increasing due to extreme weather phenomena. These natural hazards are responsible for irreparable human and economic loss. The Indian Himalayas has repeatedly been ruptured by great earthquakes in the past and has the potential for a future large seismic event as it falls under the seismic gap. Damages caused by earthquakes are different in different localities. It is well known that, during earthquakes, damage to the structure is associated with the subsurface conditions and the quality of construction materials. So, for sustainable mountain development, prior estimation of site characterization will be valuable for designing and constructing the space area and for efficient mitigation of the seismic risk. Both geotechnical and geophysical investigation of the subsurface is required to describe the subsurface complexity. In mountainous regions, geophysical methods are gaining popularity as areas can be studied without disturbing the ground surface, and also these methods are time and cost-effective. The MASW method is used to calculate the Vs30. Vs30 is the average shear wave velocity for the top 30m of soil. Shear wave velocity is considered the best stiffness indicator, and the average of shear wave velocity up to 30 m is used in National Earthquake Hazards Reduction Program (NEHRP) provisions (BSSC,1994) and Uniform Building Code (UBC), 1997 classification. Parameters obtained through geotechnical investigation have been integrated with findings obtained through the subsurface geophysical survey. Joint interpretation has been used to establish inter-relationships among mineral constituents, various textural parameters, and unconfined compressive strength (UCS) with shear wave velocity. It is found that results obtained through the MASW method fitted well with the laboratory test. In both conditions, mineral constituents and textural parameters (grain size, grain shape, grain orientation, and degree of interlocking) control the petrophysical and mechanical properties of rocks and the behavior of shear wave velocity.

Keywords: MASW, mechanical, petrophysical, site characterization

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Authors: Soyon Kim, Edward Kim

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In order to retrieve information from the massive stream of songs in the music industry, music search by title, lyrics, artist, mood, and genre has become more important. Despite the subjectivity and controversy over the definition of music genres across different nations and cultures, automatic genre classification systems that facilitate the process of music categorization have been developed. Manual genre selection by music producers is being provided as statistical data for designing automatic genre classification systems. In this paper, an automatic music genre classification system utilizing non-negative matrix factorization (NMF) is proposed. Short-term characteristics of the music signal can be captured based on the timbre features such as mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), octave-based spectral contrast (OSC), and octave band sum (OBS). Long-term time-varying characteristics of the music signal can be summarized with (1) the statistical features such as mean, variance, minimum, and maximum of the timbre features and (2) the modulation spectrum features such as spectral flatness measure, spectral crest measure, spectral peak, spectral valley, and spectral contrast of the timbre features. Not only these conventional basic long-term feature vectors, but also NMF based feature vectors are proposed to be used together for genre classification. In the training stage, NMF basis vectors were extracted for each genre class. The NMF features were calculated in the log spectral magnitude domain (NMF-LSM) as well as in the basic feature vector domain (NMF-BFV). For NMF-LSM, an entire full band spectrum was used. However, for NMF-BFV, only low band spectrum was used since high frequency modulation spectrum of the basic feature vectors did not contain important information for genre classification. In the test stage, using the set of pre-trained NMF basis vectors, the genre classification system extracted the NMF weighting values of each genre as the NMF feature vectors. A support vector machine (SVM) was used as a classifier. The GTZAN multi-genre music database was used for training and testing. It is composed of 10 genres and 100 songs for each genre. To increase the reliability of the experiments, 10-fold cross validation was used. For a given input song, an extracted NMF-LSM feature vector was composed of 10 weighting values that corresponded to the classification probabilities for 10 genres. An NMF-BFV feature vector also had a dimensionality of 10. Combined with the basic long-term features such as statistical features and modulation spectrum features, the NMF features provided the increased accuracy with a slight increase in feature dimensionality. The conventional basic features by themselves yielded 84.0% accuracy, but the basic features with NMF-LSM and NMF-BFV provided 85.1% and 84.2% accuracy, respectively. The basic features required dimensionality of 460, but NMF-LSM and NMF-BFV required dimensionalities of 10 and 10, respectively. Combining the basic features, NMF-LSM and NMF-BFV together with the SVM with a radial basis function (RBF) kernel produced the significantly higher classification accuracy of 88.3% with a feature dimensionality of 480.

Keywords: mel-frequency cepstral coefficient (MFCC), music genre classification, non-negative matrix factorization (NMF), support vector machine (SVM)

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Authors: Manal Elsayed Elkheshin, Rasha Saleh Mansour, Mohamed Fawzy Mohamed Eldnasury, Mamdouh Elbadry Mohamed

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This research Aims to identify the main factors affecting the production and the fish consumption in Egypt, through the econometric estimation for various forms functions of fish production and fish consumption during the period (1991-2014), as the aim of this research to forecast the production and the fish consumption in Egypt until 2020, through determine the best standard methods using (ARIMA).This research also aims to the economic feasibility of the production of fish in aquaculture farms study; investment cost and represents the value of land, buildings, equipment and irrigation. Aquaculture requires three types of fish (Tilapia, carp fish, and mullet fish), and the total area of the farm, about an acre. The annual Fish production from this project about 3.5 tons. The annual investment costs of about 50500 pounds, Find conclude that the project can repay the cost of their investments after about 4 years and 5 months, and therefore recommend the implementation of the project, and internal rate of return reached (IRR) of about 22.1%, where it is clear that the rate of large internal rate of return, and achieves pound invested in this project annual return is estimated at 22.1 pounds, more than the opportunity cost, so we recommend the need to implement the project.Recommendations:1. Increasing the fish agriculture to decrease the gap of animal protein. 2.Increasing the number of mechanism fishing boats, and the provision of transport equipped to maintain the quality of fish production. 3.Encourage and attract the local and foreign investments, providing advice to the investor on the aquaculture field. 4. Action newsletters awareness of the importance of these projects where these projects resulted in a net profit after recovery in less than five years, IRR amounted to about 23%, which is much more than the opportunity cost of a bank interest rate is about 7%, helping to create work and graduates opportunities, and contribute to the reduction of imports of the fish, and improve the performance of the food trade balance.

Keywords: equation model, individual share, red meat, consumption, production, endogenous variable, exogenous variable, financial performance evaluates fish culture, feasibility study, fish production, aquaculture

Procedia PDF Downloads 367

Authors: Tatiane Benvenuti, Fernando Hamerski, Alexandre Giacobbo, Andrea M. Bernardes, Marco A. S. Rodrigues

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Population growth in urban areas has caused damages to the environment, a consequence of the uncontrolled dumping of domestic and industrial wastewater. The capacity of some plants to purify domestic and agricultural wastewater has been demonstrated by several studies. Since natural wetlands have the ability to transform, retain and remove nutrients, constructed wetlands have been used for wastewater treatment. They are widely recognized as an economical, efficient and environmentally acceptable means of treating many different types of wastewater. T. domingensis Pers. species have shown a good performance and low deployment cost to extract, detoxify and sequester pollutants. Constructed Floating Wetlands (CFWs) consist of emergent vegetation established upon a buoyant structure, floating on surface waters. The upper parts of the vegetation grow and remain primarily above the water level, while the roots extend down in the water column, developing an extensive under water-level root system. Thus, the vegetation grows hydroponically, performing direct nutrient uptake from the water column. Biofilm is attached on the roots and rhizomes, and as physical and biochemical processes take place, the system functions as a natural filter. The aim of this study is to diagnose the application of macrophytes in artificial floating in the treatment of domestic sewage in south Brazil. The T. domingensis Pers. plants were placed in a flotation system (polymer structure), in full scale, in a sewage treatment plant. The sewage feed rate was 67.4 m³.d⁻¹ ± 8.0, and the hydraulic retention time was 11.5 d ± 1.3. This CFW treat the sewage generated by 600 inhabitants, which corresponds to 12% of the population served by this municipal treatment plant. During 12 months, samples were collected every two weeks, in order to evaluate parameters as chemical oxygen demand (COD), biochemical oxygen demand in 5 days (BOD5), total Kjeldahl nitrogen (TKN), total phosphorus, total solids, and metals. The average removal of organic matter was around 55% for both COD and BOD5. For nutrients, TKN was reduced in 45.9% what was similar to the total phosphorus removal, while for total solids the reduction was 33%. For metals, aluminum, copper, and cadmium, besides in low concentrations, presented the highest percentage reduction, 82.7, 74.4 and 68.8% respectively. Chromium, iron, and manganese removal achieved values around 40-55%. The use of T. domingensis Pers. in artificial floating for sewage treatment is an effective and innovative alternative in Brazilian sewage treatment systems. The evaluation of additional parameters in the treatment system may give useful information in order to improve the removal efficiency and increase the quality of the water bodies.

Keywords: constructed wetland, floating system, sewage treatment, Typha domingensis Pers.

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Authors: Faiza Abdul Latip

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One of the ultimate goals of any nation is to produce competitive manpower and this includes Philippines. Inclination in the field of Mathematics has a significant role in achieving this goal. However, Mathematics, as considered by most people, is the most difficult subject matter along with its topics to learn. This could be manifested from the low performance of students in national and international assessments. Educators have been widely using learning style models in identifying the way students learn. Moreover, it could be the frontline in knowing the difficulties held by each learner in a particular topic specifically concepts pertaining to fractions. However, as what many educators observed, students show difficulties in doing mathematical tasks and in great degree in dealing with fractions most specifically in the district of Datu Odin Sinsuat, Maguindanao. This study focused on the Datu Odin Sinsuat district grade six pupils’ learning styles along with their achievements and difficulties in learning concepts on fractions. Five hundred thirty-two pupils from ten different public elementary schools of the Datu Odin Sinsuat districts were purposively used as the respondents of the study. A descriptive research using the survey method was employed in this study. Quantitative analysis on the pupils’ learning styles on the Kolb’s Learning Style Inventory (KLSI) and scores on the mathematics diagnostic test on fraction concepts were made using this method. The simple frequency and percentage counts were used to analyze the pupils’ learning styles and their achievements on fractions. To determine the pupils’ difficulties in fractions, the index of difficulty on every item was determined. Lastly, the Kruskal-Wallis Test was used in determining the significant difference in the pupils’ achievements on fractions classified by their learning styles. This test was set at 0.05 level of significance. The minimum H-Value of 7.82 was used to determine the significance of the test. The results revealed that the pupils of Datu Odin Sinsuat districts learn fractions in varied ways as they are of different learning styles. However, their achievements in fractions are low regardless of their learning styles. Difficulties in learning fractions were found most in the area of Estimation, Comparing/Ordering, and Division Interpretation of Fractions. Most of the pupils find it very difficult to use fraction as a measure, compare or arrange series of fractions and use the concept of fraction as a quotient.

Keywords: difficulties in fraction, fraction, Kolb's model, learning styles

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Authors: Gauri Sreekumar, Sabuj Kumar Mandal

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Contributing about 18% to India’s Gross Domestic Product, the agricultural sector plays a significant role in the Indian rural economy. Despite being the primary source of livelihood for more than half of India’s population, most of them are marginal and small farmers facing several challenges due to agro-climatic shocks. Climate change is expected to increase the risk in the regions that are highly agriculture dependent. With systematic and scientific evidence of changes in rainfall, temperature and other extreme climate events, migration started to emerge as a survival strategy for the farm households. In this backdrop, our present study aims to combine the two strands of literature and attempts to explore whether migration is the only adaptation strategy for the farmers once they experience crop failures due adverse climatic condition. Combining the temperature and rainfall information from the weather data provided by the Indian Meteorological Department with the household level panel data on Indian states belonging to the Eastern and Semi-Arid Tropics regions from the Village Dynamics in South Asia (VDSA) collected by the International Crop Research Institute for the Semi-arid Tropics, we form a rich panel data for the years 2010-2014. A Recursive Econometric Model is used to establish the three-way nexus between climate change-yield-migration while addressing the role of irrigation and local non-farm income diversification. Using Three Stage Least Squares Estimation method, we find that climate change induced yield loss is a major driver of farmers’ migration. However, irrigation and local level non-farm income diversification are found to mitigate the adverse impact of climate change on migration. Based on our empirical results, we suggest for enhancing irrigation facilities and making local non-farm income diversification opportunities available to increase farm productivity and thereby reduce farmers’ migration.

Keywords: climate change, migration, adaptation, mitigation

Procedia PDF Downloads 63

Authors: Ksenija Taški-Ajdukovic, Nevena Nagl, Živko Ćurčić, Dario Danojević

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Information about genetic diversity of sugar beet parental populations is of a great importance for hybrid breeding programs. The aim of this research was to evaluate genetic diversity among and within populations and lines of diploid sugar beet pollinators, by using SSR markers. As plant material were used eight pollinators originating from three USDA-ARS breeding programs and four pollinators from Institute of Field and Vegetable Crops, Novi Sad. Depending on the presence of self-fertility gene, the pollinators were divided into three groups: autofertile (inbred lines), autosterile (open-pollinating populations), and group with partial presence of autofertility gene. A total of 40 SSR primers were screened, out of which 34 were selected for the analysis of genetic diversity. A total of 129 different alleles were obtained with mean value 3.2 alleles per SSR primer. According to the results of genetic variability assessment the number and percentage of polymorphic loci was the maximal in pollinators NS1 and tester cms2 while effective number of alleles, expected heterozygosis and Shannon’s index was highest in pollinator EL0204. Analysis of molecular variance (AMOVA) showed that 77.34% of the total genetic variation was attributed to intra-varietal variance. Correspondence analysis results were very similar to grouping by neighbor-joining algorithm. Number of groups was smaller by one, because correspondence analysis merged IFVCNS pollinators with CZ25 into one group. Pollinators FC220, FC221 and C 51 were in the next group, while self-fertile pollinators CR10 and C930-35 from USDA-Salinas were separated. On another branch were self-sterile pollinators ЕL0204 and ЕL53 from USDA-East Lansing. Sterile testers cms1 and cms2 formed separate group. The presented results confirmed that SSR analysis can be successfully used in estimation of genetic diversity within and among sugar beet populations. Since the tested pollinator differed considering the presence of self-fertility gene, their heterozygosity differed as well. It was lower in genotypes with fixed self-fertility genes. Since the most of tested populations were open-pollinated, which rarely self-pollinate, high variability within the populations was expected. Cluster analysis grouped populations according to their origin.

Keywords: auto fertility, genetic diversity, pollinator, SSR, sugar beet

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Authors: Vinay C. Doranalu, Amba Shetty

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In recent days due to climate change, there is a large variation in spatial distribution of daily rainfall within a small region. Rainfall is one of the main end climatic variables which affect spatio-temporal patterns of water availability. The real task postured by the change in climate is identification, estimation and understanding the uncertainty of rainfall. This study intended to analyze the spatial variations and temporal trends of daily precipitation using high resolution (0.25º x 0.25º) gridded data of Indian Meteorological Department (IMD). For the study, 38 grid points were selected in the study area and analyzed for daily precipitation time series (113 years) over the period 1901-2013. Grid points were divided into two zones based on the elevation and situated location of grid points: Low Land (exposed to sea and low elevated area/ coastal region) and High Land (Interior from sea and high elevated area/western Ghats). Time series were applied to examine the spatial analysis and temporal trends in each grid points by non-parametric Mann-Kendall test and Theil-Sen estimator to perceive the nature of trend and magnitude of slope in trend of rainfall. Pettit-Mann-Whitney test is applied to detect the most probable change point in trends of the time period. Results have revealed remarkable monotonic trend in each grid for daily precipitation of the time series. In general, by the regional cluster analysis found that increasing precipitation trend in shoreline region and decreasing trend in Western Ghats from recent years. Spatial distribution of rainfall can be partly explained by heterogeneity in temporal trends of rainfall by change point analysis. The Mann-Kendall test shows significant variation as weaker rainfall towards the rainfall distribution over eastern parts of the Western Ghats region of Karnataka.

Keywords: change point analysis, coastal region India, gridded rainfall data, non-parametric

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Authors: Abram Zoltan

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Over the past hundred years, human activities, particularly the burning of fossil fuels, have released enough carbon dioxide and other greenhouse gases to dissipate additional heat into the lower atmosphere and affect the global climate. Climate change affects many social and environmental determinants of health: clean air, safe drinking water, and adequate food. Our aim is to draw attention to the effects of climate change on the health and health care system. Improving climate awareness and the knowledge related to climate change's health impacts are essential among medical students and practicing medical doctors. Therefore, in their everyday practice, they also need some assistance and up-to-date knowledge of how climate change can endanger human health and deal with these novel health problems. Our activity, based on the cooperation of more universities, aims to develop new curriculum outlines and learning materials on climate change's health impacts for medical schools. Special attention is intended to pay to the possible preventative measures against these impacts. For all of this, the project plans to create new curriculum outlines and learning materials for medical students, elaborate methodological guidelines and create training materials for medical doctors' postgraduate learning programs. The target groups of the project are medical students, educational staff of medical schools and universities, practicing medical doctors with special attention to the general practitioners and family doctors. We had searched various surveys, domestic and international studies about the effects of climate change and statistical estimation of the possible consequences. The health effects of climate change can be measured only approximately by considering only a fraction of the potential health effects and assuming continued economic growth and health progress. We can estimate that climate change is expected to cause about 250,000 more deaths. We conclude that climate change is one of the most serious problems of the 21st century, affecting all populations. In the short- to medium-term, the health effects of climate change will be determined mainly by human vulnerability. In the longer term, the effects depend increasingly on the extent to which transformational action is taken now to reduce emissions. We can contribute to reducing environmental pollution by raising awareness and by educating the population.

Keywords: climate change, health impacts, medical students, education

Procedia PDF Downloads 125