Search results for: bid estimate

Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: Dibya Jivan Pati, Kazuhisa Iki, Riken Homma

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Unlike other metro cities of India, Bhubaneswar–the capital city of Odisha, is expected to reach 1-million-mark population by now. The demands of dwelling unit requirement mostly among urban poor belonging to Economically Weaker section (EWS) and Low Income groups (LIG) is becoming a challenge due to high housing cost and rents. As a matter of fact, it’s also noted that, with increase in population, the solid waste generation also increases subsequently affecting the environment due to inefficiency in collection of waste by local government bodies. Methods of utilizing Solid Waste - especially in form of Plastic bottles, Glass bottles and Metal cans (PGM) are now widely used as an alternative material for construction of low-cost building by Non-Government Organizations (NGOs) in developing countries like India to help the urban poor afford a shelter. The application of disposed plastic bottle used in construction of single dwelling significantly reduces the overall cost of construction to as much as 14% compared to traditional construction material. Therefore, considering its cost-benefit result, it’s possible to provide housing to EWS and LIGs at an affordable price. In this paper, we estimated the quantity of plastic bottles generated in Bhubaneswar which further helped to estimate the possible number of single dwelling unit that can be constructed on yearly basis so as to refrain from further housing shortage. The estimation results will be practically used for planning and managing low-cost housing business by local government and NGOs.

Keywords: construction, dwelling unit, plastic bottle, solid waste generation, groups

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Authors: Ali H.Alyami, Hussam Darraj, Faisal Hakami, Mohammed Awaf, Sulaiman Hamdi, Nawaf Bakri, Abdulaziz Saber, Khalid Hakami, Almuhanad Alyami, Mohammed khashab

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Introduction: Adolescents frequently self-report pain, according to epidemiological research. The knee is one of the sites where the pain is most common. One of the main factors contributing to the number of years people spend disabled and having substantial personal, societal, and economic burdens globally are musculoskeletal disorders. Adolescents may have knee pain due to an abrupt, traumatic injury or an insidious, slowly building onset that neither the adolescent nor the parent is aware of. Objectives: The present study’s authors aimed to estimate the prevalence of knee pain in Saudi adolescents. Methods: This cross-sectional survey, carried out from June to November 2022, included 676 adolescents ages 10 to 18. Data are presented as frequencies and percentages for categorical variables. Analysis of variance (ANOVA) was used to compare means between groups, while the chi-square test was used for the comparison of categorical variables. Statistical significance was set at P< 0.05.Result: Adolescents were invited to take part in the study. 57.5% were girls, and 42.5% were males,68.8% were 676 aged between 15 and 18. The prevalence of knee pain was considerably high among females (26%), while it was 19.2% among males. Moreover, age was a significant predictor for knee pain; also BMI was significant for knee pain. Conclusion: Our study noted a high rate of knee pain among adolescents, so we need to raise awareness about risk factors. Adolescent knee pain can be prevented with conservative methods and some minor lifestyle/activity modifications.

Keywords: knee pain, prevalence of knee pain, exercise training, physical activity

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Authors: Rupesh K. Chaudhary, Narinder P. Jain, Rajesh Mahajan, Rajat Manchanda

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Introduction: Delirium is a complex, multifactorial neuropsychiatric syndrome comprising a broad range of cognitive and neurobehavioral symptoms. In critically ill patients, it may develop secondary to multiple predisposing factors. Although it can be transient and irreversible but if left untreated may lead to long term cognitive dysfunction. Early identification and assessment of risk factors usually help in appropriate management of delirium which in turn leads to decreased hospital stay, cost of therapy and mortality. Aim and Objective: Aim of the present study was to estimate the incidence of delirium using a validated scale in medical ICU patients and to determine the associated risk factors and outcomes. Material and Method: A prospective study in an 18-bed medical-intensive care unit (ICU) was undertaken. A total of 357 consecutive patients admitted to ICU for more than 24 hours were assessed. These patients were screened with the help of Confusion Assessment Method for Intensive Care Unit -CAM-ICU, Richmond Agitation and Sedation Scale, Screening Checklist for delirium and APACHE II. Appropiate statistical analysis was done to evaluate the risk factors influencing mortality in delirium. Results: Delirium occurred in 54.6% of 194 patients. Risk of delirium was independently associated with a history of hypertension, diabetes but not with severity of illness APACHE II score. Delirium was linked to longer ICU stay 13.08 ± 9.6 ver 7.07 ± 4.98 days, higher ICU mortality (35.8% % vs. 17.0%). Conclusion: Our study concluded that delirium poses a great risk factor in the outcome of the patient and carries high mortality, so a timely intervention helps in addressing these issues.

Keywords: delirium, risk factors, outcome, intervention

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Authors: Mohammad Naeem Lakanwall, Jamshid Abdul-Ghafar

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Background: Endocrinopathies are a commonly occurring entity, particularly those of the thyroid gland; however, there is a lack of scientific literature from Afghanistan, a country with very limited health care facilities and resources. To our best knowledge, this is the first study aimed to describe the frequency of occurrence and factors associated with thyroid dysfunction in the Afghan population. The aim of this study is to estimate the frequency and to identify factors associated with thyroid dysfunction among individuals coming to a tertiary care facility in Kabul, Afghanistan. Methods: A cross-sectional study was conducted from July to Sep 2018 at the Department of Clinical Pathology, French Medical Institute for Mothers and Children (FMIC), Kabul, Afghanistan. Blood samples were obtained, serum TSH levels were analyzed, and the patients were divided into three diagnostic categories according to their serum TSH concentrations: 1) hypothyroidism, 2) hyperthyroidism, 3) normal. Results: A total of 127 individuals were included in the final analysis. The majority of study participants (77%) were females. A large number of the participants (92%) did not have a family history of thyroid dysfunction. 74% of the participants in the study had normal TSH levels classified as normal thyroid function, (14%) had lower TSH levels, and (12%) higher TSH levels, classified as hyper and hypothyroid, respectively. Conclusions: The findings of the current study showed a high frequency of thyroid dysfunctions from a single center. Further large-scale studies are needed to find out the prevalence and document this entity for better health outcomes in the country.

Keywords: Afghanistan, factors, frequency, hypothyroid, hyperthyroid, thyroid, thyroid stimulating hormone

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Authors: M. Goliszek, M. Sobiesiak, O. Sevastyanova, B. Podkoscielna

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Lignin is one of three main constituents of biomass together with cellulose and hemicellulose. It is a complex biopolymer, which contains a large number of functional groups, including aliphatic and aromatic hydroxyl groups, carbohylic groups and methoxy groups in its structure, that is why it shows potential capacities for process of sorption. Lignin is a highly cross-linked polymer with a three-dimentional structure which can provide large surface area and pore volumes. It can also posses better dispersion, diffusion and mass transfer behavior in a field of the removal of, e.g., heavy-metal-ions or aromatic pollutions. In this work emulsion-suspension copolymerization method, to synthesize the porous microspheres of divinylbenzene (DVB), styrene (St) and lignin was used. There are also microspheres without the addition of lignin for comparison. Before the copolymerization, modification lignin with methacryloyl chloride, to improve its reactivity with other monomers was done. The physico-chemical properties of the obtained microspheres, e.g., pore structures (adsorption-desorption measurements), thermal properties (DSC), tendencies to swell and the actual shapes were also studied. Due to well-developed porous structure and the presence of functional groups our materials may have great potential in sorption processes. To estimate the sorption capabilities of the microspheres towards phenol and its chlorinated derivatives the off-line SPE (solid-phase extraction) method is going to be applied. This method has various advantages, including low-cost, easy to use and enables the rapid measurements for a large number of chemicals. The efficiency of the materials in removing phenols from aqueous solution and in desorption processes will be evaluated.

Keywords: microspheres, lignin, sorption, solid-phase extraction

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Authors: Helene Thieblemont, Fariborz Haghighat

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Energy storage systems play a crucial role in decreasing building energy consumption during peak periods and expand the use of renewable energies in buildings. To provide a high building thermal performance, the energy storage system has to be properly controlled to insure a good energy performance while maintaining a satisfactory thermal comfort for building’s occupant. In the case of passive discharge storages, defining in advance the required amount of energy is required to avoid overheating in the building. Consequently, anticipatory supervisory control strategies have been developed forecasting future energy demand and production to coordinate systems. Anticipatory supervisory control strategies are based on some predictions, mainly of the weather forecast. However, if the forecasted hourly outdoor temperature may be found online with a high accuracy, solar radiations predictions are most of the time not available online. To estimate them, this paper proposes an advanced approach based on the forecast of weather conditions. Several methods to correlate hourly weather conditions forecast to real hourly solar radiations are compared. Results show that using weather conditions forecast allows estimating with an acceptable accuracy solar radiations of the next day. Moreover, this technique allows obtaining hourly data that may be used for building models. As a result, this solar radiation prediction model may help to implement model-based controller as Model Predictive Control.

Keywords: anticipatory control, model predictive control, solar radiation forecast, thermal storage

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Authors: Rajarshi Sharma, Rashidul Alam, Visavino Seleyi, Yuvila Sangtam

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The Intensity-Duration-Frequency (IDF) relationship of rainfall amounts is one of the most commonly used tools in water resources engineering for planning, design and operation of water resources project, or for various engineering projects against design floods. The establishment of such relationships was reported as early as in 1932 (Bernard). Since then many sets of relationships have been constructed for several parts of the globe. The objective of this research is to derive IDF relationship of rainfall for western watershed of Guwahati, Assam. These relationships are useful in the design of urban drainage works, e.g. storm sewers, culverts and other hydraulic structures. In the study, rainfall depth for 10 years viz. 2001 to 2010 has been collected from the Regional Meteorological Centre Borjhar, Guwahati. Firstly, the data has been used to construct the mass curve for duration of more than 7 hours rainfall to calculate the maximum intensity and to form the intensity duration curves. Gumbel’s frequency analysis technique has been used to calculate the probable maximum rainfall intensities for a period of 2 yr, 5 yr, 10 yr, 50 yr, 100 yr from the maximum intensity. Finally, regression analysis has been used to develop the intensity-duration-frequency (IDF) curve. Thus, from the analysis the values for the constants ‘a’,‘b’ &‘c’ have been found out. The values of ‘a’ for which the sum of the squared deviation is minimum has been found out to be 40 and when the corresponding value of ‘c’ and ‘b’ for the minimum squared deviation of ‘a’ are 0.744 and 1981.527 respectively. The results obtained showed that in all the cases the correlation coefficient is very high indicating the goodness of fit of the formulae to estimate IDF curves in the region of interest.

Keywords: intensity-duration-frequency relationship, mass curve, regression analysis, correlation coefficient

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Authors: Rajkumar Ghosh

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The study presents an overview of the many uses and approaches for estimating out-of-sequence thrust movement in earthquake mitigation. The study investigates how knowing and forecasting thrust movement during seismic occurrences might assist to effective earthquake mitigation measures. The review begins by discussing out-of-sequence thrust movement and its importance in earthquake mitigation strategies. It explores how typical techniques of estimating thrust movement may not capture the full complexity of seismic occurrences and emphasizes the benefits of include out-of-sequence data in the analysis. A thorough review of existing research and studies on out-of-sequence thrust movement estimates for earthquake mitigation. The study demonstrates how to estimate out-of-sequence thrust movement using multiple data sources such as GPS measurements, satellite imagery, and seismic recordings. The study also examines the use of out-of-sequence thrust movement estimates in earthquake mitigation measures. It investigates how precise calculation of thrust movement may help improve structural design, analyse infrastructure risk, and develop early warning systems. The potential advantages of using out-of-sequence data in these applications to improve the efficiency of earthquake mitigation techniques. The difficulties and limits of estimating out-of-sequence thrust movement for earthquake mitigation. It addresses data quality difficulties, modelling uncertainties, and computational complications. To address these obstacles and increase the accuracy and reliability of out-of-sequence thrust movement estimates, the authors recommend topics for additional study and improvement. The study is a helpful resource for seismic monitoring and earthquake risk assessment researchers, engineers, and policymakers, supporting innovations in earthquake mitigation measures based on a better knowledge of thrust movement dynamics.

Keywords: earthquake mitigation, out-of-sequence thrust, satellite imagery, seismic recordings, GPS measurements

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Authors: Rogelio Omar Corona-Núñez, Alma Mendoza-Ponce

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The Tropical Dry Forest not only is one of the most important tropical ecosystems in terms of area, but also it is one of the most degraded ecosystems. However, little is known about the degradation impacts on carbon stocks, therefore in carbon emissions. There are different studies which explain its deforestation dynamics, but there is still a lack of understanding of how they correlate to carbon losses. Recently different authors have built current biomass maps for the tropics and Mexico. However, it is not clear how well they predict at the local scale, and how they can be used to estimate carbon emissions. This study quantifies the forest net carbon losses by comparing the potential carbon stocks and the different current biomass maps in the Southern Pacific coast in Oaxaca, Mexico. The results show important differences in the current biomass estimates with not a clear agreement. However, by the aggregation of the information, it is possible to infer the general patterns of biomass distribution and it can identify the driving forces of the carbon emissions. This study estimated that currently ~44% of the potential carbon stock estimated for the region is still present. A total of 6,764 GgC has been emitted due to deforestation and degradation of the forest at a rate of above ground biomass loss of 66.4 Mg ha-1. Which, ~62% of the total carbon emissions can be regarded as being due to forest degradation. Most of carbon losses were identified in places suitable for agriculture, close to rural areas and to roads while the lowest losses were accounted in places with high water stress and within the boundaries of the National Protected Area. Moreover, places not suitable for agriculture, but close to the coast showed carbon losses as a result of urban settlements.

Keywords: above ground biomass, deforestation, degradation, driving forces, tropical deciduous forest

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Authors: Farouk Metiri, Halim Zeghdoudi, Mohamed Riad Remita

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Credibility theory is an experience rating technique in actuarial science which can be seen as one of quantitative tools that allows the insurers to perform experience rating, that is, to adjust future premiums based on past experiences. It is used usually in automobile insurance, worker's compensation premium, and IBNR (incurred but not reported claims to the insurer) where credibility theory can be used to estimate the claim size amount. In this study, we focused on a popular tool in credibility theory which is the Bayesian premium estimator, considering Lindley distribution as a claim distribution. We derive this estimator under entropy loss which is asymmetric and squared error loss which is a symmetric loss function with informative and non-informative priors. In a purely Bayesian setting, the prior distribution represents the insurer’s prior belief about the insured’s risk level after collection of the insured’s data at the end of the period. However, the explicit form of the Bayesian premium in the case when the prior is not a member of the exponential family could be quite difficult to obtain as it involves a number of integrations which are not analytically solvable. The paper finds a solution to this problem by deriving this estimator using numerical approximation (Lindley approximation) which is one of the suitable approximation methods for solving such problems, it approaches the ratio of the integrals as a whole and produces a single numerical result. Simulation study using Monte Carlo method is then performed to evaluate this estimator and mean squared error technique is made to compare the Bayesian premium estimator under the above loss functions.

Keywords: bayesian estimator, credibility theory, entropy loss, monte carlo simulation

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Authors: Tabti Lahouaria, Kahlouche Salem, Benadda Belkacem, Beldjilali Bilal

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The European Geostationary Navigation Overlay Service (EGNOS) provides an augmentation signal to GPS (Global Positioning System) single point positioning. Presently EGNOS provides data correction and integrity information using the GPS L1 (1575.42 MHz) frequency band. The main objective of this system is to provide a better real-time positioning precision than using GPS only. They are expected to be used with single-frequency code observations. EGNOS offers navigation performance for an open service (OS), in terms of precision and availability this performance gradually degrades as moving away from the service area. For accurate system performance, the service will become less and less available as the user moves away from the EGNOS service. The improvement in position solution is investigated using the two collocated dual frequency GPS, where no EGNOS Ranging and Integrity Monitoring Station (RIMS) exists. One of the pseudo-range was kept as GPS stand-alone and the other was corrected by EGNOS to estimate the planimetric and altimetric precision for different dates. It is found that precision in position improved significantly in the second due to EGNOS correction. The performance of EGNOS system in the north of Algeria is also investigated in terms of integrity. The results show that the horizontal protection level (HPL) value is below 18.25 meters (95%) and the vertical protection level (VPL) is below 42.22 meters (95 %). These results represent good integrity information transmitted by EGNOS for APV I service. This service is thus compliant with the aviation requirements for Approaches with Vertical Guidance (APV-I), which is characterised by 40 m HAL (horizontal alarm limit) and 50 m VAL (vertical alarm limit).

Keywords: EGNOS, GPS, positioning, integrity, protection level

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Authors: Youssef Mazloum, Haytham Sayah, Maroun Nemer

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The penetration of renewable energy sources into the electric grid is significantly increasing. However, the intermittence of these sources breaks the balance between supply and demand for electricity. Hence, the importance of the energy storage technologies, they permit restoring the balance and reducing the drawbacks of intermittence of the renewable energies. This paper discusses the modeling and the cost-effectiveness of an isobaric adiabatic compressed air energy storage (IA-CAES) system. The proposed system is a combination among a compressed air energy storage (CAES) system with pumped hydro storage system and thermal energy storage system. The aim of this combination is to overcome the disadvantages of the conventional CAES system such as the losses due to the storage pressure variation, the loss of the compression heat and the use of fossil fuel sources. A steady state model is developed to perform an energy and exergy analyses of the IA-CAES system and calculate the distribution of the exergy losses in the latter system. A sensitivity analysis is also carried out to estimate the effects of some key parameters on the system’s efficiency, such as the pinch of the heat exchangers, the isentropic efficiency of the rotating machinery and the pressure losses. The conducted sensitivity analysis is a local analysis since the sensibility of each parameter changes with the variation of the other parameters. Therefore, an exergoeconomic study is achieved as well as a cost optimization in order to reduce the electricity cost produced during the production phase. The optimizer used is OmOptim which is a genetic algorithms based optimizer.

Keywords: cost-effectiveness, Exergoeconomic analysis, isobaric adiabatic compressed air energy storage (IA-CAES) system, thermodynamic modeling

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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An estimating equation technique is an alternative method of the widely used maximum likelihood methods, which enables us to ease some complexity due to the complex characteristics of time-varying covariates. In the situations, when both the time-varying covariates and left-truncation are considered in the model, the maximum likelihood estimation procedures become much more burdensome and complex. To ease the complexity, in this study, the modified estimating equations those have been given high attention and considerations in many researchers under semiparametric transformation model was proposed. The purpose of this article was to develop the modified estimating equation under flexible and general class of semiparametric transformation models for left-truncated and right censored survival data with time-varying covariates. Besides the commonly applied Cox proportional hazards model, such kind of problems can be also analyzed with a general class of semiparametric transformation models to estimate the effect of treatment given possibly time-varying covariates on the survival time. The consistency and asymptotic properties of the estimators were intuitively derived via the expectation-maximization (EM) algorithm. The characteristics of the estimators in the finite sample performance for the proposed model were illustrated via simulation studies and Stanford heart transplant real data examples. To sum up the study, the bias for covariates has been adjusted by estimating density function for the truncation time variable. Then the effect of possibly time-varying covariates was evaluated in some special semiparametric transformation models.

Keywords: EM algorithm, estimating equation, semiparametric transformation models, time-to-event outcomes, time varying covariate

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Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

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Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion process, trends functions, bi-parameters weibull density function

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Authors: N. R. P Withana, E. Auch

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The purpose of this study was to investigate perceptions of climate change risk to forest ecosystems and forest-based communities as well as perceived effectiveness of adaptation strategies for climate change as well as challenges for adaptation. Data was gathered using a pre-tested semi-structured questionnaire. Simple random selection technique was applied. For the majority of issues, the responses were obtained on multi-point Likert scales, and the scores provided were, in turn, used to estimate the means and other useful estimates. A composite knowledge index developed using correct responses to a set of self-rated statements were used to evaluate the issues. The mean of the knowledge index was 0.64. Also all respondents recorded values of the knowledge index above 0.25. Increase forest fire was perceived by respondents as the greatest risk to forest eco-system. Decrease access to water supplies was perceived as the greatest risk to livelihoods of forest based communities. The most effective adaptation strategy relevant to climate change risks to forest eco-systems and forest based communities livelihoods in Kathmandu valley in Nepal as perceived by the respondents was reforestation and afforestation. As well, lack of public awareness was perceived as the major limitation for climate change adaptation. However, perceived risks as well as effective adaptation strategies showed an inconsistent association with knowledge indicators and social-cultural variables. The results provide useful information to any party who involve with climate change issues in Nepal, since such attempts would be more effective once the people’s perceptions on these aspects are taken into account.

Keywords: climate change, risk perceptions, forest ecosystems, forest-based communities

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Authors: G. M. Contessa, L. Lepore, G. Gandolfo, C. Poggi, N. Cherubini, R. Remetti, S. Sandri

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Practical guidelines are provided in this work for the safe use of a portable d-t Thermo Scientific MP-320 neutron generator producing pulsed 14.1 MeV neutron beams. The neutron generator’s emission was tested experimentally and reproduced by MCNPX Monte Carlo code. Simulations were particularly accurate, even generator’s internal components were reproduced on the basis of ad-hoc collected X-ray radiographic images. Measurement campaigns were conducted under different standard experimental conditions using an LB 6411 neutron detector properly calibrated at three different energies, and comparing simulated and experimental data. In order to estimate the dose to the operator vs. the operating conditions and the energy spectrum, the most appropriate value of the conversion factor between neutron fluence and ambient dose equivalent has been identified, taking into account both direct and scattered components. The results of the simulations show that, in real situations, when there is no information about the neutron spectrum at the point where the dose has to be evaluated, it is possible - and in any case conservative - to convert the measured value of the count rate by means of the conversion factor corresponding to 14 MeV energy. This outcome has a general value when using this type of generator, enabling a more accurate design of experimental activities in different setups. The increasingly widespread use of this type of device for industrial and medical applications makes the results of this work of interest in different situations, especially as a support for the definition of appropriate radiation protection procedures and, in general, for risk analysis.

Keywords: instrumentation and monitoring, management of radiological safety, measurement of individual dose, radiation protection of workers

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Authors: Sohair Hassan, Olfat Hammam, Sahar Hussein, Wessam Magdi

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Objective: Acute liver failure (ALF) is a clinical condition with an unclear history of pathophysiology, making it a challenging task for scientists to reverse the disease in its initial phase and to help the liver re-function customary: this study aimed to estimate the hepatoprotective effects of Punica granatum Lpeel and Pistacia atlantica leaves as a multi-rich antioxidants ingredients either in their normal and/or in their nanoforms against thioacetamide induced acute liver failure in a rodent model. Method: Male Wistar rats (n=60) were divided into six equal groups, the first group employed as a control; The second group administered a dose of 350 mg /Kg/ b.w of thioacetamide (TAA)-IP, from the third to the sixth group received TAA + [2mls / 100 g b.w/d] of aqueous extracts of Punica granatum L and Pistacia atlantica either in their normal and/or Nano forms consecutively for (14 days) Results: Recorded significant elevation in liver enzymes, lipid profiles, LPO (p= 0.05) and NO with a marked significant decrease in GSH and SOD accompanied by an elevation in inflammatory cytokine (IL6, TNF-α, and AFP) in addition to a noticeable increase in HSP70 level & degradation in DNA respectively in TAA challenged group. However significant and subsequent amelioration of most of the impaired markers was observed with ip nano treatment of both extracts. Conclusion: The current results highlighted the high performance of both plant nano extracts and their hepatoprotective impact and their possible therapeutic role in the amelioration of TAA induced acute liver failure in experimental animals.

Keywords: acute liver failure HPLC, IL6, nano extracts, thioacetamide, TNF-α

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Authors: Poojan Vora, Hardik Pancholi, Sanket Tajane, Harsh Shah, Elias Keedy

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The global COVID-19 pandemic has affected the industry drastically in many ways. Even though the vaccine is being distributed quickly and despite the decreasing number of positive cases, testing is projected to remain a key aspect of the ‘new normal’. Improving existing plant layout and improving safety within the facility are of great importance in today’s industries because of the need to ensure productivity optimization and reduce safety risks. In practice, it is essential for any manufacturing plant to reduce nonvalue adding steps such as the movement of materials and rearrange similar processes. In the current pandemic situation, optimized layouts will not only increase safety measures but also decrease the fixed cost per unit manufactured. In our case study, we carefully studied the existing layout and the manufacturing steps of a new Texas start-up company that manufactures COVID testing kits. The effects of production rate are incorporated with the computerized relative allocation of facilities technique (CRAFT) algorithm to improve the plant layout and estimate the optimization parameters. Our work reduces the company’s material handling time and increases their daily production. Real data from the company are used in the case study to highlight the importance of colleges in fostering small business needs and improving the collaboration between college researchers and industries by using existing models to advance best practices.

Keywords: computerized relative allocation of facilities technique, facilities planning, optimization, start-up business

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Authors: Rutebuka Evariste, Zhang Lixiao

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Mobile phone sales and stocks showed an exponential growth in the past years globally and the number of mobile phones produced each year was surpassing one billion in 2007, this soaring growth of related e-waste deserves sufficient attentions paid to it regionally and globally as long as 40% of its total weight is made from metallic which 12 elements are identified to be highly hazardous and 12 are less harmful. Different research and methods have been used to estimate the obsolete mobile phones but none has developed a dynamic model and handle the discrepancy resulting from improper approach and error in the input data. The study aim was to develop a comprehensive dynamic system model for simulating the dynamism of e-waste production from mobile phone regardless the country or region and prevail over the previous errors. The logistic model method combined with STELLA program has been used to carry out this study. Then the simulation for Rwanda has been conducted and compared with others countries’ results as model testing and validation. Rwanda is about 1.5 million obsoletes mobile phone with 125 tons of waste in 2014 with e-waste production peak in 2017. It is expected to be 4.17 million obsoletes with 351.97 tons by 2020 along with environmental impact intensity of 21times to 2005. Thus, it is concluded through the model testing and validation that the present dynamic model is competent and able deal with mobile phone e-waste production the fact that it has responded to the previous studies questions from Czech Republic, Iran, and China.

Keywords: carrying capacity, dematerialization, logistic model, mobile phone, obsolescence, similarity, Stella, system dynamics

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Authors: Min Woo Park, Jin Do Chung, Kyu Yeol Kim, Byoung Uk Im, Jang Woo Kim, Hae Yeul Ryu

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Nine representative species of trees among all the street trees were selected to estimate the absorption amount of carbon dioxide emitted from street trees in Seoul calculating the biomass, amount of carbon saved, and annual absorption amount of carbon dioxide in each of the species. Planting distance of street trees in Seoul was 1,851,180 m, the number of planting lines was 1,287, the number of planted trees was 284,498 and 46 species of trees were planted as of 2013. According to the result of plugging the quantity of species of street trees in Seoul on the absorption amount of each of the species, 120,097 ton of biomass, 60,049.8 ton of amount of carbon saved, and 11,294 t CO2/year of annual absorption amount of carbon dioxide were calculated. Street ratio mentioned on the road statistics in Seoul in 2022 is 23.13%. If the street trees are assumed to be increased in the same rate, the number of street trees in Seoul was calculated to be 294,823. The planting distance was estimated to be 1,918,360 m, and the annual absorption amount of carbon dioxide was measured to be 11,704 t CO2/year. Plans for improving the annual absorption amount of carbon dioxide from street trees were established based on the expected amount of absorption. First of all, it is to improve the annual absorption amount of carbon dioxide by increasing the number of planted street trees after adjusting the planting distance of street trees. If adjusting the current planting distance to 6 m, it was turned out that 12,692.7 t CO2/year was absorbed on an annual basis. Secondly, it is to change the species of trees to tulip trees that represent high absorption rate. If increasing the proportion of tulip trees to 30% up to 2022, the annual absorption rate of carbon dioxide was calculated to be 17804.4 t CO2/year.

Keywords: absorption of carbon dioxide, source of absorbing carbon dioxide, trees in city, improving species

Procedia PDF Downloads 350

Authors: Sonu Khanal, Mandira Shrestha

Abstract:

Snow and Glaciers are the largest dependable reserved sources of water for the river system originating from the Himalayas so an accurate estimate of the volume of water contained in the snowpack and the rate of release of water from snow and glaciers are, therefore, needed for efficient management of the water resources. This research assess the fusion of energy exchanges between the snowpack, air above and soil below according to mass and energy balance which makes it apposite than the models using simple temperature index for the snow and glacier melt computation. UEBGrid a Distributed energy based model is used to calculate the melt which is then routed by Geo-SFM. The model robustness is maintained by incorporating the albedo generated from the Landsat-7 ETM images on a seasonal basis for the year 2002-2003 and substrate map derived from TM. The Substrate file includes predominantly the 4 major thematic layers viz Snow, clean ice, Glaciers and Barren land. This approach makes use of CPC RFE-2 and MERRA gridded data sets as the source of precipitation and climatic variables. The subsequent model run for the year between 2002-2008 shows a total annual melt of 17.15 meter is generate from the Marshyangdi Basin of which 71% is contributed by the glaciers , 18% by the rain and rest being from the snow melt. The albedo file is decisive in governing the melt dynamics as 30% increase in the generated surface albedo results in the 10% decrease in the simulated discharge. The melt routed with the land cover and soil variables using Geo-SFM shows Nash-Sutcliffe Efficiency of 0.60 with observed discharge for the study period.

Keywords: Glacier, Glacier melt, Snowmelt, Energy balance

Procedia PDF Downloads 445

Authors: Kwok W. Mui, Ling T. Wong, Chi T. Cheung

Abstract:

Cooling energy consumption in the residential sector, different from shopping mall, office or commercial buildings, is significantly subject to occupant decisions where in-depth investigations are found limited. It shows that energy consumptions could be associated with housing types. Surveys have been conducted in existing Hong Kong public housings to understand the housing characteristics, apartment electricity demands, occupant’s thermal expectations, and air–conditioning usage patterns for further cooling energy-saving assessments. The aim of this study is to develop a hybrid cooling energy prediction model, which integrated by EnergyPlus (EP) and artificial neural network (ANN) to estimate cooling energy consumption in public residential sector. Sensitivity tests are conducted to find out the energy impacts with changing building parameters regarding to external wall and window material selection, window size reduction, shading extension, building orientation and apartment size control respectively. Assessments are performed to investigate the relationships between cooling demands and occupant behavior on thermal environment criteria and air-conditioning operation patterns. The results are summarized into a cooling energy calculator for layman use to enhance the cooling energy saving awareness in their own living environment. The findings can be used as a directory framework for future cooling energy evaluation in residential buildings, especially focus on the occupant behavioral air–conditioning operation and criteria of energy-saving incentives.

Keywords: artificial neural network, cooling energy, occupant behavior, residential buildings, thermal environment

Procedia PDF Downloads 158

Authors: Anwar Hussain, Muhammad Iqbal

Abstract:

The changes in the prices of the agriculture commodities combined with changes in population and agriculture productivity affect farmers’ profitability and standard of living. This study intends to estimate various domestic terms of trade for agriculture sector and also to assess the volatility in the standard of living and profitability of farmers. The terms of trade has been estimated for Pakistan and its provinces using producer prices indices, consumer price indices, input prices indices and quantity indices using the data for the period 1990-91 to 2008-09. The domestic terms of trade of agriculture sector has been improved in terms of both approaches i.e. the ratio of producer prices indices to consumer prices indices and the real per capita income approach. However, the cross province estimates indicated that the terms of trade also improved for Khyber Pakhtunkhwa, Sindh and Punjab while Balochistan’s domestic terms of trade deteriorated drastically. In other words the standard of living of the farmers in Pakistan and its provinces except Balochistan improved. Using the input prices, the domestic terms of trade deteriorated for Pakistan as a whole and its provinces as well. This also explores that as a whole the profitability of the farmers reduced during the study period. The farmers pay more prices for inputs as compared to they receive for their produce. This further indicates that the poverty at the gross root level has been increased. Further, summing, the standard of living of the farmers improved but their profitability reduced, which indicates that the farmers do not completely rely on the farm income but also utilize some other sources of income for their livelihood. The study supports to give subsidies on farm inputs so as to improve the profitability of the farmers.

Keywords: agricultural terms of trade, farmers’ profitability, farmers’ standard of living, consumer and producer price indices, quantity indices

Procedia PDF Downloads 454

Authors: Hang Meng, Wen-Bin Liu, Bi Xiao, Kai-Jun Ma, Jian-Hui Xie, Geng Fei, Tian-Ye Zhang, Lu-Yi Xu, Dong-Chuan Zhang

Abstract:

The victims in water are often found in the coastal region, along river region or the region with lakes. In China, the examination for the bodies of victims in the water is conducted by forensic doctors working in the public security bureau. Because the enter water time for most of the victims are not clear, and often lack of monitor images and other information, so to find out the corpse enter water time for victims is very difficult. After the corpse of the victim enters the water, it sinks first, then corruption gas produces, which can make the density of the corpse to be less than water, and thus rise again. So the factor that determines the corpse floating time is temperature. On the basis of the temperature data obtained in Shanghai region of China (Shanghai is a north subtropical marine monsoon climate, with an average annual temperature of about 17.1℃. The hottest month is July, the average monthly temperature is 28.6℃, and the coldest month is January, the average monthly temperature is 4.8℃). This study selected about 100 cases with definite corpse enter water time and corpse floating time, analyzed the cases and obtained the empirical law of the corpse floating time. For example, in the Shanghai region, on June 15th and October 15th, the corpse floating time is about 1.5 days. In early December, the bodies who entered the water will go up around January 1st of the following year, and the bodies who enter water in late December will float in March of next year. The results of this study can be used to roughly estimate the water enter time of the victims in Shanghai. Forensic doctors around the world can also draw on the results of this study to infer the time when the corpses of the victims in the water go up.

Keywords: corpse enter water time, corpse floating time, drowning, forensic pathology, victims in the water

Procedia PDF Downloads 184

Authors: Syed Muzyan Shahzad, Liu Jianxin, Asim Shahzad, Muhammad Sharjeel Raza, Sun Ya, Fanidi Meryem

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Electrical resistivity investigation was conducted in vicinity of Tarbela Ghazi, in order to study the subsurface layer with a view of determining the depth to the aquifer and thickness of groundwater potential zones. Vertical Electrical Sounding (VES) using Schlumberger array was carried out at 16 VES stations. Well logging data at four tube wells have been used to mark the super saturated zones with great discharge rate. The present paper shows a geoelectrical identification of the lithology and an estimate of the relationship between the resistivity and Dar Zarrouk parameters (transverse unit resistance and longitudinal unit conductance). The VES results revealed both homogeneous and heterogeneous nature of the subsurface strata. Aquifer is unconfined to confine in nature, and at few locations though perched aquifer has been identified, groundwater potential zones are developed in unconsolidated deposits layers and more than seven geo-electric layers are observed at some VES locations. Saturated zones thickness ranges from 5 m to 150 m, whereas at few area aquifer is beyond 150 m thick. The average anisotropy, transvers resistance and longitudinal conductance values are 0.86 %, 35750.9821 Ω.m², 0.729 Siemens, respectively. The transverse unit resistance values fluctuate all over the aquifer system, whereas below at particular depth high values are observed, that significantly associated with the high transmissivity zones. The groundwater quality in all analyzed samples is below permissible limit according to World Health Standard (WHO).

Keywords: aquifer, Dar Zarrouk parameters, geoelectric layers, Tarbela Ghazi

Procedia PDF Downloads 184

Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

Abstract:

In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

Procedia PDF Downloads 69

Authors: Serin Darwish, Hakim Saibi, Amir Gabr

Abstract:

The United Arab Emirates (UAE) is situated within an arid zone where the climate is arid and the recharge of the groundwater is very low. Groundwater is the primary source of water in the United Arab Emirates. However, rapid expansion, population growth, agriculture, and industrial activities have negatively affected these limited water resources. The shortage of water resources has become a serious concern due to the over-pumping of groundwater to meet demand. In addition to the deficit of groundwater, the UAE has one of the highest per capita water consumption rates in the world. In this study, a combination of time-lapse measurements of microgravity and depth to groundwater level in selected wells in Al Ain city was used to estimate the variations in groundwater storage. Al-Ain is the second largest city in Abu Dhabi Emirates and the third largest city in the UAE. The groundwater in this region has been overexploited. Relative gravity measurements were acquired using the Scintrex CG-6 Autograv. This latest generation gravimeter from Scintrex Ltd provides fast, precise gravity measurements and automated corrections for temperature, tide, instrument tilt and rejection of data noise. The CG-6 gravimeter has a resolution of 0.1μGal. The purpose of this study is to measure the groundwater storage changes in the shallow aquifers based on the application of microgravity method. The gravity method is a nondestructive technique that allows collection of data at almost any location over the aquifer. Preliminary results indicate a possible relationship between microgravity and water levels, but more work needs to be done to confirm this. The results will help to develop the relationship between monthly microgravity changes with hydrological and hydrogeological changes of shallow phreatic. The study will be useful in water management considerations and additional future investigations.

Keywords: Al-Ain, arid region, groundwater, microgravity

Procedia PDF Downloads 133

Authors: Guermache Ahmed Chafik, Khelfellah Ismail, Ait-Ali Takfarines

Abstract:

The Savonius vertical axis wind turbine is characterized by sufficient starting torque at low wind speeds, simple design and does not require orientation to the wind direction; however, the developed power is lower than other types of wind turbines such as Darrieus. To increase these performances several studies and researches have been developed, such as optimizing blades shape, using passive controls and also minimizing power losses sources like the resisting torque due to friction. This work aims to estimate the performance of a Savonius wind turbine introducing a User Defined Function to the CFD model analyzing resisting torque. This User Defined Function is developed to simulate the action of the wind speed on the rotor; it receives the moment coefficient as an input to compute the rotational velocity that should be imposed on computational domain rotating regions. The rotational velocity depends on the aerodynamic moment applied on the turbine and the resisting torque, which is considered a linear function. Linking the implemented User Defined Function with the CFD solver allows simulating the real functioning of the Savonius turbine exposed to wind. It is noticed that the wind turbine takes a while to reach the stationary regime where the rotational velocity becomes invariable; at that moment, the tip speed ratio, the moment and power coefficients are computed. To validate this approach, the power coefficient versus tip speed ratio curve is compared with the experimental one. The obtained results are in agreement with the available experimental results.

Keywords: resistant torque modeling, Savonius wind turbine, user-defined function, vertical axis wind turbine performances

Procedia PDF Downloads 148