950 resultados para Initial Value Problem
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Abstract: This paper reports a lot-sizing and scheduling problem, which minimizes inventory and backlog costs on m parallel machines with sequence-dependent set-up times over t periods. Problem solutions are represented as product subsets ordered and/or unordered for each machine m at each period t. The optimal lot sizes are determined applying a linear program. A genetic algorithm searches either over ordered or over unordered subsets (which are implicitly ordered using a fast ATSP-type heuristic) to identify an overall optimal solution. Initial computational results are presented, comparing the speed and solution quality of the ordered and unordered genetic algorithm approaches.
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Abstract- A Bayesian optimization algorithm for the nurse scheduling problem is presented, which involves choosing a suitable scheduling rule from a set for each nurse's assignment. Unlike our previous work that used GAs to implement implicit learning, the learning in the proposed algorithm is explicit, i.e. eventually, we will be able to identify and mix building blocks directly. The Bayesian optimization algorithm is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. The conditional probability of each variable in the network is computed according to an initial set of promising solutions. Subsequently, each new instance for each variable is generated by using the corresponding conditional probabilities, until all variables have been generated, i.e. in our case, a new rule string has been obtained. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the conditional probabilities for all nodes in the Bayesian network are updated again using the current set of promising rule strings. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed approach might be suitable for other scheduling problems.
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Synthetic cannabinoid receptor agonists or more commonly known as synthetic cannabinoids (SCs) were originally created to obtain the medicinal value of THC but they are an emerging social problem. SCs are mostly produced coated on herbal materials or in powder form and marketed under a variety of brand names, e.g. “Spice”, “K2”. Despite many SCs becoming controlled under drug legislation, many of them remain legal in some countries around the world. In Scotland, SCs are controlled under the Misuse of Drugs Act 1971 and Psychoactive Substances Act 2016 that only cover a few early SCs. In Saudi Arabia, even fewer are controlled. The picture of the SCs-problem in Scotland is vague due to insufficient prevalence data, particularly that using biological samples. Whilst there is evidence of increasing use of SCs throughout the world, in Saudi Arabia, there is currently no data regarding the use of products containing SCs among Saudi people. Several studies indicate that SCs may cause serious toxicity and impairment to health therefore it is important to understand the scale of use within society. A simple and sensitive method was developed for the simultaneous analysis of 10 parent SCs (JWH-018, JWH-073, JWH-250, JWH-200, AM-1248, UR-144, A-796260, AB-FUBINACA, 5F-AKB-48 and 5F-PB-22) in whole blood and 8 corresponding metabolites (JWH-018 4-OH pentyl, JWH-073 3-OH butyl, JWH-250 4-OH pentyl, AM-2201 4-OH pentyl, JWH-122 5-OH pentyl, JWH-210 5-OH pentyl, 5F-AKB-48 (N-4 OH pentyl), 5F-PB-22 3-carboxyindole)in urine using LLE and LC-MS/MS. The method was validated according to the standard practices for method validation in forensic toxicology (SWGTOX, May 2013). All analytes gave acceptable precision, linearity and recovery for analysing blood and urine samples. The method was applied to 1,496 biological samples, a mixture of whole blood and urine. Blood and/or urine samples were analysed from 114 patients presenting at Accident and Emergency in Glasgow Royal Infirmary, in spring 2014 and JuneDecember 2015. 5F-AKB-48, 5F-PB-22 and MDMB-CHMICA were detected in 9, 7 and 9 cases respectively. 904 urine samples from individuals admitted to/liberated from Scottish prisons over November 2013 were tested for the presence of SCs. 5F-AKB-48 (N-4 OH pentyl) was detected in 10 cases and 5F-PB-22 3-carboxyindole in 3 cases. Blood and urine samples from two post-mortem cases in Scotland with suspected ingestion of SCs were analysed. Both cases were confirmed positive for 5F-AKB-48. A total of 463 urine samples were collected from personnel who presented to the Security Forces Hospital in Ryiadh for workplace drug testing as a requirement for their job during July 2014. The results of the analysis found 2 samples to be positive for 5F-PB-22 3carboxyindole. A further study in Saudi Arabia using a questionnaire was carried out among 3 subpopulations: medical professionals, members of the public in and around smoking cafes and known drug users. With regards to general awareness of Spice products, 16%, 11% and 22% of those participants of medical professionals, members of the public in and around smoking cafes and known drug users, respectively, were aware of the existence of SCs or Spice products. The respondents had an overall average of 4.5% who had a friend who used these Spice products. It is clear from the results obtained in both blood and urine testing and surveys that SCs are being used in both Scotland and Saudi Arabia. The extent of their use is not clear and the data presented here is an initial look into their prevalence. Blood and urine findings suggest changing trends in SC use, moving away from JWH and AM SCs to the newer 5F-AKB-48, 5-F-PB-22 and MDMBCHMICA compounds worldwide. In both countries 5F-PB-22 was detected. These findings clarify how the SCs phenomenon is a worldwide problem and how the information of every country regarding what SCs are seized can help and is not specific for that country. The analytes included in the method were selected due to their apparent availability in both countries, however it is possible that some newer analytes have been used and these would not have been detected. For this reason it is important that methods for testing SCs are updated regularly and evolve with the ever-changing availability of these drugs worldwide. In addition, there is little published literature regarding the concentrations of these drugs found in blood and urine samples and this work goes some way towards understanding these.
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This work is concerned with the design and analysis of hp-version discontinuous Galerkin (DG) finite element methods for boundary-value problems involving the biharmonic operator. The first part extends the unified approach of Arnold, Brezzi, Cockburn & Marini (SIAM J. Numer. Anal. 39, 5 (2001/02), 1749-1779) developed for the Poisson problem, to the design of DG methods via an appropriate choice of numerical flux functions for fourth order problems; as an example we retrieve the interior penalty DG method developed by Suli & Mozolevski (Comput. Methods Appl. Mech. Engrg. 196, 13-16 (2007), 1851-1863). The second part of this work is concerned with a new a-priori error analysis of the hp-version interior penalty DG method, when the error is measured in terms of both the energy-norm and L2-norm, as well certain linear functionals of the solution, for elemental polynomial degrees $p\ge 2$. Also, provided that the solution is piecewise analytic in an open neighbourhood of each element, exponential convergence is also proven for the p-version of the DG method. The sharpness of the theoretical developments is illustrated by numerical experiments.
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The present study examined the correlations between motivational orientation and students’ academic performance in mathematical problem solving and reading comprehension. The main purpose is to see if students’ intrinsic motivation is related to their actual performance in different subject areas, math and reading. In addition, two different informants, students and teachers, were adopted to check whether the correlation is different by different informants. Pearson’s correlational analysis was a major method, coupled with regression analysis. The result confirmed the significant positive correlation between students’ academic performance and students’ self-report and teacher evaluation on their motivational orientation respectively. Teacher evaluation turned out with more predictive value for the academic achievement in math and reading. Between the subjects, mathematical problem solving showed higher correlation with most of the motivational subscales than reading comprehension did. The highest correlation was found between teacher evaluation on task orientation and students’ mathematical problem solving. The positive relationship between intrinsic motivation and academic achievement was proved. The disparity between students ’ self-report and teacher evaluation on motivational orientation was also addressed with the need of further examination.
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Cassini states correspond to the equilibria of the spin axis of a body when its orbit is perturbed. They were initially described for planetary satellites, but the spin axes of black hole binaries also present this kind of equilibria. In previous works, Cassini states were reported as spin-orbit resonances, but actually the spin of black hole binaries is in circulation and there is no resonant motion. Here we provide a general description of the spin dynamics of black hole binary systems based on a Hamiltonian formalism. In absence of dissipation, the problem is integrable and it is easy to identify all possible trajectories for the spin for a given value of the total angular momentum. As the system collapses due to radiation reaction, the Cassini states are shifted to different positions, which modifies the dynamics around them. This is why the final spin distribution may differ from the initial one. Our method provides a simple way of predicting the distribution of the spin of black hole binaries at the end of the inspiral phase.
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Increasing the amount of detergent industries in world in spite of having abundant benefits; entering a new kind of contamination into environment and attract the attention of environment liable of different countries to itself. Entering detergents into an aqueous solution cause pollution of water sources and environment in respect of appearing e problem and charges like: nutritive phenomenon, decomposition of hard group of detergent and producing foam. After using Detergents, they were poured into rivers, seas and lakes and have destructive effect on environment. A lot of hygiene problems were attributed to the water having detergents more than allowed value. So, it is specified the importance of eliminating detergents from contaminated water and it is application for secondary use. In order to attain to this aim, we can use inorganic nano and micro-caolin. In this study the adsorptive properties of detergent on the micro and nano caolin adsorbents were studied and the effect of various parameters like the amount of adsorptive materials, initial concentration of detergent, speed of stirring, electrolyte, temperature, time and pH were determined. The surface area of micro- and nano-caoline was reported 11.867 and 49.1438 m2 g-1, respectively. That increasing in nano-caoline surface area confirms increasing in capacity and more rate of adsorption. The results gained by this research recommend using micro- and nano-caolin as a plentiful, available and effective adsorbents. Also in comparison, using nano-caoline was recommended in order to have more effectiveness.
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The aim of this study is to investigate the effectiveness of problem-based learning (PBL) on students’ mathematical performance. This includes mathematics achievement and students’ attitudes towards mathematics for third and eighth grade students in Saudi Arabia. Mathematics achievement includes, knowing, applying, and reasoning domains, while students’ attitudes towards mathematics covers, ‘Like learning mathematics’, ‘value mathematics’, and ‘a confidence to learn mathematics’. This study goes deeper to examine the interaction of a PBL teaching strategy, with trained face-to-face and self-directed learning teachers, on students’ performance (mathematics achievement and attitudes towards mathematics). It also examines the interaction between different ability levels of students (high and low levels) with a PBL teaching strategy (with trained face-to-face or self-directed learning teachers) on students’ performance. It draws upon findings and techniques of the TIMSS international benchmarking studies. Mixed methods are used to analyse the quasi-experimental study data. One -way ANOVA, Mixed ANOVA, and paired t-tests models are used to analyse quantitative data, while a semi-structured interview with teachers, and author’s observations are used to enrich understanding of PBL and mathematical performance. The findings show that the PBL teaching strategy significantly improves students’ knowledge application, and is better than the traditional teaching methods among third grade students. This improvement, however, occurred only with the trained face-to-face teacher’s group. Furthermore, there is robust evidence that using a PBL teaching strategy could raise significantly students’ liking of learning mathematics, and confidence to learn mathematics, more than traditional teaching methods among third grade students. Howe ver, there was no evidence that PBL could improve students’ performance (mathematics achievement and attitudes towards mathematics), more than traditional teaching methods, among eighth grade students. In 8th grade, the findings for low achieving students show significant improvement compared to high achieving students, whether PBL is applied or not. However, for 3th grade students, no significant difference in mathematical achievement between high and low achieving students was found. The results were not expected for high achieving students and this is also discussed. The implications of these findings for mathematics education in Saudi Arabia are considered.
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PURPOSE We aimed to evaluate the added value of diffusion-weighted imaging (DWI) to standard magnetic resonance imaging (MRI) for detecting post-treatment cervical cancer recurrence. The detection accuracy of T2-weighted (T2W) images was compared with that of T2W MRI combined with either dynamic contrast-enhanced (DCE) MRI or DWI. METHODS Thirty-eight women with clinically suspected uterine cervical cancer recurrence more than six months after treatment completion were examined with 1.5 Tesla MRI including T2W, DCE, and DWI sequences. Disease was confirmed histologically and correlated with MRI findings. The diagnostic performance of T2W imaging and its combination with either DCE or DWI were analyzed. Sensitivity, positive predictive value, and accuracy were calculated. RESULTS Thirty-six women had histologically proven recurrence. The accuracy for recurrence detection was 80% with T2W/DCE MRI and 92.1% with T2W/DWI. The addition of DCE sequences did not significantly improve the diagnostic ability of T2W imaging, and this sequence combination misclassified two patients as falsely positive and seven as falsely negative. The T2W/DWI combination revealed a positive predictive value of 100% and only three false negatives. CONCLUSION The addition of DWI to T2W sequences considerably improved the diagnostic ability of MRI. Our results support the inclusion of DWI in the initial MRI protocol for the detection of cervical cancer recurrence, leaving DCE sequences as an option for uncertain cases.
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This article is concerned with the numerical detection of bifurcation points of nonlinear partial differential equations as some parameter of interest is varied. In particular, we study in detail the numerical approximation of the Bratu problem, based on exploiting the symmetric version of the interior penalty discontinuous Galerkin finite element method. A framework for a posteriori control of the discretization error in the computed critical parameter value is developed based upon the application of the dual weighted residual (DWR) approach. Numerical experiments are presented to highlight the practical performance of the proposed a posteriori error estimator.
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Repercussions of innovation adoption and diffusion studies have long been imperative to the success of novel introductions. However, perceptions and deductions of current innovation understandings have been changing over time. The paradigm shift from the goods-dominant (G-D) logic to the service-dominant (S-D) logic potentially makes the distinction between product (goods) innovation and service innovation redundant as the S-D logic lens views all innovations as service innovations (Vargo and Lusch, 2004; 2008; Lusch and Nambisan, 2015). From this perspective, product innovations are in essence service innovations, as goods serve as mere distribution mechanisms to deliver service. Nonetheless, the transition to such a broadened and transcending view of service innovation necessitates concurrently a change in the underlying models used to investigate innovation and its subsequent adoption. The present research addresses this gap by engendering a novel model for the most crucial period of service diffusion within the S-D logic context – the post-initial adoption phase, which demarcates an individual’s behavior after the initial adoption decision of a service. As a wellfounded understanding of service diffusion and the complementary innovation adoption still lingers in its infancy, the current study develops a model based on interdisciplinary domains mapping. Here fore, knowledge of the relatively established viral source domain is mapped to the comparatively undetermined target domain of service innovation adoption. To assess the model and test the importance of the explanatory variables, survey data from 750 respondents of a bank in Northern Germany is scrutinized by means of Structural Equation Modeling (SEM). The findings reveal that the continuance intention of a customer, actual usage of the service and the customer influencer value all constitute important postinitial adoption behavior that have meaningful implications for a successful service adoption. Second, the four constructs customer influencer value, organizational commitment, perceived usefulness and service customization are evidenced to have a differential impact on a iv customer’s post-initial adoption behavior. Third, this study indicates that post-initial adoption behavior further underlies the influence of a user’s age and besides that is also provoked by the internal and external environments of service adoption. Finally, this research amalgamates the broad view of service innovation by Nambisan and Lusch (2015) with the findings ensuing this enquiry’s model to arrive at a framework that it both, generalizable and practically applicable. Implications for academia and practitioners are captured along with avenues for future research.
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A Bayesian optimization algorithm for the nurse scheduling problem is presented, which involves choosing a suitable scheduling rule from a set for each nurse’s assignment. Unlike our previous work that used GAs to implement implicit learning, the learning in the proposed algorithm is explicit, i.e. eventually, we will be able to identify and mix building blocks directly. The Bayesian optimization algorithm is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. The conditional probability of each variable in the network is computed according to an initial set of promising solutions. Subsequently, each new instance for each variable is generated by using the corresponding conditional probabilities, until all variables have been generated, i.e. in our case, a new rule string has been obtained. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the conditional probabilities for all nodes in the Bayesian network are updated again using the current set of promising rule strings. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed approach might be suitable for other scheduling problems.
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International audience
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In this study, we examine the relationship between good corporate governance practices and the creation of value/performance of credit unions from 2010 to 2012. The objective was to create and validate a corporate governance index for credit unions, and to then analyse the relationship between good governance practices and the creation of value/performance. The problem question is: do good corporate governance practices provide value creation for credit unions? The research started by creating indices from factor analysis to identify latent dependent variables related to value creation and performance; next indices were created from the principal component analysis for the creation of independent latent variables related to corporate governance. Finally, based on panel data from regression models, the influence of the variables and indices related to corporate governance on the indices of value creation and performance was verified. Based on the research, it became evident that the Corporate Governance Index (IGC) is mainly impacted by Executive Management, with 40.31% of the IGC value, followed by the Representation and Participation dimension, with 34.07% of the IGC value. The contribution for academics was the creation of the Corporate Governance Index (IGC) applied for credit unions. As for the contribution to the system of credit unions, the highlight was the effectiveness of the mechanisms for economic-financial and asset management adopted by BACEN, credit unions and OCEMG.
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The gas migration during the cementing of wells is one of the main problems of oil wells engineering. Its occurrence can cause severe problems since shortly to loss of control of the well after cementation. Recently, 20/04/2010 In an accident of major proportions in the Gulf of Mexico, among other factors, faulty cementing operation provided the gas migration, causing the accident, in which 11 people died and 17 were injured occurred. Besides the serious consequences that can be caused by gas migration, remediation of the problem, which is made by injecting cement in damaged areas, usually involves additional costs and is not always effective. Therefore, preventing gas migration to be preferred. Some methods are used to prevent the migration of the pressurized gas as the annular space, application of pressure pulses, reducing the height of the cement column compressible cement pastes of low permeability, pastes and to control free filtered water, and binders of thixotropic cement expandable and flexible. Thus, the cement pastes used to prevent gas migration must meet the maximum these methods. Thus, this study aimed to formulate a cement paste to prevent gas migration, using the expanded vermiculite, and evaluate the behavior of the folder trials necessary for use in oil wells. Free water content, rheological properties, compressive strength, loss of liquid phase sedimentation of solids, specific weight, thickening time and gas migration: The following tests were performed. The results show that meets the specifications paste formulated for use in oil wells and the use of expanded vermiculite contribute to the absorption of free water, thixotropy and low density. The absorption of free water is proven to result in zero percentage test free water content, thixotropy is observed with the high value of the initial gel strength (Gi) in testing rheological properties and low density is proven in test weight specific