38 resultados para Markov chains. Convergence. Evolutionary Strategy. Large Deviations
Resumo:
The design optimization of a cold-formed steel portal frame building is considered in this paper. The proposed genetic algorithm (GA) optimizer considers both topology (i.e., frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables. Previous GAs in the literature were characterized by poor convergence, including slow progress, that usually results in excessive computation times and/or frequent failure to achieve an optimal or near-optimal solution. This is the main issue addressed in this paper. In an effort to improve the performance of the conventional GA, a niching strategy is presented that is shown to be an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Thus, population diversity is maintained and premature convergence is reduced significantly. Through benchmark examples, it is shown that the efficient GA proposed generates optimal solutions more consistently. A parametric study was carried out, and the results included. They show significant variation in the optimal topology in terms of pitch and frame spacing for a range of typical column heights. They also show that the optimized design achieved large savings based on the cost of the main structural elements; the inclusion of knee braces at the eaves yield further savings in cost, that are significant.
Resumo:
A simple yet efficient harmony search (HS) method with a new pitch adjustment rule (NPAHS) is proposed for dynamic economic dispatch (DED) of electrical power systems, a large-scale non-linear real time optimization problem imposed by a number of complex constraints. The new pitch adjustment rule is based on the perturbation information and the mean value of the harmony memory, which is simple to implement and helps to enhance solution quality and convergence speed. A new constraint handling technique is also developed to effectively handle various constraints in the DED problem, and the violation of ramp rate limits between the first and last scheduling intervals that is often ignored by existing approaches for DED problems is effectively eliminated. To validate the effectiveness, the NPAHS is first tested on 10 popular benchmark functions with 100 dimensions, in comparison with four HS variants and five state-of-the-art evolutionary algorithms. Then, NPAHS is used to solve three 24-h DED systems with 5, 15 and 54 units, which consider the valve point effects, transmission loss, emission and prohibited operating zones. Simulation results on all these systems show the scalability and superiority of the proposed NPAHS on various large scale problems.
Resumo:
Clean and renewable energy generation and supply has drawn much attention worldwide in recent years, the proton exchange membrane (PEM) fuel cells and solar cells are among the most popular technologies. Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters. This is however challenging due to the highly nonlinear and complex nature of the models. In particular for PEM fuel cells, the model has to be optimized under different operation conditions, thus making the solution space extremely complex. In this paper, an improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for these two types of cell models. This is achieved by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution. To improve the diversity of the local search a chaotic map is also introduced. Compared with the basic TLBO, the structure of the proposed algorithm is much simplified and the searching ability is significantly enhanced. The performance of the proposed STLBO is firstly tested and verified on two low dimension decomposable problems and twelve large scale benchmark functions, then on the parameter identification of PEM fuel cell as well as solar cell models. Intensive experimental simulations show that the proposed STLBO exhibits excellent performance in terms of the accuracy and speed, in comparison with those reported in the literature.
Resumo:
This paper describes how urban agriculture differs from conventional agriculture not only in the way it engages with the technologies of growing, but also in the choice of crop and the way these are brought to market. The authors propose a new model for understanding these new relationships, which is analogous to a systems view of information technology, namely Hardware-Software- Interface.
The first component of the system is hardware. This is the technological component of the agricultural system. Technology is often thought of as equipment, but its linguistic roots are in ‘technis’ which means ‘know how’. Urban agriculture has to engage new technologies, ones that deal with the scale of operation and its context which is different than rural agriculture. Often the scale is very small, and soils are polluted. There this technology in agriculture could be technical such as aquaponic systems, or could be soil-based agriculture such as allotments, window-boxes, or permaculture. The choice of method does not necessarily determine the crop produced or its efficiency. This is linked to the biotic that is added to the hardware, which is seen as the ‘software’.
The software of the system are the ecological parts of the system. These produce the crop which may or may not be determined by the technology used. For example, a hydroponic system could produce a range of crops, or even fish or edible flowers. Software choice can be driven by ideological preferences such as permaculture, where companion planting is used to reduce disease and pests, or by economic factors such as the local market at a particular time of the year. The monetary value of the ‘software’ is determined by the market. Obviously small, locally produced crops are unlikely to compete against intensive products produced globally, however the value locally might be measured in different ways, and might be sold on a different market. This leads to the final part of the analogy - interface.
The interface is the link between the system and the consumer. In traditional agriculture, there is a tenuous link between the producer of asparagus in Peru and the consumer in Europe. In fact very little of the money spent by the consumer ever reaches the grower. Most of the money is spent on refrigeration, transport and profit for agents and supermarket chains. Local or hyper-local agriculture needs to bypass or circumvent these systems, and be connected more directly to the consumer. This is the interface. In hyper-localised systems effectiveness is often more important than efficiency, and direct links between producer and consumer create new economies.
Resumo:
Promoter hypermethylation is recognized as a hallmark of human cancer, in addition to conventional mechanisms of gene inactivation. As such, many new technologies have been developed over the past two decades to uncover novel targets of methylation and decipher complex epigenetic patterns. However, many of these are either labor intensive or provide limited data, confined to oligonucleotide hybridization sequences or enzyme cleavage sites and cannot be easily applied to screening large sets of sequences or samples. We present an application of denaturing high performance liquid chromatography (DHPLC), which relies on bisulfite modification of genomic DNA, for methylation screening. We validated DHPLC as a methylation screening tool using GSTP1, a well known target of methylation in prostate cancer. We developed an in silico approach to identify potential targets of promoter hypermethylation in prostate cancer. Using DHPLC, we screened two of these targets LGALS3 and SMAD4 for methylation. We show that DHPLC has an application as a fast, sensitive, quantitative and cost effective method for screening novel targets or DNA samples for DNA methylation.
Resumo:
Background The use of technology in healthcare settings is on the increase and may represent a cost-effective means of delivering rehabilitation. Reductions in treatment time, and delivery in the home, are also thought to be benefits of this approach. Children and adolescents with brain injury often experience deficits in memory and executive functioning that can negatively affect their school work, social lives, and future occupations. Effective interventions that can be delivered at home, without the need for high-cost clinical involvement, could provide a means to address a current lack of provision. We have systematically reviewed studies examining the effects of technology-based interventions for the rehabilitation of deficits in memory and executive functioning in children and adolescents with acquired brain injury. Objectives To assess the effects of technology-based interventions compared to placebo intervention, no treatment, or other types of intervention, on the executive functioning and memory of children and adolescents with acquired brain injury. Search methods We ran the search on the 30 September 2015. We searched the Cochrane Injuries Group Specialised Register, the Cochrane Central Register of Controlled Trials (CENTRAL), Ovid MEDLINE(R), Ovid MEDLINE(R) In-Process & Other Non-Indexed Citations, Ovid MEDLINE(R) Daily and Ovid OLDMEDLINE(R), EMBASE Classic + EMBASE (OvidSP), ISI Web of Science (SCI-EXPANDED, SSCI, CPCI-S, and CPSI-SSH), CINAHL Plus (EBSCO), two other databases, and clinical trials registers. We also searched the internet, screened reference lists, and contacted authors of included studies. Selection criteria Randomised controlled trials comparing the use of a technological aid for the rehabilitation of children and adolescents with memory or executive-functioning deficits with placebo, no treatment, or another intervention. Data collection and analysis Two review authors independently reviewed titles and abstracts identified by the search strategy. Following retrieval of full-text manuscripts, two review authors independently performed data extraction and assessed the risk of bias. Main results Four studies (involving 206 participants) met the inclusion criteria for this review. Three studies, involving 194 participants, assessed the effects of online interventions to target executive functioning (that is monitoring and changing behaviour, problem solving, planning, etc.). These studies, which were all conducted by the same research team, compared online interventions against a 'placebo' (participants were given internet resources on brain injury). The interventions were delivered in the family home with additional support or training, or both, from a psychologist or doctoral student. The fourth study investigated the use of a computer program to target memory in addition to components of executive functioning (that is attention, organisation, and problem solving). No information on the study setting was provided, however a speech-language pathologist, teacher, or occupational therapist accompanied participants. Two studies assessed adolescents and young adults with mild to severe traumatic brain injury (TBI), while the remaining two studies assessed children and adolescents with moderate to severe TBI. Risk of bias We assessed the risk of selection bias as low for three studies and unclear for one study. Allocation bias was high in two studies, unclear in one study, and low in one study. Only one study (n = 120) was able to conceal allocation from participants, therefore overall selection bias was assessed as high. One study took steps to conceal assessors from allocation (low risk of detection bias), while the other three did not do so (high risk of detection bias). Primary outcome 1: Executive functioning: Technology-based intervention versus placebo Results from meta-analysis of three studies (n = 194) comparing online interventions with a placebo for children and adolescents with TBI, favoured the intervention immediately post-treatment (standardised mean difference (SMD) -0.37, 95% confidence interval (CI) -0.66 to -0.09; P = 0.62; I2 = 0%). (As there is no 'gold standard' measure in the field, we have not translated the SMD back to any particular scale.) This result is thought to represent only a small to medium effect size (using Cohen’s rule of thumb, where 0.2 is a small effect, 0.5 a medium one, and 0.8 or above is a large effect); this is unlikely to have a clinically important effect on the participant. The fourth study (n = 12) reported differences between the intervention and control groups on problem solving (an important component of executive functioning). No means or standard deviations were presented for this outcome, therefore an effect size could not be calculated. The quality of evidence for this outcome according to GRADE was very low. This means future research is highly likely to change the estimate of effect. Primary outcome 2: Memory One small study (n = 12) reported a statistically significant difference in improvement in sentence recall between the intervention and control group following an eight-week remediation programme. No means or standard deviations were presented for this outcome, therefore an effect size could not be calculated. Secondary outcomes Two studies (n = 158) reported on anxiety/depression as measured by the Child Behavior Checklist (CBCL) and were included in a meta-analysis. We found no evidence of an effect with the intervention (mean difference -5.59, 95% CI -11.46 to 0.28; I2 = 53%). The GRADE quality of evidence for this outcome was very low, meaning future research is likely to change the estimate of effect. A single study sought to record adverse events and reported none. Two studies reported on use of the intervention (range 0 to 13 and 1 to 24 sessions). One study reported on social functioning/social competence and found no effect. The included studies reported no data for other secondary outcomes (that is quality of life and academic achievement). Authors' conclusions This review provides low-quality evidence for the use of technology-based interventions in the rehabilitation of executive functions and memory for children and adolescents with TBI. As all of the included studies contained relatively small numbers of participants (12 to 120), our findings should be interpreted with caution. The involvement of a clinician or therapist, rather than use of the technology, may have led to the success of these interventions. Future research should seek to replicate these findings with larger samples, in other regions, using ecologically valid outcome measures, and reduced clinician involvement.
Resumo:
Increasing litter size has long been a goal of pig breeders and producers, and may have implications for pig (Sus scrofa domesticus) welfare. This paper reviews the scientific evidence on biological factors affecting sow and piglet welfare in relation to large litter size. It is concluded that, in a number of ways, large litter size is a risk factor for decreased animal welfare in pig production. Increased litter size is associated with increased piglet mortality, which is likely to be associated with significant negative animal welfare impacts. In surviving piglets, many of the causes of mortality can also occur in non-lethal forms that cause suffering. Intense teat competition may increase the likelihood that some piglets do not gain adequate access to milk, causing starvation in the short term and possibly long-term detriments to health. Also, increased litter size leads to more piglets with low birth weight which is associated with a variety of negative long-term effects. Finally, increased production pressure placed on sows bearing large litters may produce health and welfare concerns for the sow. However, possible biological approaches to mitigating health and welfare issues associated with large litters are being implemented. An important mitigation strategy is genetic selection encompassing traits that promote piglet survival, vitality and growth. Sow nutrition and the minimisation of stress during gestation could also contribute to improving outcomes in terms of piglet welfare. Awareness of the possible negative welfare consequences of large litter size in pigs should lead to further active measures being taken to mitigate the mentioned effects. © 2013 Universities Federation for Animal Welfare.
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Fraud in the global food supply chain is becoming increasingly common due to the huge profits associated with this type of criminal activity. Food commodities and ingredients that are expensive and are part of complex supply chains are particularly vulnerable. Both herbs and spices fit these criteria perfectly and yet strategies to detect fraudulent adulteration are still far from robust. An FT-IR screening method coupled to data analysis using chemometrics and a second method using LC-HRMS were developed, with the latter detecting commonly used adulterants by biomarker identification. The two tier testing strategy was applied to 78 samples obtained from a variety of retail and on-line sources. There was 100% agreement between the two tests that over 24% of all samples tested had some form of adulterants present. The innovative strategy devised could potentially be used for testing the global supply chains for fraud in many different forms of herbs.