Survival signature-based sensitivity analysis of systems with epistemic uncertainties

The survival signature provides a basis for efficient reliability assessment of systems with more than one component type. Often a perfect probabilistic modelling of the system is not possible due to limited information, vagueness and imprecision. Hence generalized probabilistic methods need to be used. These methods allow to explicitly model the uncertainties without the need of unjustified hypotheses and approximation. In this paper, a novel and efficient sensitivity approach is presented. The proposed approach is based on survival signature, allowing to identify and rank components in a system. A numerical example is used to illustrate the above methods

Elucidating the Role of Electrophoretic Mobility for Increasing Yield in the Electrophoretic Deposition of Nanomaterials

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Friksi Antara Permukaan Beton Spun Pile Bagian Dalam Dengan Beton Pengisi

Spun pile adalah tiang pancang berbentuk bulat dan berongga pada bagian tengah. Metode pembuatan spun pile adalah memanfaatkan gaya sentrifugal untuk proses pemadatan beton, yaitu dengan cara diputar (spinning), sehingga ada kemungkinan akan menimbulkan kuat tekan yang tidak merata pada ketebalan dinding tiang. Selain itu, pada permukaan bagian dalam lubang spun pile,biasanya terdapat lapisan yang relatif lunak (slurry). Terdapatnya lapisan slurry tersebut kemungkinan akan mempengaruhi friksi dengan beton pengisi. Penelitian ini bertujuan untuk mempelajari friksi antara beton bagian dalam spun pile dengan beton baru sebagai pengisi. Hasil penelitian pada permukaan beton spun pile bagian dalam dengan beton pengisi dengan lapisan slurry yang tipis menunjukkan bahwa semakin tinggi kandungan semen beton pengisi, friksi antara spun pile dan beton pengisi akan meningkat. Namun, pengaruh kandungan semen tersebut relatif tidak signifikan pada spun pile yang memiliki lapisan slurry yang tebal. Friksi terendah rata-rata antara beton spun pile bagian dalam dengan beton pengisi yang memiliki lapisan slurry dengan ketebalan sekitar 3 mm adalah 11,87 kg/cm2

Transformation of measurement uncertainties into low-dimensional feature vector space

Advances in technology allow the acquisition of data with high spatial and temporal resolution. These datasets are usually accompanied by estimates of the measurement uncertainty, which may be spatially or temporally varying and should be taken into consideration when making decisions based on the data. At the same time, various transformations are commonly implemented to reduce the dimensionality of the datasets for postprocessing or to extract significant features. However, the corresponding uncertainty is not usually represented in the low-dimensional or feature vector space. A method is proposed that maps the measurement uncertainty into the equivalent low-dimensional space with the aid of approximate Bayesian computation, resulting in a distribution that can be used to make statistical inferences. The method involves no assumptions about the probability distribution of the measurement error and is independent of the feature extraction process as demonstrated in three examples. In the first two examples, Chebyshev polynomials were used to analyse structural displacements and soil moisture measurements; while in the third, principal component analysis was used to decompose the global ocean temperature data. The uses of the method range from supporting decision-making in model validation or confirmation, model updating or calibration and tracking changes in condition, such as the characterization of the El Niño Southern Oscillation

What is the evidence for giving chemoprophylaxis to children or students attending the same preschool, school or college as a case of meningococcal disease?

We performed a systematic literature review to assess the effectiveness of chemoprophylaxis for contacts of sporadic cases of invasive meningococcal disease (IMD) in educational settings. No studies directly compared IMD risk in contacts with/without chemoprophylaxis. However, compared to the background incidence, an elevated IMD risk was identified in settings without a general recommendation for chemoprophylaxis in pre-schools [pooled risk difference (RD) 58·2/10⁵, 95% confidence interval (CI) 27·3-89·0] and primary schools (pooled RD 4·9/10⁵, 95% CI 2·9-6·9) in the ~30 days after contact with a sporadic IMD case, but not in other educational settings. Thus, limited but consistent evidence suggests the risk of IMD in pre-school contacts of sporadic IMD cases is significantly increased above the background risk, but lower than in household contacts (pooled RD for household contacts with no chemoprophylaxis vs. background incidence: 480·1/10⁵, 95% CI 321·5-639·9). We recommend chemoprophylaxis for pre-school contacts depending on an assessment of duration and closeness of contact

A collaborative decision support system framework for vertical farming business developments

The emerging industry of vertical farming (VF) faces three key challenges: standardisation, environmental sustainability, and profitability. High failure rates are costly and can stem from premature business decisions about location choice, pricing strategy, system design, and other critical issues. Improving knowledge transfer and developing adaptable economic analysis for VF is necessary for profitable business models to satisfy investors and policy makers. A review of current horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. Data from the literature alongside lessons learned from industry practitioners are centralised in the proposed DSS, using imprecise data techniques to accommodate for partial information. The DSS evaluates business sustainability using financial risk assessment. This is necessary for complex/new sectors such as VF with scarce data