Noise modelling, vibro-acoustic analysis, artificial neural networks on offshore platform

PhD ThesisDue to the limitations of the present noise prediction methods used in the offshore industry, this research is aimed to develop an efficient noise prediction technique that can analyze and predict the noise level for the offshore platform environment during the design stage as practically as possible to meet the criteria for crews’ comfort against high noise level. Several studies have been carried out to improve the understanding of acoustic environment onboard offshore platform, as well as the present prediction techniques. The noise prediction methods for the offshore platform were proposed from three aspects: by empirical acoustic modeling, analytical computation or neural network method. First, through evaluating the five-selected empirical acoustic models originated from other applications and statistical energy analaysis with direct field (SEA-DF), Heerema and Hodgson model was selected for calculating the sound level in the machinery room on the offshore platform. Second, the analytical model modeled three-dimensional fully coupled structural and acoustic systems by considering of the structural coupling force and the moment at edges, and structural-acoustic interaction on the interface. Artificial spring technique was implemented to illustrate the general coupling and boundary conditions. The use of Chebyshev expansions solutions ensured the accuracy and rapid convergence of the three-dimensional problem of single room and conjugate rooms. The proposed model was validated by checking natural frequencies and responses of against the results obtained from finite element software. Third, a modified multiple generalised regression neural network (GRNN) was first proposed to predict the noise level of various compartments onboard of the offshore platform with limited samples available. By preprocessing the samples with fuzzy c-means (FCM) and principal component analysis (PCA), dominant input features can be identified before commencing the GRNN’s training process. With optimal spread variables, the newly developed tool showed comparable performance to the SEA-DF and empirical formula that requires less time and resources to solve during the early stage of the offshore platform design.Singapore Economic Development Board (EDB) for providing the funding for the research under EDB-Industrial Postgraduate Programme (IPP) with SembCorp Marine in Singapore

Order continuous extensions of positive compact operators on Banach lattices

Let $E$ and $F$ be Banach lattices. Let $G$ be a vector sublattice of $E$ and $T: G\rightarrow F$ be an order continuous positive compact (resp. weakly compact) operators. We show that if $G$ is an ideal or an order dense sublattice of $E$, then $T$ has a norm preserving compact (resp. weakly compact) positive extension to $E$ which is likewise order continuous on $E$. In particular, we prove that every compact positive orthomorphism on an order dense sublattice of $E$ extends uniquely to a compact positive orthomorphism on $E$.Comment: 7 page

Association of interleukin 10 rs1800896 polymorphism with susceptibility to breast cancer: a meta-analysis.

Objective: To evaluate the correlation between interleukin 10 (IL-10) -1082A/G polymorphism (rs1800896) and breast cancers by performing a meta-analysis. Methods: The Embase and Medline databases were searched through 1 September 2018 to identify qualified articles. Odds ratios (OR) and corresponding 95% confidence intervals (CIs) were applied to evaluate associations. Results: In total, 14 case-control studies, including 5320 cases and 5727 controls, were analyzed. We detected significant associations between the IL10 -1082 G/G genotype and risk of breast cancer (AA + AG vs. GG: OR = 0.88, 95% CI = 0.80-0.97). Subgroup analyses confirmed a significant association in Caucasian populations (OR = 0.89, 95% CI = 0.80-0.99), in population-based case-control studies (OR = 0.87, 95% CI = 0.78-0.96), and in studies with ≥500 subjects (OR = 0.88, 95% CI = 0.79-0.99) under the recessive model (AA + AG vs. GG). No associations were found in Asian populations. Conclusions: The IL10 -1082A/G polymorphism is associated with an increased risk of breast cancer. The association between IL10 -1082 G/G genotype and increased risk of breast cancer is more significant in Caucasians, in population-based studies, and in larger studies

Deep attentive video summarization with distribution consistency learning

This article studies supervised video summarization by formulating it into a sequence-to-sequence learning framework, in which the input and output are sequences of original video frames and their predicted importance scores, respectively. Two critical issues are addressed in this article: short-term contextual attention insufficiency and distribution inconsistency. The former lies in the insufficiency of capturing the short-term contextual attention information within the video sequence itself since the existing approaches focus a lot on the long-term encoder-decoder attention. The latter refers to the distributions of predicted importance score sequence and the ground-truth sequence is inconsistent, which may lead to a suboptimal solution. To better mitigate the first issue, we incorporate a self-attention mechanism in the encoder to highlight the important keyframes in a short-term context. The proposed approach alongside the encoder-decoder attention constitutes our deep attentive models for video summarization. For the second one, we propose a distribution consistency learning method by employing a simple yet effective regularization loss term, which seeks a consistent distribution for the two sequences. Our final approach is dubbed as Attentive and Distribution consistent video Summarization (ADSum). Extensive experiments on benchmark data sets demonstrate the superiority of the proposed ADSum approach against state-of-the-art approaches