217 research outputs found
Moore–Penrose inverse of set inclusion matrices
No full textAbstractGiven integers s,k and v, let Wsk be the vs×vk 0–1 matrix, the rows and the columns of which are indexed by the s-subsets and the k-subsets of a v-set respectively, and where the entry in row S and column U is 1 if S⊂U and 0 otherwise. A formula for the Moore–Penrose inverse of Wsk over the reals is obtained. A necessary and sufficient condition for Wsk to admit a Moore–Penrose inverse over the set of integers modulo a prime p is given, together with a formula for the Moore–Penrose inverse when it exists
Probabilistic Lifetime Predictions Using Total Stress Concept, Remote Monitoring and Global Wave Forecast Models: Fatigue Analysis of Damen’s FCS5009 Vessels
No full textAt Damen’s Research and Development department, continuous improvements are made to existing design practices using recent technological developments and fatigue design is currently on the anvil. High speed craft operating around the globe are subject to millions of load cycles (resulting from ocean waves) and therefore suffer from metal fatigue. As per current practice, such vessels are designed for fatigue using inhouse software with a nominal stress approach supported by static sea-state scatter data and judgement based operational profiles. Recently, new data sources with real time sea-state data over the whole globe have come available, including GPS locations of ships. Together, this enables it to generate real time operational profiles for its ships. A total stress concept has been developed based on results from a JIP called VOMAS. This approach has shown to provide accurate fatigue lifetime estimates for arc-welded aluminium joints. Similar results are expected for steel joints as well. The main goal of this thesis was to explore possible improvements for the fatigue design methodology. A tool called Tanaav was developed for this purpose which makes use of both remote monitoring data and the total stress concept and provides an estimate of the yearly fatigue damage and fatigue lifetime. The tool has been used to predict the fatigue lifetime for three fatigue sensitive details in 46 FCS5009 vessels. Results have been compared to corresponding predictions using current and past fatigue analysis practices. It was observed that using both remote monitoring data as well as the total stress concept provides significant improvements in the predicted fatigue life time. Uncertainties in fatigue influence parameters affecting the predicted fatigue damage can be incorporated using probabilistic. This thesis proposes a method for this and presents two cases as a proof of concept. Work done in this thesis will be validated by Damen in future with the help of full-scale testing on an actual FCS5009 vessel during an offshore measurement campaign. After validation, this method will help in improving fatigue design practice, increasing design flexibility and in optimizing vessel weights in a responsible way. <br/
Helping Chatbots To Better Understand User Requests Efficiently Using Human Computation
No full textChatbots are the text based conversational agents with which users interact in natural language. They are becoming more and more popular with the immense growth in messaging apps and tools to develop text based conversational agents. Despite of advances in Artificial Intelligence and Natural Language Processing, chatbots still struggle in accurately understanding user requests, thus providing wrong answers or no response. An effective solution to tackle this problem is involving human's capabilities in chatbot’s operations for understanding user requests. There are many existing systems using humans in chatbots but they are not capable to scale up with the increasing number of users. To address this problem, we provide insights in how to design such chatbot system having humans in the loop and how to involve humans efficiently.We perform an extensive literature survey about chatbots, and human computation applied for a chatbot, to guide the design of our reference chatbot system. Then we address the problem of cold starting chatbot systems. We propose a methodology to generate high quality training data, with which, chatbot’s Natural Language Understanding (NLU) model can be trained, making a chatbot capable of handling user requests efficiently at run time. Finally we provide a methodology to estimate the reliability of black box NLU models based on the confidence threshold of their prediction functionality. We study and discuss the effect of parameters such as training data set size, type of intents on automatic NLU model.<br/
The Moore-Penrose inverse over a commutative ring
No full textAbstractLet R be a commutative ring with 1 and with an involution a → ā, and let MR be the category of finite matrices over R with the involution (aij) → (aij)∗ = (āji). A matrix A:m → n in MR of determinantal rank r such that u(A) = ∑α∈Qr.m∑α∈Qr.m det Aαβ det Aαβ has a Moore-Penrose inverse u(A)† in R is said to be Moore invertible with Moore idempotent u(A)u(A)† if u(A)u(A)†A = A. For every matrix A of MR, A has a Moore-Penrose inverse with respect to ∗ if and only if A is the sum of Moore invertible matrices whose Moore idempotents are pairwise orthogonal
Maternal and neonatal health expenditure in Mumbai slums (India): A cross sectional study
No full textBackground: The cost of maternity care can be a barrier to access that may increase maternal and neonatal mortality risk. We analyzed spending on maternity care in urban slum communities in Mumbai to better understand the equity of spending and the impact of spending on household poverty.Methods: We used expenditure data for maternal and neonatal care, collected during post-partum interviews. Interviews were conducted in 2005-2006, with a sample of 1200 slum residents in Mumbai (India). We analysed expenditure by socio-economic status (SES), calculating a Kakwani Index for a range of spending categories. We also calculated catastrophic health spending both with and without adjustment for coping strategies. This identified the level of catastrophic payments incurred by a household and the prevalence of catastrophic payments in this population. The analysis also gave an understanding of the protection from medical poverty afforded by coping strategies (for example saving and borrowing).Results: A high proportion of respondents spent catastrophically on care. Lower SES was associated with a higher proportion of informal payments. Indirect health expenditure was found to be (weakly) regressive as the poorest were more likely to use wage income to meet health expenses, while the less poor were more likely to use savings. Overall, the incidence of catastrophic maternity expenditure was 41%, or 15% when controlling for coping strategies. We found no significant difference in the incidence of catastrophic spending across wealth quintiles, nor could we conclude that total expenditure is regressive.Conclusions: High expenditure as a proportion of household resources should alert policymakers to the burden of maternal spending in this context. Differences in informal payments, significantly regressive indirect spending and the use of savings versus wages to finance spending, all highlight the heavier burden borne by the most poor. If a policy objective is to increase institutional deliveries without forcing households deeper into poverty, these inequities will need to be addressed. Reducing out-of-pocket payments and better regulating informal payments should have direct benefits for the most poor. Alternatively, targeted schemes aimed at assisting the most poor in coping with maternal spending (including indirect spending) could reduce the household impact of high costs
Amalā Prajñā: Aspects of Buddhist Studies : Professor P.V. Bapat Felicitation Volume
No full textRonald M. Davidson is a contributing author, “Āśraya-parāvṛtti and Mahāyānābhidharma: some Problems and Perspectives .https://digitalcommons.fairfield.edu/religiousstudies-books/1090/thumbnail.jp
On Cartesian product of Euclidean distance matrices
No full textIf A∈Rm×m and B∈Rn×n, we define the product A⊘B as A⊘B=A⊗Jn+Jm⊗B, where ⊗ denotes the Kronecker product and Jn is the n×n matrix of all ones. We refer to this product as the Cartesian product of A and B since if D1 and D2 are the distance matrices of graphs G1 and G2 respectively, then D1⊘D2 is the distance matrix of the Cartesian product G1□G2. We study Cartesian products of Euclidean distance matrices (EDMs). We prove that if A and B are EDMs, then so is the product A⊘B. We show that if A is an EDM and U is symmetric, then A⊗U is an EDM if and only if U=cJn for some c. It is shown that for EDMs A and B, A⊘B is spherical if and only if both A and B are spherical. If A and B are EDMs, then we derive expressions for the rank and the Moore–Penrose inverse of A⊘B. In the final section we consider the product A⊘B for arbitrary matrices. For A∈Rm×m,B∈Rn×n, we show that all nonzero minors of A⊘B of order m+n−1 are equal. An explicit formula for a nonzero minor of order m+n−1 is proved. The result is shown to generalize the familiar fact that the determinant of the distance matrix of a tree on n vertices does not depend on the tree and is a function only of n
Effective crowdsourced generation of training data for chatbots natural language understanding
No full textChatbots are text-based conversational agents. Natural Language Understanding (NLU) models are used to extract meaning and intention from user messages sent to chatbots. The user experience of chatbots largely depends on the performance of the NLU model, which itself largely depends on the initial dataset the model is trained with. The training data should cover the diversity of real user requests the chatbot will receive. Obtaining such data is a challenging task even for big corporations. We introduce a generic approach to generate training data with the help of crowd workers, we discuss the approach workflow and the design of crowdsourcing tasks assuring high quality. We evaluate the approach by running an experiment collecting data for 9 different intents. We use the collected training data to train a natural language understanding model. We analyse the performance of the model under different training set sizes for each intent. We provide recommendations on selecting an optimal confidence threshold for predicting intents, based on the cost model of incorrect and unknown predictions
Molecular Insights into Water Clusters Formed in Tributylphosphate–Di-(2-ethylhexyl)phosphoric Acid Extractant Systems from Experiments and Molecular Dynamics Simulations
No full textDi-(2-ethylhexyl)phosphoric acid
(D2EHPA) and tributylphosphate
(TBP) are two of the most studied and researched organophosphorous
extractants. D2EHPA is an acidic extractant, offering both hydrogen
bond donor and acceptor sites while TBP, a neutral extractant, only
offers a single acceptor site per molecule. In spite of this, it is
observed that 1 M D2EHPA in dodecane is a poorer extractant for water
than 1 M TBP in dodecane. The objective of present work is to look
into the molecular interactions that cause such behavior. Experiments
were carried out with varying molar ratios of TBP and D2EHPA in the
organic dodecane phase. Total extractant concentration was kept constant
at 1 M with dodecane as diluent. Water extraction was quantified by
measuring the moisture content of the organic phase after equilibration. 1H and 31P NMR spectra of the organic phase samples
were recorded to study the change in the chemical environment upon
extraction. Small angle X-ray scattering data of water saturated extractant
phases were analyzed for the possibility of a reverse micellar aggregate
formation. Molecular dynamics simulations could calculate free energies
in quantitative agreement with experiments. Experimental and simulation
studies showed that aggregation in the organic phase was promoted
by the presence of water. This combined approach, of experiments and
simulation, has shown that water is indispensable for the formation
of ordered aggregates of extractants in nonpolar organic solvents.
It is seen that, in the organic phase, around 80% of water’s
hydrogen bonds are with extractant molecules rather than with itself.
The analysis clearly indicates that, rather than forming an aqueous
core surrounded by extractant, water acts as a bridge between extractant
molecules
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