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Showing result 1 - 5 of 6 essays matching the above criteria.
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1. Application of Bootstrap in Approximate Bayesian Computation (ABC)
University essay from Uppsala universitet/Statistik, AI och data scienceAbstract : The ABC algorithm is a Bayesian method which simulates samples from the posterior distribution. In this thesis, the method is applied on both synthetic and observed data of a regression model. Under normal error distribution a conjugate prior and the likelihood function are used in the algorithm. READ MORE
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2. Selective Kernel Network based Crowding Counting and Crowd Density Estimation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Managing crowd density has become an immense challenge for public authorities due to population growth and evolving human dynamics. Crowd counting estimates the number of individuals in a given area or scene, making it a practical technique applicable in real-world scenarios such as surveillance and traffic control. READ MORE
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3. Estimating Median Visiting Times using Re-identification
University essay from Lunds universitet/Matematik LTHAbstract : Using customer visiting times stores can analyse customer behaviour and gain insights to help improve the store experience. This thesis investigates the possibility of using person re-identification to create a system that can estimate the median visiting time. Neural networks were used to analyse images of persons from two different views. READ MORE
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4. Parameter selection and derivative conditions for B-splines applied to gas turbine blade modeling
University essay from Lunds universitet/Matematik LTHAbstract : In gas turbine blade modeling a stable but yet flexible method of describing the blade shape is crucial. Polynomials and B ́ezier curves have previously been used and in this paper B-splines are employed instead. READ MORE
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5. R&D Efficiency in China: Can State-owned Firms Compete?
University essay from Lunds universitet/Ekonomisk-historiska institutionenAbstract : Can state-owned firms’ R&D compete with that of more nimble private and foreign innovator firms? This paper analyzes R&D efficiency in China’s high tech industries (i) theoretically, based on previous studies, and (ii) empirically, through Data Envelopment Analysis under both Constant and Variable Returns to Scale. Though Chinese state-owned firms can theoretically be R&D efficient in industries where the underlying science is well understood, a myriad of factors including persistent soft budget constraints and policy burdens mitigate the potential advantages – bureaucratic pre-screening and access to finance – that characterize state-owned firms. READ MORE