165 research outputs found
On the crossing numbers of complete graphs
No full textI hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. ii In this thesis we prove two main results. The Triangle Conjecture asserts that the convex hull of any optimal rectilinear drawing of Kn must be a triangle (for n � 3). We prove that, for the larger class of pseudolinear drawings, the outer face must be a triangle. The other main result is the next step toward Guy’s Conjecture that the crossing number of Kn is
Robust pole assignment via the Schur-Newton algorithms
No full textIn [6], the pole assignment problem was considered for the control system ẋ = Ax + Bu with linear state-feedback u = Fx. An algorithm using the Schur form has been proposed, producing suboptimal solutions which can be refined further using optimization. In this paper, the algorithm is improved, with a weighted sum of the feedback gain and the departure from normality being used as the robustness measure. Newton refinement procedure is implemented, producing optimal solutions. Several illustrative numerical examples are presented.</p
3D interconnect technology based on low temperature copper nanoparticle sintering
No full textWe explore a methodology for patterned copper nanoparticle paste for 3D interconnect applications in wafer to wafer (W2W) bonding. A novel fine pitch thermal compression bonding process (sintering) with coated copper nanoparticle paste was developed. Most of the particle size is between 10-30 nm. Lithographically defined stencil printing using photoresist and lift-off was used to apply and pattern the paste. Variations in sintering process parameters, such as: pressure, geometry and ambient atmosphere, were studied. Compared to Sn-Ag-Cu (SAC) microsolder bumps, we achieved better interconnect resistivity after sintering at 260 °C for 10 min, in a 700 mBar hydrogen forming gas (H2/N2) environment. The electrical resistivity was 7.84 ± 1.45 μΩ·cm, which is about 4.6 times that of bulk copper. In addition, metallic nanoparticle interconnect porosity can influence the electrical properties of the interconnect. Consequently, we investigated the porosity effect on conductivity using finite element simulation. A linear relationship between the equivalent conductivity and particle overlapping ratio was found.Accepted Author ManuscriptElectronic Components, Technology and MaterialsEKL Processin
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On the theory and application of pattern maximum likelihood
No full textPattern Maximum Likelihood (PML) is a method of probability estimation that works well for large alphabets. It does not assume that all elements from the unknown alphabet have been observed. PML outperforms the traditional Maximum Likelihood for sequences, and it is particularly useful when the sample size is small. In this dissertation we study both the theory and application of PML. For the theory part, we extend the previous results on the properties of PML, and also show how to find the PML distributions analytically for patterns of simple forms. For general patterns, PML probabilities can be approximated using a previously developed EM algorithm, which we will prove to be equivalent to a generalized Gradient Ascend Method. We also use the algorithm to conduct experiments on different distributions and evaluate the performance of PML. In addition, we investigate the calculation of pattern probability. We show that the pattern probability is closely related to symmetric polynomials, and it can be written as a summation over graphs using power sums. Along the way we reveal a relation between pattern probability and the enumeration of certain connected graphs as well as inversion-free trees. For applications, we show how PML can be used to predict the number of new symbols that would appear in a future sample. We conduct experiments on various distributions and compare PML to the method of Good & Toulmin and the method of Efron & Thisted. We demonstrate that PML outperforms the other methods even if the future sample size is large. Finally we apply PML to authenticating the authorship of the Taylor poem, attributed to Shakespeare, and conclude that it is consistent with Efron and Thisted's models. PML deals with samples from a single distribution. In the last part of this dissertation we extend PML to set-patterns where multiple samples are observed from concurrent Bernoulli processes. Analogous to the single-process patterns, we show that for certain forms of set-patterns we can find the exact Set-pattern Maximum Likelihood (SPML) probabilities analytically. Furthermore, for general set- patterns we extend the previous EM algorithm to approximate the SPML probabilities. We also show that for samples taken from Poisson distributions the set-pattern is reduced to the single-process pattern proble
Preparation of water-soluble chitosan by hydrolysis with commercial glucoamylase containing chitosanase activity
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Productive facilitatory acts - An empirical study of Aalto ArtSpace co-design workshops
No full textCo-design has gain its popularity in engaging various stakeholders into the design process. Across the industry and academy, co-design workshops are widely used in the early phase of design. Due to the complex interaction nature of co-design workshops, it is challenging for the facilitators to get productive outcomes that are informative to the design project. Although numerous of co-design methods are offered, few attempts to elucidate how co-design practitioners shall facilitate co-design workshops productively.
In this thesis, the author sets out to de ne co-design workshops, facilitatory acts and attempts to identify productive facilitatory acts by analysing a serious of three co-design workshop. In addition, the author experiments with the Framing Analysis of Design Articulation (FADA) method (Ylirisku, 2013) in the process of analysing the workshop video records
CDFAN: Cross-Domain Fusion Attention Network for Pansharpening
No full textPansharpening provides a computational solution to the resolution limitations of imaging hardware by enhancing the spatial quality of low-resolution hyperspectral (LRMS) images using high-resolution panchromatic (PAN) guidance. From an information-theoretic perspective, the task involves maximizing the mutual information between PAN and LRMS inputs while minimizing spectral distortion and redundancy in the fused output. However, traditional spatial-domain methods often fail to preserve high-frequency texture details, leading to entropy degradation in the resulting images. On the other hand, frequency-based approaches struggle to effectively integrate spatial and spectral cues, often neglecting the underlying information content distributions across domains. To address these shortcomings, we introduce a novel architecture, termed the Cross-Domain Fusion Attention Network (CDFAN), specifically designed for the pansharpening task. CDFAN is composed of two core modules: the Multi-Domain Interactive Attention (MDIA) module and the Spatial Multi-Scale Enhancement (SMCE) module. The MDIA module utilizes discrete wavelet transform (DWT) to decompose the PAN image into frequency sub-bands, which are then employed to construct attention mechanisms across both wavelet and spatial domains. Specifically, wavelet-domain features are used to formulate query vectors, while key features are derived from the spatial domain, allowing attention weights to be computed over multi-domain representations. This design facilitates more effective fusion of spectral and spatial cues, contributing to superior reconstruction of high-resolution multispectral (HRMS) images. Complementing this, the SMCE module integrates multi-scale convolutional pathways to reinforce spatial detail extraction at varying receptive fields. Additionally, an Expert Feature Compensator is introduced to adaptively balance contributions from different scales, thereby optimizing the trade-off between local detail preservation and global contextual understanding. Comprehensive experiments conducted on standard benchmark datasets demonstrate that CDFAN achieves notable improvements over existing state-of-the-art pansharpening methods, delivering enhanced spectral–spatial fidelity and producing images with higher perceptual quality
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