A Multi-parameter Approach to Automated Building Grouping and Generalization

This paper presents an approach to automated building grouping and generalization. Three principles of Gestalt theories, i.e. proximity, similarity, and common directions, are employed as guidelines, and six parameters, i.e. minimum distance, area of visible scope, area ratio, edge number ratio, smallest minimum bounding rectangle (SMBR), directional Voronoi diagram (DVD), are selected to describe spatial patterns, distributions and relations of buildings. Based on these principles and parameters, an approach to building grouping and generalization is developed. First, buildings are triangulated based on Delaunay triangulation rules, by which topological adjacency relations between buildings are obtained and the six parameters are calculated and recorded. Every two topologically adjacent buildings form a potential group. Three criteria from previous experience and Gestalt principles are employed to tell whether a 2-building group is ‘strong,' ‘average' or ‘weak.' The ‘weak' groups are deleted from the group array. Secondly, the retained groups with common buildings are organized to form intermediate groups according to their relations. After this step, the intermediate groups with common buildings are aggregated or separated and the final groups are formed. Finally, appropriate operators/algorithms are selected for each group and the generalized buildings are achieved. This approach is fully automatic. As our experiments show, it can be used primarily in the generalization of buildings arranged in block

Theory of Spatial Similarity Relations and Its Applications in Automated Map Generalization

Automated map generalization is a necessary technique for the construction of multi-scale vector map databases that are crucial components in spatial data infrastructure of cities, provinces, and countries. Nevertheless, this is still a dream because many algorithms for map feature generalization are not parameter-free and therefore need human’s interference. One of the major reasons is that map generalization is a process of spatial similarity transformation in multi-scale map spaces; however, no theory can be found to support such kind of transformation. This thesis focuses on the theory of spatial similarity relations in multi-scale map spaces, aiming at proposing the approaches and models that can be used to automate some relevant algorithms in map generalization. After a systematic review of existing achievements including the definitions and features of similarity in various communities, a classification system of spatial similarity relations, and the calculation models of similarity relations in the communities of psychology, computer science, music, and geography, as well as a number of raster-based approaches for calculating similarity degrees between images, the thesis achieves the following innovative contributions. First, the fundamental issues of spatial similarity relations are explored, i.e. (1) a classification system is proposed that classifies the objects processed by map generalization algorithms into ten categories; (2) the Set Theory-based definitions of similarity, spatial similarity, and spatial similarity relation in multi-scale map spaces are given; (3) mathematical language-based descriptions of the features of spatial similarity relations in multi-scale map spaces are addressed; (4) the factors that affect human’s judgments of spatial similarity relations are proposed, and their weights are also obtained by psychological experiments; and (5) a classification system for spatial similarity relations in multi-scale map spaces is proposed. Second, the models that can calculate spatial similarity degrees for the ten types of objects in multi-scale map spaces are proposed, and their validity is tested by psychological experiments. If a map (or an individual object, or an object group) and its generalized counterpart are given, the models can be used to calculate the spatial similarity degrees between them. Third, the proposed models are used to solve problems in map generalization: (1) ten formulae are constructed that can calculate spatial similarity degrees by map scale changes in map generalization; (2) an approach based on spatial similarity degree is proposed that can determine when to terminate a map generalization system or an algorithm when it is executed to generalize objects on maps, which may fully automate some relevant algorithms and therefore improve the efficiency of map generalization; and (3) an approach is proposed to calculate the distance tolerance of the Douglas-Peucker Algorithm so that the Douglas-Peucker Algorithm may become fully automatic. Nevertheless, the theory and the approaches proposed in this study possess two limitations and needs further exploration. • More experiments should be done to improve the accuracy and adaptability of the proposed models and formulae. The new experiments should select more typical maps and map objects as samples, and find more subjects with different cultural backgrounds. • Whether it is feasible to integrate the ten models/formulae for calculating spatial similarity degrees into an identical model/formula needs further investigation. In addition, it is important to find out the other algorithms, like the Douglas-Peucker Algorithm, that are not parameter-free and closely related to spatial similarity relation, and explore the approaches to calculating the parameters used in these algorithms with the help of the models and formulae proposed in this thesis

Focusing light through scattering media by transmission matrix inversion

Focusing light through scattering media has broad applications in optical imaging, manipulation and therapy. The contrast of the focus can be quantified by peak-to-background intensity ratio (PBR). Here, we theoretically and numerically show that by using a transmission matrix inversion method to achieve focusing, within a limited field of view and under a low noise condition in transmission matrix measurements, the PBR of the focus can be higher than that achieved by conventional methods such as optical phase conjugation or feedback-based wavefront shaping. Experimentally, using a phase-modulation spatial light modulator, we increase the PBR by 66% over that achieved by conventional methods based on phase conjugation. In addition, we demonstrate that, within a limited field of view and under a low noise condition in transmission matrix measurements, our matrix inversion method enables light focusing to multiple foci with greater fidelity than those of conventional methods

Time-reversed ultrasonically encoded (TRUE) focusing for deep-tissue optogenetic modulation

The problem of optical scattering was long thought to fundamentally limit the depth at which light could be focused through turbid media such as fog or biological tissue. However, recent work in the field of wavefront shaping has demonstrated that by properly shaping the input light field, light can be noninvasively focused to desired locations deep inside scattering media. This has led to the development of several new techniques which have the potential to enhance the capabilities of existing optical tools in biomedicine. Unfortunately, extending these methods to living tissue has a number of challenges related to the requirements for noninvasive guidestar operation, speed, and focusing fidelity. Of existing wavefront shaping methods, time-reversed ultrasonically encoded (TRUE) focusing is well suited for applications in living tissue since it uses ultrasound as a guidestar which enables noninvasive operation and provides compatibility with optical phase conjugation for high-speed operation. In this paper, we will discuss the results of our recent work to apply TRUE focusing for optogenetic modulation, which enables enhanced optogenetic stimulation deep in tissue with a 4-fold spatial resolution improvement in 800-micron thick acute brain slices compared to conventional focusing, and summarize future directions to further extend the impact of wavefront shaping technologies in biomedicine

Focusing light inside scattering media with magnetic-particle-guided wavefront shaping

Optical scattering has traditionally limited the ability to focus light inside scattering media such as biological tissue. Recently developed wavefront shaping techniques promise to overcome this limit by tailoring an optical wavefront to constructively interfere at a target location deep inside scattering media. To find such a wavefront solution, a “guidestar” mechanism is required to identify the target location. However, developing guidestars of practical usefulness is challenging, especially in biological tissue, which hinders the translation of wavefront shaping techniques. Here, we demonstrate a guidestar mechanism that relies on magnetic modulation of small particles. This guidestar method features an optical modulation efficiency of 29% and enables micrometer-scale focusing inside biological tissue with a peak intensity-to-background ratio (PBR) of 140; both numbers are one order of magnitude higher than those achieved with the ultrasound guidestar, a popular guidestar method. We also demonstrate that light can be focused on cells labeled with magnetic particles, and to different target locations by magnetically controlling the position of a particle. Since magnetic fields have a large penetration depth even through bone structures like the skull, this optical focusing method holds great promise for deep-tissue applications such as optogenetic modulation of neurons, targeted light-based therapy, and imaging

Stiffness of Substrate Influences the Distribution but not the Synthesis of Autophagosomes in Human Liver (LO2) Cells

Extracellular matrix (ECM) often becomes stiffer during tumor development, which not only gives the tumor's hardness feel but also actively contributes to the tumor formation. A good example is hepatocellular carcinoma (HCC) that usually develops within chronically stiffened liver tissues due to fibrosis and cirrhosis. On the other hand, HCC cells exhibit reduced autophagy in a malignancy dependent manner, suggesting autophagy is suppressed during tumor development. However, it is not known whether ECM stiffness would influence autophagy during tumor development. To investigate this issue, We cultured the human liver (LO2) cells that stably expressed autophagosome indicator LC3 on polydimethylsiloxane (PDMS) gels with stiffness varying from 11 to 1220 kPa. and on plastic cell culture dish as controls for up to 48h. We found that the total protein level of LC3-II in LO2 cells was not affected by the substrate stiffness. However the autophagosomes in LO2 cells cultured on the soft substrate (11 kPa PDMS gel) were localized and accumulated around the nucleus, while those on the stiff substrate (1220 kPa PDMS gel or plastic dish surface) were dispersed throughout the cytoplasmic space. Therefore, our data suggest that ECM stiffness may not directly synthesize nascent autophagosomes, but instead influence the location/translocation and ultimately distribution of autophagosomes in the cells

Focusing light through scattering media by transmission matrix inversion

Focusing light through scattering media has broad applications in optical imaging, manipulation and therapy. The contrast of the focus can be quantified by peak-to-background intensity ratio (PBR). Here, we theoretically and numerically show that by using a transmission matrix inversion method to achieve focusing, within a limited field of view and under a low noise condition in transmission matrix measurements, the PBR of the focus can be higher than that achieved by conventional methods such as optical phase conjugation or feedback-based wavefront shaping. Experimentally, using a phase-modulation spatial light modulator, we increase the PBR by 66% over that achieved by conventional methods based on phase conjugation. In addition, we demonstrate that, within a limited field of view and under a low noise condition in transmission matrix measurements, our matrix inversion method enables light focusing to multiple foci with greater fidelity than those of conventional methods

Deep tissue optical focusing and optogenetic modulation with time-reversed ultrasonically encoded light

Noninvasive light focusing deep inside living biological tissue has long been a goal in biomedical optics. However, the optical scattering of biological tissue prevents conventional optical systems from tightly focusing visible light beyond several hundred micrometers. The recently developed wavefront shaping technique time-reversed ultrasonically encoded (TRUE) focusing enables noninvasive light delivery to targeted locations beyond the optical diffusion limit. However, until now, TRUE focusing has only been demonstrated inside nonliving tissue samples. We present the first example of TRUE focusing in 2-mm-thick living brain tissue and demonstrate its application for optogenetic modulation of neural activity in 800-μm-thick acute mouse brain slices at a wavelength of 532 nm. We found that TRUE focusing enabled precise control of neuron firing and increased the spatial resolution of neuronal excitation fourfold when compared to conventional lens focusing. This work is an important step in the application of TRUE focusing for practical biomedical uses