Property Recommendation System With Geospatial Data Analytics Andnatural Language Processing For Urban Land Use

Recently Cuyahoga County has been tremendously improved as properties are being constructed, renovated, or altered for new land use transactions on a nearly daily basis. Most existing property recommendation systems for the area simply rely on surface-level information and user history data to produce recommendations while failing to prioritize factors according to their importance and utilizing the location based complex information efficiently. This is leading them to become stagnant and simplistic in their approach and their accuracy is worsening as there are too many factors to be considered and location based complex yet useful information such as land use aspects of neighboring areas or information about people who are living or working in the area are often hard to be discovered. To combat these issues, this thesis proposes a modern property recommendation system with new approaches: 1) Employing data analytic methods to discover complex location based geospatial knowledge from big data processing, 2) Collecting and deriving summary information on people demographic data in the neighbor, and 3) Adopting natural language processing techniques for a user given phrase query to generate accurate candidate sets. Our recommendation system consists of three key components: 1) Using derived geospatial knowledge as new features and viewpoints for a better overall understanding of neighbor for a given property. 2) Incorporating Hotspot Analysis and data analytic methods to identify which areas are the v most ideal for each type of properties based on current and history data. 3) Allowing a user query in a sentence or phrase through natural language text processing techniques to create accurate candidates to tailor recommendations to a given individual user to return the Top-N ranked results. The experimental results show the effectiveness of these new approaches

Pattern Avoidance in k-ary Heaps

In this paper, we consider pattern avoidance in k-ary heaps, where the permutation associated with the heap is found by recording the nodes as they are encountered in a breadth-first search. We enumerate heaps that avoid patterns of length 3 and collections of patterns of length 3, first with binary heaps and then more generally with k-ary heaps

OTIS 3.2 Software Released

Trajectory, mission, and vehicle engineers concern themselves with finding the best way for an object to get from one place to another. These engineers rely upon special software to assist them in this. For a number of years, many engineers have used the OTIS program for this assistance. With OTIS, an engineer can fully optimize trajectories for airplanes, launch vehicles like the space shuttle, interplanetary spacecraft, and orbital transfer vehicles. OTIS provides four modes of operation, with each mode providing successively stronger optimization capability. The most powerful mode uses a mathematical method called implicit integration to solve what engineers and mathematicians call the optimal control problem. OTIS 3.2, which was developed at the NASA Glenn Research Center, is the latest release of this industry workhorse and features new capabilities for parameter optimization and mission design. OTIS stands for Optimal Control by Implicit Simulation, and it is implicit integration that makes OTIS so powerful at solving trajectory optimization problems. Why is this so important? The optimization process not only determines how to get from point A to point B, but it can also determine how to do this with the least amount of propellant, with the lightest starting weight, or in the fastest time possible while avoiding certain obstacles along the way. There are numerous conditions that engineers can use to define optimal, or best. OTIS provides a framework for defining the starting and ending points of the trajectory (point A and point B), the constraints on the trajectory (requirements like "avoid these regions where obstacles occur"), and what is being optimized (e.g., minimize propellant). The implicit integration method can find solutions to very complicated problems when there is not a lot of information available about what the optimal trajectory might be. The method was first developed for solving two-point boundary value problems and was adapted for use in OTIS. Implicit integration usually allows OTIS to find solutions to problems much faster than programs that use explicit integration and parametric methods. Consequently, OTIS is best suited to solving very complicated and highly constrained problems

Generating Functions and Wilf Equivalence for Generalized Interval Embeddings

In 1999 in [J. Difference Equ. Appl. 5, 355–377], Noonan and Zeilberger extended the Goulden-Jackson Cluster Method to find generating functions of word factors. Then in 2009 in [Electron. J. Combin. 16(2), RZZ], Kitaev, Liese, Remmel and Sagan found generating functions for word embeddings and proved several results on Wilf-equivalence in that setting. In this article, the authors focus on generalized interval embeddings, which encapsulate both factors and embeddings, as well as the “space between” these two ideas. The authors present some results in the most general case of interval embeddings. Two special cases of interval embeddings are also discussed, as well as their relationship to results in previous works in the area of pattern avoidance in words

Trajectory Optimization: OTIS 4

The latest release of the Optimal Trajectories by Implicit Simulation (OTIS4) allows users to simulate and optimize aerospace vehicle trajectories. With OTIS4, one can seamlessly generate optimal trajectories and parametric vehicle designs simultaneously. New features also allow OTIS4 to solve non-aerospace continuous time optimal control problems. The inputs and outputs of OTIS4 have been updated extensively from previous versions. Inputs now make use of objectoriented constructs, including one called a metastring. Metastrings use a greatly improved calculator and common nomenclature to reduce the user s workload. They allow for more flexibility in specifying vehicle physical models, boundary conditions, and path constraints. The OTIS4 calculator supports common mathematical functions, Boolean operations, and conditional statements. This allows users to define their own variables for use as outputs, constraints, or objective functions. The user-defined outputs can directly interface with other programs, such as spreadsheets, plotting packages, and visualization programs. Internally, OTIS4 has more explicit and implicit integration procedures, including high-order collocation methods, the pseudo-spectral method, and several variations of multiple shooting. Users may switch easily between the various methods. Several unique numerical techniques such as automated variable scaling and implicit integration grid refinement, support the integration methods. OTIS4 is also significantly more user friendly than previous versions. The installation process is nearly identical on various platforms, including Microsoft Windows, Apple OS X, and Linux operating systems. Cross-platform scripts also help make the execution of OTIS and post-processing of data easier. OTIS4 is supplied free by NASA and is subject to ITAR (International Traffic in Arms Regulations) restrictions. Users must have a Fortran compiler, and a Python interpreter is highly recommended

Carbon stable isotope analysis of cereal remains as a way to reconstruct water availability: preliminary results

Reconstructing past water availability, both as rainfall and irrigation, is important to answer questions about the way society reacts to climate and its changes and the role of irrigation in the development of social complexity. Carbon stable isotope analysis of archaeobotanical remains is a potentially valuable method for reconstructing water availability. To further define the relationship between water availability and plant carbon isotope composition and to set up baseline values for the Southern Levant, grains of experimentally grown barley and sorghum were studied. The cereal crops were grown at three stations under five different irrigation regimes in Jordan. Results indicate that a positive but weak relationship exists between irrigation regime and total water input of barley grains, but no relationship was found for sorghum. The relationship for barley is site-specific and inter-annual variation was present at Deir ‘Alla, but not at Ramtha and Khirbet as-Samra

A unique tRNA recognition mechanism of Caenorhabditis elegans mitochondrial EF-Tu2

Nematode mitochondria expresses two types of extremely truncated tRNAs that are specifically recognized by two distinct elongation factor Tu (EF-Tu) species named EF-Tu1 and EF-Tu2. This is unlike the canonical EF-Tu molecule that participates in the standard protein biosynthesis systems, which basically recognizes all elongator tRNAs. EF-Tu2 specifically recognizes Ser-tRNA(Ser) that lacks a D arm but has a short T arm. Our previous study led us to speculate the lack of the D arm may be essential for the tRNA recognition of EF-Tu2. However, here, we showed that the EF-Tu2 can bind to D arm-bearing Ser-tRNAs, in which the D–T arm interaction was weakened by the mutations. The ethylnitrosourea-modification interference assay showed that EF-Tu2 is unique, in that it interacts with the phosphate groups on the T stem on the side that is opposite to where canonical EF-Tu binds. The hydrolysis protection assay using several EF-Tu2 mutants then strongly suggests that seven C-terminal amino acid residues of EF-Tu2 are essential for its aminoacyl-tRNA-binding activity. Our results indicate that the formation of the nematode mitochondrial (mt) EF-Tu2/GTP/aminoacyl-tRNA ternary complex is probably supported by a unique interaction between the C-terminal extension of EF-Tu2 and the tRNA

Investigating the topology of interacting networks - Theory and application to coupled climate subnetworks

Network theory provides various tools for investigating the structural or functional topology of many complex systems found in nature, technology and society. Nevertheless, it has recently been realised that a considerable number of systems of interest should be treated, more appropriately, as interacting networks or networks of networks. Here we introduce a novel graph-theoretical framework for studying the interaction structure between subnetworks embedded within a complex network of networks. This framework allows us to quantify the structural role of single vertices or whole subnetworks with respect to the interaction of a pair of subnetworks on local, mesoscopic and global topological scales. Climate networks have recently been shown to be a powerful tool for the analysis of climatological data. Applying the general framework for studying interacting networks, we introduce coupled climate subnetworks to represent and investigate the topology of statistical relationships between the fields of distinct climatological variables. Using coupled climate subnetworks to investigate the terrestrial atmosphere's three-dimensional geopotential height field uncovers known as well as interesting novel features of the atmosphere's vertical stratification and general circulation. Specifically, the new measure "cross-betweenness" identifies regions which are particularly important for mediating vertical wind field interactions. The promising results obtained by following the coupled climate subnetwork approach present a first step towards an improved understanding of the Earth system and its complex interacting components from a network perspective

Toolbox model of evolution of metabolic pathways on networks of arbitrary topology

In prokaryotic genomes the number of transcriptional regulators is known to quadratically scale with the total number of protein-coding genes. Toolbox model was recently proposed to explain this scaling for metabolic enzymes and their regulators. According to its rules the metabolic network of an organism evolves by horizontal transfer of pathways from other species. These pathways are part of a larger "universal" network formed by the union of all species-specific networks. It remained to be understood, however, how the topological properties of this universal network influence the scaling law of functional content of genomes. In this study we answer this question by first analyzing the scaling properties of the toolbox model on arbitrary tree-like universal networks. We mathematically prove that the critical branching topology, in which the average number of upstream neighbors of a node is equal to one, is both necessary and sufficient for the quadratic scaling. Conversely, the toolbox model on trees with exponentially expanding, supercritical topology is characterized by the linear scaling with logarithmic corrections. We further generalize our model to include reactions with multiple substrates/products as well as branched or cyclic metabolic pathways. Unlike the original model the new version employs evolutionary optimized pathways with the smallest number of reactions necessary to achieve their metabolic tasks. Numerical simulations of this most realistic model on the universal network from the KEGG database again produced approximately quadratic scaling. Our results demonstrate why, in spite of their "small-world" topology, real-life metabolic networks are characterized by a broad distribution of pathway lengths and sizes of metabolic regulons in regulatory networks.Comment: 34 pages, 9 figures, 2 table