EHRA worked with the District to create a comprehensive Parks Master Plan, which included recommendations for the development of over two miles of hike/bike trails adjacent to local streets, and within flood control and utility pipeline easements. The District began implementation of the Plan by prioritizing the beautification of West Road, a major arterial street that runs through the District.
EHRA offered its Landscape Architectural services to complete a Parks and Trails Master Plan for the District.
EHRA assisted with the district creation of Montgomery County Municipal Utility District No. 126 to accommodate a ±329 acre master planned community located in northern Montgomery County in the City of Conroe, south of League Line Road, west of Longmire Road, and adjacent to Lake Conroe.
EHRA worked with the District to create a comprehensive Parks Master Plan, which included recommendations for the development of over two miles of hike/bike trails adjacent to local streets, and within flood control and utility pipeline easements. The District began implementation of the Plan by prioritizing the beautification of West Road, a major arterial street that runs through the District.
EHRA completed preliminary engineering, phase one environmental site assessment and schematic development for the widening of Northpark Dr. between US 59 and Woodland Hills Dr. EHRA also provided program management, drainage analysis and design, traffic engineering, environmental documentation and schematic design for the roadway, as well as grade separation at the Loop 494/UPRR railroad crossing.
EHRA conducted traffic operations and access management studies for the Northpark Dr. corridor. This corridor is approximately 2.2 miles long and has major signalized and unsignalized intersections and driveways that access various subdivisions and industrial developments. These studies laid the groundwork for the widening of Northpark Dr. from a four-lane boulevard cross-section to a six-lane boulevard complete street. The new street design includes low impact development drainage, conventional drainage, a grade separation at the UPRR crossing with mechanically stabilized earth retaining walls, two at-grade crossings for bi-directional frontage access, reconstruction of two concrete bridges over a diversion channel, intersection improvements, a roadway-adjacent multiuse path and traffic signal improvements.
Drainage analysis and design included hydrologic and hydraulic studies of both existing and proposed conditions to demonstrate that proposed project components would not adversely affect the 100-year floodplain in the area. The roadway and traffic designs contained horizontal and vertical alignments, cross-sections, plan and profile, sidewalk and bicycle accommodations, intersection layouts, traffic control plans and signing and pavement markings.
As the program management firm, EHRA coordinated with TxDOT, UPRR, the City of Houston Council District E, COH Planning and Development Department, COH Public Works and Engineering Department, Montgomery County, Harris County, HCFCD and area residents throughout the project.
A new computer program works smarter, not harder, to solve problems faster than its predecessors. The algorithm is designed to find the best solution to a given problem among all possible options. Whereas other computer programs winnow down the possibilities one at a time, the new program — presented July 12 at the International Conference on Machine Learning in Stockholm — rules out many choices at once.
For instance, imagine a computer is assigned to compile movie recommendations based on a particular film. The ideal recommendation list would include suggestions that are both similar to the original flick — say, in the same genre — yet different enough from each other to give the viewer a variety of choice. A traditional recommendation system would pore over an entire movie library to find films that best met those criteria and add films to its roster of recommendations one by one, a relatively slow and tedious process.
By contrast, the new program starts by randomly picking a bunch of movies from the library. Among that sample, the system keeps the movies that strike the best balance between relevance to the original film and diversity, and discards the rest. From that smaller pool, the algorithm again chooses films at random and keeps only the best of the bunch. That strategy helps the algorithm build its rec list far faster.
The new algorithm, built by Harvard University computer scientists Yaron Singer and Eric Balkanski, compiled movie suggestions more than 10 times as fast as a standard recommender system. In another trial, it devised optimal routes for cabs in New York City about six times as fast as a conventional automated dispatcher.
This program could also speed up data processing for everything from drug discovery to social media analytics, engineering and analyses of genetic data.
Source: Science News