EVALUATION OF INTELLIGENT COMPACTION CONTROL IN THE M-189 RECONSTRUCTION PROJECT AT IRON RIVER, MICHIGAN

This research evaluated an Intelligent Compaction (IC) unit on the M-189 highway reconstruction project at Iron River, Michigan. The results from the IC unit were compared to several traditional compaction measurement devices including Nuclear Density Gauge (NDG), Geogauge, Light Weight Deflectometer (LWD), Dynamic Cone Penetrometer (DCP), and Modified Clegg Hammer (MCH). The research collected point measurements data on a test section in which 30 test locations on the final Class II sand base layer and the 22A gravel layer. These point measurements were compared with the IC measurements (ICMVs) on a point-to-point basis through a linear regression analysis. Poor correlations were obtained among different measurements points using simple regression analysis. When comparing the ICMV to the compaction measurements points. Factors attributing to the weak correlation include soil heterogeneity, variation in IC roller operation parameters, in-place moisture content, the narrow range of the compaction devices measurement ranges and support conditions of the support layers. After incorporating some of the affecting factors into a multiple regression analysis, the strength of correlation significantly improved, especially on the stiffer gravel layer. Measurements were also studied from an overall distribution perspective in terms of average, measurement range, standard deviation, and coefficient of variance. Based on data analysis, on-site project observation and literature review, conclusions were made on how IC performed in regards to compaction control on the M-189 reconstruction project.

Evaluation of factors affecting speed perception in a driving simulator

The present study was conducted to determine the effects of different variables on the perception of vehicle speeds in a driving simulator. The motivations of the study include validation of the Michigan Technological University Human Factors and Systems Lab driving simulator, obtaining a better understanding of what influences speed perception in a virtual environment, and how to improve speed perception in future simulations involving driver performance measures. Using a fixed base driving simulator, two experiments were conducted, the first to evaluate the effects of subject gender, roadway orientation, field of view, barriers along the roadway, opposing traffic speed, and subject speed judgment strategies on speed estimation, and the second to evaluate all of these variables as well as feedback training through use of the speedometer during a practice run. A mixed procedure model (mixed model ANOVA) in SAS® 9.2 was used to determine the significance of these variables in relation to subject speed estimates, as there were both between and within subject variables analyzed. It was found that subject gender, roadway orientation, feedback training, and the type of judgment strategy all significantly affect speed perception. By using curved roadways, feedback training, and speed judgment strategies including road lines, speed limit experience, and feedback training, speed perception in a driving simulator was found to be significantly improved.

FACTORS AFFECTING DIPOREIA GROWTH RATES IN LAKE SUPERIOR

An ability to predict population dynamics of the amphipod Diporeia is important in understanding how energy pathways in the Lake Superior food web might be altered by disturbances to the ecosystem. Estimating growth rates for this prominent prey item for fish requires information on the physiological effects of changes to its environment. These effects have been investigated for Diporeia in other Great Lakes, but little is known about Lake Superior populations. The primary objective of this study is to obtain quantitative data for rates of Diporeia respiration and consumption that can be incorporated into a bioenergetics model for Lake Superior. Benthic communities in Lake Superior were sampled bimonthly from April through September during 2011 and 2012 to investigate spatial and temporal trends of Diporeia abundances as well as size class structures of the population. Additional samples of Diporeia were collected and kept alive in natural sediment for laboratory experiments. Respiration rates for Diporeia were measured by monitoring dissolved oxygen concentrations in microcosoms using microelectrodes. Additionally, a series of experiments to estimate consumption rates based on food availability were conducted using 14C-labeled algae (Selenastrum capricornutum). Amphipod population densities are highest between 30-110 m (slope) compared to 0-30 m (shelf) or >110 m (profundal) regions in Lake Superior. This heterogeneous distribution of Diporeia in Lake Superior is an important component to quantifying lake-wide biomass. Rates of oxygen consumption by Diporeia range from 32.0 to 44.7 mgO2*gDW-1*d-1, and do not vary significantly with body size per individual. The predicted consumption rate corresponding to average Lake Superior algal carbon fluxes was 0.08 ± SE mgC*gDW-1*d-1. Data on Lake Superior Diporeia biomass and bioenergetics found in this study can be incorporated in a model used to estimate the viability of this population under potential future environmental stressors.

REVIEW OF FACTORS AFFECTING SUSTAINABILITY IN THE UNIVERSITIES

Purpose – The focus of this research is to find out a meaningful relationship between adopting sustainability practices and some of the characteristics of institutions of higher education (IHE). IHE can be considered as the best place to promote sustainability and develop the culture of sustainability in society. Thus, this research is conducted to help developing sustainability in IHE which have significant direct and indirect impact on society and the environment. Design/methodology/approach – First, the sustainability letter grades were derived from “Greenreportcard.org” which have been produced based on an evaluation of each school in nine main categories including: Administration, Climate Change & Energy, Food & Recycling, etc. In the next step, the characteristics of IHE as explanatory variables were chosen from “The Integrated Postsecondary Education Data System” (IPEDS) and respective database was implemented in STATA Software. Finally, the “ordered-Probit Model” is used through STATA to analyze the impact of some IHE’s factor on adopting sustainability practices on campus. Finding - The results of this analysis indicate that variables related to “Financial support” category are the most influential factors in determining the sustainability status of the university. “The university features” with two significant variables for “Selectivity” and “Top 50 LA” can be classified as the second influential category in this table, although the “Student influence” is also eligible to be ranked as the second important factor. Finally, the “Location feature” of university was determined with the least influential impact on the sustainability of campuses. Originality/value – Understanding the factors which influence adopting sustainability practices in IHE is an important issue to develop more effective sustainability’s methods and policies.