Estimating the Benefits of Water Quality Improvements in the Upper Narragansett Bay

An EPA-sponsored study of the benefits to Rhode Island residents of the water quality improvement in the Upper Narragansett Bay showed that the estimated annual costs ($2.9 million) exceeded the expected annual benefits ($2.0 million). That analysis evaluated only user benefits which were measured via expenditures; nonuser (intrinsic) benefits were not included. This study estimated the benefits to Rhode Island residents using the "Contingent Valuation" approach and responses from 435 residents to a 1985 survey about swimming and shellfishing. Aggregate annual benefits were estimated to be in the range of $30-60 million for "swimmable" and$30-70 million for "shellfishable" water quality, depending on the type of measure (mean or median) and survey format. Secondary objectives of the study were to test different versions of "willingness to pay" questions and compare mean and median values for measurement. Aside from payment vehicle bias, we found no evidence of serious bias.contingent valuation, pollution, water quality benefits, Environmental Economics and Policy, Resource /Energy Economics and Policy,

Enabling Explainable Fusion in Deep Learning with Fuzzy Integral Neural Networks

Information fusion is an essential part of numerous engineering systems and biological functions, e.g., human cognition. Fusion occurs at many levels, ranging from the low-level combination of signals to the high-level aggregation of heterogeneous decision-making processes. While the last decade has witnessed an explosion of research in deep learning, fusion in neural networks has not observed the same revolution. Specifically, most neural fusion approaches are ad hoc, are not understood, are distributed versus localized, and/or explainability is low (if present at all). Herein, we prove that the fuzzy Choquet integral (ChI), a powerful nonlinear aggregation function, can be represented as a multi-layer network, referred to hereafter as ChIMP. We also put forth an improved ChIMP (iChIMP) that leads to a stochastic gradient descent-based optimization in light of the exponential number of ChI inequality constraints. An additional benefit of ChIMP/iChIMP is that it enables eXplainable AI (XAI). Synthetic validation experiments are provided and iChIMP is applied to the fusion of a set of heterogeneous architecture deep models in remote sensing. We show an improvement in model accuracy and our previously established XAI indices shed light on the quality of our data, model, and its decisions.Comment: IEEE Transactions on Fuzzy System

What Drives the Choice of Third Party Logistics Provider?

It is generally believed that companies choose supply chain partners on the basis of their distinctive value propositions; a fact one would also expect holds true when companies choose a logistics service provider. However, faced with the complexities of varied customer demands, it can be difficult for logistics service companies to obtain an effective understanding of how customers differentially value the service components they offer. In this paper, we address this by identifying the factors that are important in a customer’s choice of a logistics service provider. Using stated choice methods we explore the relative importance of seven service attributes using a sample of 309 managers with a central role in purchasing logistics services across a range of industries and countries. The results reveal that three distinct decision models populate our data where the preferences for different logistics service attributes – such as price and delivery performance –vary greatly between customer groups represented by these models. Strategically, our findings provide the management of a third party logistics provider with a logical starting point from which to determine the goals that are set for their operations, particularly in choosing the customer segments to service

Extension of the fuzzy integral for general fuzzy set-valued information

The fuzzy integral (FI) is an extremely flexible aggregation operator. It is used in numerous applications, such as image processing, multicriteria decision making, skeletal age-at-death estimation, and multisource (e.g., feature, algorithm, sensor, and confidence) fusion. To date, a few works have appeared on the topic of generalizing Sugeno's original real-valued integrand and fuzzy measure (FM) for the case of higher order uncertain information (both integrand and measure). For the most part, these extensions are motivated by, and are consistent with, Zadeh's extension principle (EP). Namely, existing extensions focus on fuzzy number (FN), i.e., convex and normal fuzzy set- (FS) valued integrands. Herein, we put forth a new definition, called the generalized FI (gFI), and efficient algorithm for calculation for FS-valued integrands. In addition, we compare the gFI, numerically and theoretically, with our non-EP-based FI extension called the nondirect FI (NDFI). Examples are investigated in the areas of skeletal age-at-death estimation in forensic anthropology and multisource fusion. These applications help demonstrate the need and benefit of the proposed work. In particular, we show there is not one supreme technique. Instead, multiple extensions are of benefit in different contexts and applications

From interval-valued data to general type-2 fuzzy sets

In this paper, a new approach is presented to model interval-based data using fuzzy sets (FSs). Specifically, we show how both crisp and uncertain intervals (where there is uncertainty about the endpoints of intervals) collected from individual or multiple survey participants over single or repeated surveys can be modeled using type-1, interval type-2, or general type-2 FSs based on zSlices. The proposed approach is designed to minimize any loss of information when transferring the interval-based data into FS models, and to avoid, as much as possible, assumptions about the distribution of the data. Furthermore, our approach does not rely on data preprocessing or outlier removal, which can lead to the elimination of important information. Different types of uncertainty contained within the data, namely intra- and inter-source uncertainty, are identified and modeled using the different degrees of freedom of type-2 FSs, thus providing a clear representation and separation of these individual types of uncertainty present in the data. We provide full details of the proposed approach, as well as a series of detailed examples based on both real-world and synthetic data. We perform comparisons with analogue techniques to derive FSs from intervals, namely the interval approach and the enhanced interval approach, and highlight the practical applicability of the proposed approach

Indoor Inertial Waypoint Navigation for the Blind

Indoor navigation technology is needed to support seamless mobility for the visually impaired. This paper describes the construction and evaluation of an inertial dead reckoning navigation system that provides real-time auditory guidance along mapped routes. Inertial dead reckoning is a navigation technique coupling step counting together with heading estimation to compute changes in position at each step. The research described here outlines the development and evaluation of a novel navigation system that utilizes information from the mapped route to limit the problematic error accumulation inherent in traditional dead reckoning approaches. The prototype system consists of a wireless inertial sensor unit, placed at the users’ hip, which streams readings to a smartphone processing a navigation algorithm. Pilot human trials were conducted assessing system efficacy by studying route-following performance with blind and sighted subjects using the navigation system with real-time guidance, versus offline verbal directions

A designed screening study with prespecified combinations of factor settings

In many applications, the experimenter has limited options about what factor combinations can be chosen for a designed study. Consider a screening study for a production process involving five input factors whose levels have been previously established. The goal of the study is to understand the effect of each factor on the response, a variable that is expensive to measure and results in destruction of the part. From an inventory of available parts with known factor values, we wish to identify a best collection of factor combinations with which to estimate the factor effects. Though the observational nature of the study cannot establish a causal relationship involving the response and the factors, the study can increase understanding of the underlying process. The study can also help determine where investment should be made to control input factors during production that will maximally influence the response. Because the factor combinations are observational, the chosen model matrix will be nonorthogonal and will not allow independent estimation of factor effects. In this manuscript we borrow principles from design of experiments to suggest an 'optimal' selection of factor combinations. Specifically, we consider precision of model parameter estimates, the issue of replication, and abilities to detect lack of fit and to estimate two-factor interactions. Through an example, we present strategies for selecting a subset of factor combinations that simultaneously balance multiple objectives, conduct a limited sensitivity analysis, and provide practical guidance for implementing our techniques across a variety of quality engineering disciplines

Site of semen deposition and fertility in lactating beef cows synchronized with GnRH and PGF2α

Our objective was to determine the effect of site of semen deposition on pregnancy rate in beef cows inseminated at a fixed time or after observed estrus. Cows were synchronized with a combination of gonadotropin-releasing hormone (GnRH) prostaglandin-F α (PGF). GnRH was injected 7 days before PGF (day 0; first of breeding season). The trial was conducted at two locations, one in Kansas (147 cows) and one in Colorado (313 cows). At each location, cows were assigned to be inseminated after observed estrus (ESTRUS-AI) or at a fixed time (TIMED-AI). Within these two groups, cows either were inseminated in the uterine body (BODY-bred) or in both uterine horns (HORN-bred). Cows in the ESTRUS-AI group were observed for estrus each morning and evening until day 5 afterPGF and then inseminated 12 hr after first detected estrus. Cows in the TIMED-AI group received a second dose of GnRH on day 2 and were inseminated at that time (48 to 56 hr after PGF). Heat response, AI conception rate, and pregnancy rate were analyzed for BODY-bred and HORN-bred cows within each treatment at each location. No differences in these variables occurred between locations, so the results were combined. Within the ESTRUS-AI group, neither conception rate (70% vs. 73%) nor pregnancy rate (39% vs. 40%) was different between BODY-bred and HORN-bred cows respectively. Pregnancy rate within the TIMED-AI group tended (P=.09) to be greater for BODY-bred (53%) compared to HORN-bred (42%) cows. When BODY-bred and HORN-bred treatments were combined, the pregnancy rate of TIMED-AI cows (48%) tended (P=.07) to be greater than that of ESTRUS-AI cows (39%). Timed-insemination resulted in a greater pregnancy rate than inseminating cows according to estrus. No advantage was seen in conception rates when semen was deposited in the uterine horns compared to the uterine body

Northern Bobwhite Response to Control of Red Imported Fire Ants in the Gulf Coast Prairie of Texas

The population decline of northern bobwhite (Colinus virginianus; hereafter, bobwhite) on the Texas Gulf Coast Prairie, USA is largely attributed to habitat loss. However, red imported fire ants (Solenopsis invicta) occur throughout the region and are considered a possible contributing factor to the bobwhite decline. The objectives of our study were to determine the influence of red imported fire ants on bobwhites by comparing bobwhite nest success, survival, and density between sites treated with fire ant bait (treatment) and reference (control) sites. Our study was conducted on 3 private ranches in Goliad and Refugio counties, Texas. Each ranch contained 2 paired experimental units that consisted of a treatment and control site (500 ha each). The treatment sites received an aerial application of fire ant bait (Extinguish® Plus) during April 2018, whereas the control sites were not treated. We estimated mound density by counting fire ant mounds using distance sampling. We used radio-telemetry to monitor bobwhite nest success and survival, and we estimated bobwhite densities using distance sampling via helicopter surveys. Fire ant mound density decreased through time on both treatment and control sites. However, fire ant mound density was lower on treatment sites than control sites, indicating the insecticide was effective at decreasing fire ant mound density. Bobwhite survival, nest success, and density did not statistically differ between control and treated sites either pre-treatment (2017) or post-treatment (2018), but survival and nest success metrics were numerically higher in treated units. Bobwhite survival remained relatively stable in the treatment units 4 weeks after application but decreased in the control units. Following treatment, apparent nest success in the treated units increased by 37.4% while nest success in the control units decreased by 35.2%. Bobwhite populations were low in this ecoregion, which influenced our ability to trap and monitor many bobwhites or monitor many nests. In addition, it may be possible that repeated, annual treatments for fire ants are necessary for a benefit to accrue and be observed in bobwhites. Our results indicate that there may be potential benefits to bobwhites from fire ant reduction that deserve further research attention